Quantify Physiological and Structural Changes After a Convulsive Sub-Lethal Dose of Soman Using MRI and Oxygen Sensors in Rats

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2020-08-31 Quantify Physiological and Structural Changes After a Convulsive Sub-lethal Dose of Soman using MRI and Oxygen Sensors in Rats

Lee, Seung-Hun (Kevin)

Lee, S.-H. (2020). Quantify Physiological and Structural Changes After a Convulsive Sub-lethal Dose of Soman using MRI and Oxygen Sensors in Rats (Unpublished doctoral thesis). University of Calgary, Calgary, AB. http://hdl.handle.net/1880/112485 doctoral thesis

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Quantify Physiological and Structural Changes After a Convulsive Sub-lethal Dose of Soman

using MRI and Oxygen Sensors in Rats

Seung-Hun (Kevin) Lee

A THESIS

SUBMITTED TO THE FACULTY OF GRADUATE STUDIES

IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE

DEGREE OF DOCTOR OF PHILOSOPHY

GRADUATE PROGRAM IN NEUROSCIENCE

CALGARY, ALBERTA

AUGUST, 2020

Abstract

Chemical weapons including nerve agents pose an ongoing issue in global conflicts, terrorism, and assassination plots. The current treatment protocol against nerve agents include atropine sulfate, HI-6 oxime, and benzodiazepine, which have been successful in prolonging survival after nerve agent exposure. However, the treatments are unable to prevent neurological damage associated with nerve agent-induced seizures. The objective of this thesis is to use imaging modalities to improve our understanding of the physiological and structural changes in the brain following a sub-lethal dose of nerve agent (soman) exposure. First, we investigated changes in oxygenation using chronically implanted oxygen sensors in awake and freely moving rats. We were able to measure oxygenation before, during, and after soman exposure. We found distinct oxygen profiles that oscillated based on seizure onset, which may be due to abnormal hemodynamics. Additionally, hyperoxygenation was detected during status epilepticus and remained elevated at 24 hours. Next, in order to validate the results, we measured cerebral blood flow using continuous arterial spin labelling (CASL) MRI. We found global hypoperfusion at 1 hour and hypoperfusion in the piriform network at 18-24 hours in isoflurane anaesthetized rats.

Following this, we combined a way to simultaneously measure cerebral blood flow using CASL

MRI and oxygenation using oxygen sensors in isoflurane anaesthetized rats. Here, we found hypoperfusion but normoxia in the cortex, suggesting a decrease in metabolism. Further investigation of whether changes are due to neurological damage was explored by correlating quantitative T2 (qT2) MRI to a histological marker of neurodegeneration. No changes in qT2 or neurodegeneration was found at 1 hour after soman, suggesting hypoperfusion and hypometabolism may be mediated through oxidative stress. At 18-24 hours after soman exposure, changes in qT2 MRI correlated with neurodegenerative markers, with the strongest

correlation being in the piriform cortex. This suggests hypoperfusion in the piriform network at

18-24 hours, which may be the result of damage to the neurovascular unit. Overall, this thesis identifies impairment of vasodynamics following soman exposure as a potential therapeutic target and the use of qT2 MRI to guide efficacy of these therapies.

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Preface

Chapter 1 provides a general introduction on nerve agents and Canada’s interests towards the research.

Chapter 2 is a literature review.

Chapter 3 is an empirical data chapter outlining the changes in brain oxygenation and is published in Neurotoxicology:

Lee, K., Bohnert, S., Wu, Y., Vair, C., Mikler, J., Teskey, G. C., & Dunn, J. F. (2018).

Assessment of brain oxygenation imbalance following soman exposure in rats. Neurotoxicology,

65, 28-37. doi:10.1016/j.neuro.2018.01.007

Chapter 4 is an empirical data chapter outlining the changes in cerebral hemodynamics and is published as a special issue manuscript in Toxicological Letters: Submitted

Chapter 5 is an empirical data chapter outlining the sensitivity of quantitative T2 MRI in detect neurodegeneration following soman and is published in Scientific Reports: Accepted

Chapter 6 is a general discussion which describes the progression of the thesis and future directions.

Acknowledgements

First and foremost, I would like to show my deepest appreciation and gratitude to Dr.

Jeff F. Dunn. Jeff accepted me into his lab despite my brief research experience in petroleum microbiology. Thank you for putting me on the most exciting project I could have ever asked for.

Although the journey was bumpy at times, his guidance and leadership has helped me along the way. I will always cherish and appreciate his love for science. I thank Jeff for having so much faith in me and creating an environment where I could grow.

I would like to thank my collaborator Sara Bohnert for providing the funding and being an excellent collaborator. It has been a pleasure to work together on this project. I am grateful for your patience and understanding. I have learned a tremendous amount about nerve agents. Thank you for always being there to discuss science.

I would also like to thank my committee members Dr. Cam Teskey and Dr. Bruce Pike for your guidance and insights. Thank you, Cam, for opening up your lab to me where I was able to collaborate with members in your lab. Their support and guidance were of great help.

Thank you to my internal examiner, Dr. Pierre Levan and external examiner, Dr. Alon

Friedman, for taking their time to be examiners for my thesis defense.

A special thanks to the Dunn lab. Thank you for all the help and scientific discussions over the years. The time that was spent together have been interesting and fun. I could not have asked for a better lab family.

Thank you to members of the Defence Research and Development Canada-Suffield

Research Centre, Dr. John Mikler and Cory Vair. Thank you for making the long journey to bring up the soman.

Thank you to Dave Rushforth and Tad Foniok in the Experimental Imaging Centre. I will always appreciate the openness of Dave and Tad for sharing their expertise. It was a pleasure hanging out by the 9.4T MRI.

I would like to give a special thanks to my bestie and office mate, Dr. Lia Maria Hocke.

You were the best office mate anyone could have. I will always cherish our time watching

Doctor Who and eating fish sticks and custard. Congratulations again, I can’t wait to meet little

Branick.

I also want to thank Nikola Yee. Thank you for believing in me when I didn’t. I could not have done this without your constant support. I can only hope to repay a fraction of the support you have given me.

Last, but not least, I would like to thank my family. Thank you to my mother, Dr.

Woonyoung Baik, who gave up everything in South Korea to come to Canada, raising me as a single-mother, and giving me this opportunity. Thank you to my father, Choongsun Lee, who cheered me on from South Korea. Finally, thank you to my sister, Suyeon Lee, for bothering me with your love.

Dedication

I dedicate this thesis to my incredible family- Dr. Woonyoung Baik, Choongsun Lee, and Suyeon Lee. They have taught me the virtue of perseverance. A small token of appreciation for their guidance, support, and unconditional love.

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Table of Contents Abstract ...... ii Preface ...... iv Acknowledgements ...... v List of Tables ...... xi List of Figures and Illustrations ...... xii List of Symbols, Abbreviations and Nomenclature ...... xiv Chapter 1: General Introduction ...... 1 1.1 Nerve Agents and Canada: General Overview ...... 1 1.2 Objective and Aims ...... 2 Chapter 2: Literature Review ...... 4 2.1 Pesticide use and OP compounds ...... 4 2.2 Nerve Agents ...... 8 2.2.1 History ...... 8 2.2.2 Types of Nerve Agents ...... 11 2.2.3 Epidemiology ...... 11 2.2.4 Mechanism of action ...... 13 2.2.5 Signs and Symptoms of Exposure ...... 15 2.2.6 The Choice of Soman for this Project ...... 17 2.2.7 Animal Models to Study Nerve Agent exposure ...... 17 2.2.8 Mechanism of Nerve Agent-induced Seizures ...... 20 2.3 Cerebral Blood Flow and Metabolism ...... 22 2.3.1 Regulation of cerebral blood flow ...... 22 2.3.2 Hypoxia/Ischemia ...... 26 2.4 Neuropathophysiology associated with Nerve Agents ...... 28 2.4.1 Excitotoxicity ...... 29 2.4.2 Blood-Brain Barrier Disruption ...... 30 2.4.3 Neuroinflammation ...... 32 2.4.4 Oxidative Stress ...... 33 2.4.5 Here We Go Again ...... 35 2.5 MRI as a method to study pathology ...... 35 2.5.1 Basic principles of MRI ...... 36 2.5.2 T1 relaxation, and T2 decay ...... 39 2.6 MRI Methods ...... 40 2.6.1 Arterial Spin Labelling MRI ...... 40 2.6.2 Quantitative T2 ...... 41 2.7 Nerve Agents and MRI ...... 43 2.7.1 MRI studies in Animal models ...... 45 2.7.2 Human MRI studies ...... 48 2.8 Summary ...... 49 Chapter 3: Assessment of brain oxygenation following soman exposure in rats ...... 51

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Abstract ...... 51 3.1 Introduction ...... 52 3.2 Materials and methods ...... 53 3.2.1 Animals ...... 53 3.2.2 pO2 Probe Implantation ...... 54 3.2.3 Drugs ...... 55 3.2.4 Magnetic Resonance Imaging ...... 55 3.2.5 Experimental design ...... 56 3.2.6 Histology ...... 62 3.2.7 Data Analysis ...... 62 3.3 Results ...... 63 3.3.1 Behavioral Effects of Soman ...... 63 3.3.2 Imaging Probe Location ...... 63 3.3.3 Cortex pO2 Measurements ...... 66 3.3.4 Hippocampal pO2 Measurements ...... 71 3.3.5 Comparison between Cortex and Hippocampus ...... 75 3.4 Discussion ...... 75 3.4.1 Baseline pO2 measurements ...... 75 3.4.2 From soman exposure to seizure onset ...... 76 3.4.3 Onset of Seizures May Reduce Oxygenation ...... 77 3.4.4 Oscillating Changes in Oxygenation in the first hour ...... 79 3.4.5 Potential link between oxygenation and pathology ...... 79 3.4.6 Future Directions ...... 80 3.5 Conclusion ...... 81 Chapter 4 Cerebral blood flow and oxygenation in rat brain after soman exposure ...... 82 Abstract ...... 82 4.1 Introduction ...... 84 4.2 Methods ...... 85 4.2.1 Animals ...... 85 4.2.2 Implantation of oxygen sensor and measurement ...... 85 4.2.3 Soman and Treatments ...... 86 4.2.5 Magnetic Resonance Imaging ...... 87 4.2.6 Experimental Design ...... 90 4.2.7 Data Analysis and Statistics ...... 93 4.3 Results ...... 93 4.3.1 Cerebral Blood Flow After Soman ...... 93 4.3.2 pO2 and CBF After Soman ...... 96 4.4 Discussion ...... 106

Chapter 5 Quantitative T2 MRI is predictive of neurodegeneration following organophosphate exposure in a rat model ...... 112 Abstract ...... 113 5.1 Introduction ...... 114 5.2 Methods ...... 116

5.2.1 Experimental Design ...... 116 5.2.2 Animals ...... 117 5.2.3 Soman and Treatments ...... 118 5.2.4 Symptom and Seizure Evaluation ...... 118 5.2.5 MRI Parameters and Analysis ...... 118 5.2.6 Tissue Preparation and histology ...... 123 5.2.7 Quantification of NeuN and FJC ...... 124 5.2.8 Statistics ...... 125 5.3 Results ...... 125 5.4 Discussion ...... 137 Chapter 6 General Discussion...... 144 6.1 Thesis progression ...... 144 6.2 Significance ...... 148 6.3 Outstanding Questions and Future Directions ...... 149 6.5 Conclusion ...... 152 References ...... 153 Appendix: Copyright Material ...... 175

List of Tables

Table 2.1: Summary of pathologies in OP exposure…………………………………………….44

Table 3.1: Rating system to assess the severity of soman related symptoms. Suffield Rating Scale………..…………………………………………………………………………………….61

Table 3.2: Baseline and peak pO2 in the cortex and hippocampus after soman injection. ……...69

Table 4.1: Percent change in cerebral blood flow in the motor cortex before and 1.5-hour after soman exposure or saline. …………………………………………………………………….....99

Table 5.1: Mean T2 times of different anatomical brain structures in rats before and after exposure to a convulsive dose of soman. ………………………………………………………128

List of Figures and Illustrations

Figure 2.1 General chemical structure of nerve agents. ………………………………………..…6

Figure 2.2 Chemical structure of nerve agents. ………………………………………………..…7

Figure 2.3 Orientation of spins before and after an external magnetic field (B0) is applied…….38

Figure 3.1: Implantation of pO2 probes in the rat cortex and hippocampus……………………. 59

Figure 3.2: Time course of the study depicting the treatment timing and measurement duration…………………………………………….………………………………………….…60

Figure 3.3: Images showing the locations of the pO2 probe tips in the brain……………………65

Figure 3.4: The effect of soman injection on cortical pO2………………………………….……68

Figure 3.5: Combined cortical pO2 data……….…………………………………………….…..70

Figure 3.6: The effect of soman injection on hippocampal pO2. ………………………………..73

Figure 3.7: Combined hippocampal pO2 data…….…………………………………………...…74

Figure 4.1: Method utilized to obtain perfusion map (Lei et al., 2001). ………………………...89

Figure 4.2: Experimental timeline of the study. ………………………………………………...92

Figure 4.3: Hypoperfusion was found 1 hour and 18-24 hours after soman exposure…………..95

Figure 4.4: Representative anatomical scan for fiber-optic oxygen sensing probe localization and perfusion map 1.5-hours after soman exposure………………………………………………….98

Figure 4.5: Quantification of change in cerebral blood flow 1.5-hours after soman exposure or saline. …………………………………………………………………………………………..101

Figure 4.6: Representative oxygenation plot and quantification of change in oxygenation following soman exposure or saline. …………………………………………………………..103

Figure 4.7: Relationship between ptO2 and cerebral blood flow before and 1.5 hours after soman exposure or saline. ……………………………………………………………………………..105

Figure 5.1: Representative coronal images of the fourth echo (40 ms) at baseline and 18-24 hours after soman injection. …………………………………………………………………………..120

Figure 5.2: Representative T2 fitting and distribution before and 18-24 hours after a convulsive dose of soman in the piriform cortex. ………………………………………………………….122

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Figure 5.3: The effects of soman exposure on T2 relaxation time before exposure, 1 hour after soman (n = 9), or 18-24 hours after soman (n = 10). …………………………………………..129

Figure 5.3, supplement 1: The effects of soman exposure on T2 relaxation time in the cerebral cortex, medial amygdala, medial thalamus, and retrosplenial cortex. …………………………130

Figure 5.4: Effect of soman-induced seizures on neuronal cells following 18-24 hours after soman exposure in the cerebral cortex, medial amygdala, and piriform cortex………………..132

Figure 5.4, supplement 1: The effects of soman-induced seizures on neuronal cells following 18- 24 hours after soman exposure in the basolateral amygdala, dorsolateral thalamus, medial thalamus, and retrosplenial cortex. ………………………………………………………….…133

Figure 5.5: Effect of soman-induced seizures on the rate of relaxation (R2) correlated to the percentage of neurodegeneration in the cerebral cortex, medial amygdala, and piriform cortex……….…………………………………………………………………………………..135

Figure 5.5, supplement 1: The rate of relaxation (R2) was compared to the percentage of neurodegeneration in the basolateral amygdala, dorsolateral thalamus, medial thalamus, and retrosplenial cortex. ……………………………………………………………………………136

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List of Symbols, Abbreviations and Nomenclature

Abbreviation Definition

AA Arachidonic acid

ACh Acetylcholine

AChE Acetylcholinesterase

ADC Apparent diffusion coefficient

AMN Atropine methyl nitrate

AMPA α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid

ANOVA Analysis of variance

AS Atropine sulfate

ASL Arterial spin labelling

ATP Adenosine triphosphate

BBB Blood-brain barrier

CASL Continuous arterial spin labelling

CBF Cerebral blood flow

CCAC Canadian Council of Animal Care

CFSG Cold fish skin gelatin

CMRO2 Cerebral metabolic rate of oxygen

COX-2 Cyclooxygenase-2

CSF Cerebrospinal fluid

DFP Diisopropyl fluorophosphate

DNA Deoxyribonucleic acid

DPX Dibutylphthalate polystyrene xylene

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DRDC-SRC Defence research and development Canada- Suffield research centre

EEG Electroencephalography

FID Free induction decay

FJC Fluoro-Jade C

FOV Field of view

GABA Gamma-aminobutyric acid

GFAP Glial fibrillary acidic protein cGMP Cyclic guanosine monophosphate

HASTE Half-fourier acquisition single-shot turbo spin echo

H&E Hematoxylin and eosin

HI-6 DMS HI-6 dimethanesulfonate

IBA-1 Ionized calcium binding adaptor molecule-1

IL Interleukin

LD50 Median lethal dose

LED Light emitting diode

MRI Magnetic Resonance Imaging

NA Nerve agent

NATO North Atlantic Treaty Organization

NMDA N-methyl-D-aspartate

NNLS Non-negative least square

NO Nitric oxide

OCT Optimal cutting temperature

OP Organophosphorus

OPCW Organisation for the Prohibition of Chemical Weapons

PBS Phosphate-buffered saline

PFA Paraformaldehyde

PO2 Oxygenation

RARE Rapid acquisition with relaxation enhancement

RF Radio frequency

RNA Ribonucleic Acid

ROS Reactive oxygen species

RSDL Reactive skin decontamination lotion

SD Standard deviation

TE Echo time

TNF Tumor necrosis factor

TR Repetition time

WMD Weapons of Mass Destruction

WW World War

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Chapter 1: General Introduction

1.1 Nerve Agents and Canada: General Overview

Nerve agents (NAs) are a special type of organophosphorus (OP) compounds that have been utilized in chemical warfare, assassination schemes, and acts of terrorism. The potency and lethality of some OPs makes them better suited as Weapons of Mass Destruction. NAs are classified as Weapons of Mass Destruction because of their potential to cause a significant number of casualties. OPs also have non-lethal applications - where they are included in commonplace products such as flame retardants and pesticides. Despite all OP compounds sharing similar chemical structure, they are used in drastically different scenarios. In response to the growing global threat during the Cold War, the treaty: “The Convention on the Prohibition of the Development, Production, Stockpiling and Use of Chemical Weapons and on their

Destruction”, was started in 1993. Oversight on the elimination of chemical weapons is performed by the Organisation for the Prohibition of Chemical Weapons (OPCW). Despite international efforts in the destruction of chemical weapons, the threat remains for both civilians and military personnel. Exposure to these compounds, as a result, occur in both chemical warfare as well as innocuous agricultural scenarios. Both, however, can lead to severe neurological symptoms and death. Early research efforts have focused on (1) understanding the biomechanisms behind NA induced pathologies and (2) developing treatment protocols for victims of NA exposure. During the development of novel treatment protocols, which have focused on improving human survivability post NA exposure, new challenges have come to light. One such problem is that current treatment protocols do not prevent brain damage in subjects that have been exposed to a sub-lethal NA dosage. In order to better understand how

NAs can cause neurological damage, and how it can be prevented, the Defence Research and

Development Canada - Suffield Research Centre (DRDC-SRC) expanded their research efforts.

Canada was one of the first countries to sign the Chemical Weapons Convention on

January 13, 1993 (UN, 2020). They have supported other nations in meeting their goal of chemical disarmament. Since 2002, we have provided over $200 million of financial support to

Russia, who has the biggest stockpile of chemical weapons in the world (Austen, 2017). We have ongoing collaborations with countries in The North Atlantic Treaty Organization (NATO) to share information and research efforts to eliminate threats of chemical warfare. Additionally, the

Joint Incidence Response Unit who are part of the Canadian Special Operations Forces

Command plays a major role in responding to potential chemical, biological, radiological, and nuclear threat. Despite global efforts in eliminating chemical weapons, terrorist organizations and rogue states still pose a threat. Therefore, to gain new insights in how NAs cause neurological damage, the DRDC-SRC requested to collaborate with us due to our expertise in imaging. This thesis probes the pathological and pathophysiology of NAs with the goal of increasing our understanding of how they injure the brain and the regional sensitivity to injury.

1.2 Objective and Aims

This thesis identifies potential impairment in oxygen delivery and utilization following soman-induced seizures using imaging modalities including MRI and fiber-optic oxygen sensors.

Furthermore, this thesis correlates changes in quantitative T2 MRI to the severity of neurological damage. Overall, the objective was to improve physiological understanding, identify therapeutic targets, and identify a method to evaluate damage.

Aim 1. Measure changes in cortical and hippocampal oxygenation after soman-induced

seizures using chronically implanted oxygen sensors in awake and freely moving rats.

Aim 2. Investigate the changes in oxygen delivery after soman-induced seizures.

Aim 3. Use quantitative T2 MRI and histology to study edema and neurodegeneration

after soman-induced seizures.

Before we dive into the specifics of how the thesis aims were fulfilled, it is imperative that we first cover some background information on NAs, cerebral blood flow regulation and MRI.

Chapter 2: Literature Review

2.1 Pesticide use and OP compounds

Globally, there are up to two million cases of acute pesticide poisoning annually (Mew et al., 2017). Organophosphorus (OPs) compounds are one of the most widely used pesticides and account for 33% of the pesticides used within the United States in 2012 (Atwood & Paisley-

Jones, 2017). Although new regulations have led to a decrease in OP usage in the United States from 2000 (Atwood & Paisley-Jones, 2017), pesticide self-poisoning remains a global health problem in low to middle income countries (Mew et al., 2017). The ingestion of OPs may account for over 100,000 deaths per year (Mew et al., 2017).

OP compounds (Figure 2.1) have a central phosphorus atom with a double bonded oxygen atom (or sulfur atom), the R1 and R2 are an alkyl group, the second alkyl group (R2) is connected to an oxygen group forming an O-alkyl group, and X illustrates the leaving group

(Figure 2.1) (Cannard, 2006; Costa, 2018). The leaving group can have numerous variations including fluorine. The leaving group and O-alkyl group governs the reactivity of an OP and are most vulnerable to metabolic hydrolysis (Goldsmith et al., 2012; Worek, Thiermann, Szinicz, &

Eyer, 2004).

The chemical structure of some NAs are depicted in Figure 2.2. OP pesticides often have a sulfur atom double bonded to the central phosphorus; in this configuration OP pesticides require in vivo bioactivation to bind to their target site. The cytochrome P450 system activates

OP pesticides by removing the sulfur atom through dethiolation and replacing it with an oxygen group (Jan et al., 2016). The bioactivation process delays the toxic effects of OP pesticides compared to NAs, which does not require bioactivation to exhibit toxic effects (Jan et al., 2016).

Therefore, exposure to NAs requires immediate medical response.

The substituents of NAs provide them with unique physical properties including vapor pressure (A. Watson et al., 2006), which determine the volatility of NAs and potential route of exposure. Depending on the volatility of each compound, the exposure route can vary. In the case of tabun, sarin, and soman their high volatility makes them an inhalation hazard (A. Watson et al., 2006). VX on the other hand was designed to have lower volatility to remain in the environment for longer periods of time (A. Watson et al., 2006). The primary route for VX is dermal exposure but some risk of inhalation exposure remains. In real life scenarios of NA exposure, victims are likely to be exposed through more than one route.

NAs are synthetic compounds that were carefully chosen based on their physical and chemical properties for a singular purpose, to have a tactical advantage in war. The creation of these compounds did not start off with such malicious intents but rather a set of circumstances deeply ingrained in human history, World War II.

Figure 2.1 General chemical structure of nerve agents.

Figure 2.2 Chemical structure of nerve agents.

2.2 Nerve Agents

2.2.1 History

NAs were discovered on December 23, 1936 in Germany by Dr. Gerhard Schrader, who is known as the “Father of Nerve Agents” (Costa, 2018; Holstege, Kirk, & Sidell, 1997;

Schmaltz, 2006). Dr. Gerhard Schrader and his research team came upon their discovery while working for Interessengemeinschaft Farbenindustrie AG (I.G. Farben) (Schmaltz, 2006). The original objective of the team was to create a more effective insecticide to fight against world hunger, however, they synthesized tabun, the first NA (Holstege et al., 1997; Schmaltz, 2006).

The effectiveness of tabun was not realized until a small amount of the newly synthesized NA was spilt in the laboratory (Holstege et al., 1997; Schmaltz, 2006). At the time, Dr. Schrader and his team started to experience NA related symptoms including miosis, nausea, and respiratory distress (Holstege et al., 1997; Schmaltz, 2006). Further examination by I.G. Farben determined that tabun was too toxic for agricultural usage, however, the new NA was to be quickly adopted in the military setting (Holstege et al., 1997; Schmaltz, 2006).

NAs were weaponized due to a decree passed by the Nazi government in 1935 (Nepovimova

& Kuca, 2020). Under the decree, any German invention that may have had military significance required disclosure to the Ministry of War (Nepovimova & Kuca, 2020). Therefore, shortly after the discovery of tabun, Schrader submitted a sample to the chemical warfare section of the Army

Ordnance Office (Holstege et al., 1997; Schmaltz, 2006). The potential of tabun was quickly realized after a demonstration and Dr. Schrader’s patent and research became classified information (Schmaltz, 2006). Dr. Schrader was provided with a new laboratory to continue his research in tabun and other OPs in secrecy.

In 1938, Dr. Schrader and his team synthetized a new compound that was more potent than tabun, it came to be known as sarin (Holstege et al., 1997; Soltaninejad & Shadnia, 2014).

Sarin was named after its inventors: Schrader, Ambros, Gerhard Rudringer, and Vander Linde

(Holstege et al., 1997). The next NA was not synthesized until 1944 by Dr. Richard Kuhn, who later won the Nobel prize in chemistry for his work with vitamins (Schmaltz, 2006). While working on his antivitamin research Dr. Kuhn attempted to mimic a substance closely related to acetylcholine, his work eventually led to the discovery of soman (Schmaltz, 2006). Subsequent examination of soman revealed it to be more lethal than tabun or sarin (Schmaltz, 2006). The

NAs that were synthetized in Germany was given the code name G (German)-agents.

NAs were never used on allied forces during World War II for unknown reasons and explanations as to why this may be the case are actively debated. (Holstege et al., 1997). Some have speculated that the Nazis feared retaliation from the Allied Forces whilst others have argued that Hitler's firsthand experience with mustard gas during WWI deterred him from using it on others (Pitschmann, 2014). No matter the reason, one fact remained clear. Germany had superior chemical warfare capability compared to the Allied Forces (Schmaltz, 2006). When the war came to an end, NAs were further researched, mass produced, and stockpiled by the Allied

Forces; ultimately making them an integral part of their arsenal.

In the post-war period following WWII, the Allied Forces continued NA related research as they were concerned that NAs may be a potential threat in the future. In order to prepare for such a threat, researcher focused on understanding the mechanism, treatments, and developing personal protective equipment.

Similar to the intention of Dr. Gerhard Schrader, who was interested in developing a more effective pesticide, British scientist Dr. Ranajit Ghosh unintentionally developed the next

generation of NAs (Holstege et al., 1997). This discovery did not go unnoticed by the British

Chemical Warfare Establishment in Porton Down who further funded the research (Szinicz,

2005). In 1952, Dr. Ghosh synthesized the first V-agent. Compared to its German counterpart, the newly synthesized VX were much more lethal- with approximately 10 times more potency than sarin. The technology to produce VX was traded to the United States in exchange for thermonuclear weapons technology (N. H. Johnson, Larsen, & Meek, 2015), which shows the strategic value of NAs in warfare. Other variation of V-agents includes VE, VM, VR, CVX, and

VG.

The third generation of NAs, A-agents, were developed by the Soviet Union (USSR) between 1973 and 1976 under the name project FOLIANT. The objective of the project was to develop NAs that were more toxic then G and V- agents whilst being undetectable by NATO

(Nepovimova & Kuca, 2020). Although information remains scarce, it has been confirmed that at least three chemicals were synthetized including A230, A232, and A234 (Nepovimova & Kuca,

2020). A-agents are believed to possess the volatility of G-agents whilst expressing the persistence and toxicity of V-agents. The exact chemical structure of these agents remains unpublished. The problem with the A-agents was their instability (Nepovimova & Kuca, 2020), therefore, the project NOVICHOK (newcomer) was born. The instability of the A-agents was circumvented by turning the A-agents into binary weapons (Nepovimova & Kuca, 2020). Binary weapons divide the highly toxic A-agents into two or more precursors. Before or during the firing of ammunition, the precursors are mixed to form the final product. Through the

NOVICHOK program, at least five types of precursors were created (Nepovimova & Kuca,

2020). Even to this day, information behind NOVICHOK remains designated as a national secret and information remains scarce.

2.2.2 Types of Nerve Agents

Traditionally, NAs are categorized into two classes: G- and V- agents. The G- agents include tabun (GA), sarin (GB), soman (GD) and cyclosarin (GF). While the V (Victory)-agents were synthetized following World War II by the Allied Forces. The V-agents include VE, VM,

VG, VR, CVX, and VX. The G- and V-agents are known as the first- and second-generation

NAs. A third generation of NAs have come to light, A-agents. The A-agents were synthetized by

Russia and includes A230, A232, and A234.

2.2.3 Epidemiology

Even though approximately 12,000 tonnes of tabun was stockpiled between 1942 to

1945, it was not until the Iran-Iraq war (1983-1988) when NAs were first used (Balali-Mood &

Balali-Mood, 2008). During the Iran-Iraq war, NAs and other types of chemical weapons were used by the Iraqi military against Iranian troops and civilians. It is estimated that 45,000 to

100,000 people were poisoned during the Iran-Iraq war (Balali-Mood & Saber, 2012; Newmark,

2004a). Iraq also used chemical weapons including tabun and sarin against Halabjah, a Kurdish town killing between 5,000 to 8,000 people (Balali-Mood & Shariat, 1998).

During the Gulf War, chemical weapons were never used on the coalition forces.

Although Iraq had chemical weapon production plants, stockpiles, and armament, they were never used (Moshiri, Darchini-Maragheh, & Balali-Mood, 2012). However, US troops may have been exposed to sarin and cyclosarin due to the destruction of an Iraqi munition depot at

Khamisiyah (Walpole & Rostker, 1997). Based on plume modelling developed by the

Central Intelligence Agency, it is estimated that 98,910 US troops were exposed to low levels of sarin and cyclosarin (Walpole & Rostker, 1997).

NAs have also been used in terrorist attacks. Aum Shinrikyo sect, a Japanese cult, carried out two major attacks involving sarin in Matsomoto (1994) and in the Tokyo subway (1995); combined, these attacks poisoned over 6,000 civilians (Vale, 2005). The intention of the

Matsomoto attack in 1994 was to assassinate judges that were overseeing a real estate case against the sect (Olson, 1999). Approximately 600 people were exposed to sarin and led to the death of 7 people (Okudera et al., 1997). In the 1995 Tokyo subway sarin attack, sect members concealed sarin in lunch boxes and drink containers. The sarin infused packages were then punctured, injuring 5,500 civilians and killing 12 (Okumura et al., 1998).

In the recent decade, at least two publicly reported incidences of mass casualty have occurred during the Syrian civil war in 2013 and 2017, where sarin filled warheads were released on civilians (Dolgin, 2013; OPCW, 2017). The attack on August 2013 was the most deadly that killed 1,400 people (Dolgin, 2013).

The potency of NAs also makes them effective tools in assassination. NAs were utilized in the assassination attempts of two notable public figures, with one attack being successful.

Firstly, Kim Jong Nam - the half-brother to North Korean Leader Kim Jong-Un - was assassinated at a Malaysian airport using VX (Nakagawa & Tu, 2018). Although the assassination was captured on tape, it still remains unclear how the perpetrators were unaffected by the NA. Secondly, an assassination attempt was made on Sergei and Yulia Skripal in

Salisbury, United Kingdom (Dodd, Harding, & MacAskill, 2018). In addition to the Skripal’s, an officer who responded to the initial call and two civilians who found a perfume vial containing the agent were also poisoned. Everyone survived except for one of the civilian (BBC, 2018b).

The British authorities later disclosed the NA that was used in the attack was NOVICHOK

(BBC, 2018a).

NAs are categorized as a Weapon of Mass Destruction (WMDs) because of their potency and ability to cause mass casualties. This categorization led to banning the usage, stockpiling, and development of NAs under the Chemical Weapons Conventions Act. Despite the ban having been effective since 1997, increasing usage has been seen, especially in the Syrian Civil War

(Dolgin, 2013; OPCW, 2017). In addition to the potential of killing thousands of people, exposure to NAs at low doses or sub-lethal dose has debilitating neurological effects.

The mechanism of NA induced mortality is well understood, however, there is a lack of understanding in regard to the neuropathology associated with patients who have been exposed to a sub-lethal dosage of NA. The thousands of victims who were exposed and survived NA attacks might have preventable neurological deficits if treated correctly. Studies involving victims exposed to NAs have shown changes in regional white matter volume (Chao, Abadjian,

Hlavin, Meyerhoff, & Weiner, 2011; Heaton et al., 2007; Yamasue et al., 2007) and grey matter volume (Chao et al., 2011; Chao, Rothlind, Cardenas, Meyerhoff, & Weiner, 2010). Despite the limitations of these studies in estimating exposure dosage and being performed years after the event, they still reveal the potential neurological impact NAs can have. Part of the neurological impact can be explained by their mechanism of action.

2.2.4 Mechanism of action

Acetylcholine (ACh) is a neurotransmitter in the central and peripheral nervous system used in cholinergic neurons. When an action potential reaches the nerve terminal, the depolarization induces an influx of calcium in the presynaptic terminal of a neuron. The influx

mediates the binding of ACh containing vesicles to the membrane of the nerve terminal releasing

ACh into the synapse. ACh diffuses across the synaptic terminal and binds to a nicotinic or muscarinic ACh receptor in the post-synaptic neuron.

Nicotinic ACh receptors are ligand-gated ion channels, which are permeable to sodium, potassium, and calcium ions. Activation of nicotinic ACh receptor propagates neurotransmission.

In the case of muscarinic receptors, they are G protein-coupled receptors and tends to be slower compared to nicotinic ACh receptors. Furthermore, muscarinic ACh receptors may have either excitatory or inhibitory effects.

ACh signalling can be terminated by the enzyme acetylcholinesterase (AChE). AChE works by hydrolyzing ACh into acetate and choline. The AChE active site is comprised of the anionic and esteratic subsite (Nachmansohn & Wilson, 1951). The anionic subsite contains a negative charge that interacts with the positively charged quaternary amine in the choline moiety of ACh (Wilson & Quan, 1958). The esteratic subsite contains the catalytic triad composed of glutamate 327, histidine 440, and serine 203, to mediate the hydrolysis of ACh to choline and acetate (Sirin & Zhang, 2014). The rate limiting step in the breakdown of ACh is the diffusion of

ACh to AChE because of the high catalytic activity (Quinn, 1987; Taylor & Radic, 1994). The choline produced from the hydrolysis are taken up by choline transporters in the presynaptic terminal. The active site, which is now bound with acetate, undergoes hydrolysis to regenerate active AChE. Acetylcholine is resynthesized through choline acetyltransferase, which combines choline and acetyl-coenzyme A. NAs target the catalytic triad and inhibit the breakdown of ACh, which leads to various pathologies.

NAs are potent irreversible inhibitors of AChE. The chemical structure of NAs resembles

ACh, thereby making it easy for them to bind on the AChE active site. Inhibition of AChE

occurs through two steps. Initially, NAs covalently binds to the serine hydroxyl group (serine

203) in the catalytic triad then the leaving group breaks off causing inhibition of AChE. The inhibition of AChE at this stage is still reversible. The initial bond is reversible because spontaneous hydrolysis or AChE reactivators can break the bond thereby reactivating AChE.

Second, an aging process takes place where the NA-AChE complex undergoes an acetylation reaction liberating the O-alkyl group. In soman for example, the pinacolyl bond is lost

(Jokanovic, 2001; Zilker, 2005). The result of the aging process is the formation of negatively charged phosphorylated AChE complex, which leads to irreversible inhibition (Worek et al.,

2004). The only way to regain functional AChE after the aging process is through biosynthesis.

The aging rate is dependent on the NAs. For example, aging process for soman occurs within 2-

2.5 minutes, making soman the fastest acting NA (Worek et al., 2004). In the case of sarin, the aging process can take up to 3 hours (Worek et al., 2004). Therefore, the time window in which treatment is most effective tends to vary depending on the NA. Inhibition of AChE can manifest different physiological signs and symptoms.

2.2.5 Signs and Symptoms of Exposure

Inhibition of AChE leads to an accumulation of ACh in the synapse causing a cholinergic over-stimulation that prompts clinical manifestations (Cannard, 2006; Geoghegan & Tong, 2006;

Holstege et al., 1997). The symptoms can be divided between central and peripheral effects. The central effects are mainly related to the central nervous system while the peripheral effects are more widespread to include the respiratory, cardiovascular, and skeletomuscular system. Central nervous system related symptoms include anxiety, tremors, coma, central respiratory depression, and convulsive seizures (McDonough & Shih, 1997). Peripheral symptoms can be further

divided into muscarinic and nicotinic manifestation. Muscarinic symptoms include lacrimation, miosis, bronchorrhea, apnea, bradycardia, hypotension, sweating, salivation, nausea, diarrhea, and urination. Nicotinic symptoms include tachycardia, hypertension, fasciculation, and paralysis. Ultimately, respiratory failure is the most common cause of death. The signs and symptoms are dependent on dose and route of exposure.

The exposure route and dosage of NA are both critical factors in the development of signs and symptoms (Cannard, 2006). Exposure at high doses can cause respiratory distress within minutes following exposure; but at low doses, symptoms may only progress to miosis and shortness of breath. Exposure route changes the clinical manifestation of symptoms as well. The two most common exposure routes for NAs are dermal or inhalation. In the case of dermal exposure, initial symptoms including fasciculations and sweating which tend to be localized at the site of exposure. In the case of inhalation exposure, miosis is one of the first symptoms to develop, which is followed by rhinorrhea, and shortness of breath. In both dermal or inhalation exposure, as NAs enter the blood stream, more generalized symptoms tend to develop including muscular weakness, paralysis, convulsive seizures, and respiratory distress.

The immediate effects of NA exposure are well understood along with the mechanism associated in the symptom development. However, NA exposure has also shown to cause extensive neurological damage with behavioral deficits. The cause of NA related neurological damage are believed to be related to convulsive seizures. Before starting a NA-related project, researchers must decide on which NA they will utilize in their study.

2.2.6 The Choice of Soman for this Project

We used soman (O-pinacolyl methylphosphonofluoridate) because it is commonly used to study the neuropathological effects of NAs. This is due to two reasons. First, soman is the fastest irreversibly binding NA. Irreversible inhibition occurs within minutes, relative to hours for other NAs (Worek et al., 2004). Second, AChE inhibited by soman does not undergo spontaneous reactivation. This suggests that the neuropathology can be studied with minimal delay and treatment is more complex compared to other NAs. Treatments that are effective against soman have a high potential of being effective against other NAs. For these reasons, in this thesis, the neuropathology associated with soman exposure will be investigated. Next, the appropriate animal model must be taken into consideration based on the research question.

2.2.7 Animal Models to Study Nerve Agent exposure

To study the neuropathology following NA exposure, various animal models including guinea pigs (Due, Trap, Langenberg, & Benschop, 1994; Gullapalli et al., 2010), mice (Baille et al., 2005; Carpentier et al., 2008; Dhote et al., 2012), rats (Apland et al., 2010; Bhagat, Obenaus,

Hamilton, & Kendall, 2001; De Araujo Furtado, Aroniadou-Anderjaska, Figueiredo, Apland, &

Braga, 2020; de Araujo Furtado et al., 2010), rabbits (Koplovitz & Stewart, 1994), swine

(Sawyer, Mikler, Tenn, Bjarnason, & Frew, 2012), and primates (Baze, 1993) have been utilized.

For preclinical studies, small animal models such as guinea pigs, mice or rats are preferred as they are relatively inexpensive and allows researcher to have a high throughput. The guinea pig model is a widely accepted model by NA researchers due to their low levels of carboxylesterase similar to humans. In rats and mice, the high levels of carboxylesterase acts as a bioscavenger of

NAs, therefore a higher dose of NA is required to produce a toxic effect. For example, the

median lethal dose (LD50) for a subcutaneous injection of soman in guinea pigs is 24 μg/kg

(John, Balszuweit, Kehe, Worek, & Thiermann, 2015), and 110 μg/kg in rats (Shih, Penetar,

McDonough, Romano, & King, 1990). To mimic the lack of carboxylesterase, genetic knockout mice have been created to evaluate protective treatments against NAs (Duysen et al., 2011).

Despite the presence of carboxylesterase in mice and rats, they still remain the preferred model to study NA-induced seizures.

One shortcoming of the guinea pig model is the lack of reports on the development of spontaneous recurrent seizures following NA exposure. If the intentions are to study NA-induced seizures, the lack of recurrent seizures may not provide an accurate representation of the long- term pathologies. However, spontaneous recurrent seizures have been reported in C75Bl6/J mice

(McCarren et al., 2020) and Sprague-Dawley rats (de Araujo Furtado et al., 2010). Therefore, mice or rats are ideal models in studying the long-term neuropathology following NA-induced seizures.

A main issue in animal models of NA-induced seizures is balancing the survival rate and consistency in seizure induction. In order to induce seizures following NA exposure, >67% of

AChE needs to be inhibited (Tonduli, Testylier, Marino, & Lallement, 1999) however, the dosage required to reach the 67% threshold is near the LD50 . Unfortunately, dosage around the

LD50 are associated with high mortality rates due to an increased risk of respiratory distress. To overcome this problem, researchers have utilized treatments with limited permeability through the blood-brain barrier (BBB) to increase survival while maintaining the central effects of NAs.

The most common treatment includes atropine and HI-6. Atropine is a competitive antagonist of muscarinic receptors, where atropine inhibits ACh binding and reduces cholinergic stimulation

(Eger, 1962; Shih, Koviak, & Capacio, 1991). There are two forms of atropine utilized in NA-

related research, they are atropine methyl nitrate (AMN) and atropine sulfate (AS). Atropine methyl nitrate (AMN) is a quaternary ammonium compound while atropine sulfate is a tertiary ammonium compound (Prozorovskii, 1962; Rubin & Goldberg, 1958). The larger size of AMN limits the BBB crossing compared to AS. Additionally, HI-6 is an oxime which is able to reactivate AChE before the aging process (Jokanovic & Stojiljkovic, 2006). Two variations of

HI-6 exists, including HI-6 dimethanesulfonate (HI-6 DMS) and HI-6 dichloride (HI-6 2Cl).

Both compounds have been shown to be equally effective in reactivating AChE following NA exposure (Krummer, Thiermann, Worek, & Eyer, 2002). The limited solubility of HI-6 2Cl generates difficulty in dissolving it in saline compared to HI-6 DMS, therefore HI-6 DMS is the more commonly utilized form of HI-6 (Thiermann, Seidl, & Eyer, 1996). Although the reactivation of HI-6 may interfere with NA-induced seizures, HI-6 is unable to cross through the

BBB (Karasova, Pavlik, Chladek, Jun, & Kuca, 2013). Therefore, HI-6 DMS and AMN are used

NA-induced seizures studies as they reduce mortality without modulating activity in the central nervous system.

The timing of treatment in animal models are also a critical factor to study NA-induced seizures and related neuropathology. Typically, animals are pretreated before exposing them to

NAs to allow the pretreatment to circulate throughout the body. Following NA exposure, additional doses of treatments can be provided at intervals to help maximize survival. However, if the intentions are to mimic real-life scenarios where an unexpected NA attack happens, no pretreatment should be given, and the post-treatment should be delayed. A conservative time point to administer the post treatment tends to be 1 minute but a more realistic scenario is 5 -15 minutes. If the intentions are to maximize survival while still maintaining seizure activity,

animals should be provided with both a pre and post-treatment regime that does not have anti- seizure properties.

2.2.8 Mechanism of Nerve Agent-induced Seizures

NAs can readily cross the BBB and induce severe seizures (Shih & McDonough, 1997).

Seizures arise from a state of hyperexcitation and hypersynchronous firing of neuronal networks, which can result in neuronal damage if left untreated (Fisher et al., 2005). Currently the seizure onset site or mechanism of NA induced seizure is not fully understood. However, in comparison to epilepsy, there is a clear cause and effect in terms of what generates the seizures. This cause- and-effect relationship makes it easier to elucidate a possible path of seizure progression. A mechanism in how NA-induced seizures are generated can be proposed based on temporal neurochemical progression (McDonough & Shih, 1997), delayed seizure onset (Myhrer, Enger,

& Aas, 2008, 2010), and brain lesion studies (Myhrer, Enger, & Aas, 2007; Zimmer, Ennis,

Wiley, & Shipley, 1998). A three-phase model was proposed which includes the cholinergic phase, transition phase, and non-cholinergic phase (McDonough & Shih, 1997).

The cholinergic phase occurs within 5 minutes following soman injection and is ascribed to cholinergic hyperactivity. Immediately following soman injection, irreversible inhibition of

AChE causes an increase in ACh (Shih & McDonough, 1997), which leads to hyperactivity of cholinergic projection from the diagonal band of Broca (Zimmer et al., 1998) to the area tempestas (piriform cortex) (Myhrer, 2007), initiating the onset of convulsive seizures. ACh levels continue to rise past the onset of seizures. A transition phase occurs between 5- and 40- minutes following seizure onset and is described to be a mixture between cholinergic and non- cholinergic mechanisms that propagate the seizure activity. During the transition phase, the ACh

receptors become saturated and reach maximum receptor activity (Shih & McDonough, 1997).

Hyperactivity of the cholinergic neurons in the piriform cortex induce glutamatergic projections to release glutamate, and aspartate (Shih & McDonough, 1997) (Lallement et al., 1993) in the posterior piriform cortex, entorhinal cortex, perirhinal cortex, and hippocampus (Myhrer, 2007) thereby propagating seizure activity. A study has also reported that other neurotransmitters, such as gamma-aminobutyric acid (GABA) and dopamine, increase during the transition phase (Shih

& McDonough, 1997). The non-cholinergic phase occurs 40 minutes after seizure onset when cholinergic receptor activity reaches a maximum and does not contribute to the maintenance of seizure activity (Shih & McDonough, 1997). Excitatory amino acids continue to maintain the seizure activity. During the maintenance phase, excitatory amino acids, ACh, and inhibitory amino acid receptor activity was shown to plateau (Shih & McDonough, 1997). If left untreated, the events lead to status epilepticus.

Status epilepticus is a life-threatening condition defined by prolonged seizures due to a failure in self-termination of seizures. Survivors of status epilepticus often suffer significant neurological damage therefore intervention needs to be administered at an appropriate time.

However, there is still limited knowledge on the time point when defining status epilepticus.

Previous definition of status epilepticus was 30 minutes of ongoing or recurring seizure activity without returning to consciousness before the need of pharmacological intervention (Bone,

1993). The duration of 30 minutes was chosen due to the potential development of irreversible neurological damage beyond this time point (Trinka et al., 2015). The definition has been continuously refined over the years. The current consensus for pharmacological intervention is 5 minutes of ongoing seizure activity (Lowenstein, Bleck, & Macdonald, 1999). Seizures lasting more than 5 minutes have a lower probability of self-termination. NA exposures have been

known to cause generalized tonic-clonic seizures that can develop into status epilepticus and lead to brain damage (Lallement et al., 1998; Newmark, 2004b; Petras, 1994; Shih & McDonough,

1997). Status epilepticus is difficult to remedy when treatment is delayed due to the intravasation of GABAA receptors (Naylor, Liu, & Wasterlain, 2005) and increased excitability from trafficking N-methyl-D-aspartate (NMDA) receptors on the post synaptic terminal (Wasterlain,

Naylor, Liu, Niquet, & Baldwin, 2013). Additionally, coupled with serum albumin binding to astrocytes can further increase excitability and lead to the development of spontaneous recurrent seizures (Cacheaux et al., 2009; Ivens et al., 2007). Spontaneous recurrent seizures have been shown to manifest days after NA exposure (Bar-Klein et al., 2017; de Araujo Furtado et al.,

2010) and can result in further neurological damage.

There are a variety of pathologies that follows seizures including excitotoxicity, edema, neuroinflammation, oxidative stress, and hypoxia/ischemia. Recent studies found impairment in vasodynamics in seizures that may exacerbates neurological damage (Farrell et al., 2016; Leal-

Campanario et al., 2017). Impairment can be detected using fiber-optic oxygen sensing probes to measure tissue oxygenation. Since oxygenation is a balance between oxygen delivery (blood flow) and utilization (metabolism), changes may be indicative of hemodynamic impairment. To set the stage, it will be beneficial to have a brief review on what governs changes in oxygenation- regulation of cerebral blood flow and metabolism.

2.3 Cerebral Blood Flow and Metabolism

2.3.1 Regulation of cerebral blood flow

The brain is a complex structure made up of billions of neurons and glial cells (Azevedo et al., 2009). As such, the brain utilizes a disproportionate amount of energy compared to their

relative body weight. To meet the required energy demand, there are complex cerebrovascular architecture with redundancies to maintain a constant supply of oxygen and glucose through cerebral blood flow (CBF). CBF was shown to be correlated to local field potentials, which represents neuronal activity (Enager et al., 2009; Mathiesen, Caesar, Akgoren, & Lauritzen,

1998). The change in CBF in response to neuronal activity is referred to as neurovascular coupling (Fox & Raichle, 1986; Roy & Sherrington, 1890). Neurovascular coupling can directly or indirectly mediate the increase in CBF in response to neuronal activity, a phenomenon known as functional hyperaemia (Buxton & Frank, 1997; Buxton, Wong, & Frank, 1998; Fox &

Raichle, 1986; Fox, Raichle, Mintun, & Dence, 1988).

Oxygenated blood is supplied to the brain through two pairs of arteries, the left/right internal carotid artery and vertebral artery (Venketasubramanian, Mohr, Young, Lien, & Breuer,

1994). They branch off into smaller arteries which forms penetrating arterioles that dive into the brain. The penetrating arterioles eventually branches off into capillaries. Blood flows in the lumen of arteries, arterioles, and capillaries, where the inner layer is composed of endothelial cells. The endothelial cells are held together by tight junctions, which forms a seminar permeable layer known as the blood-brain barrier (BBB) and prevents the extracellular fluid from entering the brain (Abbott, Ronnback, & Hansson, 2006). Nutrients, metabolites, ions, and water are transported across the endothelial cells. The endothelial cells are surrounded by contractile elements including vascular smooth muscle cells (Cipolla, McCall, Lessov, & Porter, 1997) and pericytes (Hamilton, Attwell, & Hall, 2010), which changes the diameter of the blood vessels.

The arteries and arterioles are surrounded by vascular smooth muscle cells, while capillaries are surrounded by pericytes. The contractile elements are then surrounded by astrocyte end feet.

Astrocytes have numerous roles including ion, neurotransmitter, and water homoeostasis,

glycogen storage, and modulation of CBF. According to the “astrocyte-neuron lactate shuttle” model, astrocytes are believed to convert glucose into lactate through glycolysis then transfer lactate to neurons (Pellerin et al., 2007; Pellerin & Magistretti, 1994; Pellerin et al., 1998).

Neurons would then use lactate, their favored energy substrate, to produce adenosine triphosphate (ATP) through oxidative phosphorylation.

There are several methods by which CBF is regulated in response to changes in blood pressure including myogenic, metabolic, neurogenic and endothelial control. Additionally, there are different types of cells including astrocytes, mural cells, and neurons whose relative contribution on CBF has yet to be elucidated. This thesis focuses on functional hyperaemia where CBF changes based on glutamate release by neurons. Following an action potential, glutamate is released into the extracellular space which binds to NMDA receptors on neurons

(Busija, Bari, Domoki, & Louis, 2007) and metabotropic glutamate receptors on astrocytes

(Porter & McCarthy, 1996). In neurons, the influx of calcium leads to the activation of neuronal nitric oxide synthase, which synthesizes nitric oxide (NO). NO is released by neurons and acts on vascular smooth muscle cells to control vascular response (Bhardwaj et al., 2000; Yang,

Zhang, Ross, & Iadecola, 2003). Within the vascular smooth muscle cells, NO promotes vasodilation by activating soluble guanylate cyclase to convert guanosine triphosphate into cyclic guanosine monophosphate (cGMP) (Archer et al., 1994). The rise in cGMP activates potassium channels and modulates intracellular calcium concentration that hyperpolarizes the vascular smooth muscle cells.

Astrocytes also contribute to functional hyperaemia through the release of potassium into the extracellular space (Filosa et al., 2006) and arachidonic acid (AA) metabolism (Takano et al.,

2006). The binding of glutamate on metabotropic glutamate receptor leads to an increase in

intracellular calcium in astrocyte endfeet. The influx of calcium leads to the activation of large- conductance calcium activated potassium channels to release potassium into the extracellular space (Filosa et al., 2006). The rise in extracellular potassium ion concentration opens inward- rectifier potassium channel which leads to vasodilation. AA metabolism is the final pathway to be discussed (Knot, Zimmermann, & Nelson, 1996). AA is produced from the phospholipid bilayer via the activation of phospholipases A2 by the increase in intracellular calcium.

Subsequently, AA is metabolized by lipoxygenase, epoxygenases, and cyclooxygenases. The metabolic byproducts including epoxyeicosatrienoic acid and prostaglandin E2 can lead to vasodilation (Alkayed et al., 1996; Howarth et al., 2017; Peng, Zhang, Alkayed, Harder, &

Koehler, 2004). Epoxyeicosatrienoic acid activates large-conductance calcium activated potassium channels to hyperpolarize vascular smooth muscle cells (Higashimori, Blanco, Tuniki,

Falck, & Filosa, 2010). On the other hand, prostaglandin E2 activates prostaglandin E2 receptor

EP4 subtype on vascular smooth muscle cells increases cyclic adenosine monophosphate leading to hyperpolarization (Davis et al., 2004). Knockout or inhibition of neuronal NO synthase or AA metabolism has been linked to a reduction in activity driven CBF changes (Ma, Ayata, Huang,

Fishman, & Moskowitz, 1996; Peng et al., 2002).

Vasoconstriction on the other hand is largely mediated through calcium (Mulligan &

MacVicar, 2004). The increase of intracellular calcium in vascular smooth muscle cells activates calmodulin. Calcium-calmodulin complex binds to myosin light chain kinase which phosphorylates myosin light chains to form cross-bridges with actin filaments. These steps lead to vasoconstriction. AA metabolism can lead to vasoconstriction through the production of 20- hydroxyeicosatetranoic acid in an oxygen dependent mechanism (Gordon, Choi, Rungta, Ellis-

Davies, & MacVicar, 2008). 20-hydroxyeicosatetranoic acid depolarizes the vascular smooth

muscle cells through the opening of L-type calcium channels (Gebremedhin et al., 1998). The microvascular changes in capillaries and arterioles can mediate upstream vascular reactivity.

To deliver adequate oxygen and glucose for metabolic activity, arteriole and artery diameter changes based on demand. The arterial and arteriolar responses have been proposed to be mediated through retrograde signaling from endothelial cells (Chen, Bouchard, McCaslin,

Burgess, & Hillman, 2011; Iadecola, Yang, Ebner, & Chen, 1997). Gap junctions, electrical synapses, connect endothelial cells to neighboring endothelial cells, vascular smooth muscle cells, and pericytes (Chen et al., 2011). Changes in endothelial membrane potential in the capillaries including hyperpolarization will travel retrogradely to upstream arterioles and pial artery. This will allow relaxation of vascular smooth muscle cells surrounding arterioles and pial arteries to increase CBF in areas of high metabolic demand. Impairment in these regulatory mechanisms can lead to hypoxia and/or ischemia.

2.3.2 Hypoxia/Ischemia

Impairment in CBF can cause neurological damage by not being able to supply oxygen and glucose to meet metabolic demand. The involvement of hypoxia and its relation to NA neuropathology is uncertain as NA exposure causes respiratory dysfunction while seizure activity has been shown to cause hypoxia/ischemia (Farrell et al., 2016; Leal-Campanario et al.,

2017; Wolff, Farrell, Scantlebury, & Teskey, 2020). To separate the central and peripheral effects of soman, many researchers utilize atropine, a peripheral acetylcholine receptor inhibitor, to counter respiratory problems. Previous studies have found hypoxic/ischemic lesions following soman-induced convulsive seizures however, these studies did not provide treatments preventing peripheral symptoms (Baze, 1993; Petras, 1994) making it difficult to determine if the lesions are

from respiratory distress or hypoxia/ischemia. Shih and Scremin (1992) found uncoupling of

CBF and glucose utilization in the hippocampus CA3, dentate gyrus, medial thalamus, and substantia nigra. This led them to postulate that relative ischemia contributes to neuropathology.

Furthermore, inhibition of endothelial nitric oxide, a vasodilator, can cause an increase in seizure severity and subsequent neuropathology (Lallement et al., 1996). The exact cause of the increase in neuronal damage may be linked to the increase in seizure severity but the potential effects on the hemodynamics cannot be ignored.

A study by Farrell et al. (2016) detected hypoxia using fiber optic oxygen sensors and hypoperfusion in the postictal phase through a cyclooxygenase-2 (COX-2) dependent pathway.

Subsequent study has also shown that self-generating recurrent seizures post status epilepticus could cause hypoxia (Wolff et al., 2020). Following soman exposure, there was an increase in neuronal COX-2 expression in the hippocampus, basolateral amygdala, piriform cortex, and thalamus at 24 to 48 hours (Angoa-Perez et al., 2010). The finding suggests that earlier NA studies may not have been able to detect hypoxia due to the transient nature. With the increasing evidence of abnormal vasodynamics, a similar event following soman-induced seizures may be possible. Hypoxic/ischemic events after soman may disrupt cell metabolism leading to an impairment of the electrochemical gradient, mainly sodium, in neurons and astrocytes. The influx of cations into neurons and astrocytes would lead to an influx of anions, increasing osmotic pressure, resulting in an influx of water and expansion of the cells causing cytotoxic edema (D. Liang, Bhatta, Gerzanich, & Simard, 2007). Depletion of ions in the extracellular space creates a new gradient between the capillary and blood brain barrier, which can further exacerbate the injury.

2.4 Neuropathophysiology associated with Nerve Agents

This section serves to provide an overview on neuropathophysiological mechanisms involved in NA exposure. Previous research with soman in animal models has shown seizures to be a major contributing factor for neurological damage. In the absence of convulsive seizures, either through innate tolerance or pharmacological intervention, no neurodegeneration was observed (Apland et al., 2010; Baille et al., 2005; de Araujo Furtado et al., 2010; Guo et al.,

2015; Lallement et al., 1993; McDonough, McLeod, & Nipwoda, 1987; Myhrer et al., 2008).

When convulsive seizures were terminated within 20 minutes, minimal neuronal loss was seen

(Baille et al., 2005; Lallement et al., 1993), suggesting that the presence and duration of seizures are key factors in modulating soman-related neurological damage.

There are several injury prone areas in the brain following soman-induced seizures that have been the main focus for targeted treatments. Histological assessment within the first 48 hours following soman-induced convulsive seizures have shown the hippocampus, piriform cortex, entorhinal cortex, amygdala, hippocampus, amygdala, thalamus and frontal cortex to have significant neurodegeneration (Apland et al., 2010; Baille et al., 2005; Hayward et al.,

1990; Kadar, Cohen, Sahar, Alkalai, & Shapira, 1992; Lemercier, Carpentier, Sentenac-

Roumanou, & Morelis, 1983). Morphological analysis of degenerating neurons has found hybrid forms of necrosis and apoptosis with pure apoptosis to be uncommon (Baille et al., 2005).

Neurodegeneration was also accompanied by ventricular enlargement (Kadar et al., 1992;

Tryphonas & Clement, 1995), and hypertrophic astrocytes in the piriform cortex, hippocampus, and thalamus (E. A. Johnson & Kan, 2010; Tryphonas & Clement, 1995).

There are neuropathophysiological mechanisms that may be working simultaneously and temporally that contribute to neurodegeneration following soman exposure. An understanding in

the heterogeneous nature and timing is critical in developing a comprehensive treatment protocol.

2.4.1 Excitotoxicity

Excitotoxicity is believed to be a major mechanism in which soman-induced convulsive seizures cause neurodegeneration. Referring back to the proposed three-phase model (section

2.2.8) the cholinergic phase is defined by the inhibition of AChE which leads to hyperexcitation and hypersynchronous firing of cholinergic neurons resulting in convulsive seizures.

Subsequently, the transition phase occurs when cholinergic neurons recruit non-cholinergic neurons, where simultaneous, cholinergic stimulation recruits glutamatergic neurons to release glutamate (Wade, Samson, Nelson, & Pazdernik, 1987), which in turn recruits α-amino-3- hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors. Activation of AMPA receptors is followed by the activation of NMDA receptors and calcium entry. The activation of NMDA receptors activates a cell death pathway leading to apoptosis and/or necrosis (Fujikawa, Shinmei,

& Cai, 2000; Lallement et al., 1993) activated by the influx of calcium ions. In the non- cholinergic phase, the influx of calcium results in neurons being in a state of hyperexcitability further facilitating the propagation and maintenance of seizures. The high levels of calcium within the cell activates enzymes including proteases, endonucleases, and lipases, which can damage neuronal integrity (Berliocchi, Bano, & Nicotera, 2005).

The mitochondria also serve an important role in excitotoxic damage. Normally, the mitochondria act as a buffer for cytosolic calcium (Mehta, Prabhakar, Kumar, Deshmukh, &

Sharma, 2013), but excessive calcium results in the opening of mitochondrial permeability transition pore which causes metabolic impairment through mitochondrial membrane

depolarization (Brustovetsky, Brustovetsky, Jemmerson, & Dubinsky, 2002; Hunter & Haworth,

1979). The metabolic impairment reduces ATP production and increases the production of reactive oxygen species (ROS) that further damages the cell (Mehta et al., 2013). Impairment in mitochondrial function releases additional calcium into the cytosol to activate caspases and calpain which triggers apoptosis (Cao et al., 2007; Garrido et al., 2006). Therefore, extensive research was undertaken to prevent the excitotoxic damage by inhibiting glutamatergic stimulation.

Pharmacological studies involving anti-glutamatergic drugs in soman exposure prevented the development of neuropathology (Clement & Broxup, 1993; Guo et al., 2015; Hayward et al.,

1990; Lallement et al., 1993). Furthermore, upstream treatments preventing the recruitment of cholinergic hyperactivation using anti-cholinergic drugs blocked soman-induced seizures

(Myhrer et al., 2008) with minimal neuropathology (McDonough, Dochterman, Smith, & Shih,

1995; Myhrer et al., 2010). Excitotoxicity is also found in other status epilepticus models

(Fujikawa et al., 2000; Olney, Rhee, & Ho, 1974; Puig & Ferrer, 2002) suggesting the soman neuropathology to be through similar mechanisms.

2.4.2 Blood-Brain Barrier Disruption

The blood-brain barrier (BBB) is a semipermeable selective barrier that prevents solutes and water from freely entering the brain. Such barrier protects the brain against pathogens while maintaining careful control of the osmotic pressure through ion homeostasis. Dysfunction in the

BBB has been linked to variety of pathological events including NA exposure. NA-induced seizures can cause reversible opening of the BBB (Abdel-Rahman, Shetty, & Abou-Donia, 2002;

Ashani & Catravas, 1981; Carpentier, Delamanche, Le Bert, Blanchet, & Bouchaud, 1990) that

may contribute to edematous injuries (Bhagat, Obenaus, Hamilton, Mikler, & Kendall, 2005;

Carpentier et al., 2008; Gullapalli et al., 2010; Testylier et al., 2007) and to the development of spontaneous recurrent seizures (de Araujo Furtado et al., 2010; Marrero-Rosado et al., 2018;

McCarren et al., 2020). Astrocytes are an important mediator in BBB disruption. Normally, astrocytes play a critical role in potassium, water and glutamate homeostasis but a disruption in the BBB can cause an imbalance that may lead to the development of spontaneous recurrent seizures (Bar-Klein et al., 2017). Studies have found an increase in seizure susceptibility

(Frigerio et al., 2012) and correlation to abnormal electroencephalography (EEG) following BBB disruption (Tomkins et al., 2011).

An important mechanism in the development of spontaneous recurrent seizures is the binding of serum albumin on astrocytes. The extravasated serum albumin binds to transforming growth factor-beta receptors on astrocytes, where it can lead to downregulation of inward rectifying potassium channels. Such downregulation leads to an increase in extracellular potassium and enhances excitability, which leads to the development of spontaneous recurrent seizures (Frigerio et al., 2012; Ivens et al., 2007). The ion imbalance also changes the pressure gradient, which leads to an influx of fluids into the extracellular space of the brain and cause vasogenic edema. However, the binding of albumin to astrocytes alone was not enough to produce spontaneous recurrent seizures suggesting other mechanisms may be involved (Frigerio et al., 2012). Processes including increased production of glutamate following albumin binding to neurons (Tabernero et al., 2002) and neuroinflammation processes (Kim, Buckwalter, Soreq,

Vezzani, & Kaufer, 2012) are also believed to be involved.

2.4.3 Neuroinflammation

Acute inflammatory responses are important as a protective response towards pathogens, injury, and tissue damage. However, chronic inflammation can contribute to diseases pathogenesis in conditions including multiple sclerosis, seizure disorders, and traumatic brain injuries. The involvement of neuroinflammatory mechanisms in soman-related neurological damage has been shown through the identification of gene transcripts (Dhote et al., 2007;

Dillman et al., 2009; Svensson, Waara, Johansson, Bucht, & Cassel, 2001; A. J. Williams et al.,

2003) and presence of inflammatory proteins (E. A. Johnson et al., 2011; E. A. Johnson,

Guignet, Dao, Hamilton, & Kan, 2015; E. A. Johnson & Kan, 2010; Svensson, Waara, & Cassel,

2005). Proinflammatory cytokines including interleukin (IL)-1 alpha, IL-1 beta, and tumor necrosis factor (TNF)- alpha was found in the brain following soman exposure (E. A. Johnson &

Kan, 2010). With the exception of IL-6, the aforementioned cytokines peaked at 12 hours following soman-induced seizures in the hippocampus, piriform cortex, and thalamus (E. A.

Johnson & Kan, 2010). IL-1 alpha and IL-1 beta was expressed by microglia while IL-6 was expressed only by neurons and astrocytes. The expression of chemokine ligand 1 was expressed in neurons and endothelial cells while macrophage inflammatory protein-1 alpha was expressed by neurons and microglia (E. A. Johnson et al., 2011). The expression of these cytokines and chemokines preceded the infiltration of neutrophil and macrophages (E. A. Johnson et al., 2011).

Subsequently at 24 hours, neutrophil, and macrophage infiltration were found in the piriform cortex, hippocampus and thalamus (E. A. Johnson et al., 2011; E. A. Johnson et al., 2015) but T- cells were only detected in in the hippocampus and thalamus (E. A. Johnson et al., 2015).

Additionally, IL-18 was expressed by astrocytes and endothelial cells which correlated to the activation of macrophages (E. A. Johnson et al., 2015). Such inflammatory mechanisms can

further exacerbate neurological damage caused by soman and enhance the development of other pathological conditions including spontaneous recurrent seizures.

Spontaneous current seizures can develop because of proinflammatory cytokines and proinflammatory cytokine mediated BBB opening. IL-1 beta can inhibit glutamate uptake by astrocytes and increase extracellular glutamate concentration thereby generating a state of hyperexcitability (Hu, Sheng, Ehrlich, Peterson, & Chao, 2000). While TNF-alpha can increase glutamatergic transmission via upregulation of AMPA receptors and induced GABA receptor endocytosis, which also increases excitability (Pribiag & Stellwagen, 2013; Zou & Crews, 2005).

With addition of serum albumin extravasation following blood-brain barrier damage and a state of hyperexcitability from neuroinflammatory mechanisms may be the mechanism behind the development of recurrent seizures following soman exposure. Although the true extent of neuroinflammatory mechanisms on soman-related brain damage is uncertain, studies using pharmacological interventions with anti-inflammatory properties (Dhote et al., 2012; L. P. Liang,

Pearson-Smith, Huang, Day, & Patel, 2019) and genetic knockout models for IL-1 receptor

(Ferrara-Bowens et al., 2017) have found attenuation of damage.

2.4.4 Oxidative Stress

The involvement of oxidative stress in seizure related neuropathology is widely accepted and is another factor that needs to be considered following NA exposure. Under normal conditions, reactive oxygen species (ROS) are the by-product of aerobic metabolism. ROS are created through electrons escaping from the electron transport chain in the mitochondria, which is critical in energy production (Li et al., 2003; Murphy, 2009; Ray, Huang, & Tsuji, 2012). ROS can cause lipid peroxidation, which damages the phospholipid bilayer of cells and DNA

(Murphy, 2009). Cells are able to protect themselves with antioxidants, however, when there is an imbalance between ROS produced relative to the available antioxidants, macromolecular damage occurs. Since the brain has high metabolic demand even at resting state with limited antioxidants, the brain is highly susceptible to oxidative damage. Therefore, seizures which are highly metabolically demanding activities can easily produce high levels of ROS to cause extensive damage.

Oxidative stress contributes to soman-related neurological damage. Oxidative markers following soman-induced status epilepticus were found at 30 minutes (Jacobsson, Cassel, &

Persson, 1999) and 24 hours (Jacobsson et al., 1999; Klaidman, Adams, Cross, Pazdernik, &

Samson, 2003; L. P. Liang et al., 2019; Pazdernik, Emerson, Cross, Nelson, & Samson, 2001).

These oxidative markers were found in the piriform cortex, hippocampus, and amygdala

(Klaidman et al., 2003; L. P. Liang et al., 2019; Pazdernik et al., 2001), where previous studies have found severe neurodegeneration (Apland et al., 2010; E. M. Prager et al., 2014; Tryphonas

& Clement, 1995). Moreover, pharmacological intervention with an antioxidant was able to reduce damage associated with oxidative stress (L. P. Liang et al., 2019) further highlighting the involvement of oxidative damage in soman-related neuropathology. There is no doubt that high metabolic activity of seizures generates ROS, however, excitotoxicity, neuroinflammation, mitochondrial dysfunction, and inhibition of endogenous antioxidant production may also contribute to ROS production. Therefore, oxidative damages are an important part in soman- related neuropathology and cannot be overlooked to create a comprehensive treatment protocol.

2.4.5 Here We Go Again

The interconnectivity of pathologies makes it difficult to truly pinpoint the root cause behind soman-related brain damage. Multiple factors can contribute to NA-related neuropathology. In the addition to excitotoxicity, contributing factors including hypoxia/ischemia, BBB disruption, metabolic disruption, and inflammatory response likely occurs transiently. Based on the current evidence, following the onset of seizures, excitotoxicity may be one of the first pathological processes. The increase in metabolic demand from seizure onset and excitotoxic processes causes the production of reactive oxygen species that can impair mitochondrial function, thereby metabolism. Reactive oxygen species and degenerating cells can trigger neuroinflammatory processes which ultimately release proinflammatory cytokines. The combination of excitotoxicity, neuroinflammation, and oxidative stress can damage the endothelial cells, thereby causing an opening of the BBB. Additionally, hypoperfusion and hypoxia can further cause neuronal death, activate inflammatory processes, and increase permeability of the BBB. The leakage of serum albumin ultimately leads to the development of spontaneous recurrent seizures that starts the vicious cycle all over again.

2.5 MRI as a method to study pathology

MRI have been used to study NA-related neuropathology in animal models and human.

However, there are pulse sequences that can provide information on pathophysiology and more sensitivity to microstructural changes. Arterial spin labelling (ASL) is technique that can measure CBF, while quantitative T2 MRI can be used to measure edema (discussed later). Before diving into the details about these two techniques, a general overview on the basics of MRI is

provided from the following references (Brown & Semelka, 2011; McRobbie, Moore, Graves, &

Prince, 2017; Schröder & Faber, 2011).

2.5.1 Basic principles of MRI

Nuclei are made of subatomic particles called nucleons, specifically, protons and neutrons. These are composite particles themselves and consist of three quarks each, although of different properties. Each quark has an intrinsic property called spin angular momentum, when properly summed up, i.e. via addition of angular momentum in quantum mechanics, will give rise to a total nucleon spin of 1/2. When considering nuclear magnetic resonance, one must look at the nucleus as a whole and consider all the protons and neutrons that are bound together. In particular, it is important to look at the total spin of the nucleus, once again treating individual spins quantum mechanically. As a general rule of thumb, only nuclei with an odd number of protons and/or neutrons may have non-zero spins. If there is a non-zero spin, simply “spin”, then the nucleus can couple to an externally applied magnetic field to undergo nuclear magnetic resonance. In biological tissues, the hydrogen nucleus, which has a half spin state, produces majority of the MR signal due to their abundance in water and fat molecules.

When an external magnetic field is applied on a spin (hydrogen nuclei), the magnetic force applies a torque causing the spins to rotate around an axis at a specific frequency known as the Larmor frequency (f). The Larmor frequency is dependent on the applied magnetic field (B0) strength and gyromagnetic ratio (γ) which is a constant based on the size, mass, and spin properties of a nuclei. For example, hydrogen has a gyromagnetic ratio of 42.57 MHz/T). The

Larmor equation is depicted:

! = $%!

Therefore, in a 9.4T MRI, the Larmor frequency is 400.158 MHz, which is the frequency needed to achieve resonance.

Spins are oriented randomly when there is no B0, with a net magnetization of zero (Figure

2.3a). When placed in B0, spins realign themselves in simultaneous parallel and antiparallel orientation, referred to as a superposition state. For simplicity, only parallel or antiparallel orientation are shown in Figure 2.3b. Alignment parallel to B0 (parallel) is the lower energy state compared to antiparallel. Therefore, a slight excess number of spins will align parallel to B0 which generates a net magnetization (M0) (Figure 2.3b).

The spins in M0 can absorb energy and be tipped into another plane by applying an electromagnetic radio frequency (RF) pulse at the Larmor frequency. The excited spins will align themselves in the new plane and begin to dephase from each other when the RF pulse is turned off. Simultaneously, the spins recover back to their original orientation in M0 by emitting energy.

The exact nature in where the MR signals come from is unknown, however it is believed that the precessing spins generate a magnetic field that induces a current in the receiver coil. As the spins dephase from each other, the transient oscillation is referred to as the free induction decay (FID).

The emission of energy to return to M0 is called relaxation.

The direction aligned with the external magnetic field will be referred to as the longitudinal magnetization (z direction) and perpendicular to the magnetic field as the transverse magnetization (xy plane). Gradient magnetic fields can be applied in the orthogonal direction to select a region of interest through slice selection, phase encoding, and frequency encoding.

Figure 2.3 Orientation of spins before and after an external magnetic field (B0) is applied. a) In the absence of an external magnetic field, the spins are randomly oriented with no net magnetization (M0). b) When an external magnetic field is applied, spins reorient themselves with or against the magnetic field and precess around the axis. Aligning with B0 is the lower energy state therefore a slight excess number of spins align with B0 generating M0.

2.5.2 T1 relaxation, and T2 decay

T1 and T2 are both important time constants that helps generate signal and contrast in an image. T1 is the longitudinal or spin-lattice relaxation time. When a 90º RF pulse is applied, the aligned spins are excited towards to the transverse plane. Once the RF pulse is turned off, the time for the longitudinal magnetization (Mz) to recover 63% of M0 is referred to the T1 relaxation time.

#$/&' &" = &! (1 − * )

In tissues, the T1 relaxation occurs from the thermal energy transfer of the excited spins towards their surrounding environment. Therefore, solid tissues including fat are able to transfer thermal energy more readily and have a shorter T1 relaxation time. On the other hand, cerebrospinal fluid

(CSF) has a much longer T1 because the energy transfer occurs much slower.

T2 is the transverse decay time which is often referred to as spin-spin interaction. An RF pulse excites the spin in the transverse plane converting the longitudinal magnetization to become the transverse magnetization (Mxy). The Mxy immediately after the RF pulse is in phase coherence, meaning they are precessing at the larmor frequency around the z direction. This precession in the transverse plane induces a current in the receiver coil and ultimately generating the MR signal. Each spin generates its own magnetic moment in their surrounding causing nearby spins to experience a magnetic field that is the summation of B0 and magnetic moment.

Inhomogeneity created by such “spin-spin interactions” causes some spins to dephase faster or slower depending on their relative position. The interaction between spins decreases Mxy.

Therefore, T2 is the time when 37% of the Mxy is remaining.

#$/&* &() = &!*

Both T1 relaxation and T2 decay occur simultaneously but are independent from each other. T2 decay occurs more rapidly compared to T1 relaxation. Tissues where spins are close together and able to exchange energy more efficiently including fat will have shorter T2 time but in fluid compartments including cerebrospinal fluid will have longer T2 time.

The difference in T1 relaxation and T2 decay time between tissues can be used to obtain contrast in an MR image. MRI pulse sequences including T1-weighted and T2-weighted MRI generates an image based on T1 and T2 time.

2.6 MRI Methods

2.6.1 Arterial Spin Labelling MRI

ASL is an MRI method that can non-invasively measure perfusion by turning water molecules in arterial blood into an endogenous tracer. The benefit of ASL is that it does not require the injection of exogenous contrast agent including gadolinium contrast agents. The spins in arterial blood are magnetically excited (tagged) by an RF pulse before reaching the region of interest (D. S. Williams, Detre, Leigh, & Koretsky, 1992). As the tagged blood flows into the tissue, it alters the MR signal and a “tagged” image is acquired in the region of interest. A control image is acquired from the same region, without an RF pulse. Since tissues remain static, the control and tagged images can be subtracted to eliminate signals from these tissues. The remaining signal results in a perfusion weighted image where the intensity is proportional to perfusion in the region of interest (Detre et al., 1994).

In this thesis, we focus on continuous arterial spin labelling (CASL). In CASL, the RF pulse used to magnetically tag the spins in arterial blood is applied continuously over a narrow region in the presence of a gradient. This region is known as the “tagging plane” and is located

posterior to the region of interest, normally the neck. The continuous application of an RF pulse generates a constant flow of tagged blood moving towards the region of interest. After a short delay, known as the post-labeling delay, the magnetically tagged blood enters the capillaries changing the MR signal based on the rate of flow. An assumption in ASL is that water can freely diffuse into the brain from blood vessels and quickly reaching a state of equilibrium (Detre et al.,

1994). The signal from tagged blood diffusing into the tissue results in a signal to noise ratio of approximately 0.5-1.5%. CASL provides the highest signal to noise ratio compared to other variations of ASL (Wu, Fernandez-Seara, Detre, Wehrli, & Wang, 2007). The technique is further discussed in Chapter 4.

2.6.2 Quantitative T2

Previous NA-related studies have used T2-weighted MRI and T2 decay time to assess the neuropathology. T2-weighted MRI scans can be acquired by utilizing a spin echo pulse sequence that refocuses the dephasing spins. A 90 º RF pulse tips the spins into the transverse plane while simultaneously producing phase coherence. Spins will dephase at different rates, some slower or faster relative to one another due to the spin-spin interaction. The rate at which spins dephase from one another are dependent on their microenvironment. As the spins are dephasing, a 180 º

RF pulse is applied which reverses the direction of the spins and rephase them. The fast spins will have dephased further compared to the slow spins but when the 180 º RF pulse is applied, granted they are dephasing at the same rate, the spins will come together to rephase and produce a measurable echo. The TE is set to measure the echo. Successive 180 º RF pulses and TEs can be used to refocus the spins and map the change in image intensity, respectively. In mapping out

the change in intensity, the T2 decay curve can be mapped out to calculate the T2 in a region of interest and determine changes in the microenvironment.

In the brain, the microenvironment can change the T2 decay time. A homogenous environment including pure water has a long T2 time while impurities can shorten the T2. The brain is an inhomogeneous environment made up of water, proteins, and lipids. In the brain, there are water compartments that restrict the diffusion of water. Compartmentalization can result in variable shortening of T2 times based on the content of a given compartment.

There are four main compartments in the brain; myelin water, intra/extracellular water, and cerebrospinal fluid (Bjarnason, Vavasour, Chia, & MacKay, 2005). The myelin water compartment arises from water being trapped in the lipid bilayer of the myelin sheath and has the shortest T2 time. The presence of the lipid bilayer reduces T2 because of the static magnetic moment of the hydrogen atom in the lipid bilayer, slow rotation of water molecules, and magnetization transfer effects. Demyelination has been shown to cause a change in the myelin water compartment (Laule et al., 2008; Laule et al., 2006). The intra/extracellular water compartment makes up the largest T2 component. This compartment comes from water in the cytoplasm of neurons and glial cells, and external environment of the cells. The final compartment is the cerebrospinal fluid. Cerebrospinal fluid has a composition that is similar to pure water, thereby giving it a T2 time that is longer than the aforementioned compartments.

Therefore, a voxel may contain numerous water compartments. The T2 decay measured in one such voxel would be a summation of all the T2 decay components within the voxel.

A multiexponential T2 analysis can be used to study microstructural changes following soman exposure. The technique will be further discussed in Chapter 5.

2.7 Nerve Agents and MRI

In this section, we highlight how MRI can be used to study OP-induced seizures, and how this imaging modality can serve as a useful tool in evaluating NA-related pathologies. MRI has a significant role in studying neuropathological conditions because of the sensitivity to physiological and structural changes. The neuropathophysiological mechanisms associated with

NA, described previously, can cause neuropathological conditions outlined in Table 2.1. Some of these pathologies have been observed in animal models and victims of NA exposure using MRI.

Studies have linked vast majority of these pathologies to NA-induced seizures (Apland et al.,

2010; Baille et al., 2005; de Araujo Furtado et al., 2010; Guo et al., 2015; Lallement et al., 1993;

McDonough et al., 1987; Myhrer et al., 2008).

Table 2.1 Summary of pathologies in OP exposure

Neuropathology References Cerebral Edema (Baille et al., 2005; Bar-Klein et al., 2017; Bhagat et al., 2001; Bhagat et al., 2005; Carpentier et al., 1990; Carpentier et al., 2008; Gullapalli et al., 2010; Hobson et al., 2018; Hobson et al., 2017; Job et al., 2007; Rosman et al., 2012; Shrot et al., 2012; Shrot et al., 2015; Testylier et al., 2007) Neuroinflammation (Dhote et al., 2007; Dillman et al., 2009; Ferrara-Bowens et al., 2017; Hobson et al., 2018; E. A. Johnson et al., 2011; E. A. Johnson et al., 2015; E. A. Johnson & Kan, 2010; Reddy, Wu, Kuruba, Sridhar, & Reddy, 2020; Siso et al., 2017; Svensson et al., 2001; A. J. Williams et al., 2003) Blood-brain barrier damage (Abdel-Rahman et al., 2002; Ashani & Catravas, 1981; Bar-Klein et al., 2017; Carpentier et al., 1990) Excitotoxic damage (Clement & Broxup, 1993; Guo et al., 2015; Hayward et al., 1990; Lallement et al., 1993; Wade et al., 1987) Axonal Damage (Baille et al., 2005; Hernandez et al., 2015; Petras, 1994; Terry et al., 2003) Reduction in white matter integrity (Chao et al., 2011; Chao, Zhang, & Buckley, 2015; Heaton et al., 2007; Yamasue et al., 2007) Oxidative damage (Klaidman et al., 2003; L. P. Liang et al., 2019; Pazdernik et al., 2001) Reduced brain volume (Chao et al., 2011; Chao, Kriger, Buckley, Ng, & Mueller, 2014; Chao et al., 2010; Chao & Zhang, 2018; Reddy et al., 2020; Yamasue et al., 2007) Neurodegeneration (Apland et al., 2010; Baille et al., 2005; Bhagat et al., 2001; Bhagat et al., 2005; Gullapalli et al., 2010; Hobson et al., 2018; L. P. Liang et al., 2019; E. M. Prager et al., 2014; Reddy et al., 2020; Siso et al., 2017)

2.7.1 MRI studies in Animal models

T2-weighted and diffusion-weighted MRI have been used to assess neurological damage following soman exposure. Both imaging techniques are sensitive to changes in water content that reflects microstructural changes. Pathological conditions including edema, change in cellularity, inflammation, blood-brain barrier disruption, demyelination and axonal damage may be detected. Hyperintensive regions on T2-weighted images indicates an increase in water content, which could indicate edema. Diffusion-weighted imaging on the other hand tends to be more sensitive towards the different types of edema, cytotoxic or vasogenic, because the intensity is related to the diffusion of water. The apparent diffusion coefficient (ADC) can be used to quantify the level of restriction. Restricted diffusion gives hyperintense signal on a diffusion-weighted images which can indicate cytotoxic edema as water molecules get trapped within cells. An increase in diffusivity in conditions including vasogenic edema would lead to hypointensive signals due to the free movement of water.

MRI studies following OP exposure were carried out to study the development of neuropathology and evaluate the efficacy of novel treatments. T2-weighted and diffusion- weighted MRI has been used to study soman-induced seizures between 3 to 168 hours. A study using soman (1.8-2 LD50; subcutaneous) in a rat model found a decrease in T2 in the hippocampus, retrosplenial cortex, piriform cortex, amygdala, and thalamus at 12 hours (Bhagat et al., 2001; Bhagat et al., 2005). Subsequent imaging found T2 to return to normal by 24 hours after soman exposure (Bhagat et al., 2001; Bhagat et al., 2005). Diffusion-weighted imaging on the other hand found a decrease in ADC in the hippocampus, retrosplenial cortex, and thalamus up to 12 hours but returned to normal at 24 hours (Bhagat et al., 2001; Bhagat et al., 2005).

However, at 168 hours, the ADC decreased in the piriform cortex and amygdala in the addition

to the aforementioned brain regions (Bhagat et al., 2001; Bhagat et al., 2005). The study demonstrates cerebral edema with a transient change due to gliosis and neurodegeneration over a week following soman exposure. The changes in T2 and diffusion MRI at 7 days was consistent with silver staining, which is a marker for neurodegeneration (Bhagat et al., 2001; Bhagat et al.,

2005) but the histological changes at earlier time points are uncertain. A more thorough investigation was performed in a mouse model treated with soman (0.6 or 1.6 LD50; subcutaneous) where diffusion MRI found a decrease at 3 hours in the amygdala, hippocampus, cerebral cortex, thalamus, and amygdala/piriform cortex (Testylier et al., 2007). Unlike in the previous study, ADC remained lower at 24 hours (Testylier et al., 2007). Further validation was provided by another mouse study (1.6xLD50) where a decrease in ADC was also detected at 24 hours (Carpentier et al., 2008). The decrease in ADC was attributed to cerebral edema and corresponded with neuronal loss detected using hemalun-phloxine. In contrast to the previous study that utilized T2-weighted MRI, a guinea pig model after soman (1xLD50) found an increase at 6-7 hours in the amygdala, hippocampus, piriform cortex and thalamus (Gullapalli et al.,

2010). The T2 remains elevated until 7 days post exposure in the amygdala, piriform cortex, and thalamus while the hippocampus returned to normal. Neuronal death was validated with neurogranin mRNA in situ hybridization and Fluoro-Jade B 7 hours post exposure which coincided with T2 signal intensity (Gullapalli et al., 2010). Different animal models including mice, rats, and guinea pig have shown that cerebral edema was a consistent pathology detected with MRI following soman exposure.

Similar changes using T2-weighted and diffusion-weighted imaging were found in common OP variates, paraoxon and diisopropyl fluorophosphate (DFP), used as NA substitutes.

Paraoxon-induced seizures were studied between 3 hours and up to 50 days. Studies using rats

following paraoxon (1.4xLD50; intramuscular) found elevated T2 signal and values 3 hours following exposure in the thalamus, parieto-temporal cortex, and piriform cortex (Shrot et al.,

2012; Shrot et al., 2015). Similar changes were observed in a rat model 6 hours following DFP exposure with additional regions including cerebral cortex and substantia nigra (Hobson et al.,

2018). Subsequent time points, 12 – 72 hours, found additional hyperintensive lesions in the hippocampus, and caudate putamen, which corresponded to Fluoro-Jade C, a marker for neurodegeneration (Hobson et al., 2018). The early changes were related to survival within the first 24 hours; wider area of damage and higher T2 value were correlated with an increased risk in mortality (Shrot et al., 2012). The T2 intensity and values peaked at 24 hours followed by a gradual decrease 8 days after exposure (Shrot et al., 2012; Shrot et al., 2015), indicating that 24 hours is an important time point in assessing maximal damage.

BBB disruption can be evaluated using gadolinium enhanced T1-weighted MRI. When there is BBB breakdown, gadolinium can enter the brain to provide contrast on T1-weighted

MRI. A study using paraoxon (1.4xLD50) found a relationship between BBB disruption and the development of spontaneous recurrent seizures (Bar-Klein et al., 2017). The rats were treated with atropine sulfate and obidoxime 1 min after exposure, upon which seizures were terminated after 30 minutes using midazolam. Two days following exposure, gadolinium enhanced T1- weighted images found hyperintensities in the amygdala and piriform cortex in rats that developed spontaneous recurrent seizures (Bar-Klein et al., 2017). Disruption of the BBB is observable up to 1 month with additional hyperintensive regions including the neocortex, hippocampus, septum, and striatum. T2-weighted MRI found more areas of enhancement including the amygdala, corpus callosum, internal capsule, neocortex, piriform cortex, olfactory bulbs, dorsal endopiriform nucleus, inferior olive, pallidum, and striatum at 2 days (Bar-Klein et

al., 2017). The enhancement remained in the amygdala, piriform cortex, septum, and striatum at

1 week and 1 month. Thus, preventing the development of spontaneous recurrent seizures is another pathology that needs to be accounted for when treating NA exposure.

2.7.2 Human MRI studies

Two incidences (1995 Tokyo Subway Sarin attack and destruction of weapons depot in

Khamisiyah, Iraq) have led to the utilization of MRI to study long-term pathologies following

NA exposure in humans. The victims of the Tokyo attack were exposed to an acute dose of sarin and presented NA-related symptoms (Yamasue et al., 2007). MRI was conducted 5 years after the subway attack, but the neurological deficits still haunts the victims. T1-weighted MRI found reduced regional gray matter volume in the right insular cortex, temporal cortex, and left hippocampus (Yamasue et al., 2007). Diffusion tensor imaging revealed microstructural damage in the white matter of the parietal and temporal lobe, temporal stem, and brain stem (Yamasue et al., 2007). Interestingly, serum cholinesterase levels, a marker of sarin exposure, correlated with insular white matter volume (Yamasue et al., 2007). This is the only MRI study in victims of acute NA exposure. On the other hand, MRI studies on Gulf War veterans involved in the destruction of the weapons depot in Khamisiyah have revealed structural changes in the brain

(Chao et al., 2011; Chao et al., 2014; Chao, Raymond, Leo, & Abadjian, 2017; Chao et al., 2010;

Chao & Zhang, 2018; Chao et al., 2015; Heaton et al., 2007). Although the dose of exposure is unknown, the United States Department of Defense created a plume model to estimate the dose of exposure in the veterans (Walpole & Rostker, 1997). The amount of exposure to personnel in the immediate area was determined to not cause overt symptoms (McCauley et al., 2001). The first MRI study performed T1-weighted imaging and found a dose-dependent relationship to

lower white matter volume and enlargement of ventricles (Heaton et al., 2007). Subsequent studies have found lower gray matter, white matter, and hippocampal volume (Chao et al., 2011;

Chao et al., 2014; Chao et al., 2010; Chao & Zhang, 2018), changes in white matter integrity

(Chao et al., 2015), and hippocampal microstructure (Chao & Zhang, 2018). The hippocampus

CA2, CA3, and dentate gyrus volume were specifically reduced (Chao et al., 2014; Chao et al.,

2017). Therefore, exposure to NA have been shown to cause structural changes in the human brain even at dosages that do not produce symptoms.

2.8 Summary

This project is a collaboration with the DRDC-SRC who were interested in gaining new insights in NA-related neurological damage. NAs, through inhibition of AChE, can induce seizure activity. NA-induced seizures are believed to be a major contributor to NA-related neurological damage. Pathophysiological mechanisms including excitotoxicity, oxidative stress, neuroinflammation, and BBB disruption have been implicated in NA-related neurological damage, however the involvement of hypoxia/ischemia remains uncertain. The first two aims of this thesis attempt to understand additional pathophysiological mechanisms that can exacerbate

NA-related injuries. The first aim measures brain oxygenation using fiber-optic oxygen sensing probes while the second aim measures changes in oxygen delivery using oxygen sensing probes with CASL MRI. In the third aim, the resulting neurological damage following soman was measured using quantitative T2 MRI.

The objective of this thesis is to improve our understanding of the physiological and structural changes in the brain following a sub-lethal dose of soman exposure. In utilizing oxygen sensors and MRI, I provide data on the changes in hemodynamics following soman-

induced seizures. Furthermore, I identify that quantitative T2 is effective in determining cerebral edema, which can be correlate the severity of neurodegeneration.

Chapter 3: Assessment of brain oxygenation following soman exposure in rats

Kevin Leea, Sara Bohnertb, Ying Wua, Cory Vairb, John Miklerb, G Campbell Teskeya, Jeff F.

Dunna a: Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary,

Alberta, Canada b: Defence Research and Development Canada- Suffield Research Centre, Department of

National Defence, Suffield, Alberta, Canada

This chapter is published as: Assessment of brain oxygenation following soman exposure in rats. We have made modifications to make the topic flow within the context of the thesis.

Author Contributions

J.F.D. oversaw the project. K.L. designed and performed all experiments. S.B. provided soman, carried out exposure, and advised on the project. Y.W. assisted in surgery and experiments. C.V. assisted in soman exposure. J.M. assisted in soman exposure. G.C.T. advised on the project. K.L. wrote the main manuscript and prepared all of the figures with oversight from J.F.D. All authors reviewed and edited the manuscript.

Abstract

Nerve agents (NAs) are potent organophosphorus (OP) compounds with applications in chemical warfare. OP compounds act by inhibiting acetylcholinesterase (AChE). Soman (O- pinacolyl methylphosphonofluoridate) is one of the most potent NAs. It is well known that small doses of NAs can be lethal, and that even non-lethal exposure leads to long-term mental

debilitation/ neurological damage. However, the neuropathology following exposure to sub- lethal nerve agents is not well understood.

In this study we examined changes in tissue oxygenation (pO2) in the cortex and hippocampus after a sub-lethal dose of soman [80-90 μg/kg; subcutaneous]. pO2 changes can provide information regarding oxygen delivery and utilization and may be indicative of disruption in cerebral blood flow and/or metabolism. Changes in oxygenation were measured with chronically implanted oxygen sensors in awake and freely moving rats. Measurements were taken before, during, and after soman-induced convulsive seizures.

Soman exposure resulted in an immediate increase in pO2 in the cortex, followed by an even greater increase that precedes the onset of soman-induced convulsive seizures. The rise in hippocampus pO2 was delayed relative to the cortex, although the general pattern of brain oxygenation between these two regions was similar. After convulsive seizures began, pO2 levels declined but usually remained hyperoxygenated. Following the decline in pO2, low frequency cycles of large amplitude changes were observed in both the cortex and hippocampus. This pattern is consistent with recurring seizures.

Measuring real-time changes in brain pO2 provides new information on the physiological status of the brain following soman exposure. These results highlight that the measurement of brain oxygenation could provide a sensitive marker of nerve agent exposure and serve as a biomarker for treatment studies.

3.1 Introduction

Chapter 2 outlines background information on NAs, justification on why we are interested in NA-induced seizures and factors that affect CBF. In this chapter, we are interested

in measuring brain oxygenation (pO2). Measurements of pO2 provide information about metabolic imbalance in the brain, which in turn can lead to neuronal damage. By directly measuring pO2, we can get an indication of the balance between oxygen delivery (cerebral blood flow or CBF) and cerebral metabolic rate of oxygen (CMRO2).

We have developed a method to measure the partial pressure of oxygen (pO2) in tissues using chronically implanted fiber-optic oxygen sensing probes in awake and freely moving rats

(Ortiz-Prado, Natah, Srinivasan, & Dunn, 2010). An advantage in using a fluorescence-based system to measure oxygenation is that the probe does not consume oxygen (Griffiths &

Robinson, 1999). The consumption of oxygen leads to an underestimation of pO2. The probes are also composed of biocompatible materials, which allows for chronic implantation. Therefore, pO2 can be measured without anaesthesia or other stresses (handling or restraint) that can potentially alter related physiological responses. Some disadvantages include the finite sampling time for the fluorescence-based system, where oxygenation can be measured for a total sampling time of 24 hours. Additionally, the chronic implantation limits the spatial resolution.

The objective of this study was to measure pO2 in the rat brain after soman-induced convulsive seizures. This paper is the first to measure pO2 changes before, during, and after soman-induced convulsive seizures in awake and freely moving rats. Brain oxygenation was directly measured in the cortex and hippocampus, which are areas selected for their sensitivity to

NA related neurological damage (Abdel-Rahman et al., 2002; Petras, 1994).

3.2 Materials and methods

3.2.1 Animals

Animal care protocols were approved by the University of Calgary Animal Care

Committee and meet the Canadian Council of Animal Care (CCAC) guidelines. Twelve male

Sprague-Dawley rats were obtained from Charles River Laboratories (Montréal, QC, Canada) weighing 200-350g. Rats were housed in the University of Calgary Animal Care Facility

(Calgary, AB, Canada) with a 12-hour light/dark cycle. Each cage housed two rats until probe implantation. Rats were handled for an additional 2-3 days to acclimate to human touch. Surgical implantation of probes was completed following acclimation. Following the probe implantation, rats were housed in individual cages with access to food and water ad libitum. Rats were closely monitored on a daily basis by staff for general health status.

3.2.2 pO2 Probe Implantation

Fiber-optic probes were implanted in the cortex and hippocampus via microsurgical methods. The fiber lengths were 4 mm for the hippocampus and 3mm for the cortex. Animals were anesthetized with isoflurane via inhalation prior to surgery and maintained on 70% N2, 30%

O2, and 2% isoflurane during the surgical procedure. Temperature and respiration rate were monitored and maintained over the course of implantation. Scalp was shaved and sterilized with iodine solution, a midline incision was made, and the skin was retracted laterally to expose the skull. Holes were drilled through the skull at stereotaxic coordinates relative to the bregma.

Cortex coordinates: +1 mm anterior/posterior, +1.5 mm medial/lateral, and -2 mm from the top of the skull. Hippocampus coordinates: -4 mm anterior/posterior, -3.5 mm medial/lateral, and -3 mm from the top of the skull. To further secure the probes, 3 additional holes were drilled and implanted with plastic screws. The probes and screws were secured with dental cement and molded into a head cap. The retracted skin was secured to the head cap with cyanoacrylate glue.

Rats were administered buprenorphine (0.1mg/kg; subcutaneous) post-surgery for analgesic

control. Rats were monitored closely during surgical recovery to ensure the head cap was secure and discomfort was minimized. Rats were given two doses of buprenorphine (0.1 mg/kg) per day for up to three days post-surgery and were monitored minimum of twice daily for general health status and any signs of pain or stress.

3.2.3 Drugs

Soman (CAS 96-64-0) was diluted in isopropyl alcohol (Sigma-Aldrich, Millwaukee, WI,

USA) and then sterile saline (0.9% NaCl, Baxter, Canada) to the maximum concentration required for the heaviest rat used on the day of exposure. A dose of 80-90 µg/kg was used in this study based on a pilot study that showed this dose consistently resulted in convulsive seizures.

This dose is 0.72-0.82xLD50 based on a published LD50 of 110 µg/kg subcutaneous (Shih et al.,

1990).

The oxime, HI-6 dimethanesulfonate (CAS 144252-71-1) was provided by the Defence

Research and Development Canada (DRDC) Suffield Research Centre. A dose of 125 mg/kg was prepared in 0.9% sterile saline. The same dose of HI-6 was used pre- and post soman injection.

Atropine Methyl Nitrate (AMN) was purchased from Sigma Aldrich (Milwaukee, WI,

USA). A dose of 20 mg/kg of AMN was prepared in 0.9% sterile saline. The same dose of AMN was used pre- and post soman injection.

3.2.4 Magnetic Resonance Imaging

Rats were imaged after probe implantation to confirm the relative probe location and check for intracranial bleeding 24 hours after surgery. Imaging was done with a 9.4T MRI and a

Bruker Avance console (Bruker Biospin GmbH, Rheinstetten, Germany). Rats were secured in

place with ear bars and ventilated with 70% N2, 30% O2, and 1.5-2.5% isoflurane. Body temperature (36.5 to 37°C and respiration rate (60-80 breaths/min) were monitored during imaging. Imaging was performed with a 20 mm surface coil using a rapid acquisition with relaxation enhancement (RARE) T2-weighted sequence: TR = 2500ms, TE = 36ms, flip angle =

180º, RARE factor = 8, averages = 1, matrix = 384 x 384, 9 slices, and thickness of 0.5mm. Total acquisition time was 20 minutes per rat.

3.2.5 Experimental design

Fiber-optic oxygen probes (Oxford Optronix, Oxford, UK) (Figure 3.1a) were used to measure cortical and hippocampal pO2. The fiber-optic oxygen sensing probes contain a fluorophore composed of platinum (II) meso-tetra (pentafluorophenyl) porphine. At the tip of an optical fiber, the fluorophore is embedded in a silicone rubber. The approximate diameter of the of the fiber is 250 µm. A short pulse of LED light is emitted at 520 nm, which excites the fluorophore. The excited fluorophore emits light at 650 nm. The quenching of the fluorophore is dependent on the oxygenation from a volume of tissue, approximately 500 μm3. The decay time for the fluorophore is mapped by three measurements and is inversely proportional to oxygenation. Therefore, if there is more oxygen present, the decay time is shorter.

Each rat was implanted with 2 probes, one in the cortex and one in the hippocampus

(implantation coordinates were standardized for all rats based on bregma). A structural MRI was obtained after surgery to confirm location of the pO2 probes and check for intracranial bleeding.

Rats were monitored for 5-7 days prior to initial baseline measurement to allow for healing around the implant.

During pO2 measurements, fiber-optic cables were attached to the implanted oxygen-

sensing probes, which protrude from the implant (Figure 3.1b). Animals were allowed to explore the measurement cage for 10 minutes before collection of pO2 data at 1 Hz. The rats were awake and freely moving in an empty cage over the course of the measurement period. Fiber-optic cables were supported on a lab stand to minimize tension on the head cap.

Baseline pO2 measurements were obtained for 15 minutes on 4 consecutive days (Figure

3.2). The first measurement day was ignored in case of a training effect. A 15-minute baseline was taken on the day of soman injection. During measurements, background stimuli (movement, noise) were kept to a consistent minimum. To reduce potential variability between rats, each rat was measured within 1 hour at the same time of day. In addition, the first 5 minutes of each baseline measurement were discarded in case there was a handling effect causing stress. In total, we evaluated three baseline measurements of 10 minutes for each rat, which were averaged to one data point per baseline measurement.

Pretreatments of HI-6 dimethanesulfonate and atropine methyl nitrate (AMN) (125 mg/kg and 20 mg/kg; intraperitoneal) were co-administered 20-30 minutes before soman exposure to increase survival of rats (Figure 3.2). HI-6 is an acetylcholinesterase reactivator (Jokanovic &

Stojiljkovic, 2006) and has been shown to reduce mortality without affecting seizure occurrence

(McDonough & Shih, 1993). AMN is an acetylcholine muscarinic receptor antagonist and reduces soman-induced peripheral symptoms. HI-6 and AMN do not readily cross the blood- brain barrier and therefore do not interfere with the central effect of soman (Shih et al., 1991).

Pretreatment pO2 values were measured 20 to 30 minutes after pretreatment injection until time of soman administration.

For soman injection, rats were temporarily disconnected from the Oxylite and anesthetized with 5% isoflurane for approximately 3-5 minutes. Anesthetized rats were moved

into the fume hood and injected with soman (80-90 μg/kg; subcutaneously). The injection site was immediately scrubbed with Reactive Skin Decontamination Lotion (RSDL). Anesthesia was discontinued directly after soman injection and rats were reconnected to the Oxylite and pO2 measurements and video recordings were taken.

Short-term measurements were taken directly after soman injection for 30-60 minutes

(Figure 3.2). The first set of rats we measured was for 60 minutes. In all of these, the peak oxygenation occurred before 30 minutes. In order to increase our data collection throughput and reduce stress, we subsequently reduced the initial post soman recording to 30 minutes. Following short-term measurement, rats were transported into an empty cage to be continuously monitored and rated based on physical symptoms overnight (Table 3.1). To minimize mortality rate, additional treatment of AMN (20 mg/kg; i.p) was given every 20-30 minutes for up to three doses. Treatments were provided to minimize muscarinic effects of soman exposure.

A video camera was mounted on a stand to monitor behavioral seizure activity in the rats.

Recordings began immediately following soman-injection and were stopped when pO2 measurements were complete. The video recording was later analyzed to confirm the onset of soman-induced convulsive seizures in relation to pO2 measurements. Observations of convulsions have been used to confirm the occurrence of seizures (Racine, 1972).

A final long-term measurement was taken for 15 minutes, 10-24 hours after soman injection and rats were sacrificed immediately after (Figure 3.2). To preserve brain tissue, the rats were perfused and fixed.

Figure 3.1: Implantation of pO2 probes in the rat cortex and hippocampus. a) Example probe. The red circle indicates the location of the fluorophore. b) Bilateral implantation of pO2 probes in the cortex and hippocampus with the measurement leads attached.

Figure 3.2: Time course of the study depicting the treatment timing and measurement duration.

Table 3.1: Rating system to assess the severity of soman related symptoms. Suffield Rating Scale Symptoms Rating 1 Normal

Rating 2 One of the following signs: fasciculations, tremors, lacrimation, mouth movement, salivation, vocalizations, abnormal mobility, or abnormal responsiveness Rating 3 2 or more of the above signs

Rating 4 Any of the above signs and partial paralysis (fore OR hind limbs affected)

Rating 5 Any of the above signs, full body paralysis (unable to right hind or front limbs), severely labored breathing, and/or seizures/convulsions

3.2.6 Histology

Histology was performed to determine exact probe location as MR images only provide a relative position. Rats were euthanized with euthanyl (200 mg/kg i.p) for transcardial perfusion with 100 ml of 1X PBS, then 100 ml of 4% paraformaldehyde (4% PFA). Brains were carefully excised and fixed overnight in 4% PFA for up to 48 hours. 4% PFA solution was replaced with

30% sucrose solution and remained in sucrose solution until sectioning. Tissue was embedded in optimal cutting temperature (OCT) compound and sectioned at 20 μm. Sections were stained with hematoxylin and eosin (H&E) to assess probe location.

3.2.7 Data Analysis

Video recording of the pO2 measurement after soman injection was reviewed for a rating

5 on the symptom severity (Table 3.1) to estimate the time point of onset of soman-induced convulsive seizures.

Heterogeneity in baseline oxygenation was expected between rats. Mean baseline and standard deviation was calculated using approximately 30-minutes of baseline pO2 recordings on

3 consecutive days prior to pretreatment and soman injection. Any value above or below two standard deviations from the average baseline was defined as being significantly different from baseline.

A comparison between different time points (described in section 3.2.5) was performed by averaging the pO2 at each time point. All statistical analysis was performed using IBM SPSS

Statistics. An F-test was performed for normal variance. If the F-test was significant, a non- parametric test (Friedman) was used. For the cortex pO2, a Friedman test was used to compare the baseline, pretreatment, short-term, and long-term followed by a Wilcoxon rank sum post-hoc

test. The hippocampal pO2 was analyzed using a one-way repeated measure analysis of variance

(ANOVA) with a Tukey post-hoc test to test for between group differences. p-values < 0.05 were considered statistically significant.

The baseline pO2 between the cortex and hippocampus was compared for each rat. In addition, the timing to peak oxygenation was compared between the cortex and hippocampus. A paired t-test was performed where a p-value < 0.05 was considered statistically significant.

3.3 Results

3.3.1 Behavioral Effects of Soman

Soman induced convulsive seizures were assessed based on behavior. Within 5 minutes after soman exposure, rats exhibited a symptom rating of 2 (Table 3.1; facial movement and salivation). Ten minutes following exposure, all rats exhibited signs rating of 5 (Table 3.1; convulsive seizures). After the convulsive seizures had terminated, rats exhibited a symptom rating of 4. Most had splayed hind limbs throughout the short-term measurement (within 30 to 60 minutes post-soman injection). Even at the time of euthanasia (after 10 to 24 hours post-soman injection), most had rhythmic head movement. Three unexpected deaths occurred following soman exposure, one before the 1 hour and two before the 24 hour marks, most likely from respiratory difficulty due to reduced respiration and excessive secretions. However, all available data from these rats were included in the pO2 analysis.

3.3.2 Imaging Probe Location

MRI showed that all probes were located in the region of interest (cortex and hippocampus). Representative sections of the cortex and hippocampus are shown in Figure 3.3a

and b, respectively. Histology confirms that the probes were located in the cortex and hippocampus (Figure 3.3c and d).

Figure 3.3: Images showing the locations of the pO2 probe tips in the brain. Example of a RARE T2-weighted image showing the relative location of the tips (white circles) in the a) cortex and b) hippocampus. H&E stained sections showing the exact location of the probe tip (black circles) in the c) cortex and d) hippocampus.

3.3.3 Cortex pO2 Measurements

During baseline measurements in the cortex (n = 10), the absolute baseline pO2 remained relatively stable overtime for each rat (Figure 3.4a-j). Variation in the average baseline pO2 between rats ranged from 25.9 ± 4.2 mmHg to 45.5 ± 6.1 mmHg (mean ± SD) (Table 3.2) as expected (T. W. Johnson et al., 2016; Ortiz-Prado et al., 2010; Schilte et al., 2015). Mean cortical pO2 from 10 rats was 32.4 ± 6.3 mmHg.

Absolute cortical pO2 during the 10 minutes of pretreatment is shown in Figure 3.4a-j

(yellow). During most of the pretreatment, the absolute cortical pO2 was within two standard deviations from the baseline in all rats (Figure 3.4a-j).

Shortly after soman injection, there was a large increase in absolute cortical pO2 to above two standard deviations from the mean baseline in every rat. The largest increase was 43.8 mmHg (Figure 3.4c, Table 3.2). Upon seizure onset (based on observed convulsions), pO2 began to decline (arrows, Figure 3.4a-j). 40-60 minutes post soman injection; pO2 generally remained elevated over baseline (data not shown). Cortical pO2 in two rats returned to near baseline values, within two standard deviations of the mean baseline (Figure 3.4e and g) within 40 minutes. Two rats died unexpectedly, and values are shown in Figure 3.4d and f. Cyclical large amplitude changes in cortical pO2 could be observed in every rat.

Long-term cortical pO2 measurements (10-24 hours post-soman injection) were variable between rats (n = 6/10). Due to the severity of symptoms, two rats were measured at 10 hours and immediately euthanized. Cortical pO2 10 hours post soman injection (n = 2/10) did not show any significant changes from the mean baseline (Figure 3.4a and b). At 24 hours (n = 4/10), two of the four rats had significantly elevated pO2 with a decreasing trend (Figure 3.4g and h), while

the other two rats did not show a significant difference between baseline and 10 hours post- soman injection pO2 values (Figure 3.4c and j).

Figure 3.5a shows the change in the cortical pO2 for each time point. When compared to the baseline (n = 10), the short-term (n = 10) exhibited higher pO2 in the cortex (p = 0.005). No significance was found between the baseline and pretreatment (p = 0.285). Furthermore, the long-term (n = 6) showed an increase in cortical pO2 values 10-24 hours post-soman injection compared to the baseline, but this was not statistically significant (p = 0.075).

Although there are two outliers in the baseline group (Figure 3.5a), pO2 values for every rat followed the same general trend (Figure 3.5b): Cortical pO2 remained relatively stable between baseline and pretreatment, followed by a large increase in the short-term assessment.

Long-term assessment had more variability as some rats had elevated pO2, while others returned to or near baseline values.

Figure 3.4: The effect of soman injection on cortical pO2. Plots of pO2 data collected at 1 Hz from the cortex for 10 rats (a-j). Rats were awake and freely moving during recording. The dotted black lines indicate ±2xSD of the mean baseline. Time 0 for short-term starts within 1 minute of soman injection. The other plots are aligned to 0 for ease of comparison. Arrows indicate the onset of soman-induced convulsive seizures. Short-term (within 40 minutes). Long- term (10 minutes of measurement between 10-12 hours for a,b and 22-24 hours post injection for c-j).

Table 3.2: Baseline and peak pO2 in the cortex and hippocampus after soman injection. Each line represents a rat (n = 10). (Mean ± SD, mmHg) Cortex Hippocampus Δ in Baselines Baseline Short Term Peak- Baseline Short Term Peak- Cortex- Peak Baseline Peak Baseline hippocampus 40.9±3.4 77.5±4.2 37 20.2±6.2 58.5±4.0 38 21

33.1±4.7 60.2±2.7 27 17.9±3.4 67.0±3.2 49 15

30.4±4.0 74.2±7.7 44 13.6±2.3 47.6±1.6 34 17

33.3±2.9 63.5±4.8 30 15.9±3.1 50.4±6.8 35 18

45.5±6.1 74.8±3.4 29 34.1±3.1 58.8±5.0 25 11

31.7±3.0 63.9±3.8 32 22.6±3.5 53.1±5.1 31 9

28.7±2.3 60.7±0.9 32 21.1±2.3 46.9±1.2 26 8

25.8±4.2 62.2±0.4 36 16.9±5.0 47.8±0.3 31 9

28.8±2.2 62.4±0.7 34 25.4±2.7 54.7±0.6 29 3

26.0±3.6 65.8±2.4 40 24.6±2.3 54.5±0.8 30 1 Two animals were excluded from the hippocampus from cortical probes not working. Short-term peak data are calculated from the peak pO2 pre-seizure ± 30s Baseline is calculated from three consecutive days including on the day of soman injection for a total of 30 minutes.

a) ** b) 80 80

70 70

60 60

50 50

40 40 (mmHg) (mmHg) 2 2 pO pO 30 30

20 20

10 10

0 0 Baseline Pretreatment Short -Term Peak Long- Term Baseline Pretreatment Short- Term Peak Long- Term

Figure 3.5: Combined cortical pO2 data. a) grouped data showing the baseline, pretreatment, short-term peak and long-term data. Baseline (n = 10), pretreatment (n = 10) and long-term (n = 6) values were plotted using a 10 minutes mean. Short-term peak (n = 10) was the mean including 30s before and after the peak pO2 measurement that occurs near the onset of seizure. The black bars show the maximum and minimum. Middle black line indicates the median. Plus signs are outliers. **p ≤ 0.01 (Friedman test with Wilcoxon signed-rank test) b) Cortical oxygenation trend after each treatment. Each individual shape and line indicate one rat.

3.3.4 Hippocampal pO2 Measurements

Within each rat, the absolute baseline pO2 remains relatively stable over time in the hippocampus (n = 12) (Figure 3.6a-l). As with the cortex, variation between rats in baseline pO2 ranged from 13.6 ± 2.3 mmHg to 34.1 ± 3.1 mmHg (mean ± SD) (Table 3.2). The combined average pO2 in 12 rats was 21.1 ± 5.5 mmHg.

Measurements of hippocampal pO2 had small variation within each rat (n = 12) and remained relatively stable (Figure 3.6a-l). Most rats had pO2 values that remained close to the baseline and within two standard deviations of the mean baseline. However, two had elevated pretreatment pO2 values and at times above two standard deviations of the average baseline

(Figure 3.6d and l). The majority of pO2, measured after pretreatment, did not show significant change compared to the mean baseline, as the pretreatment pO2 remains within two standard deviations of the mean baseline. Between rats, there is some variability in the pretreatment pO2 values, ranging from 16.0 ± 4.4 mmHg to 30.3 ± 2.6 mmHg (Table 3.2).

Immediately following soman injection, there is an elevation in the hippocampal pO2 above two standard deviations from the mean baseline value in most rats (Figure 3.6a-l). The largest increase in pO2 was seen in Figure 3.6b, and with 49.1 mmHg (Table 3.2). After the onset of convulsive seizures, there was a delayed decrease in pO2 in some rats (n = 4/12). However, the majority of rats’ pO2 continues to increase after seizure onset followed by a dip in pO2 (n =

8/12). During the short-term (30-60 minutes post soman injection), we observed large variation in hippocampal pO2 measurement (Figure 3.6a-l). Shortly following the decrease, there was an increase in every rat above two standard deviations until the end of measurement except for one rat that died during the experiment (Figure 3.6f). In every rat, we observed cyclical large amplitude changes in pO2 within the hippocampus.

Hippocampal pO2 measurement showed variation between rats during the long-term assessment. At 10 hours (n = 2/12) after soman injection, one rat had significantly elevated hippocampal pO2 above two standard deviations of the mean baseline (Figure 3.6a), while another had long-term pO2 near the baseline (Figure 3.6b). At 24 hours (n = 5/12), four had elevated long-term hippocampal pO2 above +2xSD (Figure 3.6c, g, h, and l) and one had pO2 near the baseline level (Figure 3.6j).

Hippocampal oxygenation shows a similar trend as the cortex. No significant difference was found between baseline and pretreatment pO2 values (p = 0.985). There was a large increase in the short-term measurement (Figure 3.7a). When baseline was compared to peak oxygenation during short-term assessment, short-term measurements were significantly elevated (p < 0.001).

The long-term assessment (10 to 24 hours) had significantly elevated hippocampal pO2 compared to the baseline (p = 0.005).

Despite outliers in the baseline and long-term (n = 3), similar trends could be observed in every rat (Figure 3.7b): Each rat had similar baseline and pretreatment pO2, followed by an increase during the short-term measurement. A decreasing trend can be observed in the long- term measurements, which were still elevated compared to the baseline.

Figure 3.6: The effect of soman injection on hippocampal pO2. Plots of pO2 data collected at 1 Hz from the hippocampus for 12 rats (a-l). Rats were awake and freely moving during recording. The dotted black lines indicate ±2xSD of the mean baseline. Time 0 for short-term starts within 1 minute of soman injection. The other plots are aligned to 0 for ease of comparison. Arrows indicate the onset of soman-induced convulsive seizures. Short-term (within 40 minutes). Long- term (10 minutes of measurement between 10-12 hours for a,b and 22-24 hours post injection for c-l).

a) b) 80 80 *** 70 *** 70

60 60

50 50

40 40 (mmHg) (mmHg) 2 2

pO 30 pO 30

20 20

10 10

0 0 Baseline Pretreatment Short -Term Peak Long -Term Baseline Pretreatment Short- Term Peak Long- Term

Figure 3.7: Combined hippocampal pO2 data a) grouped data showing the baseline, pretreatment, short-term peak and long-term data. Baseline (n = 12), pretreatment (n = 12) and long-term (n = 7) values were calculated from a 10-minute mean. Short-term peak (n = 12) was the mean including 30s before and after the peak pO2 measurement that occurs near the onset of seizure. The black bars show the maximum and minimum. Middle black lines indicate the median. Plus signs are outliers. ***p ≤ 0.001 (ANOVA with Tukey-b post-hoc) b) Hippocampal oxygenation trend after each treatment. Each individual shape and line indicate one rat.

3.3.5 Comparison between Cortex and Hippocampus

The time to peak pO2 was compared between the cortex and the hippocampus. During baseline measurements, the cortex had a significantly higher pO2 than the hippocampus (p <

0.001) (Table 3.2). The largest difference in pO2 between the cortex and hippocampus baseline was 21 mmHg (Table 3.2). The peak pO2 in the cortex occurred at a similar time to that of seizure onset (based on using behaviour as a marker for seizure onset). The peak pO2 in the hippocampus was significantly later (n = 8/10) with the timings being 5.8 ± 1.5 min and 8.2 ± 3 min (mean ± SD, p < 0.01) for the cortex and hippocampus, respectively.

3.4 Discussion

Changes in cortical and hippocampal oxygenation after a convulsive dose of soman were measured using chronically implanted fiber optic oxygen probes. We used a novel method to measure oxygenation in vivo without the need for anesthesia and restraints (Ortiz-Prado et al.,

2010). Using this method, we demonstrated that 1) pO2 increases in the cortex and the hippocampus shortly after injection of a convulsive dose of soman, until a maximum value was recorded prior to seizure onset; 2) after seizure onset, pO2 declined but usually remained elevated above baseline for at least 60 minutes post soman exposure; 3) low frequency cycles of high amplitude changes in both cortical and hippocampal pO2 were observed; and 4) pO2 remained elevated after 10 to 24 hours (long term) in the hippocampus but returned to baseline in the cortex.

3.4.1 Baseline pO2 measurements

The baseline pO2 measurements were variable as exemplified by the fact that the cortical

pO2 between rats ranged from 26 to 46 mmHg (Table 3.2). This was the first time that both hippocampal and cortical pO2 were measured simultaneously in the same rat. Interestingly, the cortex pO2 (32.4 ± 6.3 mmHg) was higher than the hippocampus (21.23 ± 6 mmHg). The values were within ranges reported previously for the cortex (30.2 ± 3.3 mmHg) (Ortiz-Prado et al.,

2010) and hippocampus (18 to 30 mmHg) (Farrell et al., 2016). We expect some level of variability between rats as pO2 values can change depending on conditions including stress level

(Paisansathan et al., 2007), temperature (Gupta, Al-Rawi, Hutchinson, & Kirkpatrick, 2002), and neuronal activity (Lindauer, Gethmann, Kuhl, Kohl-Bareis, & Dirnagl, 2003). Variation between subjects has been seen in other studies that measured brain pO2 (T. W. Johnson et al., 2016;

Ortiz-Prado et al., 2010; Schilte et al., 2015).

3.4.2 From soman exposure to seizure onset

Our results show that soman injection causes hyperoxygenation in the cortex and the hippocampus (Table 3.2). Soman inhibits AChE, which will cause an accumulation of ACh in the synapse, leading to sustained firing of cholinergic neurons and induce a state of hyperexcitability. Hyperexcited neurons have an increased CMRO2 (Sheth et al., 2004). One would expect that if there is an increase in CMRO2 there would also be in increase in CBF

(Buxton et al., 1998) and pO2 (Leniger-Follert, 1985; Offenhauser, Thomsen, Caesar, &

Lauritzen, 2005). Thus, this initial increase in pO2 may reflect an increase in CMRO2 causes by increased neuronal excitability.

There is an additional increase in pO2 in the cortex (and often in the hippocampus), associated with the onset of soman related symptoms. This increase in pO2 would be expected, as

AChE becomes inhibited and more neurons are stimulated to a hyperexcitable state. As

cholinergic neurons are stimulated, excitatory projection neurons such as glutamatergic neurons are recruited, CMRO2 and CBF increase even more and pO2 rises.

Although it is hypothetical, it may be interesting to keep in mind that increased metabolism can increase oxidative stress. This could cause membrane and mitochondrial damage

(Baille et al., 2005). Oxidative stress has also been implicated in stimulating vasodilation through the effect of reactive oxygen and nitrogen species (Sobey, Heistad, & Faraci, 1997). The vasodilatory effects will lead to an increase in CBF and pO2, which may attribute to the secondary increase that is observed.

3.4.3 Onset of Seizures May Reduce Oxygenation

The onset of soman-induced convulsive seizures correlates with a decrease in oxygenation in the cortex (although the pO2 was still higher than “pre-soman”). We reason above that a hyperexcitable state would result in an elevated pO2. However, seizures arise when neurons are in both a state of hyperexcitability and hypersynchrony (Fisher et al., 2005). This condition is highly metabolically demanding (Duffy, Howse, & Plum, 1975). We know that there is an increase in CBF (Goldman, Berman, Hazlett, & Murphy, 1993; Shih & Scremin, 1992) and metabolism (McDonough, Hackley, Cross, Samson, & Nelson, 1983; Shih & Scremin, 1992) after soman-induced convulsive seizures, but if the demand is too high for supply then we would expect a decline in pO2. Such a decline with seizure has been termed the “epileptic dip” (Bahar,

Suh, Zhao, & Schwartz, 2006; Suh, Bahar, Mehta, & Schwartz, 2005). Similar decreases in cortical pO2 at or near onset of seizures were reported in epilepsy patients, where an increase in cerebral oxygenation has preceded seizures (Moseley, Britton, Nelson, Lee, & So, 2012; Seyal,

2014; Slone, Westwood, Dhaliwal, Federico, & Dunn, 2012; Zhao et al., 2007).

There may be more factors involved. There is evidence for abnormal vascular regulation in seizures (Farrell et al., 2016; Leal-Campanario et al., 2017; Zhao et al., 2011). Near the onset of seizures, vasoconstriction (Leal-Campanario et al., 2017; Zhao et al., 2011) would reduce

CBF and lead to a decrease in pO2 if CMRO2 were to remain high.

Vasoconstriction can be long lasting. In a study using both electrically-induced and convulsant-induced seizures, both hypoxia and hypoperfusion were recorded following the termination of seizures (Farrell et al., 2016). In our study, we did not observe hypoxia following seizures. Except for the rats that unexpectedly died during pO2 recording, pO2 in the cortex and hippocampus never dropped below the severe hypoxic threshold as was reported in the previous study (where pO2 regularly declined to <10 mmHg) (Farrell et al., 2016). This is likely due to a difference in the method of inducing seizures. Brief electrical stimulation in a non-epileptic animal results in a relatively short duration seizure and a rapid return to the non-epileptic state.

Whereas following soman administration, the compound will continue to keep the brain in a hyperexcitable state and cause brain damage. We expect similar results to the chemically- induced seizure experiment once soman has been hydrolyzed and rats exhibit spontaneous recurrent seizures (de Araujo Furtado et al., 2010).

The decrease in hippocampal pO2 after seizure onset was not as evident compared to the cortex. The secondary increase in the hippocampus did not reflect the time point when early soman related symptoms appeared. The temporal delay between the cortex and hippocampus pO2 increase may be from a difference in neuronal innervation affecting vascular response. Areas surrounding a seizure focus showed a difference in vascular regulation (vasoconstriction and vasodilation) and metabolism (Zhao et al., 2011) suggests pO2 changes depending on the onset site. The hippocampus receives projections from the medial septum and the entorhinal cortex.

The medial septum is a speculated site for the generation of soman-induced convulsive seizures.

The entorhinal cortex relays seizures that have been evoked from the area tempestas (Halonen,

Tortorella, Zrebeet, & Gale, 1994), another speculated soman-induced seizure onset site.

3.4.4 Oscillating Changes in Oxygenation in the first hour

Oscillating changes in oxygenation after soman-induced convulsive seizures are similar to a status epilepticus model (Kreisman, Sick, & Rosenthal, 1983). In the cortex, following the initial gradual decline in pO2 following the onset of seizures, large amplitude, low frequency cycles began to appear, indicating a non-steady state. The oscillating changes in pO2 may reflect ongoing changes in vascular regulation during status epilepticus. When seizures stop momentarily, vasodilation allows reperfusion of the tissue and increases pO2. At the onset of another seizure, vasoconstriction restricts blood flow.

In the hippocampus, the oscillating changes appear before the onset of seizures and become more distinct following onset. Cycling between vasoconstriction and vasodilation may be similar to the cortex. The difference in the oscillating pO2 may be due to a regional difference in neuronal activity, changing the neurovascular response between the cortex and hippocampus

(Shih & Scremin, 1992). There was less increase in CBF relative to the increase in metabolism in the hippocampus compared to the cortex after soman-induced convulsive seizures (Shih &

Scremin, 1992). The difference in the proportional uncoupling between the cortex and hippocampus may explain why there is no direct relationship in the oscillating changes in pO2.

3.4.5 Potential link between oxygenation and pathology

Measurements at 10-24 hours following soman exposure showed significantly elevated

pO2 in the hippocampus but not in the cortex. Elevated pO2 indicates there may be changes in oxygen utilization likely due to neurodegeneration following soman-induced seizures. In rats that have been exposed to higher doses of soman (105-154 μg/kg; sc), neurodegeneration was histologically detected using Fluoro-Jade B (Apland et al., 2010; RamaRao, Afley, Acharya, &

Bhattacharya, 2014) and H&E (Shih, Duniho, & McDonough, 2003; Tryphonas & Clement,

1995) in the hippocampus. Although most studies use a higher dose than we have used, rats exposed to a similar dose (80 μg/kg; sc) showed neurodegeneration as early as 45 minutes after convulsive seizures in the hippocampus, amygdala, and piriform cortex (Myhrer, Andersen,

Nguyen, & Aas, 2005). Studies have shown seizures lasting more than 40 minutes are an important factor in the development of neurodegeneration (Baille et al., 2005; Guo et al., 2015;

Lallement et al., 1993; Myhrer et al., 2005). Histological damage in the hippocampus has also been observed in mice (172 μg/kg; sc) (Baille et al., 2005) and guinea pigs (26.6 μg/kg; sc)

(Gullapalli et al., 2010) following soman-induced convulsive seizures. The sustained elevation of pO2 over the 24 hours post exposure may reflect a condition where oxygen utilization has been greatly reduced due to cell death in the hippocampus. In the cortex, the return to control pO2 suggests that cell damage may not be as severe. This is consistent with previous reports arguing that the neocortex is less sensitive than the hippocampus to soman-related damage (Lemercier et al., 1983; Rossetti et al., 2012).

3.4.6 Future Directions

In the future, it will be important to link the increase in pO2 to soman-related cell death.

This linkage would support the use of oxygen measurements during the acute phase post exposure as a biomarker of future neuropathological outcome. It would also be useful to study

the mechanism behind the changes in oxygenation by correlating with changes EEG and CBF.

This will better allow us to correlate neuronal activity and cerebral vascular regulation with pO2 data. Furthermore, pO2 measurements may be useful in treatment studies to provide a sensitive biomarker of whether metabolism and blood flow have been protected. The similarity of changes in pO2 with that observed in animal models during status epilepticus supports further work studying anti-seizure treatment.

3.5 Conclusion

Measurements of brain oxygenation provide new information on changes in the physiological status of the brain over time following soman exposure. The temporal pO2 profile support evidence that soman-induced seizures result in irregular vascular reactivity similar to that in other seizure models. Measurements of brain oxygenation could provide a sensitive marker of exposure and could be used as a biomarker for treatment studies.

Chapter 4 Cerebral blood flow and oxygenation in rat brain after soman exposure

Kevin Lee1, Sara Bohnert2, Cory Vair2, John Mikler2, Jeff F. Dunn1

1: Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary,

Alberta, Canada

2: Defence Research and Development Canada- Suffield Research Centre, Department of

National Defence, Alberta, Canada

This chapter has been submitted for publication in Toxicological Letters- Some additional text and data were added to show the complete data set we collected as well as to make the topic flow within the context of the thesis.

Author Contributions

J.F.D. oversaw the project. K.L. designed and performed all experiments. S.B. provided soman, carried out exposure, and advised on the project. C.V. assisted in soman exposure. J.M. assisted in soman exposure. K.L. wrote the main manuscript and prepared all of the figures with oversight from J.F.D. All authors reviewed and edited the manuscript.

Abstract

Nerve agent exposure can cause debilitating neurological damage even with treatment.

Currently accepted treatments involve attenuating the cholinergic crisis and seizure onset but do not focus directly on neuroprotection. Hence, there is a need for improved treatments to reduce neurological deficits. It is important to understand the pathophysiology of nerve agent mediated

injury in order to identify effective treatment targets. Nerve agent-induced seizures are believed to be the main contributor to the neuropathology. Recently seizures have been shown to cause vascular changes that may actually attenuate neurological damage. This study evaluated the effect of soman-induced convulsive seizures on the relationship between brain oxygen consumption and supply.

To simultaneously assess changes in oxygenation and perfusion, rats were implanted with permanently fixed fiber-optic tissue oxygen sensing probes in the motor cortex and imaged with continuous arterial spin labelling MRI to measure cerebral blood flow. Baseline tissue oxygen tension (pO2) and cerebral blood flow (CBF) were measured in isoflurane anaesthetized rats at least one day prior to soman or saline exposure. Rats were pretreated with HI-6 dimethansulfonate and atropine methyl nitrate (125 mg/kg and 20 mg/kg; intraperitoneal) followed by a convulsive dose of soman (90 μg/kg; subcutaneous) or equal volume of saline.

Three additional treatments of HI-6/AMN were administered to improve survival. At 1.5-hours after exposure, pO2 and cerebral blood flow measurements were conducted.

There was a significant decrease in CBF 1.5-hours following soman exposure but no change in pO2 was found. When we correlated pO2 and CBF, for a given pO2, there was lower

CBF following soman exposure. This may indicate metabolism is inhibited, possibly because of oxidative stress, therefore reducing oxygen demand. Although this contradicts some previous studies which showed an increase in cerebral metabolism, the decreases may have been due to administration of isoflurane for anesthesia. However, as pO2 did not decline this supports that isoflurane may be neuroprotective. Furthermore, prolonged hypoperfusion was found 18-24 hours after soman exposure in the piriform network. Damage to the neurovascular unit may inhibit reperfusion. In conclusion, the results presented here show hypoperfusion of brain areas

following soman exposure and this decrease in perfusion may contribute to soman-related neuropathology.

4.1 Introduction

Chapter 2 outlines background information NAs, neuropathophysiology associated with

NAs, and regulation of CBF. In this chapter, impairment of oxygen delivery was investigated.

Vascular pathology has been found in seizures which was previously believed to be mainly a network disorder. Hypoxia and vasoconstriction lasting as long as 40 minutes (Farrell et al.,

2016) and microhypoxia (Leal-Campanario et al., 2017) have been observed in animal models of seizures which have been implicated in seizure pathophysiology. We also found abnormal changes in brain oxygenation where soman-induced seizures correlated with oscillating tissue oxygen tension (pO2) (Lee, Bohnert, Wu, et al., 2018). Since tissue oxygenation is a sensitive marker for physiological changes, we investigated the relationship between cerebral blood flow

(CBF) and tissue pO2 (oxygenation or pO2).

The objective of the study was to use continuous arterial spin labelling (CASL) MRI and fiber-optic oxygen sensing probes to simultaneously measure the CBF and pO2 before, and 1.5- hours after the initiation of soman-induced convulsive seizures. This multi-modal study combines a unique tissue pO2 measurement system with 9.4T MRI to study physiological changes in the brain after soman exposure. We hypothesize that soman-induced convulsive seizures will cause a disruption in cerebral metabolism and blood flow relationship.

4.2 Methods

4.2.1 Animals

All research was conducted in adherence to the animal care protocols that were approved by the University of Calgary animal care committee and meet the Canadian Council of Animal

Care guidelines.

Male Sprague-Dawley rats (n = 37), weighing 200-270 g, were acquired from Charles

River Laboratories (Montréal, QC, Canada). Upon arrival, the rats were housed in pairs at the

University of Calgary Animal Care Facility (Calgary, AB, Canada). Environmental conditions were a 12-hour light/dark cycle with access to food and water ad libitum.

4.2.2 Implantation of oxygen sensor and measurement

Tissue oxygen tension measurements were acquired using a 7 mm fiber-optic oxygen sensing probes with a diameter of 250 mm (Oxford Optronix, United Kingdom) implanted in the motor cortex (Ortiz-Prado et al., 2010). The implanted fiber-optic oxygen sensing probe was connected to a fiber-optic cable and measurements were conducted using Oxylite Pro (Oxford

Optronix, United Kingdom). A short pulse of LED light at 525 nm excites an embedded fluorophore, which emits at 650 nm with quenching corresponding to the surrounding oxygen.

For microsurgical implantation the rats were anaesthetized with an inhalation mixture of

1.5-2.5% isoflurane, 70% nitrogen, and 30% oxygen. Temperature and respiration rate were monitored and maintained throughout the procedure. The surgical site was shaved and sterilized using betadine and 70% ethanol. An incision was made midline and the skin retracted to expose the skull. pO2 probes were implanted in stereotaxic coordinates relative to the bregma through holes created using a dremel with a dental drill bit (C. Watson & Paxinos, 1986). Motor cortex

coordinates were +1.5 anterior posterior, +1.5 medial lateral, and -2 mm from the top of the skull. Three plastic screws were implanted for support. Dental cement was used to secure the probes and screws to form a head cap. The scalp was sealed to the head cap with cyanoacrylate glue.

Post-surgery the rats were administered buprenorphine daily (0.1 mg/kg; intraperitoneal) for analgesic control. During surgical recovery to ensure the head cap remained secure and discomfort was minimized, the rats were monitored on a daily basis. Additional analgesic control was provided with two doses of buprenorphine (0.1 mg/kg) per day for up to three days.

pO2 measurements were acquired simultaneously in the MRI one week after surgery.

Real-time measurements were taken for 8 minutes at 1 Hz during the CASL MRI scan before and 1.5-hours after soman or saline control exposure.

4.2.3 Soman and Treatments

Atropine methyl nitrate (AMN) (CAS 52-88-0) was purchased from Sigma Aldrich

(Milwaukee, WI, USA). HI-6 dimethanesulfonate (HI-6) (CAS 144252-71-1) was provided by the Defence Research and Development Canada- Suffield Research Centre (DRDC-SRC).

(±) Soman (O-pinacolyl methylphosphonofluoridate; CAS 96-64-0) is a schedule 1 substance according to the Chemical Weapons Convention and not commercially available. In order to conduct the study, soman was provided by the DRDC-SRC as allowed under the

Chemical Weapons Convention. Soman was diluted in isopropyl alcohol (Sigma-Aldrich,

Millwaukee, WI, USA) and then diluted further in sterile saline (0.9% NaCl, Baxter, Canada).

4.2.4 Symptoms and Seizure Evaluation

Rats were monitored and rated every 10 minutes following soman injection until being anesthetized for imaging. The soman-related symptoms were evaluated using the Suffield Rating

Scale (Lee, Bohnert, Wu, et al., 2018). The seizures were behaviourally monitored and rated based on the Racine scale (Racine, 1972).

4.2.5 Magnetic Resonance Imaging

MRI was performed using a 9.4T Bruker Avance console (Bruker Biospin GmbH,

Rheinstetten, Germany) with a 35 mm quadrature volume coil. During imaging, rats were anaesthetized with 1-2% isoflurane in 70% nitrogen, and 30% oxygen. Normal physiological temperature and respiration rate was maintained at 36.5 °C and 60 breaths per minute (Small

Animal Instruments Inc, New York, USA).

For single-slice perfusion imaging, continuous arterial spin labeling with a half-fourier acquisition single-shot turbo spin echo sequence (CASL-HASTE) was used. To account for magnetization transfer, four images were acquired: two control and two tagged images (Figure

4.1a) (Pekar et al., 1996). Parameters were TR= 3000 ms, TE = 2.66 ms, averages = 16, RARE factor = 32, matrix size = 128 x 128, voxel size = 0.23 x 0.23 x 1 mm (Acquisition time = 8 min).

At the same location, a T1 map was acquired using a rapid acquisition with refocused echoes variable repetition time (RARE-VTR) sequence (Figure 4.1b). Parameters were TR = 100, 500,

1000, 3000, 7500 ms, TE = 10 ms, matrix size = 128 x 128, voxel size = 0.23 x 0.23 x 1 mm

(Acquisition time = 6 min). Total acquisition time for each rat was 14 minutes.

An in-house MATLAB script was used to generate a perfusion map from the four images and T1 map (Figure 4.1c). A voxel-by-voxel approach was used to calculate the CBF with the formula (Zhang, Williams, & Koretsky, 1993):

1 / &- − &. ,%- = , 2 3 . ' 21 &-

Where CBF is calculated in mL/100 g/min, Mc is the sum of intensity of the control images, ML is the sum of intensity after arterial inversion. We assumed the spin labelling efficiency (α) =

’ 0.75 and blood-brain partition coefficient for water (λ) = 0.9 mL/g. The T1 for each voxel is T 1 where we assume free diffusion of water between brain and blood. Regions of interest were drawn on a tagged image because of the higher contrast to noise ratio.

Figure 4.1: Method utilized to obtain perfusion map (Lei et al., 2001). a) The tagging plane magnetically labels water molecules in the blood at the neck. After the post-labelling delay, time for magnetically labelled blood to move into the brain, an image is taken at the region of interest. b) Representative T1 relaxation data where the signal intensity is plotted against repetition time to calculate the brain T1. c) Representative perfusion map where the intensity is proportional to the intensity of the image.

4.2.6 Experimental Design

To localized CBF changes, CASL-HASTE MRI was performed on three separate groups- saline (n =4), 1 hour after soman (n = 9), and 18-24 hours after soman (n = 13). Peripheral cholinergic effects were minimized by using a treatment of HI-6 dimethanesulfonate (HI-6) (125 mg/kg) and atropine methyl nitrate (AMN) (20 mg/kg), which was given before and after soman exposure. Twenty minutes after the initial HI-6 and AMN treatment, a dose of soman (90 µg/kg) or saline was injected in the scruff of the neck. The soman injection site was decontaminated with reactive skin decontamination lotion (RSDL, Emergent Inc). The rats were placed in empty cages without bedding for observation until MRI. Additional treatments of HI-6 and AMN were given every 20 minutes for up to three doses to reduce peripheral symptoms.

Simultaneous CBF and pO2 study was performed in another cohort of rats- saline (n = 4) and 1.5 hours after soman (n = 7). Fiber-optic oxygen sensing probes were implanted using microsurgical techniques in the motor cortex. Post-surgical MRI scans were acquired to ensure no bleeding and correct localization of the pO2 probes. The rats were allowed to recover for a minimum of 7 days prior to experimentation (Figure 4.2).

Baseline CASL-HASTE MRI and pO2 were simultaneously acquired in rats anaesthetized with 1-2% isoflurane, 70% nitrogen, and 30% oxygen. To minimize the effect of stress, baseline

MRI and pO2 were acquired at least 24 hours prior to soman exposure (Figure 4.2). Respiration and temperature were monitored and maintained. Isoflurane was adjusted to maintain respiration at 60 breaths per second while a heating pad with a rectal thermometer was used to maintain a core temperature of 36.5°C.

HI-6 and AMN was given 20 minutes before and after soman exposure. A dose of soman or saline was injected in the scruff of the neck. The soman injection site was decontaminated

with RSDL. The rats were placed in empty cages without bedding for observation until MRI.

Additional treatments of HI-6 and AMN were given every 20 minutes for up to three doses.

The Suffield rating scale was used to determine the severity of soman-related symptoms

(Lee, Bohnert, Wu, et al., 2018) and the Racine scale was used to determine behavioral seizures

(Racine, 1972). At 1.5-hour following soman-induced seizures, post exposure CASL-HASTE

MRI and pO2 measurements were simultaneously acquired (Figure 4.2).

Day 9 Day 1 Day 8 Day 9 Soman # ptO2 probe Baseline Pretreatment (90 μg/kg) Day 9:* implantation ptO2 and MRI (HI-6 and AMN) or saline ptO2 and MRI

Recovery from surgery 24 hours 20 min 20 min 20 min 20 min 30 min Post-treatments (3)#

* ptO2 and MRI was performed 1 hour after initiation of seizure every 20 minutes # Pre- and post-treatment was 20 mg/kg AMN and 125mg/kg HI-6 DMS

Figure 4.2: Experimental timeline of the study.

4.2.7 Data Analysis and Statistics

All statistical analyses were performed using IBM SPSS Statistics for Mac, version 26

(IBM Corp., Armonk, N.Y., USA). CBF study had three groups- saline, 1 hour after soman, and

18-24 hours after soman. A two-way analysis of variance (ANOVA) was performed taking groups and sides (left and right) into consideration. A Bonferroni post hoc test was performed to determine which groups were different. Simultaneous CBF and pO2 study had each group (saline or soman) were measured twice, at least 24 hours before saline or soman to determine the respective baseline and 1.5-hours after saline or soman. CBF and pO2 were normalized using the respective baseline by calculating the change in CBF and pO2. The change in CBF in the caudate putamen and piriform cortex was compared using an unpaired t-test. To compare the changes in

CBF in the motor cortex, a one-way ANOVA was performed between the ipsilateral and contralateral side of the motor cortex following saline or soman exposure. This was followed by a Bonferroni correction post hoc test. The change in T1 in saline or soman exposed group was compared using an unpaired t-test. The changes in pO2 between saline and soman group was also compared using an unpaired t-test. The relationship between pO2 and CBF was determined using a linear regression followed by determining the correlation coefficient (R) and equation of the line. Statistical significance was determined a priori using α = 0.05.

4.3 Results

4.3.1 Cerebral Blood Flow After Soman

Identifying regional changes in CBF after soman exposure can provide a target region to measure pO2. CASL-HASTE MRI was utilized to measure CBF in three separate groups- 24

hours after saline, 1 hour after soman, and 18-24 hours after soman (Figure 4.3). Compared to saline treated group, 1 hour after soman had diffuse hypoperfusion throughout the brain. At 18-

24 hours, CBF appears to recover in most parts of the brain except for the piriform network

(Figure 4.3a). Based on these observations, the piriform cortex was compared between the three groups (Figure 4.3b). There was no significant difference in the piriform cortex by side (left and right) in any group (p = 0.29). However, there was a significant change by group (p < 0.001). At

1 hour, there was a significant bilateral reduction in CBF (p < 0.001) (Figure 4.3b). A significant bilateral reduction in CBF remains 18-24 hours after soman (p < 0.001) (Figure 4.3b). Compared to the 1 hour after soman group, CBF was significantly higher (p < 0.001 (Figure 4.3b) suggesting that some recovery does occur at 18-24 hours. Overall, these results indicate ongoing hypoperfusion after soman up to 18-24 hours.

In order to simultaneously measure CBF and pO2, there is a depth limit when implanting fiber-optic oxygen sensing probe. Taken that into consideration, a shallow region of interest needed to be identified. Based on the results 1 hour after soman where diffuse hypoperfusion was observed and coinciding with the previous study (Chapter 3), the motor cortex was chosen.

Figure 4.3: Hypoperfusion was found 1 hour and 18-24 hours after soman exposure. a) Perfusion map 24 hours after saline, 1 hour and 18-24 hours after soman. There was restricted CBF 1 hour after soman. At 18-24 hours after, CBF appears to recover in most areas except for the amygdala, piriform part of the caudate putamen, and piriform network. b) Quantification shows there was a significant group-wise change in CBF (Two-way ANOVA, F2, 46 = 69.02, p < 0.001). There was a significant bilateral decrease in CBF 1 hour and 18-24 hours after soman in the piriform network compared to the saline treated group (Bonferroni post hoc test: ***p < 0.001). Each shape represents a rat. The middle black bar is the mean while the upper and lower are ±standard deviation.

4.3.2 pO2 and CBF After Soman

To ensure the chronically implanted fiber-optic oxygen sensing probe was localized in the motor cortex, MRI was performed prior to soman exposure. A representative image shows the probe tip is localized in the motor cortex (Figure 4.4a- black arrow).

The cerebral blood flow was then assessed using CASL-HASTE to ensure the implantation process did not change the physiology of the surrounding tissue. The contralateral motor cortex to the implanted probe served as a control. Respective perfusion map shows no change in intensity between the probe implantation site (left) and contralateral motor cortex

(right) (Figure 4.4b). When the change in CBF was compared, there was no significant difference between the motor cortices in either saline or soman exposed rats (Figure 4.5). Before saline, the CBF near the probe was 149 ± 41 mL/100 g/min (mean ± standard deviation) while the contralateral side was 150 ± 40 mL/100 g/min (Table 4.1). Before soman exposure, the ipsilateral CBF was 126 ± 36 mL/100 g/min while the contralateral was 132 ± 40 mL/100 g/min

(Table 4.1). This is consistent with our previous observations where minimal gliosis and scarring were found near the tip of the probe indicating implantation does not interfere with the physiology or result in pathological changes (Lee, Bohnert, Wu, et al., 2018). These results demonstrate that any observed changes near the probe are not from the implantation process and maintain normal physiological response.

To study the neurophysiology from soman-induced seizures, the seizure activity was validated through behavioral evaluation. Within 12 minutes after soman exposure, soman exposed rats developed generalized tonic-clonic seizures (Rating 5 on Racine Scale). Rats continued to show signs of seizures until sedation with isoflurane for MRI at 1.5-hours post- soman exposure.

Using CASL-HASTE and oxygen sensing probes the CBF and pO2 in the motor cortex

1.5-hours after soman-induced seizures were quantified. Representative perfusion maps before and 1.5-hours after soman exposure found extensive hypoperfusion throughout the brain (Figure

4.4). In the caudate putamen, CBF in the saline group changed by -8 mL/100 g/min compared to soman which changed by -95 mL/100 g/min (p = 0.007). Before exposure, CBF was 151 mL/100 g/min while saline was 140 mL/100g/ min and soman decreased to 57 mL/100 g/min. In the piriform cortex the saline group had a decrease in CBF by -0.9 mL/100 g/min compared to soman which changed by -81 mL/100 g/min (p < 0.001). CBF before exposure was 135 mL/100 g/min, while saline was 137 mL/100 g/min and soman exposure decrease CBF to 56 mL/100 g/min. This is a decline of 62% in the caudate putamen and 59% in the piriform cortex. In the motor cortex, there was a decrease in CBF from 126 mL/100 g/min to 59 mL/100 g/min (-53%) in the ipsilateral side while in the contralateral side CBF decreased from 132 mL/100 g/min to 53 mL/100 g/min (-60%) (Table 4.1). Hence there was an overall decrease in the piriform cortex, caudate putamen, and motor cortex.

Figure 4.4: Representative anatomical scan for fiber-optic oxygen sensing probe localization and perfusion map 1.5-hours after soman exposure. a) The tip of the probe (arrow) was localized in the motor cortex. b) Qualitatively the ipsilateral (left square) and contralateral (right square) motor cortex did not show a difference which indicates the probe implantation did not change cerebral blood flow. 1.5-hours after soman exposure there was a global decrease in cerebral blood flow. The image intensity is proportional to the relative cerebral blood flow (mL/100 g/min). All images were acquired in isoflurane anaesthetized rats.

Table 4.1: Percent change in cerebral blood flow in the motor cortex before and 1.5-hour after soman exposure or saline. Cerebral Blood Flow (mL/100 g/min) Changes in Ipsilateral motor cortex Change in CBF Contralateral motor cortex CBF Subject Saline Soman Saline Soman (1.5 hour) (1.5 hour) Saline Soman (1.5 hour) (1.5 hour) Saline Soman Before After Before After Before After Before After

#1 194 ± 32 190 ± 35 96 ± 24 37 ± 31 -0.4% -62% 191 ± 40 194 ± 39 100 ± 22 29 ± 25 2% -71% #2 148 ± 38 131 ± 23 120 ± 43 46 ± 32 -11% -62% 155 ± 30 127 ± 39 111 ± 41 33 ± 21 -18% -71% #3 96 ± 25 93 ± 30 120 ± 35 96 ± 35 -3% -20% 96 ± 28 107 ± 22 114 ± 27 96 ± 27 -3% -16%

#4 159 ± 32 144 ± 32 139 ± 35 35 ± 22 -9% -75% 159 ± 30 161 ± 32 180 ± 35 33 ± 23 -15% -82%

#5 - - 107 ± 30 64 ± 34 - -40% - - 114 ± 29 60 ± 30 - -47%

#6 - - 99 ± 27 68 ± 34 - -31% - - 103 ± 22 59 ± 30 - -43% #7 - - 202 ± 31 69 ± 31 - -66% - - 200 ± 35 61 ± 30 - -70% Mean 149 ± 41 140 ± 41 126 ± 36 59 ± 22 -6% -53% 150 ± 40 148 ± 38 132 ± 40 53 ± 24 -0.6 -60%

Percent change were calculated by (After – before)/before *100 Data are mean ± standard deviation Saline and soman treated rats were two separate group and do not correspond to the same subject number

The changes in CBF were compared before and after (saline or soman) in the ipsilateral and contralateral motor cortex. There was a significant difference in the change in CBF between saline group and soman exposed group in the ipsilateral and contralateral motor cortex (F3,18 =

10.421, p < 0.001). When compared to the ipsilateral side of the saline treated group, there was a significant decrease in CBF 1.5-hours following soman exposure in the both the ipsilateral (p <

0.05) and contralateral (p < 0.01) motor cortex (Figure 4.5). Similar results were found in the contralateral side of the saline treated group where CBF showed a decrease following soman exposure in the ipsilateral (p < 0.01) and contralateral (p < 0.01) motor cortex (Figure 4.5). The

T1 relaxation time before soman was 2204 ± 158 ms and 1.5-hours after soman was 2254 ± 97 ms. While the time before saline was 2218 ± 73 ms and after was 2222 ± 149 ms. When the change in T1 relaxation time before and after treatment (saline or soman) was compared, 4 ± 183 ms for saline and 50 ± 228 ms for soman exposed group, there was not a significant difference (p

= 0.74). The results indicate that the decrease in CBF is not from a change in water content but as a response to soman exposure.

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Figure 4.5: Quantification of change in cerebral blood flow 1.5-hours after soman exposure or saline. There was a significant decrease in cerebral blood flow following soman exposure in both the ipsilateral and contralateral motor cortex compared to the saline group (mean ± standard deviation). When the ipsilateral and contralateral side of the motor cortex was compared within group, there was no significant difference. The middle black line is the mean and the lines represent the standard deviation. Each individual shape corresponds to an individual rat. *p < 0.05, **p < 0.01 (One-way ANOVA with a Bonferroni correction post hoc test)

101

Representative pO2 plot of a rat before and 1.5-hours after soman exposure shows consistent pO2 over time (Figure 4.6a). There was no significant difference between saline and soman exposed group (p = 0.76) (Figure 4.6b). Despite the change in cerebral blood flow, pO2 remained at normoxic levels.

102

a b

Time (min)

Figure 4.6: Representative oxygenation plot and quantification of change in oxygenation following soman exposure or saline. a) Representative oxygenation plot for the duration of the CASL-MRI. b) There was no significant change in oxygenation 1.5-hours after soman exposure compared to the saline. The middle black line is the mean and the lines represent the standard deviation. *p < 0.05 (unpaired t-test).

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In order to understand the relationship between pO2 and CBF in the motor cortex, we correlated the values before and following saline or soman exposure (Figure 4.7). Before exposure, there was a significant correlation where the coefficient of correlation (r) was 0.76 with a slope of 0.23 (p = 0.007). The slope is in good agreement with previous study correlating pO2 and CBF, where a slope of 0.21 was reported in the caudate putamen (Demchenko et al.,

2005). Following saline, there was no significant correlation (r = 0.52, slope = 0.04, p = 0.48). At

1.5-hours after soman, there was no significant correlation (r = 0.71, slope = 0.31, p = 0.08). Due to the low power of the saline group, we compared the slopes before exposure and after saline to ensure that saline did not change the pO2 and CBF relationship. There was no significant difference (p = 0.06), indicating that the saline treated group was within the norm. When we compared the relative change in pO2 and CBF before exposure and after soman, an increase by two-fold in CBF corresponded with a pO2 increase of 23 mmHg before exposure (Figure 4.7).

Similar changes occur 1.5-hours after soman exposure, where pO2 changes by 25 mmHg when

CBF doubles. Although the response in pO2 is similar, the leftward shift in the pO2 response to

CBF after soman exposure indicates lower metabolic activity.

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Figure 4.7: Relationship between pO2 and cerebral blood flow before and 1.5 hours after soman exposure or saline. There was a significant correlation in pO2 and cerebral blood flow before soman or saline (R= 0.76 and p = 0.007). After saline, there was no significant correlation (R = 0.52 and p = 0.48). 1.5-hours after soman exposure, there was no significance (R = 0.71 and 0.08). However, for a given pO2, the cerebral blood flow was lower. The equation of the line are shown.

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4.4 Discussion

The potential dysregulation between cerebral metabolism and blood flow can be determined after soman exposure by simultaneously measuring cerebral blood flow and pO2. The dysregulation may contribute to soman-related neuropathology and restoring normal cerebral blood flow may become a potential therapeutic target.

In a previously reported study it was determined that one-week recovery following implantation of probes was sufficient time for pO2 measurements to reach a steady state (Ortiz-

Prado et al., 2010). The results shown here also show that cerebral blood flow did not change as a result of mechanical trauma from the probe implantation. Although physiological changes from mechanical trauma cannot be completely discounted, these effects were minimized by implanting the probes at an angle which reduces the probability of damaging the penetrating arterioles and therefore preserving normal hemodynamic responses. Consequently, this technique can provide confidence in assessing potential vascular dysfunction following soman-induced seizures.

Previous studies in awake rats without treatments have shown an increase in cerebral blood flow (Goldman et al., 1993; Scremin, Shih, & Corcoran, 1991). The increase in cerebral blood flow was further validated in our previous study with pre- and post- treatments (HI-6 and

AMN) where hyperoxia was found in the cerebral cortex within 1-hour after soman (Lee,

Bohnert, Wu, et al., 2018). In the present study, isoflurane-anaesthetized rats had a decrease in

CBF and normoxia suggesting a potential dysfunction of the hemodynamics after soman exposure. Although isoflurane has been shown to cause a decrease in cerebral glucose utilization and increase in CBF, the coupling response was preserved (Lenz, Rebel, van Ackern,

Kuschinsky, & Waschke, 1998). Since we also control for potential anaesthetic and treatment

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(HI-6 and AMN) effects, the hemodynamic changes observed are likely from soman-induced seizures.

In our study, for pO2 to remain constant despite a decrease in CBF, there would have to be a decrease in cerebral metabolic rate of oxygen (CMRO2). This is supported by the leftward shift in the pO2 versus CBF line observed in the soman exposed group (Figure 4.7).

Hypoperfusion (Geneslaw, Zhao, Ma, & Schwartz, 2011; Suh et al., 2005) and hypometabolism

(Jupp et al., 2012; Shiha et al., 2015) have been found in seizure models. A study found vascular response impairment in the capillaries and arterioles in a recurrent seizure model (O. Prager et al., 2019) suggesting that hypoperfusion following soman may have a similar mechanism.

Another similarity is that oxygenation never falls below normoxia, which was due to mitochondrial impairment (O. Prager et al., 2019). Since reactive oxygen species were found 30 minutes after soman-induced seizures (Jacobsson et al., 1999), we speculate the physiological mechanism that decreases CMRO2 in soman-induced seizures may be oxidative stress.

Oxidative stress provides a compatible explanation for the decrease in CMRO2 and CBF.

Since mitochondrial damage was not found until 8-hours after soman-induced seizures (Baille et al., 2005), a much more likely mechanism is oxidative stress. Markers of oxidative stress including nitric oxide was found as early as 30 minutes following soman-induced seizures in the cortex (Jacobsson et al., 1999). Seizures are metabolically demanding activities and in a previous study, we have found sustained hyperoxia (Lee, Bohnert, Wu, et al., 2018) which may generate high levels of reactive oxygen species. The reactive oxygen species that are produced could cause mitochondrial dysfunction without direct damage (Jarrett, Liang, Hellier, Staley, & Patel,

2008; Rowley et al., 2015; Ryan, Backos, Reigan, & Patel, 2012). Metabolic dysfunction via reactive oxygen species would prevent cells from utilizing delivered oxygen and result in a shift

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in energy production to anaerobic glycolysis. Soman-induced seizures have been found to also increase lactic acid (A. L. Miller & Medina, 1986), which is a by-product of anaerobic glycolysis, leading to cerebral lactic acidosis. This starts a deleterious cycle that continues to produce reactive oxygen species causing further damage, mitochondrial dysfunction, and sustained vasoconstriction.

Overproduction of reactive oxygen species can impair vascular reactivity and cause vasoconstriction. At low concentrations, reactive oxygen species induces vasodilation through the production of hydrogen peroxide (Didion & Faraci, 2002; A. A. Miller, Drummond, Schmidt,

& Sobey, 2005; Park et al., 2004). However, an overproduction of reactive oxygen species during soman-induced seizures an cause an upregulation of endothelin-1 which is a potent vasoconstrictor (Palmer, Tayler, & Love, 2013). Additionally, reactive oxygen species reduces the bioavailability of nitric oxide, a vasodilator, through the generation of peroxynitrite (Park et al., 2005; Tong, Nicolakakis, Kocharyan, & Hamel, 2005). Although we cannot be certain whether vascular reactivity is altered, the pericytes which are the contractile elements of the capillaries are highly susceptible to oxidative damage (Ding, Zhang, Gu, Xu, & Wu, 2017).

Therefore, oxidative stress may be the unifying neuropathology that could cause a reduction in

CBF and CMRO2.

Perfusion at 18-24 hours after soman may not recover due to damage to the neurovascular coupling unit. The piriform network has remained a major region of interest with regards to NA- related neurological damage. A study using sarin found impairment in BBB at 24 hours after exposure (Abdel-Rahman et al., 2002). Damage to the endothelial cells early on due to oxidative stress may impair vascular regulation by these cells. Hence, even though most areas have recovered CBF, the piriform network remains hypoperfused. Prolonged hypoperfusion may

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exacerbate neurological damage following soman exposure. Additionally, the piriform cortex has been speculated as the seizure onset site following NA exposure (Myhrer, 2007; Zimmer et al.,

1998). Hypoperfusion in the seizure onset site following soman exposure is consistent with a study that utilized ASL to localize seizures in epilepsy patients (Gaxiola-Valdez et al., 2017).

These results not only validate that the piriform cortex is the seizure onset site but also restoring

CBF may be a therapeutic target in preventing further damage.

An important factor to note in this study was that the rats were under isoflurane anaesthesia and exposed to a potent acetylcholinesterase inhibitor. Despite the vasodilatory effect of isoflurane (Conzen et al., 1992) and possibly excess acetylcholine (ACh) (Heistad, Marcus,

Said, & Gross, 1980) we found hypoperfusion throughout the brain. It is possible that atropine can attenuate ACh mediated vasodilation (Heistad et al., 1980) but that is unlikely in these studies as AMN does not readily cross the blood-brain barrier (Samuel, Kodama, & Mennear,

1965). There are no known effects of HI-6 on CBF but we also expect the effects to be minimal due to the limited entry into through the blood-brain barrier (Ligtenstein, Moes, & Kossen,

1988). Therefore, the major reduction in CBF is likely caused by a pharmacodynamic interaction between soman and isoflurane. Previous known pharmacological interactions with acetylcholinesterase inhibitors include improved recovery from isoflurane anaesthesia (Wiese,

Brosnan, & Barter, 2014), and prevention of memory impairment caused by isoflurane (Su et al.,

2011). However, we believe the most relevant property is the anti-seizure effect of isoflurane

(Hilz, Bauer, Claus, Stefan, & Neundorfer, 1992). Isoflurane may terminate seizures (Hilz et al.,

1992) causing a reduction in cerebral metabolism. The depressive effects of soman have also been noted in a previous study, where termination of soman-induced seizures caused a decrease in cerebral glucose utilization below normal (Samson et al., 1984). Such decrease in metabolism

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was not found when rats were treated with diisopropyl fluorophosphate, which may indicate the effects to be unique to soman. Overall, the fact that pO2 did not change, whereas in a previous study we found hyperoxia without anaesthesia (Lee, Bohnert, Wu, et al., 2018), is evidence to support that isoflurane appears to be neuroprotective. Brief isoflurane administration has shown to reduce neuronal damage and terminate seizures following organophosphate exposure, demonstrating the neuroprotective effect (Hobson et al., 2018; Krishnan et al., 2017). However, in terms of survival following sarin exposure, the LD50 was similar between awake and isoflurane anaesthetized swine at normal oxygen tensions (Sawyer et al., 2012) indicating minimal pharmacodynamic interaction on survival. Since our study focuses on vascular hemodynamics in the brain, where isoflurane has a known effect, we cannot discount a pharmacodynamic interaction between isoflurane and soman.

In the future, we will study changes in cerebral blood flow and/or pO2 with a different type of anaesthetic or sedative. In utilizing a different type of anaesthetic or sedative, we can gain more information on the potential effects of anaesthesia. Additionally, we will study changes in cerebral blood flow and/or pO2 at different time points. There may also be certain brain regions where reperfusion has not occurred, thereby contributing to the neuropathology.

This would correspond with other reports where postictal hypoperfusion and the administration of vasodilators resulted in neuroprotection (Farrell et al., 2016).

In conclusion, we present strong evidence for hypoperfusion throughout the brain 1.5- hour after soman exposure. As this is associated with a stable oxygen level, we argue that a drop- in oxygen utilization possibly due to reactive oxygen species damaging the mitochondria.

Additionally, prolonged hypoperfusion was found in the piriform network at 18-24 hours which

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may be linked to damage to the neurovascular unit. A further understanding of oxygenation and

CBF, could lead to new therapeutic targets.

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Chapter 5 Quantitative T2 MRI is predictive of neurodegeneration following

organophosphate exposure in a rat model

Kevin Lee1, 2, 3, Sara Bohnert4, Matthew Bouchard1, 2, 3, Cory Vair4, Jordan S. Farrell1, 5, G.

Campbell Teskey1, John Mikler4, and Jeff F. Dunn*1, 2, 3

1: Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary,

Alberta, Canada

2: Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary,

Alberta, Canada

3: Department of Clinical Neuroscience, Cumming School of Medicine, University of Calgary,

Calgary, Alberta, Canada

4: Defence Research and Development Canada- Suffield Research Centre, Department of

National Defence, Alberta, Canada

5: Department of Neurosurgery, Stanford University, Stanford, California, USA

This chapter is published as: Quantitative T2 MRI is predictive of neurodegeneration following organophosphate exposure in a rat model. We have made modifications to make the topic flow within the context of the thesis.

Author Contributions

J.F.D. oversaw the project. K.L. designed and performed all experiments. S.B. provided soman, carried out exposure, and advised on the project. C.V. assisted in soman exposure. J.M. assisted in soman exposure. M.B. assisted in histology, MRI data analysis, and histology quantification.

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J.S.F. provided protocols for histology and advised on the project. G.C.T. advised on the project.

K.L. wrote the main manuscript and prepared all of the figures with oversight from J.F.D. All authors reviewed and edited the manuscript.

Abstract

Organophosphorus compounds, such as chemical warfare nerve agents and pesticides, are known to cause neurological damage. This study measured nerve agent-related neuropathology and determined whether quantitative T2 MRI could be used as a biomarker of neurodegeneration.

Quantitative T2 MRI was performed using a 9.4T MRI on rats prior to and following soman exposure. T2 images were taken at least 24 hours prior, 1 hour and 18-24 hours after soman exposure. Rats were pre- and post-treated with HI-6 dimethanesulfonate and atropine methyl nitrate. A multicomponent T2 acquisition and analysis was performed. Brains were stained with

Fluoro-Jade C to assess neurodegeneration. Rats exposed to soman developed behavioral expression of electrographic seizures. At 18-24 hours after soman exposure, significant increases in T2, a possible marker of edema, were found in multiple regions. The largest T2 changes were in the piriform cortex (before: 47.7 ± 1.4 ms; 18-24 hours: 82.3 ± 13.4 ms). Fluoro-Jade C staining showed significant neurodegeneration 18-24 hours post exposure. The piriform cortex had the strongest correlation between the change in relaxation rate and percent neurodegeneration (r = 0.96, p < 0.001). These findings indicate there is regionally specific neurodegeneration 24 hours after exposure to soman. The high correlation between T2 relaxivity and histopathology supports the use of T2 as a marker of injury.

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5.1 Introduction

Chapter 2 outlines background information on NAs, neuropathophysiology associated with NAs, basic MRI physics, and MRI methods. A key problem is that following nerve agent exposure, assessing the extent of brain injury is difficult. A non-invasive method that is sensitive to nerve agent related pathology would allow for the monitoring of patients and determining the efficacy of nerve agent treatment protocols. Current treatment protocols are effective in protecting against lethality; however, they may not prevent nerve agent-related neuropathology and associated long-term sequelae. MRI has been used to assess brain pathology post OP exposure (Bhagat et al., 2001; Bhagat et al., 2005; Carpentier et al., 2008; Gullapalli et al., 2010;

Hobson et al., 2018; Hobson et al., 2017; Rosman et al., 2012; Testylier et al., 2007) but few studies have directly correlated the MR changes to histopathology (Hobson et al., 2017; Rosman et al., 2012; Testylier et al., 2007). Diffusion MRI provides contrast that relates to cell swelling, changes to myelin, and water content (Hagmann et al., 2006). In models of OP exposure, diffusion MRI has shown contrast that correlates with histological damage detected with hematoxylin and eosin (Hobson et al., 2017; Rosman et al., 2012) or hemalun-phloxine

(Testylier et al., 2007), and neuroinflammation detected with ionized calcium binding adaptor molecule 1 (IBA1) and glial fibrillary acidic protein (GFAP) (Hobson et al., 2017). The main contributor to nerve agent-related neurological damage is believed to be from prolonged nerve agent-induced seizure activity (Myhrer et al., 2008). Nerve agents irreversibly inhibit acetylcholinesterase which leads to hyperactivity of cholinergic neurons in the piriform cortex and medial septum (Zimmer et al., 1998). This hyperactivity initiates a cascade that recruits glutamatergic neurons in the temporal lobe causing the onset of seizures (McDonough & Shih,

1997; Shih & McDonough, 1997). Prolonged nerve agent-induced seizures have been shown to

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cause consistent damage in the cerebral cortex, piriform cortex, amygdala, thalamus, and hippocampus (Baille et al., 2005).

Quantitative T2 imaging (qT2) can be used to study the neuropathology following soman- induced convulsive seizures as it is sensitive to the changes in water content (edema) in the brain microstructure. Previous T2 relaxivity studies using soman have mainly focused on using signal intensity (Hobson et al., 2018; Rosman et al., 2012) or change in T2 time (Bhagat et al., 2001;

Bhagat et al., 2005) to identify regions of damage followed by histology to validate the damage

(Bhagat et al., 2001; Bhagat et al., 2005; Hobson et al., 2018; Rosman et al., 2012). However, there have been no studies published that have attempted to correlate T2 relaxivity with the percentage of neurodegeneration following soman exposure.

This study used quantitative T2 MRI to correlate the severity and regional specificity of neurodegeneration following soman exposure. Soman is typically used to study the neuropathology of nerve agents since it is the fastest aging (form an irreversible bond with acetylcholinesterase) nerve agent (Worek et al., 2004) and produces consistent convulsive seizures in defined models. Aging occurs within 2-3 mins compared to hours for other nerve agents (Worek et al., 2004), which introduces complexity in treating soman exposure. Therefore, treatments that are effective against soman are often effective, if not more so, against other nerve agents (Shih et al., 2003).

The first objective of the study was to use qT2 MRI to identify structural changes in the brain 1 hour and 18-24 hours after a convulsive dose of soman. The second objective was to correlate the changes in qT2 MRI to the severity of neurodegeneration using histology. We hypothesized that soman-induced convulsive seizures would cause edematous injury and neurodegeneration within 24 hours that could be consistently detected using qT2 MRI.

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Establishing the sensitivity of qT2 MRI to soman-related neuropathology will be useful as a diagnostic biomarker and facilitate the application to examining the efficacy of treatments in the future.

5.2 Methods

5.2.1 Experimental Design

Previously, we determined that 90 µg/kg (subcutaneous) of soman consistently induced convulsive seizures in a rodent model (Lee, Bohnert, Wu, et al., 2018). HI-6 dimethanesulfonate

(HI-6) (125 mg/kg) and atropine methyl nitrate (AMN) (20 mg/kg), were dissolved in saline, and given as pre- and post-treatment (volume of 1 ml/kg; intraperitoneal) to reduce peripheral soman-related symptoms thereby increasing animal throughput. HI-6 reactivates AChE by breaking the phosphate bond between AChE and soman before the aging process (Jokanovic &

Stojiljkovic, 2006). AMN is a competitive inhibitor of ACh at muscarinic receptors, which reduces peripheral cholinergic symptoms (Shih et al., 1991). HI-6 and AMN are poor at crossing the blood-brain barrier (BBB), hence have minimal therapeutic benefit for seizure control.

For MRI, rats (n = 23) were anaesthetized with a mixture of 1-2.5% isoflurane, delivered in 70% nitrogen and 30% oxygen. Baseline qT2 MRI was performed using a 9.4T MRI at least

24 hours prior to saline or soman treatment. Pre-treatment was administered 20 minutes prior to soman exposure. For safety during soman exposure, rats were lightly anaesthetized with isoflurane for a maximum of 2-3 minutes and injected (25G 5/8 needle, volume of 0.4 ml/kg) subcutaneously with soman (90 µg/kg) at the scruff of the neck. The injection site was immediately decontaminated with Reactive Skin Decontamination Lotion and the rat was placed in an observation cage. Rats were observed for the development of soman-related symptoms

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based on the Suffield rating scale (Lee, Bohnert, Wu, et al., 2018) and behavioral seizures using the Racine scale (Racine, 1972). An additional three doses of the post-treatment regimen were administered at 20-minute intervals (intraperitoneal).

Separate groups of soman treated rats were imaged at 1 hour (n = 9) or 18-24 hours (n =

10) after exposure. Rats that were given saline were imaged at 1 hour and 24 hours (n = 4). To account for the neuroprotective properties of isoflurane (Krishnan et al., 2017), the brain tissues of soman treated rats were preserved through fixation (see section 3.6) immediately after imaging. The brain tissues of saline treated rats were collected at 24 hours. Fluoro-Jade C histochemistry was performed and level of staining quantified as an indicator of neurodegeneration.

5.2.2 Animals

Animal care protocols were approved by the University of Calgary Animal Care committee and met the Canadian Council of Animal Care (CCAC) guidelines. Rats were closely monitored daily by qualified staff to ensure animal welfare standards were maintained.

Male Sprague-Dawley rats, weighing 240-300 g, were obtained from Charles River

Laboratories (Montréal, QC, Canada). Rats were housed in pairs at the University of Calgary

Animal Care Facility (Calgary, AB, Canada) in an environmentally controlled room on a 12-hour light/dark cycle. Access to food and water ad libitum. All experiments were performed following a minimum acclimatization period of five days in their new environment and to human interactions.

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5.2.3 Soman and Treatments

(±) Soman (O-pinacolyl methylphosphonofluoridate; CAS 96-64-0), HI-6 dimethanesulfonate (CAS 144252-71-1), and Reactive Skin Decontamination Lotion were provided by the Defence Research and Development Canada Suffield Research Centre. Atropine

Methyl Nitrate (CAS 52-88-0) was purchased from Sigma Aldrich (Milwaukee, WI, USA).

5.2.4 Symptom and Seizure Evaluation

The Suffield Rating Scale was used to evaluate soman-related symptoms (Lee, Bohnert,

Wu, et al., 2018) while the Racine scale was used to measure behavioral seizures (Racine, 1972).

Rats treated with soman were monitored and rated every 10 minutes for up to 2 hours. If the rats were rated 4 or higher on the Suffield Rating Scale, additional observations were required until an improvement was observed for at least two consecutive observation periods.

5.2.5 MRI Parameters and Analysis

MRI was performed using a 9.4T Bruker Avance console (Bruker Biospin GmbH,

Rheinstetten, Germany) with a 35-mm quadrature volume coil. Rats were anaesthetized with 1-

2.5% isoflurane, in 70% nitrogen and 30% oxygen. An in-house built restraining system including ear bars and a bite bar that was used to secure the head and prevent motion artifacts.

Scanning protocol involved a multi-slice multi-echo T2 sequence: TR = 6534 ms, 32 echoes were collected with 10 ms echo spacing, 1 average, 20 slices, field of view = 30 x 30 mm2, and matrix size = 128 x 128, voxel size = 0.23 x 0.23 x 0.8 mm3. Respective baseline images were obtained for each rat followed by either saline or soman injection (Figure 5.1). Throughout the image

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acquisition, temperature and respiration rate were monitored and maintained at normal physiological range (approximately 36.5°C and 60 breaths per minute).

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Figure 5.1: Representative coronal images of the fourth echo (40 ms) A, baseline and B, 18-24 hours after soman injection. C, Comparison of baseline, saline, 1 hour after soman, and 18-24 hours after soman. At 18-24 hours after soman exposure, extensive hyperintensive regions were observed in the piriform cortex, cerebral cortex, amygdala, and thalamus (colored arrows). Additionally, ventricular enlargement was seen 18-24 hours after soman exposure.

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Multiexponential T2 analysis was performed using AnalyzeNNLS

(https://sourceforge.net/projects/analyzennls/), which is a compilation of open source MATLAB scripts (Bjarnason & Mitchell, 2010). The T2 relaxation curve was mapped starting with the second echo due to complications with the stimulated echoes. Tissue heterogeneity produces a decay curve composed of multiexponential components. The different components in a multiexponential decay curve can be analyzed by Eq. (1) (Kenneth P Whittall & MacKay, 1989):

4 (#$!⁄&"#) 4/ = ∑05' 60* 7 = 1,2, … , : (1) where ti is the echo time, M = 120 which are the logarithmically spaced T2 times between 5 to

640 ms, N = 32 which represents the total number of echoes, and sj represents the relative signal amplitude at the partitioned T2 time (T2j). The analysis utilizes a non-negative least square

(NNLS) algorithm to minimize misfit and smoothing constraint for the T2 distribution. This provides a more consistent fit when noise is present (Lawson & Hanson, 1995; Kenneth P

Whittall & MacKay, 1989). We defined the area under the amplitude of the T2 curve as three different water compartments depending on the T2 values. We used the range of T2 < 25 ms for myelin associated water, T2 of 25-200 ms for intra/extracellular water, and T2 > 2000 ms for cerebrospinal fluid.

A rat brain atlas (Paxinos & Watson, 2006) was used as a reference to manually draw the corresponding regions of interest in the qT2 images. Signal changes before and after exposure were measured in the piriform cortex, basolateral amygdala, medial amygdala, medial thalamus, dorsolateral thalamus, cerebral cortex, and retrosplenial cortex. Representative T2 fitting and distribution before and 18-24 hours after soman-induced seizures in the piriform cortex can be seen in Figure 5.2.

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Figure 5.2: Representative T2 fitting and distribution before (A and B) and 18-24 hours after a convulsive dose of soman (C and D) in the piriform cortex. A, signal intensity decayed by 250 ms. B, the mean geometric T2 distribution was 48 ms. C, 18-24 hours after soman higher signal intensity was detected with the signal decay by 320 ms. D, 18-24 hours after soman the mean T2 distribution was 93 ms which widened and shifted to the right.

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5.2.6 Tissue Preparation and histology

Rats were deeply anaesthetized with sodium pentobarbital (200 mg/kg; intraperitoneal) immediately following MRI imaging. To preserve the brain tissue, rats were intracardially perfused with 150 mL of cold 1% phosphate-buffered saline (PBS) and fixed with 200 mL of 4% paraformaldehyde (PFA) solution. Brains were extracted and stored in 4% PFA for 24 hours at

4°C then transferred to a 30% sucrose solution for long-term storage. The brains were sliced to

25 μm thickness using a cryostat (Leica, Biosystems). Slices were placed on electrostatically charged slides and stored at -80°C.

To determine the number of neurons in control tissue, saline treated rats were stained for

Neuronal Nuclei (NeuN) (no. ab177487, Abcam Inc, ON, Canada). The slides were removed from the freezer and air dried for 30 minutes. The slides were then incubated for 1-hour in a blocking serum composed of 10% horse serum, 1% bovine serum albumin (BSA), 0.1% cold fish skin gelatin (CFSG), 0.5% Triton X-100, and 0.05% Tween-20 in 1x PBS. Following incubation slides were rinsed in a 0.05% Tween-20 solution in 1x PBS for 10 minutes. The primary antibody NeuN, diluted with 5% horse serum, 1% BSA, 0.1% CFSG, and 0.5% TritonX-100 in

1x PBS, was applied on the slides for 12-hours. Slides were once again rinsed in 0.05% Tween-

20 in 1x PBS for 10 minutes. The secondary antibody Alexa Fluor 594 (no. 711-585-152,

Jackson ImmunoResearch Laboratories Inc, PA, USA) was diluted in 1% BSA, 0.1% CFSG, and

1% TritonX-100 solution in 1x PBS. Slides were incubated with the secondary antibody for 1- hour and rinsed in 0.05% Tween-20 in 1x PBS for 10 minutes. Throughout the secondary incubation and all subsequent steps, the slides were kept in a dark environment at room temperature. Slides were then fitted with coverslips using Immuno-Mount (Thermo Scientific,

ON, Canada).

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Tissues were stained using Fluoro-Jade C (no. AG325, Millipore, ON, Canada), which has been shown to selectively stain for degenerating neurons (Schmued, Stowers, Scallet, & Xu,

2005). Frozen sections were rehydrated followed by incubation in 0.06% KMnO4 for 20 min.

The sections were then drained and rinsed for 2 min with distilled water followed by incubation in 0.00001% Fluoro-Jade C (FJC) solution for 20 min. Following incubation slides were rinsed three times in distilled water and dried with a hair dryer for five minutes in a dark environment.

Dried slides were placed in xylene for 5 minutes, and cover slipped with dibutylphthalate polystyrene xylene (DPX) mounting medium (Sigma Aldrich, Milwaukee, WI, USA).

5.2.7 Quantification of NeuN and FJC

A rat brain atlas (Paxinos & Watson, 2006) was used to determine the counting frame in

FJC and NeuN stained slices. The stained sections were visualized using the Olympus BX61-

DSU microscope. FJC was viewed with a fluorescein isothiocyanate filter at 450-490 nm and

NeuN was viewed with a tetramethylrhodamine filter at 488-532 nm. The images were taken using a high-resolution digital camera from MBF Bioscience (Williston, VT, USA).

Quantification of FJC and NeuN positive cells was performed manually using Stereo Investigator

(version 11, MBF Bioscience). Regions of interests were identified at 10x magnification

(Numerical aperture= 0.24). The counting frame was 400 x 400 μm2 in the regions of interest.

The FJC and NeuN positive cells per area were calculated via number of cells over the area of the counting frame.

To quantify and compare the extent of neurodegeneration, the heterogeneity in cells per area between regions must be accounted for. As such, we calculated the percentage of neurodegeneration by comparing the FJC and NeuN positive cells per area.

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5.2.8 Statistics

All statistical analyses were performed using R 3.5.0 (Team, 2013) or MATLAB 2018a

Statistics and Machine Learning Toolbox (Mathworks, Natick, MA, US). There were three groups (saline, 1 hour after soman, and 18-24 hours after soman), each imaged twice before and after saline or soman exposure. A general linear model was performed evaluating the changes in

T2 after exposure. Group (saline, soman 1 h, soman 18-24 hrs), treatment (before, after exposure), and brain regions were entered as fixed effects. This was followed by Tukey’s honestly significant difference post-hoc test. For the linear regression, the relaxation rate (R2) was calculated using R2 = 1/T2. The relationship between changes in R2 vs. percentage of neurodegeneration was determined through linear regression to calculate the correlation coefficient (r), and equation of the line. We excluded one rat from the linear regression because tissues did not adhere to the slides and FJC staining could not be assessed. Statistical significance was determined a priori using α = 0.05.

5.3 Results

Consistent with our previous study (Lee, Bohnert, Wu, et al., 2018), rats (n = 19) exposed to soman developed generalized tonic-clonic seizures within 7-21 minutes post exposure. These rats continued to exhibit intermittent mild tremors with rhythmic head movement until imaging at 1 hour (n = 9) or 18-24 hours (n = 10). As expected, rats (n = 4) treated with saline did not exhibit behavioral abnormalities.

To consider qT2 MRI as an accurate depicter of brain damage following soman-induced seizures, the images that it produces need to clearly depict the regions of damage. Compared to the baseline (Figure 5.1a), at 18-24 hours after soman exposure we found clearly defined

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hyperintensive regions in the basolateral amygdala, medial amygdala, dorsolateral thalamus, medial thalamus, and piriform cortex (Figure 5.1b). Whereas more subtle hyperintensity was observed in the cerebral cortex and retrosplenial cortex (Figure 5.1b). The cohort 18-24 hours after soman had notable changes that were easily identifiable, while there were no observable changes in saline treated and 1 hour after soman exposure groups (Figure 5.1c). As there were substantive changes found 18-24 hours after soman exposure, the change in T2 relaxation time was quantified in the regions of interest, using a multiexponential T2 decay analysis.

Multiexponential T2 analysis was used to obtain the T2 distribution and decay curves because it provides enhanced pathological specificity compared to a monoexponential T2 analysis (MacKay et al., 2006). A representative analysis using the piriform cortex as an example is shown in Figure 5.2. As expected, at 18-24 hours after soman exposure the T2 distribution was higher and wider with a rightward shift (Figure 5.2b and 5.2d). The baseline had a geometric mean T2 of 48 ms (Figure 5.2b) while 18-24 hours after soman exposure the T2 was 93 ms

(Figure 5.2d). We did not see any peaks between 200-2000 ms, which is consistent with previous observations (MacKay et al., 1994; Menon & Allen, 1991; K. P. Whittall et al., 1997).

We quantified the changes in T2 relaxation time after soman-induced seizures to determine the damage in the regions of interest (Table 5.1). There was a three-way interaction between group, treatment, and brain region (F12, 280 = 11.71, p < 0.001). Post-hoc test was performed and revealed that there was no significant change pre and post saline exposure (n = 4) in every brain region (Figure 5.3 and Figure 5.3, supplement 1). Additionally, at 1 hour after soman exposure (n = 9) there was no significant change before and after soman in regions of interest (Figure 5.3 and Figure 5.3, supplement 1). At-18-24 hours after soman exposure (n =

10), there was a significant increase in T2 in the basolateral amygdala by 36% (t = 14.8, df = 280,

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p < 0.001), dorsolateral thalamus by 35% (t = 12.5, df = 280, p < 0.001), and piriform cortex by

42% (t = 20.5, df = 280, p < 0.001) (Figure 5.3). A significant increase in T2 was also found in the cerebral cortex by 20% (t = 5.8, df = 280, p < 0.001), medial amygdala by 21% (t = 7.3, df =

280, p < 0.001), and medial thalamus by 29% (t = 10.2, df = 280, p < 0.001) (Figure 5.3, supplement 1). Quantification of T2 reveals that the piriform cortex had the most severe damage followed by the basolateral amygdala and dorsolateral thalamus.

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Table 5.1: Mean T2 times of different anatomical brain structures in rats before and after exposure to a convulsive dose of soman Saline Soman - 1 hour Soman - 18-24 hours Degenerating (n = 4) (n = 9) (n = 10) neurons

T (msec) T (msec) T (msec) 2 FJC+ cells/area 2 FJC+ cells/area 2 FJC+ cells/area 2 2 2 Location Before After (# cells/mm ) Before After (# cells/mm ) Before After (# cells/mm )

Basolateral Amygdala 44.6±1.1 44.1±2.0 0 43.9±1.3 42.3±1.5 0 44.5±1.3 69.4±8.6 *** 519±215 55%

Cerebral Cortex 39.3±0.3 38.0±0.7 0 39.7±1.4 37.6±1.3 0 38.7±1.5 48.4±7.1 *** 381±165 23%

Dorsolateral Thalamus 39.8±0.7 38.1±0.8 0 37.3±1.8 36.9±2.1 0 38.4±1.3 59.4±6.2 *** 521±61 69%

Medial Amygdala 46.4±1.0 46.4±1.8 0 45.4±1.4 46.9±2.2 0 46.1±1.0 58.4±3.2 *** 747±205 50%

Medial Thalamus 42.2±0.6 42.8±1.0 0 42.0±1.0 42.9±1.7 0 42.8±1.4 59.9±6.0 *** 669±181 60%

Piriform Cortex 48.2±0.4 47.6±0.5 0 46.8±1.9 46.9±1.3 0 47.7±1.4 82.3±13.4 *** 701±139 76%

Retrosplenial Cortex 39.4±0.9 37.2±1.5 0 36.4±2.0 36.9±1.2 0 37.3±1.3 39.1±1.6 ``` 291±110 25%

Percent degenerating neurons were calculated by comparing the FJC+ cells per area in soman treated rats and NeuN+ cells per area in saline treated rats Data are mean ± standard deviation. General linear model. Statistical significance were calculated using each rats respective control images prior to treatment. Significance: * p < 0.05, ** p < 0.01, *** p < 0.001.

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aA bB C 110 Basolateral Amygdala 110 Dorsolateral Thalamus c 110 Piriform Cortex ***

100 *** 100 100 90 90 90 (ms) (ms) (ms) 80 80 80 2 2 2 ***

70 70 70

60 60 60

50 50 50 Geometric Mean T Geometric Mean T Geometric Mean T 40 40 40

30 30 30

20 20 20 Before1 After2 Before3 After4 Before5 After6 Before1 After2 Before3 After4 Before5 After6 Before1 After2 Before3 After4 Before5 After6 Saline Soman (1h) Soman (18-24hrs) Saline Soman (1h) Soman (18-24hrs) Saline Soman (1h) Soman (18-24hrs) Figure 5.3: The effects of soman exposure on T2 relaxation time before exposure, 1 hour after soman (n = 9), or 18-24 hours after soman (n = 10). A-C, there was no significant difference 1 hour after soman exposure from the respective baseline. There was a significant difference 18-24 hours after soman exposure from the respective control in the basolateral amygdala (t = 14.8, df = 280, p < 0.001), dorsolateral thalamus (t = 12.5, df = 280, p < 0.001), and piriform cortex (t = 20.5, df = 280, p < 0.001). There was no significant difference in the saline treated group (n =4). Rats were imaged at least 24 hours before treatment. Black bars are the maximum and minimum T2 time. Middle black line is the median and the plus signs are outliers. The baseline for each group served as their own respective control. *p < 0.05, **p < 0.01, ***p < 0.001

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aA Bb Cc Dd 110 Cerebral Cortex 110 Medial Amygdala 110 Medial Thalamus 110 Retrosplenial Cortex

100 100 100 100

90 90 90 90 (ms) (ms) 80 (ms) 80 (ms) 80 80 2 2 2 2 *** 70 70 70 70 *** *** 60 60 60 60

50 50 50 50 Geometric Mean T Geometric Mean T Geometric Mean T Geometric Mean T 40 40 40 40

30 30 30 30

100 100 100 100

90 90 90 90 (ms) (ms) 80 (ms) 80 (ms) 80 80 2 2 2 2 *** 70 70 70 70 *** *** 60 60 60 60

50 50 50 50 Geometric Mean T Geometric Mean T Geometric Mean T Geometric Mean T 40 40 40 40

30 30 30 30

20 20 20 20 Before1 After2 Before3 After4 Before5 After6 Before1 After2 Before3 After4 Before5 After6 Before1 After2 Before3 After4 Before5 After6 Before1 After2 Before3 After4 Before5 After6 Saline Soman (1h) Soman (18-24hrs) Saline Soman (1h) Soman (18-24hrs) Saline Soman (1h) Soman (18-24hrs) Saline Soman (1h) Soman (18-24hrs) Figure 5.3, supplement 1: The effects of soman exposure on T2 relaxation time in the cerebral cortex, medial amygdala, medial thalamus, and retrosplenial cortex before, 1 hour after soman (n = 9), and 18-24 hours after soman (n = 10). A-D, there was a no significant change 1 hour after soman exposure compared to their respective pre exposure. At 18-24 hours after soman exposure, there was a significant increase in the T2 relaxation time in the cerebral cortex (t = 5.8, df = 280, p < 0.001), medial amygdala (t = 7.3, df = 280, p < 0.001), medial thalamus (p < 0.001, t = 10.22, df = 9), and retrosplenial cortex (t = 10.2, df = 280, p < 0.001). No significant difference in the saline treated group (n = 4). Pre exposure images were acquired at least 24 hours before treatment. The black bars are the maximum and minimum T2. Middle black line is the median and the plus signs are outliers. Each group has their respective control. *p < 0.05, **p < 0.01, ***p < 0.001

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Using FJC, which is a stain for neurodegeneration (Schmued et al., 2005), we validated the damage found in the regions of interest when using qT2 MRI. The qualitative assessment suggests that there was no neurodegeneration in saline treated rats or in rats examined 1 hour after soman exposure (Figure 5.4 and Figure 5.4, supplement 1). While at 18-24 hours after soman exposure, there were a high number of FJC positive cells in the regions of interest (Figure

5.4 and Figure 5.4, supplement 1). To quantify this observation, we analyzed the FJC positive cells per area in the regions of interest (Table 1). We found the medial amygdala had the highest

2 neurodegeneration per area of 747 ± 205 cells per mm (mean ± SD) while the retrosplenial cortex had the lowest neurodegeneration per area of 291 ± 110 cells per mm2. However, when the heterogeneity in cells per area between regions were accounted for, using NeuN, we found the piriform cortex had the highest percentage of neurodegeneration of 76% while the cerebral cortex had the lowest percentage of 23%. These finding suggests there may be heterogeneity in the progression of neurodegeneration that are region dependent and are not reflective of the T2 relaxation time.

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Figure 5.4. Effect of soman-induced seizures on neuronal cells following 18-24 hours after soman exposure in the cerebral cortex, medial amygdala, and piriform cortex. Rats were perfused and fixed immediately after MR imaging and stained using Fluoro-Jade C, which is a marker for neurodegeneration. Fluoro-Jade C positive cells were manually quantified in regions corresponding to the T2-weighted MR images.

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Figure 5.4, supplement 1: The effects of soman-induced seizures on neuronal cells following 18-24 hours after soman exposure in the basolateral amygdala, dorsolateral thalamus, medial thalamus, and retrosplenial cortex. There was extensive Fluoro-Jade C staining indicative of neurodegeneration at 18-24 hours after soman exposure.

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To determine the efficacy of qT2 MRI in delineating soman-related brain damage, the changes in the relaxation rate (R2 = 1/T2) were correlated to the percentage of neurodegeneration in regions of interest. The percentage of neurodegeneration was used to account for heterogeneity between regions. We correlated with R2 as the relaxation rate changes linearly with factors that influence relaxation of water (Villringer et al., 1988). Since there were no FJC positive cells in saline treated or 1 hour after soman exposure, only the 18-24 hours after soman exposure group (n = 9) was analyzed. There was a significant correlation in the cerebral cortex (r

= 0.86, p = 0.003 with a slope of 0.013), medial amygdala (r = 0.86, p = 0.003 with a slope of

0.006), and piriform cortex (r = 0.96, p < 0.001 with a slope of 0.008) (Figure 5.5). Additional correlations are shown in the supplementary information: dorsolateral thalamus (r = 0.76, p =

0.02, with a slope of 0.014), and medial thalamus (r = 0.78, p = 0.014 with a slope of 0.0065)

(Figure 5.4, supplement 1). Notably, there was no significant correlation in the basolateral amygdala (r = 0.07, p = 0.87 with a slope of 4.99x10-4), and retrosplenial cortex (r = 0.63, p =

0.07 with a slope of 0.004). The piriform cortex had the highest correlation coefficient of 0.96 followed by the cerebral cortex and medial amygdala with a correlation coefficient of 0.86.

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A Cerebral Cortex B Medial Amygdala C Piriform Cortex a 12 b 12 c 12

10 10 10

8 8 8 (1/s) (1/s) (1/s)

2 6 2 6 2 6 R R R 4 r = 0.86 4 r = 0.86 4 r = 0.96 p = 0.003 p = 0.003 p < 0.001 2 y = 0.2179x – 0.335 2 y = 0.084x + 0.222 2 y = 0.0709x + 2.055

0 0 0 0 20 40 60 80 100 0 20 40 60 80 100 0 20 40 60 80 100 Neurodegeneration (%) Neurodegeneration (%) Neurodegeneration (%)

Figure 5.5: Effect of soman-induced seizures on the rate of relaxation (R2) correlated to the percentage of neurodegeneration in the cerebral cortex, medial amygdala, and piriform cortex. A-C, significant correlation was found in the cerebral cortex (r = 0.86, p = 0.003), medial thalamus (r = 0.86, p = 0.003), and piriform cortex (r = 0.96, p < 0.001). Each point represents one rat.

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A Basolateral Amygdala B Dorsolateral Thalamus C Medial Thalamus D Retrosplenial Cortex a 12 b 12 c 12 d 12

10 10 10 10

8 8 8 8 (1/s) (1/s) (1/s) (1/s) 2 2 2 6 6 6 2 6 R R R R 4 4 4 4 r = 0.07 r = 0.76 r = 0.78 r = 0.63 p = 0.87 p = 0.02 p = 0.014 p = 0.07 2 y = 0.0047x + 7.703 2 y = 0.1078x - 1.913 2 y = 0.0717x + 2.153 2 y = 0.0457x - 0.021

0 0 0 0 0 20 40 60 80 100 0 20 40 60 80 100 0 20 40 60 80 100 0 20 40 60 80 100 Neurodegeneration (%) Neurodegeneration (%) Neurodegeneration (%) Neurodegeneration (%) A Basolateral Amygdala B Dorsolateral Thalamus C Medial Thalamus D Retrosplenial Cortex a 12 b 12 c 12 d 12

10 10 10 10

0 0 0 0 0 20 40 60 80 100 0 20 40 60 80 100 0 20 40 60 80 100 0 20 40 60 80 100 Neurodegeneration (%) Neurodegeneration (%) Neurodegeneration (%) Neurodegeneration (%) Figure 5.5, supplement 1: The rate of relaxation (R2) was compared to the percentage of neurodegeneration in the basolateral amygdala, dorsolateral thalamus, medial thalamus, and retrosplenial cortex. A-D, there was no significant correlation in the basolateral amygdala (r = 0.07, p = 0.87), and retrosplenial cortex (r = 0.63, p = 0.07). There was a significant correlation in the dorsolateral thalamus (r = 0.76, p = 0.02), and medial thalamus (r = 0.78, p = 0.014). Each point represents a rat.

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A potential challenge in predictive MRI is the inter-subject variability. The heterogeneity of T2 relaxation times in the baseline was within 2 ms in each brain region, which is a coefficient of variation of less than 6%. At 1 hour after soman exposure, when no neurodegeneration was observed, the standard deviation was 2.2 ms, which is a coefficient of variation less than 5%.

When high levels of neurodegeneration were noted, at 18-24 hours after soman, the standard deviation was 13.4 ms, with a coefficient of variation of 16%.

5.4 Discussion

T2 has been widely used in MRI to detect major changes in water content and tissue pathophysiology in preclinical models such as cancer (Ali et al., 2015; Blasiak et al., 2010) and stroke (Hoehn-Berlage, Eis, Back, Kohno, & Yamashita, 1995; van Dorsten et al., 2002). Much of the previous T2 related literature quantifies T2 using less than seven echo times to describe a relaxation curve following soman exposure (Bhagat et al., 2001; Bhagat et al., 2005; Gullapalli et al., 2010). In order to quantify the T2 more accurately, more echoes were utilized to fit the decay curve. The brain is a heterogeneous structure mainly composed of water, lipids, and proteins.

The decay curve can be processed as a multiexponential function to describe different T2 components representative of the microstructures in the brain. The complex nature of the different water environments results in multiple T2 decay times within a single voxel. In utilizing a NNLS T2 fitting algorithm, the T2 decay curve can be separated into the respective water compartments that contribute to the total T2 signal. Analysis using NNLS algorithm is advantageous as it makes no assumptions a priori on the number of water compartments that make up the T2 decay curve (Kenneth P Whittall & MacKay, 1989). Therefore, rather than assuming a set number of water compartments through a few number of exponentials, NNLS can

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analyze relaxation data in a continuous model (Kenneth P Whittall & MacKay, 1989). Compared to a discrete spectrum a continuous spectrum considers slow and fast decaying protons in addition to intermediate decaying protons, which may arise from an interaction between compartments, (Zimmerman & Brittin, 1957) thereby better modelling biological samples. In a healthy brain with high signal to noise, three components are commonly seen, a short component associated with myelin water, a medium component associated with intra/extracellular water, and a long component associated with CSF (MacKay et al., 2006; MacKay et al., 1994; K. P.

Whittall et al., 1997) . Although a healthy brain can be accurately modelled with three components, in pathological states, having a large number of relaxation components can provide a more accurate overview on the changes in microstructures. For a discussion on the pros and cons of using NNLS see paper by Kenneth P Whittall and MacKay (1989).

In our study, we rarely saw a short T2 component in the grey matter. This component has been attributed to water interacting with myelin or myelin water fraction (K. P. Whittall et al.,

1997). It is common in animal studies to only detect one component in the grey matter. This is because of the low myelin content (MacKay et al., 1994). This study focused on detecting cerebral edema as well as the pathophysiology of tissue damage in the grey matter following soman exposure.

At 18-24 hours post-soman exposure, rats had cerebral edema and neurodegeneration in the amygdala, cerebral cortex, piriform cortex, and thalamus based on increases in T2. These findings correspond with previous studies where cerebral edema was observed 24 hours after

OP-induced seizures (Baille et al., 2005; Bhagat et al., 2001; Bhagat et al., 2005; Carpentier et al., 2008; Gullapalli et al., 2010; Rosman et al., 2012; Testylier et al., 2007) and is thought to be a combination of both cytotoxic and vasogenic edema (Carpentier et al., 2008). The edema

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following soman-induced seizures likely developed from the damage sustained through excitotoxicity (Guo et al., 2015; Lallement et al., 1993; Wade et al., 1987), oxidative stress

(Jacobsson et al., 1999; Pazdernik et al., 2001) and neuroinflammation (E. A. Johnson et al.,

2011; E. A. Johnson et al., 2015; E. A. Johnson & Kan, 2010). When the neurons are unable to recover from the damage, they undergo degeneration. This corresponds to our study where the edematous regions showed extensive neurodegeneration using FJC (Figure 5.3 and Figure 5.3 supplement 1). FJC staining was used to assess neurodegeneration as this stain shows specificity towards degenerating neurons (Schmued et al., 2005). Normalization using NeuN has shown the piriform cortex to have the highest level of neurodegeneration, which is similar to what was observed using qT2. Therefore, we speculate that the extent of neurodegeneration may mediate cerebral edema.

T2 is often used as a marker of edema but it also shows changes in cell pathophysiology.

The strong correlation with FJC indicates that either edema strongly correlates with neurodegeneration or that T2 is detecting changes from two processes, cell integrity and edema.

Regardless, qT2 is proving to be a sensitive metric of neurodegeneration associated with edema.

Based on a study using sarin, changes in the BBB occurs as early as 2 hours but leakage does not occur until 24 hours (Abdel-Rahman et al., 2002). The severity of localized BBB disruption may be proportional to the inflammatory cytokines released from degenerating neurons following soman-induced seizures. Cytokine release including interleukin (IL)-6, IL-1 α, IL-1 β, and tumor necrosis factor- α following soman-induced seizures (E. A. Johnson & Kan, 2010; Spradling,

Lumley, Robison, Meyerhoff, & Dillman, 2011) were found to increase the permeability of the

BBB (de Vries et al., 1996). The increased permeability may allow neutrophil infiltration, which can further exacerbate the initial injury and cause BBB leakage. The piriform cortex was shown

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to have a high number of neutrophil infiltrations at 24 hours following soman-induced seizures

(E. A. Johnson et al., 2011) which matches the time point where vasogenic edema is expected to occur. A study using a nerve agent substitute, diisopropyl fluorophosphate, found a correlation between diffusion MRI (apparent diffusion coefficient) and neuronal necrosis and neuroinflammation (Hobson et al., 2017). Thus, the vasogenic edema that we observed at 18-24 hours may be mediated through neuroinflammation. As a result, we were able to demonstrate that qT2 was able to detect the severity of neurodegeneration non-invasively.

The high degree of correlation between R2 and neurodegeneration following soman exposure demonstrates the feasibility of qT2 MRI as a marker of injury (Figure 5.5 and Figure

5.5, supplement 1). The cerebral cortex, medial amygdala, and piriform cortex showed consistent pathology with T2 (Figure 5.3 and Figure 5.3 supplement 1) and histology (Figure 5.4 and Figure

5.4, supplement 1). However, there appears to be significant regional specificity of neurological damage following soman-induced seizures. In particular the piriform cortex had the highest correlation between R2 and percent neurodegeneration among the regions of interest (Figure

5.5c). The difference in the level of predictability may be due to the regional susceptibility to seizures or the time course for the development of neuropathology. The piriform cortex was speculated as the site of seizure onset following OP exposure (Zimmer et al., 1998) which may allow more time for edema to develop. This region has been shown to also play an important role in initiating and mediating seizure activity in rodents (Piredda & Gale, 1985). Based on qT2, regional differences in the pathophysiology post soman exposure, and changes in T2 that are proportional to the magnitude of neurodegeneration can be clearly detected. This method of imaging can be useful for diagnosis of nerve agent mediated brain injury, assessment of efficacy of novel treatments, and provide a critical time course of recovery.

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One might expect that the early time course of T2 could be predictive of long-term pathology. Prior to this study, the earliest time point following soman-induced seizures where T2 was measured was 3 hours 12,13 and 6 hours 32. No changes were reported (Bhagat et al., 2001;

Bhagat et al., 2005; Gullapalli et al., 2010). We also found no significant reduction in T2 1 hour after soman, although there was a trend in the cerebral cortex and basolateral amygdala.

Interestingly, a study in a febrile seizure model found a decrease in T2 in the basolateral amygdala two hours post seizures (Curran et al., 2018). A decrease in T2 in the basolateral amygdala was predictive of epileptogenesis (Curran et al., 2018). Spontaneous recurrent seizure have also been detected following soman exposure (de Araujo Furtado et al., 2010).

The decrease in T2 found in febrile seizure model may be due to hypoxia, which results in an increase in deoxyhemoglobin (Choy et al., 2014). We have previously found a decrease in cerebral blood flow throughout the brain 1-hour after soman exposure (Lee, Bohnert, Bouchard, et al., 2018). Despite such a decrease in cerebral blood flow either from neurovascular uncoupling (Scremin et al., 1991) or transient vasoconstriction (Farrell et al., 2016; Lee, Bohnert,

Wu, et al., 2018), T2 did not change. The growing evidence of physiological changes at this time point suggests that early changes in T2 may be difficult to detect.

The present study demonstrates the value of qT2 MRI as a marker for neurodegeneration following OP exposure. The extent of neurodegeneration from seizures are often difficult to determine as the pathologies are transient. MRI non-invasive characteristics has the advantage that it could be undertaken over a time course which would help describe regional progression of injury. We suggest that qT2 MRI, as a non-invasive assessment of acute OP toxicity, has the potential to be a paradigm for determining the effectiveness of treatments aimed at reducing OP related neuropathology. Previous studies have found the neurodegeneration to be the highest at

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24 hours following OP exposure (Baille et al., 2005). Therefore, reducing damage within that time frame may be critical in the prevention of long-term pathologies including the development of spontaneous recurrent seizures (Bar-Klein et al., 2017; de Araujo Furtado et al., 2010).

Another area of interest may lie in the translational value of the results as a diagnostic marker. The similar symptomology of nerve agents with both cyanide poisoning and opioid overdose makes diagnosis difficult, especially when time is a critical factor (Ciottone, 2018). In our results, we found the high level of changes in the piriform cortex. A closely related structure to the piriform cortex is the insular cortex in human. Victims of the 1995 Tokyo subway sarin attack had decreased brain volume in the insular and temporal cortex, five to six years following the attack (Yamasue et al., 2007). A recent report on the Havana Syndrome, which suspects OP insecticide exposure, has found BBB leakage in the insular cortex (Friedman et al., 2019). Both of these studies were conducted using MRI and detected subtle changes. Therefore, we propose that detecting localized damage in the insular cortex using qT2 MRI may help clinicians to identify acute OP toxicity.

In the future, qT2 MRI should be used to acquire additional time points to elucidate the development of OP related neuropathology over time including both short- and long-term changes. Additionally, the development of neurodegeneration should be compared with other physiological measures including, seizure duration, serum acetylcholinesterase, cerebral blood flow, tissue oxygenation, and BBB leakage.

Using qT2 MRI, we demonstrated that T2 relaxation time was correlated to neurodegeneration following soman exposure. At 18- 24 hours after soman, we found that an increase in T2, which is indicative of cerebral edema, correlated with neurodegeneration.

Although correlations were seen in many different regions, we found the highest correlation in

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the cerebral cortex, medial amygdala, and piriform cortex. The high degree of correlation and consistency of T2 relaxation time provide evidence that qT2 could be used as a biomarker for civilian and military personnel for nerve agent exposure.

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Chapter 6 General Discussion

6.1 Thesis progression

Current research efforts have been focused on developing and testing new treatments.

However, without proper understanding of how NA pathology is induced, we will be unable to

(1) produce effective treatment protocols as we (2) will not fully understand what to counteract.

Therefore, the main objective of this thesis was to deepen the current understanding behind soman-related neurological damage. In Chapter 2, there are multiple mechanisms discussed that co-contribute to the development of neurological damage following NA exposure. Neurovascular involvement has not been thoroughly investigated following soman-induced seizures. The increasing evidence of neurovascular abnormality in seizures have renewed our interest.

Thereby, the work in Chapter 3 and Chapter 4 attempts to rekindle the interest of the neurovascular involvement in NA related neuropathology. Chapter 5 follows how MRI was utilized in identifying the severity of neurodegeneration in an attempt to guide future research efforts during treatment development.

Chapter 3 of the thesis covered changes in cortical and hippocampal pO2 measurements following soman-induced seizures using chronically implanted oxygen sensors in awake and freely moving rats. The time course pO2 data during the first hour changes with initiation and propagation of seizures. Almost immediately after soman injection an increase in pO2 was recorded, followed by a subsequent dip in pO2, which was ultimately superseded by a secondary increase. A physiological explanation for the initial increase in pO2 is that the brain is likely in a state of hyperexcitability. Soman inhibits AChE, which will cause an accumulation of ACh in the synapses, leading to sustained firing of cholinergic neurons. The secondary increase in pO2 may be from cholinergic neurons recruiting glutamatergic neurons, further increasing metabolic

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demand and CBF due to autoregulatory processes. The autoregulatory processes appears to be momentarily disrupted at or near onset of seizures. In an absence seizure model, small dips in cortical oxygenation was predictive of seizures onset (Farrell, Greba, Snutch, Howland, &

Teskey, 2018). In our study, the overt decrease in pO2 may be due to the severity of seizure. A consistent dip in pO2 is observed that may be the result of vasoconstriction (Zhao et al., 2011) along with a concurrent increase in metabolic demand. In a focal seizure model, vasoconstriction preceded in regions surrounding the seizure onset site, which may indicate the redirection of blood flow (Zhao et al., 2011). Similar mechanisms may occur following soman exposure because soman-induced seizures involve the whole brain and are defined as secondary generalized tonic-clonic seizures, which may cause the vasoconstriction to be more diffuse.

Momentary disruption in the autoregulatory processes may continue past the initial dip, where oscillating changes in pO2 is seen, which we attribute to status epilepticus. A study has shown subsequent seizures causes failure in the vasodilatory mechanisms leading to momentary decrease in pO2 (O. Prager et al., 2019). Hyperoxygenation was measured following soman, which was consistent with other status epilepticus models (Wolff et al., 2020).

Our goal in Chapter 4 was to investigate the neurovascular relationship between CBF and

CMRO2 following soman. Contrary to our pO2 findings in Chapter 3, where we found hyperoxia, global restriction of CBF (CASL-HASTE MRI) and normoxia (fiber-optic oxygen sensors) was observed 1.5-hours after soman exposure. Although anaesthesia changes metabolism and blood flow, the coupling between were shown to be preserved (Lenz et al.,

1998). Our observation of normoxia and hypoperfusion may be from metabolic disruption due to oxidative stress (Jarrett et al., 2008; Rowley et al., 2015; Ryan et al., 2012) or damage to the neurovascular unit (Chapter 5) (Bar-Klein et al., 2017; Ryu et al., 2013). Another possible cause

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behind our observation is the anti-seizure properties of isoflurane (Prasad, Krishnan, Sequeira, &

Al-Roomi, 2014; Tasker & Vitali, 2014). Whether the change in CBF does have a role in exacerbating the neurological damage following soman remains to be investigated. However,

CBF does not remain restricted. At 24 hours after exposure, reperfusion was seen in most of the brain except for the piriform network. Unsurprisingly, the region with hypoperfusion was associated with cerebral edema and neurodegeneration.

Neurodegeneration was indeed observed as shown in Chapter 5, where we found that cerebral edema - which was imaged using qT2 18-24 hours following soman exposure - correlated with the severity of neurodegeneration. The region that showed the most severe neurodegeneration, the piriform cortex, also had extensive cerebral edema and hypoperfusion. At

18-24 hours, assessment of microstructural environment in the piriform cortex following soman exposure has shown significant changes in T2, indicating cerebral edema. Based on the current data, the role of hypoperfusion in neurodegeneration remains uncertain as we do not know if hypoperfusion is a cause or consequence of damage. If there truly was damage in the neurovascular unit, which has been previously observed (Abdel-Rahman et al., 2002; Bar-Klein et al., 2017), hypoperfusion may be a consequence of the associated damage. Damaged neurons and astrocyte may not be able to generate vasodilatory messengers or mural cells may not respond to vasoactive messengers. Therapies that can restore blood flow may prevent further damage. However, if hypoperfusion at 24 hours was an underlying cause of neurodegeneration where oxygen supply cannot meet metabolic demand, including therapies that restore blood flow should be considered at an early timepoint. There is a likelihood that pathophysiological conditions are interrelated and creates a vicious cycle. However, the interconnection between

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pathophysiology following soman may allow for an indirect assessment of neurological damage which can guide future therapies.

The Defence Research and Development Canada (DRDC) was interested in finding a method to quantify neurological damage using MRI- with intent of using this to determine treatment efficacy in future studies. We were able to satisfy the DRDC’s interest using qT2 MRI, which correlated to a histological marker of neurodegeneration, FluoroJade-C. Although we found heterogeneity between brain regions in the correlation, we believe the piriform cortex, cerebral cortex, and medial amygdala are important regions to assess the efficacy of new treatments at 24 hours. A study using DFP found diffusion MRI to be correlated to neuroinflammation and neuronal necrosis (Hobson et al., 2017) suggesting the mechanism that drives the correlation may be linked to neuroinflammation. At 24 hours following soman exposure, peak level of neuroinflammatory markers including IL-1 alpha, IL-1 beta, IL-6 and

TNF-alpha were found (E. A. Johnson & Kan, 2010), which have the ability to increase permeability of the BBB (Rochfort, Collins, McLoughlin, & Cummins, 2016; Wang et al., 2014).

The severity of BBB disruption may be proportional to cytokines released in response to neuronal damage. Therefore, using qT2 MRI that is sensitive towards water content in microstructures, we were able to identify a method to measure the severity of neurodegeneration following soman exposure.

Overall, I believe this thesis provides a foundation for future studies to investigate the changes in neurovascular mechanisms and influence on neurological damage following NA exposure. Furthermore, studies can also use qT2 MRI to determine the neuroprotective properties of new treatments.

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6.2 Significance

The findings from this thesis have several significant impacts on organophosphate research as well as in the field of epilepsy. The development and application of multi-modal methods in measuring soman-induced physiological changes is crucial in animal studies of NA and seizures. Invasive chronically implanted oxygen sensors can provide in vivo real-time physiological data on brain oxygenation which is an indirect measure of CBF and metabolism in awake and freely moving rats. Measuring these parameters is especially beneficial because introducing an anaesthetic or restraint can change physiological response. These oxygen sensors can be combined with various techniques including EEG, laser doppler flowmetry, and MRI.

Simultaneous measurement can determine changes in the neurovascular relationship. This will determine potential causes to the neuropathology and also allow drug trials to correct for the disruption in the neurovascular relationship.

The distinctive changes in oxygenation previously seen in the motor cortex can provide support for developing near-infrared spectroscopy headgear to monitor NA exposure. A major concern of the military is sending in troops into an area with potential exposure to nerve agents.

If people are exposed, and appropriate treatments are not administered in time, the possibility of long-term neurological damage becomes likely. Hence, understanding mechanisms of injury should help with developing targeted treatments. The distinctive changes in oxygenation we saw in Chapter 3 suggest measuring oxygenation changes in the motor cortex may be a viable clue for understanding the underlying physiology. It may also be a biomarker for determining if someone is exposed to nerve agents and eliminating the uncertainty in administering treatments.

Determining neurological structural and physiological changes using MRI in response to soman induced seizures is important for discovering biomarkers. It is also a major interest of the

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DRDC. An area of damage that is commonly found in animal models include the piriform cortex

(Apland et al., 2010; Baille et al., 2005; Hayward et al., 1990; Kadar et al., 1992; Lemercier et al., 1983). In human, the insular cortex has been found to be damaged in victims of Tokyo subway sarin attack (Yamasue et al., 2007) and Canadian diplomats who were exposed to insecticides in Cuba (Friedman et al., 2019). NAs have the tendency to hydrolyze quickly in the environment and require extensive investigation by the United Nation and Organization for the prohibition of Chemical Weapons to determine if they have been used in an attack. A structural biomarker that can be detected non-invasively can provide essential information. In addition, biomarkers in animal models can also be used to determine the treatment response of potential therapies. A relationship can be used to observe whether the neurophysiological changes following soman-induced convulsive seizures contribute to neurological damage. Furthermore, this relationship can be used to examine if preventing those neurophysiological changes will reduce the neuropathology.

Lastly, understanding the neuropathology following soman-induced convulsive seizures is translatable to epilepsy. Soman induced seizures are complicated to treat and novel neuroprotectants aimed at treating status epilepticus and spontaneous recurrent seizures can be valuable in epilepsy patients.

6.3 Outstanding Questions and Future Directions

The thesis sets up a foundation for multiple future studies to better understand and protect the brain against NA exposure. Having the experience and knowledge I now have, there are parts of the thesis I would have done differently.

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Before starting the oxygenation study, I would have used pimonidazole to identify spatial and temporal locality of hypoxia following soman exposure. Pimonidazole is a histological marker for hypoxia (Aguilera & Brekken, 2014; Chapman, Franko, & Sharplin, 1981; Hockel &

Vaupel, 2001) and staining rats at different time points would have provided a more targeted approach in the probe placement. The piriform cortex has always been an area of major interest because it is the seizure onset site following NA exposure (Myhrer, 2007; Zimmer et al., 1998).

In Chapter 4, restricted CBF was found throughout the brain after soman exposure. Building on this, at 24 hours reperfusion was observed in most areas except for the piriform network. Given the findings from Chapter 5, extensive neurodegeneration has occurred by 24 hours. A study using implantable oxygen probe in the piriform cortex would be of great interest to map out changes in hemodynamics overtime.

One limitation in the study is the use of isoflurane anaesthesia due to the anti-seizure

(Prasad et al., 2014; Tasker & Vitali, 2014) and neuroprotective properties (Bar-Klein et al.,

2016; Krishnan et al., 2017), which can reduce the severity of neurological damage following soman exposure. Additionally, isoflurane has a known effect on CBF and CMRO2 (Lenz et al.,

1998) that may affect physiological response to soman exposure. The physiological changes and neurological damage under isoflurane may not be an accurate representation. Fortunately, in order to maximize the neurological damage following soman, I took the neuroprotective effect into account and immediately perfused the rats after imaging. However, in terms of anti-seizure properties and physiological changes, the effects from isoflurane cannot be fully discounted.

Given the importance of anaesthesia in MRI related studies, there will always be a trade-off where anaesthesia will have some effect on the pathophysiology. Understanding the effects of anaesthesia and minimizing potential confounding factors should be a priority going forward. On

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that note, it would be beneficial to use a different anaesthetic including urethane and dexmedetomidine following soman exposure. Additionally, rather than placing rats under anaesthesia, a sedating dose may be more beneficial in mimicking normal physiological conditions.

Collaborators at DRDC Suffield have found high dose scopolamine (0.5 mg/kg; intramuscular) to be effective at increasing survival and terminating NA-induced seizures.

Previous studies have also shown the effectiveness of scopolamine (D. Anderson et al., 1994; D.

R. Anderson et al., 1997; Capacio & Shih, 1991; Harris et al., 1994; Raveh et al., 2002;

Wetherell, Hall, & Passingham, 2002). Scopolamine is an anti-cholinergic and competitively binds to muscarinic receptors (Renner, Oertel, & Kirch, 2005). Similar to atropine, scopolamine prevents the binding of acetylcholine thereby reducing cholinergic overstimulation following NA exposure. Unlike atropine, scopolamine can readily cross the BBB and have higher central potency (Ketchum, Sidell, Crowell, Aghajanian, & Hayes, 1973; Parkes, 1965; Pradhan & Roth,

1968; Samuel et al., 1965). To examine the efficacy of scopolamine, quantitative T2 MRI

(described in Chapter 5) can be used to determine the neuroprotective properties when rats are exposed to soman. Additionally, going forward, mimicking real-life scenarios where treatments are delayed will also be an important. Currently, extensive research is taking place in finding the right “cocktail” to treat NA exposure as no single treatment is effective. Hence the pharmacokinetic interactions with conventional treatment (HI-6 DMS, atropine sulfate, and diazepam) and potential new treatments (procyclidine, levetiracetam, cyclopentyladenosine, allopregnanolone, and perampanel) needs to be carefully considered.

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6.5 Conclusion

In summary, we have shown there may be abnormal vasodynamics following soman exposure. Either soman or a combination of soman and isoflurane may cause restriction of CBF in the brain with the effects potentially lasting until 24 hours. Whether these changes have a direct link to structural changes remains to be investigated. However, at 18-24 hours using qT2

MRI, we present evidence of microstructural changes after soman exposure which correlates to the severity of neurodegeneration. This thesis highlights the hemodynamic changes following soman exposure that was never seen before and draws a potential link to the development of neurodegeneration. Finally, we also underline how qT2 MRI can be used to determine the severity of neurodegeneration and determine the efficacy of new treatments.

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Permission to reproduce: Lee, K., Bohnert, S., Wu, Y., Vair, C., Mikler, J., Teskey, G. C., & Dunn, J. F. (2018). Assessment of brain oxygenation imbalance following soman exposure in rats. Neurotoxicology, 65, 28-37. doi:10.1016/j.neuro.2018.01.007

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Copyright permission for: Lee, K., Bohnert, S., Bouchard, M., Vair, C., Farrell, J. S., Teskey, G. C., Mikler, M., Dunn, J. F. (2020). Quantitative T2 MRI is predictive of neurodegeneration following organophosphate exposure in a rat model. Sci Rep, 10(1), 13007. doi:10.1038/s41598-020- 69991-z

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