Potassium Channels As Tumour Markers
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Ion Channels 3 1
r r r Cell Signalling Biology Michael J. Berridge Module 3 Ion Channels 3 1 Module 3 Ion Channels Synopsis Ion channels have two main signalling functions: either they can generate second messengers or they can function as effectors by responding to such messengers. Their role in signal generation is mainly centred on the Ca2 + signalling pathway, which has a large number of Ca2+ entry channels and internal Ca2+ release channels, both of which contribute to the generation of Ca2 + signals. Ion channels are also important effectors in that they mediate the action of different intracellular signalling pathways. There are a large number of K+ channels and many of these function in different + aspects of cell signalling. The voltage-dependent K (KV) channels regulate membrane potential and + excitability. The inward rectifier K (Kir) channel family has a number of important groups of channels + + such as the G protein-gated inward rectifier K (GIRK) channels and the ATP-sensitive K (KATP) + + channels. The two-pore domain K (K2P) channels are responsible for the large background K current. Some of the actions of Ca2 + are carried out by Ca2+-sensitive K+ channels and Ca2+-sensitive Cl − channels. The latter are members of a large group of chloride channels and transporters with multiple functions. There is a large family of ATP-binding cassette (ABC) transporters some of which have a signalling role in that they extrude signalling components from the cell. One of the ABC transporters is the cystic − − fibrosis transmembrane conductance regulator (CFTR) that conducts anions (Cl and HCO3 )and contributes to the osmotic gradient for the parallel flow of water in various transporting epithelia. -
Spatial Distribution of Leading Pacemaker Sites in the Normal, Intact Rat Sinoa
Supplementary Material Supplementary Figure 1: Spatial distribution of leading pacemaker sites in the normal, intact rat sinoatrial 5 nodes (SAN) plotted along a normalized y-axis between the superior vena cava (SVC) and inferior vena 6 cava (IVC) and a scaled x-axis in millimeters (n = 8). Colors correspond to treatment condition (black: 7 baseline, blue: 100 µM Acetylcholine (ACh), red: 500 nM Isoproterenol (ISO)). 1 Supplementary Figure 2: Spatial distribution of leading pacemaker sites before and after surgical 3 separation of the rat SAN (n = 5). Top: Intact SAN preparations with leading pacemaker sites plotted during 4 baseline conditions. Bottom: Surgically cut SAN preparations with leading pacemaker sites plotted during 5 baseline conditions (black) and exposure to pharmacological stimulation (blue: 100 µM ACh, red: 500 nM 6 ISO). 2 a &DUGLDFIoQChDQQHOV .FQM FOXVWHU &DFQDG &DFQDK *MD &DFQJ .FQLS .FQG .FQK .FQM &DFQDF &DFQE .FQM í $WSD .FQD .FQM í .FQN &DVT 5\U .FQM &DFQJ &DFQDG ,WSU 6FQD &DFQDG .FQQ &DFQDJ &DFQDG .FQD .FQT 6FQD 3OQ 6FQD +FQ *MD ,WSU 6FQE +FQ *MG .FQN .FQQ .FQN .FQD .FQE .FQQ +FQ &DFQDD &DFQE &DOP .FQM .FQD .FQN .FQG .FQN &DOP 6FQD .FQD 6FQE 6FQD 6FQD ,WSU +FQ 6FQD 5\U 6FQD 6FQE 6FQD .FQQ .FQH 6FQD &DFQE 6FQE .FQM FOXVWHU V6$1 L6$1 5$ /$ 3 b &DUGLDFReFHSWRUV $GUDF FOXVWHU $GUDD &DY &KUQE &KUP &KJD 0\O 3GHG &KUQD $GUE $GUDG &KUQE 5JV í 9LS $GUDE 7SP í 5JV 7QQF 3GHE 0\K $GUE *QDL $QN $GUDD $QN $QN &KUP $GUDE $NDS $WSE 5DPS &KUP 0\O &KUQD 6UF &KUQH $GUE &KUQD FOXVWHU V6$1 L6$1 5$ /$ 4 c 1HXURQDOPURWHLQV -
Ion Channels
UC Davis UC Davis Previously Published Works Title THE CONCISE GUIDE TO PHARMACOLOGY 2019/20: Ion channels. Permalink https://escholarship.org/uc/item/1442g5hg Journal British journal of pharmacology, 176 Suppl 1(S1) ISSN 0007-1188 Authors Alexander, Stephen PH Mathie, Alistair Peters, John A et al. Publication Date 2019-12-01 DOI 10.1111/bph.14749 License https://creativecommons.org/licenses/by/4.0/ 4.0 Peer reviewed eScholarship.org Powered by the California Digital Library University of California S.P.H. Alexander et al. The Concise Guide to PHARMACOLOGY 2019/20: Ion channels. British Journal of Pharmacology (2019) 176, S142–S228 THE CONCISE GUIDE TO PHARMACOLOGY 2019/20: Ion channels Stephen PH Alexander1 , Alistair Mathie2 ,JohnAPeters3 , Emma L Veale2 , Jörg Striessnig4 , Eamonn Kelly5, Jane F Armstrong6 , Elena Faccenda6 ,SimonDHarding6 ,AdamJPawson6 , Joanna L Sharman6 , Christopher Southan6 , Jamie A Davies6 and CGTP Collaborators 1School of Life Sciences, University of Nottingham Medical School, Nottingham, NG7 2UH, UK 2Medway School of Pharmacy, The Universities of Greenwich and Kent at Medway, Anson Building, Central Avenue, Chatham Maritime, Chatham, Kent, ME4 4TB, UK 3Neuroscience Division, Medical Education Institute, Ninewells Hospital and Medical School, University of Dundee, Dundee, DD1 9SY, UK 4Pharmacology and Toxicology, Institute of Pharmacy, University of Innsbruck, A-6020 Innsbruck, Austria 5School of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, BS8 1TD, UK 6Centre for Discovery Brain Science, University of Edinburgh, Edinburgh, EH8 9XD, UK Abstract The Concise Guide to PHARMACOLOGY 2019/20 is the fourth in this series of biennial publications. The Concise Guide provides concise overviews of the key properties of nearly 1800 human drug targets with an emphasis on selective pharmacology (where available), plus links to the open access knowledgebase source of drug targets and their ligands (www.guidetopharmacology.org), which provides more detailed views of target and ligand properties. -
Molecular Signatures Differentiate Immune States in Type 1 Diabetes Families
Page 1 of 65 Diabetes Molecular signatures differentiate immune states in Type 1 diabetes families Yi-Guang Chen1, Susanne M. Cabrera1, Shuang Jia1, Mary L. Kaldunski1, Joanna Kramer1, Sami Cheong2, Rhonda Geoffrey1, Mark F. Roethle1, Jeffrey E. Woodliff3, Carla J. Greenbaum4, Xujing Wang5, and Martin J. Hessner1 1The Max McGee National Research Center for Juvenile Diabetes, Children's Research Institute of Children's Hospital of Wisconsin, and Department of Pediatrics at the Medical College of Wisconsin Milwaukee, WI 53226, USA. 2The Department of Mathematical Sciences, University of Wisconsin-Milwaukee, Milwaukee, WI 53211, USA. 3Flow Cytometry & Cell Separation Facility, Bindley Bioscience Center, Purdue University, West Lafayette, IN 47907, USA. 4Diabetes Research Program, Benaroya Research Institute, Seattle, WA, 98101, USA. 5Systems Biology Center, the National Heart, Lung, and Blood Institute, the National Institutes of Health, Bethesda, MD 20824, USA. Corresponding author: Martin J. Hessner, Ph.D., The Department of Pediatrics, The Medical College of Wisconsin, Milwaukee, WI 53226, USA Tel: 011-1-414-955-4496; Fax: 011-1-414-955-6663; E-mail: [email protected]. Running title: Innate Inflammation in T1D Families Word count: 3999 Number of Tables: 1 Number of Figures: 7 1 For Peer Review Only Diabetes Publish Ahead of Print, published online April 23, 2014 Diabetes Page 2 of 65 ABSTRACT Mechanisms associated with Type 1 diabetes (T1D) development remain incompletely defined. Employing a sensitive array-based bioassay where patient plasma is used to induce transcriptional responses in healthy leukocytes, we previously reported disease-specific, partially IL-1 dependent, signatures associated with pre and recent onset (RO) T1D relative to unrelated healthy controls (uHC). -
S41598-019-42654-4.Pdf
www.nature.com/scientificreports OPEN Epigenome-wide Analysis Identifes Genes and Pathways Linked to Neurobehavioral Variation in Received: 22 November 2018 Accepted: 3 April 2019 Preterm Infants Published: xx xx xxxx Todd M. Everson1, Carmen J. Marsit1, T. Michael O’Shea2, Amber Burt 1, Karen Hermetz1, Brian S. Carter3, Jennifer Helderman4, Julie A. Hofeimer2, Elisabeth C. McGowan5, Charles R. Neal6, Steven L. Pastyrnak7, Lynne M. Smith8, Antoine Soliman 9, Sheri A. DellaGrotta10, Lynne M. Dansereau10, James F. Padbury5 & Barry M. Lester5,10,11 Neonatal molecular biomarkers of neurobehavioral responses (measures of brain-behavior relationships), when combined with neurobehavioral performance measures, could lead to better predictions of long-term developmental outcomes. To this end, we examined whether variability in buccal cell DNA methylation (DNAm) associated with neurobehavioral profles in a cohort of infants born less than 30 weeks postmenstrual age (PMA) and participating in the Neonatal Neurobehavior and Outcomes in Very Preterm Infants (NOVI) Study (N = 536). We tested whether epigenetic age, age acceleration, or DNAm levels at individual loci difered between infants based on their NICU Network Neurobehavioral Scale (NNNS) profle classifcations. We adjusted for recruitment site, infant sex, PMA, and tissue heterogeneity. Infants with an optimally well-regulated NNNS profle had older epigenetic age compared to other NOVI infants (β1 = 0.201, p-value = 0.026), but no signifcant diference in age acceleration. In contrast, infants with an atypical NNNS profle had diferential methylation at 29 CpG sites (FDR < 10%). Some of the genes annotated to these CpGs included PLA2G4E, TRIM9, GRIK3, and MACROD2, which have previously been associated with neurological structure and function, or with neurobehavioral disorders. -
1 1 2 3 Cell Type-Specific Transcriptomics of Hypothalamic
1 2 3 4 Cell type-specific transcriptomics of hypothalamic energy-sensing neuron responses to 5 weight-loss 6 7 Fredrick E. Henry1,†, Ken Sugino1,†, Adam Tozer2, Tiago Branco2, Scott M. Sternson1,* 8 9 1Janelia Research Campus, Howard Hughes Medical Institute, 19700 Helix Drive, Ashburn, VA 10 20147, USA. 11 2Division of Neurobiology, Medical Research Council Laboratory of Molecular Biology, 12 Cambridge CB2 0QH, UK 13 14 †Co-first author 15 *Correspondence to: [email protected] 16 Phone: 571-209-4103 17 18 Authors have no competing interests 19 1 20 Abstract 21 Molecular and cellular processes in neurons are critical for sensing and responding to energy 22 deficit states, such as during weight-loss. AGRP neurons are a key hypothalamic population 23 that is activated during energy deficit and increases appetite and weight-gain. Cell type-specific 24 transcriptomics can be used to identify pathways that counteract weight-loss, and here we 25 report high-quality gene expression profiles of AGRP neurons from well-fed and food-deprived 26 young adult mice. For comparison, we also analyzed POMC neurons, an intermingled 27 population that suppresses appetite and body weight. We find that AGRP neurons are 28 considerably more sensitive to energy deficit than POMC neurons. Furthermore, we identify cell 29 type-specific pathways involving endoplasmic reticulum-stress, circadian signaling, ion 30 channels, neuropeptides, and receptors. Combined with methods to validate and manipulate 31 these pathways, this resource greatly expands molecular insight into neuronal regulation of 32 body weight, and may be useful for devising therapeutic strategies for obesity and eating 33 disorders. -
KCNA3 Antibody / Kv1.3 (R32012)
KCNA3 Antibody / Kv1.3 (R32012) Catalog No. Formulation Size R32012 0.5mg/ml if reconstituted with 0.2ml sterile DI water 100 ug Bulk quote request Availability 1-3 business days Species Reactivity Human, Mouse, Rat Format Antigen affinity purified Clonality Polyclonal (rabbit origin) Isotype Rabbit IgG Purity Antigen affinity Buffer Lyophilized from 1X PBS with 2.5% BSA and 0.025% sodium azide UniProt P22001 Applications Western blot : 0.1-0.5ug/ml Limitations This KCNA3 antibody is available for research use only. Western blot testing of 1) rat brain, 2) mouse brain, human 3) K562, 4) HeLa and 5) 22RV1 lysate with KCNA3 antibody. Expected molecular weight ~64 kDa, observed here at ~55 kDa. Description Potassium voltage-gated channel, shaker-related subfamily, member 3, also known as KCNA3 or Kv1.3, is a protein that in humans is encoded by the KCNA3 gene. This gene encodes a member of the potassium channel, voltage-gated, shaker-related subfamily. This member contains six membrane-spanning domains with a shaker-type repeat in the fourth segment. It belongs to the delayed rectifier class, members of which allow nerve cells to efficiently repolarize following an action potential. It plays an essential role in T-cell proliferation and activation. This gene appears to be intronless and it is clustered together with KCNA2 and KCNA10 genes on chromosome 1. And Kv1.3 has been reported to be expressed in the inner mitochondrial membrane in lymphocytes. The apoptotic protein Bax has been suggested to insert into theouter mitochondrial membrane and occlude the pore of Kv1.3 via a lysine residue. -
Graded Co-Expression of Ion Channel, Neurofilament, and Synaptic Genes in Fast- Spiking Vestibular Nucleus Neurons
Research Articles: Cellular/Molecular Graded co-expression of ion channel, neurofilament, and synaptic genes in fast- spiking vestibular nucleus neurons https://doi.org/10.1523/JNEUROSCI.1500-19.2019 Cite as: J. Neurosci 2019; 10.1523/JNEUROSCI.1500-19.2019 Received: 26 June 2019 Revised: 11 October 2019 Accepted: 25 October 2019 This Early Release article has been peer-reviewed and accepted, but has not been through the composition and copyediting processes. The final version may differ slightly in style or formatting and will contain links to any extended data. Alerts: Sign up at www.jneurosci.org/alerts to receive customized email alerts when the fully formatted version of this article is published. Copyright © 2019 the authors 1 Graded co-expression of ion channel, neurofilament, and synaptic genes in fast-spiking 2 vestibular nucleus neurons 3 4 Abbreviated title: A fast-spiking gene module 5 6 Takashi Kodama1, 2, 3, Aryn Gittis, 3, 4, 5, Minyoung Shin2, Keith Kelleher2, 3, Kristine Kolkman3, 4, 7 Lauren McElvain3, 4, Minh Lam1, and Sascha du Lac1, 2, 3 8 9 1 Johns Hopkins University School of Medicine, Baltimore MD, 21205 10 2 Howard Hughes Medical Institute, La Jolla, CA, 92037 11 3 Salk Institute for Biological Studies, La Jolla, CA, 92037 12 4 Neurosciences Graduate Program, University of California San Diego, La Jolla, CA, 92037 13 5 Carnegie Mellon University, Pittsburgh, PA, 15213 14 15 Corresponding Authors: 16 Takashi Kodama ([email protected]) 17 Sascha du Lac ([email protected]) 18 Department of Otolaryngology-Head and Neck Surgery 19 The Johns Hopkins University School of Medicine 20 Ross Research Building 420, 720 Rutland Avenue, Baltimore, Maryland, 21205 21 22 23 Conflict of Interest 24 The authors declare no competing financial interests. -
Potassium Channels and Their Potential Roles in Substance Use Disorders
International Journal of Molecular Sciences Review Potassium Channels and Their Potential Roles in Substance Use Disorders Michael T. McCoy † , Subramaniam Jayanthi † and Jean Lud Cadet * Molecular Neuropsychiatry Research Branch, NIDA Intramural Research Program, Baltimore, MD 21224, USA; [email protected] (M.T.M.); [email protected] (S.J.) * Correspondence: [email protected]; Tel.: +1-443-740-2656 † Equal contributions (joint first authors). Abstract: Substance use disorders (SUDs) are ubiquitous throughout the world. However, much re- mains to be done to develop pharmacotherapies that are very efficacious because the focus has been mostly on using dopaminergic agents or opioid agonists. Herein we discuss the potential of using potassium channel activators in SUD treatment because evidence has accumulated to support a role of these channels in the effects of rewarding drugs. Potassium channels regulate neuronal action potential via effects on threshold, burst firing, and firing frequency. They are located in brain regions identified as important for the behavioral responses to rewarding drugs. In addition, their ex- pression profiles are influenced by administration of rewarding substances. Genetic studies have also implicated variants in genes that encode potassium channels. Importantly, administration of potassium agonists have been shown to reduce alcohol intake and to augment the behavioral effects of opioid drugs. Potassium channel expression is also increased in animals with reduced intake of methamphetamine. Together, these results support the idea of further investing in studies that focus on elucidating the role of potassium channels as targets for therapeutic interventions against SUDs. Keywords: alcohol; cocaine; methamphetamine; opioids; pharmacotherapy Citation: McCoy, M.T.; Jayanthi, S.; Cadet, J.L. -
Potassium Channel Modulators for the Treatment of Autoimmune Disorders
Potassium channel modulators for the treatment of autoimmune disorders 1 Autoimmune disorders . During normal immune responses white blood cells protect the body from antigens such as bacteria, viruses, toxins, cancer cells • The cellular immune system attacks infected cells with CD4 (helper) and CD8 (cytotoxic) T cells • The humoral system responds to bacteria and viruses by instigating attack by immunoglobulins produced by B cells . In patients with an autoimmune disorder the immune system cannot distinguish between foreign antigens and healthy tissue, resulting in destruction of tissue or abnormal growth patterns . Many different organ or tissue types may be affected • Blood vessels, connective tissue, nerves, joints, muscles, skin . More than 80 discrete autoimmune disorders have been identified . The aggregate prevalence of AI disorders is ~5000 per 100,000 • Incidence is higher in women than men . Different AI disorders have different molecular phenotypes 2 Autoimmune phenotypes Effector memory T cells and class switched B cells predominate Disease Target organ Autoreactive lymphocyte Psoriasis Skin CD45RO+CD45RA- CCR7- TEM cells Grave disease Thyroid IgD-IgG+ memory B cells Rheumatoid arthritis Joints CD28nullCD45RA-CCR7- TEM cells CD45RA- memory T cells Hashimoto disease Thyroid IgD-IgG+ memory B cells Vitiligo Skin, mucous membranes CD45RO+ memory T cells Crohns disease Digestive tract CD45RO+CD28null memory T cells Type I diabetes CD28 costimulation-independent memory T- Pancreas mellitus cells CD28 costimulation-independent Multiple sclerosis CNS CD45RO+CD45RA-CCR7- TEM cells IgD-CD27+ class-switched memory B cells 3 Prevalence of AI disorders 1600 1400 1200 1000 800 Prevalence of Autoimmune Diseases 600 400 200 (cases/100,000) 0 Psoriasis Grave disease Rheumatoid arthritis Hashimoto's disease Vitiligo IBD Type I diabetes (adults) Pernicious anemia Glomerulonephritis Multiple sclerosis System lupus erythematosis Primary systemic vasculitis Addison Disease . -
Prefrontal Co-Expression of Schizophrenia Risk Genes Is Associated with Treatment Response
bioRxiv preprint doi: https://doi.org/10.1101/323428; this version posted May 16, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 1 Title: Prefrontal co-expression of schizophrenia risk genes is associated with treatment response 2 in patients 3 4 One Sentence Summary: Schizophrenia risk genes co-expressed in the dorsolateral prefrontal cortex 5 are associated with clinical outcome in patients with schizophrenia. 6 7 Authors: Giulio Pergola1,†, Pasquale Di Carlo1,2,†, Andrew E. Jaffe2,3,4,5, Marco Papalino1, Qiang 8 Chen2, Thomas M. Hyde2,7,8, Joel E. Kleinman2,7, Joo Heon Shin2, Antonio Rampino1,10, Giuseppe 9 Blasi1,10, Daniel R. Weinberger2,6,8,9, Alessandro Bertolino1,10,* 10 11 Affiliations: 12 1Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense 13 Organs, University of Bari Aldo Moro, Bari, Italy 14 2Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland, 15 USA 16 3Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, 17 Maryland, USA 18 4Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, 19 USA 20 5Center for Computational Biology, Johns Hopkins University, Baltimore, Maryland, USA 21 6Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, Maryland, USA 22 7Department of Neurology, Johns Hopkins School of Medicine, Baltimore, 1 bioRxiv preprint doi: https://doi.org/10.1101/323428; this version posted May 16, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. -
Transcriptome Profiling Reveals the Complexity of Pirfenidone Effects in IPF
ERJ Express. Published on August 30, 2018 as doi: 10.1183/13993003.00564-2018 Early View Original article Transcriptome profiling reveals the complexity of pirfenidone effects in IPF Grazyna Kwapiszewska, Anna Gungl, Jochen Wilhelm, Leigh M. Marsh, Helene Thekkekara Puthenparampil, Katharina Sinn, Miroslava Didiasova, Walter Klepetko, Djuro Kosanovic, Ralph T. Schermuly, Lukasz Wujak, Benjamin Weiss, Liliana Schaefer, Marc Schneider, Michael Kreuter, Andrea Olschewski, Werner Seeger, Horst Olschewski, Malgorzata Wygrecka Please cite this article as: Kwapiszewska G, Gungl A, Wilhelm J, et al. Transcriptome profiling reveals the complexity of pirfenidone effects in IPF. Eur Respir J 2018; in press (https://doi.org/10.1183/13993003.00564-2018). This manuscript has recently been accepted for publication in the European Respiratory Journal. It is published here in its accepted form prior to copyediting and typesetting by our production team. After these production processes are complete and the authors have approved the resulting proofs, the article will move to the latest issue of the ERJ online. Copyright ©ERS 2018 Copyright 2018 by the European Respiratory Society. Transcriptome profiling reveals the complexity of pirfenidone effects in IPF Grazyna Kwapiszewska1,2, Anna Gungl2, Jochen Wilhelm3†, Leigh M. Marsh1, Helene Thekkekara Puthenparampil1, Katharina Sinn4, Miroslava Didiasova5, Walter Klepetko4, Djuro Kosanovic3, Ralph T. Schermuly3†, Lukasz Wujak5, Benjamin Weiss6, Liliana Schaefer7, Marc Schneider8†, Michael Kreuter8†, Andrea Olschewski1,