A STUDY OF BIOSENSORS: NOVEL APPLICATION AND NOVEL ELECTRODE
by
PO-YUAN (PAUL) LIN
Submitted in partial fulfillment of the requirements
For the degree of Doctor of Philosophy
Dissertation Advisor: Dr. Chung-Chiun Liu
Academic Advisor: Dr. James D. McGuffin-Cawley
Department of Materials Science and Engineering
CASE WESTERN RESERVE UNIVERSITY
May, 2013
0 CASE WESTERN RESERVE UNIVERSITY SCHOOL OF GRADUATE STUDIES
We hereby approve the thesis/dissertation of
Po-Yuan (Paul) Lin
Candidate for the Doctor of Philosophy degree*.
(signed) Prof. James D. McGuffin-Cawley (chair of the committee)
Prof. Chung-Chiun Liu
Prof. Mark R. DeGuire
Prof. Pirouz Pirouz
(date) March 7, 2013
*We also certify that written approval has been obtained for any proprietary material contained therein.
i
Table of Content
Table of Content ...... ii
List of Tables ...... iv
List of Figures ...... v
Abstract ...... viii
Part I: Background and Introduction ...... 1
Prostate Cancer ...... 1 Diagnosis Methods of Prostate Cancer ...... 3 Stages of Prostate Cancer and Treatments ...... 8 Biomarker Candidates ...... 9 Novel Prostate Cancer Biomarker, Alpha-Methylacyl-CoA Racemase ...... 13 AMACR Assay and Biosensor ...... 16 Methods of AMACR Detection ...... 16 Pristanic Acid ...... 20 Amperometric Biosensor ...... 26 Fabrication of Biosensor ...... 37 Ir-C Biosensor ...... 42 Experiments ...... 44
Enzyme Activity ...... 44 ACOX3 Reaction Time ...... 45 H2O2 Measurement ...... 46 AMACR Measurement ...... 47 AMACR in Blood Serum ...... 48 Hospital Samples ...... 49 Results and discussion ...... 51
H2O2 Measurement ...... 51 AMACR Measurement in PBS Solution ...... 55 ACOX3 Reaction Time ...... 58 AMACR Concentration Measurement ...... 60 SLC27A2 for the Reduction of Incubation Time ...... 62 AMACR Concentration Measurement in Serum ...... 64 Hospital Samples ...... 67 Conclusion ...... 70
Future Research ...... 71
ii
Part II: Background and Introduction ...... 73
Hydrogen Peroxide (H2O2) ...... 73 Applications of H2O2 ...... 74 Role of H2O2 in the Detection of Diseases ...... 75 Platinum ...... 76 Rotating Disk Electrode (RDE) ...... 81 Transmission Electron Microscope (TEM) ...... 84 Energy-Dispersive X-ray Spectroscopy (XEDS) ...... 85 Preparation of Pt/Ru Nanoparticle Catalyst ...... 86 Material Characterization ...... 87 Electrochemical Testing ...... 87 Results and Discussion ...... 89
Structure ...... 89 Electrochemical Characterization ...... 92 Conclusion ...... 102
Future work ...... 103
References ...... 104
iii
List of Tables
Table 1 Risk factors relevant to prostate cancer probability [7] ...... 3
Table 2 Side effects and complications of transrectal ultrasound-guided biopsy of
prostate[19] ...... 6
Table 3 Questions ...... 9
Table 4 Candidates of biomarkers for prostate cancer detection[27-29] ...... 12
Table 5 AMACR real-time RT-PCR results in peripheral blood specimens[30] ...... 14
Table 6 Sensitivity and average of standard deviation ...... 66
Table 7 Gleason scores and their representations ...... 66
Table 8 Population description and mean AMACR levels by patient group ...... 68
Table 9 Sensitivities of Pt, Ru and Pt-Ru at ηtotal = +0.2V and +0.4V versus Ag/AgCl 100
Table 10 Average standard deviation of Pt, Ru and Pt/Ru at ηtotal = +0.2V and +0.4V
versus Ag/AgCl reference electrode ...... 100
iv
List of Figures
Figure 1 Prostate location and structure[1] ...... 1
Figure 2 Age-specific rates of prostate cancer globally. (data taken in 2002)[5] ...... 2
Figure 3 Transrectal ultrasound-guided prostate biopsy[20] ...... 6
Figure 4 NIH grants from 1986 to 2009 in biomarker related fields[26] ...... 10
Figure 5 Enzyme lowering activation energy to accelerate a reaction[41] ...... 18
Figure 6 Schematic representation of the mechanism of an enzymatic reaction ...... 20
Figure 7 Pathway of pristanic acid formation from phytol.[46] ...... 22
Figure 8 Activation of fatty acid (acyl-CoA) ...... 24
Figure 9 Pathway of pristanic acid to pristanoyl-CoA[39] ...... 25
Figure 10 Schematic of the components of a biosensor ...... 27
Figure 11 Typical layout of an ion-selective sensor[58] ...... 29
Figure 12 Schematic of a impedance-based polymer coated electrode[60] ...... 30
Figure 13 Schematic of 3-electrode electrochemical cells ...... 33
Figure 14 Schematic diagram of H2O2 amperometric biosensor. Left: Side view; Right:
Plain view. Electrons flow from working electrode to counter electrode.
(note: The arrows represent the direction of electrons flow. The direction of
current flow is the exact opposite.) ...... 35
Figure 15 Procedures of the PVD process ...... 38
Figure 16 Steps of a thick-film screen printing process ...... 39
Figure 17 Schematic of a typical setup for inkjet printing technique[87] ...... 41
Figure 18 Screen-printed single-use, disposable Ir nano-catalyst contained H2O2 platform
biosensor prototype ...... 43
v
Figure 19 Activity of AMACR with respect to pH value [93] ...... 45
Figure 20 Cyclic voltammogram of H2O2 and PBS solution...... 51
Figure 21 Amperometric i-t curve measurement for H2O2 of different concentrations ... 52
Figure 22 Concentration versus oxidation current for H2O2 measurement ...... 54
Figure 23 Cyclic voltammograms of the current generated through the beta-oxidation
pathway (AMACR = 0.0065µg/µl). A comparison between the present and
absent of AMACR and/or ACOX3...... 56
Figure 24 Cyclic voltammograms of PBS + Pristanic Acid and PBS only ...... 57
Figure 25 Cyclic voltammograms of PBS + AMACR (0.0065µg/µl) and PBS only ...... 58
Figure 26 a) Sample vs. Current; b) Time vs. Current ...... 59
Figure 27 Linear relationship between current of the H2O2 generated through the beta-
oxidation pathway and the concentration of AMACR ...... 61
Figure 28 ACOX3 reaction time comparison a) 2 days vs. b) 11 days ...... 62
Figure 29 Comparing concentration versus oxidation current of samples a) with
SLC27A2 (1.5hours incubation); b) without SLC27A2 (1 day incubation) .... 63
Figure 30 Concentration vs. oxidation current of AMACR in serum ...... 65
Figure 31 Blind test results of patients’ plasma samples provided by University Hospitals.
a) Sample vs. Oxidation Current from biosensors; b) Sample vs. Concentration
of AMACR c) Concentration of AMACR vs. Oxidation Current from
Biosensor. (Note: Sample 10 is not available) ...... 69
Figure 32 Anthraquinone process of hydrogen peroxide production[104] ...... 74
Figure 33 Volcano plot of oxygen oxidation[127] ...... 80
Figure 34 Catalytic activity as a function of O and OH binding energy[127] ...... 80
vi
Figure 35 Schematic of a rotating disk electrode ...... 82
Figure 36 Nernst diffusion layer model ...... 84
Figure 37 TEM images of Pt nanoparticles. Figure 37b) is from the red square of a) .... 89
Figure 38 TEM images of Ru nanoparticles. Figure 38b) is from the red square of a) ... 90
Figure 39 TEM images of Pt-Ru nanoparticles. Figure 39b) is from the red square of a)
...... 91
Figure 40 XEDS of Pt, Pt/Ru and Ru nanoparticles. (Note: Fe peaks were signals from
the column of TEM; Cu was the TEM grid used to hold the nano-particles; Na
and O in the Pt-Ru sample could be residuals left during synthesis...... 92
Figure 41 Amperometric i-t measurements a) Overpotential = +0.2V versus Ag/AgCl
reference electrode; b) Overpotential = +0.4V versus Ag/AgCl reference
electrode ...... 97
Figure 42 Concentration of H2O2 vs. Current a) Overpotential = +0.2V versus Ag/AgCl
reference electrode; b) Overpotential = +0.4V versus Ag/AgCl reference
electrode ...... 99
vii
A Study of Biosensors: Novel Application and Novel Electrode
Abstract
By
PO-YUAN (PAUL) LIN
Amperometric biosensing technology received increasing attention in the medical field. This dissertation was divided into two parts: novel application for Ir-C sensor, specifically the detection of a biomarker for metastasis of prostate cancer; and novel electrode materials for enhancing sensing performance particularly the bi-metallic nano-catalyst Pt-Ru.
Part I
Prostate-specific antigen (PSA) test was commonly used in clinical practice to screen and diagnose prostate cancer. Weaknesses of this approach included a lack of specificity and the inability to distinguish between aggressive and indolent cancers. A promising prostate cancer biomarker, alpha-methylacyl-CoA racemase (AMACR), had been previously demonstrated to distinguish cancer from healthy and benign prostate cells with high sensitivity and specificity. However, no accurate clinically useful assay has been developed.
Therefore, the development of a single use, disposable biosensor for AMACR detection was reported in Part I of this dissertation. Human blood samples were used to verify its validity, reproducibility and reliability. The average AMACR levels in the
viii prostate cancer patients were 10-fold higher than either the controls or HGPIN patients.
We were able to achieve 100% accuracy in separating prostate cancer patients from controls. Our results provided strong evidence demonstrating that this biosensor can perform a reliable assay for prostate cancer detection and diagnosis.
ix
Part II
Platinum is generally an excellent catalyst, however, it is known to reduce in its catalytic performance due to poisoning. In order to overcome this shortcoming, a second metal such as ruthenium is mixed with Pt forming a bi-metallic material for electrochemical oxidation/reduction. Ru requires less activation energy than Pt to absorb
OHabs and Oads, common poison species. Consequently, Pt-Ru bi-metallic electrode material outperformed pure Pt and Ru electrodes.
In order to study the electrochemical performance of Pt-Ru electrodes, we compared the three electrode materials for their abilities to detect H2O2. At an applied electrochemical potential of +0.2 versus Ag/AgCl reference electrode, the sensitivities of
Pt, Ru and Pt-Ru for detection of H2O2 oxidation were 76µA/mM, 15µA/mM and
118µA/mM respectively. Pt-Ru electrode had the best performance because the presence of a second metal such as Ru helped to minimize the poisoning of Pt active sites.
x
Part I: Background and Introduction
Prostate Cancer
Prostate is a gland found in the male reproductive system. As shown in
Figure 1, it is located in front of the rectum and below the urinary bladder.[1] As age increases, the size of prostate increased. The function of prostate is to produce a slight alkaline fluid that is milky and white in appearance, and 50-75% of semen is composed of this fluid.[2-4] This prostatic fluid helps extend the lifespan of semen by neutralizing the acidity of the vaginal tract. In addition, prostate contains smooth muscles that could aid the expelling of semen during ejaculation.[2]
Figure 1 Prostate location and structure[1]
Prostate cancer, which starts at the prostate gland, is the second most common cancer in United States among males. The most common cancer for male is lung cancer.
Globally, it ranked 6th of the most common cancer deaths of men but ranked 2nd in terms of most commonly diagnosed cancer among men.[5] Prostate cancer typically occurs in old ages; men aged over 65 have greater chance of developing prostate cancer, and this risk will increase with further aging. The age-specific rates are shown in Figure
2. 1
1000
100
10 people) 1
0.1 Age specific rates (per 100,000 15-44 45-54 55-64 >65
Age
Figure 2 Age-specific rates of prostate cancer globally. (data taken in 2002)[5]
Other factors relating to the increased risk of developing prostate cancer are shown in Table 1. According to the National Cancer Institute, in 2012, the estimated number of new cases of prostate cancer is approximately 241,740 and 28,170 death caused by prostate cancer, respectively. More people are diagnosed with prostate cancer compared to the number of new cases and death in 2011, 240,890 and 33,720 respectively. According to the American Cancer Society, about 1 in every 4 men will be diagnosed with prostate cancer in their lifetime and 1 in every 36 will die from it.[6]
Most of prostate cancers are slow growing, though there are still cases of fast aggressive ones. During early stages, prostate cancer grows slowly and has no symptoms; therefore, the need for developing an accurate and practical way to detect prostate cancer in its early stages is desirable.[7]
2
Age Men over age 65 have higher risk.
Family History Higher risk if close male relative has prostate cancer.
Race Black male has higher risk than white, Hispanic, Asian/Pacific
islander male and American Indian/Alaska Native men.
Genome changes • Genetic changes at specific regions of certain chromosomes will
increase risk.
• Changes in genes such as breast cancer type 1 susceptibility
protein (BRCA1) and Breast Cancer 2 susceptibility protein
(BRCA2) will result in higher risk.
Others Men with high-grade prostatic intraepithelial neoplasia (PIN) will
have higher risk.
Table 1 Risk factors relevant to prostate cancer probability [7]
Diagnosis Methods of Prostate Cancer
Currently, common methods of detecting for prostate cancer include digital rectal exam (DRE) and measuring the level of prostate-specific antigen (PSA) through blood sample. DRE involves a doctor physically feeling the prostate for hard or lumpy areas. The accuracy of this method depends on the experience of the physician, and digital rectal exam can be painful for patients. In addition, the accuracy of DRE is only around 52%.[8]
Today, the most common biomarker for prostate cancer is PSA, a protein produced by prostate gland. PSA level below 4.0 ng/ml is formerly considered by doctors as normal; however, further researches have proven it to be wrong. Recent studies show that there are prostate cancer patients with PSA level lower than 4.0 ng/ml.
3
Although PSA level does relate to prostate cancer, there is no specific level and testing results which can be misleading due to the fact that prostate cancer is not the only source for elevated PSA level. Other causes of elevated PSA level include benign prostate enlargement, inflammation, infection, age, and race.[7, 9] As a matter of fact, the over- diagnosis rate of prostate cancer could be as high as 30%.[10] As a result of false diagnoses, unnecessary treatments to people who do not actually need them can increase a chance of needless side effects such as unnecessary painful biopsies, surgical complications, radiation burns, incontinence, erectile dysfunction, bowel injury, and patient anxiety.[11-13] Since the introduction of PSA screening, the number of prostate cancer detected has increased but morbidity and mortality have not reduced.[14] PSA level of more aggressive stage of prostate cancer is lower than that of a less aggressive stage.[15] PSA, as a biomarker for prostate cancer, lacks the ability to differentiate between greater and lesser risk cancer.[14] Currently the United States Preventative
Service Task Force (USPSTF) does not recommend prostate cancer screening using PSA.
The USPSTF’s position on prostate screening is the result of the inability of using PSA to demonstrate a reduction in the risk of death.[16-18] In order to effectively lower the morbidity and the mortality rates, it is important to find a new biomarker and develop its detection methods. A new biomarker should be specific for prostate cancer and should remain elevated during either earlier or later stages of carcinoma. More ideally, a new marker that is able to distinguish prostate cancer of different stages and grades is desired.
Because of the increased number of diagnosed prostate cancer due to PSA screening, millions of biopsies were performed annually world-wide. Transrectal ultrasound-guided biopsy of prostate is currently the most accurate way to diagnose
4 prostate cancer. Samples of prostate tissue are collected and analyzed in laboratories.
Typically, 10 to 12 samples are removed from the prostate gland using biopsy needle.
First, a lubricated ultrasound sensor is passed through rectum as shown in Figure 3.
Then, biopsy needles are passed through the shaft of the ultrasound sensor for sample collection. During each tissue collection, individuals undergoing the biopsy could feel sharp sensation. Local anaesthesia is required to ease the slight pain and discomfort. As with any other procedures, there are risks involved with transrectal ultrasound-guided biopsy of prostate. [19]
5
Figure 3 Transrectal ultrasound-guided prostate biopsy[20]
There are side effects and complications involved with transrectal unltrasound-guided biopsy of the prostate. Side effects and complications are shown in
Table 2. All of the side effects will eventually disappear with time and major complications do not occur as often.[21]
Side Effects Complications
Discomfort in rectal area If quality of specimens are poor, repeat of
biopsy is required
Blood-stained urine and faeces Urinary or bowel infection
Blood-stained or discoloured semen
Difficult to urinate
Table 2 Side effects and complications of transrectal ultrasound-guided biopsy of
prostate[19]
6
Despite the risks of transrectal ultrasound-guided biopsy of prostate, it is still the most assuring methods for prostate cancer detection. However, as accurate as biopsy is, there are still limitations. There are studies showing that biopsy could not detect small focal prostate cancer and this small focal cancer is not insignificant. Almost half of patients diagnosed with small focal prostate cancer are at moderately advanced or advanced stage of the disease. Small focal prostate cancer is realized on the final radical prostatectomy. Failure to diagnose this condition in biopsy will delay proper treatment and may lead to unfavorable results.[22]
Failure to detect small focal cancer is not the only challenge faced by transrectal ultrasound-guided biopsy of prostate, and it is not uncommon. Both underdiagnosis of small focal prostate cancer and over-diagnosis of benign lesions will cause undesired outcomes for patients. There are various reasons that the detection of small focal cancer is a challenge for biopsy. First, it is easy to miss malignant cells that are limited to a few glands. Secondly, there is no one histological feature that is sufficient to represent the diagnosis of prostate cancer. The determination of prostate cancer usually involves a combination of several histological features such as architectural, cytological, and extracellular material change. Thirdly, some histological features of benign prostate conditions are indistinguishable from that of prostate cancer.
Benign prostate conditions such as small-crowded glands, atrophy, inflammatory atypia, and basal cell hyperplasia can all cause such confusion. Finally, because of the variations in sampling, small focal cancer does not necessary mean the volume of cancer is small.[23] Also because of the small focus of prostate cancer, there are possibilities that tumors are not sampled during re-biopsy.[24]
7
Stages of Prostate Cancer and Treatments
There are four stages of prostate cancer. During stage I and II, cancer is confined in prostate only. By the time cancer reaches stage III and IV, it will have been spread beyond prostate. As other types of cancers, early detection of prostate cancer provides more options and greater likelihood for the curing of the disease since during early stages of cancer it has not started to spread to other organs. First step after early detection is usually constant monitoring and many times no treatment is necessary immediately. Methods of monitoring the progression of prostate cancer include blood test, rectal examination and biopsy. As cancer progress, more treatment options become available and necessary; treatments like surgery, radiation therapy, hormone therapy, freezing treatment, heating with ultrasonic, and chemotherapy become available.
There are risks during the monitoring stage of treatment. In between checkups, there is possibility that cancer may grow and spread.[25] As cancers grow and spread, the probability of curing decreases. It will be beneficial and reduce the risk between checkups if there is an efficient and inexpensive way of detecting prostate cancer. In this research, we propose a novel detection method of prostate cancer using a new biomarker, Alpha-methylacyl-CoA racemase (AMACR). Using an Ir-C sensor strip, concentration of AMACR can be determined almost immediately. If successful, it will be possible for patients to perform self-checkups. The benefits will be increased interval of checkups and decreased risk of not knowing when cancer is growing and spreading. It will also be more economically sound because the exclusion of fees paid to medical personnel during regular checkups. For this idea to be realized, several questions, listed in Table 3, must be answered first. In this report, not all of the questions have been
8 addressed, many of the questions require further collaboration with experts from the biomedical field.
Questions
What is the detection limit and range of Ir-C sensor in detecting AMACR? Is the
concentration of AMACR in question detectable by the sensor?
What is the relationship between AMACR and age, race, stage of cancer, other
diseases etc.? How specific is AMACR for prostate cancer.
What is the cutoff of AMACR concentration for prostate cancer patients?
Table 3 Questions
Biomarker Candidates
A biomarker, also known as molecular marker and signature molecule, is defined as “A biological molecule found in blood, other body fluids, or tissues that is a sign of a normal or abnormal process, or of a condition or disease,” by the National
Cancer Institute. It can be used to detect diseases and monitor how well a patient responds to a treatment. Biomarkers are unbiased and are indicators for illness onset.
They are able to differentiate the state of diseased and healthy. Often, they provide information and insight to the stage and severity of disease.[26] Biomarkers are useful both in patient care and drug development.
The significance of and attention towards biomarkers and biosensors increase rapidly. Organizations such as National Institutes of Health (NIH) have been giving out grants in this field of study. In 2008 and 2009, NIH gave a total of 4,928 grants, costing over $1.4 billion, to researches related to biomarkers. Grant awards to biomarker-related subjects account for almost half of the funding given out by NIH in the years of 2008 and
9
2009.[26] As shown in Figure 4, the number of grants given by NIH has increased since
1985. Grants and funding given by other institutes for biomarker-related researches are also growing.
Figure 4 NIH grants from 1986 to 2009 in biomarker related fields[26]
Biomarkers can be used for prognosis and diagnosis. Prognosis is for predicting the possible outcome of an illness, whereas diagnosis is for identifying the present of an illness. In this research the biomarker we seek for is for the purpose of diagnosis. There are many biomarker candidates for prostate cancer and Table 4 lists several examples.
10
Marker Description/Type/Biol Advantages Disadvantages ogical Function α- • Peroxisomal and • Quite specific for • Possible Methylacyl mitochondrial prostate cancer increase in the Coenzyme A racemase • Present in both present of Racemase • Engaged in bile acid blood and urine urological (AMACR) synthesis, • AMACR level disorders like stereoisomerization, corresponds to the BPH andβ-oxidation of stage of prostate • Over branched-chain fatty cancer expression is acids observed in several other cancers Glutathione • CpG island • GST-π has been • Some study S-transferase hypermethylation of shown to be suggested GST- π (GST-π) DNA encoding the acutely sensitive π is almost protein, glutathione in detecting the universal S-transferase π presence of absence in • Hypermethylation of prostatic situations like GSTP1 inhibits intraepithelial PIN and transcription. GSTP1 neoplasia and prostate cancer. usually acts by prostrate cancer, • Tissue conjugation of thereby biomarker* oxidant and distinguishing electrophilic patients with these carcinogens to diseases from glutathione to patients with BPH inactivate them Prostate- • It is a type II integral • Levels of PSMA • Decrease in specific membrane protein in men with advanced cases Membrane that exhibits prostate cancer is of prostate Antigen numerous enzymatic considerably cancer (PSMA) activities higher than in • High level of those with BPH or PSMA has been those free of observed both disease in prostate cancer and breast cancer Prostate • Membrane • Increase levels of • Increase levels Stem Cell glycoprotein PSCA expression of PSCA Antigen predominantly in most prostate expression in (PSCA) expressed in the cancers and most prostate prostate higher Gleason cancers and grade and more higher Gleason advanced tumor grade and more stage advanced tumor
11
stage • Inadequate number of published studies supporting PSCA as a valuable clinical biomarker Early • Nuclear matrix • EPCA was found • EPCA appears Prostate protein linked with in prostate cancer not to be Cancer the nuclear precursor lesions, present in Antigen transformations that specifically in patients devoid (EPCA)3 occur in early prostatic of prostate prostate cancer intraepithelial cancer, it has development neoplasia and been detected proliferative in surroundings inflammatory free of, but atrophy, as well as adjacent to, the prostate cancer cancer tissue • More studies • The protein has are needed to been identified in further men with a characterize the preliminary protein as a negative biopsy suitable but who later biomarker to developed the diagnose cancer prostate cancer Table 4 Candidates of biomarkers for prostate cancer detection[27-29]
*This is categorized as a disadvantage from our point of view because a tissue biomarker could not be readily measured through electrochemical method while a fluid biomarker could.
A ideal biomarker should consist the following characteristics[29]:
• Economical, quick and consistent.
• Expression is significantly different between healthy and diseased condition.
• Readily quantifiable in accessible biological fluid such as blood or urine.
• Shown to correlate with an interested outcome progression.
12
For prostate cancer, a biomarker should have the ability to detect it in the early stage. It should be readily detectable in blood or urine and prostate cancer specific.
In this study, AMACR is the selected biomarker.
Novel Prostate Cancer Biomarker, Alpha-Methylacyl-CoA Racemase
To better predict prostate cancer, a more specific biomarker is required and one potential candidate would be alpha-methylacyl-CoA racemase (AMACR), also known as P504S.[15, 30] In many recent studies, elevated AMACR level has been shown corresponding to higher risk of prostate cancer. AMACR is an enzyme involved in the metabolism of branched-chain fatty acid and bile acid intermediates. AMACR is a mitochondrial and peroxisomal enzyme. It is responsible for catalyzing the racemization of alpha-methyl, branched carboxylic coenzyme A thioesters. It is also important in the oxidation of bile acid intermediates and branched-chain fatty acids.
Over-expression of AMACR has been shown in numerous different cancers such as colorectal, prostate, ovarian, breast, bladder, lung, and renal cell carcinomas, lymphoma, and melanoma. However, the highest over-expressions of AMACR are found in prostate cancer.[30, 31] In another words, AMACR is more specific towards prostate cancer.
According to Z.M. Liu’s research, using enzyme-linked immunosorbent assay
(ELISA) as the technique for AMACR detection, out of 64 prostate cancer patients, 62 of them showed an over-expression of AMACR.[32] For a normal person, the concentration of AMACR ranged from 1 to 5 ng/ml. Z.M. Liu suggested that on average, the concentration of AMACR of a prostate cancer patient was 20 times greater (20 ~ 100 ng/ml) than that of a healthy individual. Rogers et al also showed that the presence of
13
AMACR in urine using Western blot technique. In that study, the sensitivity of AMACR detection for diagnosing prostate cancer in post-biopsy urine specimens was 100%.[33]
These two studies and many others showed the existence of over-expressed AMACR level in both sera and urine of prostate cancer patients.
AMACR was a specific biomarker of prostate cancer. In a study by Zehentner et al, in addition to prostate cancer patients, they also tested AMACR level for patients with breast cancer, ovarian cancer and lung cancer. None of them showed a positive result for AMACR.[30] A specific biomarker like AMACR was important in aiding the screening of prostate cancer especially in cases where quantity and quality of biopsies were limited.[34]
In a previous study, amount of AMACR presented in blood specimens was proportional to the degree of severity of prostate cancer.[30] Reverse transcription polymerase chain reaction (RT-PCR) was utilized to determine the quantity of AMACR of patients at different stages of prostate cancer. At early stages of prostate cancer, the copies of AMACR were greater than that at earlier stages as shown in Table 5.
Group Average AMACR copies
Prostate cancer in remission 76.6
Organ-confined prostate cancer 449.1
Metastatic prostate cancer 713.0
Table 5 AMACR real-time RT-PCR results in peripheral blood specimens[30]
AMACR was also linked to cancer growth. It had been shown that the over- expression of AMACR was correlated to the increase in AMACR activity.[35] Studies
14 showed that decreasing the expression of AMACR and decreasing its activity can decrease or impair the proliferation of prostate cancer cells.[34]
AMACR was an ideal biomarker because it is specific to prostate cancer, detectable in blood and urine, and its level was correlated to the severity of the disease.
AMACR not only had the potential of either replacing or aiding PSA diagnosis, it could also benefit transrectal ultrasound-guided biopsy of prostate. Transrectal ultrasound- guided biopsy, being the most accurate method currently for diagnosing prostate, remained to have its challenges. Transrectal ultrasound-guided biopsy was unable to detect small focal prostate cancers.
In a study by B. M. Carswell et al, they showed that AMACR was helpful to transrectal ultrasound-guided biopsy. Specimens with small focal prostatic carcinoma that were missed by biopsy had shown positive in AMACR. They demonstrated high sensitivity (80% ~ 100%) of AMACR towards small focal prostate cancer.[22, 24]
However, sensitivity varies from one laboratory to another; more reproducible method of detecting AMACR was needed.
Even though if AMACR did not become the dominant replacement as a biomarker for prostate, it had great potential in aiding existing method for diagnose prostate cancer to become more accurate. Therefore, the detection of AMACR provided an overall higher chance and accuracy of detection prostate cancer, giving patients an opportunity of better judgment and make better treatment decision. Because the correlation between AMACR and the proliferation of prostate cancer cells, development of a detection method AMACR not only helped the identification of prostate cancer but possible applications also included aiding the development of treatments and medicines
15 for such disease. It was possible to weaken proliferation by lowering AMACR expression.[34, 36]
Currently, there was no assay for AMACR that was acceptable by both clinicians and researchers in the field of prostate cancer. The development of a reliable method to detect AMACR would simplify the clinical protocol for prostate cancer examination. In this study, we proposed a method to detect AMACR that was easy, fast, reliable, portable and economically sound.
AMACR Assay and Biosensor
It would be a significant breakthrough if AMACR detection for diagnosis of prostate cancer can be standardized replacing PSA as the biomarker for prostate cancer provided that it was an easy and time saving detection method. We proposed to develop an in vitro assay technique for the AMACR detection in blood and eventually in urine.
This assay should be reliable and later provide a method to detect and quantify AMACR level. Furthermore, we proposed to develop a single-use and disposable AMACR biosensor with high selectivity, high sensitivity and low production cost.
Methods of AMACR Detection
Currently, a single standard method for detection of AMACR did not exist.
The most common way of detection was though immunostaining methods such as enzyme-linked immunosorbent assay (ELISA). Immunostaining was a term given to detection methods that use anti-bodies to detect proteins such as AMACR. ELISA, for example, was utilized to quantify AMACR in blood plasma, serum or other cell/tissue extracts. Anti-AMACR was mixed with AMACR and the resulting color change was used to identify and quantify AMACR.
16
Reverse transcription polymerase chain reaction (RT-PCR) was another method which researchers used to detect AMACR. RT-PCR was a common technique used to measure
RNA expression level. There were studies showing that AMACR mRNA in prostate tissues could be quantified with RT-PCR.
In some studies, sensing devices were also applied to detect AMACR.
Piezoelectric-excited millimeter-sized (PEMC) sensors used the difference in resonance frequency to determine the level of AMACR expression. In a study by David Maraldo, anti-AMACR was immobilized onto the PEMC sensor and then 3mL of urine sample was exposed to the sensor.[37] The PEMC was a macrocantilever consists of a piezoelectric layer bonded with a nonpiezoelectric layer. When an electric field was applied to the sensor, the piezoelectric layer caused the structure to bend. By altering the applied field, the structure started to oscillate. The sensor started to resonate when its natural mechanical frequency was reached. When an analyte was added onto the sensor, the resonance frequency changed. This change in frequency resulted in the detection of
AMACR.
Sample preparation, maintenance-intensive equipment and skilled personnel prevented ELISA or other immunostaining techniques from becoming a point-of-care testing method.[37] We proposed to detect AMACR with a screen-printed nano-particle biosensor. It was relatively easy, inexpensive and was possible to achieve point-of-care testing. In addition, using a screen-printing method to fabricate these sensors was reliable, efficient and economically sound. The PEMC sensors are fabricated individually and manually; therefore, each sensor was different with different resonance
17 characteristics. Another advantage of fabricating sensors with the screen-print technique was that each sensor was uniform and performs consistently, making the calibration for each sensor un-necessary.
The first step for achieving the proposed goals was to establish a reliable assay for AMACR, and a suitable substrate would be necessary. This substrate combining with AMACR should result in a product that was detectable by our sensor.
Several studies showed some possible substrate candidates.[38-40] Coenzyme A esters of pristanic acid, bile acids derived from cholesterol, and ibuprofenyl CoA were all substrate candidates for AMACR.[35]
Figure 5 Enzyme lowering activation energy to accelerate a reaction[41]
A substrate in biochemistry is the biological molecule, which an enzyme, such as AMACR, will react with. Enzyme, a protein, is a catalyst that accelerates a chemical reaction. In order to reach proper rate to sustain life, the majority of chemical reactions
18 in biological cells require enzymes. Enzymes themselves do not react or change forms before or after completion of reactions. Enzymes are specific and selective of their substrates. It works by lowering the activation energy for a reaction without changing the position of chemical equilibrium of such reaction. As shown Figure 5, the red and blue curve represents the same reaction while the red curve represents the reaction without enzyme and blue curve represents that with enzyme, respectively. The barrier, activation energy, from reactants to products is lower in the present of enzyme. Of the many possibilities, an enzyme only accelerates certain reactions. Most of the reactions with enzyme are million times faster than the same reaction un-catalyzed.[41] During reaction, one or more reactants will bind to the enzyme forming an intermediate complex.
Before an enzymatic reaction, the molecule is called substrate and after reaction it is converted to a different molecule called product. Enzymes are 3-D in structure and most enzymes are larger than their substrates. However, only small portion of an enzyme can catalyze a reaction and these parts are called active sites. Schematic drawing of an enzymatic reaction is shown in Figure 6. First, substrates are bound to the active sites and for an intermediate complex as depicted in Figure 6 and described in Equation 1.
This is called induced fit hypothesis, where the active site of an enzyme can be induced to alter its shape to surround the substrate for a close fit. This process, the binding of substrate to enzyme is a reversible process as described by the double arrow shown in
Equation 1. After substrate reacted into product, it leaves the active site so the next substrate can come in and repeat the whole process again.
19
k f kcat E + S⇔ES →E + P kr
E = Enzyme
€ S = Substrate ES = Complex
P = Product
kf = rate constant forward
kr = rate constant reverse
kcat = turnover number (the maximum number of molecules of substrate converted into
product per enzyme per second)
Equation 1 Enzymatic reaction
Figure 6 Schematic representation of the mechanism of an enzymatic reaction
Pristanic Acid
There were few possible substrate candidates for AMACR and pristanoyl-
CoA derived from pristanic acid (2,6,10,14-tetramethylpentadecanoic acid) was the one
20 chosen. In this study pristanic acid was a branched-chain fatty acid found in blood plasma with micromolar concentration for a healthy individual. The presence of pristanic acid was usually accompanied by phytanic acid.
Pristanic acid could be used to identify neurological disease, peroxisome biogenesis disorders (PBD). PBD included Zellweger syndrome and rhizomelic chondrodysplasia punctata type 1.[42-45] Symptoms of PBD included mental impairment, confusion, learning difficulties and liver damage. The deficiency of
AMACR was found to relate to PBD. In the absent of AMACR, pristanic acid accumulated and as a result measuring pritanic acid level could be used to detect PBD.
Though PBD was nowhere as common as prostate cancer, with small alteration, it was possible using our proposed method to detect pristanic acid level. This gave our proposed research an additional minor application.
Figure 7 shows the formation of pristanic acid from the phytol side chain of chlorophyll.[46]
21
Figure 7 Pathway of pristanic acid formation from phytol.[46]
Both phytanic and pritanic acids could not be produced de novo by humans.
Their direct source was from the ingestion of dairy and red meats. Pristanic acid was the
α-oxidation product of phytanic acid as described in Figure 7. AMACR was responsible for the β-oxidation of pristanic acid. An increase in pristanic acid level increased
AMACR activity and level.[47-49] AMACR was associated with prostate cancer in many studies. Though currently, there was no direct evidence nor any suggestion of a mechanism of the role AMACR played in prostate cancer, many studies hinted that
AMACR was responsible for the initiation or progression of prostate cancer tumors.[48]
22
AMACR was used to convert (2R)-pristanoyl-CoA to (2S)-pristanoyl-CoA; therefore, as shown in Figure 9, pristanic acid was used as the substrate. Pristinic acid must first be activated to its corresponding CoA-ester by the addition of CoA, Mg2+ and -
ATP. Similar to any other acyl-CoA forming reaction, CoA, Mg2+ and ATP were required.[50] Acyl-CoA belonged to a group of coenzymes which involved in the metabolism of fatty acids. When coenzyme A was attached to the end of a long chain fatty acid, such as pristanic acid, inside a living cell, Acyl-CoA was temporary formed.
The steps for activation of acyl-CoA were depicted in the schematic diagram, Figure 8.
The activation of acyl-CoA started with replacement diphosphate group of ATP with fatty acid. Then the AMP was replaced with coenzyme A forming acyl-CoA.
Magnesium, especially in the form of Mg2+ ion, was essential in many biological systems. Though the role of Mg2+ in the activation of pristanic acid was not clear, it was highly possible that for ATP to become biologically active, it must bound to Mg2+.[51,
52] The activation of pristanic acid to pristanoyl-CoA was not fully understood yet.
However, for AMACR to catalyze β-oxidation, it was necessary to have pristanic acid converting in its CoA-ester form. Limited information is available on the actual activation of pristanic acid in a laboratory setting. The quantities of ATP, CoA, and Mg2+ required, and experimental conditions, such as temperature, incubation time etc., are not established. Extensive trial and error evaluations have been utilized to find the experimental parameters for preparing substrate solution for AMACR. We did not have the knowledge differentiating pristanic acid and pristanoyl-CoA.
23
Figure 8 Activation of fatty acid (acyl-CoA)
AMACR then catalyzed the reaction of (2R)-pristanoyl-CoA to (2S)-
pristanoyl-CoA. The addition of peroxisomal acyl-coenzyme A oxidase 3 (ACOX3) was
also known as pristanoyl-CoA oxidase.[53] ACOX3 was not found in human tissues; its
present was found in gene with small expression. The function of ACOX3 was oxidizing
the CoA esters of 2-methyl branched fatty acid. It catalyzed the reaction to form
hydrogen peroxide, H2O2, as shown in Equation 2.[54] ACOX3 donated electrons
directly to O2 so it could form H2O2. In this research, the most critical role ACOX3
played is the generation of H2O2.
ACOX 3 (2S) − pristanoyl − CoA + O2 ⇒ trans − 2,3− dehydropristanoyl − CoA + H2O2
Equation 2 Reaction of (2S)-pristanoyl-CoA changing into H2O2 € The production of H2O2 was one of the most important aspects in this research
and would be described in later section, amperometric biosensor. AMACR was not
directly measured; instead, H2O2 provided the detectable signal which correlated to the
AMACR level.
24
Figure 9 Pathway of pristanic acid to pristanoyl-CoA[39]
In order to detect and quantify AMACR, we proposed to use an electrochemical amperometric biosensor to detect the quantity of H2O2 produced by the
β-oxidation of (2S)-pristanoyl-CoA catalyzed by ACOX3. The amount of (2S)- pristanoyl-CoA governed the concentration of H2O2 measured by the biosensor. As shown in Equation 2, ACOX3 was responsible for catalyzing the desaturation of (2S)- pristanoyl-CoA to trans-2,3-dehydropristanoyl-CoA and, simultaneously, forming H2O2.
ACOX3 was specific to (2S)-pristanoyl-CoA, and (2R)-pristanoyl-CoA could not undergo β-oxidation. As shown in Figure 9, AMACR catalyzes the transformation of
(2R)-pristanoyl-CoA to (2S)-pristanoyl-CoA. With the presence of AMACR, there will be a greater quantity of (2S)-pristanoyl-CoA was available to be converted to H2O2 using
ACOX3. A sample containing ACOX3 and not AMACR is used as a baseline, and an
AMACR-containing sample yielded higher H2O2 concentration than the baseline. This
25 allowed us to detect the presence or absence of AMACR in the sample. In a fixed time, samples with a higher concentration of AMACR converted more (2S)-pristanoyl-CoA from (2R)-pristanoyl-CoA, and hence, more H2O2 was produced through ACOX3.
Because H2O2 was generated only from (2S)-pristanoyl-CoA, the presence and absence of AMACR resulted in different (2S)-pristanoyl-CoA and H2O2 concentrations. In addition, different concentrations of AMACR eventually resulted in different concentrations of H2O2, therefore AMACR could be quantified by the measurement of
H2O2 concentration.
Amperometric Biosensor
A sensing device, sensor, detected the present of physical properties and/or measure the change in physical quantities, and then converted them into signals comprehensible by a person or instrument.[55, 56] Many physical properties (e.g. heat, light, sound, pressure, magnetism, motion, radiation etc.) could be detected using a sensor. Sensors were everywhere and their applications were vast. Sensors were found in electronics, transportations, home appliances, manufacturing, robotics and others.
Even in the field of medicine, sensors were commonly applied.
Biosensors were used to monitor the health of individuals and it was designed to detect the present or absent of some diseases. It was a sensing device detecting selected analytes. In medical term, an analyte was a substance or chemical constituent that was under analyzed. In this research, analyte was the biomarker, AMACR, detected by the biosensor. Typical biosensor was composed of a biological part and a physico- chemical part. The biological component was responsible for interacting with analyte.
This biological part could be tissues, microorganisms, organelles, cell receptors,
26 enzymes, antibodies, nucleic acids and others. The physico-chemical part typically was a transducer, which responded for the transferring of signal resulted from interaction between biological component and analyte into another form of signal that could be read by an observer or instrument. Figure 10 was a schematic diagram summarizing the components of a biosensor and their relationships. During operation, analyte interacted with the bioreceptor generating a signal. This signal was then received and transformed by the electrical interfaces to another form of signal. Final, this “new signal” was analyzed by the electronic system such as a computer and displayed on a monitor in a form that could be understood by an operator. The output signal from transducer should be proportional to the input analyte.
Transducers
Bioreceptor Electrical Sample, Electronic System (e.g. (e.g. Interfaces (e.g. Analyte computer, amplifier, pristanic electrodes, (e.g. AMACR) + monitor) acid, ACOX3) nanoparticles)
Figure 10 Schematic of the components of a biosensor
Different types of biosensors could detect chemical compounds by electrical, thermal, or optical signals. The sensor propose was of the electrochemical type. There were several different types of electrochemical sensors: ion-selective, impedance-based, conductance-based and amperometric-based sensors.
27
Ion-selective type electrochemical sensors transformed activities of ions into an electric potential. In a biochemical system, an ion-selective sensor was used to measure ion concentration in an aqueous solution.[57] Common applications for ion- selective sensor included pH meter and voltmeter. Ion-selective membrane was the sensing component and wasmost important part of an ion-selective sensor. A membrane was used in such that only one type of ion was allowed to penetrate. Membrane allowed the differentiation between analyte and rest of the interfering ions in the sample. Figure
11 showed the typical layout of an ion-selective sensor, and it is consisted of 2 electrodes and one membrane. On one side was the ion-selective electrode and the opposite one was a reference electrode. Two electrodes were essentially identical except the ion-selective electrode had a membrane and the reference electrode without the membrane but with a porous frit. The potential difference between the two electrodes was contributed majorly by the target ion/analyte.
28
Electrode Ag/AgCl
Internal electrolyte
Sample Solution
Membrane Porous frit
Ion-selective Reference electrode Electrode
Figure 11 Typical layout of an ion-selective sensor[58]
The total potential of the system was describe in Equation 3.[59]
�!"!#$ = �!"# + ∆� − �!"#
∆� = !" ln !!"# Nernst Equation !" !!"# where,
Etotal = potential of the entire system
Eref = electrode potential of the reference electrode
EISE = electrode potential of the ion-selective electrode
Δϕ = potential difference across membrane
R = gas constant
T = absolute temperature z = number of electrons transferred. (Charge of the target ion)
F = Faraday’s constant
29 aISE = activity of analyte in ion-selective electrode asol = activity of analyte in solution
Equation 3 Potential of ion-selective electrodes
The system was under quasi-equilibrium during measurement suggesting that there was no current flow. The potential change across the membrane corresponded to the amount of analyte passing through the membrane. pH meter, for example, measured the concentration of H+ ion in the solution. The major drawback of an ion-selective sensor was diffusion. Diffusion affects the accuracy of the system. For example, larger analyte resulted in difficulty of diffusion through the membrane.
For an impedance-based sensor, the resulting current was measured when a sinusoidal potential with a small peak-to-peak amplitude was applied. Because the resultant sinusoidal current changed when substances were absorbed onto the electrode surface, the change in impedance could be used to detect the presence or absence of an analyte.[60] Figure 12 showed a schematic of a polymer coated electrode.
Figure 12 Schematic of a impedance-based polymer coated electrode[60]
30
The capacitance of the electrical double layer for the electrode shown in
Figure 12 can be calculated by the follow relation:
� � � � = ! ! !" � where,
Cdl = capacitance of double layer
ε0 = permittivity of free space
εr = dielectric constant of the polymer material
A = surface area d = distance (charge separation)
Equation 4 Capacitance of double layer
In this arrangement, impedance could be changed in several ways. The absorption of the analyte onto the electrode was one of them. Another way was to change the thickness of the charge separation. This was be achieved by incorporating an enzyme specific for the analyte which catalyzed a reaction creating products that degrade the polymer layer. As thickness of the polymer changed/degraded, the capacitance changed. The disadvantage of an impedance-based sensor was greatly influenced by contamination. Also, instruments required were relatively expensive.
A conductance-based sensor depended on the change in conductivity between electrolytes to detect the change in a system.[57] Conductance of an analyte solution was given as followed
�� � = � where,
G = conductance
31
σ = specific conductivity of the electrolyte
A = cross-sectional area of the electrode
L = distances between two electrode
Equation 5 Conductance of solution containing analyte of interest[61]
As the concentration of analyte changed in electrolyte, the conductance changed as well. It was easy to assemble experimentally but this system was less specific towards the analyte. Contamination or unknown species in electrolyte easily affected the accuracy of measurement.
The last type of electrochemical sensor was an amperometric sensor, which was used in this study. Electrochemical sensors usually involved enzymatic reaction that produced or consumed electrons. Amperometric biosensor depended on the oxidation- reduction reactions of analyte on the electrode generating the current flow, which could be measured by instruments such as a potentiostat. Typically, as shown in the schematic drawing in Figure 13, it consisted of three electrodes: a working electrode, counter electrode and reference electrode. Working electrode would be in contact with the analyte. Depending on the potential applied to working electrode, it could be either a cathode or an anode. Reduction took place at cathode while oxidation took place at the anode. The function of the counter electrode is, as the name suggested, to “counter”. It exactly opposited the working electrode, balancing charge generated by working electrode whether it was by generating or consuming electrons. Counter electrode completed the circuit. Finally, the reference electrode monitors the potential allowing the maintaining of a steady potential while current flows through the electrochemical cell.
The reference electrode stayed at its equilibrium potential and no current passes through
32 it. A constant potential, positive or negative depending on the application, was applied to the working electrode and a current was generated through the oxidation-reduction reaction.
A
V
Electrolyte Counter Working Reference
Figure 13 Schematic of 3-electrode electrochemical cells
H2O2 amperometric sensor, as shown in the schematic drawing in Figure 14, was a good illustration for this type of sensor. In this case, a positive potential was applied, at the working electrode, H2O2 was oxidized to oxygen and hydrogen ions.
Electrons were generated and flow from working electrode toward counter electrode through the external electrical connection. At the opposite end, on the counter electrode, oxygen and hydrogen ions are reduced to water. Through the oxidation-reduction reaction, a complete chemical cell was formed and current is generated, in this case, by the redox reaction of H2O2. The magnitude of current heavily depended on the concentration of H2O2 in the electrolyte because, by design, our sensor is specific to the oxidation of H2O2. Consequently, the concentration of H2O2 could be determined from the resulting current because of their linear proportionality.
33
The relationship between oxidation current and concentration of H2O2 was described by the Cottrell equation.
����! !!!! !! ! � = ! ! �� where, i = current n = number of electrons transferred
F = Faraday’s constant
A = area of the planar electrode
0 C H2O2 = initial concentration of analyte, H2O2
DH2O2 = diffusion coefficient of analyte, H2O2 t = time
Equation 6 Cottrell’s Equation describing the change of current with respect to time
at a constant applied potential
In our experiment, most of the variables remained constant and the only
0 variable is C H2O2 and time. According to the Cottrell equation, a linear relationship could be established between the concentration of H2O2 and oxidation current. A linear proportionality was a key criterion of a good sensor.
Adjusting the applied potential controled the species to be reduced, oxidized or to remain unaffected. This provided amperometric sensor with a great advantage that was adaptivity. Amperometric sensors could be very portable and a good example was the currently home-used glucose strip. Instruments required were also relatively inexpensive. The simplest arrangement required merely a potentiostat and a computer.
The challenges sometimes involved insufficient selectivity and determining an applied
34 potential that would minimize interferences while providing a good signal of the analyte.
In our research, the electrodes are specifically designed for the detection of H2O2. It processed great sensitivity and selectivity towards H2O2 and would be described in more details in later sections. In addition, our electrode was operated under a low applied potential minimizing interference but at the same time still able to detect H2O2 efficiently.
e- Counter Working Reference
Electrolyte
Figure 14 Schematic diagram of H2O2 amperometric biosensor. Left: Side view;
Right: Plain view. Electrons flow from working electrode to counter electrode.
(note: The arrows represent the direction of electrons flow. The direction of current
flow is the exact opposite.)
Under appropriate electrochemical conditions, H2O2 could readily start the oxidation-reduction reaction. The oxidation current of H2O2 would be proportional to the concentration of H2O2. This relation between current and concentration allowed the development of many biosensors including the commonly known, single-use disposable glucose biosensor for diabetic patients. With typical electrodes, metals and carbon, the oxidation potential of H2O2 was relatively high, and a downside for this is that other
35 biological species, such as uric acid, ascorbic acid and others, could be oxidized interfering the measurement of oxidation current from H2O2.
Hydrogen peroxide, produced by analyte, could be detected electrochemically providing a way to quantify target analyte.[62, 63] However, in order for the described method to work properly, co-oxidation of species other than hydrogen peroxide needed to be minimized. In order to overcome this problem, there are four strategies, which could be applied.[63] First, mediators could be used to lower the applied potential and reduced interference. Mediators were electron transfer agents that increased the rate of electron transfer.[64-67] Secondly, instead of lowering the applied potential, interferences were blocked from the electrode with a permselective membrane.[68-73] Thirdly, electrodes modified with Prussian blue, a dark blue pigment, could effectively lower the reduction potential of hydrogen peroxide.[74-78] Lastly, metalized carbon could be utilized to lower the potential required to reduce or oxidize H2O2.[63, 79-81] Metal particles such as platinum, rhodium, and ruthenium were mixed with carbon in the working electrode.
These metal particles showed good electrocatalytic properties for lowering both oxidation and reduction pontential of H2O2. Iridium had excellent electrocatalytic property.
Incorporating iridium nano-particles into carbon electrode was known to effectively lower the reduction and oxidation potential of hydrogen peroxide.[62, 63, 82]
With the addition of nano-metallic particle catalysts into the electrochemical process, it was possible to lower the oxidation potential of H2O2 to a level minimizing interference.[63, 83] In this study, iridium, Ir, was incorporated into the working and counter electrodes of our biosensor effectively lowering the oxidation potential of H2O2 to +0.25 Volts vs. Ag/AgCl reference electrode. At this applied potential of +0.25 Volts
36 vs. Ag/AgCl reference electrode, we are able to establish a linear relationship between the H2O2 concentration and oxidation current was established. More detail in the measurement of H2O2 would be discussed in the result and discussion section.
Fabrication of Biosensor
Three commonly used fabrication methods for amperometric biosensor were physical vapor deposition (PVD), thick-film printing, and ink-jet printing. Some sensors were fabrication only by one technique but some were fabricated by a combination of techniques.
PVD, a vacuum deposition method, was often used in the semiconductor industry.[84] It was a technique used to deposit a thin-film of materials onto a variety of surfaces. Variations of PVD included: cathodic arc deposition, electron beam physical vapor deposition, evaporative deposition, pulse laser deposition sputter deposition.[85]
Typical PVD utilized either high temperature vacuum evaporation with subsequent condensation or plasma sputter bombardment.[57] A simplified procedure of a PVD process was shown in Figure 15. The source was typically called a target which was in either solid or liquid phase. Through evaporation or bombardment of a high energy source, the material from the target was transported and deposited onto the substrate surface. In order for atoms dislodged from a target to migrate to the substrate in PVD, the placement and configuration of target and substrate followed a line of sight. Vacuum was essential to ensure minimum contamination and the path traveled by atoms was not interfered. Typically thickness of the film deposit using PVD ranges from 100Å to
10µm. Thickness of the deposited film was determined by time, energy applied to bombard the target and the rate of the target atoms could be dislodged. Films deposited
37 by PVD were uniform and adhered well to the substrate. Operation cost of PVD was high and uniform deposition of larger surfaces was difficult; these drawbacks prevented
PVD from producing cost effective biosensors as the one we proposed.
Source (Solid/Liquid)
Evaporation
Gas Phase
Transport & Deposition
Solid Phase
Figure 15 Procedures of the PVD process
Think film screen printing was one of the easiest, flexible, low cost fabrication methods for planar sensors that was applied to large scale applications. Steps of a thick- film screen printing were shown in Figure 16. Four components involved in these steps were squeegee, ink, stencil and the substrate. A stencil contained the pattern that was transferred to the substrate and the ink contained the electrode materials. As depicted in
Figure 16, ink was first placed on the stencil. After stencil was push to contact with the substrate, the squeegee sweeped across the stencil pushing the ink across the pattern opening and transferring the pattern alone with the ink onto the substrate surface.[57]
The film was then baked to remove the solvent and cured maintaining the pattern intact.
Thermal curing was done gradually to prevent inducing stresses into the film.[86]
Baking and curing took place at temperature depending of the properties of the ink. It
38 took place either in ambient environment or in an oven. Typically the lateral resolution ranged from 100µm to 1mm and thickness ranged from 10 to 50µm.
squeegee ink stencil
substrate
Figure 16 Steps of a thick-film screen printing process
A stencil could be made of steel or masking film. The real challenge in thick- film screen printing was the design of ink. An ink consisted of 3 components, solvent, binder and electrode material. When formulating an ink, one must consider the
39 compatibility of the solvent as well as its drying time, viscosity etc. Solvent should not dry before printing process was completed. In addition to holding the pattern together, the function of a binder was to bind the electrode material to the substrate. When aspect- ratio of the pattern was high, the difficult in designing the ink increased. Another problem was that extra ink that did not fill the pattern opening of the stencil was usually wasted and the problem became serious with expensive inks. Despite these challenges and difficulties, thick-film printing was still one of the most efficient ways to mass produce planer structure sensors.
Inkjet printing technique was well-known in the world of computer. Inkjet printers were used in office or home printing documents and photographs. An increasing trend was to use inkjet printing technology for fabricating sensors and other devices. The basic principle for printing a document or making a sensor using this technology was identical. Figure 17 showed a schematic diagram of a simplified assembly. Ink with materials of interest was stored in a cartridge and was then ejected through a nozzle towards the substrate. The volume and size of the ink droplet were well-controlled.
40
Figure 17 Schematic of a typical setup for inkjet printing technique[87]
Depositing the ink towards substrate was one of the most important aspects of inkjet printing. Three common methods of depositing the ink included thermal filament, piezoelectric, and spring actuation. Thermal filament utilized resistors for heating. This heat caused the ink to vaporize and bubble was generated. As bubbles expanded, pressure was built up pushing ink out of the nozzle. Finally, when the bubbles burst, the vacuum space created drew in ink to replace the volume of the ink just ejected.
Piezoelectric technique utilized piezoelectric crystals and they were located at the back of the ink and nozzle.[88, 89] The crystal vibrated when an electrical charge was applied to it. Ink is pressured out of the nozzle onto the substrate and the amount of ink ejected is filled and replaced during vibration. The use of piezoelectric crystals is more expensive than the use of thermal filament. However, piezoelectric technique was usually more durable requiring less operation cost. In addition, the ink used did not need to be volatile
41 to react with heat. A spring was used to move a piston in spring actuation technology.
For printing involving biological species, such as an enzyme, lower temperature technique was preferred.
Ir-C Biosensor
Incorporating Ir into electrode allowed lowering the oxidation potential for
H2O2. Figure 18 showed the platform structure of our Ir-C single-use disposable biosensor fabricated with thick film printing fabrication technique. The sensor consisted of three electrode, working electrode, counter electrode and reference electrode. The materials for both working and counter electrode were active carbon containing 2~5 wt% of Ir nano-catalyst particles. The reference electrode was the commonly used silver/silver chloride electrode. Ag/AgCl electrode was inexpensive and it was stable potential and no-toxic.[90]
Inclusion of nano-catalyst particles in thick film printing ink or paste was a process for the advancement of H2O2 sensors with high selectivity and sensitivity. The quality of screen printable ink was crucial because it contained the active materials, Ir nano particles, active carbon particles, binding material and solvent, and together they must be homogeneous. The screen-printable iridium carbon modified carbon ink consisted only of non-toxic chemicals, which included hydroxyethyl cellulose, polyethylenimine, and a commercial carbon material containing iridium nanoparticles (<2 nm in particle size) uniformly dispersed on carbon black pellets (30 nm in particle size).[63] Details of the screen printable ink were discussed elsewhere.[63, 91] The sensor substrate was made of an opaque white polyester (DuPont Melinex 329). Typical applications of Melinex 329 include pressure sensitive labels, security cards, access cards, multiple use tickets and
42 printing application. A single sensor was easily cut out from a sheet of sensors because the substrate is made of polyester. In addition, it is often used for medical diagnostic test strips, biosensors.[92] The diameter of the iridium-contained carbon working electrode was approximately 0.8 mm2 and a minimum of 2 µl of analyte volume was required.
Figure 18 Screen-printed single-use, disposable Ir nano-catalyst contained H2O2
platform biosensor prototype
43
Experiments
Enzyme Activity
Enzyme activity was estimated based on the amount of substrate converted into product per unit time. For substrates to convert into products, energy barriers were crossed. Enzymes effectively lowered the barrier making substrate to product probability higher. Factors affecting enzymatic activity included concentration of enzyme, concentration of substrate, temperature, and pH. In this study, the concentration of enzyme, ACOX3, was fixed once an optimum and practical concentration was determined.
Temperature usually associated with kinetic energy. At higher temperature, there were more collisions between molecules and consequently, amount of molecules reaching activation energy barrier per unit time increased. The number of collisions between enzyme and substrate would also increase; therefore, the rate of reaction increased with increasing temperature. However, at a high temperature, protein could be denatured becoming inactive. Because enzyme had a 3-D structure, heating could disrupt the structure making it inactive. An optimal temperature existed at which the rate of an enzymatic reaction was the highest and most efficient.
One of the parameters affecting the activity of an enzyme was the acidity, pH.
Enzyme was only effective in a range of pH value and this range varied for each enzyme.
Protein recognition rendered ineffective at the pH outside of the range. At different pH, the bonding of an enzyme was altered or even broken; as a result, shape of such enzyme iwass changed. Acidity could alter the shape, electrical charge, and properties of both enzyme and substrate; therefore, for a given enzymatic reaction, an optimal pH value and
44 range existed. The optimum activity of a-methylacyl-CoA racemase, as shown in
Figure 19, was between pH 6 and 7 but the enzyme remained active between 4 and beyond 9.[93] This range of pH was a good starting point for the AMACR assay despite the same information was not available for ACOX3.
Figure 19 Activity of AMACR with respect to pH value [93]
ACOX3 Reaction Time
ACOX3 was an important component in this research; it was responsible for converting (2S)-pristanoyl-CoA into H2O2, which could be detected electrochemically by our sensor. However, the enzyme activity of ACOX3 was unknown. Before conducting
AMACR measurement, it would be helpful to acquire an approximate time required for
ACOX3 to convert most of (2S)-pristanoyl-CoA into H2O2.
45
Substrate solution were prepare by mixing 100µl of pristanic acid (purchased from Sigma-Aldrich) with 3mg of adenosine triphosphate (ATP) (purchased from Sigma-
Aldrich), 3mg Magnesium chloride, 3mg coenzyme A (CoA) (purchased from Sigma-
Aldrich) and 150ul of phosphate buffered saline (PBS) in a micro vial. This solution was then incubated in -20°C for 2 days.
Fixed quantities of ACOX3(1µl) and substrate solution(5µl) were mixed.
Amperometric i-t measurements were conducted after a number of mixtures were allowed to undergo reaction for different amount of times.
H2O2 Measurement
Phosphate buffered saline (PBS) with pH 7 was prepared by mixing monobasic and dibasic sodium phosphates with deionized water, and 200 mM of potassium chloride was added as the supporting electrolyte improving the conductivity of the buffer. In order to prepare a 150 ml buffer, 2.32 g of dibasic sodium phosphate,
1.1564 g of monobasic sodium phosphate, and 2.25 g of potassium chloride were mixed into 150 ml of deionized water.
Different volumes of H2O2 were then mixed with the prepared PBS making different concentration of H2O2 solution. 5 µl of mixed solution from each concentration was dropped onto the Ir-C sensor. Each concentration was measured for at least three times.
Cyclic Voltammogram diagram (CV graph) was obtained using an electrochemical workstation model CHI660C from CH Instruments, and the range of potential scanned from -0.2 to +0.5 Volt vs. Ag/AgCl reference electrode. According to
46 the resulting CV graphs, a potential was then selected to be applied to the amperometric i-t measurement.
AMACR Measurement
The preliminary measurement was performed without present of blood/serum.
Typical pH value for human blood was around 7. To mimic a human being environment, a phosphate buffer with pH 7 was prepared as PBS was prepared in the H2O2 measurement. The resulting buffer strength was 100 mM, which, for the concentration of
AMACR measured, was sufficient to maintain the acidity constant.
The substrate consisted of 100 µl of pristanic acid mixed with 3mg of adenosine triphosphate (ATP), 3mg Magnesium chloride, 3mg coenzyme A (CoA) and
150ul of phosphate buffered saline (PBS) in a micro vial. Limited information was available regarding the quantity of each chemical that is added to pristanic acid. The amount of ATP, Mg and CoA added into pristanic acid was pursued by trial and error approach and was not yet optimized. Based on experimental results, an incubation time of 2 days (48hours) in a -20oC freezer was needed. Pristanic acid was transferred to
(2S)-pristanoyl-CoA and (2R)-pristanoyl-CoA during this period of time. This incubation time was needed to be optimized but, for preliminary results, it proved to be sufficient. This incubation time provided us a good starting point for future optimization.
The enzyme activity for both AMACR and ACOX3 (both purchased from
Abnova) were not known; therefore, the required reaction time for each enzyme was obtained by trial and error experimental approach. In a micro vial, first the desired amount of AMACR was added to mix with the 5ul of substrate solution keeping at room temperature for 30 minutes. This allowed the enzyme, AMACR, to transfer (2R)-
47 pristanoyl-CoA in the substrate into (2S)-pristanoyl-CoA. Then, ACOX3 was added to the mixture for 5min. During this period, (2S)-pristanoyl-CoA was transferred to H2O2 and trans-2,3-dehydropristanoyl-CoA. 5ul of the final mixture was then extracted from the micro vial and dropped on sensor. Since the activities for the enzymes used were not known, the time allowed for each enzyme to work was acquired through experimental results. Optimization of the time for reaction was needed.
Cyclic Voltammogram diagram (CV graph) was measured using an electrochemical workstation model CHI660C from CH Instruments, and the range of potential scanned from -0.2 to +0.7 Volt vs. Ag/AgCl reference electrode.
Voltammograms of different concentrations of AMACR were recorded and compared to that of background solution in order to determine the potential used for amperometric i-t curve measurement.
From the observation of CV graphs, +0.4 volt vs. Ag/AgCl reference electrode was selected as the potential used for amperometric i-t measurement and each measurement was for 400 seconds. One must be aware that the applied potential will be different from +0.25 volt vs. Ag/AgCl reference electrode as stated before. The materials in test samples altered the applied potential, but the function of the metallic catalyst, Ir in this case, lowering the activation potential remained. Each concentration was measured for at least three times in the experiment. This allowed to determine the reproducibility of the measurements. Both the CV and i-t curves were performed at room temperature.
AMACR in Blood Serum
In order to further simulate a real human body environment, human blood serum (purchased from Sigma-Aldrich) was used. The ratio for pristanic acid, PBS and
48 serum was 2:2:1. pH of PBS of 6.5 was founded providing better results in the present of serum. Our objective was to measure the concentration of AMACR in human blood.
Therefore, serum and AMACR were mixed together first. This mixture was then added into the substrate solution and finally, ACOX3 was added. Volume of serum used in each measurement was 1 µl and the substrate solution was consisted of 2 µl pristanic acid and 2 µl PBS. Volumes and masses of the rest of the chemicals required for the measurements were maintained as mentioned earlier. Incubation time from finished mixing all chemicals to measurement was 60 minutes. Each measurement required 5µl of the final mixed solution dropped onto the sensor.
With more interference resulted from the addition of serum, the applied potential used for amperometric i-t curve measurement was increased from +0.4 to +0.7
Volt vs. Ag/AgCl. Higher applied potential provided greater signal but at a cost of increasing interference.
Hospital Samples
In order to further test the practicality of this AMACR biosensor, measurements of the level of AMACR in human biological specimens were carried out.
The level of AMACR was expected to increase in prostate cancer patients. In order to evaluate this assessment, plasma samples from 9 healthy males, 10 men with high grade prostatic neoplasia (HGPIN) and 5 men with prostate cancers were used in a laboratory- blinded test of the AMACR levels in these samples. 5 mL of blood was collected from each patient in standard heparinized tubes. Through centrifugation, cells were removed from whole blood and the part left is known as plasma. Plasma was isolated by standard
49 protocols and frozen until future use. All samples were collected prior to treatment, where relevant.[94]
In preparing the substrate solution, pristanic acid solution was mixed with the phosphate buffered saline solution (PBS), and the volume ratio between PBS and pristanic acid solution was 1:1. PBS solution with pH 6.5 was prepared by mixing monobasic and dibasic sodium phosphates with deionized water, and 200 mM of potassium chloride was added as the supporting electrolyte improving the conductivity of the buffer. As before, in addition to the PBS/pristanic acid mixture, 3 mg of adenosine triphosphate (ATP) (purchased from Sigma-Aldrich), 3 mg magnesium chloride and 3 mg coenzyme A (CoA) (purchased from Sigma-Aldrich) were added. This solution was incubated in -20°C freezer for 3 days.
The applied potential for amperometric i-t curve measurement was +0.4 volt vs. Ag/AgCl and each measurement was run up to 360sec. In our AMACR plus serum measurement the applied potential was +0.7 volt vs. Ag/AgCl, however, +0.4 volt vs.
Ag/AgCl was also used and the results showed that this applied potential was sufficient for complete oxidation of the H2O2 produced. 5 µl of substrate solution was first mixed with 1 µl of Peroxisomal acyl-coenzyme A oxidase 3 (ACOX3) and then mixed with 1 µl of blood sample from hospital. After one hour of incubation in room temperature, 5 µl of the mixture was drawn and placed on the sensor for measurement.
50
Results and discussion
H2O2 Measurement
A series of measurement for difference concentration of H2O2 was performed and compared in this study. As shown in Figure 20, a cyclic voltammogram was first obtained. The separation between solution with 0.5 mM of H2O2 and PBS solution was observed in the cyclic voltammograms. This difference between the two curves could be observed over the whole potential range. This indicated that H2O2 was detected over a wide range of applied potential. However, a low potential was preferred in order to minimize any interference derived from the oxidation of any species at a higher potential.
Figure 20 Cyclic voltammogram of H2O2 and PBS solution.
51
+0.25 Volts against Ag/AgCl reference electrode was selected as the applied potential for the amperometric i-t measurements. At this potential, sufficient distinction between present and absent of H2O2 existed and it was also low enough and interfering species was not oxidized at this potential. The resulting amperometric i-t measurement was shown in Figure 21. At time zero, the current was infinitely high the starts to decay rapidly until it was stabled and leveled. This phenomenon was described by Equation 6,
Cottrell’s equation, where � ∝ ! ; therefore, when t equals to zero, i reached infinity. !"
Figure 21 Amperometric i-t curve measurement for H2O2 of different
concentrations
According to Cottrell’s equation, current was proportional to the concentration
! of H2O2, � ∝ �!!!!. The relationship between current and concentration was linear as shown in Figure 21. PBS solution containing 0 mM of H2O2, concentration and
52 measurements started from 0.1mM to 0.5mM with an increment of 0.1mM. The gaps between curves of different concentration were evenly spaced showing good linearity.
The relationship between concentration and current was established. First, a fixed time was selected as shown in Figure 21 by the vertical dotted red line at 150 second. Currents and concentrations intersecting the dotted red line were plotted and shown in Figure 22. The resulting results showed linearity between concentration of
2 H2O2 and its oxidation current. The coefficient of determination, R , was as high as 0.99.
Coefficient of determination was a term used in statistics. In linear regression,
R2, is simply the square of correlation coefficient, R. Developed by Karl Pearson, an
English mathematician, the correlation coefficient was represented by
! 1 � − � � − � � = ! ! � �! �! !!! where, n = number of data points
Xi = value of X at i
� = mean of X sX = standard deviation of X n = number of data points
Yi = value of Y at i
� = mean of Y sY = standard deviation of Y Equation 7 Correlation coefficient, R
53
R2 was a measure of regression having an value between 0 and 1.0. When R2 equaled to 1.0, it suggested that the sample data fitted the regression line very well.
However, at 0, it meant that there was no correlation between data and regression line.
2 In the measurement of H2O2, R equaled to 0.99 which meant that 99% of the data in y, current could be explained by the linear relationship between x and y, concentration and current respectively.
Sensitivity was represented by the slope of the concentration vs. current curve which was equaled to 0.16mM/µA. Because the Ir-C sensor was a single-use disposable sensor, each measurement was performed using a fresh new sensor. In Figure 22, the y error bars represented the standard deviation at each H2O2 concentration. Average of the standard deviations of each concentration was only 0.0023 µA. This meant that repeat measurements of a same concentration, on average, only deviates 0.0023 µA.
Figure 22 Concentration versus oxidation current for H2O2 measurement
54
AMACR Measurement in PBS Solution
A cyclic voltammogram assisted is determining the reproducibility of beta- oxidation and forming H2O2. Additional information such as the potential used for amperometric i-t curve was determined through the aid of a cyclic voltammogram.
Figure 23 was a comparison between substrate, substrate with ACOX3, and substrate with both ACOX3 and AMACR. The curves indicated as pristanic acid + PBS (ATP,
Mg2+ and CoA were added into this solution and incubated for a minimum of two days) which was used as a reference. Figure 23 confirmed the previous discusion regarding the generation of H2O2 from pristanic acid with the aid of AMACR and ACOX3. When
ACOX3 was added into the background, as illustrated in the figure, current rose above that of the background. This result was a good evidence that (2S)-pristanoyl-CoA and
(2R)-pristanoyl-CoA was successfully produced from pristanic acid solution, and
ACOX3 had catalyzed the β-oxidation of (2S)-pristanoyl-CoA and H2O2 was generated.
Also as illustrated in Figure 23, when AMACR was further added into the solution, the current rose even higher, suggesting that the present of higher H2O2 concentration. This suggested that more (2S)-pristanoyl-CoA was converted from (2R)-prstanoyl-CoA catalyzed by AMACR. Higher concentrations of (2S)-pristanoyl-CoA implied a greater quantity of H2O2 which would be produced through the β-oxidation catalyzed by
ACOX3.
The results indicated the procedure for transferring pristanic acid into its coenzyme A esters form was successful. The raise in current in “pristanic acid + PBS +
ACOX3” offered a proof (2S)-pristanoyl-CoA present in our pristanic acid substrate solution and ACOX3 was able to create H2O2. The further increased in current was
55 observed when AMACR was added to the mixture proving the present of (2R)-prstanoyl-
CoA. It suggested that AMACR could effectively catalyzed the reaction of (2R)- prstanoyl-CoA transferring to (2S)-pristanoyl-CoA.
Figure 23 Cyclic voltammograms of the current generated through the beta-
oxidation pathway (AMACR = 0.0065µg/µl). A comparison between the present
and absent of AMACR and/or ACOX3.
Between the applied potential of -0.2 ~ +0.7 Volts vs. Ag/AgCl reference electrode, pristanic acid did not contribute in the raising of the current. As shown in
Figure 24, pristanic acid did not add to the interference in the potential range applied. In fact, the addition of pristanic acid actually just altered the shape of cyclic voltammogram because the solution resistivity had been changed and hence, changing the resistance
56 overpotential. This would not affect the AMACR measurement because PBS + pristanic acid was used as the base solution instead of PBS.
Figure 24 Cyclic voltammograms of PBS + Pristanic Acid and PBS only
In Figure 23, an increase in current for the pristanic acid + PBS + ACOX3 +
AMACR curve was observed. At this stage, we needed to first verify the source of the increased current. The addition of AMACR may cause the current to increase, it would be important to understand the mechanism leading to such an increase. In order to ensure that the increase in current was due to the oxidation of H2O2, we compared the cyclic voltammograms of PBS and PBS + AMACR. In the PBS + AMACR sample, there was neither prsitanic acid substrate solution nor ACOX3. In Figure 25, the cyclic voltammograms were shown. The voltmmeograms of PBS and PBS + AMACR overlapped each other and were almost identical. The results confirmed that AMACR
57 alone would not increase current and it was undetectable by the Ir-C sensor. Thus the increase in current of the voltammogram including AMACR in Figure 23 was due to the generation of H2O2 through the pathway described earlier.
Figure 25 Cyclic voltammograms of PBS + AMACR (0.0065µg/µl) and PBS only
ACOX3 Reaction Time
Currently, no available information regarding the enzyme activity of ACOX3 was available. However, it was important to obtain an estimation of the rate of ACOX3 which could catalyze (2S)-pristanoyl-CoA into generating H2O2. This played a crucial role in measureing AMACR concentration. If there were two samples, one containing x amount and other containing 2x amount of (2S)-pristanoyl-CoA, the time required was essential for the entire 2x of (2S)-pristanoyl-CoA to be converted into H2O2. For example, if the time given for reaction only allows x or less than x amount of (2S)- pristanoyl-CoA to be converted, differentiating the two samples would be impossible.
58
Therefore, a test was conducted to in order to determine the time required for ACOX3 converting all of the (2S)-pristanoyl-CoA in 5µl of prsitanic acid substrate solution.
ACOX3 was relatively fast in converting (2S)-pristanoyl-CoA into H2O2.
Figure 26 showed that most of the (2S)-pristanoyl-CoA in 5µl of substrate solution was converted into H2O2 within 5 minutes. Four samples were tested as shown in Figure 26a.
One of the samples contains no ACOX3 and was used as a baseline. Reaction times experimented includes 5, 30 and 60 minutes. An obvious current difference could be observed in the absent and present of ACOX3. In the present of ACOX3, with only 5 minutes of reaction time, a rise in current could be observed. Beyond 5 minutes, the current remained constant through 1 hour, the longest reaction time tested. All (2S)- pristanoyl-CoA in 5µl of substrate solution were converted in 5 minutes or less. If the amount of (2R)-pristanoyl-CoA in 5µl of substrate solution was identical to that of the
(2S)-pristanoyl-CoA, then, for example, a mere 10 minutes or less should be sufficient to complete the process.
Figure 26 a) Sample vs. Current; b) Time vs. Current
59
On the other hand, enzyme activity of AMACR was also not known. No literature or even the manufacture, where AMACR was purchase, could provide additional information about the rate of AMACR could catalyze the reaction of (2R)- pristanoyl-CoA transferring to (2S)-pristanoyl-CoA. In addition, the actual concentration of (2S) and (2R) pristanoyl-CoA in 5µl of substrate solution were unknown.
Through trial and error approach, it appeared that, in the case of detecting
AMACR in the absent of blood, at least 30 minutes was required in order to provide enough discernible currents for detection. In the case when blood serum was used, an hour of reaction time was required.
Information for the enzyme activity of AMACR was useful but not a requirement in this research. If large amount of (2R)-pristanoyl-CoA was available and the time for AMACR to catalyze the (2R)-pristanoyl-CoA was sufficient and was a constant, the concentration of AMACR could then be determined.
Comparing with ACOX3, AMACR required longer time to catalyze the 2R to
2S process to a detectable level. AMACR catalysis was the rate limiting step. When
AMACR and ACOX3 were both mixed with substrate solution, almost immediately, the
(2S)-pristanoyl-CoA converted from (2R)-pristanoyl-CoA and would be transformed into H2O2.
AMACR Concentration Measurement
As shown in Figure 27, a linear relationship between AMACR concentration and oxidation current from 0 to 0.0065 µg/µl was established. Figure 27 showed repeated measurements over 3 consecutive days using the same pristanic acid solution
60 prepared on day 0. The only difference for the 3 measurements was the length of incubation time. Day 1 meant an incubation period of 1 day, day 2 being 2 days and day
3 being 3 days. As mentioned previously, reproducible measurements was achievable with incubation time longer than 2 days. The square of correlation coefficient, R2, for the day 1 was much lower than that of day 2 and day 3. It was important to determine the incubation time required allowing sufficient amount of pristanic acid to be transferred into pristanoyl-CoA and the duration for the solution becoming inactive.
Figure 27 Linear relationship between current of the H2O2 generated through the
beta-oxidation pathway and the concentration of AMACR
Figure 27 showed that after an incubating time of 48 hours the substrate solution, the measured results showed good linearity. In the entire detection process, the
61 most time consuming step was the incubation of substrate solution. Therefore, if this time was shortened, the AMACR detection process would be more efficient.
The longest incubation time attempted in this study was 11 days. After 11 days of incubation, as shown in Figure 28b, the substrate solution remained functional.
Comparing with Figure 28a, current in Figure 28b was slightly higher. This indicated that more pristanoyl-CoA may be produced with time. However, the small increase in current from the 9 extras days appeared to be insignificant.
Figure 28 ACOX3 reaction time comparison a) 2 days vs. b) 11 days
SLC27A2 for the Reduction of Incubation Time
Very long-chain acyl-CoA synthetase (SLC27A2) was an enzyme that converted free long-chain fatty acids into fatty acyl-CoA esters. It activated long-chain, branched-chain and very long chain fatty acids containing 22 or more carbons to their
CoA derivates. In this case, SLC27A2 could possibly shorten the 48 hours incubation time of substrate solution. A comparison between the present and absent of SLC27A2
62 was given in Figure 29. In Figure 29a, current measurement was performed after the substrate solution was mixed with SLC27A2 and incubated for 1.5 hours. R2 is comparable for the two substrate solutions, 1.5 hours incubation with SLC27A2 and 1 day incubation without SLC27A2 as shown in Figure 29b. Higher current shown in
Figure 29b comparing to that in Figure 29a, in the absent of SLC27A2. The results showed that after 1 day of incubation, the amount of pristanoyl-CoA converted remained greater than in the present of SLC27A2 (1.5hours). The sensitivity in the absent of
µA µA SLC27A2 was 1.45 comparing to 11.17 without SLC27A2. Though (µg/µl) (µg/µl) both the sensitivity and amount of pistanoyl-CoA converted appeared to be lower in the present of € SLC27A2, however, the incubation€ time was significantly reduced in the present of SLC27A2. Hence, the use of SLC27A2 in order to shorten incubation time would be worth for further investigating.
Figure 29 Comparing concentration versus oxidation current of samples a) with
SLC27A2 (1.5hours incubation); b) without SLC27A2 (1 day incubation)
63
AMACR Concentration Measurement in Serum
It was possible to detect AMACR using pristanoyl-CoA as substrate and
ACOX3 to aid the production of H2O2. However, prior to test this method, we need to ensure our approach was valid or blood contained potential interferences. Proteins, antibodies, antigens and so on could be sources of interference. Two of the major interferences were uric acid and ascorbic acid. Under an applied potential, uric and ascorbic acids could be oxidized resulting in additional oxidation current.
In this study, we mixed human blood serum with AMACR. Figure 30 showed a linear relationship between concentration of AMACR and current measured existed in the presence of ascorbic acid and uric acid. This was an evident of that our sensor and process had good selectivity towards the detection of AMACR.
64
Figure 30 Concentration vs. oxidation current of AMACR in serum
Comparing the results in Figure 30 and Figure 27, measured current was higher in human serum. Also, higher potential was need due to the change in chemistry of the solution with the addition of blood serum. Comparing the sensitivities of measurements in environments with and without interferences from blood, as shown in
Table 6, the sensitivity was higher in human serum. In the case of testing in human serum, higher potential was applied to overcome the higher resistivity of serum.
Consequently, as applied potential increased, deviation increased simultaneously. The total amount of deviations for different experiments, day 1 to 3 and serum, were averaged and presented in Table 6. Because the present of serum and the increase in applied potential, the average of standard deviation was higher comparing data from day 1 to 3.
However, sensitivity of the serum samples also increased due to the increase in applied potential.
65
Average of standard Sample sets (applied µA Sensitivity ( ) deviation from data points g/ l potential) (µ µ ) (µA)
Day 1 (0.45V) € 11.17 0.0066 Day 2 (0.45V) 14.00 0.00932
Day 3 (0.45V) 11.73 0.0049375
Serum (0.7V) 52.16 0.095364816
Table 6 Sensitivity and average of standard deviation
The Gleason grade and score indicated the rate of prostate cancer spreading.
Number of 1-5 was used to grade tumors. Grade was decided by inspecting biopsied samples with microscopes and through their appearances determined by pathologists who graded these samples. The Gleason score was consisted of two grade numbers, a primary and a secondary grade. The majority of tumor was represented by the primary grade and the second most common tumor was represented by the secondary grade. Primary grade represents more than 50% of tumor while secondary grade represents 50% to 5% of tumor. Gleason score was a good indication of the severity of prostate cancer. [95-97]
Gleason Score Representation
2-5 Low-grade prostate cancer. The aggressiveness of cancer is low
6-7 Intermediate grade cancer (most prostate cancers fall into this
group). The aggressiveness of cancer in intermediate.
8-10 High-grade cancer. Cancer highly aggressive.
Table 7 Gleason scores and their representations
66
As shown in Table 7, severity of cancer increases with Gleason score.
Because there was a primary grade and a secondary grade, patients with same Gleason score were not identical. Two patients with the same Gleason score of 7, one with 4+3 and the other with 3+4, the severity of the 4+3 patient was greater than that of the 3+4 patient because the former had a higher primary grade.
Hospital Samples
24 samples were provided by the University Hospitals of Cleveland Ohio for blind test. Among the 24 samples, 5 samples were from patients with prostate cancer but the information was kept secret prior to our measurements. Table 8 listed the Gleason score, PSA level and AMACR level of these 24 samples. 10 of the samples were from patients with HGPIN and the mean PSA level, 18.86ng/mL. The PSA levels of these samples were higher than those of the prostate cancer patients. Hence, PSA level was unable to differentiate patients with HGPIN from patients with prostate cancer. On the other hand, AMACR level was a capable indicator that could differentiate prostate cancer patients from healthy people and individuals with HGPIN. This was a significant improvement for detecting prostate cancer over the current PSA detection.
67
Healthy HGPIN Prostate Cancer
Controls (N = 10) Cases
(N = 9) (N = 5)
Gleason score, N (%) N/A N/A
3 + 3 4 (80%)
3 + 4 1 (20%)
Mean (SD) Plasma PSA, 2.31 (1.67) 18.86 (7.43) 15.81 (11.43)
ng/mL
Mean (SD) Plasma AMACR, 0.005 (0.001) 0.0004 0.077 (0.10)
µg/µL (0.0005)
Table 8 Population description and mean AMACR levels by patient group
Elevated AMACR level was shown consistently in cancer patients. Higher
AMACR content resulted in higher H2O2 production in a fixed reaction time. At a higher
H2O2 concentration, oxidation current was increased. This allowed us to differentiate between samples of the prostate cancer patients and others. As shown in Figure 31a and b, 5 of the data points were clearly having AMACR concentrations. In Figure 31c, data points circled by the red oval (sample 21~25) were confirmed cases of prostate cancer patients by University Hospitals. The data points inside the green oval are from healthy individuals and HGPIN patients.
68
Figure 31 Blind test results of patients’ plasma samples provided by University
Hospitals. a) Sample vs. Oxidation Current from biosensors; b) Sample vs.
Concentration of AMACR c) Concentration of AMACR vs. Oxidation Current from
Biosensor. (Note: Sample 10 is not available)
According to University Hospitals, among the 24 samples provided, 5 of them were from prostate cancer patients, sample 21-25. Sample 1-9 were from healthy men and sample 11-20 are from individuals with HGPIN. The accuracy of detecting prostate cancer and differentiating it from healthy and HGPIN individuals was 100%. All of the 5 prostate cancer samples showed elevated AMACR level and accurately detected.
69
Conclusion
The relationship between AMACR and prostate cancer was confirmed.
Patients with prostate cancers were associated with elevated AMACR content. Using Ir-
C biosensor along with the pathway of transferring pristanic acid to H2O2, we were able to detect and measure different concentration of AMACR. Linear relationship established between the measured current and AMACR demonstrated the feasibility of the pathway and the ability to determine concentration of AMACR through the detection of H2O2.
AMACR were successfully detected in test samples with and without blood serum. Only simple adjustments of the conditions such as applied potential, pH of PBS and reaction time were required in order to achieve the evaluation of AMACR in PBS and in human blood serum. In the present of blood serum, interferences such as ascorbic acid and uric acid did not affect the detection and measurement of AMACR.
Blood samples of 24 people were provided by University Hospitals. 5 of the samples were from prostate cancer patients. 100% of accuracy was achieved in detecting the AMACR as a biomarker for prostate cancer of these samples. Unlike PSA screening,
HGPIN samples were not confused with that of prostate cancer and were successfully separated. Consequently, detection of AMACR provided great accuracy and less false positive in testing prostate cancer. This result showed the potential of AMACR as the new biomarker for prostate cancer and our Ir contained biosensor can be used to efficiently, cost effectively and accurately to detect AMACR in actual blood samples from patients.
70
Future Research
In order to shorten the incubation time for the substrate solution, addition of
SLC27A2 could accelerate this incubation step. We demonstrated that in the present of
SLC27A2, instead of incubating for days, only 1.5 hours of incubation time was needed for the detection of AMACR. The sensitivity of the detection was lower comparing to results obtained from days of incubation without SLC27A2, and future research would further define the incubation time required in the present of SLC27A2.
The lowest AMACR concentration detected in this study was 0.0029 µg/µl.
According to Z.M. Liu’s research, AMACR concentration of a healthy person is
0.000001 ~ 0.000005 µg/µl. In the study, the concentration of AMACR in prostate cancer patients was 20 times greater than the normal concentration, making the AMACR concentration of a prostate cancer patient equaled to 0.00002 ~ 0.0001 µg/µl.[32] Our lower detection limit was 29 ~ 145 times greater than the suggested AMACR concentration of a prostate cancer patient. Therefore, in practical applications, we needed to either lower the detection limit or to increase AMACR concentration in the serum higher. However, in our study, the limitation for prostate cancer was set around 0.1
µg/µl. This was significantly higher than that suggested by Z.M. Liu. The difference may be due to many parameters. Age, race, stages and grades of cancer, time of blood sample extraction (before/after biopsy) etc. could all have an effect on the measured concentration of AMACR. More studies would be needed to establish relationships between AMACR and these variables.
71
When AMACR concentration was lower than our detection limit, as shown in
Z.M. Liu’s study, we proposed to use a secondary method: namely to concentrate the
AMACR level in serum. This could be achieved by the use of a centrifugal filter device.
The molecular weight of AMACR was 47.52kDa and, with this information, the Amicon
Ultra centrifugal filter unit from Sigma with a molecular weight cut-off (MWCO) at
50kDa seems to be suitable for this application.[98] This filtration system allowed anything greater than 50kDa appeared be retained by the membrane. Using a sample volume 100 times greater than that needed for measurement and this centrifugal filter unit, we should be able to concentrate the AMACR 100 times. Thus, with the lower detection limit of 0.0029 µg/µl and 5µl total volume, using this filtration system we would be able to detect AMACR using our biosensor.
Finally, we still need to test our ability to detect AMACR in urine samples.
Urine samples are much easier to collect comparing to blood sample. Large quantity of urine could be easily collected without causing any discomfort to patient.
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Part II: Background and Introduction
In Part I of this dissertation, we discussed the usage of an established Ir-C sensor to detect prostate cancer. In Part II of this dissertation, we will discuss developing novel electrode materials in order to enhance the detecting of H2O2.
As mentioned in Part I of this dissertation, the detection of H2O2 played an important role as a base for many measurements of enzymatic reactions. Biomarkers of many diseases could be enzymatically catalyzed into generating H2O2. In Part I of this dissertation, we demonstrated that by detecting H2O2 generated through an enzymatic reaction, we were able to estimate the concentration of AMACR and to determine the present of prostate cancer. Other examples diseases included diabetes, heart disease etc.
Platinum was a superior catalyst however, its performance often decayed due to poisoning of the active sites. Incorporating an additional element into the Pt could minimize the effect of poisoning and further improve the performance of the platinum catalyst.
Hydrogen Peroxide (H2O2)
Hydrogen Peroxide was a clear liquid and a strong oxidizer. In 1818, a
French chemist, Louis Jacques Thenard was the first to discover and describe hydrogen peroxide. He first produced H2O2 by reacting barium peroxide with nitric acid.[99, 100].
In 1885, the production of H2O2 was improved by reacting barium peroxide with phosphoric, hydrochloric and sulphuric acids.[101]
���! + �!��! → �!�! + ����!
Equation 8 Production of H2O2
73
Today, many more advanced ways of H2O2 production were invented.
Among them the most common commercial process of H2O2 manufacture was Riedl-
Pfleiderer or anthraquinone process.[102, 103] This process used the autoxidation of 2- alkyl anthrahydroquinone to the corresponding 2-alkyl anthraquinone . During this process, H2O2 was generated. As shown in Figure 32, AHQ was transferred to AQ to generated H2O2 and AQ could be reduced back to AHQ so the cycle of H2O2 production continued.
Figure 32 Anthraquinone process of hydrogen peroxide production[104]
Applications of H2O2
Because of its strong oxidizing properties, H2O2 was commonly used as bleach and cleaning agent. Other than these common applications, H2O2 played a significant role in the field of biosensing technology.
74
It was Clark and Lyons[105] who first demonstrated using an amperometric sensor to oxidize and detect H2O2 for the purpose of glucose measurement. Many enzymatic reactions generated H2O2. Therefore, similar to the example we demonstrated in Part I, if a linear relationship could be established between a biomarker and H2O2, it was possible to utilize an amperometric sensor to detect this biomarker.
Role of H2O2 in the Detection of Diseases
Diabetes was a metabolic disease that occurred when the blood sugar level of a person was dangerously high. If not treated, diabetes can caused heart diseases, kidney diseases, and retinal damages.[106] Most common way to diagnose diabetes was to measure the glucose level in blood.[107-110] Generation of H2O2 through the enzymatic reaction involving glucose and glucose oxidase as described below
!"# � − ������ � − ������������� + �!�!
GOx = glucose oxidase
Equation 9 Enzymatic reaction of Glucose to Hydrogen Peroxide[110]
Cholesterol could also be monitored through the measurement of H2O2.
Cholesterol was used to diagnose disease such as coronary heart disease, myocardial infarction and arteriosclerosis. Cholesterol was oxidized with cholesterol oxidase
(ChOx) forming 4-cholesten-3-one and H2O2.[111] H2O2 was then measured by electrochemical oxidation.
Liver disease was another example where H2O2 detection was used utilizing in aiding the diagnosis of such disease. Common biomarkers for liver diseases included cholesterol, bilirubin and aminotransferases.[112] All three of the biomarkers underwent
75 enzymatic reactions generating H2O2, which can then detected by an electrochemical sensor.
The diagnose of Alzheimer’s disease was also reported to correlated to
H2O2.[113] Many detections of disease biomarkers actually measured H2O2. Extensive amount of work were reported in the field of medicine with biosensing related H2O2 applications. More ongoing and future researches focused on enzymatic reaction of biomarkers that eventually lead to the generation of H2O2.
Because of the significant role H2O2 played in the field of biosensing technology, the pursuit of improving H2O2 sensors was equally important. In Part I of this dissertation, we discussed four strategies of minimizing interference during H2O2 detection. One of the strategies was to utilize metals with good electrocatalytic properties. The sensor used to detect prostate cancere utilized Ir nanoparticle as part of the electrode material to electrocatalyze the redox reaction of H2O2.
Platinum
In part II of our research, we chose to use electrocatalyic properties of metals in order to enhance the performance of H2O2 detection. Common metals catalysts used for biosensing applications of H2O2 included platinum, palladium, gold, and iridium.
More than often, platinum was the material of choice because its greatest catalytic ability for many applications.
Platinum was known for its resistance to corrosion and higher temperature as well as its stability under applied electrochemical potential. In addition, Pt showed superior electrocatalytic properties. The decomposition of H2O2 into water and oxygen gas is strongly catalyzed by Pt.[114]
76
�!�! + ��!" ↔ ��!" ∙ �!�!
! ��!" ∙ �!�! → �� + 2� + �!
! �� → ��!" + 2�
Equation 10 Mechanism of H2O2 binding to and being oxidized by Pt[115]
PtBS represented the surface binding site of Pt. Series of steps shown in
Equation 10 was the mechanism of H2O2 being oxidized by Pt. In the first step, H2O2 was bound to the binding sites of Pt. Then electrons were transferred from H2O2 to PtBS making PtBS to Pt. Finally, Pt gave up two electrons and changes back to PtBS completing the circuitry. The circle of oxidating H2O2 by Pt electrode then continued. Because Pt surface was susceptible to poisoning, the number of binding sites decreased resulting in slowing the whole process.
Poisoning of Platinum
Poisoning of electrode significantly degrades the performance and efficiency of an electrode due to the blockage of active sites on electrode surface by poison species.
In the field of fuel cell, poisoning of Pt by carbon monoxide (CO) was reportd. Usually a small trace quantity of CO was introduced into the system, and the fuel cell efficiency was significantly reduced.[116] In the present of CO, it was absorbed to the surface and blocking the active sites of Pt. In the field of biosensing technology, the present of CO was uncommon, however, other species such as hydroxide (OH-) was specie known to poison Pt electrode as well.[117]
The mechanism of poisoning electrode materials was not yet fully understood.
A solution to minimizing to poisoning of metal was proposed by Watanabe and
Motoo[118], defined as “bi-functional mechanism”. The idea was that elements in an
77 alloy material would improve the catalytic activity of the alloy surface over a single metal alone. The bi-functional mechanism is most often used to describe the methanol oxidation reaction (MOR), the key reaction for methanol fuel cell. Pt catalyzed the methanol oxidation reaction but with time, the performance degraded due to Pt poisoning.
Intermediates such as COabs were adsorbed onto the Pt surface covering up the active sites and hence, the catalytic activity significantly decreased. The adsorption of oxygen- contained species was more readily on Ru at lower potential than comparing with Pt.
Therefore, by incorporating Ru into Pt, the overall performance should increase.
Bimetallic Pt-Ru electrode were studied extensively and improvement in performance were reported.[119-121] However, there were fewer studies on biosensing applications utilizing bi-metallic electrode material, Pt-Ru.
Pt-Ru Electrode
Fuel cell studies showed that by combining Ru with Pt, the Pt electrode was less susceptible to CO poisoning. Although carbon monoxide generally was not a
+ concern in biosensing, Pt was susceptible to be poisoned by species such as O2 and H .
! ! �!�! → �! + 2� + 2�
Equation 11 Oxidation of H2O2
+ As shown in Equation 11, O2 and H were both products of H2O2 after oxidation.
��!" + �! ↔ ��!" ∙ �!
Equation 12 Poisoning of Pt by O2 [115]
! ! ��!" ∙ �!�! + � ↔ ��!" ∙ �!�! ∙ �
Equation 13 Poisoning of Pt by H+ [115]
78
+ Mechanism describing the O2 and H poisoning the active sites of Pt was given in Equation 12 and Equation 13. Blockage of the binding sites of Pt prevented and slowed down further catalysis of H2O2.
Through calculation and simulation, several studies [122-126] showed that Ru required less activation energy than Pt to absorb OHabs and Oads. This could be observed on a volcano plot from Sabatier principle.[127] The volcano plot in Figure 33 related the binding energy with catalytic activity towards oxygen. Sabatier,[128] a French chemist, stated that an optimum interaction between catalyst and substrate was when the activity was high and the binding was neither too strong nor too weak. If a binding was too strong, products would be unable to dissociate from the catalyst sites and hence preventing further catalysis. If it was too weak, there would be no binding between catalyst and substrate, and as a result, there would be no reaction. The x-axis of Figure
33 represents the chemisorptions, which was an adsorption involving chemical reaction.
The strength of chemisorption increased as ΔEO decreased and vice versa. Strong chemisorption suggested that the binding between substrate and catalyst was strong and dissociation between them was difficult. Platinum was at the tip of the volcano plot, which indicated that it was more active in oxidizing oxygen. However, Pt was susceptible to poisoning. Because Ru was at the further left of Pt, mixing Pt and Ru together could minimize poisoning of active sites of Pt. Consequently, more active sites of Pt would be available for catalyzing the decomposition of H2O2 and therefore, the performance of H2O2 detection is enhanced. This concept can be applied to the oxidation and adsorption of OH as shown in Figure 34.
79
Figure 33 Volcano plot of oxygen oxidation[127]
Figure 34 Catalytic activity as a function of O and OH binding energy[127]
In this research, Pt/Ru nanoparticles were synthesized using sodium borohydride (NaBH4) reduction. NaBH4 reduction was a common method for precipitation Pt/Ru nanoparticles at low temperature. The idea for precipitation Pt or Pt-
80 based nanoparticle was as simple as adding a reducing agent to a platinum-salt solution.[118] A bimetallic catalyst was made by simultaneously precipitate a solution containing the precursor salts of both metals. In the case of preparing bimetallic Pt/Ru catalysts, a solution containing H2PtCl6 and RuCl3 were reduced using sodium borohydride. In this study, we followed the preparation method for Pt/Ru nanoparticles proposed by Shimazaki et al.[129]
The amperometric properties of Pt, Ru and Pt/Ru nanoparticles as electrode materials were compared. Rotating disk electrode (RDE) was employed for the studies of amperometric properties. Material characterization instruments such as TEM and XEDS were used to illustrate the effects of the microstructures and chemical compositions on the electrochemical properties of these nanoparticles.
Rotating Disk Electrode (RDE)
Rotating disk electrode was emplThreeoyed in this study and it was an arrangement using a three electrodes. It was categorized as a hydrodynamic working electrode and was used to typically study redox reactions. As the name RDE suggested, during experiments, the electrode rotates.[130] A typical construction of a RDE, as schematically shown in Figure 35, was with a disk electrode embedded in an insulating material and they were connected to a motor which was responsible for the rotation of the electrode. During rotation, solution near the electrode was span away from the electrode and solution from the bulk was drawn perpendicularly to the electrode surface.
Consequently, the rate of reaction was no longer controlled by diffusion as in an unstirred arrangement but was controlled mainly by convection.
81
Insulating Material Disk Electrode
Laminar Flow
Figure 35 Schematic of a rotating disk electrode
For a redox reaction, electrons were transferred between the solution and the electrode. For reactant to be continuously transferred to product, it was necessary to have constant removal of product from the electrode and constant introduction of reactant to the electrode.[131] Thus, mass transport became a dominate consideration. There were three forms of mass transport: diffusion, convection and migration. Diffusion occurred when there was a concentration gradient. Convection existed when an external mechanical energy was applied (e.g. RDE). Migration was for charge species and it took place when there was a potential gradient.
Nernst diffusion layer model, shown in Figure 36, stated that there were two zones.[131] In one zone, the bulk solution, concentrations of species were constant. In this zone, there was only convection and no diffusion. The second zone was the diffusion zone and the assumption was that this layer was immobile; therefore, diffusion was the only form of mass transport in this area. The thickness of the diffusion layer, δ, was described by Veniamin Grigorievich Levich as
82
� = 1.61�!.!""�!.!!�!!.! where,
v = kinematic viscosity of the solution
D = diffusion coefficient
ω = angular rotation rate of the disk = 2πN (N = revolution per second)
Equation 14 Thickness of the Nernst diffusion layer
Increase in rotation rate decreased the thickness of the diffusion layer; hence, minimized the influence of diffusion. The increase in rotation rate could increase the limiting current as described by Levich’s equation[132],
!/! !!/! !/! �!"#"$ = 0.62����!"#$� � � where,
n = number of electrons transferred
F = Faraday’s constant
A = electrode area
Cbulk = concentration of the bulk solution
Equation 15 Levich’s equation
83
Diffusion Convection
Cbulk Concentratoin Electrode
Bulk Solution
C = 0 X = δ x = 0
Distance away from electrode
Figure 36 Nernst diffusion layer model
Transmission Electron Microscope (TEM)
TEM was a powerful microscopy instrument allowing imaging structures as small as columns of atoms. The resolution of TEM was ideal for studying nanoparticles.
During operation, a beam of electron was transmitted through an extremely thin sample.
The small wavelength of electrons gave TEM its high resolution which was impossible to achieve with light. However, vacuum was crucial preventing electrons form interacting with anything other than specimen. In our research, a TEM with 300keV accelerating voltage was utilized and at this voltage, the wavelength of the electron was approximately
0.02Å. For visible light, the wavelength was between 380 to 740 nm.
There were many functions of TEM. In this research, a high power microscope to study the size, distribution and shape of the nanoparticles was used.
Contrast was formed by the interaction between electrons and the sample. When electron beams passed through an empty space, it appeared as a bright area in the final image.
84
Conversely, it appeared darker in the image when electron beams diffracted as they passed through areas that are occupied, such as by nanoparticles.
Energy-Dispersive X-ray Spectroscopy (XEDS)
The TEM, Tecnai F30 FEI, used in this research was equipped with energy- dispersive X-ray spectroscopy, which was often used to elemental characterization. Each element had its own characteristic X-ray. Energy from the incident electron beam interacted with the specimen and excited an electron from the inner shells of an atom.
The electron from the inner shell was then ejected outside of the atom and an electron hole was left. This was an unstable state; therefore, an electron from an outer shell with higher energy dropped down filling the electrons hole, and at the same time X-ray was emitted. The energy of the X-ray represented the energy different between the two shells.
The energy could be detected by a Si(Li) detector. By analyzing the energy of the emitted X-ray, elements within a specimen could be identified.
85
Experiments
Chemical Materials for the Synthesis
The precursor salt for Pt was hydrogen hexachloroplatinate (IV) hexahydrate
(H2PtCl6•6H2O, 37.5% Pt Basis) and the precursor salt for Ru was ruthenium (III) chloride hydrate (RuCl3•nH2O, 99.8% purity). Citirc acid (99.5 wt.%) was prepared and used as the capping agent to stabilize nanoparticles preventing them from aggregation.
Sodium borohydride (NaBH4, 99 wt.%) was used as the reducing agent. The pH of the solution was adjusted by sodium borohydride. All of the chemicals described above were purchased from Sigma Aldrich. The carbon powder supporting material used was Vulcan
XC 72 carbon black (Cabot, Bonton, MA). Finally, Nafion solution (LIQUION) was purchased from Ion Power Inc.
Preparation of Pt/Ru Nanoparticle Catalyst
Several modifications were made to the preparation method suggested by
Shimazaki. The Pt and Ru precursor salts were both made into metal solution with 1.8 mM by dissolving the precursors separately in deionized (DI) water. 5.55 mL of each solution was then mixed together and the ratio between Pt and Ru solution was maintained at 1:1. The concentration of Pt-Ru of the mixed solution was 0.01 M. Citric acid with a molar ratio of 1:0.42 of the metal solution was added stabilizing and preventing particles from agglomeration. Using 0.1 M of NaOH solution, the pH of the
Pt-Ru solution was adjusted to 7. Finally, the nanoparticle solution was then added drop- wise into NaBH4. The amount of NaBH4 was 1.4 times greater than the theoretical value required to reduce the metal solution. This final solution was stirred overnight allowing the completion of reduction.
86
For preparing the nanoparticle-containing carbon-paste catalyst, the Pt/Ru solution was then sonicated for 30 minutes before mixing with active carbon black powder Vulcan XC. Finally, the solution was again stirred for an entire evening. Liquid was then removed by centrifugation and then dried in a 50°C vacuum environment for 12 to 20 hours.
Material Characterization
TEM images were obtained with Tecnai F30 FEI with an acceleration voltage of 30keV. Samples, Pt, Ru, and Pt/Ru nanoparticle solution were sonicated 3 hours before a droplet of each solution was deposited onto an ultrathin carbon-copper grid purchased from Ted Pella Inc. After, the TEM samples were kept at room temperature till dried. Chemical compositions were performed by utilizing the XEDS system in the
Tecai F30 FEI.
Electrochemical Testing
Amperometric measurements were performed using the three different catalysts to detect H2O2. A glassy carbon rotational disk electrode (RDE) with a diameter of 5 mm was used. The model of the electrochemical workstation was Model 660C from
CH Instrument. Before depositing any chemical, the electrode was cleaned thoroughly by rinsing with isopropanol then with acetone. Then it was polished with a 0.05µm aluminum powder solution. Finally, a 10 minutes sonication was applied to ensure all of the remaining residues were removed.
First, 8 mg of the 5 wt. % Pt-Ru nanoparticles was ground and mixed with
200 µl of ethanol. Then, 4 µl of the solution was then deposited onto the glass carbon
87 electrode allowing to dry in room temperature for 10 minutes. Then, 4 µl of 5 wt. %
Nafion solution was placed on top of the dried Pt-Ru solution on the electrode allowing to dry for 10 minutes in room temperature. In this research a three electrode arrangement was applied for the amperometric studies. The arrangement consisted of a Pt counter electrode, an Ag/AgCl reference electrode and the glassy carbon electrode deposited with nanoparticle material of interest as the working electrode. The rotation speed for the
RDE was maintained at 900 rpm, which was determined sufficient for keeping the hydraulic effect. All of the testings were performed in a 0.1M PBS solution with pH equaling to 7.2 and 0.15M of KCl was used as the supporting electrolyte.
Two applied potential, +0.2V and +0.4V versus Ag/AgCl reference electrode, were used for the studies of amperometric properties of Pt, Ru and Pt-Ru.
88
Results and Discussion
Structure
The clusters of Pt particles appeared to be linked to other clusters forming a branch-liked structure as shown in Figure 37. This indicated that the condition of capping agent for synthesizing Pt particles was not ideal. However, for the purpose of comparison and retained the synthesis procedure constant, citric acid remained to be used as the capping agent for all three materials. The size of the Pt particles ranged from 1 to
7 nm, and on average, the size of these Pt particles were 4 nm.
a) b)
Figure 37 TEM images of Pt nanoparticles. Figure 37b) is from the red square of a)
Using the sodium borohydride reduction method, the average size of Ru particles was around 2 nm. However, according to Figure 38, they appeared to be in a form of ill-defined clusters. From these TEM images, it appeared that Ru particles were poorly distributed and heavily clustered.
89
a) b)
Figure 38 TEM images of Ru nanoparticles. Figure 38b) is from the red square of
a)
Comparing to pure Pt and Ru particles, the Pt-Ru particles, shown in Figure
39, were well defined and evenly spread. Size of Pt-Ru particles ranged from 2 to 6 nm.
The average Pt-Ru particle size was similar to the size of Pt particles and was also around
4 nm.
90
a) b)
Figure 39 TEM images of Pt-Ru nanoparticles. Figure 39b) is from the red square
of a)
XEDS was used to confirm the chemical composition of each specimen.
Figure 40 showed the XEDS spectrums of the three materials investigated. As confirmed by these spectrums, syntheses of all three specimens were successful. In the Pt-Ru material, the weight percents for Pt and Ru were 44% and 56% respectively.
91
Figure 40 XEDS of Pt, Pt/Ru and Ru nanoparticles. (Note: Fe peaks were signals from the column of TEM; Cu was the TEM grid used to hold the nano-particles; Na
and O in the Pt-Ru sample could be residuals left during synthesis.
Electrochemical Characterization
The electrochemical performances of all three materials, Pt, Pt-Ru, and Ru, were analyzed. Open circuit potentials, also known as equilibrium potential, for each material were determined. Equilibrium potential was referred to the quist thermodynamic equivalent potential when there was no current flow. In this research, all three of the materials showed different equilibrium potentials. The highest equilibrium potential was
+0.3V versus Ag/AgCl reference electrode for Pt working electrode. The second highest equilibrium potential was from Pt-Ru working electrode; its open circuit potential was
92
+0.25V versus Ag/AgCl reference electrode. The lowest equilibrium potential measured was from Ru electrode and it was +0.00 versus Ag/AgCl reference electrode.
When there was current flow, the difference between actual applied potential and equilibrium potential was known as overpotential. It could be represented by
� = � − �!" where,
η = overpotential
E = applied potential
Eeq = equilibrium potential
Equation 16 Definition of overpotential
In general, there were 3 types of overpotential: activation overpotential, concentration overpotential, and resistance overpotential.
�!"!#$ = �!"# + �!"#! + �!"#$# where,
ηtotal = total overpotential
ηact = activation overpotential
ηconc = concentration overpotential
ηresis = resistance overpotential = iR (usually)
Equation 17 Total overpotential consisting of activation, concentration and
resistance overpotential (usually iR drop)
Activation overpotential referred to the energy required for transferring electrons from electrode to analyte and vice versa. The amount of energy depended on
93 the redox reaction of interest and varied from reaction to reaction. The activation overpotential was related to electric current by Butler–Volmer equation,
� ��� � ��� � = � exp ! !"# − exp ! !"# ! �� �� where,
i = electrode current density
i0 = exchange current density
αa = charge transfer coefficient (anode)
αc = charge transfer coefficient (cathode)
n = number of electrons transferred
F = Faraday’s constant
R = universal gas constant
T = absolute temperature
ηact = activation potential
Equation 18 Butler–Volmer equation
The Butler-Volmer equation was useful when the reaction was controlled by the rate of electron transfer as difference controlled by mass transfer.
Concentration overpotential was caused by the concentration difference between bulk solution and the electrode surface. Because of slow diffusion, as shown in
Figure 36, a concentration gradient could be formed. When the redox reaction was faster than the rate of diffusion, concentration overpotential dominated. Based on the Nernst equation, the concentration overpotential could be expressed as
94
�� �!"#"$ − � �!"#! = ln �� �!"#"$ where,
R = ideal gas constant
T = absolute temperature
n = number of electrons transferred
F = Faraday’s constant
Ilimit = limiting current
i = current
Equation 19 Concentration overpotential
As current, i, increased the concentration overpotential was increased. When i
= ilimit, ηconc became infinite. As shown in Equation 15, the limiting current increased with faster rotation speed. Therefore, utilizing RDE, the effect of concentration overpotential could be minimized.
Resistance overpotential contained many aspects and a wide definition. The capacitance at electrode surface, the diffusion of species across the bulk electrolyte and more could be categorized into resistance overpotential. The design of electrochemical cell played an important role in resistance overpotential. Every component in an electrochemical cell, including electrolyte, electrode, electrode/solution interface, separator etc., contained resistance. However, most commonly, the resistance potential was referring to the ohmic drop of the electrolyte,
95
�!"#$# = �� where,
i = current
R = resistance (electrolyte)
Equation 20 Ohms law describing the resistance potential coming from the
resistance of electrolyte
The overall overpotential was experimentally measured but it was rather difficult to evaluate the individual overpotentials by their categories. In this study, we limited in control over the activation and resistance overpotentials. However, through
RDE, we minimized the effect of concentration overpotential.
In summary, the equilibrium potentials for the three electrode materials and their overpotentials were different. Hence, two overpotentials, +0.2V and +0.4V versus
Ag/AgCl reference electrode, were arbitrary selected for the H2O2 detection. The applied potential was then the equilibrium potential with addition of overpotential. For example, in the case of Pt-Ru, the applied potential would be 0.45V or 0.65V versus Ag/AgCl.
96
a)
b) Figure 41 Amperometric i-t measurements a) Overpotential = +0.2V versus
Ag/AgCl reference electrode; b) Overpotential = +0.4V versus Ag/AgCl reference
electrode
97
Figure 41 showed the ampoermetric i-t curves for both overpotential +0.2V and +0.4V versus Ag/AgCl reference electrode. At time 0, the concentration of H2O2 was 0 mM and H2O2 was added every 100 second. In this figure, after the first 100 seconds, each step represented an increase in H2O2 concentration. The corresponding
H2O2 concentrations were 0, 0.5, 1, 2, 3, 5, 7 and 9 mM. Using the measured current from Figure 41, a relationship between the concentration and current could be established as shown in Figure 42.
As listed in Table 9, sensitivities of the electrodes at different potentials were calculated from the results shown in Figure 42. When overpotential was +0.2V, among the three electrode materials, Pt-Ru showed the highest sensitivity. Compared to Pt, Pt-
Ru electrode was 1.6 times greater in sensitivity. Ru electrode had the lowest sensitivity;
Pt-Ru electrode had sensitivity that was 7.9 times greater than Ru alone. However, the sensitivity of Pt electrode surpassed that of Pt-Ru and became the electrode with highest sensitivity when overpotential was changed to +0.4V. In this case, Pt electrode was 1.1 times more sensitive than Pt-Ru electrode.
98
a)
b) Figure 42 Concentration of H2O2 vs. Current a) Overpotential = +0.2V versus
Ag/AgCl reference electrode; b) Overpotential = +0.4V versus Ag/AgCl reference
electrode
99
Material Pt Ru Pt-Ru ηtotal +0.2V 76 µA/mM 15 µA/mM 118 µA/mM
+0.4V 147 µA/mM 45 µA/mM 128 µA/mM
Table 9 Sensitivities of Pt, Ru and Pt-Ru at ηtotal = +0.2V and +0.4V versus Ag/AgCl
At low potential, Pt/Ru was a promising electrode material for H2O2 detection for it offered greater sensitivity than Pt alone. When comparing sensitivity at higher potential (+0.4V) Pt electrode maintained the advantage. However, this advantage was not significant and, in practical use, lower-potential sensitivity was more important. As mentioned before, higher potential increased the risks of oxidizing interfering species.
Thus, detecting H2O2 at ηtotal = +0.2V versus Ag/AgCl reference electrode was preferred.
Even though, at higher potential, Pt electrode had better sensitivity, the average standard deviation of Pt-Ru electrode was lower. As shown in Table 10, the sensitivities of all three electrode materials at the two ηtotal tested. Good stability of
Pt/Ru was indicated as ηtotal increases from +0.2V to +0.4V. Unlike the sensitivities of both Ru and Pt single metal, the Pt-Ru sensitivity remained relatively stable throughout this potential increased.
Material Pt Ru Pt/Ru ηtotal +0.2V 5∗10−5 A 1∗10−5A 6∗10−5A
+0.4V 10∗10−5 A 3∗10−5 A 4∗10−5A
Table 10 Average standard deviation of Pt, Ru and Pt/Ru at ηtotal = +0.2V and
+0.4V versus Ag/AgCl reference electrode
100
At low potential, the Pt-Ru electrode showed improved performance over Pt electrode in detecting H2O2. This result confirmed with our hypothesis earlier. At low potential, Ru adsorbed Oads and OHads more easily than Pt. Therefore, there were more active sites available for catalysis and hence, the improvement in performance. As expected, the performance of Ru , having lower catalysis activity than Pt, and Ru was the worst in both high and low potentials. This was also an indication that Ru was more susceptible to poisoning. The poor particle structure contributed to the bad performance of Ru as well. However, at higher potential, Ru became less effective as Pt started to be poisoned.
101
Conclusion
In this study, we compared 3 electrode materials (Pt, Ru, and Pt-Ru) for their ability to detect H2O2 in biosensing. Through TEM and XEDS, we confirmed that we were able to successfully synthesis Pt-Ru nanoparticles for the use of electrode material.
At low potential, Pt-Ru electrode performed the best because the present of Ru aided in preventing the poisoning of Pt active sites. At the overpotential of +0.2V versus
Ag/AgCl reference, Pt-Ru showed the best sensitivity, 118 µA/mM. When overpotenial was increases to +0.4V, the advantage in sensitivity of Pt-Ru was decreased but with lower average standard deviation, it remained to be a stable electrode material.
Therefore, the bimetallic electrode material which effectively improved the catalytic reaction of H2O2 oxidation.
Another advantage of utilizing bimetallic electrode material was lowering the cost of the electrode materials. On Feb 22, 2013, the price of Pt was $1629/troy ounce and price of Ru was $78/troy ounce. Pt was almost 21 times more expensive than Ru.
Thus, by incorporating Ru in the making of electrode, cost was decreased greatly as less
Pt was required.
102
Future work
As shown in the volcano plot, Figure 33, there were several metals, other than
Ru, that are on the left side of Pt. Combination of different materials should be attempted to access the performance of different bi-metallic electrode materials.
Pt-Ru shown improvement over pure Pt but optimization of the bi-metallic composition was not done in this study. Extended assessment would be needed.
Controlling the size of nanoparticles and composition could affect on the final performance of the electrode.
103
References
[1] "Prostate Cancer: Early Detection," http://www.cancer.org/acs/groups/cid/documents/webcontent/003182-pdf.pdf. [2] "Prostate," http://en.wikipedia.org/wiki/Prostate. [3] C. Huggins, W. W. Scott, and J. H. Heinen, “CHEMICAL COMPOSITION OF HUMAN SEMEN AND OF THE SECRETIONS OF THE PROSTATE AND SEMINAL VESICLES,” American Journal of Physiology -- Legacy Content, vol. 136, no. 3, pp. 467-473, May 1, 1942, 1942. [4] N. N. I. o. D. a. D. a. K. D. NIDDK. "What I need to know about Prostate Problems," http://kidney.niddk.nih.gov/KUDiseases/pubs/prostate_ez/prostate_ez_508.pdf. [5] P. D. Baade, D. R. Youlden, and L. J. Krnjacki, “International epidemiology of prostate cancer: geographical distribution and secular trends,” Mol Nutr Food Res, vol. 53, no. 2, pp. 171-84, Feb, 2009. [6] “What are the key statistics about prostate cancer?,” American Cancer Society. [7] "Prostate Cancer," http://www.cancer.gov/cancertopics/types/prostate. [8] R. H. Riffenburgh, Statistics in Medicine, p.^pp. 102-104: Academic Press, 2011. [9] I. M. Thompson, D. K. Pauler, P. J. Goodman et al., “Prevalence of Prostate Cancer among Men with a Prostate-Specific Antigen Level ≤4.0 ng per Milliliter,” New England Journal of Medicine, vol. 350, no. 22, pp. 2239-2246, 2004. [10] G. Draisma, R. Boer, S. J. Otto et al., “Lead Times and Overdetection Due to Prostate-Specific Antigen Screening: Estimates From the European Randomized Study of Screening for Prostate Cancer,” Journal of the National Cancer Institute, vol. 95, no. 12, pp. 868-878, June 18, 2003, 2003. [11] M. K. Brawer, M. P. Chetner, J. Beatie et al., “Screening for prostatic carcinoma with prostate specific antigen,” J Urol, vol. 147, no. 3 Pt 2, pp. 841-5, Mar, 1992. [12] M. L. Essink-Bot, H. J. de Koning, H. G. Nijs et al., “Short-term effects of population-based screening for prostate cancer on health-related quality of life,” J Natl Cancer Inst, vol. 90, no. 12, pp. 925-31, Jun 17, 1998. [13] F. J. Fowler, Jr., M. J. Barry, B. Walker-Corkery et al., “The impact of a suspicious prostate biopsy on patients' psychological, socio-behavioral, and medical care outcomes,” J Gen Intern Med, vol. 21, no. 7, pp. 715-21, Jul, 2006. [14] L. Esserman, Y. Shieh, and I. Thompson, “Rethinking screening for breast cancer and prostate cancer,” JAMA, vol. 302, no. 15, pp. 1685-92, Oct 21, 2009. [15] H. B. Carter, and W. B. Isaacs, “Improved Biomarkers for Prostate Cancer: A Definite Need,” Journal of the National Cancer Institute, vol. 96, no. 11, pp. 813- 815, June 2, 2004, 2004. [16] R. Chou, J. M. Croswell, T. Dana et al., “Screening for prostate cancer: a review of the evidence for the U.S. Preventive Services Task Force,” Ann Intern Med, vol. 155, no. 11, pp. 762-71, Dec 6, 2011. [17] V. A. Moyer, “Screening for Prostate Cancer: U.S. Preventive Services Task Force Recommendation Statement,” Annals of Internal Medicine, vol. 157, no. 2, pp. 120-134, 2012.
104
[18] USPSTF. "Screening for Prostate Cancer - Current Recommendation," http://www.uspreventiveservicestaskforce.org/prostatecancerscreening.htm. [19] Bupa. "Transrectal ultrasound-guided prostate biopsy," http://www.bupa.co.uk/individuals/health-information/directory/t/transrectal- prostate-biopsy. [20] C. National Guideline. "Transrectal ultrasound guided biopsy of the prostate," http://www.guideline.gov/content.aspx?id=33570. [21] L. V. Rodriguez, and M. K. Terris, “RISKS AND COMPLICATIONS OF TRANSRECTAL ULTRASOUND GUIDED PROSTATE NEEDLE BIOPSY: A PROSPECTIVE STUDY AND REVIEW OF THE LITERATURE,” The Journal of urology, vol. 160, no. 6, Part 1, pp. 2115-2120, 1998. [22] B. M. Carswell, B. A. Woda, X. Wang et al., “Detection of prostate cancer by alpha-methylacyl CoA racemase (P504S) in needle biopsy specimens previously reported as negative for malignancy,” Histopathology, vol. 48, no. 6, pp. 668-73, May, 2006. [23] M. R. Cupp, D. G. Bostwick, R. P. Myers et al., “The volume of prostate cancer in the biopsy specimen cannot reliably predict the quantity of cancer in the radical prostatectomy specimen on an individual basis,” J Urol, vol. 153, no. 5, pp. 1543- 8, May, 1995. [24] Z. Jiang, C. L. Wu, B. A. Woda et al., “P504S/alpha-methylacyl-CoA racemase: a useful marker for diagnosis of small foci of prostatic carcinoma on needle biopsy,” Am J Surg Pathol, vol. 26, no. 9, pp. 1169-74, Sep, 2002. [25] M. C. Staff. "Prostate Cancer - Treatments and drugs," http://www.mayoclinic.com/health/prostate- cancer/DS00043/DSECTION=treatments-and-drugs. [26] A. S. Ptolemy, and N. Rifai, “What is a biomarker? Research investments and lack of clinical integration necessitate a review of biomarker terminology and validation schema,” Scandinavian Journal of Clinical & Laboratory Investigation, vol. 70, no. 242, pp. 6-14. [27] "Chromogranin A," http://en.wikipedia.org/wiki/Chromogranin_A. [28] M. S. Cookson, V. E. Reuter, I. Linkov et al., “Glutathione S-transferase PI (GST-pi) class expression by immunohistochemistry in benign and malignant prostate tissue,” J Urol, vol. 157, no. 2, pp. 673-6, Feb, 1997. [29] C. O. Madu, and Y. Lu, “Novel diagnostic biomarkers for prostate cancer,” J Cancer, vol. 1, pp. 150-77. [30] H. Zehentner Bk Fau - Secrist, X. Secrist H Fau - Zhang, D. C. Zhang X Fau - Hayes et al., “Detection of alpha-methylacyl-coenzyme-A racemase transcripts in blood and urine samples of prostate cancer patients,” Molecular Diagnosis and Therapy, vol. 10, no. 6, pp. 397-403, 2006. [31] M. Zhou, A. M. Chinnaiyan, C. G. Kleer et al., “Alpha-Methylacyl-CoA Racemase: A Novel Tumor Marker Over-expressed in Several Human Cancers and Their Precursor Lesions,” The American Journal of Surgical Pathology, vol. 26, no. 7, pp. 926-931, 2002. [32] Z. M. Liu, Z. H. Li, and Z. P. Li, “Comparision of sensitivity on α methylacy CoA racemase, NMP in early diagnosis of prostate cancer,” Chinese Journal of Current Clinical Medicine, vol. 7, no. 2, pp. 97-102, 2009.
105
[33] R. Craig G, Y. A. N. Gai, Z. H. A. Shan et al., “PROSTATE CANCER DETECTION ON URINALYSIS FOR Œ± METHYLACYL COENZYME A RACEMASE PROTEIN,” The Journal of urology, vol. 172, no. 4, pp. 1501-1503, 2004. [34] S. Zha, S. Ferdinandusse, S. Denis et al., “Alpha-methylacyl-CoA racemase as an androgen-independent growth modifier in prostate cancer,” Cancer Res, vol. 63, no. 21, pp. 7365-76, Nov 1, 2003. [35] B. A. Wilson, H. Wang, B. A. Nacev et al., “High-throughput screen identifies novel inhibitors of cancer biomarker alpha-methylacyl coenzyme A racemase (AMACR/P504S),” Mol Cancer Ther, vol. 10, no. 5, pp. 825-38, May, 2011. [36] C. Kumar-Sinha, R. B. Shah, B. Laxman et al., “Elevated alpha-methylacyl-CoA racemase enzymatic activity in prostate cancer,” Am J Pathol, vol. 164, no. 3, pp. 787-93, Mar, 2004. [37] D. Maraldo, F. U. Garcia, and R. Mutharasan, “Method for quantification of a prostate cancer biomarker in urine without sample preparation,” Anal Chem, vol. 79, no. 20, pp. 7683-90, Oct 15, 2007. [38] S. Ferdinandusse, S. Denis, L. IJlst et al., “Subcellular localization and physiological role of α-methylacyl-CoA racemase,” Journal of Lipid Research, vol. 41, no. 11, pp. 1890-1896, November 1, 2000, 2000. [39] M. D. Lloyd, D. J. Darley, A. S. Wierzbicki et al., “α-Methylacyl-CoA racemase – an ‘obscure’ metabolic enzyme takes centre stage,” FEBS Journal, vol. 275, no. 6, pp. 1089-1102, 2008. [40] M. A. K. Westin, M. C. Hunt, and S. E. H. Alexson, “Peroxisomes Contain a Specific Phytanoyl-CoA/Pristanoyl-CoA Thioesterase Acting as a Novel Auxiliary Enzyme in α- and β-Oxidation of Methyl-branched Fatty Acids in Mouse,” Journal of Biological Chemistry, vol. 282, no. 37, pp. 26707-26716, September 14, 2007, 2007. [41] Wikipedia, “Enzyme,” 2013. [42] S. J. Steinberg. "Peroxisome Biogenesis Disorders, Zellweger Syndrome Spectrum," http://www.ncbi.nlm.nih.gov/books/NBK1448/. [43] S. J. Steinberg, G. Dodt, G. V. Raymond et al., “Peroxisome biogenesis disorders,” Biochimica et Biophysica Acta (BBA) - Molecular Cell Research, vol. 1763, no. 12, pp. 1733-1748, 2006. [44] Wikipedia. "Alpha-methylacyl-CoA racemase," http://en.wikipedia.org/wiki/Alpha-methylacyl-CoA_racemase#cite_note- pmid11861706-9. [45] Wikipedia, “Peroxisomal disorder,” 2012. [46] A. W. M. Zomer, B. van der Burg, G. A. Jansen et al., “Pristanic acid and phytanic acid: naturally occurring ligands for the nuclear receptor peroxisome proliferator-activated receptor Œ±,” Journal of Lipid Research, vol. 41, no. 11, pp. 1801-1807, November 1, 2000, 2000. [47] M. Stacewicz-Sapuntzakis, G. Borthakur, J. L. Burns et al., “Correlations of dietary patterns with prostate health,” Mol Nutr Food Res, vol. 52, no. 1, pp. 114- 30, Jan, 2008.
106
[48] M. E. Wright, P. Bowen, J. Virtamo et al., “Estimated phytanic acid intake and prostate cancer risk: a prospective cohort study,” Int J Cancer, vol. 131, no. 6, pp. 1396-406, Sep 15. [49] J. Xu, T. Thornburg, A. R. Turner et al., “Serum levels of phytanic acid are associated with prostate cancer risk,” Prostate, vol. 63, no. 3, pp. 209-14, May 15, 2005. [50] N. M. Verhoeven, and C. Jakobs, “Human metabolism of phytanic acid and pristanic acid,” Prog Lipid Res, vol. 40, no. 6, pp. 453-66, Nov, 2001. [51] L. E. Fish, R. Deshaies, and A. T. Jagendorf, “A Mg2+ requirement for rapid ATP-driven protein synthesis by intact pea chloroplasts,” Plant Science Letters, vol. 31, no. 2‚Äì3, pp. 139-146, 1983. [52] Wikipedia. "Magnesium in biology," http://en.wikipedia.org/wiki/Magnesium_in_biology#cite_note- cancerweb.ncl.ac.uk-4. [53] V. JC, M. P, M. GP et al., “- Evidence for the existence of a pristanoyl-CoA oxidase gene in man,” Biochem J, vol. 325, no. Pt 3, pp. 593-9, 1997. [54] "ACOX3 Reaction," http://brie8.cshl.org/cgi- bin/eventbrowser?DB=gk_central&FOCUS_SPECIES=Homo%20sapiens&ID=3 89891&. [55] Wikipedia. "Sensor," http://en.wikipedia.org/wiki/Sensor. [56] "Sensor," Merriam-Webster. [57] B. Bartling, “Development of a Thick-Film Printed Ir/C Biosensor for the Detection of Liver Disease Related Biomarkers,” Chemical Engineering, Case Western Reserve University, Cleveland, January 2010. [58] A. R. B. Huilong Fei. "Ion Selective Electrode," http://cnx.org/content/m43567/latest/. [59] J. Koryta, “ION-Selective Electrodes,” Annual Review of Materials Science, vol. 16, pp. 13-27, 1986. [60] C. J. McNeil, D. Athey, M. Ball et al., “Electrochemical Sensors Based on Impedance Measurement of Enzyme-Catalyzed Polymer Dissolution: Theory and Applications,” Analytical Chemistry, vol. 67, no. 21, pp. 3928-3935, 1995. [61] C.-C. Liu, The Biomedical Engineering Handbook: Second Edition: CRC Press LLC, 2000. [62] H. Elzanowska, E. Abu-Irhayem, B. Skrzynecka et al., “Hydrogen Peroxide Detection at Electrochemically and Sol-Gel Derived Ir Oxide Films,” Electroanalysis, vol. 16, no. 6, pp. 478-490, 2004. [63] J. Shen, L. Dudik, and C.-C. Liu, “An iridium nanoparticles dispersed carbon based thick film electrochemical biosensor and its application for a single use, disposable glucose biosensor,” Sensors and Actuators B: Chemical, vol. 125, no. 1, pp. 106-113, 2007. [64] A. Chaubey, and B. D. Malhotra, “Mediated biosensors,” Biosensors and Bioelectronics, vol. 17, no. 6–7, pp. 441-456, 2002. [65] S. Dong, B. Wang, and B. Liu, “Amperometric glucose sensor with ferrocene as an electron transfer mediator,” Biosensors and Bioelectronics, vol. 7, no. 3, pp. 215-222, 1992.
107
[66] M. E. Ghica, and C. M. A. Brett, “Development of a Carbon Film Electrode FerroceneMediated Glucose Biosensor,” Analytical Letters, vol. 38, no. 6, pp. 907-920, 2012/09/12, 2005. [67] P.-C. Nien, T.-S. Tung, and K.-C. Ho, “Amperometric Glucose Biosensor Based on Entrapment of Glucose Oxidase in a Poly(3,4-ethylenedioxythiophene) Film,” Electroanalysis, vol. 18, no. 13-14, pp. 1408-1415, 2006. [68] C. Deng, M. Li, Q. Xie et al., “New glucose biosensor based on a poly(o- phenylendiamine)/glucose oxidase-glutaraldehyde/Prussian blue/Au electrode with QCM monitoring of various electrode-surface modifications,” Analytica Chimica Acta, vol. 557, no. 1–2, pp. 85-94, 2006. [69] W. J. Sung, K. Na, and Y. H. Bae, “Biocompatibility and interference eliminating property of pullulan acetate/polyethylene glycol/heparin membrane for the outer layer of an amperometric glucose sensor,” Sensors and Actuators B: Chemical, vol. 99, no. 2–3, pp. 393-398, 2004. [70] J.-J. Xu, Z.-H. Yu, and H.-Y. Chen, “Glucose biosensors prepared by electropolymerization of p-chlorophenylamine with and without Nafion,” Analytica Chimica Acta, vol. 463, no. 2, pp. 239-247, 2002. [71] M. Yang, Y. Yang, Y. Yang et al., “Microbiosensor for acetylcholine and choline based on electropolymerization/sol–gel derived composite membrane,” Analytica Chimica Acta, vol. 530, no. 2, pp. 205-211, 2005. [72] C.-J. Yuan, C.-L. Hsu, S.-C. Wang et al., “Eliminating the Interference of Ascorbic Acid and Uric Acid to the Amperometric Glucose Biosensor by Cation Exchangers Membrane and Size Exclusion Membrane,” Electroanalysis, vol. 17, no. 24, pp. 2239-2245, 2005. [73] M. Yuqing, C. Jianrong, and H. Yong, “Electrodeposited nonconducting polytyramine for the development of glucose biosensors,” Analytical Biochemistry, vol. 339, no. 1, pp. 41-45, 2005. [74] K. Derwinska, K. Miecznikowski, R. Koncki et al., “Application of Prussian Blue Based Composite Film with Functionalized Organic Polymer to Construction of Enzymatic Glucose Biosensor,” Electroanalysis, vol. 15, no. 23-24, pp. 1843- 1849, 2003. [75] M. Ferreira, P. A. Fiorito, O. N. Oliveira, Jr. et al., “Enzyme-mediated amperometric biosensors prepared with the Layer-by-Layer (LbL) adsorption technique,” Biosens Bioelectron, vol. 19, no. 12, pp. 1611-5, Jul 15, 2004. [76] A. A. Karyakin, O. V. Gitelmacher, and E. E. Karyakina, “Prussian Blue-Based First-Generation Biosensor. A Sensitive Amperometric Electrode for Glucose,” Analytical Chemistry, vol. 67, no. 14, pp. 2419-2423, 2012/09/13, 1995. [77] T. Li, Z. Yao, and L. Ding, “Development of an amperometric biosensor based on glucose oxidase immobilized through silica sol–gel film onto Prussian Blue modified electrode,” Sensors and Actuators B: Chemical, vol. 101, no. 1–2, pp. 155-160, 2004. [78] W. Zhao, J.-J. Xu, C.-G. Shi et al., “Multilayer Membranes via Layer-by-Layer Deposition of Organic Polymer Protected Prussian Blue Nanoparticles and Glucose Oxidase for Glucose Biosensing,” Langmuir, vol. 21, no. 21, pp. 9630- 9634, 2012/09/13, 2005.
108
[79] L. Ming, X. Xi, and J. Liu, “Electrochemically platinized carbon paste enzyme electrodes: a new design of amperometric glucose biosensors,” Biotechnol Lett, vol. 28, no. 17, pp. 1341-5, Sep, 2006. [80] J. Wang, J. Liu, L. Chen et al., “Highly Selective Membrane-Free, Mediator-Free Glucose Biosensor,” Analytical Chemistry, vol. 66, no. 21, pp. 3600-3603, 2012/09/13, 1994. [81] Z. Zhang, H. Liu, and J. Deng, “A Glucose Biosensor Based on Immobilization of Glucose Oxidase in Electropolymerized o-Aminophenol Film on Platinized Glassy Carbon Electrode,” Analytical Chemistry, vol. 68, no. 9, pp. 1632-1638, 2012/09/13, 1996. [82] J. Wang, G. Rivas, and M. Chicharro, “Iridium-dispersed carbon paste enzyme electrodes,” Electroanalysis, vol. 8, no. 5, pp. 434-437, 1996. [83] J.-S. Luo Yc Fau - Do, C.-C. Do Js Fau - Liu, and C. C. Liu, “An amperometric uric acid biosensor based on modified Ir-C electrode,” Biosensors and Bioelectronics, vol. 22, no. 0956-5663 (Print), pp. 482-488, 2006. [84] J. S. Michael Quirk, Semiconductor Manfacturing Technology, p.^pp. 314-320: Pearson Prentice-Hall, 2001. [85] Wikipedia. "Physical vapor deposition," http://en.wikipedia.org/wiki/Physical_vapor_deposition. [86] C. A. Galán-Vidal, J. Muñoz, C. Domínguez et al., “Chemical sensors, biosensors and thick-film technology,” TrAC Trends in Analytical Chemistry, vol. 14, no. 5, pp. 225-231, 1995. [87] C. Z. Jun Xu, Chun Fu, “Novel methodfor printing high-quality metal wires,” SPIE Newsroom, 2007. [88] J. Tyson. "How Inkjet Printers Work," http://computer.howstuffworks.com/inkjet- printer3.htm. [89] C. Yu. "What is iezo printing technology?," http://www.247inktoner.com/blog/post/2012/03/25/What-is-Piezo-printing- technology.aspx. [90] Wikipedia. "Silver chloride electrode," http://en.wikipedia.org/wiki/Silver_chloride_electrode. [91] L. Fang, W. Li, Y. Zhou et al., “A single-use, disposable iridium-modified electrochemical biosensor for fructosyl valine for the glycoslated hemoglobin detection,” Sensors and Actuators B: Chemical, vol. 137, no. 1, pp. 235-238, 2009. [92] DuPont. "DuPont Teijin Films," http://www.dupontteijinfilms.com/FilmEnterprise/Datasheet.asp?Result=Print&I D=50&Version=US. [93] W. Schmitz, R. Fingerhut, and E. Conzelmann, “Purification and properties of an alpha-methylacyl-CoA racemase from rat liver,” European Journal of Biochemistry, vol. 222, no. 2, pp. 313-323, 1994. [94] P.-Y. Lin, K.-L. Cheng, J. D. McGuffin-Cawley et al., “Detection of Alpha- Methylacyl-CoA Racemase (AMACR), a Biomarker of Prostate Cancer, in Patient Blood Samples Using a Nanoparticle Electrochemical Biosensor,” Biosensors, vol. 2, no. 4, pp. 377-387, 2012. [95] "Prostate cancer," http://www.ncbi.nlm.nih.gov/pubmedhealth/PMH0001418/.
109
[96] P. H. Lange, and C. Adamec. "Making the Grade with the Gleason Score," http://www.dummies.com/how-to/content/making-the-grade-with-the-gleason- score.html. [97] Wikipedia. "Gleason Grading System," http://en.wikipedia.org/wiki/Gleason_Grading_System. [98] "AMACR Recombinant Protein (P01)," http://www.abnova.com/products/products_detail.asp?Catalog_id=H00023600- P01. [99] L. J. Thenard, Obervations sur des nouvelles combinasions entre l'oxigene et divers acides, p.^pp. 306-312, 1818. [100] L. Calmers, Domestric and Industrial Chemical Specialties, p.^pp. 67-69: Leonard Hill, 1966. [101] E. A. Khudais, “The Electrochemical Oxidtion Of Hydrogen Peroxide On Platinum Electrodes AT Phosphate Buffer Solutions,” Chemistry, MAssey University, 1999. [102] Wikipedia. "Hydrogen Peroxide," http://en.wikipedia.org/wiki/Hydrogen_peroxide#cite_note-6. [103] C.-M. JM, B.-B. G, and F. JL, “- Hydrogen peroxide synthesis: an outlook beyond the anthraquinone process,” Angew Chem Int Ed Engl, vol. 45, no. 42, pp. 6962- 84, 2006. [104] Chemsystems. "Hydrogen Peroxide," http://www.chemsystems.com/about/cs/news/items/PERP%200708_3_Hydrogen %20Peroxide.cfm. [105] L. C. Clark, and C. Lyons, “ELECTRODE SYSTEMS FOR CONTINUOUS MONITORING IN CARDIOVASCULAR SURGERY,” Annals of the New York Academy of Sciences, vol. 102, no. 1, pp. 29-45, 1962. [106] Wikipedia. "Diabetes mellitus," http://en.wikipedia.org/wiki/Diabetes_mellitus. [107] W. J, “- Electrochemical glucose biosensors,” Chem Rev, vol. 108, no. 2, pp. 814- 25, 2008. [108] N. JD, and T. AP, “- Home blood glucose biosensors: a commercial perspective,” Biosens Bioelectron, vol. 20, no. 12, pp. 2435-53, 2005. [109] K. N, G. Y, and F. M, “- Simultaneous determination of glucose and 1- deoxyglucose in serum by,” J Chromatogr, vol. 620, no. 1, pp. 9-13, 1993. [110] R. Z, and K. R, “- Analytical properties and sensor size effects of a micrometer- sized optical fiber,” Anal Chem, vol. 68, no. 8, pp. 1408-13, 1996. [111] M. M. F. Choi, “Progress in Enzyme-Based Biosensors Using Optical Transducers,” Microchimica Acta, vol. 148, no. 3-4, pp. 107-132, 2004/12/01, 2004. [112] S. MJ, Y. DH, M. NK et al., “- Electrochemical biosensor array for liver diagnosis using silanization technique,” J Biosci Bioeng, vol. 103, no. 1, pp. 32-7, 2007. [113] R.-a. Doong, P.-S. Lee, and K. Anitha, “Simultaneous determination of biomarkers for Alzheimer's disease using sol–gel-derived optical array biosensor,” Biosensors and Bioelectronics, vol. 25, no. 11, pp. 2464-2469, 2010. [114] R. Petrucci, General Chemitry: Principles and MOdern Applications 9ed., p.^pp. 606: Prentice Hall, 2007.
110
[115] S. B. Hall, E. A. Khudaish, and A. L. Hart, “Electrochemical oxidation of hydrogen peroxide at platinum electrodes. Part V: inhibition by chloride,” Electrochimica Acta, vol. 45, no. 21, pp. 3573-3579, 2000. [116] J. C. Amphlett, “The effect of carbon monoxide contamination on anode efficiency in PEM fuel cells,” pp. 1477-1482. [117] Y. Zhang, “Improvement of Amerometric Biosensor Performance for H2O2 Detection based on Bimetalic PtM (M = Ru, Au, and Ir) Nanoparticles,” International Journal of Electrochemistry, vol. 2012, pp. 8, 2012. [118] J. Zhang, PEM Fuel Cell Electrocatalysts and Catalyst Layers: Fundamentals an Applications, p.^pp. 448: Springer, 2008. [119] M. E. Tess, P. L. Hill, K. E. Torraca et al., “Bimetallic Pt/Ru Complexes as Catalysts for the Electrooxidation of Methanol,” Inorganic Chemistry, vol. 39, no. 17, pp. 3942-3944, 2000/08/01, 2000. [120] C. Roth, A. J. Papworth, I. Hussain et al., “A Pt/Ru nanoparticulate system to study the bifunctional mechanism of electrocatalysis,” Journal of Electroanalytical Chemistry, vol. 581, no. 1, pp. 79-85, 2005. [121] D. Z. Yonglang Guo, Huiyong Liu, A. Friedrich and J. Garche, “Investigations of Bifunctional Mechanism in Methanol Oxidation on Carbon-Supported Pt and Pt- Ru Catalysts,” Journal of New Materials for Electrochemical Systems vol. 9, no. 1, pp. 33-39, 2006. [122] J. Kua, and W. A. Goddard, “Oxidation of Methanol on 2nd and 3rd Row Group VIII Transition Metals (Pt, Ir, Os, Pd, Rh, and Ru): Application to Direct Methanol Fuel Cells,” Journal of the American Chemical Society, vol. 121, no. 47, pp. 10928-10941, 1999. [123] T. Bligaard, J. K. Nørskov, S. Dahl et al., “The Brønsted–Evans–Polanyi relation and the volcano curve in heterogeneous catalysis,” Journal of Catalysis, vol. 224, no. 1, pp. 206-217, 2004. [124] J. Greeley, J. Rossmeisl, A. Hellmann et al., “Theoretical Trends in Particle Size Effects for the Oxygen Reduction Reaction,” Zeitschrift für Physikalische Chemie, vol. 221, no. 9-10, pp. 1209-1220, 2007/10/01, 2007. [125] M. Lischka, C. Mosch, and A. Groß, “Tuning catalytic properties of bimetallic surfaces: Oxygen adsorption on pseudomorphic Pt/Ru overlayers,” Electrochimica Acta, vol. 52, no. 6, pp. 2219-2228, 2007. [126] Q. Ge, S. Desai, M. Neurock et al., “CO Adsorption on Pt−Ru Surface Alloys and on the Surface of Pt−Ru Bulk Alloy,” The Journal of Physical Chemistry B, vol. 105, no. 39, pp. 9533-9536, 2001/10/01, 2001. [127] J. K. Nørskov, J. Rossmeisl, A. Logadottir et al., “Origin of the Overpotential for Oxygen Reduction at a Fuel-Cell Cathode,” The Journal of Physical Chemistry B, vol. 108, no. 46, pp. 17886-17892, 2004/11/01, 2004. [128] G. Rothenberg, "Introduction," Catalysis, pp. 1-38: Wiley-VCH Verlag GmbH & Co. KGaA, 2008. [129] S. Y, K. Y, Y. S et al., “- Preparation and characterization of aqueous colloids of Pt-Ru nanoparticles,” J Colloid Interface Sci, vol. 292, no. 1, pp. 122-6, 2005. [130] L. R. F. Allen J. Bard, Electrochemical Methods: Fundamenals and Applications, 2 ed.: Wiley, 2000.
111
[131] J. Nikolic, E. Expósito, J. Iniesta et al., “Theoretical Concepts and Applications of a Rotating Disk Electrode,” Journal of Chemical Education, vol. 77, no. 9, pp. 1191, 2000/09/01, 2000. [132] Z. Galus, C. Olson, H. Y. Lee et al., “Rotating Disk Electrodes,” Analytical Chemistry, vol. 34, no. 1, pp. 164-166, 1962/01/01, 1962.
112