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An assessment of the baseline variability in the level of DNA damage in women as measured by the single… Ell, Karalynn Elizabeth 1996

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AN ASSESSMENT OF THE BASELINE VARIABILITY IN THE LEVEL OF DNA DAMAGE IN WOMEN AS MEASURED BY THE SINGLE CELL GEL ELECTROPHORESIS ASSAY by KARALYNN ELIZABETH ELL B.Sc, The University of Alberta, 1992 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE STUDIES (Occupational Hygiene Programme) We accept this thesis as conforming to the required standard  THE UNIVERSITY OF BRITISH COLUMBIA April 1996 © Karalynn Elizabeth Ell, 1996  In presenting this thesis in partial fulfilment of the requirements for an advanced degree at the University of British Columbia, I agree that the Library shall make it freely available for reference and study. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by the head of my department  or by his  or her representatives.  It is  understood  that  copying or  publication of this thesis for financial gain shall not be allowed without my written permission.  Department of  GroxUa4e, S-WllfrS  The University of British Columbia Vancouver, Canada Date  DE-6 (2/88)  0 l / 3 Q / %  Abstract  It is thought that a correlation between levels of DNA damage expressed in an individual and the potential for the future development biomonitoring for such damage could eventually before the onset of disease.  of cancer exists, and that  be used to detect individuals at risk  The purpose of studies such as that described in this  thesis is to develop and refine methods of biomonitoring for genetic damage. The objective of this thesis was to assess the background levels of DNA damage in women using the Single Cell. Gel Electrophoresis (SCGE) assay and interpret the meaning of the observed variability with respect to future study design and the sample size  necessary to ensure statistical  Thirteen female  significance.  subjects were recruited from the Vancouver Hospital-UBC site  and the Occupational Hygiene programme at the University of British Columbia. Each subject was to provide six blood samples over a period of ten weeks, at varying or irregular intervals.  A total of 73 blood samples were obtained.  Peripheral blood  lymphocytes were isolated from the samples, embedded in agarose, lysed to release the nuclear contents, and exposed to an electric current in order to allow the DNA to migrate from the nucleus. enables the detection DNA,  This procedure, known as the SCGE or "Comet" assay,  of single strand breaks and alkali-labile sites in the cellular  as smaller fragments created by breakage will travel farther from the nucleus  of the cell than larger fragments  or unbroken DNA.  Both technical and biological variability were observed in the sample data. calculation of the coefficient  of variation for several groups of data provided a crude  estimate of variation for this study.  The components of overall or total variability  could not be determined, but both the inter- and intra- individual variability appeared to  exceed the  A  replicate-to-replicate  technical  variability.  The internal  standard used in this study did not provide the information desired with respect to day-to-day  variability.  It was concluded that the observed variation within individual subjects in the study necessitates the use of a longitudinal or multiple-samples-over-time study design, rather than cross sectional.  The sample size necessary for statistical  significance in a cross-sectional study comparing two groups with an alpha of 0.05 and a power of 0.80 is approximately 70 individuals per group if the detection of an increase of fifteen  percent in image length is desired, and approximately 20  individuals per group if an increase of thirty percent in image length is to be detected.  iv  Table  of  Contents  Abstract  ii  Table of Contents  iv  List of figures  viii  List of tables  ix  Abbreviations  ix  I.  1  Introduction and background 1.1  Introduction  1  1.2  Rationale  for biomonitoring  4  The link between biomarkers of genetic damage and cancer  4  1.2.1 1.2.2 1.3.  5  Issues in biomonitoring 1.3.1  1.4  Different types of biomarkers  6  Lymphocytes - the physiology of sampling and monitoring  and kinetics  6  1.3.2  Variability of response  8  1.3.3  Sources of variability and methods of minimization  9  1.3.3.1  Biological  9  1.3.3.2  Technical  10  Measuring. Genotoxicity 1.4.1  11  Lymphocyte  Assays  1.4.1.1  Sister Chromatid Exchange (SCE)  11  1.4.1.2  Chromosome Aberrations (CA)  12  1.4.1.3  Micronucleus (MN)  12  1.4.1.4  Single strand breakage assays (ssb) 1.4.1.4.1  1.4.2  11  Single Cell Gel Electrophoresis (SCGE or "Comet") assay  Comparison of lymphocyte assays: of the Comet assay  advantages  12 13  14  1.5  History of the determination of background levels from genotoxicity assays  II.  Objective and specific  III.  Materials and Methods  19  III. 1  Contacting and recruitment of subjects  19  111.2  Development  20  111.3  Blood sample collection  21  111.4  Lymphocyte  21  III.4.1  18  and administration of the questionnaire  isolation Counting of cells in a solution  22  111.5  Control cells - culturing and usage of a MOLT-4 cell line  23  111.6  Procedure for the SCGE Assay  24  111.6.1 111.6.2  111.7 IV.  aims  15  Preparation of slides Cell lysis  24 25  111.6.3  DNA unwinding and electrophoresis  25  111.6.4  Neutralization  26  111.6.5  Alcohol fixing  26  111.6.6  Staining of slides  26  111.6.7  Scoring of slides  26  Enumeration and analysis of data  Results  28 30  IV. 1  Recruitment of subjects  30  IV.2  Blood Sampling  31  IV.3  Photographic  IV.4  Questionnaires  34  IV.5  Data Analysis  35  IV.5.1 IV.5.2  examples of the  images observed  Presentation of results Comparison of means when fifty versus one hundred cells are scored  31  35 36  vi  IV.5.3  Investigating the relationship between assay results and the date of sample.  36  IV.5.4  Use of different metrics for analysis  47  IV.5.5  Assessment of the effectiveness of MOLT-4 cells as -an internal standard  IV.5.6  Assessment of the technical, inter- and intraindividual variability  58  IV.5.7  Comparison of the blood sample and questionnaire data.  61  IV. 5.8 IV. 6 V.  VI  54  Normality testing of the data  Sample size calculation  Discussion  66 66 67  V. l  Recruitment  67  V.2  Development of the experimental protocol for the comet assay  68  V.3  Future changes  70  V.4  Correlation between date of sample and mean image length  70  V.5  Analysis of the technical variability  71  V.6  Assessment  73  V.7  Comparison of the different test metrics  74  V.8  What do the results say about study design?  75  V.9  Future considerations for the use of the comet assay in field studies  75  Conclusions  to the experimental protocol  of the inter- and intra-individual variability  V. 9.1  Development of the Comet assay protocol  75  V.9.2  Use of the MOLT-4 cell line as an internal standard  77  V.9.3  Development and assessment of the questionnaire  78  V.9.4  Recruitment of subjects  79  V.9.5  Statistical analysis of the data obtained  79  V.9.6  Summary  79 81  vii VII  References  VIII  Appendices  83  A - Information sheet and letter of introduction provided to the nursing units for the purpose of recruitment  88  B - Letter of consent to participate in this study  91  C - Questionnaire  94  D - Results of Blood sampling  107  E  109  - Questionnaire results  F - Raw data  113  G - The t-test results for each 50 cell sample  129  viii  List  Figure  1  Figure  2: a.) b.)  Figure  3: P h o t o g r a p h i c  Figure  4  Figure  5: a.)  of  Figures  C o n c e p t u a l basis for the development molecular epidemiology  c. )  in  5  D i a g r a m m a t i c representation of the s c o r i n g p r o t o c o l , and 2 9 D i a g r a m m a t i c representation o f the g r a t i c u l e  a.-m.)  b. )  o f b i o m a r k e r s for use  examples  of  the  images  observed  Statistical analysis and histogram measurements, for a l l subjects  T h e relationship and the date o f the relationship day is removed, the relationship also removed.  for  image  32-33  length  37-43  between the mean image length i n p m sample, after the samples from the first s a m p l i n g after  the  following  G r a p h i c a l representation o f the sample, grouped by subject.  two  s a m p l i n g days  six test metrics  44-46  are  Figure  6-11:  for each  Figure  12:  C o m p a r i s o n of a.) mean blood sample image length with the mean image length o f the c o r r e s p o n d i n g M O L T - 4 slide and b.) c o m p a r i s o n with large M O L T - 4 cells e x c l u d e d .  Figure  13:  S a m p l e plots o f questionnaire responses versus b l o o d sample a. ) age o f subject versus mean image length, b. ) v i t a m i n C intake versus mean image length, and c. ) s m o k i n g status versus mean image length  48-53  55-56  data  63-65  ix  List Table 1: Table 2: Table 3:  of  Tables  Examples of the determination of background variability in genotoxicity assays Coefficient of variation and ANOVA calculations used to assess the stability of the MOLT-4 cell line Coefficient of variation for a.) replicate blood sample slides, b.) between subjects, within days, and c.) between subjects.  Abbreviations  ANOVA-  analysis-of-variance  CA-  chromosome  CV-  coefficient  EDTA -  ethylenediaminetetraacetic  FBS -  fetal  HepB -  hepatitis B  HBSS -  Hank's buffered  HIV -  human  immunodeficiency  HLA -  human  leukocyte  HPRT -  hypoxanthine  MN -  micronucleus  PBL -  peripheral  SCE -  sister  chromatid  SCGE-  single  cell  UBC-  University of British Columbia  aberrations of variation acid  bovine serum  saline  gel  virus  antigen  guanine  blood  solution  phosphorybosyltransferase  lymphocytes exchange electrophoresis  15-16 57 59-60  1  /.  Introduction and Background  1.1  Introduction It is  well  known  play a potential  from  human  populations.  disease frequency  in the  exist  reasons: between  to  relationship  exposure an  with  in a significant  can  established.  chemicals  between  ambient  exposure  are derived by comparing the estimated  estimation exposure  is and  number of people  exposures.  difficult the  before  and  This  situation  considerable  biologically  relevant  for the disease of  a cause-effect  desirable to obtain data by looking directly at  individuals or groups for early biological effects.  exposure  could be minimized before  negative  health  effects.  to  to monitor and obtain  that is received, and it is necessary  In light of this, it is often exposed  ambient  develop be  it is desirable  interest  population  exposures  In order to understand and  Historically, relationships  general  internal dose of a substance interest  of cancer.  in a population of  is unfavorable for two can  and occupational  for disease development,  and disease frequency  differences  environmental  role in the development  minimize this potential data  that  In this way,  a harmful  the onset of disease in order to minimize future  2  A method of biological monitoring in humans is the use of biological markers. Biomarkers are cellular, biochemical or molecular changes that are measurable in biological media, such as body fluids and tissues, that can provide information on internal exposure,  susceptibility,  and/or biological effects such as DNA damage  (Hulka, 1990; Wilkosky, 1990). Biomonitoring has several advantages ambient exposure  measurements.  than one source of entry (i.e.  Fluctuating exposures  and exposure  from more  inhalation and dermal absorption) can be integrated  into one exposure measurement, term exposure associations  over the inference of exposure via  non-specific  hazards can be detected,  acute and long  can be made, and an increase in the knowledge of disease  mechanisms can be gained (Wilkosky, 1990; Wilkosky & Griffith, 1990).  The use of  biomarkers can also improve risk assessment by increasing the validity and decreasing bias in epidemiological genetic variability and susceptibility  studies,  and can increase  the understanding of  in an individual (Hulka, 1990; Perera & Whyatt,  1994). A common application of biological markers in epidemiology is to the study of mutagenic and carcinogenic agents. cancer development  Because of the latency period involved in  it can be difficult to establish  an exposure-disease relationship.  By providing an earlier occurring and more sensitive outcome formation,  a biomarker, assuming  than tumour  a valid relationship with future cancer  development, may overcome these problems of latency (Perera & Whyatt, 1994).  In  addition, utilization of biomarkers of genetic damage can potentially lead to an avoidance  of cancer development  exposures  before  the  by stimulating a reduction of potentially  initiation of carcinogenesis  occurs.  harmful  3  There are several types of information needed  regarding a particular  biological marker in order to determine its utility in epidemiological research, all of which are concerned with validity.  There are three broad categories  measurement, internal study, and external (Schulte & Mazzuckelli,  of validity:  1991; Vine, 1992).  Measurement validity refers to the ability of a marker to correctly reflect dose, characterize a dose-response  relationship between exposure  a predictive relationship between marker response  and disease, and exhibit  and disease  development.  Internal study validity has been defined as "the degree to which index and comparison groups are selected and compared so that, apart from sampling errors, the observed differences  between the dependent variables are attributed only to the  hypothesized effects" (Last, 1983).  In other words, internal study validity refers to  the variability of the analytical technique and other factors that can influence the marker.  and the effect of genetic, environmental,  the total variability, affecting the reliability of  The external validity refers to the applicability of the biomarker to  large numbers of people in a non-experimental setting (Hulka, 1990).  For many biomarkers, methodological  development  and exposure  assessment  are well documented, but the background variability in a "normal" population is not well quantified or understood.  The purpose of this thesis is to assess the internal  study validity or the baseline variability of a specific biomarker assay of DNA damage, the Single cell gel electrophoresis or "Comet" assay.  4  1.2  Rationale  1.2.1  The  for  link  biomonitoring  between  biomarkers  of  genetic  damage  and  cancer:  F o r a biomarker to be a useful tool, there has to be a relationship to biological must  phenomenon  measure  an  of  interest.  occurrence  which  a l l cancers  are  In  the  can  be  case  of  carcinogenesis,  causally  associated  the  with  the  biomarker  tumour  development. Essentially results  in  uncontrolled  Mclnnes, & Willard, and  tumour  can  result  growth  1991).  suppressers. in tumour  It  is k n o w n  development.  and  in chronic myelogenous 1991).  conditions anemia,  8 and  Increased  resulting  Bloom  proliferation  in  that  (Therman,  chromosomal  T w o well  1986;  defects  k n o w n examples  14 in B u r k i t t ' s l y m p h o m a and  risk  leukemia (Therman,  cell  which  Thompson,  and  i n s t a b i l i t y , such  xeroderma  such are  as  the  between  -  translocations translocation  Mclnnes,  associated  with  as  Telangectasia,  pigmentosum  ataxia  (Cleaver,  oncogenes  chromosomes  1986; T h o m p s o n ,  of m a l i g n a n c y is also  chromosome  syndrome,  in a somatic  There are at least two types o f genes i n v o l v e d  chromosomes  Willard,  result o f mutation  and  between 22  the  &  inherited Fanconi  1968; L o h m a n ,  M o r o l l i , D a r r o u d i , Natarajan, Gossen, V e n e m a , et a l . , 1992; T h o m p s o n , et a l . , 1991). well,  there  breakage  damage any  is  (Sorsa,  tendency Wilbourn,  for  known  carcinogenic  & Vainio,  1992).  It seems reasonable  to  assume,  then,  is directly related  to  cancer  agent capable  carcinogenicity by  a  much  o f causing  (Vine,  experimental  1992). evidence  This  that somatic  formation.  structural  In fact,  changes  logical  in humans,  chemicals  to  it  cause  As  chromosome  c h r o m o s o m a l and D N A it is generally  D N A has  inference, as  to  9  the  however,  is u s u a l l y  is  believed that  potential not  yet  i m p o s s i b l e to  for supported correlate  5 biomarker responses to measurement  1.2.2  was  Different  tumour incidence  that is measured.  Internal dose  Metabolites A  absorption, distribution, metabolism  Figure 1:  types of biomarkers, classified  effective dose, biological  I  Environmental genotoxic chemical  the  types of biomarkers:  disease development  Exposure  years after  made.  There are several different  biologically  occurring many  Biologically effective dose  I DNA and protein ndducts  These classifications  by the stage in  are internal dose,  response, and susceptibility  Early biological effect  Altered structurefunction  HPRT, HLA, SCEs, M N , SC.CIi  1  Mutations, deletions, translocations  cell proliferation, clonal expansion  Conceptual basis for the development epidemiology (Wogan, 1992)  1).  Clinical disease  1  1  repair, replication  (figure  Malignant tumour  further genetic change  of biomarkers for use in molecular  Internal dose biomarkers involve the measurement  of the amount of a  carcinogen or its metabolite present in cells, tissues, or body fluids (Perera & Whyatt, 1994). urine.  An example of this would be the measurement of mutagenic compounds in  6  Markers of biologically effective interacted  with critical  surrogate  target.  synthesis.  dose indicate amount  subcellular targets, usually D N A , or with  metabolism of the chemical in question  changes  an  response  markers  in cells or tissues  established  this class accounts  for differences  and repair mechanisms  measure  (Hulka,  irreversible biological  that arise from deleterious  or  interactions  sister  chromatid  micronuclei, D N A strand  exchanges,  chromosome  chemical  at the target site,  to  markers  carcinogens,  inherited mutations, The amount  measure  & Whyatt,  individual  including variability  difference  of  1994).  differences  that  in D N A repair,  can  equipment  the  influence  micronutrient  in meiabolic activity (Perera & Whyatt,  of information available regarding  availability of the necessary sensitivity  formation  specific and can be influenced by lifestyle and  environmental factors(Hulka, 1990; Perera  response  This group  breaks (including the S C G E assay), and gene mutations.  None of these markers are exposure  Susceptibility  aberrations,  in  1990).  and are thought to be a step in the pathological process toward disease. includes  has  This group includes D N A and protein adducts and unscheduled D N A  Unlike internal dose measures,  Biological  of chemical that  exposure  levels,  1994).  of interest,  and the cost of performing the  the  analysis,  the  and specificity of the biomarker desired, and the knowledge of the  relationship between  the  marker  and the  development  of disease  all influence  the  decision of which type of biomarker to use for a given experiment.  1.3.  1.3.1  Issues  in biomonitoring:  Lymphocytes - the  physiology and kinetics of sampling and monitoring:  While biomarker assays  may be performed in a variety of cell and tissue types,  the most commonly used is peripheral blood lymphocytes ( P B L ) . themselves  The lymphocytes  are not the target tissue for carcinogens, and the associated  lesions  7 detected in mature lymphocytes do not lead to cancer.  However, exposures that cause  a response in lymphocytes will probably also affect other tissues where malignancies can occur (Sorsa, et al., 1992; Wilkosky, 1990; Wilkosky & Griffith, 1990). The reason that levels of a given biomarker in lymphocytes is thought to have a relationship with the effects on target tissues is because throughout the body.  lymphocytes circulate  Blood-borne lymphocytes make up less than five percent of  the total body pool, with most found in the spleen, lymph nodes, and other lymphatic tissue  (Boggs & Winkelstein, 1983).  These cells move freely in and out of circulation,  and there is continuous movement from one tissue to another, so that a given cell is likely to have traveled through each tissue type in the body.  The average time that a  given lymphocyte of the recirculating pool spends in the peripheral blood has been estimated at 30 minutes, and the estimated overall recirculation time for the body is 12 hours (1986).  This means that lymphocytes with DNA damage that has been  induced somewhere else in the body will eventually be present in the peripheral blood. The kinetics of PBL also affects biomonitoring, as the persistence of the response to an exposure is dependent on the half life of the cells involved. three types of PBL:  T-cells, B-cells, and null cells.  There are  T-cells make up sixty to eighty  percent of circulating lymphocytes, B-cells make up five to ten percent of the lymphocyte pool, and the number of null cells in circulation is more variable (Boggs & Winkelstein, 1983).  By kinetic criteria, both B- and T-lymphocytes can be long or  short-lived, but T-cells have an average half-life of 3 years, and B-cells live an average of 1 to 10 days (MacKay, 1994; Sprent & Tough, 1994).  This suggests that  both acute and long-term or past exposures can be detected in PBL, by differentiation of the response of B- and T-lymphocytes, respectively. Some biomarker assays, such as those evaluating DNA single strand breakage, may be affected by the fact that lymphocytes can undergo programmed cell death  8 (Ashwell, 1994).  This term describes the mechanics of regulated cell death, and  apoptosis  the morphology.  describes  The most often  with apoptosis is the fragmentation of nuclear DNA.  reported experimental finding A photograph of an apoptotic  cell is shown in figure 4(d).  1.3.2  Variability  of  response:  All evidence to date suggests that there is a high degree of variability in biomarker levels among persons with similar exposures,  due to factors other than the  exposure itself (Anderson, Francis, Godbert, Jenkinson, & Butterworth, 1993; Perera & Whyatt, 1994).  Such variability is referred to as normal or baseline, occurring  throughout the general . population and in all experimental settings. understanding of this variability in a genetic endpoint will increase results  obtained form monitoring these endpoints  or occupationally exposed. allows  An confidence  in a group that is environmentally  Also, knowledge of the levels of background variation  elucidation of the appropriate study design, increasing statistical  the sensitivity  in  and specificity  of  power and  measurements.  There are two types of variability that can be observed with the use of biomarkers:  biological variability and technical variability.  Biological variability  can itself be described both in terms of between different individuals and within a given individual.  The sources of this variation are discussed in the following  section. Biomarkers in any classification variability.  For instance,  exposure  may result in misclassification identical internal doses. susceptibility  group can be affected  by biological  assessment based on ambient air measurements  because identical ambient doses may not result in  Differences  in metabolic  can also lead to misclassification  clearance, cellular repair, and  by increasing the variability between  9 individuals and therefore Vesterberg, 1985). serious exposure  1.3.3  affecting  the biologically effective  dose (Elinder &  A knowledge of the different types of variability can prevent or disease misclassification  in epidemiological  studies.  Sources of variability and methods of minimization  1.3.3.1 Biological: The nature of the endpoint measured by a given biomarker has some influence on what factors affect biological variability.  For most markers,  differences  and environment account for  in susceptibility,  genetic factors,  lifestyle,  the majority of this type of variability, particularly between different individuals. For example, cigarette smoking status, age, sex, and white blood cell count have been shown to account for 20-30% of the total observed interindividual variation in baseline SCE rates, and about 30% of the variation may be accounted for by genetic factors (Lazutka, Dedonyte, & Krapavickaite, 1994).  Exposures to Vitamin C (Green,  Lowe, Waugh, Aldridge, Cole, & Arlett, 1994), exercise (Hartmann, Plappert, Raddatz, Grunert-Fuchs, & Speit, 1994), and estrogen in the form of human reproductive hormones (Joseph-Lerner, Fejgin, Ben-Nun, Legum, & Amiel, shown to increase the variability in biomarker response. exposures  have found ambient pollution to be associated  1993)  have also been  Studies of environmental with increases  in biomarker  levels (Perera & Whyatt, 1994). Intraindividual natural  variability is influenced  variation over time,  health,  lifestyle  by a number of factors, including and environment  exposures, and other personal characteristics (Wilkosky, 1990). damage may be affected  changes,  synergistic  Levels of DNA  in a given individual by circadian rhythms, circa-annual  effects, and monthly rhythms in females (D'Souza, Thomas, & Das, 1988; Haus, Lakatua, Swoyer, & Sackett-Lundeen, 1983).  10 Any type of biological variability, with knowledge and ascertainment  of its presence in a potential  of the underlying cause  study participant, can be minimized.  This can be achieved by matching for that factor in the exposed and control groups, excluding that individual from the study, or using the subject as his/her own control. Intraindividual variability can be decreased informing the participants of factors  in longitudinal study  designs by  that should not vary throughout the course of  the study, or sampling at the same time each day, week or month.  However,  manipulation of the study population in this manner can decrease external validity, as results obtained may not be applicable to the general population.  It may be  desirable to choose a biomarker that is not as susceptible to biological variability if possible.  1.3.3.2  Technical: Sources of technical variability are both easier to define and easier to control  than biological variation. introduce  technical  Variation in each step of the experimental  variability, including sample  collection  process can  and storage,  lymphocyte  isolation and culturing, slide preparation, scoring of data, analysis of data, and day to day variation if all experiments are not performed on the same day.  This variation  can be minimized to some extent by preparing large batches of reagents and aliquoting amounts  for daily use,  gaining confidence  through practice, and building checks prevent  in the experimental  protocol  into the scoring protocol to indicate and  or correct bias.  Technical variability can also be quantified through the use of internal standards  and controls.  Internal standards  can include measurement  of  confounding  substances for biomarkers of internal dose, assessment of biomarker response to a substance exhibiting  a well  concurrent with measurement  documented  and constant  effect  (i.e.  radiation)  of response to the substance of interest,  and analysis  11 of a control cell population that is from one source or a non-deviating source along with test cells.  This cell population could be composed of a cell line that is cultured  throughout a study period or a collection of purified cells that is preserved in stasis, perhaps  by  freezing.  1.4  Measuring  1.4.1  Lymphocyte  Genotoxicity  Assays  Although there are many different  types of biomarkers available for use, the  most common method of detecting DNA damage is with lymphocyte assays such as sister chromatid exchange,  chromosome  single cell gel electrophoresis.  aberrations,  micronuclei  formation, and  These assays will be explained in the following  sections.  1.4.1.1 Sister Chromatid Exchange (SCE): During mitosis,  through mechanisms  involving DNA breakage  and rejoining  that are not well understood, sister chromatids can exchange seemingly  identical  segments of DNA, apparently without affecting cell viability or function (Wilkosky & Rynard, 1992). mutagen.  Elevated SCEs apparently indicate that cells have been exposed to a  Chemicals most likely to cause SCEs in vitro include alkylating agents, DNA  binding agents, DNA base analogs, inducers. the affected  repair interferents,  and single  strand break  Persistence of SCEs depends on rate of DNA repair and normal half life of cell.  Sister chromatid exchange appears extensively in the scientific method of measuring the effect of potentially  carcinogenic  exposures.  literature as a  1.4.1.2 Chromosome Aberrations (CA): Chromosome aberrations are defined  as gross morphological changes in  chromosome structure, detected by metaphase These changes can include chromosome  analysis (Littlefield & Goh, 1973).  breaks, dicentrics,  inversions, and separation of the sister chromatids. in patients response primarily  with congenital  rings and  Such alterations can be detected  malformations, in malignant tumour tissue, and in  to environmental and occupational exposure clastogenic  translocations,  to  certain agents with  effects.  1.4.1.3 Micronucleus (MN): Micronuclei consist of small amounts of DNA that arise in the cytoplasm when chromatid/chromosomal  fragments  or whole  chromosomes  are not incorporated into  daughter nuclei during mitosis (Vine, 1992).  Formation of micronuclei is the result  of two different  or chromosome  aneugenicity  mechanisms:  clastogenicily  or improper segregation  1992; Vine, 1992).  of chromosomes  breakage and  during mitosis  (Sorsa, et al.,  Many agents have been shown experimentally to increase the  level of micronuclei in a population of cells.  1.4.1.4  Single strand breakage assays (ssb): Single strand breakage assays measure the formation of breaks in one strand  of DNA. Examples of DNA ssb assays include(Ahnstrom, 1988):  a)  velocity  sedimentation, which takes advantage of the fact that DNA will separate by size of fragments on a sucrose gradient, b)  DNA unwinding, a process using denaturation of  DNA to isolate the more quickly separating sections containing breaks from unbroken segments, c)  filter elution, which utilizes the ability of filters to  discriminate DNA fragment sizes, d) DNA precipitation, in which DNA that is damaged  13 by strand breaking agents will not precipitate out of solution with unbroken strands, and e) microelectrophoresis of single  1.4.1.4.1  cells.  Single Cell Gel Electrophoresis (SCG'E or "Comet") assay:  A comprehensive review of the Comet assay is given by Fairbairn, Olive and O'Neill (Fairbairn, Olive, & O'Neill, 1995).  A detailed description of the assay is given  below. The comet assay is based on a simple property of DNA; nucleic acids have a negative charge.  A small number of cells are embedded in an agarose gel, lysed to  expose the contents of the nucleus, immersed in electrophoresis buffer, and subjected to an electric current which pulls the negatively charged DNA toward the positive electrode.  Smaller fragments travel farther through the gel matrix, which  allows the amount of DNA damage to be quantified if the damage causes a break in the strands of the DNA or causes unwinding from the scaffolding.  The cells are stained  with a fluorescent DNA-binding dye so that they can be visualized under a fluorescent microscope and analyzed.  The image that is seen, if there is DNA damage,  resembles a comet, with the smaller DNA fragments creating the tail. The conditions of electrophoresis greatly influence the types of damage that can be seen with this assay.  The original development of the SCGE method used a  neutral electrophoresis buffer (Ostling & Johanson, 1984), which, because it did not denature the DNA before electrophoresis, only allowed the detection of doublestranded DNA breaks.  Singh et al (Singh, McCoy, Tice, & Schneider, 1988) modified  this procedure by using a strongly alkaline electrophoresis buffer (pH 13) in order to allow the DNA to denature, thus allowing the detection of single-strand breaks and alkali-labile sites. damage because  This increases the sensitivity of the assay in detecting DNA many agents produce much greater amounts of single-stranded than  14  double-stranded damage, and the alkaline conditions also degrade RNA, a common source of artifacts (Singh, et al., 1988). Several methods of quantifying the amount of damage that is present have been used.  These methods include:  image length or tail length (Hartmann, et al.,  1994; Singh, Stephens, & Schneider, 1994), percentage of DNA in the tail (Anderson, et al., 1993), and the tail moment, or. the product of the percentage of DNA in the tail and the tail length (Olive, Banath, & Durand, 1990).  1.4.2  Comparison of lymphocyte assays -  advantages of the Comet assay:  The biomarker that is the focus of this thesis is the single cell gel electrophoresis (SCGE) or "Comet" assay.  It is advantageous to utilize the comet assay  because it is relatively quick and simple, requires a small number of cells for analysis, and can be used on both proliferating and non-proliferating cells. cytogenetic methods of assessing exchange  Other  levels of DNA damage, such as sister-chromatid  and the micronucleus assay,  are limited to proliferating cells (Hartmann,  et al., 1994), and often to circulating lymphocytes.  Other methods of detecting single  strand breaks are tedious and require a more complicated analysis and interpretation than the SCGE method.  SCGE also allows for intercellular comparisons of damage and  repair, which these other ssb assays do not.  The comet assay has been shown to be  extremely sensitive in the detection of DNA damage induced by some sources (Anderson, et al., 1993; Betti, Davini, Giannessi, Loprieno, & Barale, 1994) and may detect levels of damage caused by low concentrations of toxic substances that other assays cannot (Hartmann, et al., 1994).  It has been observed that the SCGE assay lacks  specificity for radiation-induced DNA damage (Tice & Strauss, 1995 May), but it may be feasible to identify this type of DNA damage in certain subtypes of cells.  The  comet assay can also be used to observe the repair of DNA damage, and, as individual  15  cells can be analyzed, identify sub-populations of cells based on resistance or sensitivity to permanent damage (Olive, et al., 1990).  1.5  History of determination of background levels in genotoxicitv As  mentioned earlier, the development  assays:  and utilization of genotoxicity  assays  did not always involve an assessment of background levels of the biomarker of interest.  Table 1 summarizes a selection of papers focusing on baseline variation,  representing of  an extremely  small proportion of the  total  literature concerning assays  genotoxicity.  Reference  Assay used MN  (DiGiorgio, Meo, Laget, Guiraud, Botta, & Dumenil, 1994) (Thierens, MN Vral, & Ridder, I 1991) (Lazutka, et SCE al., 1994)  (Huber, MN Braselmann, & B auchinger, 1989) (Bender, CA, Preston, SCE Leonard, Pyatt, & Gooch, 1989)  Sample size  Results  and Conclusions  122 males and 78 females  large inter-individual variability; variation factors considered were age, sex, and smoking, and only smoking could be attributed to a rise in MN frequency (25%).  5 male and 5 female  Interindividual differences in micronucleus frequencies at higher doses of radiation increase the uncertainty of dose assessment  variation factors of age, sex, and smoking were considered and accounted for 31.3% of variability measured (26.7% from smoking) Significant interindividual variability was 30 people detected for baseline levels; the max. difference between lowest and highest yields was a factor of 15. Frequency of induced micronuclei decreased with age. 493 males and Inter-sample variance was no greater between females, age samples from the same subject than that range of 1.1 to between samples from different subjects. No 83.7 effect seen with age and race for both CA and SCE; mean SCE frequency was 5% higher in fern ales „i.h£ri_majes^ ^..^^.^^^ .„ . 8 samples over Significant effects of year and season of 2 years from 24 sampling, with no pattern; no significant males and 24 effects with age or sex, although SCE frequency females. were always higher in females than males. 123 male and female  m  (Anderson, et al., 1993)  Table 1:  CA, SCE  Examples of publications focusing on the determination of background variability in genotoxicity assays  m  16  Sample size  Results  (Littlefield CA & Goh, 1973)  10 men and 23 women  Intraindividual variability was greater than interindividual variability, greater variability was seen in cultures from women than in cultures from men, and differences were seen in cultures obtained at different times of the  (Dewdney, SCE Lovell, Jenkinson, & Anderson, 1986)  73 males and 33 females; 23 males and 9 females sampled again 6 months later  Highly significant interindividual variation found, with less but still highly significant variation between replicate samples. Sex and smoking habits affected SCE frequency, with females having significantly higher than males. Most of the variation was between cells  (Tucker, SCE Christensen, Strout, McGee, & Carrano, 1987)  4 females, twice a week for 8 weeks, and 2 males and 2 females for 5 days.  Reference  Assay used  (Betti, et al., SCGE, 1994) SCE  and Conclusions  Some variation was associated with the menstrual cycle, with peaks corresponding to ovulation and the beginning and end of menstruation. Day-to-day changes in the mean S C E were no different from those expected with random sampling. In the weekly study, there were significant differences that were not attributable to chance. 49 males and 51 SCE did not reveal any significant effect of smoking, sex, or age, while SCGE DNA migration females was significantly affected by smoking (more in males than in females), and no difference was seen with age. _™.„ Women average 0.5 SCE/cell higher than men reexamination among normal healthy adults of other studies m  (Margolin & Shelby,  SCE  (Fenech, Neville, & Rinaldi, 1994)  MN  152 females and 113 males  Clear and consistent frequency of MN in in females), and a frequency in females  SCGE  (Betti, Davini, Giannessi, Loprieno, & Barale, 1995)  SCGE  Table 1:  difference was seen in the males and females (higher greater dispersion in MN over 40 was seen, which  Qy. ^L,.^ £J9:..19,1L.PXJ.!}.^.J^„£^ JB°§2!S^ ™~™ 49 males and 51 DNA migration was significantly increased by females smoking, particularly in men, and no difference was seen from age. No difference was found with S C E , suggesting a higher responsiveness of the comet assay. SCGE is more sensitive than SCE in revealing 85 males and 115 females; 60 smoking habit effects but comet induction did smokers not seem related to the amount of tar inhaled. Sampling time played a greater role in SCGE versus SCE. m  (Betti," et al., 1994)  m m  U  0  Examples of publications focusing on the determination of background variability in genotoxicity assays (cont.)  Examination although study  much  of  the  v a r i a t i o n is seen  group, it is difficult  information genotoxicity on a large  results  also  attests to  assays scale.  and  and both  conclusions within  to establish causes the  fact  is important  that to  an  from  these  individual  or reasons  and  studies  indicates  between  those  for this v a r i a b i l i t y .  that in a This  v a r i a t i o n exists  in the  response  detected  assess  manner  before  u s i n g that  in some  by ass  18  //.  Objective  and  Specific  Aims  The objective of this thesis is assess the background levels of DNA damage in women using the Single Cell Gel Electrophoresis assay and interpret the meaning of the observed variability with respect to future study design and the sample size necessary  Specific  to  ensure  statistical  significance.  aims:  1. )  Establish a protocol for the Single cell gel electrophoresis or "Comet" assay.  2. )  Recruit a population of 15-20 female nurses unexposed to known DNA damaging agents.  3. )  Develop and administer a questionnaire containing questions concerning possible  4. )  genetic  and environmental  exposures.  Obtain six sequential blood samples for each participant over a period of ten weeks.  5. )  Perform the comet assay on the samples and analyze.  6. )  Assess the results and perform statistical analysis.  7. )  Inform workers, publish results, and write and defend thesis.  19  ///.  Materials  III.I  Contacting Subjects  Occupational participants  and  and  were  recruitment recruited  radiotherapy,  to  be  were  females  not  oxide,  pregnant  or breastfeeding,  who  suggested  contacting be  nurses  contacted  With  the  several  or anesthetic  they  1994.  never  not  for  were  Appendix  sheet  (see  information  book,  i n order  last  made  units.  to  It  least  A ) and  to contact for  with  the  most  likely  suggested  individuals  were to  procedure was also f o l l o w e d i n two other units (wards It was may  be  brought  to the  attention  confusing, with  respect  of the to  the  that  to experience , the  author  to  X-rays,  currently  author  not  of  spoke  left  present  was  psychiatry  chemical  answer  consider  which  the  to  nurses  during  questions. in the and  units  exposures.  An  unit  provide  participation.  the  This  1 A and B , and wards 2A  at this time that the  reference  or  HepB.  feasible  i n f o r m a t i o n and  who  inclusion criteria,  not  the  Occupational Health Nurse,  a sign-up sheet were  those  the  drugs,  were  H I V or  the  managers  provide  years,  with  was  and  chemotherapy  antineoplastic  five  recruitment,  the  period  to  site  T o meet  received  infected  hospital was  in order  hour  in the  were  shifts  twenty-four  had  n u r s i n g unit  information  required  who  options  approval o f the  different  Vancouver Hospital-UBC  in December,  d i r e c t l y i n their  first, as  the  gases  and  at the  several  subjects  o c c u p a t i o n a l l y exposed  ethylene  contact  of  from  H y g i e n e programme had  Initial  Methods  and B ) .  i n f o r m a t i o n sheet  o c c u p a t i o n a l exposures  in  the  20  exclusion criteria.  A new sheet was provided to these two units which more clearly  impressed the fact that these were occupational, rather than theraputic or diagnostic,  exposures.  Names from the list were contacted to verify interest in participation, and at a convenient time before samples were taken the individuals were given two copies of the consent form (see Appendix B), one of which was signed and taken by the author, and the other retained by the participant.  At this time, dates were scheduled for six  blood samples to be given, over a period of ten weeks.  Sampling was scheduled on  days when the participant was able to give blood between 12 noon and 3 pm, with an attempt made to sample at random intervals during the ten week period. The subjects  from the occupational hygiene program were approached by the  author with the second information sheet mentioned above, and consent obtained in the same manner.  was  These participants were scheduled for blood sampling  to coincide with nurses, in no specific groupings, so that more than one blood sample could be worked on each day.  All samples were scheduled between noon and three  pm.  III.2  Development  and administration of  the questionnaire  The primary purpose of the questionnaire (Appendix C)  was to provide  information on possible exposures to anything that is known to damage DNA. Environmental factors such as occupation, diet, and tobacco use, possible  genetic  factors such as a history of cancer, and other factors such as age and menstrual cycle may have an effect on the levels of DNA damage observed by various different methods (Hayes, 1992). necessary  The information gathered on the questionnaires was  to compare the presence and levels of such factors between  the study and between different samples given by a single individual.  individuals in  21 The questionnaire was based on one developed by Hugh Davies of the Quintana laboratory (personal communication, 1994), and was modified to elicit information more specific to females and less geared toward employment history.  A longer form  was used for the first blood sample, gathering detailed information; the  subsequent  samples were accompanied by a shorter form which asked only those questions where the information could have potentially changed between samples. removable coversheet  contained the name of the subject  A  and contact information,  and an identification number which was used to link this information to the rest of the  questionnaires. The questionnaire was not tested before administration but was critiqued on  the clarity of questions  and the possibility of biases by several individuals not  involved in the study. Each participant recruited from the hospital was given one copy of the primary questionnaire as well as five copies of the shorter version at the time the consent form was signed.  When blood samples were given, the appropriately labeled  questionnaire was sent back to the author via campus mail within one to two days. The participants from the Occupational Hygiene programme were given the appropriate questionnaire whenever a blood sample was taken, and usually filled it out before leaving, or within one day.  III.3  Blood sample  collection  Six blood samples from each participant were collected on various days over the period of January 25 to April 6, 1995.  Five of the participants had venous blood  samples drawn into heparinized tubes at the Medical Laboratory at the Vancouver Hospital - UBC site.  The remaining 8 participants gave blood via a fingerstick by the  author in the laboratory.  Using a semi-automatic  lancet (Becton-Dickson,  22  Rutherford, NJ), the tip of a finger was pricked, and two samples of approximately 100 u.L were drawn.  III.4  Lymphocyte  All samples were drawn between 12:00 and 3:00 in the afternoon.  isolation  For the venous samples, 100 uL whole blood was mixed with 500 uL cold Hank's buffered saline solution (HBSS, Sigma, St. Louis, MO) in a 1.5 mL microfuge tube.  For  the fingerstick samples, 90-100 uL of whole blood was mixed with 500 uL cold HBSS with 2% ethylenediaminetetraacetic coagulation.  acid (EDTA, Sigma, St. Louis, MO) to prevent  100 uL of cold Ficoll-paque (Pharmacia, Baie D'Urfe, PQ) was then  carefully layered at the bottom of each tube. The samples were then spun in a microfuge for 3 minutes at 3500 rpm.  This  results in a layering of the components of the blood, with the red blood cells at the bottom, followed vertically by a Ficoll layer, a thin cloudy layer containing lymphocytes, and then the HBSS in the upper layer.  100 uL of the layer containing  the lymphocytes was extracted with a micropipet, removing as little of the Ficoll layer as possible.  The lymphocyte solution was then washed by adding 800 uL of cold  HBSS, mixed thoroughly by inverting the tube, min.  and centrifuged at 3000 rpm for 5  The supernatant was then removed, and the pellet that formed was  resuspended  in 10 uL cold HBSS.  III.4.1  Counting of cells in a solution Normally, the isolated lymphocytes are counted in order to determine what  volume of cell suspension should be used.  Cells are counted using a hemocytometer  (Fisher Scientific, Vancouver) according to the protocol of Sigma (1992).  A cell  suspension is prepared in a balanced salt solution, 10 uL of which is thoroughly mixed with 10 uL of 0.4% trypan blue solution (Sigma, St. Louis, MO). With the coverslip in place, approximately 10 uL of this mixture is transferred to the  23 hemocytometer,  the chambers of which fill by capillary action.  one or more of the etched squares until 100 cells are observed.  Cells are counted in The average cell  count per square multiplied by the dilution factor multiplied by 10  4  yields the  number of cells per mL, and this value multiplied by the original volume of fluid from which the cell sample was removed gives the total number of cells. To eliminate this step from the experimental protocol, the number of cells that could be isolated from different volumes of whole blood, using the above procedure, was identified.  It was concluded that 100 pL of whole blood would yield  approximately 35 000 lymphocytes, which, from previous experience,  is known to be  an adequate number to allow for enough cells on a slide without excessive overlapping  III.5  of the  images.  Control cells - culturing and usage of a MOLT-4 cell line For this series of experiments, a MOLT-4 cell line was used as an internal  control.  An internal control series is necessary to ensure that the levels of DNA  damage observed are the result of biological variability and not technical variability. This is accomplished by monitoring the response of a stable or known component of the experiment, such as a cell line, and comparing this response each time the experiment is performed.  These cells were originally from American Cell Type  Cultures and were obtained from Dr. NP Singh at the University of Washington in Seattle.  This cell line is a stable T-cell leukemia, derived from peripheral blood, and  is characteristically hypertetraploid, having a modal chromosome  number of 95  (occurring in 24% of cells) and 0.8% of the cells having higher ploidy (Minowada, Ohnuma, & Moore, 1972).  The original passage number for the cells  at the end of the experiments  the cells had undergone sixty-five  is not known but  additional passages.  The cell line was cultured in RPMI 1640 /10% FBS (both solutions from Terry Fox  Laboratory, Vancouver); every four to five days, the culture was split under  24 sterile conditions by creating a 8:1 solution.  or  T h e d i l u t i o n was determined  16:1  dilution  by a visual  o f the  c e l l s used  culture was split three days culture  was  dense enough  exponential  growth phase  in every  for harvesting and  tube,  resuspended  and spun at  an  c o n t a i n i n g as  approximately This would  adequate number few dead  previously.  the  same age,  ensure that  of cells,  but  or d y i n g c e l l s as  the  still  in  the  possible.  1500 rpm for  10 minutes.  T h e resulting pellet  v o l u m e o f solution that  was  was  for 5 minutes.  T h e final  in 50 u L H B S S and 10 u L was removed and counted  Whatever  a  1.5 m L of the cell solution was removed, placed in a  in 1 m L o f H B S S and respun at the same speed  pellet was resuspended  fresh  made.  were  prior to b l o o d s a m p l i n g .  W h e n used i n experiments, microfuge  experiment  with  inspection o f the culture to be split,  and i f the density o f cells was l o w , an 8:1 dilution was So that the  previous culture  determined  to  as described  contain  approximately 25 000 cells was removed and fresh cold H B S S was added to 10 u . L .  III.6  Procedure  for  The procedure  the  Single cell  gel  for the Comet assay  electrophoresis used was  (Comet ) A s s a y -  a m o d i f i c a t i o n o f the  protocols  from two sources ( S i n g h , et a l . , 1994; T i c e & A n d r e w s , 1993). All and is  o f the  aliquoted  solutions used  into  the  required  in this assay volumes  so  were made  in advance  that day-to-day  in large  v a r i a t i o n from  quantities  this  source  minimized.  III.6.1  Preparation After  o f slides:  the l y m p h o c y t e s were isolated and resuspended  in 10 u.L o f H B S S ,  the  sample was m i x e d with 100 u L o f 0.5% agarose (Seakem G o l d , F M C Bioproducts) in phosphate  buffered saline ( P B S , S i g m a , St. L o u i s , M O ) at 4 2 ° C .  q u i c k l y pipetted onto a fully coverslip  (both  frosted  This  mixture was  microscope slide, covered with a 24 x 60 m m  from F i s h e r S c i e n t i f i c ,  V a n c o u v e r , B C ) , and placed on a flat  ice pack  25 for 30 seconds.  The slide was allowed to warm slightly, a second layer  of 100 u,L  agarose was added, the coverslip was replaced, and the slide was again placed on the ice pack for 30 seconds.  111.6.2  Cell lysis: The  coverslip was removed from the slides, which were then immersed in cold,  freshly prepared lysing solution for one to two hours at 0°C.  Lysing solution  consisted of the pre-prepared base (2.5 M NaCI (Fisher Scientific, Vancouver, BC), 1% Na-lauroyl sarcosinate (Sigma, St. Louis, MO), 100 mM EDTA, and 10 mM Tris base (Boehringer-Mannheim)),  with  Mannheim) added before use.  1% Triton  X-100  (peroxide-free,  Boehringer-  When the Triton X-100 was added, the solution was  placed on a rocker in a 4°C refrigerator for 30 minutes.  111.6.3  DNA unwinding and electrophoresis: Slides were placed  the box and electrophoresis  in the electrophoresis buffer (see  assembly near the positive end of  below) was gently poured over the slides.  After 20 minutes to allow for DNA unwinding (Tice & Andrews, 1993) the power supply was set to 24 V and the buffer level was adjusted until the approx. 300 mAmps.  The slides were electrophoresed  amperage was  for 20 min.  The electrophoresis buffer consisted of 300 mM NaOH (JT Baker, Inc), 0.1% 8hydroxyquinoline (Sigma, St. Louis, MO), Sigma), and 10 mM EDTA.  To make  2% dimethyl sulfoxide (DMSO, also from  1L of the buffer, first add 700-800 mL dH20 to a  beaker and add, in order, lg 8-hydroxyquinoline, 20 mL of 500 mM stock EDTA (pH 7.5),  30 mL of 10 N NaOH,  volume to 1 L .  and stir. Add 20 mL of DMSO to the buffer, and adjust  26 111.6.4  Neutralization After electrophoresis, the slides were removed and immersed in  50 mL 0.4 M  Tris (pH 7.5) for 1 hour.  111.6.5  Alcohol fixing After Tris treatment, the slides were dipped in 100% ethanol (JT Baker, Inc) for  15 minutes in order to fix the DNA by drying the agarose.  The slide was then  removed, drained, and air blown slightly to dry off the ethanol from the slide.  111.6.6  Staining of slides A coverslip was placed on each slide, and then one slide at a time was  uncovered and 50 mL of YOYO-1 dye (Molecular Probes, ;1 mL/mL of distilled water) was added.  The slides were then analyzed using a FITC filter  (Nikon Canada).  Analysis involved measuring the image length and the head diameter with the eyepiece  III..6.7  micrometer.  Scoring of slides All slides were scored on a Nikon LABOPHOT2-POL microscope with a  fluorescence unit attached and a B2-A filter cube (Ex 450-490, DM 510, BA 520). The majority of slides were scored within one week of preparation; all slides were scored within two weeks of preparation. placement under the microscope. Hugh Davies, an independent  Each slide was stained just before  After slide preparation, each slide was blinded by  coworker, who covered the identification  mark and  affixed  a code number unknown to the author, who performed all scoring for this  study.  When all scoring was completed, the code was broken and the slides were  recoded with the subject  and sample  identification  numbers.  27  Scoring protocol is depicted in figure 2a; scoring was initiated at the position indicated, and proceeded from the bottom of the slide to the top.  Generally, 50 cells  could be scored from this one area, but if there was not enough cells, the slide would be moved horizontally to the left over two fields of view, and then scoring would resume from the top to bottom until 50 cells were scored.  When a cell was located, the image was measured in the following manner.  As  depicted in figure 2b, the cell was arranged in the field of view so that the edge of the head was at the left or the beginning of the eyepiece micrometer (point A).  The end  of the image 'tail' is characterized by the point farthest to the right where three concentrated units of dye or "pixels" can be found on the same vertical plane (point B) (Singh, et al., 1994).  The value on the micrometer at this point is the image length.  The radius of the head was also measured as the value on the micrometer at the center of the image 'head' (point C), multiplied by two.  If an image was longer than  the micrometer, the image was shifted so that the point at 100 moved to 0, and the remainder of the image was measured as described above. The eyepiece graticule was calibrated by measuring the length of a micrometer with divisions known to be 0.01  mm in length.  The graticule itself was 20  micrometer divisions or 0.20 mm in length, with each of the 100 graticule divisions measuring 0.002 mm or 2 pm . Photographs were taken of random images which were representative various types of cells that could be observed.  of the  The camera (Nikon N2000) was mounted  on the microscope and several different shutter speeds were used.  28 III.7  Enumeration and analysis of data Data obtained from both questionnaires and scoring was entered into a  Microsoft Excel™ Quadra™  spreadsheet.  605 using an SPSS™  Statistical analysis was performed on a Macintosh (SPSS Inc, Chicago IL) software package.  a.) Slide  Coverslip  =T 1i  begin scoring  b.)  Figure 2: a. ) Diagrammatic representation of the scoring protocol, showing point where scoring begins and the direction of slide movement to find new images, and b. ) Diagrammatic representation of the graticule, with image that measures a head diameter of 18 microns and an image length of 29 microns. Point A is the beginning of the image, point B is the midpoint of the head, and point C is the last point where three "pixels" of DNA line up vertically, corresponding to the end of the image.  30  IV.  IV.1  Results  Recruitment of  subjects  With the method of recruitment described in the previous section, thirteen female participants were obtained for this study.  Of this number, five were recruited  from the hospital and eight from contacts within the Occupational Hygiene programme. It is hard to determine the refusal rate for the method of recruiting volunteers used in this study.  It can be noted that, with respect to the nurses, while the author  did experience much interest in the results of this study, there was little interest in actual participation.  Thirty percent of the individuals contacted directly in the  wards who met the exclusion criteria agreed to participate, and one individual who initially agreed later refused.  Two of the five nurses who agreed to participate did so  after reading about the study in the information books.  It can be assumed that this is  a very low percentage of the actual number of individuals who work in these units. Ninety percent of those approached in the occupational hygiene to participate.  programme agreed  31 IV.2  Blood  Sampling  Obtaining allotted for  was very  various  three.  six b l o o d  successful.  reasons,  one  In total, 73 b l o o d A  number  information  samples  Eleven  individual  be  usable data was acquired from  IV.3  Photographic Figure  experiments.  individual  contributed  gave four  the  full  samples  ten  number and  week  period  o f samples  another  from  resulted  them.  Upon  in a loss o f samples  gave  before  and, only  56 of the blood samples g i v e n , or 77 percent.  of  the  images  observed  3 is a photographic example o f the diameter  any  c o m p l e t i o n of a l l p o s s i b l e s c o r i n g ,  D.  example  The head  over the  samples were collected.  obtained  in Appendix  each  individuals  o f technical difficulties  could  is presented  from  images  observed  and image length are given  in  in these  um .  This  data  Figure 3(a and b): Example of images observed - a.) undamaged cell, 11 head diameter, b.) slightly damaged cell, 11 nm head diameter and 30 nm image length.  33  Figure 3 (c and d): Example of images observed - c.) fairly damaged cell 12 nm head diameter and 95 um image length, and d.) apoptotic cell, 4 um head diameter and 180 um image length.  34  IV.4  Questionnaires Questionnaires were completed for all blood samples taken, and although  consent to recontact was given in all cases it proved to be unnecessary.  For each  question asked, possible answers were coded in a numerical format for ease of analysis.  Upon receipt of the final questionnaire for each individual, all data was  entered and coded. ease analysis.  After all of the data was compared, some questions were recoded to  For example, the amount of vitamin C used was changed from an actual  amount taken in milligrams to an assignment  into one of three groups  corresponding to high, medium, and low usage, determined by the data itself. A summary of the questionnaire data used for analysis is given in Appendix E. Many differences  existed  both between the individuals in the study and  between different samples given by the same person. from 23-57 years.  The age of participants ranged  Seventeen percent of samples were taken when the individual  sampled was inflicted with a cold or other virus, and 75% had experienced a cold or other virus within a month of the sampling date.  Two of the participants, or 15%,  had been diagnosed with cancer in the past, affecting 19% of the samples.  Twenty-  three percent of samples were drawn from an individual vaccinated in the last six months, and 54% were vaccinated in the last two years. Sixty-three percent of the samples were drawn within one year of a diagnostic X-ray exposure, and the number of X-rays experienced in the last ten years ranged from 0 to 30.  The majority of these X-rays were dental.  Thirty-one percent of the thirteen study participants ever used oral contraceptives, with current usage by three.  One individual was using a Norplant  contraceptive device for the duration of the study. participants experienced  regular menstrual cycles  (28  Sixty-nine percent of the days ± 1) and the days since  35 the start of the last menstrual cycle ranged from 2 to 175, with one participant postmenopausal. Three of the participants, or 23%, were smokers, consuming less than one package of cigarettes per day.  For only 25% of the samples the individual exercised  vigorously 6 to 48 hours prior to the sample being drawn. stressful  For 42% of the samples a  event occurred prior to sampling.  Over half of the individuals, or 54%, reported no vitamin C use, and 75% reported no vitamin E use.  Of the half which did use vitamin C, 32% reported low  usage, and 62% used relatively high amounts of vitamin C on a regular basis. Information on diet also showed great variation between study individuals. None were strict vegetarians, although servings of vegetables per day ranged from 2 to 10, and the amount of red meat intake ranged from none to relatively high amounts.  There were also significant difference in the amount of cured and grilled  meat in the diet, as well as the amount of caffienated beverages, particularly  coffee,  consumed per day. Observed differences  in exposures  or circumstances that can change over  time, such as the presence or absence of viral infections and menstrual period, are indicative of the potentially significant events that can occur between sampling dates.  IV.5  Data Analysis  IV.5.1 Presentation  of  results  The raw data is presented in Appendix F.  All scorable slides for both blood  samples and MOLT-4 samples are included. A histogram created from all data for each subject, and the results of a statistical analysis of this data, is presented in figure 4 (a-m).  36  IV.5.2  C o m p a r i s o n o f means As  mentioned  prepared  for  each  samples,  or 57  performed  information  on  two  versus  set  variation  one  methods,  hundred two  slides on  which  scored  thirty-two the  o f the  c e l l s were  T h e results  during  slide  were fifty-six  numerous  h o w to treat this data,  o f replicates.  introduced  cells are  slides or replicates  However, only  In order to determine  for each  the  and  taken.  produced  to score.  fifty  materials  b l o o d sample  percent,  distinct enough test was  in the  when  a two-tailed t-  o f these t-tests p r o v i d e d  preparation,  the  effect  from the two slides scored  in A p p e n d i x G .  The t-tests suggest that the data from the two slides scored can  to  for  that  further  without  introducing  T h e t-test results  significant  bias  to  the  Investigating It was  noted  measurement  was  investigate  the  relationship  early on in the  decreasing,  the  decreases The  in  sample  greatly  author  felt  handling,  relationship  first  the  that  large  and  potentially bias results. the days  analysis are  (figure  also  5b),  removed,  i f included I f the the the  data  length  should exist, but  between the  image  that the week  first  and  initial in  from  relationship relationship  last  as can  of the  are listed be  interpretation  of  and  first day  decreases. decreases  be  were  sample  o v e r a l l image of  length  sampling.  seen  sampling  measurements  statistical the  for  date  If no  mean  mean  since  and  M O L T - 4 slides was plotted versus the date of sample (figure 5a). present, no  the  results  s c o r i n g of samples  particularly  observation,  assay  blood  were  this  between  each  effects  of  analysis.  IV.5.3  to  analysis  when possible.  and  p o o l i n g the data  pooled  and  In  sample  and  systematic  by  the  plot,  due  to  following  (figure  the  inexperience  analysis  o f s a m p l i n g is removed  again  the  days.  questionnaire  If the  order  5c).  two  could from  sampling  37 Basic Statistics end histogram for a l l data from a l l subjects: Count  Midpoint  1682 740 416 241 172 110 110 153 122 88 47 21 16 14 1 2 6 3 0 0  13.00 23.00 33.00 43.00 53.00 63.00 73.00 83.00 93.00 103.00 113.00 123.00 133.00 143.00 153.00 163.00 173.00 183.00 193.00 200.00  Ona symbol equals approximately 40.00 occurrences  _i  400 800 1200 Histogram frequency  1600  2000  Basic Statistics "eon Mode Kurtosis S E Skew Maximum  33.829 11.000 8.004 .039 405.000  Std err .476 Std dew 29.900 S E Kurt .073 Range 397.000 Sum 133624.500  Median variance Skewness Minimum  21.000 894.004 2.056 8.000  Statistics and histogram for subject 566 Count  Midpoint  211 31 17 9 6 4 7 5 3 4 1 1 1 0 0 0 0 0 0  15.00 25.00 35.00 45.00 55.00 65.00 75.00 85.00 95.00 105.00 115.00 125.00 135.00 145.00 155.00 165.00 175.00 185.00 195.00  One symbol equals approximately 8.00 occurrences  r  80 160 240 Histogram frequency  Mean Mode Kurtosis S E Skeu Maximum  Figure 4:  a.)  22.933 11.000 6.263 . 141 138.000  Std err Std dew S E Kurt Range Sum  1.306 22.620 .231 128.000 6895.000  Med i an Oar Iance Skewness Mini mum  320  400  13.000 511.662 2.518 10.000  Basic statistics and histogram for all image length measurements from all subjects, and b.) statistics and histogram for all image length measurements for subject 566.  38  Statistics and histogram for subject 574  Midpoint  Count 129 59 16 9 6 10 2 7 2 3 4 0 3 0 0 0 0 0 0  One symbol equals approximately  4.00 occurrences  15.00 25.00 35.00 45.00 55.00 65.00 75.00 ' 85.00 95.00 105.00 115.00 125.00 135.00 145.00 155.00 165.00 175.00 185.00 195.00 40 80 ' 120 Histogram frequency  Mean Mode Kur tosIs S E Skeu Maximum  28.588 11.000 4.506 . 154 131.000  Std err Std dev S E Kurt Range Sura  1.604 25.355 .307 - 121.000 ' 7147.000  160  Median Variance Skeuiness Minimum  200  19.000 642.862 2.222 10.000  Statistics and histogram for subject 655 Count 89 21 14 13 12 It 4 9 11 5 3 5 2 1 0 0 0 0 0  Midpoint  One symbol equals approximately  2.00 occurrences  15.00 25.00 33.00 45.00 55.00 65.00 75.00 85.00 95.00 103.00 115.00 '125.00 135.00 145.00 155.00 165.00 175.00 185.00 195.00 20 40 60 Histogram frequency  Mean Mode KurtosIs S E Skeu Maximum  Figure 4:  c.)  39.885 11.000 .098 .172 145.000  Std err Std dev S E Kurt Range Sum  2.409 34.064 .342 135.000 7977.000  Median UarIance Skewness Minimum  80  100  22.000 1160.343 1.112 10.000  Basic statistics and histogram for all image length measurements for subject 574, and d.) statistics and histogram for all image length measurements for subject 655  39  Statistics and histogram for subject 681 Count 83 27 8 5 4 10 4 7 1 1 0 0 0 0 0 0 0 0 0  Midpoint  One symbol equals approximately 2.00 occurrences  15.00 . 25.00 35.00 45.00 55.00 65.00 75.00 85.00 95.00 105.00 115.00 125.00 135.00 145.00 155.00 165.00 175.00 185.00 1S5.00 20 40 60 Histogram frequency  Mean Mode Kurtosis S E Skeo Maximum  27.733 11.000 1.161 . 198 101.000  Std err Std dew S E Kurt Range Sum  1.814 22.222 . .394 91.000 4160.000  Med i an UarIance Skewness Mini mum  100  80  18.000 493.821 1.526 10.000  Statistics and histogram for subject 703 Count  Midpoint  128 95 52 21 19 15 13 22 13 10 5 2 2 2 0 0 0 0 0  15.00 25.00 35.00 45.00 55.00 65.00 75.00 85.00 95.00 105.00 115.00 125.00 135.00 145.00 155.00 165.00 175.00 185.00 195.00  One symbol equals approximately 4.00 occurrences  40 80 120 Histogram frequency Mean Mode Kurtosis S E Skew Max I mum  Figure 4:  e.)  38.993 12.000 31.489 . 122 405.000  Std err 1.721 Std dew • 34.423 S E Kurt .243 Range 395.000 Sua 15597.000  Med I an UarIance Skewness MI n i mum  160  200  27.000 1184.915 3.788 10.000  Basic statistics and histogram for all image length measurements for subject 681, and f.) statistics and histogram for all image length measurements for subject 703.  40  Statistics and histogram for subject 711 Count  Midpoint  230 94 42 31 12 7 11 15 22 18 11 1 1 , 3 0 0 2 0 0  15.00 25.00 33.00 45.00 55.00 • 65.00 75.00 85.00 95.00 105.00 115.00 125.00 135.00 145.00 155.00 165.00 175.00 185.00 195.00  One symbol equals approximately 8.00 occurrences  80 160' 240 Histogram frequency Mean Mode Kurtosis S E Skeo Max i mum  34.659 11.000 1.999 . 109 175.000  Std err Std deu S E Kurt Range Sum  1.418 31.714 .218 165.000 17329.500  Median Uariance Skeuiness Minimum  320  400  20.000 1005.776 1.655 10.000  Statistics and histogram for subject 715 Count  Midpoint  234 84 49 23 18 5 5 11 7 5 4 0 3 2 0 0 0 0 0  15.00 25.00 33.00 45.00 55.00 65.00 75.00 85.00 95.00 105.00 115.00 125.00 135.00 145.00 155.00 165.00 175.00 185.00 195.00  One symbol equals approximately 8.00 occurrences  80 160 240 Histogram frequency Mean Mode Kurtosis S E Skeo Maximum  Figure 4:  g.)  28.216 12.000 5.225 .115 143.000  Std err Std deu S E Kurt Range Sum  1.145 24.284 .230 133.000 12697.000  Median Uariance Skeuiness Minimum  320  400  18.000 589.711 2.261 10.000  Basic statistics and histogram for all image length measurements for subject 711, and h.) statistics and histogram for all image length measurements for subject 715.  41  Statistics and histogram for subject 728 Count 108 42 14 13 5 0 2 4 5 3 3 0 0 0 0 0 1 0 0  Midpoint  One symbol equals approximately  4.00 occurrences  16.00 26.00 36.00 46.00 56.00 65.00 76.00 86.00 95.00 105.00 116.00 126.00 136.00 146.00 155.00 166.00 176.00 186.00 196.00 40 80 120 Histogram frequency  Mean Mode Kurtosis S E Skew Max i mum  28.845 14.000 7.955 . 172 180.000  Std err Std deu S E Kurt Range Sum  1.S31 25.894 .342 169.000 5769.000  200  160  Median far i ance Skewness Mini mum  19.000 670.493 2.629 11.000  Statistics and histogram for subject 812 Count  Midpoint  168 48 22 7 12 8 9 16 6 3 1 0 0 0 0 0 0 0 0  15.00 25.00 35.00 45.00 55.00 65.00 75.00 85.00 95.00 105.00 115.00 125.00 135.00 145.00 155.00 165.00 175.00 185.00 195.00  One symbol equals approximately  4.00 occurrences  40 80 120 Histogram frequency Mean Mode Kurtosis S E Skeo Maximum  F i g u r e 4:  i.)  28.433 11.000 1.281 .141 113.000  Std err Std deu S E Kurt Range Sum  1.437 24.885 .281 103.000 e530.000  Median Uariance Skewness Minimum  160  200  16.000 619.263 1.574 10.000  B a s i c statistics and histogram for a l l image length measurements subject 7 2 8 , and j . ) statistics and histogram for a l l image length measurements for subject 8 1 2 .  for  42  Statistics and histogram for subject 851 Count 103 51 37 20 7 5 10 12 2 0 1 1 0 1 0 0 0 0 0  Midpoint  One symbol equals approximately 4.00 occurrences  15.00 25.00 33.00 45.00 55.00 65.00 75.00 85.00 95.00 105.00 115.00 125.00 135.00 145.00 155.00 165.00 173.00 185.00 195.00 40 80 120 Histogram frequency  Mean Mode Kur tos i s S E Skew Max i mum  31 100 15 000 3 034 154 140 000  Std err Std dev S E Kurt Range Sum  1 462 23 114 307 130 000 7775 000  160  Median far i ance Skeuiness Mini mum  200  22.500 534.235 1.73? 10.000  Statistics and histogram for subject 906 Count  Midpoint  69 10 7 5 2 3 1 1 0 1 0 1 0 0 0 0 0 0 0 0  13.00 23.00 33.00 43.00 53.00 63.00 73.00 83.00 93.00 103.00 113.00 123.00 133.00 143.00 153.00 163.00 173.00 183.00 193.00 200.00  One symbol equals approximately  1.50 occurrences  15 30 45 HIs togram frequency Mean Mode KurtosIs S E Skeo Maximum  Figure 4:  k.)  22.070 11.000 8.561 .241 125.000  Std err Std deu S E Kurt Range Sum  2.052 20.523 .478 117.000 2207.000  -  Median Uariance Skeuiness Mini mum  60  75  13.000 421.197 2.726 8.000  Basic statistics and histogram for all image length measurements for subject 851, and 1.) statistics and histogram for all image length measurements for subject 906  43  Statistics and histogram for subject 933 Count 72 25 4 9 2 3 5 10 7 4 3 3 2 0 0 0 1 0 0  Midpoint  One symbol equals approximately  1.50 occurrences  15.00 25.00 35.00 45.00 55.00 65.00 75.00 85.00 95.00 105.00 115.00 125.00 135.00 145.00 155.00 165.00 175.00 185.00 195.00 15 30 45Histogram frequency  Mean Mode Kurtosis S E Skeur Max 1 mum  38.467 11.000 .691 . 198 170.000  Std err Std dew S E Kurt Range Sum  2.912 35.667 .394 160.000 5770.000  60  Median War Iance Skeiuness Mini mum  75  21.000 1272.130 1.300 10.000  Statistics and histogram for subject 942 Count 174 65 32 19 6 9 7 11 6 11 3 0 0 2 1 1 2 1 0  Midpoint  One symbol equals approximately  4.00 occurrences  15.00 25.00 35.00 45.00 55.00 65.00 75.00 85.00 95.00 105.00 115.00 125.00 135.00 145.00 155.00 165.00 175.00 185.00 195.00 40 80 120 Histogram frequency  Mean Mode Kurtosis S E Skeo Maximum  F i g u r e 4:  32.380 12.000 5.402 . 130 180.000  Std err Std dew S E Kurt Range Sua  1.654 30.939 .260 170.000 11333.000  Median Uar i ance Skemness Minimum  160  200  20.000 957.233 2.261 10.000  m.) B a s i c statistics and histogram for a l l image length measurements subject 938 and n.) statistics and histogram for a l l image length measurements for subject 942  for  samp Ii ng day 115 c a s e s p l o t t e d . R e g r e s s i o n s t a t i s t i c s o f MEAN on DflTEHO: C o r r e l a t i o n - . 4 6 1 4 4 R Squared .21293 S . E . o f E s t 28.56345 S i g . .0000 Intercepts.E.> 104.97009C 5.20930> S l o p e C S . E . > -3.05753< .55300>  Figure 5(a.):  Scatter plot depicting the relationship between the mean image length for both lymphocytes and MOLT-4 cells in u,m and the sampling day for the slide.  ri  180-  1  1  Comparison  1  1  when f i r s t s a m p l i n g day e x c l u d e d  1  1  1  1  1  1  \  s a m p l i n g day 107 c a s e s p l o t t e d . R e g r e s s i o n s t a t i s t i c s o f MERN on DRTENO: C o r r e l a t i o n - . 3 3 6 7 7 R Squared .11341 S . E . of E s t 27.50336 S i g . .0004 IntercepUS.E. > 94.45247< 5.67919) SlopeCS.E. ) -2.1321K .58176)  Figure 5 (b.):  T h e r e l a t i o n s h i p between the mean image length f o r both l y m p h o c y t e s and M O L T - 4 cells i n u.m and the s a m p l i n g day for the slide after the samples from the first s a m p l i n g day are r e m o v e d .  samp I i n g day 94 c a s e s p l o t t e d . R e g r e s s i o n s t a t i s t i c s o f MERN on DRTENO: C o r r e l a t i o n - . 1 2 6 9 8 R Squared .01612 S . E . o f E s t 25.65819 S i g . .2226 Intercepts.E. > 77.97603 < 6 . 4 5 7 2 4 ) Slope<S.E.) -.7647K .62279)  Figure  5(c):  T h e relationship between the mean image length for both lymphocytes and M O L T - 4 cells in p m and the sampling day for the slide that exists after the first three s a m p l i n g days are r e m o v e d .  47  IV.5.4  U s e o f different Several  provided image  different  clearer  length,  or  metrics for metrics  more  median  analysis  were  used  interpretable  image  length,  194 u m  analysis  information.  mode  72 u.m i n length, percentage of images images over  in this  image  over  The length,  134 u m  to  determine  metrics  used  percentage  in length,  i f any were  of  mean  images  over  and percentage o f  in length.  T h e most c o m m o n l y used metric is the mean, but this value may not give an accurate  s u m m a r i z a t i o n of the  and mode are not affected concern.  Because  damage to c e l l s , utilized.  the  deviation  (134  representation 6  from  because  the  it is influenced by outliers.  influences  or  factors  that equal  values correspond  lymphocyte  samples  may  (72  through  these 11.  metrics  for  each  cause  u.m), the  sample,  different  or exceed certain  to the mean  u m ) , and the mean plus two standard of  The  median  by outliers and may be a better choice i f outliers are o f  percentage o f images  In this case,  measurements  figures  different  data  of all image  mean  plus one  types  values was  by  subject,  also  length standard  deviations (194 u.m).  grouped  of  A graphical  is given in  48  y.  do"  c  <T>  Mean image length in um o  ro  4^  o  o  CO  o  K3  o  o  o  O  O  O 566  ST  (D 3  o'  05  574  o  3 (Q <D  655  :  3  CD  O  3  681  •  •  703  -•  3 o  W 3  •  •  71 1  o  c  |  715  °  728  o o a.  3  -a  03 0)  3  •a o w o  c  81 2  CD  '8 5 1  (A  c ^cr *<D o  ><  d cr  t—i.  906  o  (£2  938  O  c •a  (A  942  >  O  •  •  CO  CO  CO  CO  CO  3 •o  3 -o  3 TJ  CD CJ>  ro  CD  03  03  en  03  in  3 X3  03  3 T3  03  CD CO  CD  CD  03  ro  31  m c  Median  <T>  image  ro o  length,  co o  o  oo o  in  um o o  ro o  Q —i  566  T3  er o'  fD Q. 0)'  SB  574  3  T3  655  O 3  -o-  <D  O 3  681  •  (Q  703  sr  -•-a  3  o.. S 3  o>  71 1  • —  O ID  •  •  in  o  c  0!  o 3  00  •r  8  7 1 5  °  728 812  o o c o.  C7  oo—» .  —  •  —  o o a.  •  in  3  oa—•  CD  851 (A C CT  906  o  3  .cr a  o  938  «-*  • —D-  CQ  o c ~a cn  942  > CO 03  •  CO  3  3  CD  CD  CO  cn  "O  O  •  CO 03  CO 03  X)  T3  CD  CD  3  3  W  •  •  CO 03  CO 03  3  CD  3  T3 CD  CM  CO  LO  CD  QJ  03  03  03  03  03  CL  Q.  CL  CL  Q_  O-  ro  ro  cc  E  E  CO  ro  CO  •  •  E  E  E  E  ro  CO  00  ro  CO  CO  <  o  •  (fi  2176  Q. 13 O  8S6  o  906  E  3  (-9 8 o  0)  C3  •LO  Q.  2  E CO (fi T3 O O  "O  .Q  L8  4)  82/  60  9 LZ S  60  C  E  .C O (0  I-  <u  VI  o -a o E  D  L«>  £01  U)  189  c o  <D cn co  999  c  E o  t>Z9  c  a,  T3 O  999 I  H  r-  h  H  h  O O O O O O O O O O O C O C D T l - C M O C O C D T f C M C\J  T-  uin  1-  I-  uj  T'i|i6u3|  T-  o  o IS  D. iS3  o  oo  OBBLUI  epo|/\| 3 60  51  era' C  m  Percent o  PO  ->•  o  o  of cells over 72 um co 4^ cn a> - v i o o o o o T3  O  566  T3  CD  -a  O CD  O  574 o •a  »—*•  •-a  0)  IQ  CD  655  3  O  -O-  -*  O CD  O 3  681  3*  703  wT o  cn  <  CD  • o-»-  T3  -t  ^1  ft  »-t o 3  w  era  o  3 CO  CO c  f  <•—O  7 1 5  ro  •—«  ubj  ft  71 1  CD O  >-r>  5'  -i o c (Q  728  O  <-+  ft  N5  3  (Q  CJQ  o < o  c  CO  3*  812  •  851  . •  CD  o  IT  a;  906  o o  ft  3  OQ  Q.  938  CO 03  3  ft SB  O 3"  c a. C ft'  o  942  c  o-  "O CD  •  •  CO  CO  CO  CO  CO  3 XJ  3 XJ  3 XJ  3  3 X3  .X J 3  CD  CD  CD  CD  CD  CD  co  cn  CO  ro  > 03  O 03  03  •  03  -a  03  03  52  21 Percent  of  cells  over  134  um  o c n o c n o c n o c n o c n 4 — I — I — h  IT  H  13  CD  —r  566  cr w  <—  O CD 3 j-t Q)  574  CQ  CD T3  C9  655  CD  3  O CD  O  681  3  W  o < CD  703  5' CD  o CD  S3  rs  3  CO c  f  w c  71 1  728 i  -•  1 / 1 CO  851  Q-  3  O  CD 3  W  3"  o  09 CD  812  co  cr c  7 1 5  o <  _ L  CD  4^  CD  .-a  O  =7  906 O O Q.  CD  3  era  CD W O  938  >—a-  CO  fi)  3  942  •D  CD  sr  c  CL  >  •  O  •  •  •  CO  CO  CO  CO  CO  CO  CO  W  CO  CO  CO  CO  3  3 T3  •a  3  X)  T3  3 T3  CD  CD  CD  CD  CD  CD  a>  en  4^  CO  ro  —*•  X5  3  3  53  31  ere' c  Percent  of cells  over 194 um _ L  o r o * > - c  H c r cs  1  1  r  1  _!.  - I .  |\)  > 0 3 o r o 4 ^ c o c o o  1  1—H  1  1  1 1  -o CD  566  o CD  3  OS  #—  0) IQ  574  CD  T3 fl> 3  655 O CD  O 3  CO O < CD  3* O T3 CD *n O  -a  o 3  ere  CO  c a c Q  3  •  ere o  -  o (Q  •  O <  8 5 1 . •—>:  3  O  CD  co  -x  3  CD  0)  o  3 906 cs 3 ere  4^  -  o  4^  CO  o o o_  938  CO  0)  m CO o tr O-  3 •o  942  CD  r> CO 03  3 ~o CD CO  •  O  '•  CO  CO  CO  CO  3  3  T3  3  CD  3 T> CD  cn  4>  •  03  03  •  CO  03  03  •o  •o  CD  CD  CD  CO  ro  03  3  54 IV.5.5 Assessment  o f the  effectiveness  In order for the M O L T - 4 cell standard assay remain assay  it has  to possess several  i n a manner stable  over an extended assessed  quantitative  performed.  mean  blood  image  statistically  insignificant  When  the  with  with  in the  between  response  mean  between  MOLT-4  respond  image  to  the  cell  by  length  response  the  of  T h i s plot shows a slight but these  two  cells were observed  factors. under  the  m i c r o s c o p e , two  was very s i m i l a r in size and appearance  lymphocytes,  noticeably  in  the  the  other  i n t r o d u c t i o n , the  group  MOLT-4  w i t h a m o d a l chromosome  was cell  larger cells contained  found  from  in a cell  the  mean  corresponding figure  blood sample  MOLT-4  12(b).  blood  samples.  in all l i k e l i h o o d and  therefore,  length  large  indicates  with  the  c e l l s removed  head  T-cell  o f cells.  A s noted leukemia,  It  was  four times the  amount  possessing  potential  mean from  the  analysis.  and that o f the  of D N A for a  A comparison  image length  of  the  analysis, is presented  a slight relationship between  by the Comet assay  to  region.  hypertetraploid  should be excluded from  image  slide, with  T h i s plot also  the c e l l l i n e as detected  line is a stable  b l o o d samples,  greater e x h i b i t i o n o f D N A damage, plot o f the  larger i n the  number of 95 o c c u r r i n g in 24 percent  decided that the  the  corresponding  subsets o f cells could be seen; one set and  the  sample cells was  comparison of  of  l i n e itself.  measured  of the tissue  the  must  technical variability  by v a r i a b i l i t y  accomplished  in figure 12(a).  relationship  slides made  was  the  standard:  as an internal  line must  that the  relationship  assessment  M O L T - 4 slide; this is presented  The cell  augmented  of  length  an internal  type or tissue monitored, and  and the measured  A qualitative  sample  not  assessment  of the c e l l l i n e by this assay not  characteristics.  period of l i m e so  and  cells as  line to be considered useful  s i m i l a r to that o f the cell  is accurately  A  of M O L T - 4  the  response  lymphocytes from  the  in of  55  a. ) Comparing b l o o d s a m p l e i m a g e t  l e n g t h w i t h c o r r e s p o n d i n g MOLT-  160  140+ M a n i m a 9  120f  100-H  I e n 9 t h i n u m  100 Mean MOLT image  120  140  l e n g t h i n um  3? c a s e s p l o t t e d . R e g r e s s i o n s t a t i s t i c s o f MERN on MOLT Correlation .24465 R Squared .05985 S . E . o f E s t 20.21062 S i a 1445 Intercepts.E.) 43.28115< 13.07405) S l o p e < S . E . > . 19509< ."13069)  Figure 12(a.)  Scatter plot with regression line for mean image length in fim and the corresponding MOLT-4 group slide.  56 b. ) Comparison when Iarge MOLT e e l Is  excIuded  160+  140+  120+  100+  Mean MOLT image  length  in um  37 c a s e s p l o t i e d . R e g r e s s i o n s t a t i s t i c s o f MERN on LRGMERN: Correlation 1 2 9 4 8 R Squared .01676 S . E . o f E s t 20.66857 S i g . .4450 Intercepts.E. ) 54.48260< 10.49337) S l o p e C S . E . ) .17240< .22317) v  Figure  12-(b.) i  Scatter plot with regression line for mean image length in u.m corresponding M O L T - 4 group slide with large cells e x c l u d e d .  and  the  57  An calculation  assessment o f the o f coefficients  stability of the  o f variation  C V for all M O L T - 4 slides produced, the  percentage  and  samples The  of variation  from  different  results o f this  for  cell each  line over time  was  sampling  as  day,  and with the execution  attributed  to  days,  between  or  statistical  samples  analysis  from  a  a l l o w e d by  well  as  of an A N O V A given  day,  or  an  the overall  to determine within  sample,  samples. are  presented  i n table  2.  a.) Molt-4 ID  Date o f Sample  Coefficient  of  variation  25-Jan A, B 3.01 K, L 8-Feb ' " ' M, N, 0 10-Feb 23772 " R, S 23-Feb _„ . . J 1 I I _ 24-Feb 11.22 T, U . 7-Mar 21.07 W,X AA, Y, Z 8-Mar GG.HH 22 Mar_ 3535 23 - M a r II, J J 13" 4 3 " Z MM, NN 30-Mar 6.54 average coefficient o f v a r i a t i o n for •eplicale s l i d e s :  _ _  j :  (%)  ~  m  Z Z I  T5?72 O v e r a l l coefficient produced:  of variation  for all M O L T - 4 27.63  slides  b.) Source o f variation  sum o f squares  degrees o f freedom  mean square  Between ( c e l l s from different  18460.801  14  1318.529  3177.814  12  264.818  Within (cells from same day) Total  T a b l e 2:  21638.614  ""83T254  F,  significance of F  4.979,  0.004  % o f total variability 85  15 100  a.) Coefficient o f variation and b.) A n a l y s i s - o f - V a r i a n c e calculations to assess the stability o f the M O L T - 4 cell line.  used  58  The  overall coefficient of variation calculated for the MOLT-4 slides indicates  that there is approximately 28% variation between the means for the MOLT-4 slides over the course of the study.  The average replicate CV of 15.72% suggests that some  of this variation may be biological in nature; however, the component of variation that is attributable to biological differences  and the proportion resulting from  technical variation over the time course of the study cannot be elucidated. The  ANOVA results indicate that the variability between cells from different  days is significantly higher than the variability between cells from the same day, as would be expected.  IV.5.6  Assessment of the technical, inter- and intra-individual  variability  In order to make a crude comparison of the information obtained from each slide, the coefficient of variation was calculated for each of the six test metrics.  One  CV value was calculated for each set of replicate slides when a sample produced two scorable slides.  A value was also obtained for each of the thirteen subjects, using all  samples available (three to six values, depending on the subject).  A comparison  between subjects was made by calculating a coefficient of variation value for the mean image length of the  first, second, and third samples from each subject, as well  as a value using the average mean image length of all days for each subject. results of these calculations are given in Table 3.  The  59  Coefficient of variation calculation for each replicate pair, for each test metric % of % of mean median mode % of images im ages images image image image Replicatt length over 72 over over ID length length 194 mm mm 134 mm 40.02 60.61 38.04 66.99 27.66 30.50 566/1 141.42 141.42 141.42 566/2 60.92 44.19 12.86 141.42 71.22 0.00 128.56 ""51.74" 566/3 20.20 9.43 _ 4.88 7.29 25.38 9.43 574/3 141.42 574/4 2.64 35.36 4.29™' 24.38 141.42 28.28 1.14 16.97 655/4 15.71 0.00 7.86 22.33 2.77 0.00 681/1 4.07 5439 n/a 2438 681/2 6.67 15.7*1 47.14 9.87 12.86 703/2 3.87 4.29 """45.00 1577 5.89 """"4.56 45.25 703/3 5.17""" 47.14 n/a 23.57 703/4 41.39 " 0.00 5.11 " 0.00 711/1 24.75 44.19 """""~ 4 . 0 8 12.36 32.64 42.43 711/2 15.56 20.48 _ 47.14™" 8732 28.28 5.89 3.45 54.39 711/3 9.08 n/a 711/4 10.88 20.20 5.66 0.00 ~~72 28.28" 58.64 80.81 " 715/2 _39.77~" 35J03 T77™" 47,14""" "'""T'5'71 3.14 715/3 17.68 28.28 n/a 715/4 4.26 4.7 f" "6. T5~"~ ""l 06.07 84.85 " " 117785 715/6 "~41.59~~ 48~>0 38.57 6.58 14.35 6.43 728/1 8.23 2.30 22.33 0.00 728/2 6.94 17.88 11.47 7.71 '"15.71™ ''10.10 0.00 728/3 2T70 TT™47 20.20 n/a 11.38 10.10 20.20 812/3 7.91 67764' 86781" " 812/5 37.28 123.74 n/a _l .j£9__ 851/1 141.42 15.71 "™447 "4"" '"'"54739 851/2 T4L42 13T6'9 " """'TT.47 94.28 l'5'.7'i' l".5"9" 2 5 " . " 3 " 8 " " 906/3 """'5T89"™ _41.25_ 9A3 1.47 8.95 938/1 3.51 1.36 23.90°"°"""" ..... ^ _ 47.14 3.07 38.57 938/3 ~ 34.03 27.94 35.36 942/2 4.56 66.55 66.00 39.70 10.10_ "28.28 20.20 942/3 11.79 1.93 0.00 28.28 942/4 0.32 4.56 6.15 6.15 or each test metric Average coefficient of variation for all replicate pairs, 45.51 63.85 16.30 17.07 16.65 35.48  "'"o7oo"'-  ""'"d'oo"  :  r  5T01  jiir  676o  "o76o'""" "  67oo" "  3  67oo  IJ2-AL..Z .__ 8  -  Table 3(a.):  Coefficient of variation calculation to compare replicate slides, for human lymphocytes, for each test metric.  60  Coefficient of variation calculation for each subject, for each test metric % of images % of images mean median mode % of over over image image image images Subject 194 mm 134 mm length length over 72 length ID mm 81.65 124.10 25.84 58.25 566 6.28 4.65 58.08 67.84 70.31 574 29.88 29.43 35.29 72.11 46.46 38.74 64.57 116.07 655 65.54 141.42 103.71 11.79 681 23.86 1.94 92.93 165.27 32.90 703 """' W.54~' " 57.90 48748" 59753" 711 33.73 42.99 39.20 51.66 41.66 99.86 70.71 37.44 75.98 28.76 715 39.00 49.21 103.62 12.06 87.30 36.82 30.20 728 93.26 141.42 63.51 812 19.70 26.98 13.86 141.42 33.67 0.00 *8J. 6 8 ™" 851 9.69 7.24 60.61 6.15 12.86* 906 30.30 " 35.36" " "4.37 35.25 26.19 4.95 16.67 15.24 32.47 938 30.43 35.36 38769 942 Tf.83 207*32 ~ ™30.34"" Average coefficient of variation foi all subjects, for each test metric: 58.12 91.65 51.96 24.42 28.83 33.30 Table 3(b.):  Coefficient Using Using Using Using  Coefficient of variation calculated to compare within each subject, between days, for each of the six test metrics. of variation calculated for correspondin g samples from each subject Coefficient of Variation (%) 29.1 33.6 24.6°' 20.9  first sample from each subject second sample from each subject third sample, from each subject the average of all days from each subject  Table 3(c):  Coefficient of variation for comparing between  subjects  The average CV for the mean image length of the replicate slides was calculated as 16.3%, with a range of values from 0.32% to 71.2%. although the average difference between  This suggests that  two replicate slides from the same sample  can be very low, the mean image length measured can also be quite different between two slides that should have a relatively similar population of cells.  These  61 values but  give  some  g i v e no The  idea  of  information  within  technical  on  subject,  variability  from  the  technical  replicate-to-replicate  other  types  of  variability,  between  days  C V c a l c u l a t i o n s resulted  such  as  in an  2 4 . 4 2 % for the mean image length, with a range o f 4 . 3 7 % to 38.74%. that  some  i n d i v i d u a l s are  measured the  by the comet  average  variation  value  seen is  that c o u l d  not  make  up  an  cautious, be  assay  is greater  within  suggestion  more  than others than  however,  in the  be  because  by the  portion  time  with  to  the  replicate  attributable  to  biological  of  the  other  variability  day-to-day.  average  types from  seen  of  this  within  of  T h i s suggests the  response  It also suggests that,  for  information gained  of the  respect  study.  that calculated  i n d i v i d u a l s may  assessed  unknown  variable over  source,  because  slides, some effects.  a given  the  This  technical study,  of  variability  and  which  subject  could  over  time. The from  each  study  C V c a l c u l a t i o n s for subject,  subjects  at  indicate any  from 2 4 . 6 % to 33.6%.  that  given  the  calculation of  as  well. A an  images  over  mean  are  IV.5.7  an  more  to  may  values,  between remain  and  c o m p a r i s o n o f the whether  the  by  mean  image  length  within  an i n d i v i d u a l subjects  o f the  length  to  o u t l y i n g or extreme  sample  sample data  observed  data  the  biological  muted  decrease  test  percentage  metrics of than  the  points.  and questionnaire and  only  subject  are  would  different the  of  ranging  of all days for each  between  image  sample  T h i s should be expected, as the metrics other  blood  the  the  mean  r e l a t i v e l y constant,  as extremes variance  using a certain  the  C V values calculated for each  in length.  influenced  elucidate  point  i n v a r i a t i o n from  192 u m  difference  be expected  average,  C o m p a r i s o n s of the A  order  increase  subject  The C V calculated using the average  c o m p a r i s o n o f the  shows  between  the  time  was l o w e r , at 2 0 . 9 % , as w o u l d by  the  data  questionnaire  data  v a r i a t i o n was  the  was  necessary  result  of  in  known  62 genetic  or  and mean with  environmental image  respect  matching  to  length the  different  points  (data  factor  were found  that this  not  factor  factors.  are  shown  questionnaire factors,  shown).  such  plots  for  in figure  13.  A n a l y s i s o f the  data as  was  a  affect  questionnaire  cold-like  v i r u s , to  data  value for the  inter-individual variability. may  have  had  the  responses  various study  achieved by p l o t t i n g all o f the  average  there is no evidence o f anything w h i c h DNA  several  If a higher proportion of the  to lie above the  may  Sample  data  corresponding points  be  F o r a l l o f the  study  a positive effect  on  and  sample  correlated  metric, it c o u l d  metrics  with  the  suggested metrics, levels o f  damage. Looking  provided  little  variation.  at  each  insight  individual into  the  with  factors  respect  to  responsible  their for  questionnaire the  within  responses  individual  also  63  Mean image  l e n g t h v e r s u s age i v e r s u s age  1  160  M  h  140+  120  100-  60+  40  20+  0+ 15  25  35  45  55  65  Rge in y e a r s 47 c a s e s p l o t t e d . R e g r e s s i o n s t a t i s t i c s o f MERH on RGEC o r r e l a t i o n -.22901 R Squared .05245 S . E . o f E s t 20.86506 S i q 1215 InterceptCS.E. ) 81.33680< 11.51609) S l o p e C S . E . > -.50949<.,.'32283)  Figure  13(a): E x a m p l e s o f sample data:  c o m p a r i s o n plots o f questionnaire responses age o f subject versus mean image length  versus  blood  64  Mean image l e n g t h v e r s u s v i t a m i n C i n t a k e 160  140  120f  100  Uitarn in C i n t a k e ( 0 - 1 ,  lowest to h i g h e s t  47 c a s e s p l o t t e d . R e g r e s s i o n s t a t i s t i c s o f MEAN on UITC_: C o r r e l a t i o n - . 0 2 4 2 3 R Squared .00059 S . E . o f E s t 21.42844 S i g . .8716 IntercepUS.E. ) 64.28933< 4.30486) S l o p e < S . E . ) -.56546C 3.47810)  Figure  13(b): E x a m p l e s o f sample data:  comparison vitamin  plots of questionnaire responses versus C intake versus mean image length  blood  65  Mean  l e n g t h v e r s u s smoking s t a t u s  160+  Smoking s t a t u s  (Onon-smoker,  1=smoker)  47 c a s e s p l o t t e d . R e g r e s s i o n s t a t i s t i c s o f MERN on SMOKER—: C o r r e l a t i o n - . 0 9 0 2 6 R Squared .00815 S . E . o f E s t 21.34724 S i g . .5463 Intercepts.E.) 64.91657< 3 . 6 0 8 3 4 ) S l o p e < S . E . ) -4.34157< 7.14111)  Figure  13(c):  Examples of sample data:  c o m p a r i s o n plots o f questionnaire responses versus s m o k i n g status versus mean image length  blood  66  IV.5.8  N o r m a l i t y testing of data It  is important  data to be analyzed  when  as this  choosing will  methods of analysis  affect  to  test the  the types o f statistical  normality  analysis that can  of  the  be  performed. Looking samples  taken,  slightly  IV.6  at the the  histogram  data  cannot  be  4a)  for the  considered  image  normal  but  length can  o f all c e l l s from all  be  characterized  as  lognormal.  Sample  size  One o f the  calculation desired  results  to  enable  the  determination  to  ensure  the  statistical  A  be  of  In order  thirty needed.  an  percent  study  of size  in  sample  the  necessary  increase  length  for  levels o f variation  future  studies,  in  is  order  results.  i n d i v i d u a l s per  image  size  for  statistical  c o m p a r i n g two groups  to detect an 70  assessment o f background  appropriate  sample  size o f approximately  increase  of an  significance  for a cross-sectional  p o w e r o f 0.80. sample  of  c a l c u l a t i o n o f the  executed  would  (figure  of fifteen group  with  an  20  be  was  alpha o f 0.05  percent in image  would  approximately  significance  required;  length  and a  to detect  i n d i v i d u a l s per  group  an  a  67  V.  Discussion  V.l  Recruitment The  individuals  recruitment d i d agree  and 20 nurses There recruitment  can  have  a  to  study  always  be  drugs  assessing from  It was  not  the of  audience  initial the  that  initial  could  participants  by  o f the  some  the  could  potentially site. for  the  From  was a  being  theoretical  variability  was  have  to  Although  recruit  increased  A s in many samples  other  given.  participation  perspective  also have  reached sheet  have  by  or  from  stimulated  more  research  between  13  15  the  to  Although  interpreted  may  that it  hospital. as  individuals would  valuable,  approach  the  but  have  been  findings  this  a large number  participation.  contained  this  it is l i k e l y the  of  value  from is  not  subject.  information sheet have  success  studies,  perspective,  extremely  of a potential  the  may  studied  are  possible in this situation  may  objective  anticipated.  that i f an exposure of concern to this group, such  background  was  than  i n d i v i d u a l s who volunteer,  amount  or X - r a y s ,  information  nurses  to  intentions  participate.  personally, which target  factors  given  increased  clear  the  successful  study.  It is also l i k e l y  willing  less  Vancouver Hospital-UBC  in the  antineoplastic  was  participate,  several  at the  create a bias  to  for the are  remuneration  would  procedure  A s it was, most  alone.  some  of  It  vague  excluding occupational  was  noted  nurses of  earlier  i n f o r m a t i o n , and  exposures  such  the  as  that  some X-rays  68 and  anesthetic  gases  as  considered  themselves  forwarded  to  second  the  physically  to  units  sheet was  referring be  approach  and  personal  invalid  but  it  carefully  to  is  as  participants.  unlikely  regarded.  speak  exposures  with  A  that, h a v i n g  If it had these  in  been  nurses,  a patient  second seen  amended  the  the  problems  and  sheet  information  possible for  such  setting,  once,  author  could  was this  to  have  been  avoided.  V.2  Development The  longer  of  the  development  than  o f the  anticipated.  effectiveness  and  experimental  experimental  Because  sensitivity  protocol  are  this  still  test  for  the  protocol  for  is  occurring  comet the  relatively at  assay  Comet  new,  a constant  assay  look  refinements rate,  and  much  in  in order  for  the data from this study to be most useful, it is desirable to use the most up to date methods.  A t some  Several the  Comet  involving with the  a  problems  assay  used  image  and effort  was  that  the  were  upon w h i c h  this  only  with  the  were  laboratory,  analysis  of  image  the  accepted.  introduced  the  most  images  length  to  the  of  slides  the  increased  until  image  analysis  was  intensity,  system,  and  could  protocol  the be  for  performed and  Change to a more  imaging  sensitivity  the  time-consuming  produced  but  and tail regions.  computer  be  and  newly  therefore  sensitive  although It  much  the  time  was  discovered  performed,  dye  potential  newer  dye  used.  Preparation  There  not  must  spent on remedying this situation, it was not successful.  preserving  samples  havoc  because  w o u l d s t i l l be  the  in  Initial  protocol  modifications  o f D N A in both the head wreaked  for  a final  when  previously  measuring  (YOYO-1)  decided  arose  analysis.  computer,  amount,  point, however,  o f slides  were two  from  compromised  reasons why this  ours were based,  the before  b l o o d samples any  occurred.  went  information From  the  s m o o t h l y , but  could protocols  be  23  extracted  for the  percent from  Comet  it was stated that the slides c o u l d be left in the  of them.  assay lysis  69 buffer at 4°C for at least four weeks without affecting the results (Tice & Andrews, 1993).  For all but 10 of the 73 samples, the slides were left in the lysis buffer for a  maximum of two hours.  The slides from those ten samples, from the second and third  day of sampling, were left in the lysis buffer for approximately seven days due to an illness on the part of the researcher.  After the slides were scored, it was noted that  cells on all slides from that time period were increased dramatically in tail length, and, as this was not seen for samples from any other date, the data from the affected samples was discarded.  This effect of prolonged exposure in our laboratory was not  noted early on because even in the early stages of protocol development slides were never left longer than overnight in the lysis buffer.  It should also be noted that,  after personal communication with Dr. NP Singh (1994), several changes were made to the composition of the lysis buffer that may have decreased the amount of time slides could remain immersed without any effect.  These changes involved the  removal of dimethyl sulfoxide (DMSO) from the lysis solution and the addition of Triton X-100. Another seven samples were lost toward the end of the study because of another assumption of stability that was proved false in our laboratory. demonstrated to the author that, from  It had been  previous experimental verification,  the  technique of alcohol drying would allow the slides to be preserved for at least six months (Dr. NP Singh, personal communication).  Normally, the slides were scored  within one week of preparation; for these seven samples, however, it was more than two weeks before the slides were looked al. visible cells or DNA on them.  Al this time, the slides no longer had any  Some of the slides from the same sampling days were  scored two days after they were prepared and were normal, indicating thai something happened to the cells on the slides in ihe following weeks.  It could be  possible that, since alcohol drying fixes the DNA to the microscope slide, the DNA loosened and was washed off when dye was added to the slide.  While  this may  incidents that in other  obvious in hindsight, it can  i f a protocol developed for use  laboratories  experimental  seem  upon w h i c h  outcome  data  d e r i v e d from  V.3  Future  detailed  the  changes  it was  by  these  be c o n c l u d e d from  is appreciably different  based,  the  effect  o f different  other  laboratories  should  these  from  that  steps on  be  verified  the with  new p r o t o c o l .  to  the  experimental  protocol  It has been suggested  by Sardas el al (Sardas, W a l k e r , A l k o y l ,  & Karakaya,  Dec.)  that  the  of Ihe  assay  p r o t o c o l may be necessary  longer  T h i s is l i k e l y  used  times  for  u n w i n d i n g and  electrophoresis  steps  i f the detection of l o w e r levels of damage  for agents having a subtle effect  on D N A damage,  1995  comet is desired.  and may have been a  beneficial  addition to the protocol for a study o f background or baseline l e v e l s o f D N A  damage.  It w o u l d  also have been  each slide, w h i c h  would  V.4  between  Correlation When  allow  beneficial  to score a greater  for a more v a l i d  dale  a l l available data  o f sample from  and  this study  estimate  mean  interesting, assay honing the  because  itself. the  total  technique  measured  taken from Both  the  assignation of a sample  The correlation could  nature to the  over  lime,  decreased  image  to the  number  the  a c c o r d i n g l y , or  the  January  25 to A p r i l  This  is in no  introduction o f sample  mean.  sample number,  two factors.  be explained in two ways: and  true  length  way  the  number,  as  observation related  to  is  the  experimenter  was  variability  into  technical  date o f s a m p l i n g , indicated some sort o f seasonal  being  effect,  related  by  as samples  were  6.  explanations may have  i n d i v i d u a l s started correlation  the  of the  is compared  in figure 5, there is a large correlation between  number o f cells on  some  validity,  but  the  first is verifiable.  Some  to give samples later on in the study, and there is less of a  between  mean  and  sample  number  for  these  participants  than  those  who  71  gave samples in the first few weeks.  In fact, the first three days of sampling resulted  in average image lengths so much greater than the days that followed that it was decided to remove these samples from analysis.  When these data points are removed,  there is less of a correlation between mean and sample number overall.  V.5  Analysis of Two  the  technical variability  groups of information could potentially allow for an analysis of the  technical variability in this study:  comparison of replicate slides and analysis of  MOLT-4 variability. Each time that a blood sample was taken, two replicate slides were prepared and analyzed.  A comparison of these replicates gives insight into the degree of technical  variability  that  results  from replicate-to-replicate  variation.  Theoretically, if all  steps of the experimental protocol are performed identically, there should be no significant  difference  between the replicates.  The average  coefficient  of variation  calculations for the blood sample replicates was 16.30%, and the MOLT-4 same-day slides had an average CV of 15.72%, deviating significantly form the theoretical zero percent to suggest that some amount of technical variability at the replicate-toreplicate level exists in this study. Because both slides in any two replicate sets were treated to the same conditions throughout preparation, it is difficult to pinpoint the source of this observed variation.  The most likely candidate for an introduction of variation at this  level is during scoring, when errors in judgment on the part of the scorer and an inadvertent non-random sample of the total cells on a slide can occur. been desirable to rescore some slides in order to determine whether scorer effects on the test metrics occurred; unfortunately,  It would have significant  as mentioned earlier in  the discussion, the slides were not stable enough to enable rescoring.  72 It is interesting to note m u c h greater for  this  than  regarding This  u s i n g the  MOLT-4  image  the  explanations  from  cell  as to  and the  stable  amount  of  biological  lymphocytes (data  not  more  subtle  under  There  sample replicates is  is no o b v i o u s  that only  cell  could  the  not  mean  study  time course  was  of  variation.  a comfortable  degree  of  confidence  length.  exists  It  cannot damaging  sources  between  There  not occur:  extremely study  the  of  determined.  relationship  image  of the  provide information sources  is dramatically different  the  than  l o w , or the  but  instead  are  the  subject  three  response  of  the  that o f l y m p h o c y t e s , cell  had  line d i d  not  a relatively large  itself.  c o n d i t i o n s where  less  reason  day-to-day  be  relationship does  variability  also  line, however, because  a slight  MOLT-4  can  o f the M O L T - 4 cells was very s i m i l a r to that o f the  shown). and  itself  to  analyzed to  the M O L T - 4  i n this  over the  T h e response  slides.  variability  respect be  C o m e t assay  technical v a r i a b i l i t y  remain  not  why a greater  cells in the  line  with  line  indicates  length  cell  variability,  obtained  12  same-day  blood  exist.  of the  within  Figure  MOLT-4  MOLT-4  o f v a r i a t i o n could  data  variability  the  to  technical  source  mean  that for the  difference  Analysis  that the range o f C V s for the  be  a large  amount  determined  exposures  of D N A damage  without  will  quantitative  produce  similar  sample  was  induced  evidence  responses  whether  in both  cell  types. T h e stability o f the cell confidence  in  coefficient  o f v a r i a t i o n o f 2 7 . 6 3 % calculated  MOLT-4 amount in the  this  standard  as  line over lime has the greatest effect an  slides suggests that the cell o f D N A damage  measured.  study, p r o v i d i n g samples  accurate  measurement from  line is not If one  of  ihe mean  technical image  variability.  length  The  for a l l  stable over time, but varied in the  looks at the cell  over an extended  on our lack o f  line as another  participant  time period, the value o f 2 7 . 6 3 % is  73 quite  close to the  that the  cell  biological  line varies  and  components the  Visual  proportions  of  of the  Dec),  pesticides  Hemminki,  & Lambert,  the  in  this  total  1995 Jul.),  study,  two  amount  and  d i d , e x h i b i t i n g both  be  could  (Sardas,  1995  radiation  not  sources:  Environmental  the be  sources  Walker, Alkoyl, Aug.),  Oct.; V o d i c k a , (Plappert,  increase  in the  levels o f D N A strand  1995 N o v . ) as w e l l breakage  variability  styrene  1995  (Bastlova,  Bastlova, Vodickova,  Raddatz,  peripheral  and  genetic  & Karakaya,  Roth,  types  of  or  of  varying  proportions  between  biological  differences  Kastner, & Magnussen,  assess  calculated.  1992).  ( H o l z , Jorres,  to  exact  1995 M a y ; V i j a y a l a x m i , T i c e , & Strauss,  include  the  used  1995 M a y ; T i c e & Strauss, could  on  o f both  although  B a r a l e , & M a r c o s , 1995  & Lambert,  cannot  suggesting  variability  variability  have  smoke  study  information  information  that some  differences.  to cigarette  detailed  of 24.40%,  study.  indicates  up  days  i n the  intra-individual  detected  (Ribas, Frenzilli,  V o d i c k a , Peterkova,  and  more  this  this  i n d i v i d u a l s can  environmental  include exposures  line,  in  between  participants  Without  data  was  subjects,  the  cell  make  between  and  the  inter-  which  could  Peterkova,  the  variability  Variability  as  variability  observation  o f each  differences  for  technical  individual  time  variability.  of v a r i a b i l i t y  Assessment  within  C V for within  over  technical  day-to-day  V.6  average  cell  & Fliedner, Genetic in  as syndromes  the  which  blood cause an  (Cleaver, 1968; L o h m a n , et a l . , 1992;  T h o m p s o n , et a l . , 1991). None either  of  the  information  o f these two sources,  Similarity explain  in these  There account  some  could  unknown  gained  from  the  be associated  genetic  or  questionnaires,  with  unqueried  an increase  characterizing  in D N A damage.  environmental  factor  could  relationships.  is a also  for in this  a relatively large  study.  Variability  amount  within  one  of w i t h i n individual  individual  variability  is d i f f i c u l t  to  to  attribute  to  74 a certain the  environmental  case here.  of the  Cyclical,  menstrual and  factor  diet  continuous  v i t a m i n intake  &  Speit, 1995 A p r . ) ,  damage  (Tucker, et a l . , 1987).  could  be  V.7  attributed  the  variance  the  relative 6-11  the  also  from  attribution  and  the  i f exposure  of  effects  can also have  percentage o f images Looking  that  from  clear of the  the  metrics  were  presentation  differences the  stages changes  in the level o f D N A  an effect  factor  from  on levels o f D N A  the  in one  used  in this  of the  data  in the  different  different  questionnaire  person  over  analysis  test  questionnaire  metrics  for  an  to  on the  mean  image  over  length  a large  value  different  amount  of  The  time.  was  changes  not  detect  (ie.  the  mean  useful  for the or  in the  to  and  variation  levels of  metrics  a l l o w e d an  be  dependent  on  F o r example,  to a small number o f cells,  +/-  interesting  for  levels of D N A damage.  would  this  data  subject within  of  being studied.  o f damage  may  metrics  different  type  both  different  exposure  tissue  each  coefficient  detect  o f the  environmental  from  range o f values  metrics.  H o w e v e r , none  o f that exposure  the  as  is  metrics metrics  a graphical  each  at several  increase  no  such  as  Neiss, Grunert-Fuchs, Poch,  with changes  to c h e m i c a l A causes a large amount  c a l c u l a t i n g the  potentially  lest  present,  taken,  et a l . , 1993) and  Hartmann,  variability,  different  same samples.  choice  biological  always  are  usefulness.  depict  show  o f factors  The  are  o f samples  variation in D N A damage  different  provide  i n d i v i d u a l s for  calculations  could.  with  that several  reason  test metric,  only  individual  The  between  the  between  of  Figures each  the  a l . , 1994;  Seasonal differences  Comparison  determine  which  could possibly be associated  in one person.  data  a s m a l l number  effects  ( G r e e n , et  damage  with  only  c y c l e ( D ' S o u z a , et a l . , 1988; Joseph-Lerner,  in  As  when  effect, two  from  while  standard any  the deviations)  g i v e n study  information  obtained.  could  75  V.8  W h a t do the  T h e data differences observed to  results say about study  collected for a l l i n d i v i d u a l s  can be detected intra-individual  The protocol  a  variability  o f the  V.9  for  evidence  participants  over  particularly  size c a l c u l a t i o n s indicate that, a relatively large  in order to detect  (Betti, et a l . , 1995) detected  suitable  gives  study,  C o m e t assay,  w o u l d be needed  individuals,  from  cross-sectional  sample  in this study  suggesting agents  indicates that, over time,  in the levels o f D N A damage  obtain m u l t i p l e samples  performing  design?  that  causing  that  it  a period when for  V.9.1  more  appropriate  o f time,  rather  than  women.  a cross-sectional  number  o f participants  study (70  using per  than  or  subtle  group)  Betti et al  15% for s m o k i n g in a group o f 200  this p r o t o c o l for detecting small  this  D N A damage  increases  in  may  response  in field  not  be  levels.  studies o f  exposures  Development o f the C o m e t assay protocol The  results  of  repetitive v a l i d a t i o n After interest  be  assaying  Future Considerations for the use o f the Comet assay occupational  may  This  a 15% difference in mean image length.  a smaller effect  only  in the same person.  this  of the  experimental  test p r o t o c o l to  a p p l i c a t i o n o f the  i n order  to become  process  initial  familiar  underline  be used  the  before  importance  any  experimental p r o t o c o l to with  the  technique,  a test  field the  samples  cell  series  of a are  taken.  type o f using  an  agent  76 known to produce an observable response in the assay should be performed.  For the  comet assay, the cells could be exposed to different concentrations of hydrogen peroxide (Holz, et al., 1995 Nov.) and the response at these each level recorded.  This  test should be replicated until it is clear that the responses observed are consistent and reproducible.  A maximum acceptable amount of error should be decided upon  before initiating the validation series.  When any subsequent  change to the  experimental protocol is introduced, this same experiment should be performed in order to assess the effect of that change on the response measured. should be introduced independently so that any noticeable response observed can be attributed to a certain factor.  difference  All changes in the  Only after such validation is  carried out should a change be incorporated into the experimental protocol. The attempted  introduction of refinements  or changes  to the experimental  protocol continued until about one month prior to the collection of the first blood samples from the study participants. 1. )  These changes included:  the use of immuno-magnetic beads to separate sub-populations of lymphocytes.  2. )  the use of proteinase K to digest cellular proteins.  3. )  the addition of 8-hydroxyquinoline and dimethyl sulfoxide to the electrophoresis  buffer.  4. )  the addition of triton X-100 to the lysis buffer.  5. )  alcohol drying of the slides before staining.  6. )  the use of the YOYO-1 fluorescent dye instead of ethidium bromide to stain the cells.  7. )  measurement of the image length of the cells observed rather than a computer-aided  image  analysis.  The first six of these changes had been incorporated successfully  by other  laboratories, and the effects on the response of cells measured by the assay had been  77 assessed  i n these laboratories  Andrews,  1993).  Several o f the  protocol on the is  difficult  however,  assumption  to  as  and found  draw  the  to be n e g l i g i b l e ( S i n g h , et a l . , 1994; T i c e  steps or changes  that no effect  would  a c o n c l u s i o n regarding  steps for  a repetitive  done,  of the the  many  study.  final  cellular  o f the  Also,  It w o u l d incorporated  may  be  into  protocol have  a protocol,  experimental  V.9.2  listed above  i f they  ensure  that  added  perceived had  the  been o f the  positive  as w e l l .  this  were  can  It  assumption, not  undertaken  however, that, had to the  that cannot negative  changes effects  be found i n  effects  validated  this  information base  on  properly. that  are  exceed  the  negative.  of l i m e available for c o m p l e t i o n o f the  which  authors'  be allotted lo v a l i d a t i o n o f  study,  the  protocol.  U s e o f the M O L T - 4 cell line as an internal c o n l r o l T h e use o f the M O L T - 4  provide  information  intended. inter-  instead  of  of  protocol  to assume,  rigorous track  amount  proportion of that time  changes  added  and  have  into the  in our laboratory  appropriateness  It is safe  because  to keep  One should also consider the and the  used,  been  expedient  the  lost could  potentially useful  experimental response,  samples  be seen  incorporated  v a l i d a t i o n o f the  at any stage o f the protocol development. been  were  &  and  attributable  The  on  between  line as an internal control d i d not  sample,  day  calculations o f coefficient  intra-day to  cell  variability,  technical  but  rather  than  the  on  day-to-day  of a single b l o o d sample, testing  was performed.  should  therefore  have  technical thawed Each  technical  o f variation indicate  proportion  biological  because o f the variability o f the M O L T - 4 cell information  lo day  of  this  variability  may  and treated as the  have  the  same  a large  value  average  be  amount  was  may  of  both  be  elucidated  A better source of to  use  cells were  from  as  amount  which  cannot  been  sample  aliquot of cells originated  approximately  variability,  line itself over time.  variability  effectively  the  frozen every  day  same sample  o f damage.  aliquots  It  that and  may  be  78 appropriate to use a method other than the MOLT-4 cell line to determine the amount of  day-to-day  V.9.3  technical variability.  Development and assessment of the questionnaire The questionnaire used in this study could have been improved in several  ways.  Similar to the testing of the protocol for the comet assay, the questionnaire  should have been validated in a structured manner before it was used on the actual study participants.  This would ensure that the questions asked were clear to both the  person writing them and the individuals answering them.  It would also allow for the  fine-tuning of questions so that the data would be more easily analyzed when the sampling was completed.  It is important to have a clear idea of why you are asking  the questions and how you are going to use and record or code the data before the questionnaire  is  used.  It may also have been beneficial to ask additional questions that were more specific to the unique aspects of this study.  For example, more specific questions on  the menstrual cycle could have been incorporated in the questionnaire  so that more  detailed information could have been used to assess the effects of variations in cycle on levels of DNA damage.  A questionnaire for providing such detailed menstrual  cycle information was produced and given to the author University of British Columbia (personal  by Dr. Jerilyn Prior, of the  communications).  However, because the  participants had to be trained over several months time to be able to properly answer the questions, it was decided that these questions could not be incorporated into the study at such a late date.  79 V.9.4  Recruitment of subjects It was expected that there would be a higher response rale for this study.  The  number of participants could have been increased if a greater number of potential subjects could have been approached in person, rather than rely on the information letters distributed on the wards.  Recruitment of nurses from other hospital sites  could have been attempted as well.  V.9.5  Statistical analysis of the data obtained It is important to have access to a strong background in slatistics in order to  complete the complicated statistical analysis required for this data.  The types of  analyses which may have to be performed should be determined or at least estimated before the collection  of samples  commences.  V.9.6  Summary  1. )  A repetitive validation of the assay protocol should be performed on both the original  procedure and any changes introduced before  any field  samples  are  taken. 2. )  Rigorous track of the changes thai are incorporated into a protocol should be kept, and insurance obtained that the positive effects of inclusion in the protocol  3. )  exceed the  negative.  Consider the amount of time available for completion of the study, and the proportion of that time which can be allotted to validation of the experimental protocol.  4. )  Consider another method other than a cell line to determine the amount of day-to-day  5. )  technical  variability.  Any questionnaire used should be validated before it is given to the study participants.  6. )  O b t a i n more  detailed  information  with  respect  to  menstrual  cycle  on  the  questionnaire. 7. )  A p p r o a c h more study  8. )  Obtain  potential  participants  in  person  to  increase  the  number  of  subjects. experience  samples.  in  statistical  manipulations  and  analysis  before  collecting  81  VI  1.  Conclusions  An experimental  with confidence incorporated  2.  protocol  should undergo repetitive  validation and be handled  before that protocol is applied to a study population.  into  Significant  the  protocol  amounts  should be validated  of technical  Any changes  independently.  and biological  variability were observed, but  the proportion of each in the overall or total variability could not be determined. The amount of biological variation appeared to exceed the technical variation.  3.  None of the variability observed was attributable with any degree of  confidence  4.  to any of the questionnaire data.  A larger number of cells should be scored for each sample to increase the  validity of the test  5.  measurements.  The MOLT-4 cell line appeared lo be unstable over lime, expressing some levels  of biological variability.  Because the components  accurately assessed with the data available,  of variability could not be  this cell line should not be used as an  internal standard for this assay until more information is  collected.  82 6.  T h e results  longitudinal  study  particularly  when  7.  sample  The  of this study design, the  suggest that it may  rather  population  size  necessary  than of  for  cross-sectional,  interest  with an alpha o f 0.05  individuals  i f the  length percent  group  is desired,  and  i n image  length  detection  approximately is to  be  is  statistical  c o m p a r i n g two groups per  be necessary  of an 20  and  when  comprised  increase  the  a  Comet  assay,  women.  in  a cross-sectional  a power o f 0.80 o f fifteen  i n d i v i d u a l s per  delected.  using  of  significance  to employ  group  is approximately percent  i f an  in  increase  study 70  image of  thirty  83  VII  References  (1986). 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E n v i r o n m e n t a l Health P e r s p e c t i v e s . 9 8 , 167-178.  88  Appendix Information  sheet  and  letter  A  o f i n t r o d u c t i o n p r o v i d e d for purpose o f recruitment  the  nursing  units  for  the  89  December  16, 1994  Nurses V H H S C , U B C - s i t e Hospital  Re: R e q u e s t for p a r t i c i p a n t s for a research background levels o f D N A strand breakage in the  study i n v o l v i n g white b l o o d cells  the assessment of of female nurses.  The purpose o f this letter is to ask for volunteers to give b l o o d samples for a research project that w i l l contribute to the study o f o c c u p a t i o n a l exposures to nurses. I am a graduate student in the O c c u p a t i o n a l H y g i e n e P r o g r a m m e al the U B C ; the p r i m a r y focus o f this f i e l d is the r e c o g n i t i o n , e v a l u a t i o n , and c o n t r o l o f hazardous e x p o s u r e s i n the w o r k p l a c e . A d e s c r i p t i o n o f the thesis project that 1 am u n d e r t a k i n g i n order to c o m p l e t e the requirements for m y degree is p r o v i d e d on the attached page. A sheet w i l l be p r o v i d e d in y o u r c o m m u n i c a t i o n s book so that y o u can leave y o u r name and a contact number i f you wish to participate in this study or w o u l d l i k e more i n f o r m a t i o n . Y o u s h o u l d also feel free to contact K a r a l y n n E l l at 822-9573 d u r i n g the day i f y o u have any questions or w o u l d l i k e more details about the research that I am doing. Thank y o u for taking the time to read this i n f o r m a t i o n and c o n s i d e r i n g my request. Sincerely,  Karalynn  Ell  90  F o r my thesis, I w i l l be c o n d u c t i n g a study o f b a s e l i n e v a l u e s for genetic markers a m o n g female nurses w h o have not been exposed to k n o w n D N A d a m a g i n g agents. T h e purpose o f this study is lo obtain information on the levels o f D N A strand breakage caused by n o r m a l a c t i v i t y and the v a r i a b i l i t y between different i n d i v i d u a l s and w i t h i n an i n d i v i d u a l over time. Breaks in D N A o c c u r in healthy i n d i v i d u a l s and a n o r m a l b a c k g r o u n d l e v e l is not i n d i c a t i v e o f potential problems. The information obtained in this study w i l l be used to plan future studies o f o c c u p a t i o n a l exposures in nurses (for e x a m p l e , a study of nurses exposed to antineoplastic drugs). Y o u r p a r t i c i p a t i o n in this study w i l l be beneficial in many w a y s . T h i s study w i l l draw attention to the n u r s i n g profession and its potential hazards. It w i l l also increase k n o w l e d g e r e g a r d i n g w o m e n and n o r m a l l e v e l s o f D N A strand breakage, as research on w o m e n is currently l a c k i n g in the literature. A d d i t i o n a l l y , it is not often k n o w n for even the more e s t a b l i s h e d b i o m o n i t o r i n g tests what l e v e l s o f v a r i a b i l i t y exist w i t h i n a given person over the course o f l i m e . One o f the unique aspects o f this study is that it asks the participants to contribute six blood samples o v e r a period o f f o u r m o n t h s , so that this v a r i a b i l i t y w i t h i n one person can be assessed. This i n f o r m a t i o n i n itself is a significant c o n t r i b u t i o n to research in this f i e l d . Because we are looking for b a c k g r o u n d levels of D N A breakage, some c i r c u m s t a n c e s , such as p r e v i o u s e x p o s u r e s to k n o w n d a m a g i n g agents or elevated h o r m o n e l e v e l s , can create problems with the analysis o f results. O n this basis, we have d e c i d e d that it is necessary to try and s i m p l i f y our a n a l y s i s by l i m i t i n g our study to participants who do not belong in the f o l l o w i n g categories. If you have ever received chemotherapy or r a d i o t h e r a p y , are c u r r e n t l y pregnant or b r e a s t f e e d i n g , or have H I V or H e p B infection we unfortunately must e x c l u d e you from our study. In addition, if your occupation within the last five years involved work with a n t i n e o p l a s t i c drugs (by m i x i n g , preparation or a d m i n i s t r a t i o n a c t i v i t i e s ) , X - r a y s (of other people, n o t y o u r s e l f ) , ethylene o x i d e , or anesthetic gases (again, used on other people), you w o u l d also have to be excluded. P a r t i c i p a t i o n w i l l require s i x b l o o d samples g i v e n at random dates o v e r a three month period and c o m p l e t i o n of a questionnaire. The blood samples w o u l d be g i v e n at the l a b o r a t o r y i n the U B C - s i t e h o s p i t a l on the p a r t i c i p a n t s o w n t i m e , and the q u e s t i o n n a i r e s w i l l be p r o v i d e d as a package, c o m p l e t e d at the c o n v e n i e n c e o f the p a r t i c i p a n t , and returned to me v i a campus m a i l . T h e entire process s h o u l d take 30 minutes o f y o u r time per blood sample g i v e n .  Appendix B Letter  of consent  to  participate  in this  study  92  Consent Determination  of  Form  baseline values of DNA strand population of female nurses  breakage  in  a  B A C K G R O U N D and PURPOSE Dr PJE Quintana, an assistant professor with the Occupational Hygiene Programme, and a graduate student, Ms. Karalynn Ell, will be conducting a study at the University Hospital-UBC site of baseline values for genetic markers among female nurses who have not been exposed to known DNA damaging agents. The purpose of this study is to obtain information on the levels of DNA strand breaks in relation to the menstrual cycle and normal activity, and the variability between different individuals and within an individual over time. Breaks in DNA occur in healthy individuals and a normal background level is not indicative of potential problems. The information obtained in this study will be used to plan future studies of occupational exposures in nurses (for example, a study of nurses exposed to antineoplastic drugs). Because we are looking for background levels of DNA breakage, some circumstances, such as previous exposures to known damaging agents or elevated hormone levels, can create problems with the analysis of results. On this basis, we have decided that it is necessary to try and simplify our analysis by limiting our study to participants who do not belong in the following categories. If you have ever received chemotherapy or radiotherapy, are currently pregnant or breastfeeding, or have HIV or HepB infection we unfortunately must exclude you from our study. In addition, if your occupation within the last five years involved work with antineoplastic drugs (by mixing, preparation or administration activities), X-rays (of other people, not yourself), ethylene oxide, or anesthetic gases (again, used on other people), you would also have to be excluded.  This study will measure DNA strand breakage in lymphocytes from a blood sample, using the single cell gel electrophoresis or "Comet" assay, a relatively new technique for measuring levels of single stranded DNA breaks, as the assessment method. The comet assay has the potential to be a very powerful measurement tool, but little work has been done with this assay on human populations, and there is limited information on the variability that exists among normal, healthy individuals.  93 PARTICIPATION Each study participant will donate six venous blood samples at random dates over a period of roughly three months. The blood samples will be quite small (5 mL) and taken from the arm by a registered nurse. This procedure may cause some discomfort, and slight bruising. On rare occasions infection may occur. The participant will also be required to answer some questions about their diet, health, and work history. Each blood sample will take only a few minutes, and the questionnaire less than ten minutes.  CONFIDENTIALITY All information gathered about an individual will be kept confidential. Anonymity of individuals is guaranteed in any publication. Names and other identifying information will be kept in a secure place, separate from the data. Medical information, identified by code known only to the researchers, may be released to a physician for interpretation. CONTACTS Dr. PJE Quintana and Karalynn Ell may be contacted al any time at 822-9595 if you have questions or concerns regarding your participation in the study. If you have any questions or concerns about your treatment and rights as a research subject, you may feel free to coniaci Dr. RD Spratley, Director, Office of Research Services, at 822-8595.  YOUR RIGHTS as a SUBJECT You may decline to participate in the study, and after signing this form you remain completely free to withdraw from the study at any time without any adverse effect. You will be informed of the overall or group results of this study; there will be no indication of individual results, conforming to the confidentiality agreement above. It must be emphasized that these tests are experimental and their predictive value, if any, unknown at this time.  Statement by subject: I acknowledge receipt of a copy of this consent form. The investigators have explained its contents to my satisfaction, and 1 understand that I may withdraw from the study whenever 1 wish. 1 hereby consent to participate:  Signature Date  _  Name (Please Print) Witness  .  94  Appendix  C  Questionnaires  95  o"  >— ft  o  s» co  ^  co  ^  5'  O  sr  2 Crq o o. °  sr  o 2 s; si. p o A" co CO  W  T3  CO  00  CP  r-r- <  o o c S oo  ^ ->  o  O  oCD  op  CP  o  sr  a.  rr  CP  -a P >-i P  i—.  CP  o 3  sr  sr c o  C  — t p  -I  TJ O  -1 "2  CO —  oo  n os P. 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S 3 C o=  05  05  3*" CD  -l  05  CD  ^<  3"  3  o  3 O  VO  5'  CD  VO  05  oo  9. <  O  c  < 05  VO  o o  05  o  3  3  oo —I  —t  Z Z  00  3  o' o  Appendix D Results of  Blood  Sampling  Mode* % over % over % over Mean* Median* Subject Sample Date of Group 72 um 134 um 194 um in um in jj.m in jj.m # Sample ID 7 19 53 50 76 88.46 4 8-Feb 1 566 5 2 13 20 26 44.62 21-Feb 9 2 566 4 16 22 22 28 58.26 7-Mar , 16 3 566 0 0 6 22 24 32.6 . 21 22-Mar 5 566 2 2 8 22 26 37.44 25 27-Mar 6 566 15 7 30 46 48 74.78 8 10-Feb 3 574 3< 2 4 8 34 43.9 28-Feb 15 4 574 4 6 _ 13 """"22 "' 48.52 27 31-Mar 6 574 1 64 52 _ 10 140 133.6 2 „25™laj]i_ 1 i ° l „ 655 2 2 5 ' "22 26 55.08 "l8 12 42 30 58 88.08 22 23 23-Mar 5 655 42 16 66 184 108 124.08 26 30-Mar 6 655 36 19 68 104 120.24 99 3 7-Feb 1 681 13 0 22 29 37 61.52 20 8-Mar 2 681 2 2 6 26 36 43.76 15-Mar 99 3 681 3 22 43 30 65 86.16 7 10-Feb 2 703 18 31 48 66 70 111.14 14 24-Feb 3 703 0 9 24 24 41 57.26 20 8-Mar_ 4 703 24™" 19 10 2 36 58.52 ' 22-Mar ' 22 5 0 10 16 28 42 56.24 29 21 32 5 2 _ 80 7 10-Feb 1 711 11™ 48 26 *20 100.68 14 """52"" 24-Feb 2 711 44 17 5 39 42 72.32 15 28-Feb 3 711 7 0 13 22 26 17 41.6 7-Mar 4 711 4 12 14 22 22 45.46 22 22-Mar 5 711 6 14 20 22 35 58.52 28 31-Mar 6 711 48™" 41 14 5 60 79.12"" 10-Feb 6 2 715 3 18 9 32 44 60.34 23-Feb 11 3 715 ,„™.™.. Q 5 45.78"' 18 '"""2T™ ™8~-Mar 4 715 2 4 4 22 25 38.84 15-Mar 99 5 715 5 8 12 24 28 49.28 21 22-Mar 6 715 11 44 164 69 124 120.28 25-Jan 1 1 728 4 38 55 172 87 105.16 5 8-Feb 2 728 5 20 9 26 40 55.42 12 23-Feb 728 3 8 54 _ _ 2 0 _ 28 55 81.32 26 30-Mar 5 728 8 0 0 22 30 38.6 29 6 728 „„„.... 84'"" 81" ~ 137 _ 132.16 1 25-Jan 812 "~ 1 ™™™5.'86™ 4'i"'""' ~ 7 0™"™ 30"" 3 812 YT-Feb™ 0 8 18 24 28 47.6 8-Mar 19 4 2 14 23 22 24 52.96 98 16-Mar 5 812 6 26 30 24 42 73.96 27 31-Mar 6 812 0 10 16 100 34 52.64 8 10-Feb 1 851 2 13 37 28 60 73.7 12 23-Feb 2 851 2 10 26 24 39 58.32 24 23-Mar 4 851 6 39 89 80 125.54 119 4 8-Feb 3 906 5 _ J 3 0 _ 22 22 56 21-Feb 4 906 ™~2 24 , 1 8„ .... ^ ' 52.64"" 906 6 " 48 156 186" 144.34 l 1 " 25-Jan 938 9 25 90 92 104.76 3 7-Feb 66 „ 3 938 22™ 42 30 8 89.32 10 55 21-Feb 4 ' 938 24 " ~~18 6 66 98 29 16-Mar 5 938 22 12 30 24 38 75.48 25 27-Mar 6 938 8 15 34 30 54 75.02 6 10-Feb 942 2 7 15 24 30 42 74.12 11 23-Feb 942 3 5 12 23 24_ 30 62.14 16 7-Mar 4 942 6 4 12 " '" 29 24 " 46.96 24 • 23-Mar 6 942  L„  ""To"  m  n  To  Tl™"  r  * These values refer to the mean, median, and mode image  length  IT ™  Appendix Questionnaire  E Resu  Subject  566 566 566 566 574 574 655 655 655 681 681 703 703 703 703 703 711 711 711 711 711 711 715 715 715 715 728 728 728 728 812 812 812 812 851 851 851"" 906 906 938 938 938 938 942 942 942  Sample number  Age  2 3 5 6 4 6  42  5 6 2 3 2 3 4 5 6 1 2 3 4 5 6 3 4 6 5 2 3 5 6 3 4 6 5 1 2 4 4 6 3 4 6 5 2 3 4  Last virus Ever been Vaccination Vaccination Cold or in the last Nurse? virus when more or less diagnosed in the last than one with six months? two years? sample month ago? cancer? taken?  1  2 2 2 2 0 0  42 42 32 32 '""26"' 26 0 26 0 57 1 57 ' 1 47 47 1 47 1 47 1 47 1 27 1 27 1 27 1 27 1 27 1 27 1 43 0 43 0 0 43 43 0 31 1 31 1 31 1 31 1 30 0 30 0 30" " 0 30 0 24 0 24 0 24 o 46 .0 46 0 31™ 31 1 0 31 31 1 23 0 23 23 0 ™  ™  „  ™  0  5  *6'""  0 0 0 0  0 0 0 0  0 0 0 0 0 0 0 0 0 1 0 1 0 0 1 0 0 0 0 1 0 0 0 0 0  "6""  0 0 1 1 0 0 0 0 0 "i"" 1 1 1 1  0 ""o 0 0 0 0  0 0 0 0 0  6""~  ~"*""T  0 0 0 0 1 1 1 1 1 b""'""" 0 0 0 0 o" 1 1 1 1 0 cf 0 0 0 0  0 o 0 0 1 1  0 0 1 1 „  0 0 1 1 """™"'o"" 0 0 0 0  0 0 0 0 o 0 1 0 1 0 1 0 1 " 1 ™ "1 o 1 1 1 1 1 1 1 1 1 1 1 . 1 o™ ~~ ~b~~ ~""""~0 ~~ 6"' "d 0 0 0 0 0 0 0 0 0 ~"0 0 ""6"'"" ~0 "b" T 1 0 0 0 0 0 0 o0 0 0 0 0 0 0 0 o"" 0~'"™~ o 0 0 0 0 1 1 0 0 0 0 . o" " " " " " " o " """""""cf o""~" 0 0 0 0 1 1 "6" o ""b 0 6"""" 0 ~b 0 "~ T"" 0 0 0 1 1 '6""" '""'"""7 ""' ~'"i 0 0 0 0 0 1 1 „ .  .  0  „  „  Ill  Days since the Regular Any X-rays Number of Ever used oral contraceptives menstrual start of the last X-rays in in the last menstrual cycles (28 12 months the last ten cycle days ± 11 years  Subject  Sample number  Vitamin C usage  Vitamin E usage  566  2  0  0  1  5  0  1  5  566  3  0  0  1  5  0  1  19  566  5  0  0  1  5  0  1  7  1  12  1  0  566  6  0  0  1  5  0  574  4  0  1  6  1  574  6  0  0 0™"™"  655  4  0  0  ™T  ~~6  0  4  1  1  1  ~j  1  1  25  15  0  0  n/a  655  5  0  0  0  4  655  6  0  0  0  ~4  1  ™""™-1 3  "~~  TaT™  681  2  0  0  681  3  0  0  15  0"  0 '  n/a  0  0  1  12  0  1  32  3  0  0  1  12  0  1  19  4  0  0  1  f„.„  0  1  3  703  5  0  0  1  12  0  1  17  703  6  0  0  1  "" 12  "b  711  1  2  0  1  5  9  0  8  711  2  2  0  1  5  9  0  22  711  3  2  0  1  5  9  ~~~"~o  711  4  2  0  1  5  0  711  5  2  9 9" 9  0  57  0  1  9  703 703 703  711 ' 715  2  6 3  2 2  o™ 0 1  *""™~  ™" T™" 1 0  5 0  "  26 33 „  „ „ „  0  715  4  2  1  0  0  0  1  715  6  2  1  0  0  !  o"  o '  0 0"™""'  "1  12 -"5""  1  0  5  0  1  24  0  5  0  1  39  0  1  715 728 728  2 3  2 2  1  1  728  5  2  1  0  5  728  6  2  1  0  5  0  0  1  0 0™"  0  0  1  0  0  9  0  0  1  0  0  4  1  0  0  812 812 812  3 4 6  1 1  1 ""0""""  29 29  812  5  1  0  0  851  1  0  0  1  30  1  0  19  0  0  1  30  1  1  4  0  0  1  30  1  1  5  4  1  1  14  851 851  2 4  906  4  2  0  0  906  6  2  0  0  4  1  1  1  1  4  0  1  1  1  1 1  938 938  3 4  1  ™  o~~~~™  2  ~——"4""—  938  6  1  1  938  5  1  1  1  4  0  1  15  0  0  942  2  0  0  1  942  3  0  0  1  15  0  0  0  0  1  15  0  0  0  0  1  -15  6  942 942  4 6  12  25 175 8 "24"  112  Subiect  SamDle Current number smoker?  566  2  1  566  3  1"""""  566  5  1  Exercised vigorously 6 to 48 hours prior to samplinq?  How How Any stressful Servings of much much vegetables event red meat cured per day occurring in diet? meat in prior to diet? samplinq?  0 ™0 0  2.5 „„._„,.  0  '™""6"""~  "2.5  0  Cups of cups of How much regular regular grilled coffee tea per meat in per day day diet?  1  1  "T™  1  1  1  0  2  5.5  2~"~  '5.5 ™  2  5.5  0  2  5.5  0  ™  0  2.5  1  1  0  1  4  2  1  0  0  4  2  1  1  0  0  1  2  0.5  566  6  1  1  574  4  0  574  6  0  655  4  0  1  1  3  1  1  655  5  0  1  0  3  1  1  1  2  0.5  0  3  1  1  1  2  0.5  1  1  655  6  1  0  681  2  0  0  0  1.5  681  3  0  0  1  1.5  1  1  3  4  0  703  2  1  1  0  0  2  0  0  703  3  1  1  1  10 10  0 0  0  2  0  0  703  4  1  1  0  10  0  0  2  0  0  703  5  1  0  1  10  0  0  2  703  6  1  0  1  10  0  0  2  0  0  711  1  0  1  1  7  2  2  1  2  0  711  2  0  0  1  7  2  2  1  2  0  711  3  0  1  1  7  2  2  1  2  0  711  4  0  0  0  7  2  2  1  711  5  0  1  1  7  2  2  1  0  2  „  „  ™0  711  6  0  0  0  7  715  3  0  0  1  6  1  0  2  1  0  0  2  1  0  715 715  4 "6~  0 0  1  6  1  0  6  1  0  0  2.5  2  1  0 Tj™  0  1  2.5  2  1  0  0  0  0  0  0  0  .1'  0  0  0  6  "™  728 728  3 5  728  6  812  3  812 812 812  4 6 5  0  0 0  „„.„„  0  2.5  "  2  0  2.5  0  1  1 '  851  2  1  0  0  1  0  3 3  2  0  0  • 2  1  0  2  1  4  906  4  0  0  906  6  0  0  "6" "  938  "o " ™  0 0 0 0  0 0 0 0  2"'™"  'o  "~'""o"'"""" m  """2  2  -  ~~  „1 _  1  0.5  1  „  1  ™" 0'  2"  0  2  0  0  0  1.5  6"™"  1  0  0  1  0  0  1  1  0  'i  4  1  6  0  0  0  2  1  938  5  0  0  1  2  1  942 ™942  2  0  1  1  5  0  0 0 0 0  3~  o'""  o~"~~""  0  ™'Tf""""  942  4  0  1  1  0  0  1  6  1  0.5  0  2  942  0.5  1  0  ™i """"  „  "'1 " """"0™"" "T"  0  938  0  3  2  2  0  2.5  0.5  "3'""  0  938  0  2.5 2.5'""  2  0  2T5  2 2  T  0  "  T"'~ 2.5  851 851  2~~  1  715 728  ~2  2  0  "0 0  0  ~ "0 " 0  .„„..„.  1 1  1  Appendix Raw  data  114  I Blood (lymphocyte) cell samples Subject ID Sample ID Date of Samplej Group ID  566  566  566  566  566  566  1A  1B  2A  2B  3A  566 3B  5A  8-Feb  8-Feb  21-Feb  21-Feb  7-Mar  7-Mar  22-ME  4  4  9  9  16  16  21  1  12  15  1 0  1 0  1 0  1 0  1 0  13  20  .1 o  1 0  1 1  1 0  10  14  22  10  1 0  1 1  1 0  1 0  14  23  1 0  10  1 1  1 1  10  15  25  1 0  11  1 1  1 1  10  15  25  1 0  1 1  1 1  1 1  10  1 6  26  10  12  1 2  1 1  10  17  26  10  12  12  1 1  10  10  12  12  1 1  1 1  19  '  27  20  29  1 0  12  1 2  1 1  1 1  20  31  10  12  12  1 1  1 1  20  31  10  12  13  1 1  1 1  21  31  10  12  1 4  1 1  1 1  21  32  10  13  1 7  1 1  1 1  22  35  10  13  1 8  1 2  22  36  10  13  20  1 2  23  40  1 1  1 4  21  1 2  23  40  1 1  16  22  1 2  1 1  24  41  1 1  16  22  12  1 1  25  42  1 1  1 7  22  1 2  1 1  25  42  1 1  17  22  12  1 1  25  42  1 1  1 7  23  1 2  1 1  26  43  1 1  17  24  12  1 1  26  44  1 1  19  27  1 2  1 1  26  45  1 1  2 0  27  1 3  1 2  27  47  1 1  22  29  1 3  1 2  27  48  1 1  22  32  13  12  28  50  1 1  23  32  13  12  33  50  1 1  23  33  1 3  12  35  52  1 1  26  42  13  12  35  54  1 1  27  43  13  12  55  12  27  45  13  12  37  56  12  27  49  13  1 2  37  58  1 2  30  56  13  1 2  38  62  1 2  32  68  13  1 2  41  64  12  35  70  1 4  1 2  42  70  1 3  35  71  1 4  1 3  43  71  13  48  73  1 4  13  43  75  13  49  75  1 4  1 3  44  77  13  56  82  1 4  1 4  44  78  13  57  82  1 4  1 5  48  81  1 4  57  83  15  1 7  52  84  14  62  85  15  22  62  85  1 4  64  91  15  22  63  90  15  67  92  1 8  36  76  99  16  74  93  22  36  76  100  1 7  75  105  23  36  83  105  25  82  107  33  50  101  110  35  100  110  35  50  123  110  35  138  125  49  78  37  .  :  1 1 •  1 1 1 1  115  655  566  574  574  574  574  574  655  6A  3A  3B  4A  4B  6A  1B  4A  27-Mar  10-Feb  10-Feb  28-Feb  28-Feb  31-Mar  25-Jan  8-Mar  25  8  8  15  15  27  2  18  1 0  10  10  10  10  10  20  10  10  11  12  1 1  1 1  10  20  10  1 1  1 3  12  1 1  1 1  11  30  10  1 3  1 1  30  10  1 1 1 11  14  13  1 1  14  14  11  13  1 1  33  1 1  15  15  1 2  13  11  33  1 1  11  15  16  12  13  11  33  1 1  11 11  16  16  12  13  11  34  1 1  16  16  12  1 4  11  36  1 1  1 7  16  1 2  1 4  11  36  1 1  11 11 11  17  17  1 2  1 4  11  39  1 1  1 7  18  1 2  1 4  11  44  1 1  18  19  1 2  1 5  1 1  44  1 1  11  19  20  1 3  1 5  1 1  50  1 1  1 2  20  20  1 3  1 5  1 1  53  1 1  12  20  20  1 3  1 5  1 2  55  1 2  12  20  20  1 3  16  1 2  57  1 2  1 2  21  21  1 3  16  1 2  58  12  1 2  21  21  1 3  16  1 2  59  1 2  12  21  22  1 4  16  12  59  1 2  12  23  22  14  16  12  60  12  13  23  23  1 5  17  1 2  62  12  13  23  23  16  17  1 3  63  1 2  13  23  24  16  1 7  13  66  12  13  23  25  16  17  13  68  12  13  23  26  16  1 7  14  70  1 2  14  24  27  17  1 7  1 4  71  1 3  14  27  28  1 7  1 7  1 4  72  13  15  27  29  1 7  18  1 4  73  13  18  14  74  1 3  1  1  1  15  27  30  1 7  16  28  32  1 7  19  15  75  1 3  16  31  32  18  19  1 5  75  15  17  32  34  18  20  18  82  16  17  32  35  19  21  18  82  23  17  33  43  20  21  19  82  29  17  33  50  20  21  19  82  30  19  40  51  20  21  21  83  39  19  46  62  20  22  21  85  40  20  47  62  21  22  23  86  53  20  48  63  21  22  26  87  54  22  58  65  25  25  30  87  57  22  59  72  25  27  30  88  63  27  67  80  28  28  40  90  67  27  69  82  28  30  40  91  67  34  77  82  28  33  55  92  69  34  96  85  32  48  60  99  70  38  98  87  33  55  60  103  82  47  110  105  46  66  85  105  83  47  111  107  105  68  131  107  83  101  112  11 0  130  82  131  11 0  90  116  681  655  655  655  681  681  681  681  4B  5A  6A  1A  1B  2A  2B  3B  8-Mar  23-Mar  30-Mar  7-Feb  7-Feb  8-Mar  8-Mar  15-Mar  1 1 1 1 1 11 1 1 1 1 12  23  26  3  3  20  20  99  12  1 3  1 3  20  1 0  10  1 2  12  1 3  1 5  23  1 1  1 0  1 2  12  16  1 6  25  1 1  1 1  12  13  18  1 7  27  1 1  1 1  12  13  18  1 7  27  1 1  1 1  1 2  14  1 9  20  28  1 1  1 1  12  14  1 9  22  29  1 1  1 1  12  1  14 15  21  22  30  1 1  1 1  1 3  21  23  30  1 1  1 1  1 3  1  1 5 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32 32 33 34 34 35 38 48 50 56 56 73 88 100 143  715 3B 23-Feb 11 1 1 13 13 14 15 15 15 15 16 16 16 16 16 16 17 17 17 17 18 18 18 18 19 19 21 22 22 23 23 24 25 25 25 26 27 27 29 30 34 34 36 38 38 44 57 72 75 81 92 140  715 4A 8-Mar 18 10 10 10 10 1 1 1 1 1 1 1 1 1 1 1 1 12 12 12 12 12 12 12 13 13 13 13 14 14 14 14 15 15 15 15 15 16 16 18 19 22 22 25 26 27 33 34 38 41 43 44 45 45 52 80 91  715 4B 8-Mar 18 10 11 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 12 12 12 12 12 13 13 13 13 13 13 14 14 15 15 16 16 17 17 17 20 21 21 21 22 22 23 24 25 27 31 32 35 44 45 53 60 87 88 90  120  728  715  715  715  728  728  728  728  5A  6A  6B  2A  1A  1B  2B  3A  15-Mar  22-Mar  22-Mar  8-Feb  25-Jan  25-Jan  8-Feb  23-Feb  99  21  21  5  2  1  5  12  10  10  10  1 1  1 2  17  12  12  1 1  10  10  1 3  16  17  1 3  12  1 1  1 1  19  14  1 2  1 1  12  20  1 5  1 3 13  10 10  1 5 16  1 7 20  17  21  21  16  1 1  1 7  22  21  18  1 3  12  1 1  17  23  23  20  1 3  1 1  12  1 1  1 9  23  24  20  1 3  1 1  12  1 1  21 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140  11 0  138  123  938  906  906  938  938  938  938  3B  4A  6A  1A  1B  3A  3B  4B  8-Feb  21-Feb  23-Mar  25-Jan  25-Jan  7-Feb  7-Feb  21-Feb  4  9  23  1  2  3  3  10  32  8  1 1  18  18  26  12  10  33  8  1 1  1 9  23  27  12  1 1  34  8  24  28  13  1 1  25  25  29  13  1 1  12  26  30  32  15  1 1  10  1 2  2 7  31  35  17  1 1  10  12  27  33  35  17  1 1  12  27  36  36  17  12  37  18  1 2  39  38  20  1 4  32  40  39  22  1 5  14  34  43  42  24  15  43  43  24  1 5  906  35 35 38 38.  1 1 12  9 10  39  1 9  40  1 1  40  1 1  40  1 1  42  1 1  43  1  14  35  43  1 1  14  38  53  44  25  17  45  1 1  14  40  59  45  26  18  46  1 1  15  45  60  46  27  19  53  61  46  27  1 9  66  47  29  20  1 2 13  1  1 3  28 30  37  47  1 1  47  1 1  16  54  50  1 1  16  56  67  47  29  21  50  1 1  16  58  72  47  32  21  16  62  75  48  33  22  50  33  22 24  52 53  1 1 1 1  55  1 1  55  1 -i  16  16  66  75  66  77  52  34  1 7  69  77  55  34  25  78  58  35  27  17  56  1 1  17  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12  10  1 0  1 1  1 0  1 0  10  10  13  1 1  1 3  11  1 1  1 1  10  10  13  1 1  1 4  1 1  1 1  1 2  11  1 1  1 1  12  12  11  1 1  12  938 5A  938  14  11  14  1 1  1 4  1 1  12  15  1 2  15  11  12  1 3  1 6  1 2  1 5  1 1  1 3  13  1 1  1 6  1 2  15  12  13  13  12  12  1 6  12  1 5  1 2  1 4  13  12  12  17  1 2  15  1 2  14  1 3  12  12  17  1 5  1 2  14  1 3  12  1 6  12  1 4  1 4  21  1 2  1 6  1 2  15  14  1 2  24  1 2  1 6  12  1 5  1 4  12  .1 2  24  13  1 6  1 3  15  1 5  13  13  26  13 •  17  13  15  15  13  13  17  1 3  15  1 5  1 3  17  13  1 6  15  30  1 3  1 7  1 3  1 7  1 6  15  30  1 3  18  1 4  18  1 6  14  15  30  1 3  20  1 4  1 9  1 6  14  15  33  1 3  20  1 4  20  17  14  16  34  14  20  1 4  20  17  14  1 6  20  15  21  17  21  20  11 11 11  12 12 12  13 13 14  1 1 1 1  12 12  13 15  15  1 8  26 29  36  1 2  13  1 4  14  18  36  1 6  20  1 5  15  20  37  1 6  21  1 5  21  20  21  37  1 6  21  15  21  21  1 6  21  37  17  21  1 6  22  21  18  22  38  17  22  17  23  24  18  22  40  18  22  1 9  24  25  21  23  24  21  25  27  25  23  25  27  26  23  26  28  22  28  26  26  28  52  22  30  26  29  28  55  24  30  28  30  32  47  61  26  31  32  31  34  47  61  29  31  35  31  40  47  59  67  37  32  36  32  44  47  86  75  38  36  42  37  45  51  86  77  42  36  44  61  52  74  86  40  51  73  53  57  40  60  79  62  63  79  77  15  22 24 24 28 38 45 46  77  24 26 28 30 37  95  42 42 46 47  82 86  18 21 22  46  81  96  90  67  41  82  100  97  82  49  83  83  81  61  85  83  100  92  110  98  85  93  11 1  100  90  79  96  85  103  100  121  103  93  101  105  100  115  101  121  105  165  103  107  11 0  140  170  130  11 0  140  450  177  150  170  125 MOLT-4 Cell samples A  AA  B  GG  HH  II  J  23-Mar  25-Jan  8-Mar  25-Jan  22-Mar  22-Mar  23-Mar  7-Feb  24  1  20  2 .  21  22  23  3  16  13  18  1 0  10  10  17  1 1  18  17  18  1 0  10  10  1 9  1 1  20  18  20  1 1  10  1 1  20  1 1  21  18  24  1 1  10  1 1  22  1 1  22  1 1  1 1  1 1  22  25  1 1  1 1  1 1  28  18  26  1 1  1 1  1 1  30  23  1 9  27  1 1  1 1  1 1  30  1 2  23  1 9  28  1 1  1 1  1 1  31  12  25  20  28  1 1  1 1  1 1  35  1 2  26  36  942 6A  1 1  1 1 1 1 12  18 18  22 23  24  32  1 1  1 2  12  20  32  1 1  12  12  36  29  20  32  1 2  12  13  43  12  29  20  35  12  1 2  1 3  46  12  29  20  38  12  12  13  47  12  30  21  52  1 2  1 2  1 3  52  12  12  14  54  1 2  1 2  14  55  1 5  58  12 1 2  12 12  20  29  21  32  21  36  59 60  21  62  12  1 3  22  67  1 2  1 3  18  60  42  23  72  1 3  1 3  1 9  60  14  52  25  72  13  13  19  65  14  53  25  73  1 3  1 3  22  65  14  92  26  82  1 3  13  22  80  82  1 3  14  23  88  14  26  90 93  13 1 3 13  14  40 42  28  93 93  31  85  1 3  15  93  32  88  14  14  27  16  97  34  89  1 4  14  55  95  17  98  38  94  14  1 5  75  100  17  100  40  95  1 4  1 5  75  105  14  16  88  1 1 5  1 4  16  92  117  96  14  16  92  120  98  1 4  16  92  120  82  99  1 4  17  92  120  106  84  99  15  17  93  120  20  106  85  101  1 5  17  95  120  22  106  86  102  1 5  17  97  123  24  106  87  103  15  54  98  125  25  107  88  103  17  54  100  125  25  107  90  104  1 7  86  103  125  21  86  103  125  105  21  88  105  130  94  11 6  31  88  105  130  114  95  120  31  91  105  130  120  100  122  33  91  107  130  44  121  100  123  37  91  110  130  100  127  37  91  110  140  15  17 17 17 18 1 9 19  26 28 30 37 40  42  102  42  102  59  103  75  103 103  93  108  93  11 0 110  ,  95 95  104  82  123  100  124  102  130  87  103  11 1  140  180  130  103  133  87  103  120  180  126  JJ  K  KK  L  LL  M  MM  N  23-Mar  8-Feb  27-Mar  8-Feb  30-Mar  10-Feb  31-Mar  10-Feb  25  5  26  6  27  7  1 1  12  24  4  13  15  1 1  12  1 2  1 3  13  15  12  1 2  1 2  14  1 1  13  17  12  1 3  12  14  12  14  13  17  1 2  1 3  1 2  15  12  15  14  18  1 2  1 3  1 3  1 9  12  1 5  14  19  12  14  1 3  20  1 2  1 5  15  20  13  14  1 3  22  13  16  1 5  21  1 3  15  1 3  24  13  16 1 6 1 6  13  16  22  1 3  16  14  26  1 3  27  14  16  22  13  16  14  16  22  14  17  1 4  27  14  17  16  23  14  1 7.  14  28  14  17  17  23  14  17  1 5  30  18  1 7  17  25  1 5  17  1 5  31  18  17  18  16  33  20  17  33  22  17  17  25  15  27  1 5  1 9  16  1 9  27  17  20  20  34  24  17  1 9  28  17  21  20  36  46  18  20  30  1 7  23  30  37  85  1 9  21  30  17  25  32  38  100  1 9  21  30  1 9  27  32  49  105  20  23  30  20  28  35  58  105  22  32  20  28  35  62  11 0  23  32  32  23  30  35  73  112  25  85  32  26  33  41  75  112  26  85  36  26  42  41  79  11 3  27  95  46  26  54  50  81  30  95  55  33  72  50  88  32  82  50  96  33  97  35  17  32  99  58  36  80  40  85  72  100  93  40  86  72  100  40  100  93  83  87  82  100  44  100  94  98  87  82  101  47  103  96  100  88  82  101  48  103  97  100  88  82  103  56  103  98  100  90  82  104  57  103  100  100  90  82  105  71  105  101  100  93  84  11 0  75  93  84  11 0  75  110  75  99  106  105  102  11 0  104  94  85  108  110  104  94  85  11 0  77  108  110  105  96  87  11 0  85  110  11 1  105  96  87  110  88  110  .113 .  105  98  90  110  95  112  115  105  100  90  112  97  112  115  105  101  90  115  98  106  115  117  110  104  90  115  102  115  120  111  105  95  11 6  105  110  97  117  11 0  115  97  139  11 0  135 135  120 122  117 120  127  NN  O  CO  R  S  T  U  V  31-Mar  10-Feb  6-Apr  23-Feb  23-Feb  24-Feb  24-Feb  28-Feb  28  8  29  11  1 2  13  14  1 5  12  10  12  1 1  20  1 2  11  11  12  13  12  11  25  15  13  14  12  13  1 5  14  14  12  13  28  16  14  15  15  1 5  13 13  1 1 11  26  14  1 1  30  16  14  11  32  16  17  16  17  16  11  32  16  17  17  13  17  16  1 1  32  17  1 9  17  13  19  17  14  32  17  20  17  13  1 9  34  17  21  17  14  20  22  17  13 13 13  14  15 17  21  1 7  14  18  1 5  38  17  18  1 9  45  1 7  22  17  47  17  22  18  14  21  18  24  14  23  18  25  48  17  22  18  15  26  20  26  48  18  22  19  15  26  48  20  24  19  25  20  20  27  16  30  20  31  50  20  16  30  20  31  51  20  26  20  20  32  52  20  28  20  30  20  32  60  21  30  20  18  33  20  36  63  21  35  20  18  33  20  36  65  21  37  20  20  37  66  21  40  20  36  68  22  40  21  24  42  21  18 18  20  30  40  23 23  36  41  40  37  75  21  60  40  40  77  24  42  22  24  75  41  40  79  27  48  24  24  81  41  41  80  27  50  30  37  90  42  42  82  27  51  30  28  55  30  83  28  70  31  85  30  77  31  66  85  30  82  32  69  75  87  32  82  33  103  77  82  87  43  83  35  103  77  82  88  81  87  36  61  105  92  89  90  92  90  37  61  105  92  95  90  100  90  52  62  107  97  100  92  100  90  56  62  107  93  105  92  70  95  105  95  75  100  95  107  99  75  100  101  97  11 0  103  78  11 0  100  101  99  110  105  79  110  104  103  103  11 0  11 0  81  114  104  105  105  11 2  110  83  100  120  105  106  11 0  115  115  90  100  125  105  107  110  120  115  92  102  130  110  11 0  115  125  117  101  102  139  .11 0  11 0  120  127  120  125  21  37 42 42 42 42 46 46  92 92 95 95 96 96  92 95 97 97 100  107 11 0 110  42 65 65 69  97 98 9 8  45 46 52  100 100  82  128  X  Y  Z  -Mar  7-Mar  8-Mar  8-Mar  16 1 1 1 1 1 1 1 1 1 1 1 1  1 7  1 8  1 9  11  1 1  17  1 1  1 1  20  1 1  1 2  21  11  1 2  23  11  1 3  28  1 2  1 3  28  12  1 2  14  28  12  1 2  14  28  1  1 2  1 4  31  1 2  1 2  1 5  32  12  1 2  15  33  12  12  1 6  35  1 2  1 2  1 6  36  12  1 2  17  40  1 2  1 2  1 8  40  1 2  1 2  18  41  13  1 2  1 8  47  13  1 2  21  48  13  14  25  50  1 3  1 5  26  59  1 3  15  29  67  13  1 5  32  68  14  15  41  70  1 4  1 5  45  70  14  1 5  59  72  18  76  73  14  26  77  74  1  65  80  77  14  68  82  80  1 4  70  82  81  1 5  70  85  82  15  73  85  82  15  74  85  85  1 6  75  87  85  18  77  88  85  1 8  79  88  87  40  80  89  87  55  80  90  90  65  80  91  92  78  82  93  92  80  83  94  93  80  84  96  95  81  84  96  96  82  85  97  96  83  85  97  96  90  85  98  98  95  87  100  99  97  90  102  100  110  90  11 8  101  125  101  138  105  w  2  14 4  129  Appendix t-test results  for each  G 50 c e l l  sample  j Seperate variarice estimate Pooled variance estimate t value idegrees of freedomj 2-tailed probability |<degrees of freedorrj 2-tailed probability | 0.001 96.9 -3.53 0.001  I  899 0  -3.53  I  0.27  1  I  0.713  0.785  IV  t value  0.457  2-tailed probability I  1.24  f value  I  |  52.59  -4.87  -4.87  27.24  I  |  0.564  0.018  I  -0.37  0.001  0.564  -0.37  0.27  -3.96  -0.2  -0.81  -1.51  2.09  0.98  0.43  65.87  96.26  97.95  88.44  97.62  97.61  97.72  93.56  91.47  97.91  94.1  0.001  0.713  0.785  0.843  0.419  0.135  0.039  0.329  0.668  0.651  3.51  |  |  53.18  6.03  0.651  0.881  |  I  0.346  CD 00  CD  o  CD  CD 00  o  o cn  o  o 3.51  I  6.03  23.4  j  0.329  0.649  0.53  I  |  0.039  1  0.691  -0.58  I  97.99  |  0.038  0.45  CD oo  0.135  -0.46  -0.46  0.784  0.43  co 00  I  0.649  0.939  > .152  I 0.98  CD oo  0.419  0.824 0.824  0.837 |  2.09  CD 00  I  88.99  |  0.058 |  -1.51  CD oo  0.843  -0.22  -0.22  0.125  I  -0.81  CD 00  I  I  0.023  0.659  -0.2  CD 03 CD 00  0.71  0.664  o  -3.96  o  CD 00  CD 00  CO CO  O ro 00 ro  5.63  0.933 0.933  o o  97.68  CD oo  0.08  I  CD oo  I  0.08  CD 00  90.35  CD 00  0.53  CD 00  97.85  CD oo  -0.58  o  I  I  o  CD CO  o 00  5' ro ro  -* ro  ->• r o ro ->•  ro ro ro  ro  cn CO  o CT) cn CD CO  o  CO ooCO  jO \3  ro ro ro ro  -» ro  -» ro  cr  ro  PO  l\3 -»• ro  i'  JI  .0  *>•  3> .5; 3> 3)  vl  vl £>• ji  jO  •O -0  vl -n  .n  ji  X  vl -j  vl  vl  \3  <J)  Ji  cj\ 3) D  JI ji ji  3) 3> 3> X>  vl z> vl -si  130  < n  v  1.24  f value  0.798  0.602  0.453  I  I  I  I 2-tailed probability I  0.22  -0.81  t value 1.15  Idegrees of freedom 2-tailed probability 96.88 0.253 |  Seperate variance estimate |  0.825  probability |  .97.45  |  0.445  0.253  97.87  j  0.422  I  96.9  I 0.22  |  0.007  -0.81  0.825  0.77  |  I  0.445  76.39 ||  91.89  96.37  87.16  0.003  0.598  0.137  0.157  61.98  |  0.007  | |  I  2.77  0.422  Pooled variance estimate I Idegrees of freedomj 2-tailed  1.16  I I  t value  1.08 0.456 |  4.15 -1.43  I 890 0  |  600 0  I  I  96.9  97.96  97.03  66.15  0.99  0.984  0.881  600 0  728/1  ISubject ! variable  728/2 728/3 | 2.77  I  1.24  I  I  |  ro  0.77  3.27 4.15  0.156  -0.54  -1.43  I  3.09  0.457  1.24  |  I  I I |  o oo  812/3  I 7.41 0.001  0.137 0.589  I  2.65  r  |  0.003  I  0.15  0.15  -0.54  I  I |  0.363 3.09  0.881  0.888  0.02  I  |  1.04  0.984  I  I  0.484  0.02  |  !  1.22  -0.01  I  | |  0.991 0.682  [  !  -0.01  |  2.65  |  bi  O  oo  CD  00  812/5  I I 0.011  CD  00 00  CD  CO  03  851/1 2.68 |  CO  I  I 2.09  CD CD  oo 00  CO  00  00 00  CD  oo  03  CO  03  CD CO CO  *>•  851/2 |  Ol  cn  o  CD  906/3 938/1 938/3 942/2 942/3 942/4 50/1 00  o  CO •-j  Ol  to to ro  to  - ro ro  ro ro ro  ro ro ro ro ro  

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