FIFRA SCIENTIFIC ADVISORY PANEL (SAP) OPEN MEETING

REEVALUATION OF THE HUMAN HEALTH EFFECTS OF ATRAZINE:

REVIEW OF NON-CANCER EFFECTS AND DRINKING WATER MONITORING FREQUENCY

DOCKET NUMBER: EPA-HQ-OPP-2010-0481

UNITED STATES ENVIRONMENTALPROTECTION AGENCY

CONFERENCE CENTER LOBBY LEVEL ONE POTOMAC YARD (SOUTH BUILDING) 2777 SOUTH CRYSTAL DRIVE ARLINGTON, VIRGINIA 22202

SEPTEMBER 15, 2010 8:30 A.M.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 2

1 FIFRA SCIENTIFIC ADVISORY PANEL 2 MEETING 3 SEPTEMBER 15, 2010 4 DR. STEVEN HEERINGA: Good morning 5 everyone and welcome to the second day of the four-day 6 proceeding of the FIFRA Science Advisory Panel, a 7 meeting on the topic of the Re-Evaluation of the Human 8 Health Effects of Atrazine: A Review of Non-Cancer 9 Effects and Drinking Water Monitoring Frequency. 10 I'm Steve Heeringa of the University of 11 Michigan. I'm the Chair for this Panel and will be 12 serving in that role for the next three days. 13 I'd like to go around the table today 14 and have the Panel members briefly introduce themselves 15 and state their affiliation and specific expertise in 16 relation to this particular Panel with you, and I'll 17 begin with Dr. Portier on my left. 18 DR. KENNETH PORTIER: Thank you. 19 Good morning, I'm Ken Portier, Director 20 of Statistics at the American Cancer Society National 21 Office in Atlanta. I'm an applied biostatistician and 22 a member of the permanent Panel. 23 DR. JANICE CHAMBERS: I'm Jan Chambers, 24 I'm Professor in the College of Veterinary Medicine at 25 Mississippi State University. I'm a pesticideFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 3

1 toxicologist with an emphasis on neurotoxicology, and 2 I'm a member of the permanent Panel. 3 DR. CAREY POPE: Good morning. My name 4 is Carey Pope. I'm a Professor and Head of the 5 Division of the Department of Physiological Sciences at 6 the Center for Veterinary Health Sciences at Oklahoma 7 State University. I am a toxicologist, and neurotox is 8 my interest and expertise. 9 DR. JOHN BUCHER: I'm John Bucher. I'm 10 the Associate Director of the National Toxicology 11 Program at the NIEHS, and I'm a member of the permanent 12 Panel. 13 DR. DANIEL SCHLENK: Good morning, my 14 name is Dan Schlenk. I'm a Professor of Environmental 15 Toxicology in the Department of Environmental Sciences 16 at University of California Riverside. My expertise is 17 in fate and effects of pesticides in aquatic organisms, 18 and I'm a member of the permanent Panel. 19 DR. RICHARD GREENWOOD: I'm Richard 20 Greenwood from University of Portsmouth. I'm Professor 21 of Environmental Science, and my expertise is in the 22 area of general toxicology and pharmacokinetics. 23 DR. KANNAN KRISHNAN: I'm Kannan 24 Krishnan, Professor of Occupational and Environmental 25 Health at the University of Montreal, Canada. I'm aFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 4

1 toxicologist. 2 DR. NELSON HORSEMAN: Good morning, 3 Nelson Horseman from the University of Cincinnati. I'm 4 a physiologist with particular expertise in mammary 5 gland biology. 6 DR. JAMES MCMANAMAN: Good morning, I'm 7 Jim McManaman from the University of Colorado 8 Department of Obstetrics and Gynecology, and I have 9 expertise in the mammary gland. 10 DR. KATHERINE ROBY: Good morning, Kathy 11 Roby from University of Kansas Medical Center, 12 Department of Anatomy and Cell Biology, and my 13 expertise is in female reproduction. 14 DR. BARRY DELCLOS: Barry Delclos from 15 the FDA's National Center for Toxicological Research. I 16 do research on toxicology and carcinogenesis. 17 DR. SANDRA LEGAN: Good morning. My 18 name is Sandy Legan. I'm Professor of Physiology at 19 the University of Kentucky, and my expertise is in 20 female reproductive neuroendocrinology. 21 DR. WESLEY STONE: Good morning, Wes 22 Stone with United States Geological Survey; area is 23 chemical transport. 24 DR. RICHARD COUPE: Richard Coupe with 25 the U.S. Geological Survey at the Water Science Center,FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 5

1 and I'm a hydrologist. 2 DR. HERBERT LEE: Herbert Lee of 3 University of California Santa Cruz, Professor of 4 Statistics and Associate Dean of Graduate Studies and 5 Research in the Baskin School of Engineering, and I'm 6 an applied statistician. 7 DR. BETTE MEEK: And I'm Bette Meek from 8 the University of Ottawa on interchange with Health 9 Canada with a background in toxicology and regulatory 10 risk assessment. 11 DR. SUSAN AKANA: Susan Akana, a 12 research physiologist from the University of California 13 San Francisco. I study the hypothalamic-pituitary14 adrenal axis and its interaction with energy balance. 15 DR. PENELOPE FENNER-CRISP: Penny 16 Fenner-Crisp, I'm a private consultant from 17 Charlottesville, Virginia. My area of expertise is 18 toxicology and risk assessment. 19 DR. ELLEN GOLD: I'm Ellen Gold. I'm a 20 Professor of Epidemiology and Chair of the Department 21 of Public Health Sciences at the University of 22 California Davis, and my expertise is the epidemiology 23 of adverse reproductive health effects on women. 24 DR. SHELLEY HARRIS: Hi, I'm Shelley 25 Harris; I'm Associate Professor at University ofFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 6

1 Toronto and a scientist at Cancer Care Ontario, and I'm 2 an epidemiologist with expertise in pesticide exposure 3 assessment. 4 DR. JOHN BAILAR: John Bailar, retired 5 from the University of Chicago, now Scholar in 6 Residence at the National Academies here in Washington. 7 I am a physician and statistician. 8 DR. GERALD LEBLANC: Gerry LeBlanc, I'm 9 Professor and Head of the Department of Environmental 10 and Molecular Toxicology at North Carolina State 11 University. My area of expertise is in endocrine 12 toxicology, and I'm a member of the permanent Panel. 13 DR. STEVEN HEERINGA: Thank you, Panel 14 members, and we'll give Dr. Mumtaz a moment to get 15 seated to introduce himself. 16 DR. MOIZ MUMTAZ: I'm Moiz Mumtaz at 17 ATSDR, interested in clinical research risk assessment. 18 DR. STEVEN HEERINGA: At this point, I 19 want to turn it over briefly to the Designated Federal 20 Official for this FIFRA meeting, and that's Mr. Joe 21 Bailey. 22 MR. JOSEPH BAILEY: Good morning, 23 everyone; as Dr. Heeringa said, my name is Joe Bailey, 24 the Designated Federal Official for the meeting. 25 I want to welcome everyone back thisFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 7

1 morning, and the public and Panel as well. If you 2 weren't here yesterday, EPA made its presentation, and 3 all of the slides for that presentation are now 4 available in the Public Docket, along with all the 5 other background materials for the meeting. 6 And with the public comment session 7 today, we'll probably have quite a bit of handouts to 8 give to the Panel. They will be placed in the Docket 9 as well and will be available for the public as soon as 10 we can get them up. 11 Once again, welcome, everyone, back to 12 day two, and I'll turn the mic back to Dr. Heeringa. 13 DR. STEVEN HEERINGA: Thank you very 14 much, Joe. 15 And again, just to review where we're at 16 in the proceedings, we have heard presentations from 17 the Scientific Staff of the Environmental Protection 18 Agency that have been working on the Issue Paper and 19 the background work. 20 We have another presentation scheduled 21 this morning with Dr. Suzanne Fenton, and following 22 that presentation and the Panel's questions and 23 clarification, we'll move on to the period of public 24 comment. 25 The period of public comment will beFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 8

1 substantial today, with a number of people contributing 2 various links. Times have been agreed upon with the 3 FIFRA SAP Office, and so I'm going to hold all of the 4 presenters in the public comment period to the allotted 5 timing so use the time wisely; we want to make sure 6 that we have an open exchange and that the Panel has 7 the opportunity to hear everything that you need to 8 present, but I also need to keep the meeting on track. 9 We have a busy three days ahead of us, and so I'll try 10 to enforce times pretty rigidly today. 11 At this point in time, I'd like to turn 12 to Dr. Steven Bradbury, who is the Acting Director of 13 the Office of Pesticide Programs at the EPA, and just 14 to see if there are any opening comments or any follow15 ups from yesterday's proceedings. 16 DR. STEVEN BRADBURY: Thank you, Dr. 17 Heeringa. 18 I want to thank the Panel for 19 yesterday's interaction. I thought it was a very good 20 first opening day, a lot of time to get your clarifying 21 questions, and appreciate the opportunity to go over 22 the Charge Questions at the end of the day. I think 23 that will help us as we move forward. 24 We don't have anything additional to 25 offer after yesterday's discussion at this time. ThankFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 9

1 you again, and we're prepared to move towards Dr. 2 Fenton's presentation. I think that's it for the 3 Panel. 4 DR. STEVEN HEERINGA: Okay. I think 5 just briefly to the Panel members, any 6 Oh, Dr. Levine? 7 DR. TINA LEVINE: We're just checking 8 with you to see if there are any follow-up questions 9 that you have. 10 DR. STEVEN HEERINGA: Right. Panel 11 members, anything from yesterday that's a question or 12 clarification that you'd like to have answered before 13 we move on to Dr. Fenton's presentation? 14 Yes, Dr. Greenwood. 15 DR. RICHARD GREENWOOD: I'd just like to 16 clear up one point. Yesterday in Slide 61 where you 17 showed the trapezoidal rule and you showed and 18 indicated that it was first-order elimination, and 19 you've got three points, is that correct? You could 20 only use the last three points, the last -- 21 MALE: Yes, that is correct. Yeah, we 22 only have three data points for each of those groups. 23 DR. RICHARD GREENWOOD: It just seems 24 that you are missing something, because there's a very 25 rapid fall before those three points that you use.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 10

1 And then I guess you fit in a two2 parameter model with three points, because for a first3 order PK, you have two parameters to estimate them. 4 You've got three points, so there could be a little bit 5 of doubt about the values of those rate constants. 6 DR. CHESTER RODRIGUEZ: So the only 7 thing that we estimated from that plot was slope of 8 line 9 DR. RICHARD GREENWOOD: Yeah. 10 DR. CHESTER RODRIGUEZ: Okay. So you 11 plot pretty much the natural log, the plasma 12 concentration versus time, and you take the slope of 13 that line as your initial rate constant. 14 DR. RICHARD GREENWOOD: Right. 15 DR. CHESTER RODRIGUEZ: So it's really 16 one parameter of estimating. 17 DR. RICHARD GREENWOOD: The function 18 does have two parameters, because it's a measure of 19 location as well. But in those curves, there is this 20 big speed drop before the first point that you start to 21 use. Did you have any idea of what that's about? 22 DR. CHESTER RODRIGUEZ: No, actually, we 23 did not. 24 DR. RICHARD GREENWOOD: Okay. 25 DR. CHESTER RODRIGUEZ: Those points areFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 11

1 the only representation of the elimination phase. 2 DR. RICHARD GREENWOOD: Because if it 3 were biphasic, what you've done is estimate the second 4 phase; it may be a good explanation to give. And 5 there's no way you can get at the first points. 6 Also, to some extent I guess the scaling 7 is set by the time points, because there's a big gap 8 between the time points. If I understood correctly, 9 there was three hours between the last dose and the 10 first point that you could use, that's correct? 11 DR. CHESTER RODRIGUEZ: Yes, that is 12 correct. 13 DR. RICHARD GREENWOOD: Okay, thanks 14 very much. 15 DR. CHESTER RODRIGUEZ: Yeah, but is it 16 okay if I make one more point? 17 DR. RICHARD GREENWOOD: Yes. 18 DR. CHESTER RODRIGUEZ: So that's why we 19 decided to use a non-compartmental approach for the 20 analysis. That means that we're not selecting a 21 substitute model. 22 DR. RICHARD GREENWOOD: Yeah. No, no, 23 I understand that. 24 I think the other point which I'm a 25 little unclear about I guess was in that work, theFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 12

1 blood samples are always taken virtually having this 21 2 hours after the dose; is that correct? 3 DR. CHESTER RODRIGUEZ: It's actually 24 4 hours. 5 DR. RICHARD GREENWOOD: 24 hours, okay. 6 So it's before the next dose? 7 MALE: Yup. 8 DR. RICHARD GREENWOOD: So the top of 9 that factor isn't really the average, because it will 10 be at its lowest point before you get the next dose 11 every time you take a sample. 12 DR. CHESTER RODRIGUEZ: That is correct, 13 and that's why we're describing that as pseudo-steady 14 state and not a steady state per se. 15 DR. RICHARD GREENWOOD: Yeah, but with 16 the way that it's being done will probably 17 underestimate the area under the curve. You should 18 always take it to the lowest point, not the mean point 19 or average. 20 DR. CHESTER RODRIGUEZ: Yeah, but that's 21 the only information we have. 22 DR. RICHARD GREENWOOD: No, I understand 23 that. I just want to be clear. 24 Thank you. 25 DR. STEVEN HEERINGA: Thank you, Dr.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 13

1 Greenwood; Dr. Rodriguez, too. 2 Dr. Akana. 3 DR. SUSAN AKANA: I'd like clarification 4 on one detail. It's on Figure 5.8, which is the very 5 flat tall figure on 71 of the Issue page. This is the 6 one that has multiple studies plotted with the X axis 7 of the atrazine dose. The question is, the Y axis is 8 LH surge attenuation, percent control. Is that peak LH 9 at 1800 of LH area under the curve? 10 DR. CHESTER RODRIGUEZ: That represents 11 the peak of the surge at 1800 hours. 12 DR. SUSAN AKANA: Thank you. 13 DR. STEVEN HEERINGA: Good, Dr. Akana. 14 Any other questions or clarification at 15 this point? We'll have another opportunity before we 16 move to the public comment period; but Dr. Greenwood, 17 Dr. Akana, thank you for bringing those up. 18 At this point in time, I think we're 19 ready to view the presentation by Dr. Suzanne Fenton of 20 the Cellular and Molecular Pathology Branch of the 21 National Institute of Environmental Health Sciences. 22 Good morning, Dr. Fenton. 23 DR. SUZANNE FENTON: Good morning. I 24 hope that everyone has gotten my handouts. I estimate 25 you have. Sorry to not be here yesterday, but myFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 14

1 schedule did not permit it. 2 Today I'm going to talk about The Fetal 3 Mammary Gland and Prostate as Sensitive Developmental 4 Targets for Atrazine. I understand that you will also 5 have access to one of the papers I am going to talk 6 about today that is actually available online in ECOG. 7 There are many potentially mistakes and misconceptions 8 in the Summaries of some of our work, and I want to 9 make sure I hit the highlights of our work today so you 10 understand what our findings are, how we came to those 11 conclusions. 12 The reason we do the work that we do is 13 because breast cancer is a global problem. In 2010, 14 about 1.5 million people will be diagnosed with breast 15 cancer. It's the most common cancer of women in the 16 world. One of every ten women in the world will have 17 breast cancer in their lifetime. It is a primary cause 18 of death, and in the U.S. one in eight women are 19 diagnosed with breast cancer each year. 20 Men are also affected by this disease, 21 and the most recent SEER data in 2006 reports 400 men 22 died of breast cancer; it does not just affect women. 23 Also precocious breast development in 24 girls, especially in the U.S. and Scandinavian 25 countries, is at an epidemic rate. Pediatricians haveFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 15

1 rewritten the book on precocious puberty, and several 2 studies have been reviewed by the NCEA, the USEPA's 3 NCEA, a couple of years ago when our Panel decided that 4 or came to the conclusion that body fat and endocrine 5 disruptors were regarded as critical modifiers of 6 breast developmental timing. 7 Also a recent study by Dr. Biro at 8 University of Cincinnati with over 1500 girls with 9 puberty at the age of 9, almost 23% of white girls had 10 breast development at age 9, and over 50% of black 11 girls had breast development at the age of 9. Body fat 12 and Tanner scores were not very well correlated and 13 only explained 30% of the variance in this outcome. So 14 the effect of endocrine disruptors on breast 15 development, breast cancer, is something that is very 16 near and dear to my heart, and that's why I do the work 17 that I do. 18 There is a technique that you may have 19 read about in the Summary, mammary gland whole mounts, 20 that I'm going to go through very quickly today; but 21 it's very important that you understand how we do this 22 and why we do it. 23 This is a mouse and a rat. Hopefully, 24 I'm going to point to the front. In the rat there are 25 six glands, not five as shown here. The sixth oneFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 16

1 would be down here near the tail. We removed the 2 entire fourth and fifth gland as a unit, with the 3 inborn lymph node being in between those two. 4 The whole mount procedure is very quick 5 and is not very expensive. In fact, I had a high6 school junior in my lab this summer who was able to 7 learn this technique in less than a day. After a week 8 she was able to teach it to others, and after two weeks 9 she was evaluating the slides in a manner that was 10 consistent with my own. 11 On the day of necropsy, we place the 12 slides in a Carnoy's fixative. It's glacial acetic 13 acid, ethanol and chloroform. This takes us about 14 15 minutes. 15 The next day we rinse these slides and 16 put them in Carmine Alum stain; takes about 25 minutes. 17 The day after that, or maybe one after, 18 we may, depending on the thickness of the tissue, rinse 19 these slides in increasing graded alcohol to 100%; 20 transfer to xylene. This clears the fat pad so that 21 you can see through the gland on the slide, takes about 22 30 minutes; and then these are allowed to sit in xylene 23 entirely until they're clear. 24 We permanently mount the slides and dry 25 them on bench coat. We fill the air pockets as needed.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 17

1 It takes us about an hour-and-a-half for 100 slides. 2 We recommend three time points of 3 collection for potentially estrogenic or anti4 androgenic compounds so that developmental pace and 5 permanence of the effect can be determined. We 6 evaluate these on a macroscope, which is a dissecting 7 scope, or computer-generated scans. It may take 8 between two and four hours on the macroscope. 9 We evaluate the slides in a way that is 10 consistent with pathology assessment of sliced sections 11 and H&E stain sections. This is something that's been 12 going on for 40 or 50 years in pathology. This is not 13 a new technique. 14 We assess all controls within an age group first, and 15 we determine what it's for: what is our best-looking, 16 most well-developed slides; what do they look like; 17 what is our best situation. We then assess all high18 dose slides within that same age group and define that 19 as 1, what is our worst-case scenario, essentially the 20 same as a pathologist would do. 21 We then mix the slides, evaluate the slides 22 as an entire set. We don't know the identification of 23 the slide when we are evaluating it. We stack the 24 slides into scores; so 4 is the best, 1 is the poorest. 25 They don't always fit into a single category, so thereFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 18

1 may be a stack in between a 4 and a 3. 2 We then pick up each stack, re-evaluate them 3 again to make sure that a 2 at the beginning of the 4 study, at the beginning of a 2- or 4-hour microscope 5 session, is the same as a 2 at the end. 6 We then record the ID off that slide and the 7 score that we gave it and any other notes that we used 8 to decide the score. 9 We then repeat the entire process with 10 another score, mixing the slides, starting from 11 scratch. They have to know what a 4 and a 1 is also, 12 so they start from scratch. 13 We evaluate the two sets of scores and 14 reconsider any scores for which there was a variance of 15 more than 1. We want the scorers to be thinking in a 16 consistent manner, and usually we have about 13% to 16% 17 error. So we average the scores and report them. The 18 pictures that we show you in pictures that you'll see 19 today represent the mean score of that group. 20 When we score these glands, when we evaluate them, we 21 have six criteria that we're really most interested in: 22 the terminal end number and the stage of development; 23 that they are a terminal duct, a terminal end bud, an 24 alveolar bud. We look at longitudinal duct growth; 25 lateral duct growth; number of primary ducts; densityFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 19

1 at ductal branching; and the amount of budding on the 2 ducts. 3 So you can see here a picture of what we 4 normally look for. You can see the lateral branching 5 would be from side to side. One of the longitudinal 6 growths would be from the nipple area down here not 7 shown to the end of the glands. The terminal end buds 8 are a specific size. They should measure about 120 to 9 150 microns. We do look at the size of these; we don't 10 just count any end as a terminal end bud, even though 11 it just looks like one. 12 We also look at the budding off the ducts 13 that's shown here. And here is an example of the 14 operating procedure that we had signed off on at the 15 EPA; it is actually an operating procedure that we use. 16 So essentially you can see that 1 would have few or 17 none; that we use words like "few", "none", 18 "undersized" and "one or few". 19 When increased to a 2, you'll see minimal, 20 few branches, few buds. 21 Increase to a 3, you are going to see 22 moderate growth, moderate branching, moderate budding. 23 I mean, we do use a scale to determine this for each of 24 these end points. 25 The visual mammary gland evaluations or the subjectiveFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 20

1 scoring is not a new concept. Historically, this has 2 been used by mammary gland biologists evaluating early 3 life environmental exposures. Some very well-known 4 mammary gland biologists used this method back in the 5 '70s and '80s and still today: Cliff Welch has used it 6 on a 1:6 scale for caffeine exposure following prenatal 7 development -- and you'll notice one of the themes 8 here is prenatal or early life exposure -- Leena 9 Hilakivi-Clarke, Marc Lippman, who was at one time the 10 Head of the Lombardi Cancer Center at Georgetown, and 11 they work within the NCI or use developmental 12 polyunsaturated fat exposures and genistein exposures 13 using a 4-point scale. They found a 0.7 to 0.9 14 correlation coefficient between morphometric analysis 15 and visual evaluation. This work was published in 16 PNAS. 17 Again this same group with Nick Kenney, who has worked 18 with Dick de Augustine and Ken Croik at the NIEHS, used 19 neonatal estrogen, TGF-alpha and ICI estrogen 20 inhibitor. Again, they used both methods, and you'll 21 see here a statement from that paper that characterizes 22 the density of the whole thing. The relative density 23 of the following characteristics were evaluated using a 24 double-blind 4-point scale, and you can read that: 25 "This scale was used instead of counting the actualFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 21

1 number of different structures on total mammary gland 2 or randomly selected areas, which we found not to give 3 an accurate description of the mammary tree." So 4 others also use this method. 5 But in my own work, early work on TCDD, we 6 felt the same as the early researchers and others that 7 measuring one component of the system or one or a 8 couple of components doesn't give you a very good 9 estimation of what the actual gland looks like. 10 At the bottom, you can see control and TCDD11 treated mammary glands from postnatal day 4, which is 12 what we are going to really focus on. You see here 13 this large structure here -- these are on the same 14 scale -- this smaller structure with much less 15 branching. 16 What we did in the study is we measured the 17 number -- sorry this is off; it was not yesterday -- 18 but we measured the number of primary branches; we 19 looked at the percent extension to the gland, which it 20 looks at longitudinal growth. We also looked at the 21 number of terminal structures, giving us an idea of how 22 many branch points there were, because each branch will 23 form an end. And what we found is that the sum of the 24 parts really equals the whole; that each one of these 25 things didn't really give us an accurate picture ofFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 22

1 what we were looking at. And we then confirmed this 2 with immunohistochemical stains, or with re-sectioning 3 the tissue, so these are contralateral glands. Here 4 you can see much epithelium staining dark purple in 5 this fat pad and much less shown here, and these are 6 longitudinal sections. 7 So one of the important things that we do is 8 we assess pace of development. So the fourth and fifth 9 mammary gland are separate and then grow up together 10 within that fat pad. Once they grow together, they 11 have contact inhibition. The ends differentiate. They 12 are no longer proliferating actively; they are more in 13 a static state, varying just slightly based on the 14 stage of the estro cycle that they're in. Normally 15 after puberty, we see this contact inhibition and 16 differentiated ends. We see fewer terminal end buds, 17 increased number of lobules and budding and a decreased 18 proliferative index measured by BrdU Incorporation or 19 however else you'd like to measure it. 20 If you see a delay at puberty, one of the 21 things that we always see with a delay is an increase 22 in the number of terminal end buds in the gland, a 23 decreased number of lobules and buds compared to 24 control and an increased proliferative index. This 25 increase in terminal end buds has been shown byFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 23

1 multiple groups, and Jose Russo and his wife Irma are 2 the most thorough example, where the terminal end buds 3 are correlated with the number of tumors that may be 4 formed if exposed to a carcinogen. So having these 5 terminal end buds around for an extended period of time 6 could lead to an increased susceptibility to another 7 carcinogen or another EDC. Impaired lactation is also 8 possible if they're mated when terminal end buds are 9 still present and the gland is not fully formed. 10 So one of the other things that we like to do -- and we 11 don't always do this, but it is very useful in aged 12 animals studies and highly recommended -- is that we 13 look at horizontal or longitudinal sections of the 14 mammary gland. These are cut in the same plane as what 15 we're looking at on the whole-mount evaluation. Here 16 you can see all of the mammary gland in a cross17 section: you can see duct development; you can see 18 stroma; you can see if there was a problem with the 19 lymph node such as lymphoma; and you can see entire 20 ductal structures this way. Using a cross-section or 21 transverse section, which has been far overused in 22 pathology, you see very little of the gland and only 23 really a very small snippet of what's going on. 24 There are three major critical periods of 25 development in the mammary gland. They are that inFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 24

1 early life, either just early gestation or in just 2 postnatal, pubertal development and pregnancy. These 3 are times when the gland is undergoing rapid 4 proliferation, metallic index is elevated, and the 5 effect of environmental chemicals has been noted by 6 labs across the country -- not just mine, a lot of labs 7 have participated in this effort. Changes in 8 development during these times can lead to adverse 9 outcomes, including lactational impairment, breast 10 cancer, altered susceptibility to other compounds. 11 In our studies of atrazine, we have three 12 main aims. The aim was to define the atrazine dose and 13 exposure parameters that are the minimum requirements 14 to induce female offspring mammary gland effects 15 without changes in body weight. Changes in body 16 weight, significant changes in body weight, will affect 17 mammary gland development. You will have a smaller 18 mammary gland if you have a smaller animal, and 19 therefore body weight is very important in the analyses 20 that we do. 21 We always plot body weight, and we always 22 compare to it in our analyses. We also want to 23 determine if an environmentally relevant mixture of 24 atrazine and chlorotriazine metabolites affect the 25 mammary gland and prostrate during developmentalFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 25

1 exposures, and are there adverse mammary gland effects 2 of fetal and early neonatal atrazine exposures. 3 For all of these studies, we have used the 4 Long-Evans hooded rat as a model. We always get them 5 from Charles River. Normal cyclicity patterns, 6 reproduction, good reproductive patterns and the fact 7 that they are not really prone to spontaneous mammary 8 tumor formations or other abnormalities in mammary 9 development were the reasons that we chose this strain. 10 Also because some of the early work in Ralph Cooper's 11 lab had used the LE rat. They have large litters, and 12 they're good mothers if you leave them alone. 13 You cannot stress these rats, and this is 14 really important for us in the conversations that are 15 coming up next. You should not manipulate these pups 16 at birth. Food restriction, metal-bottom cages, twice17 a-day inspection of the newborns, which is typical in 18 19 GLV studies and removal of pups from their dam will 19 stress these animals to the point of cannibalism, and 20 it will increase pup loss and weight loss in the 21 animals. We were trained in how to use these animals 22 by Earl Gray and Linda Birnbaum's group, who had used 23 them extensively before us. And we typically equalize 24 our litters on PND4. We took special care, and then 25 the next study that I'm going to describe, to make sureFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 26

1 that we did not stress these animals. 2 So in our cross-foster study, which is the 3 Rayner 2004 study, which is in the section on aromatase 4 for reasons that I don't understand; but we carried out 5 a cross-foster study in which half-litters were crossed 6 on PND1. We removed the five pups from a dam, tattooed 7 these pups and returned them immediately. We changed 8 gloves in between every cage, and we were intensely 9 quiet in the room while doing this; we didn't speak. 10 We had a plan. 11 So we took the rest of the pups out of the 12 cage, and five of those animals were removed and went 13 to another cage, making four cross-foster groups. So 14 there were controls where half the litter was cross15 fostered to another control, there were controls where 16 half the litter was cross-fostered with atrazine, and 17 there were atrazine-exposed animals that were given 18 control pups and atrazine-atrazine groups; but in every 19 case, half a litter was crossed. Always, the dams' own 20 pups were tattooed. 21 So one of the major findings from this study 22 is the effect on mammary gland development. It was the 23 first study that we'd done demonstrating this effect. 24 We saw the effects in the animals that were not only in 25 utero-exposed but also lactationally exposed. TheFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 27

1 effect was worse when they were in utero- and 2 lactationally exposed, and you can see here at 3 postnatal day 33 it's a little easier to see that 4 there's a delay in growth of these glands together. 5 Also in these animals we looked at vaginal 6 opening, which was delayed in the animals lactationally 7 exposed to atrazine and atrazine-atrazine-exposed. But 8 interestingly, we saw changes in both aromatase and EGF 9 receptor gene expression that were prepared from 10 contralateral glands from the same animals, as shown 11 here. We saw significant decreases in aromatase with 12 gene expression, which would suggest slowed and less 13 rapid development, and also EGF receptor. EGF receptor 14 is one of the important growth factors in mammary gland 15 development, and aromatase in the mammary gland 16 produces endogenous estrogen for the gland itself, 17 which helps in the branching morphogenesis. 18 We also did look at BrdU Incorporation in the 19 study. It's noted in your Charge that we did not, and 20 we did look at this. We did not see significant 21 effects; but there was an increase, a general increase 22 in the atrazine-treated animals in BrdU Incorporation 23 at this time point, suggesting that they're more 24 rapidly dividing than the controls, trying to catch up 25 in development.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 28

1 We also looked at males in this study. This 2 is reported in Rayner 2007 paper. In this study, we 3 looked at 120 days and 220 days at the offspring, male 4 offspring. We saw an increase in lateral prostate 5 weight at 120 days in the atrazine-atrazine group, and 6 actually in all the treated groups; but we always base 7 these on body weight, and one body weight was 8 considered. This group was a little larger, so this 9 became insignificant. So there was an increase in 10 lateral prostate weight there, also. 11 This is just an example of an unaffected and 12 an affected gland. I don't want you to associate this 13 with any dose in particular, but this is just an 14 example of what we were seeing in the prostate. These 15 sections were read by EPL pathologist Angela Wolf, who 16 is an EPL employee and a pathologist by training, 17 veterinary pathologist by training. 18 We saw an increase at necropsy of prostate 19 abnormalities. These were like focal areas on the 20 outside of the prostate that were noted. There was 21 also a change in preputial separation timing or 22 pubertal timing in these males in only the atrazine23 atrazine group, and this is reported in that study. 24 At 120 days, the pathology results were 25 significant changes in this lactationally exposed groupFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 29

1 in distribution of the inflammation, and we also saw 2 significant effects in severity. In the affected 3 animals, we saw an increase of severity due to atrazine 4 treatment. Also in the atrazine-atrazine group there 5 was only one noted, and there was a significant effect 6 on the severity there as scored as a 5. 7 In the next paper I want to bring up, this is Critical 8 Windows of Mammary Sensitivity to Atrazine found in the 9 Regrown Tissue section of the Issues Paper. Here, 10 really, the main goal of the study was to assess not 11 only the F1 offspring as we had done in the previous 12 study but also to assess the F2 offspring. These 13 animals were treated for shorter windows of time, again 14 with 100 mg/kg of atrazine. We needed to make sure 15 that we had a positive control, a negative control, and 16 then we broke down this 7-day period into 3-day 17 stretches: 13 to 15, 15 to 17 and 17 to 19. 18 In this study we dosed and we evaluated the 19 offspring at several time points, also assessing 20 vaginal opening; early cyclicity. And then at 67 days, 21 the animals were bred over a 3-day period. And at this 22 time we saw changes in the mammary gland development 23 study, with rat data. We assessed their offspring 4 24 days later and 11 days later after birth. 25 In this study there were two blocks of eightFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 30

1 dams per treatment group that were dosed. There were 2 no block effects. 3 And by the way, this paper received Best 4 Paper in Tox Sci as voted by all of their reproductive 5 and developmental tox papers that year by the 6 Reproductive and Developmental Tox Specialty Section as 7 a team. 8 The major thing that we found in the study 9 was that the 3-day exposure during late gestation did 10 also cause this persistent mammary gland developmental 11 delay. On the top, you can see postnatal day 22. 12 These are just examples of what we saw. Here's the 13 control, here's the delayed development of the 3-day 14 exposure and the 7-day exposure. 15 Shown here at day 67, these are mature 16 animals. We saw very few terminal end buds remaining 17 in this tissue at 67 days in the control. We saw 18 numerous terminal end buds in the 3-day exposed and 19 even more in the 7-day exposed animals. There was no 20 change in VO in these 3-day exposed animals, and there 21 was also no change in body weight in these animals at 22 any point and, if anything, there was a slight increase 23 in body weight. There was delayed vaginal opening down 24 in the 7-day exposed animals. 25 When we bred the siblings to the animals IFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 31

1 just showed you, because obviously we can't breed them 2 if we've taken a mammary gland out, we looked at the 3 weight of the offspring. We also did a lactational 4 challenge on postnatal day 11, in which we didn't find 5 anything; essentially, there was no change in maternal 6 behavior that could be measured, and there was no 7 change in weight gain of the pups after nursing its 8 period of 20 minutes that was significant. 9 What is shown here is in green the control. 10 Yellow is 13 to 15, orange is 15 to 17, blue is 17 to 11 19, and red is 13 to 19. You can see here that a 3-day 12 period and a 7-day period ended up with significantly 13 decreased weight gain in both female and male pups on 14 PND4, ranging from about 12% to 15% and what most would 15 consider adverse, and on postnatal day 11 these weight16 gain deficits were even worse. They were between 13% 17 and 25% in the varying groups. This is an indication 18 that this very brief period -- so these are the 19 granddaughters and grandsons. This very brief period 20 caused persistent changes in the mammary gland that, 21 when present and bred, led to lactational deficits. We 22 did not test them at a period past this time. We 23 tested them when we saw the effect. 24 In the third study that I want to talk about 25 today, we looked at an atrazine metabolite mixture.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 32

1 This mixture is similar to what was presented in some 2 USGS and state-level biomonitoring data from Illinois 3 and North Carolina. We developed this mixture in a way 4 that was similar to what was found in the groundwater 5 in a ratio of how it was found in the groundwater, with 6 25% being atrazine, 20% being hydroxyatrazine, 5% DIA, 7 15% DEA and the majority of it being DACT final 8 metabolite. The percentages were on a massed basis. 9 The estimated maximum cumulative level from the 10 literature that we found was 25 parts per million, so 11 the estimated maximum cumulative level sorry, I just 12 said "million"; I meant billion. So in our study, the 13 minimum level that we gave them was 25 parts per 14 billion. 15 In the study there is some more that I just showed you. 16 We dosed with again the negative control, positive 17 control: 0.09 mg/kg, or 2.5 parts per million; 0.87 18 mg/kg, or 25 parts per million; 9 mg/kg, or 250 parts 19 per million. And the way that we developed this is 20 detailed in this Enoch paper. So there is a chart 21 there that can give you much more information than I am 22 going to go over here. 23 This study was done in two blocks with 24 greater than six dams per treatment group that were 25 dosed. There were between 10 and 18 dams in everyFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 33

1 treatment group for the final analyses. 2 In this paper, we state that we evaluated 3 this data using the dam as the unit; that is true. 4 There is confusion in this paper, and I'm glad we did 5 this because it brought it to my attention and I didn't 6 realize this was here. 7 In the paper, we say that the dam was the 8 unit of measure; that is true. The significant results 9 that are reported are correct. This paper states pup 10 numbers, though; so in several of the figure legends, 11 you'll see "and greater than 10 pups". That's true, 12 but they were not the unit used for the analyses. So 13 that is a misconception, and I'm sorry for the 14 confusion; but what's in the paper is correct. So 15 these numbers, the dam number is at least as great as 16 10 for all of these data. 17 One of the major things that we found in this 18 paper is again this delay in mammary gland development. 19 At the low doses, we did not see it consistently in all 20 the time points and in all of the doses. It was not as 21 consistent in the early stages. We saw this decreased 22 branching pattern again; so here is the control, the 23 branching pattern was decreased in all the doses, and 24 over time you can see these changes. In this postnatal 25 33 group, for whatever reason -- and this happensFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 34

1 sometimes, it's happening in most studies of ours using 2 different compounds before also -- sometimes we get a 3 control that is not normally developed; but as an 4 average, the average mean for that group is not what we 5 typically expect. We typically expect somewhere 6 between 3.2 and 3.5; this PND 33 group was at 2.5. We 7 have no reason for it. There was no weight differences 8 to account for it. But it did cause us to lose 9 significance in this one group; however, at all the 10 time points after 33, which there were two, we did see 11 significant effects of atrazine in all the groups. And 12 you can see here in these groups that the branching 13 morphogenesis just is not what it is in the control. 14 Oh, no, this is really messed up and I'm 15 sorry. I don't know how this happened. It was good 16 this morning. 17 So let me just explain. These are the males 18 from this same study, and these are not discussed in 19 your Issue Paper because there was a snafu with the 20 Journal. The embargo was not released on time, and so 21 this was not in press by the July, although it was 22 accepted and we were told that was in press; but it was 23 not publicly available in mid-July. But it is publicly 24 available now in Reproductive Toxicology. So let me 25 just explain, and you are going to have to watch theFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 35

1 front screen to see if you can follow with me. 2 So we're going to look at controls 0.9, 0.87, 3 8.73. In incidence of information in the controls, we 4 saw 48% of the animals, and there was 25 animals in 5 this group; 48% had inflammation in the lateral and 6 ventral prostate; 67% in the 0.9 group had 7 inflammation; 76 in the 0.87 group; and 80% in the 8.73 8 group, similar to what we saw in atrazine, which was 9 81%. So you can see there was between 21 and 25 10 animals in these groups. These were significantly 11 increased inflammation. 12 We also saw an increase in severity of the 13 affected animals. And this was again the severity 14 scoring that pathologists typically use; this is 15 typical, done by one of the NIEHS pathologists and EPL 16 and a pathology team at the NIEHS. So there was an 17 increase in severity of inflammation for all three of 18 these; but it wasn't quite significant for atrazine, 19 the inflammation severity. 20 And then we also looked at whether or not 21 preputial separation was delayed in these animals, and 22 for 0.9 the answer was no because there was a little 23 bit of higher variability in that group; but for 0.87, 24 8.73 and atrazine, we saw delayed preputial separation. 25 And again, you can probably access that paper.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 36

1 The male prostate effects were also noted at 2 necropsy. This necropsy was not done by my laboratory; 3 it was done by a pathology team, a necropsy team from 4 EPL with a Board-certified pathologist onsite 5 overseeing the necropsy. We saw an increase in the 6 observation of epididymal fat necrosis which looked 7 like lipomas and also prosthetic foci, as I explained 8 we saw in the Rayner paper in the cross-foster study. 9 Shown here again is a control on the top 10 panels, and the bottom panels are examples of what we 11 saw in inflammation, and an example on the bottom of 12 what we saw in the fat. 13 So one thing that I did not talk a lot 14 about today is body weight. In our studies, 100 15 mg/kg of atrazine does cause a significant decrease in 16 body weight gain in the dams in all of these studies. 17 This information is reported on our papers. However, 18 when we used the atrazine metabolite mixtures, not only 19 did we not see a decrease in body weight gain, we saw 20 small increases in body weight gain. This low-dose 21 atrazine metabolite mixture did not affect weight gain 22 in the dams. 23 Not only did it not affect weight gain in the 24 dams, it did not affect weight gain in the pups. In 25 two of our studies, both the Rayner paper and the EnochFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 37

1 paper, we specifically go over the effects on body 2 weight in the fetuses. So separate studies were done 3 in which we exposed the animals to either a dose4 response of atrazine, 25, 50 or 100 mg/kg of 5 atrazine, during the normal dosing period that we have 6 used for all of our other studies; but we also did this 7 for the high dose and the mixture, for the 8.73 AMM 8 mixture. In all these cases, we either saw slight 9 increases in fetal body weight at gestation day 20 or 10 no change at all, as shown here and in the papers. So 11 body weight is not the issue here. 12 So some final thoughts, and so I kind of 13 bring all of these back together. What we've found in 14 all of our work is that atrazine has little, if any, 15 effect on body weight of the F1 pups. We saw a 5% and 16 6% decrease in the PND4 pups in the cross-foster study 17 that were transient; that weight deficit disappeared, 18 and that was only found in the atrazine- atrazine 19 exposure group, again 5% and 6% decreases. 20 We also saw that a high dose of atrazine 21 affects vaginal opening. 22 Preputial separation seems to be more 23 sensitive to the effects of atrazine, and the lowest 24 dose that we saw with an effect was .87 mg/kg. 25 There is little effect on serum hormones.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 38

1 And I didn't talk about it at all today, because they 2 were either inconsistent or showed no pattern and they 3 were also transient; so if we saw it one time, we 4 didn't see them at the next time period that we 5 evaluated them. 6 We strongly thought that prolactin may be 7 involved in branching morphogenesis issues that we have 8 in these glands. That did not turn out to be the case. 9 There is also little effect on female 10 reproductive tissues, which I didn't show you besides 11 the mammary gland. There is some consistency in 12 increased anterior pituitary weight gain in 100 mg/kg 13 across all of our studies, and that has been shown in 14 other studies by Tammy Stoker and Susan Laws. 15 There is no effect of this exposure on early 16 cyclicity, none at all. We evaluated it in two 17 different studies, there was no effect. 18 Prostatitis is apparent on postnatal day 120 19 in two different studies that we've done; but it does 20 not seem to worsen in the rat. We've used two time 21 periods to evaluate this, and in both studies the 22 latter time period was not worse than the earlier one. 23 We have not gone past 220 days to evaluate this effect; 24 but the inflammation is present in both lateral and 25 ventral prostate, with the ventral having a higherFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 39

1 background of inflammation than the lateral. 2 And finally, the mammary gland development 3 changes are visible to the eye. I hope I've shown you 4 that today. You can look at the gland, and you can see 5 the effects. We show you the mean score; we don't show 6 you the worst scenario in these situations. 7 We've also shown that there is gene 8 expression changes that are concomitant with these 9 morphological changes, changes in genes that are known 10 to be involved in early growth and development. We've 11 also shown adverse effects on F2 pup body weight gain 12 if bred when the developmental delays are apparent in 13 the mammary gland siblings. 14 There is an extended window of terminal end 15 bud development in mammary gland. This may also be 16 present in young girls who are taking longer to develop 17 their breasts, so they may start development early and 18 take a longer period of time to reach full development 19 of the breasts. Numerous pediatric epidemiological 20 studies are now discussing this non-progression in 21 girls; it does happen. Unfortunately, I just had a 22 daughter that had it happen; I never believed it until 23 I saw it myself, but it is happening. The NIEHS funds 24 a study called the Breast Cancer and Environment 25 Research Centers. Within that Center there is three --FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 40

1 Mount Sinai, University of Cincinnati and Kaiser 2 Permanente in San Francisco -- that are evaluating 3 girls early in their life looking at the environmental 4 exposures, and they are reporting non-progression. 5 So this issue of extended windows of terminal end bud 6 development is not just important in the rat; it is 7 important in girls also. This leaves them susceptible 8 to increased susceptibility to another hit: a 9 carcinogen, another endocrine destructor. I can't 10 define what another hit would be; but in an animal 11 study, chemical carcinogens are known to increase 12 tumors if there are more terminal end buds present. 13 Also, the mammary gland does seem to be more 14 sensitive than other reproductive endpoints in our 15 studies, in the female at least. And that is not just 16 true in this study -- and I'm sorry it's a little hard 17 to read, and I hope you can read it on your handouts -- 18 but in a paper that has been submitted to EHP, four 19 scientists have gone through all the mammary gland 20 literature that they could find where the mammary gland 21 and any other reproductive endpoint were evaluated in 22 the same study -- and that's part of the problem with 23 mammary gland development is that not everyone looks at 24 multiple reproductive outcomes, so it's hard to assess 25 if mammary gland is more sensitive in these studies.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 41

1 But in the studies shown here, mammary gland was found 2 to be more sensitive or to need a shorter exposure 3 parameter than other reproductive endpoints to have 4 significant outcome. 5 So two of our papers, both the Enoch paper 6 and the 2005 Rayner paper, were noted. Several papers 7 on this interlay, DDT, genistein and one by one of your 8 SAP Panel members, Barry Delclos. And I just want to 9 let you know that it's not just these studies in which 10 it happens, but other studies are showing the mammary 11 gland is a very sensitive endpoint. 12 And finally, I just want to make it clear 13 that we do not know the mechanism of action for these 14 effects. We are studying that in my lab now, but some 15 of the data that is presented in the Summaries document 16 -- maybe you want to bring this to everyone's attention 17 -- and that is that I don't think we know a whole lot 18 about atrazine and oxytocin. Many of you are probably 19 much more well-versed on oxytocin than I am. But it is 20 critical in stimulation of milk ejection reflex, it 21 stimulates uterine smooth muscle contractions at birth, 22 and it establishes maternal behavior. 23 As you can see here, this is one of the many 24 studies that were done back in the '80s showing that 25 just injection of oxytocin will bring on rapid onset ofFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 42

1 maternal behavior. It's critical, and one of the 2 important things about oxytocin is that it is a stress 3 hormone; it's released from the hypothalamus. Acute 4 stress, such as food restriction, wire-bottom cages, 5 pup handling, removal just after birth, will inhibit 6 oxytocin release. If that happens, you and actually, 7 I have some examples here of things that you can see. 8 I mean, atrazine could interfere with oxytocin release 9 at the level of the hypothalamus, and this could lead 10 to decreased oxytocin, which could then cause decreased 11 milk production just after birth, which may be why we 12 saw transient declines in PND4 body weights here and 13 there and potentially in F2 study. 14 We know that it causes delayed parturition, 15 atrazine causes delayed parturition. If we dose all 16 the way up to gestation day 21, we will cause delayed 17 parturition in these animals; they will lose their 18 litters. They may or may not have undergone normal 19 birth. And this is reported by Mike Narotsky eight to 20 ten years ago in the Fischer rat. And they also put 21 this show for maternal behavior, and this can be even 22 worse if they are stressed. 23 And so I just want to leave you with the 24 thought of where we're going with our mechanistic 25 studies. The prostate and the mammary gland do seem toFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 43

1 be sensitive tissues affected by atrazine. There are a 2 lot of similarities, actually, between the prostate and 3 the mammary gland. They both develop late in the 4 fetus, they are developing in the last third of the 5 gestational period. Budding of the epithelium happens 6 just prior to birth in both tissues. And there is an 7 important role in androgens, actually, in both tissues; 8 so androgens make male mammary glands either not have a 9 port to the nipple area, not develop a nipple, or in 10 the mouse they don't have branching of epithelium at 11 all. There is also branching morphogenesis that occurs 12 primarily just before and after birth, and there is 13 also differentiation of the epithelium. 14 But the one good thing about the similarities 15 between these two is that there is a whole lot more 16 known about prostate and its branching morphogenesis 17 than there is about the mammary gland. So we're using 18 some of the information known from the prostate to look 19 for candidate genes that may be involved in regulation 20 of the effects of androgen in the mammary gland, and I 21 understand the fetal mammary gland development is going 22 to be critical to that. 23 With that, thank you. 24 DR. STEVEN HEERINGA: Thank you, Dr. 25 Fenton.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 44

1 At this point, if you will, I'd like to 2 open it up to the Panel for some questions or 3 clarification on your presentation or material that is 4 presented in the Issue Paper. 5 Dr. Akana. 6 DR. SUSAN AKANA: Thank you. 7 In your studies when you order pregnant 8 rats to come into the lab, I assume that this is all 9 their first-time pregnancy, primiparas? 10 DR. SUZANNE FENTON: Yes. 11 DR. SUSAN AKANA: And when did they 12 generally arrange for them to be shipped to your lab? 13 What gestational date are they in when they come to 14 your lab? 15 DR. SUZANNE FENTON: There were fixed 16 days that deliveries took place. We usually had them 17 in the room for gestation in 10 for an acclimation 18 period. 19 DR. SUSAN AKANA: The other question I 20 had is between your studies, did you have a difference 21 in the gavage, like once daily or twice daily, in the 22 different studies? 23 DR. SUZANNE FENTON: In the first study, 24 the Rayner 2004 paper, there was a once-a-day gavage. 25 Information that was gathered after that time caused usFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 45

1 to change our scheduled dosing to half-doses twice 2 daily. So the total for the day was the same as we had 3 given previously; but we split the dose based on the 4 morning body weight of the animals, and then we studied 5 after that. 6 DR. SUSAN AKANA: Are you willing to 7 comment on the rationale for changing to twice? 8 DR. SUZANNE FENTON: Sure, sure. We had 9 better information on the half-life of atrazine, and 10 that's really what caused us to shift this. So the 11 half-life is short, anywhere from estimations at that 12 time were from 11 to 17 hours half-life. So we thought 13 that it would be more accurate and less episodic if we 14 gave half-doses twice daily. 15 DR. SUSAN AKANA: That's true; but then, 16 of course, you have to handle the moms twice. 17 My next question is, there is some 18 literature that when you cross-foster pups mom still 19 knows her own pups, and there is more licking and 20 grooming of her own pups. So that could be a concern - 21 - well, there is the control there -- but in the 22 atrazine-atrazine litter, that litter. And did you 23 actually test within litter the cross-fostered groups - 24 - 25 DR. SUZANNE FENTON: Yes. So the beautyFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 46

1 of having her own pups tattooed and keeping some for 2 her own pups in the litter was for exactly the reason 3 you mentioned; so thank you for that comment, because 4 that's exactly why we did it. We knew exactly which 5 animals had a tattoo on their paw. Those animals and 6 the other animals within the litter were compared to 7 see if there was an effect, and we did not see any. So 8 we tested for block effect; any sort of differences 9 that could be there, we always tested for those. 10 DR. SUSAN AKANA: That's great. And 11 then I have a couple more questions but a comment. I'm 12 interested in a lot of the results that hit on 13 postnatal day 4 and 11 because, as you know, those are 14 the ends of the critical period for the hyporesponsive 15 period in the adrenal-pituitary axis, and I'm wondering 16 if you had thought about how that might impact the 17 reproductive results. 18 In other words, in a standard rat 19 litter, roughly the ages postnatal day 4 to 10, 11, 12, 20 there is a period where the pup is secreting very low 21 corticosterone, and it's thought to be a protective 22 mechanism for the development of feedback mechanisms in 23 the brain. But of course if you're not secreting as 24 much corticosterone because of this feedback 25 inhibition, that could mean that hypothalamic circuitsFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 47

1 are also vulnerable in other areas of the hypothalamus. 2 DR. SUZANNE FENTON: That's a really 3 good question, and actually not one that we considered. 4 I mean, in going forward in our mechanistic studies, 5 that is something that we should consider, and thank 6 you for your comment. 7 What we focused more on was the 8 potential for fetal programming. So it's still kind of 9 our thoughts that we may be affecting something in the 10 fetal mammary gland and the fetal prostate that's 11 changing our receptor population for the lifetime of 12 the animal or changing the responsivity to the normal 13 hormonal milieu. That's the hypothesis we were working 14 off of, but what you just suggested is interesting 15 also. So our thoughts were somewhat a little 16 different; but definitely, it's something to think 17 about. Thank you. 18 DR. SUSAN AKANA: I have three more 19 questions. I respect the subjective scoring of the 20 mammary gland development and its long validated 21 history; but have you tried a head-to-head comparison 22 of the classic method versus the imaging programs that 23 you can get on software nowadays, and how did they 24 compare if you 25 DR. SUZANNE FENTON: Yes. So now thatFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 48

1 I'm at the NIEHS in the National Toxicology Program, 2 I've been challenged to do that on a very specific 3 level. So that is something that we are doing now. We 4 are using the Holland Sprague-Dawley rat, and we're 5 looking at from gestation to day 15 out to day 70, and 6 that is exactly what we're doing: we're doing a head7 to-head comparison. 8 But again, in other studies that I have 9 performed, not talked about today because they had 10 nothing to do with atrazine, we have done that in the 11 mouse, and again single measurements do not seem to get 12 us a very good portrayal of what you actually see in 13 the scope. And we're working with a pathologist within 14 the NIEHS, Mark Cesta, and a pathologist at the NCTR, 15 John Otondras, to further evaluate what endpoints need 16 to be measured so that it does look like what you see 17 underneath the scope. So there are three of us, and 18 we're all kind of working together toward that end. 19 DR. SUSAN AKANA: I was thinking perhaps 20 of analysis with four compartments or more for each of 21 your hallmark so a combination in the genotype, say 22 four times on four different elements. 23 DR. SUZANNE FENTON: Uh-huh. 24 DR. SUSAN AKANA: Okay. My next 25 question is, I'm very interested in the lactationalFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 49

1 challenge. If I understand correctly, the mom and pup 2 3 separated for a stretch of time, reunited. You 3 measured the time before mom was allowed to latch on, 4 and 20 minutes after that you reweighed the litter and 5 there was no difference in the weight gain in different 6 litters across different treatment groups; is that 7 correct? 8 DR. SUZANNE FENTON: That is correct, 9 and that was in the F2 pups. 10 DR. SUSAN AKANA: Okay. My question 11 here, if I recall correctly in the F2 pups, they were 12 lighter in weight. 13 DR. SUZANNE FENTON: Uh-huh. 14 DR. SUSAN AKANA: So if the litter as a 15 whole gained the same amount of weight, the little pups 16 must have drank more milk. 17 DR. SUZANNE FENTON: Or more often. 18 DR. SUSAN AKANA: Or more often. 19 DR. SUZANNE FENTON: And when we found 20 the results, it was already too late to have assessed 21 that. We have not had an opportunity to repeat the 22 study to see if that's the case. It is possible that 23 they nursed a lot more often than did the pups in the 24 control group. We were not able to assess that. 25 DR. SUSAN AKANA: But is this correct:FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 50

1 the likelihood is that they had more milk in their 2 stomach at the end of 20 minutes? 3 DR. SUZANNE FENTON: I don't know. I 4 think what we could I can't directly answer that; but 5 what I can address is the fact that they gained a 6 similar amount of weight, which tells me that their 7 thriftiness was similar to control animals. They 8 didn't have a problem suckling. 9 DR. SUSAN AKANA: Uh-huh. 10 DR. SUZANNE FENTON: So why did they 11 gain less weight? I don't know. 12 DR. SUSAN AKANA: One last comment is in 13 the rat there is on day about 10 an incredible spike in 14 leptin developmentally, and it's thought to have 15 important, important roles in programming feeding 16 circuits in the brain. So there would be an incredible 17 opportunity to measure leptin in those animals that 18 they 19 DR. SUZANNE FENTON: Uh-huh. Actually, 20 John Rogers at EPA is doing some studies on fetal basis 21 of adult disease, and he used atrazine as a model 22 compound because at high enough doses you can cause 23 small decrements like 10% weight decrements in 24 offspring. So he's using like 150 or 200 mg/kg -- I 25 can't remember which one -- to cause those weightFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 51

1 decrements. And in his study, he actually saw an 2 increase in weight gain over time in those animals. So 3 in late adulthood and in late life, he saw an increased 4 weight gain in the animals. 5 So, I mean, there may be some issues 6 going on there, and we have an interest in leptin 7 because of the mammary gland. And it also impacts the 8 mammary fat pad development, and so we also have an 9 interest in that. So we will be looking at that in the 10 future. 11 DR. STEVEN HEERINGA: Thank you, Dr. 12 Fenton, and we'll make sure that the observations that 13 were made are recorded in the final report, too; so Dr. 14 Fenner may not be here for Charge Questions. 15 Dr. LeBlanc. 16 DR. GERALD LEBLANC: Gerry LeBlanc. 17 A couple of quick questions of 18 clarification. In the histological examination of your 19 slides I think you mentioned it, but I missed it. How 20 are discordant results between the two examiners dealt 21 with? 22 DR. SUZANNE FENTON: We sit down 23 together, and we evaluate them together. We talk about 24 why one might have scored one higher or lower so that 25 we can understand the perspective that each is comingFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 52

1 from. Typically, we're not more than one apart; I 2 mean, it doesn't happen very often. So there have been 3 a few instances where one of us needs to have more 4 consistency with how to score the rest of them. 5 DR. GERALD LEBLANC: So if the scores 6 vary by one or less, you use the average? 7 DR. SUZANNE FENTON: Yes. 8 DR. GERALD LEBLANC: And if the scores 9 vary by greater than one -- 10 DR. SUZANNE FENTON: Actually, if it's 11 less than one. 12 DR. GERALD LEBLANC: Okay. 13 DR. SUZANNE FENTON: If it's one or 14 greater, we sit down and talk about it. 15 DR. GERALD LEBLANC: And then you decide 16 on it. 17 DR. SUZANNE FENTON: Yeah. 18 DR. GERALD LEBLANC: And with regards to 19 the scoring, it's a qualitative measure; but I was 20 wondering within the derivation of a score, are there 21 any quantitative measures? In other words, do you 22 count limb buds or terminal buds, or do you measure 23 branch lengths or anything of that nature? 24 DR. SUZANNE FENTON: Yeah. One of the 25 things that we like to do is to get an assessment ofFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 53

1 how many terminal ends there are and then what 2 percentage of those are terminal end buds, especially 3 at weaning if this is easy to do, and a lot of times we 4 will do that. We don't necessarily report it; it 5 doesn't add anything, as it's usually consistent with 6 our score. We haven't had instances where it wasn't. 7 DR. GERALD LEBLANC: Thank you. 8 DR. STEVEN HEERINGA: Dr. Bailar. 9 DR. JOHN BAILAR: Could you say a little 10 more about the relevance of these dose levels to 11 ordinary human exposures? 12 DR. SUZANNE FENTON: Sure. The mixture 13 that we used, like I said -- and I probably didn't do a 14 great job of explaining this, because it is complicated 15 -- but we used data that was produced in Illinois and 16 North Carolina on what is actually present in ground17 and surface water. So essentially any wildlife species 18 could be exposed to this water as is, and the maximum 19 contaminant limit there was 25 parts per 20 billion. So when you added all the different 21 chlorotriazine metabolites together with atrazine that 22 was measured, it was 25 parts per billion. So that 23 essentially is what any wildlife species could be 24 exposed to. 25 We went 100, 1,000 and 10,000 higher than that, soFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 54

1 that's the actual translation: it's 100, 1,000, 2 10,000. So our high dose of atrazine metabolite 3 mixture was 10,000 times higher than what's found in 4 ground- and surface water. The lowest dose, 0.09, is 5 only 100 times higher. 6 DR. JOHN BAILAR: Thank you. 7 DR. STEVEN HEERINGA: Dr. Horseman. 8 DR. NELSON HORSEMAN: I wonder if you 9 could go back to your Slides 7 and 8 on the scoring 10 system 11 DR. SUZANNE FENTON: Uh-huh. 12 DR. NELSON HORSEMAN: and clarify 13 for us; it seems to be saying two different things. 14 DR. SUZANNE FENTON: Okay. 15 DR. NELSON HORSEMAN: In 7 it seemed 16 like a post hoc scaling within your experiment, whereas 17 in 8 it sounds like an a priori scaling based upon some 18 absolute scoring criteria. So if you could, help us 19 with that because that scoring system runs through the 20 experiments. 21 DR. SUZANNE FENTON: Sure. So once we 22 have all of our mammary gland hallmarks prepared and 23 cleaned and ready to go, we go through all the 24 controls. Someone goes through and makes a pile of 25 controls. We go through all of them. We want to knowFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 55

1 what the best developed glands look like. Then someone 2 has made a pile of the high dose, of the positive 3 control usually in our studies. 4 DR. NELSON HORSEMAN: So this is within 5 a particular experiment. 6 DR. SUZANNE FENTON: Within each 7 experiment, right. And so something that I didn't 8 mention and that is listed on here is that a lot of 9 times what we'll do is we'll take slides from a 10 previous study and put them back in with our group to 11 make sure that whatever we scored them in the previous 12 study is still what they're being scored that day. We 13 use the same strain of rat from the same distributor 14 each time so we should be able to do that, and so we 15 use that for consistency's sake. So what looks like a 16 4 in one study should look like a 4 in another. 17 But every study, we do this fresh each 18 study. Controls are defined, high doses defined so we 19 can have a 1 and a 4. Again we mix the slides, and we 20 go through the entire set, making these stacks of 21 scores, and we usually have a tray with 1 through 4 on 22 it and we just lay them out on there. Once we're done, 23 pick up each stack, every stack, and go through it, 24 make sure every 4 looks like each other, every 3 looks 25 like a 3, every 2 looks like a 2 so that when we'reFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 56

1 done, we're fairly certain that we were consistent 2 throughout, however much length of time it took us to 3 do that. 4 Then our second score within, you know, 5 we take the slides, put them all back. Someone comes 6 in and starts all over again. 7 So I don't know what the post hoc part 8 of that was, sorry. 9 DR. NELSON HORSEMAN: So within the 10 experiment, what seemed to guarantee that there'd be a 11 difference between your high dose and your control 12 group, which is different? 13 So in Slide 8, if we go to back, these 14 are not experiment-particular definitions of these 15 rats. In other words, you could have conceivably in 16 this with these criteria on their own, you could have 17 an experiment where every sample is a 4 18 DR. SUZANNE FENTON: Oh, we don't see 19 that. 20 DR. NELSON HORSEMAN: or every -- 21 well, I'm just trying to conceivably -- 22 DR. SUZANNE FENTON: Right. 23 DR. NELSON HORSEMAN: I mean, that is 24 just outside of -- 25 DR. SUZANNE FENTON: Conceivably, yeah.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 57

1 Right. 2 DR. NELSON HORSEMAN: So there's no bias 3 per experiment in the system where the morphological 4 definitions are a priori as opposed to post hoc 5 DR. SUZANNE FENTON: Yeah. Well, we -- 6 DR. NELSON HORSEMAN: kind of 7 system, that's my question. 8 DR. SUZANNE FENTON: Right. We set 9 these criteria actually, these criteria have been set 10 since we did our first experiment with dioxin. We felt 11 we had to have criteria to base this on. We do see 1s 12 in control groups. Not every control is a 4. But we 13 do try to stay on the same scale for everything that we 14 do so that we have a basis and an unbiased way to make 15 this assessment. 16 DR. STEVEN HEERINGA: I think we'll take 17 a few more questions. I just want to mention we want 18 to keep these compact here, because I will close it off 19 at 10:00; I just have to keep things moving today. 20 So Dr. Chambers, Dr. Pope. 21 DR. JANICE CHAMBERS: Two questions for 22 clarification. One is with respect to the Enoch paper. 23 It had low mammary gland scores on day 33 in the 24 controls. How did you handle that? Did you have your 25 three groups compare to that low control, then?FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 58

1 DR. SUZANNE FENTON: There were 4s in 2 that group, in that control group; there just weren't 3 very many of them, all right? And honestly, we have no 4 idea why that one group was so low. We have had that 5 happen here and there in other studies -- not atrazine 6 studies, but it's happened in our mouse studies; it 7 does happen every once in a while. We just used all 8 the data that we had. 9 DR. JANICE CHAMBERS: Okay. And the 10 other question I had, with respect to your prostate 11 data that you presented on the slides here, you had 48% 12 inflammation in the controls. Is that typical? 13 DR. SUZANNE FENTON: Most of that is 14 coming in the ventral prostate. In the Rayner paper, 15 the 2007 Rayner paper, we actually noticed this high 16 background inflammation in the ventral prostate, and 17 our pathologists were very, very thorough in this 18 evaluation. So most of the background is coming from 19 the ventral; very little in the lateral prostate. You 20 can't tell that from the percentages, but percentage of 21 animals with inflammation goes up pretty dramatically 22 in the atrazine-treated groups. 23 DR. JANICE CHAMBERS: Well, I saw that; 24 but I'm just wondering, is your typical control that 25 high in the amount of inflammation?FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 59

1 DR. SUZANNE FENTON: Yeah, in two 2 different studies we saw the same thing in the ventral. 3 DR. STEVEN HEERINGA: Dr. Pope. 4 DR. CAREY POPE: Yes, I'd like to kind 5 of repeat the earlier thought about the confusion over 6 this ranked scoring. It makes perfectly good sense if 7 you use a scale like this that's a number of the 8 animals as you see them; but to me, I'm still confused 9 about the pile as controls and now calling them a 4 and 10 calling another group as a high dose and calling them 11 1. 12 DR. SUZANNE FENTON: I think you 13 misunderstood that, I'm sorry. 14 DR. CAREY POPE: Yeah. 15 DR. SUZANNE FENTON: We looked through 16 all the controls to see what a 4 looks like; we don't 17 put them into a pile as 4s. 18 DR. CAREY POPE: I'm asking you about -- 19 DR. SUZANNE FENTON: That's not their 20 assessment. Right. 21 DR. CAREY POPE: Yeah. 22 DR. SUZANNE FENTON: So we just need to 23 know in each study what does a 4 look like, what does 24 the best developed gland look like for reference. We 25 then look at all the high-dose, assuming that thoseFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 60

1 will be our worst-case scenario. To date, that has 2 been the case. We look at what does a 1 look like. 3 Then those slides are not scored at that point. We 4 just need to know what our reference points are. 5 Those slides are then taken and mixed in 6 with everything else, scattered, we don't know what 7 they are; we go through them all one by one, and then 8 we make the stacks. And we may have treated animals at 9 the 4 group, which certainly does happen sometimes, 10 especially at the lowest doses. 11 But the stacks are made for 12 consistency's sake in the scoring; they are not made at 13 the initial look-see to see what a 4 and a 1 look like. 14 They're not done then. 15 DR. CAREY POPE: Okay. I think the 16 white paper makes a point about the hydroxyatrazine as 17 not a measurement-making metabolite; but you were 18 basing this mixture of concentration on water 19 concentrations? 20 DR. SUZANNE FENTON: Yes, sir. So 21 that's a very important point, and I'm glad you brought 22 it up. We didn't make this mixture based on what the 23 animal produces in its body; we made it based on what's 24 going to be in the water that you drink, or any mammal 25 might drink.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 61

1 DR. CAREY POPE: Okay. 2 DR. SUZANNE FENTON: So that's why we 3 added hydroxyatrazine to this mixture: because we 4 could all drink it. 5 DR. CAREY POPE: Yeah, and 6 hydroxyatrazine is approximately the same concentration 7 as atrazine, roughly? 8 DR. SUZANNE FENTON: Yeah, 20, 20% -- 9 DR. CAREY POPE: And 25%? 10 DR. SUZANNE FENTON: -- and 25%, right, 11 uh-huh. 12 DR. CAREY POPE: Yeah, okay. The last 13 thing is regarding again this ranked data and how it 14 was analyzed. It was unclear from Enoch's paper the 15 statistical approach to evaluate that kind of data. 16 DR. SUZANNE FENTON: Actually, I thought 17 it was clear in the paper. It's not clear from the 18 review of our paper or the Summary that you have in 19 your Issues document. 20 We used the dam as a unit of measure in 21 all of those studies. She, the dam, was the identifier 22 for those pups throughout the entire study, even at the 23 older time points. We did have some confusion in the 24 way we reported the end in the paper, but this data 25 analysis was done with the dam as the unit of --FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 62

1 DR. CAREY POPE: Yeah, I'm not referring 2 of the number of the pups or dams used, but how was the 3 data actually analyzed. 4 DR. SUZANNE FENTON: Using ANOVAs and 5 ANCOVAs with dams; so when we do our analyses we always 6 look for block effect, and once we're clear that 7 there's no block effect, we use the entire database and 8 run ANOVAs, which usually has done its comparison so 9 that each of them are compared back to control, and 10 this squares reporting. So in addition to the dam as 11 the unit of measure, we always consider body weight as 12 a random variable or covariant in our analyses. 13 DR. CAREY POPE: So there's no kind of 14 normalization or derivatization the day before that 15 kind of analysis? 16 DR. SUZANNE FENTON: No, sir. 17 DR. STEVEN HEERINGA: Dr. Krishnan. 18 DR. KANNAN KRISHNAN: Regarding the 19 mixture study, I just wanted to know whether there's 20 been any interpretation of these data, particularly the 21 ones at much lower doses such as 0.9 or 0.09 mg/kg 22 based on individual competence, simply meaning in dose23 response that are any thoughts of interpretation along 24 those lines since that 2007 publication? 25 DR. SUZANNE FENTON: No, sir; just ourFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 63

1 recent publication on the prostate effects that confirm 2 the low-dose effect in the prostate. We've tried. 3 Nothing there. 4 DR KRISHNAN: Then so it would be fair 5 to say that there is not a dose-response even just for 6 atrazine using this experimental design. I know 7 there's one dose that's used here under fetal weight, 8 so, dose-response. 9 DR. SUZANNE FENTON: No. So there is a 10 dose-response for the fetal weight, and we have 11 performed and submitted papers on dose-response for 12 mammary gland development with using atrazine only. 13 Didn't present that here today, because we've only just 14 submitted the work. Beyond that, no, we have not. 15 When we developed the atrazine mixture 16 slide, we didn't do this for cumulative risk 17 assessment; we wanted to know if environmentally based 18 exposures would affect the mammary gland. And, yes, I 19 think it's important to understand each of the 20 individual components; that isn't why we did the study. 21 We just wanted to know if those relevant mixtures would 22 cause an effect. 23 DR. KRISHNAN: Okay. The objective was 24 clear, right? 25 The later study material, just referringFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 64

1 to the effects on mammary gland, what were the doses of 2 atrazine used? 3 DR. SUZANNE FENTON: We used 25, 50 and 4 100. 5 DR. STEVEN HEERINGA: Dr. Legan, 6 question? 7 DR. SANDRA LEGAN: Thank you. 8 Dr. Fenton, it's clear from what you've 9 said you understand very well about not stressing the 10 animals, and with regard to that I wondered in looking 11 at one report of your serum for prolactin models, you 12 say -- I think it's in the 2005 paper -- and this was 13 taken from samples obtained I guess at necropsy, 14 because you did all the hormone levels and you need a 15 lot of sample to do that. And you have a really large 16 range in some of your hormone levels, and prolactin was 17 I thought a very high range; and prolactin is a stress 18 hormone, and I'm wondering 19 DR. SUZANNE FENTON: Uh-huh. 20 DR. SANDRA LEGAN: and it also varies 21 with time of day and for the period of dependence. So 22 did you do necropsy on a given postnatal day at the 23 same time of day, or how did you do it -- 24 DR. SUZANNE FENTON: Good question, good 25 question. So this is what we did for all the studiesFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 65

1 that I talked about today. In the EPA Building, we 2 have a very nice animal facility that has a holding 3 room just across the hall that's a quiet room, closed 4 door, that the animals are being moved there the day 5 ahead of necropsy. We would walk across the hall with 6 a plastic decapping cone, place the animals in there, 7 and they were decapitated within 20 to 30 seconds based 8 on the technical person that's doing a count. I hope 9 that's a fair estimate, 20 to 40 seconds, something 10 like that. And so we made every effort to keep the 11 noise down, to keep the stress down, to very quickly 12 euthanize the animals. So we took every precaution 13 that we could to minimize that stress, any stress. 14 DR. SANDRA LEGAN: So do you think -- 15 DR. SUZANNE FENTON: Also -- oh, sorry. 16 You had a second part of that question. 17 DR. SANDRA LEGAN: All right. 18 DR. SUZANNE FENTON: So the time of day 19 was similar for all the studies. We typically started 20 between 8:00 and 9:00 in the morning, typically ended 21 around 2:00 or 3:00 in the afternoon. We tried to kill 22 the animals in rotating order so that you're not 23 killing all your controls first or something like that. 24 We do controls, treated, controls, treated all through 25 the day.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 66

1 DR. SANDRA LEGAN: Okay. So do you have 2 any idea why you had such a large range in prolactin? 3 Is it always that much? 4 DR. SUZANNE FENTON: No. I think we had 5 prolactin measures in more than just that one study, 6 and so taking it one study at a time, I'm not sure I 7 can answer that; but generally, we found prolactin 8 levels that were typical prolactin levels, that were 9 comparable to looking normal that we find, I think. 10 Did you feel like they were out of range of normal? 11 DR. SANDRA LEGAN: Well, the range, I 12 don't measure prolactin and I don't remember the 13 normal; but you mentioned in the paper that there were 14 wide ranges, and I looked and it was from 20 to 144, 15 and that seems like a really large range to me. And 16 I'm not familiar, as I said -- 17 DR. SUZANNE FENTON: And without having 18 that in front of me, I can't answer it specifically. 19 DR. SANDRA LEGAN: Okay. Just wondered. 20 DR. SUZANNE FENTON: But we have 21 measured it in other studies. You know, we try to take 22 care to interpret that data and say whether or not it 23 was within normal range. 24 DR. SANDRA LEGAN: Yeah, well, other 25 studies also have shown, some of them show increases inFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 67

1 prolactin, some of them show decreases in prolactin; so 2 there's something I don't understand about prolactin. 3 DR. SUZANNE FENTON: Yeah, more than 4 likely it's a necropsy data-specific event. 5 DR. SANDRA LEGAN: That's why I asked. 6 DR. SUZANNE FENTON: Yeah, right. 7 DR. SANDRA LEGAN: Thank you -- and one 8 last thing. In one of the papers, you look at 9 postnatal day 58, I think it is, and if you look at 10 mammary gland development and there's no difference 11 from controls in any of the dose groups -- or is there? 12 I can't remember. 13 Okay, this was only the 100-dose paper, 14 the '04. So my impression from reading the papers was 15 that these changes that occur that you see in mammary 16 gland development are transient. So they may be 17 delayed in early adulthood; but, you know, some time 18 after that like day 58 or something or maybe later, the 19 mammary glands look normal. 20 DR. SUZANNE FENTON: Well, yeah. Is 21 this a -- 22 DR. SANDRA LEGAN: That's all, I just 23 wanted to hear what you is that a reasonable 24 conclusion, or is that through 25 DR. SUZANNE FENTON: In one study --FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 68

1 DR. SANDRA LEGAN: the transient 2 effect of atrazine? 3 DR. SUZANNE FENTON: In one study, we 4 carried these animals out to like 90 days old. I mean, 5 it wasn't even a study; we just wanted to know what 6 would happen if we kept them longer. And 7 unfortunately, it's very difficult to do a whole mount 8 at 90 days. It's difficult to look at, and it's hard 9 to clear the fat pad; so I can't show you that. But I 10 think that this is not permanent for the life of the 11 animal. I think that small changes that take place 12 each cycle probably compensate for whatever happened 13 early in life over time. 14 But in this study, in the critical 15 period study, the Rayner 2005 study, we do have 16 dramatic effects on differentiation on these terminal 17 end buds after a 7-day exposure or a 3-day exposure. 18 So these are 67-day-old animals, so it's possible that 19 although we didn't see the persistence in the paper 20 that you're referencing -- again, I don't have it in 21 front of me, I'm sorry -- but we do definitely see an 22 increase in terminal end buds and lack of 23 differentiation in the exposed animals in this other 24 critical period study, and that I mean, we were able 25 to then breed the siblings to this and show that thereFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 69

1 was an impairment in lactation or weight gain in the 2 offspring or serious lactational effects. 3 So based on that, if you see the 4 differences at that point, I think they can translate 5 to an adverse effect. But I do agree that this is not 6 a persistent compound. 7 And one thing I didn't mention today is 8 that in our F2 pups, we did see decrements in mammary 9 gland development; but that was not significant once we 10 based it on their body weight. Because they were 11 smaller, we disregarded that change. 12 DR. SANDRA LEGAN: Uh-huh. 13 DR. SUZANNE FENTON: So that is a really 14 important consideration, and it's possible that these 15 are not permanent effects but that they were made 16 persistent until sexual maturity. 17 DR. SANDRA LEGAN: Right. And finally, 18 the atrazine isn't continually administered throughout 19 their postnatal life. 20 DR. SUZANNE FENTON: Right. 21 DR. SANDRA LEGAN: So if it is 22 transient, it may be because of the exposures. 23 Thank you. 24 DR. STEVEN HEERINGA: One last question 25 before we take a break from Dr. Mumtaz.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 70

1 DR. MOIZ MUMTAZ: I am Moiz Mumtaz, 2 ATSDR CDC. 3 Two quick questions. One, regarding the 4 parent complement of the metabolite and the fact that 5 most metabolites could be a common topic from other 6 compounds, is there any feel you have about 7 administered dose versus what could be there in terms 8 of either the concentrations of the proportion after 9 you perform these tasks? 10 DR. SUZANNE FENTON: Yes, that's a good 11 question. So it is true that other chlorotriazine 12 metabolites do produce three of these similar 13 metabolites, or chlorotriazine herbicides produces 14 three similar metabolites. That's one of the reasons 15 that we wanted to evaluate that mixture: because it 16 didn't just come potentially from one herbicide; it may 17 be coming from a family. 18 At the time we did these studies, we did 19 not have anyone that could measure internal dosimetry 20 for us. Since then, we have carried out two studies to 21 evaluate dosimetry of these exposures, both of the 22 mixture and of the parent compound, in pregnant and 23 lactating animals. 24 Those data have not been released from 25 the CDC, because the person who did the study left theFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 71

1 CDC. They are going back through another quality2 assurance check to make sure that they can be released. 3 So hopefully, I will have that information for you 4 before the spring. 5 DR. MOIZ MUMTAZ: That's great. Risk 6 assessors always depend on weight of evidence, and if 7 you look at the way the species handle, you could get a 8 little more comfortable with it. But what's your view 9 about that being a good model for this particular 10 endpoint? 11 DR. SUZANNE FENTON: Yeah, that's a very 12 good question. So last year in November, I chaired a 13 session on mammary gland evaluation and risk assessment 14 in Oakland, California. We brought together 70 experts 15 in the field of both risk assessment and mammary gland 16 biology, and we had a round-robin assessment. It was 17 really double-blind. 18 There were seven labs chosen from around 19 the world to evaluate a set of slides from both rats 20 and mice. One of the compounds we used for this 21 assessment was atrazine. We used 100 mg/kg of atrazine 22 just as a model compound in both rats and mice. We 23 gave the sets of slides to all seven labs. They were 24 asked to evaluate the slides in whatever fashion they 25 saw fit. I didn't tell them how to evaluate theFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 72

1 slides, but the slides were prepared the same way for 2 all the evaluations in one place. 3 So what happened at the end of that, we 4 had a round-robin evaluation at the workshop, and 5 atrazine was shown to have significant delays in both 6 rats and mice on day 21 in five of seven or seven of 7 seven of the evaluators, and then at day 45 in mice in 8 seven of seven evaluators. So no matter which way they 9 evaluated the glands, whether it was using morphometry 10 or whether it was using a subjective-scoring situation 11 -- and both were used almost equally -- it didn't 12 matter how they evaluated it; everyone saw the 13 developmental delay in both rats and mice at 100 mg/kg 14 of atrazine. And this work is going to be published 15 soon. 16 DR. STEVEN HEERINGA: Thank you very 17 much. 18 DR. MOIZ MUMTAZ: I do, I do want to 19 acknowledge the real life mixing in your type of test. 20 Ideally it's great to have a hypothesis to say it's 21 additive or realistic; but working from the public22 health perspective, I think it's a great deal of effort 23 to do something that's a real life mix. Thank you so 24 much. 25 DR. SUZANNE FENTON: Thank you.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 73

1 DR. STEVEN HEERINGA: I am going to 2 thank Dr. Fenton for her presentation and the Panel for 3 the questions; I think there probably are a few 4 remaining questions. 5 Dr. Fenton, are you here today, or are 6 you returning to-- 7 DR. SUZANNE FENTON: All day. 8 DR. STEVEN HEERINGA: Okay. 9 DR. SUZANNE FENTON: I'll be here all 10 day. 11 DR. STEVEN HEERINGA: All day; okay, 12 very good. And so again, if a Panel member has the 13 opportunity to speak to you and there's any information 14 that's brought forward that would influence your 15 comments, please acknowledge that conversation. 16 But at this point in time, I'd like to 17 call a 15-minute break and, if we could, reconvene at 18 25 minutes after 10:00. At that point in time, we'll 19 have a short period of closure with the scientific 20 presentations and then turn to the public comment 21 period, and I believe that the, in order that the 22 office has scheduled the public comments, I think the 23 first session will be a fairly long session dedicated 24 to the Registrant. And so if Syngenta and that team 25 would like to get set up during the break, that wouldFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 74

1 be great. 2 ( WHEREUPON , a recess was taken.) 3 DR. STEVEN HEERINGA: Welcome back, 4 everyone, to the second half of our Wednesday morning 5 session on the FIFRA Science Advisory Panel meeting on 6 the topic of the Re-Evaluation of Human Health Effects 7 of Atrazine: A Review of Non-Cancer Effects and 8 Drinking Water Monitoring Frequency. 9 I have spoken with Steve Bradbury, and I 10 understand that I mislabeled Steve's title. He 11 actually is the Director of the Office of Pesticide 12 Programs; acting in some capacity, I'm sure, but he is 13 the Director. 14 [Laughter.] 15 DR. STEVEN HEERINGA: So at this point, 16 the EPA has indicated to me that they are satisfied at 17 this point that the points that they'd like to bring 18 across have been made, and we will have the opportunity 19 at the start of the Charge Questions for clarification. 20 And in the interest of time, I think 21 we're ready to move on to the period of public comment, 22 and the first scheduled public commenter is Syngenta 23 Crop Protection. And I think that Dr. Janis McFarland 24 will coordinate the introduction of the presenters. 25 I believe the way that we'd like toFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 75

1 handle this, this is likely to be a multipart 2 presentation covering the different aspects of the 3 white paper and the topic at hand. We are scheduled 4 for 2 hours and 15 minutes, according to the SAP 5 Office. We will go up to lunch; we may break at lunch, 6 and I will work with you to sort of find a logical 7 breaking point. I don't expect that we could push it 8 all in before lunch and return. 9 So, Dr. McFarland, I'll turn it over to 10 you. 11 DR. JANIS MCFARLAND: Okay, thank you, 12 Mr. Chairman. I'm Janis McFarland, I'm the Head of the 13 Regulatory Affairs Department for Syngenta for the 14 NAFTA Region, U.S., Canada and Mexico. It's an honor 15 to be here today. 16 As my background, I started about 24 17 years ago as a metabolism chemist and throughout my 18 career have worked on many different pesticides and 19 been involved in various aspects of the science 20 regulation and stewardship of atrazine since late 1994. 21 On behalf of Syngenta, I'd like to 22 express our sincere appreciation for all of the hard 23 work and deliberation and science that's been 24 progressed and understanding by both the Science 25 Advisory Panels on atrazine as well as the work fromFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 76

1 the Environmental Protection Agency. 2 We are really excited about the work 3 we're going to be presenting today. There has been a 4 lot of progress in the areas of basic research and Mode 5 of Action. 6 And before we go into that, we did feel 7 that there was an underlying question that was actually 8 missing in some of the Charge Questions, and that had 9 to do with the assessment with the EPA making the 10 determination in Charge 6 of whether or not there is a 11 new risk assessment needed for atrazine, and also then 12 whether or not monitoring should be modified. 13 We felt that the area that was not 14 included that we would love to have advice from the 15 Panel and also additional advice from EPA would be 16 given weight of evidence of atrazine, the comprehensive 17 database as well as the state of the new science and 18 the basic research, is there a need to look at a 19 shorter exposure duration and, if so, type of -- the 20 shorter duration study, and if so, what type of study 21 should be designed or conducted to look at that shorter 22 exposure duration study. 23 We feel that the Cooper 2010 study with 24 the 4-day long evidence, intact long evidence study 25 that has been proposed for the new point of departure,FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 77

1 we do realize provides very important information on 2 Mode of Action, basic research for atrazine; but we do 3 not feel that the study design is appropriate to 4 actually establish a point of departure. 5 We did put some of our initial 6 assessments and analyses of that study design in the 7 Docket yesterday, and it's under a Sielken & Associates 8 paper, and we also in the Docket today along with our 9 slide presentations have put in some information to try 10 to address some background information asked by the 11 Panelists yesterday. Some of that has to do with a 12 quick summary of metabolite exposure levels in water; 13 also, a statistical study of how robust -- when we have 14 about 300,000 samples of raw and finished and non15 drinking water samples and drinking water samples in 16 the atrazine database, and you look at either the raw 17 intake that could serve as drinking water or the 18 finished drinking water, what is the statistical 19 robustness of being able to estimate a peak. And we 20 feel very confident that the studies and comprehensive 21 databases are robust enough to actually estimate the 22 peak centile. 23 We also have, when we look at the 24 maximum levels ever -- and we started voluntarily 25 monitoring with frequent monitoring; we voluntarily didFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 78

1 that for ten years prior to working on study designs 2 and monitoring programs with EPA in 2003, and we 3 generated almost 50,000 samples with that. We feel 4 very confident that no single maximum peak or no 5 duration, short-term duration exposure window that we 6 monitored in looking at both daily and then some 7 smaller daily sets but very frequent monitoring weekly, 8 that those maximum levels, single max daily in 4-day or 9 10-day rolling averages, have always been at levels 10 that are more than a thousandfold lower than our no11 effect levels that we're currently being regulated on, 12 which is the rapid for acute and the 6.25 mg/kg EPA 13 preputial separation study for the intermediate. 14 So we look forward to continuing to 15 progress the data and the basic research and look 16 forward to continuing to see the good progress that EPA 17 is making on the basic research, and we're looking 18 forward to telling you about that today. 19 And I wanted you to know as a company, 20 we are very committed to listening to the advice from 21 Scientific Advisory Panels and also to advice or areas 22 of uncertainty that EPA identifies and voluntarily 23 doing studies. In fact, what you'll see today is since 24 this re-review started, we've conducted more than 10 25 studies in this year in all aspects of completing theFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 79

1 breast bud development work, in basic research Mode of 2 Action, in exposure areas, immunotoxicology areas. We 3 started pharmacokinetic work, comparison between gavage 4 and feeding and what type of exposures you'll get and 5 hepatocyte work. 6 And we are grateful for Dr. 7 Breckenridge, who is our Senior Toxicology Fellow at 8 Syngenta who is leading the scientific advancements in 9 that, and you'll be hearing from him, as well as we're 10 very grateful for all of the university scientists who 11 are helping to both advise and conduct those studies. 12 We will also be hearing from Dr. Hendley 13 and can answer some of the questions on any of the 14 statistical side or metabolite exposure profiles when 15 Dr. Hendley is on at the end of our session. 16 So with that, I'm going to turn it over 17 to Dr. Breckenridge. We again thank you so much for 18 the work and look forward to the next few days of 19 deliberations. 20 DR. CHARLES BRECKENRIDGE: Thank you, 21 Janis. 22 My name is Charles Breckenridge; I'm a 23 Senior Syngenta Fellow. I have been working on 24 atrazine since approximately 1994. I'm responsible for 25 the human safety assessment of the compound.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 80

1 We have today with us a team of 2 scientists who participated in the conduct of studies 3 over the course of the last couple of years. We will 4 start with first Dr. Russ Hovey, this gentleman second 5 to my right, who will present our research on the 6 breast bud development project. 7 Secondly, then, we will actually turn 8 over to the key theme of this meeting, which is the LH 9 surge and the adverse effects associated with impacts 10 of the LH surge suppression. But to start that 11 particular discussion out, and mindful that Dr. Covern 12 last meeting in April indicated that there was some 13 differences between rodent and primate and human 14 control mechanisms, we took the opportunity to invite 15 Dr. Plant, who's an expert in this field, to give us 16 perhaps a little more clarity on those differences and 17 how they relate then to the risk assessment process. 18 Dr. Handa will continue with some of the 19 research that we elaborated last time, and it's a 20 little bit unfortunate that the Panel changes in some 21 makeup so that we cannot necessarily go back and brief 22 everyone of what went before; but Dr. Handa will try to 23 catch everybody up with what we presented in April and 24 then how we have extended that onward. 25 We will then turn to some significantFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 81

1 new work that we've conducted, and Dr. David Kim 2 from Syngenta will be summarizing this. This is PK 3 work and PBPK model development work. He is not at the 4 table at the moment, but he will join us. 5 And finally, Dr. Jim Simpkins will try 6 to put in context of adverse effect the impacts of LH 7 suppression, especially on ovarian function, but also 8 on sexual maturation in males and females and the 9 maintenance of steroidogenesis in adult animals. 10 I will close that session then, and we 11 will have one other speaker that will come up, which 12 will be Dr. Paul Hendley from Syngenta, who will be 13 discussing the water information. 14 So just so I can make certain in the 15 context of the complexity of the topics that we're 16 going to be discussing, I'm going to try to give you 17 highlighted conclusions. These are not obviously going 18 to be supported by actual data at this point, my 19 speakers will provide that; but I want you to be aware 20 of at least what the themes of the conclusory evidences 21 that we are showing here. 22 So in the first instance, you can see a 23 chemograph up in the top left panel, and we're simply 24 using this to remind ourselves -- and Dr. Hendley will 25 cover this rather extensively -- that Syngenta doesFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 82

1 have an extensive sampling data with 300,000 samples 2 approximately being well characterized, and I believe 3 Dr. Hendley will suggest some alternative strategies 4 that might be of interest to this SAP and some of the 5 Charge Questions that relate to that. 6 Secondly, then, we turn to Dr. Russ 7 Hovey, and there is no need to really extemporize on 8 the breast bud development project, because Dr. Fenton 9 has gone before and provided a description of her 10 research. 11 I guess I could just say at a high level 12 that in our hands and in an attempt to replicate some 13 of the work of Dr. Fenton, we have not been able to 14 demonstrate a breast bud development delay, and Dr. 15 Hovey will deal with that subject and present that data 16 to you. 17 Moving on, we now step back to the 18 question of the HPG and the HPA axis, and the first 19 speaker, Dr. Plant, will provide some discussion around 20 the differences between rodent, non-human primate and 21 primate neuronal control mechanisms, especially as it 22 relates to the LH surge and pulsatile generation. 23 That little cartoon up there is, you'll 24 see it reappearing in Dr. Plant's presentation, and 25 it's partially to orient ourselves to the differencesFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 83

1 in the anatomy and physiology and the functionality of 2 primates versus rodents. 3 The bottom line of that whole discussion 4 is that there is some substantial evidence to suggest 5 that the rodent model for LH surge control mechanisms 6 are not the same as in primates, and Dr. Plant will 7 elaborate on that; however, the pulsatile LH processes 8 clearly are similar, and we will discuss that in the 9 context of hazard endpoints. 10 The bottom line from that discussion 11 will actually be that perhaps the LH surge processes 12 such as we're studying in the rodent may not be 13 appropriate for modeling to human, and you'll see the 14 basis for that suggestion momentarily. 15 We will then turn back to some of the 16 basic research that Dr. Handa has conducted over the 17 course of four or five years working on Mode of Action. 18 And just to summarize what we had heard 19 in April, I believe it was fairly convincing evidence, 20 and even in work that we had not done but that had been 21 done in EPL's lab or EPA's labs, is that it does not 22 appear that the pituitary is a target of atrazine. The 23 evidence that Dr. Handa will show and Dr. Lee Tyree and 24 Dr. Cooper have presented is that the pituitary seems 25 to be responding to changes further upstream to theFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 84

1 pituitary. 2 Dr. Handa has also spent considerable 3 time characterizing the generation neurons and their 4 characteristics under LH surge suppression, and all 5 things point to that, in fact, the effects are 6 upstream to the GnRH neurons as well. And just so that 7 we orientate that, perhaps those effects are in 8 preoptic area or other regions of the brain that 9 perhaps aren't as well represented in the primate. 10 Finally, when we get to the concept of 11 interaction between the hypothalamic-pituitary axis and 12 the adrenal axis, last time, Dr. Handa presented 13 evidence that, in fact, there seems to be a role of a 14 stress response or something like a stress response 15 that at least is mediating some aspect of the LH 16 suppression in the pulsatile LH model. Insofar as we 17 have shown that adrenalectomy actually reverses, it 18 prevents the effect of atrazine on pulsatile LH, 19 whereas it does not seem to impact the LH surge itself. 20 We also note from work that Dr. Handa 21 has conducted that the surge and the effect of atrazine 22 on it recovers quickly. Within 2 days after removal of 23 the compound you get partial recovery, and within 4 24 days you get full recovery. We would like to suggest 25 that that's probably connected to the kinetic profiles,FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 85

1 which we will also demonstrate later. 2 We have turned beyond the effect on the 3 LH system to evaluating the adrenal response itself, 4 and last time you heard about atrazine activating 5 immediately corticosterone synthesis or release from 6 the adrenal gland with a very rapid ACTH response 7 accompanying that. We actually will report today that 8 we have verified that in fact, like males, by 28 days 9 the females no longer display that response; so short10 term acutely, females and males do respond acutely and 11 elaborate a cort response, which is characterized by 12 elevated corticosterone and progesterone but not 13 prolactin, and that effect appears to disappear with 14 repeated dosing. 15 We will relate that to the fact that we 16 have not been able to demonstrate any effect on immune 17 tox endpoint in both males and females; so the study we 18 are adding to the discussion we had last time is the 19 fact we have now completed a dose-response assessment 20 for females; the no-effect level is the high dose 21 tested in that study. So whatever is going on with 22 cort it's not actually having an effect, and it 23 probably is because it's a transitory response. The 24 NOAEL is 50 mg/kg on immune parameters in males and 25 25 mg/kg in females. The cartoon there is obviously wrongFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 86

1 relative to the way the cort is displayed; atrazine 2 would induce their elevation rather than decline. 3 Finally, Dr. Handa will return to the aspects of the 4 HPG axis and then set the stage for a discussion of 5 substantially new research. We were mindful of the 6 research that was described by Dr. Cooper last time 7 when he gave a few indications of the characteristics 8 of the study that he had conducted: 4 days of 9 exposure; intact females of Long-Evans rat dosed with 10 atrazine beginning on the day of estrus, leading 11 through to sampling of blood for LH on the day of 12 afternoon proestrus 4 days later. 13 We have emulated that study. We have done an 14 intensive dose-response. We have conducted this study 15 in a very short time period of approximately two weeks 16 in a random fashion. We have doses of 0.75, 1.5, 3, 6, 17 10 and 50, and we will report today that in fact there 18 are no effects on LH surge at doses of 10 mg/kg and 19 lower, and that is perhaps contributory evidence to the 20 discussion we had yesterday in relationship to dose21 response modeling and those dose ranges. 22 We took that one step further. Realizing 23 that humans don't get bolus doses of atrazine-- what 24 they get is distributed doses that they drink in water, 25 if they get any -- and so we emulated that by doing aFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 87

1 dietary feeding study, and this study was conducted at 2 three equivalent doses that matched up with our gavage 3 doses. These were attempting to achieve doses of 3, 10 4 and 50 mg/kg, and that translated to feeding levels of 5 30, 100 and 500 ppm. We report here that in fact there 6 is no effect of atrazine on the LH surge at 500 ppm in 7 young adult females animals, 13-week-old. 8 We believe that is related to kinetic 9 parameters, and Dr. David Kim will illustrate that, 10 because at the same time as we conducted the study on 11 LH surge, we had comparable animals set aside for 12 characterizing the PK kinetics of atrazine and the 13 three metabolites and Dr. Kim will elucidate that in 14 relationship to the toxicological endpoints. 15 In addition to that, these and other studies 16 will actually allow for a full elaboration of a PBPK 17 model. Dr. Tami McMullin had conducted and designed 18 and constructed a PBPK model. And I should say that 19 Syngenta was involved in funding that work, as she was 20 a graduate student at Colorado State University under 21 the mentorship of Mel Andersen. We are going to take 22 that model that she has tentatively developed and 23 extend it and enhance it. We believe that that will 24 become the basis upon which true internal dose metrics 25 can be calculated, and we also believe that it willFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 88

1 then be possible to achieve the estimation of human 2 internal dose under conditions of actual human 3 exposure. So Dr. Kim will further elaborate that. 4 Finally, we turn back to the question of, 5 well, what does LH do and how much surplus capacity is 6 there, and how much consequence is there for a one7 standard-deviation reduction in the LH surge amplitude 8 or any other aspect of LH released, and Dr. Legan 9 yesterday talked about that excess capacity. We have 10 some discussion around that. 11 And in addition to that, then, we turn to the 12 more critical question is, what is the appropriate 13 endpoint to benchmark off of. In fact, you're going to 14 set a regulatory standard. Within the context of the 15 way the Agency regulated atrazine in regard to 16 carcinogenicity, we were within the traditional 17 framework analysis; that is to say, LH suppression, 18 extension of the cycle in rodents and the development 19 of tumors. Those were key events, and they were 20 concordant with each other in dose and time. And we 21 submit that in fact that's the procedure that should be 22 followed here, with a mindful coupling of the key 23 event, which would be LH suppression, to adverse 24 effect, and this will be the subject of Dr. Simpkins's 25 discussion as it relates to all of the data that existsFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 89

1 on atrazine. 2 And actually, we heard yesterday that some 3 members of EPA thought there wasn't data adequate for 4 this purpose. We do remind the Panel that in fact for 5 the metabolites, we have conducted 90-day rodent and 6 rat studies. We have conducted all the acute studies 7 and immunogenicity studies, and EPA in fact has 8 conducted very nice studies on the metabolites and we 9 actually are going to be discussing some of that data. 10 This was Dr. Tammy Stoker's research. 11 So that there is information on the 12 metabolites, I don't believe that we can resolve the 13 question of which subcomponent is responsible. And in 14 2006 when EPA created their common mechanism group for 15 the triazine, we concurred with their decision that the 16 chlorotriazine, including other molecules that are of 17 that type, were an adequate representation of the risk. 18 We likewise believe and are in agreement with 19 the statements made yesterday that the conjugated 20 metabolites likely have no impact on the LH surge. We 21 have no actual direct evidence of that, and we probably 22 will acquire such evidence for a few of the major 23 metabolites relative to the LH surge. We do have 24 obviously differential information on that with respect 25 to aromatase, which we presented last time.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 90

1 And it was correctly stated yesterday in fact 2 there are metabolite differential sensitivities in 3 regard to, say, the activation of the adrenal axis. 4 DACT does not activate the adrenal axis. We heard that 5 from Dr. Cooper's lab and we believe that is very 6 important in the context of the kinetics, and you'll 7 see that. 8 So that's roughly what we are going to do in 9 the hazard side, and then we will return to the 10 characterization of the water. 11 With that, I'll stop, and I think probably 12 DR. STEVEN HEERINGA: Thank you, Dr. 13 Breckenridge. And I think just so that we're all on 14 the same page, because of the number and sort of depth 15 of many of the public comments in contrast to the way 16 I've managed this in some of the other meetings, I'd 17 like to go through the initial presentations, 18 particularly related to the toxicological effects, and 19 then we'll have a series of questions which will cover 20 those presenters, if that is satisfactory with the 21 Panel members. We will then turn to the water-sampling 22 issue probably after lunch and have questions on that. 23 If we can divide it up that way, I think that would 24 save us some time. 25 DR. CHARLES BRECKENRIDGE: Okay, thankFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 91

1 you very much, Mr. Chairman, and I'll ask Dr. Russ 2 Hovey to identify himself. 3 DR. RUSS HOVEY: Good morning. My name 4 is Dr. Russ Hovey from the University of California at 5 Davis. 6 Can I please ask for the first slide, 7 sir, to be posted? 8 So I'm an Associate Professor with a 9 specific interest in mammary gland development and 10 lactation physiology, and I'm in Animal Science with an 11 appointment in the UC Davis Cancer Center. 12 So what I'd like to do this morning is 13 speak to you about some work that we've done looking to 14 try and understand, based on some previous work that 15 Dr. Fenton presented this morning, about possible in 16 utero exposure effects of atrazine on subsequent 17 mammary gland development in the Long-Evans rat. This 18 is work that is currently under review at Toxicology 19 Sciences. This is a collaborative study that was 20 supported by Syngenta. The animal side of the work was 21 conducted at WIL Research, the pathology and analysis 22 was done by EPL and statistical analysis by Sielken & 23 Associates. 24 So what I'd like to do is briefly 25 describe to you the stages of mammary glandFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 92

1 development, and one of the things I point out -- it 2 seems like the slide doesn't conveying it properly -- 3 but in the top left, the mammary gland originally 4 develops from the epidermis during embryogenesis, and 5 so the epithelial cells actually arise from the 6 epidermis and invaginate into the surrounding 7 mesenchyme. 8 And then the next slide on the right 9 would have shown you that during postnatal development 10 by prepuberty, as mentioned this morning, the ductal 11 development is concentrated around the nipple and is 12 positioned to advance to be a different process of 13 ductal elongation into the surrounding mammary fat pad. 14 And so in essence the mammary gland is a secondary 15 reproductive organ, in that its development is 16 coordinated with what you would see here during puberty 17 is the ductal extension and branching morphogenesis 18 actually occurs with the onset of ovarian function. 19 And so by the time of sexual maturation, 20 this is a whole mount depiction of the mouse mammary 21 gland; in the rat, you would see more lobular 22 development. But the point to be made here is that the 23 mammary gland is developed fully; it's undergone 24 branching morphogenesis and ductal elongation. 25 Now, having said this and as I pointedFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 93

1 out, because the mammary gland is responsive to a 2 variety of different external influences throughout the 3 body, it's important to take into account that 4 development or function of the mammary gland, even in 5 the dam, can be influenced by her metabolic state, for 6 example, and her nutrition. And then in the progeny, 7 the course of mammary gland development likewise can be 8 influenced by factors such as nutrition, reproductive 9 development, as well as changes in the endocrine axis. 10 And as Dr. Fenton mentioned this 11 morning, a recent gathering of a variety of experts in 12 the field pointed out that if the mammary gland is to 13 be used as a tox endpoint, there's a lot of different 14 things that we need to pay particular attention to in 15 terms of making that type of analysis. This is a brief 16 review of some of those points, some of which are 17 specifically relevant to the work I want to present 18 today. 19 In our analysis, we have used the fourth 20 mammary glands. One particular point of emphasis was 21 that both histological and morphological analysis is 22 imperative for this type to work, quantitative 23 assessment of that morphological analysis is required, 24 and the things like reproductive development such as 25 stage of the estrus cycle needs to be taken intoFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 94

1 account. 2 Dr. Fenton mentioned taking into 3 consideration body weight as a covariant. I would 4 suggest, based on work 50 years ago, that needs to be 5 metabolic body weight, and adequate numbers of animals 6 need to be analyzed. 7 So in terms of revisiting this question 8 as to whether there's any in utero exposure effect on 9 subsequent mammary gland development, there's five 10 points that I'd like to bring to your attention based 11 on our previous work that's been done on this topic. 12 The first is, as has been mentioned 13 previously, that maternal dosing with atrazine can have 14 significant effects on maternal body weight. So this 15 is excerpted from Rayner, et al., 2005. You can see 16 there the maternal. The control dams, for example, 17 dosed between days 13 and 19 gained about 80 grams, 18 whereas dosing dams during that same period with 100 19 mg/kg of atrazine suppresses body weight gain by about 20 50 percent. Now, that's going to have significant 21 effect both on her ability to support the pups during 22 fetal development but also during lactation. And it 23 has been well acknowledged in the literature that a dam 24 will support normal fetal birth weight of her young 25 such that there won't be a difference, but her abilityFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 95

1 to support those pups during lactation will be severely 2 compromised. 3 So in our study, what we've done to 4 account for this is to actually use a pair-feeding 5 approach, whereby we pair-fed dams through the body 6 weight gain that was accomplished by the dams dosed 7 with 100 mg/kg of atrazine. 8 Another point with respect to this whole 9 morphological analysis of the mammary gland, it's 10 absolutely imperative that one carefully sample the 11 mammary glands in terms of making this morphological 12 assessment. 13 And so depicted here is images from the 14 previous studies that have been conducted regarding in 15 utero exposure to atrazine. What I'd like to bring 16 your attention to is the fact that if you are to make 17 any type of assessment of the mammary glands, it's 18 important that the whole structural network needs to be 19 intact. 20 And so my boxed areas here highlight the 21 fact that there has been some omission of certain parts 22 of the mammary tissue, and that can really have effects 23 both on quantitative as well as subjective analyses. 24 And so in our study, we have blindly removed any 25 samples that did not pass quality control. That led toFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 96

1 the omission of about 10% of samples. 2 The other thing that was previously 3 mentioned was the fact that maternal dosing with 4 atrazine can also affect aging of vaginal opening of 5 the offspring. 6 As a result, I mentioned previously the 7 mammary gland is responsive to reproductive function; 8 so what we hypothesized was potentially that this delay 9 in vaginal opening in the progeny born to the dams 10 dosed with atrazine may have actually explained the 11 delay in mammary gland development that was previously 12 described. 13 And so the way we have accounted for 14 this is to sample progeny both at a fixed age, as has 15 been done previously and is widely done in the field, 16 but then also to sample daughters of progeny at the 17 same reproductive state, namely, to include a group 18 where we sample those animals at vaginal opening. 19 We have had some previous discussion 20 about the pros and cons of subjective analysis of 21 mammary gland development, and so in terms of using a 22 subjective scale, these are both samples that would 23 receive a score of 4.0 in the previous work based on 24 their matching corresponding groups, and we felt that 25 in this type of work it is absolutely imperative thatFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 97

1 all types of analyses need to be quantitative, taking 2 into account the methods that might be able to describe 3 any phenotypic changes. 4 And then finally in terms of looking at 5 any potential changes, another approach that's widely 6 utilized is to look at self-proliferation; in this 7 case, this is an analysis of early uptake in that 8 previous work. And in that work, it was previously 9 suggested that there's a significant difference in 10 terms of self-proliferation when it was subjectively 11 analyzed in terms of the early uptake. 12 But then subsequently when that was 13 actually quantified, there was no significant 14 difference. And so in our approach, what we have 15 sought to do is specifically quantify self16 proliferation and, consistent with what was found from 17 the round-robin discussion group, we have broken that 18 proliferation down into various important compartments 19 of the mammary gland, whether they be ducts, terminal 20 end buds or lobules. 21 So this is our experimental design. In 22 essence, we followed that that was implemented by 23 Rayner, et al., in 2005, and we used time, pregnant 24 Long-Evans rats, dosed them with either vehicle 25 control, low, medium or high doses of atrazine at 6.5,FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 98

1 50 and 100 mg/kg/d between gestation day 13 and 19. 2 And as I mentioned, we also yoked a pair-fed group to 3 the highest dose of atrazine such that their intake was 4 controlled for that or yoked that consumed by the high5 dose group. 6 I'd point out that we had additional 7 animals in separate groups that were not involved with 8 these groups that we sought to do a cross-foster study 9 to try and account for any lactational exposure, and 10 cannibalism led to the omission of those animals; but 11 that was in separate groups within this study. 12 This is the maternal body weight change 13 both during gestation and lactation in those dams. So 14 on the Y axis, we have body weight change during the 15 respective period, and then the different treatment 16 groups on the X axis. 17 The light purple bars reflect the body 18 weight change during gestation, and as you can see and 19 as we expected, the high doses of atrazine led to a 20 significant suppression in maternal body weight gain, 21 consistent with previous reports. And as we planned or 22 expected to see, the pair-fed group also had a 23 suppression in body weight gain that was comparable to 24 that seen in the high-dose atrazine group. 25 And then in the darker bars this isFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 99

1 their body weight change during lactation, and you can 2 see that there was no significant difference in terms 3 of body weight change during lactation in the different 4 treatment groups, although the pair-fed group during 5 gestation had a small but significant reduction in body 6 weight gain during lactation. 7 This is the experimental design in terms 8 of sampling of those F1 progeny. So on the top of the 9 line, I'd just like to draw your attention to a couple 10 of different experimental procedures that were 11 performed. 12 At PND4 the litters were normalized, 10 13 equals 10. They were weaned at postnatal day 21, and 14 then from postnatal day 25 the onset of vaginal opening 15 was monitored in all animals; and then subsequently 16 from postnatal day 50 through day 72 we monitored for 17 estrus cyclicity in those progeny that were remaining 18 in the study. 19 The sampling protocol was as follows: 20 daughters, one from every litter, were analyzed at 21 postnatal days 1, 21, 33, day of vaginal opening or as 22 mature adults, and we specifically controlled for 23 reproductive state by sampling all those females at 24 diestrus and at their first diestrus after their first 25 estrus after postnatal day 58.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 100

1 And the other thing I'd point out is 2 that we sampled on postnatal day 1 specifically to try 3 and examine any changes within the mammary gland before 4 there was any significant exposure to any compound in 5 the milk, for example. 6 And so the analysis we performed 7 involved two different approaches. One was a whole 8 mount analysis, whereby we conducted a morphological 9 assessment using various quantitative criteria, and 10 then we also examined self-proliferation via BrdU 11 uptake. 12 This was all performed in an operator13 blinded fashion, and as I mentioned, all samples had to 14 pass strict quality control in terms of containing all 15 aspects of ductal structures in the whole mounts. 16 We used a variety of different 17 quantitative approaches to make these morphological 18 assessments, and what I'd like to do is briefly talk 19 you through those. And these measures were used to try 20 and specifically capture all aspects of phenotypic 21 change that might occur during postnatal development. 22 One of those measures was ductal length, 23 which is from the nipple; you can see it intact here 24 right through to the external region of the ductal 25 network. Epithelial area was characterized basicallyFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 101

1 to try and understand how much of the tissue was 2 epithelial. 3 The ductal area was polygonal assessment 4 of the entire ductal network. And then we also 5 manually tagged all end bud structures that met a 6 specific criteria in terms of their size and 7 appearance, and then that was automatically counted by 8 the computer. We also expressed a measure of 9 epithelial density by calculating epithelial area as a 10 proportion of the ductal area to try and capture any 11 changes within the mammary glands. 12 So what I'd like to do is talk you 13 through the results of the control animals; so this is 14 just looking at stage-specific changes within some of 15 these measures to validate our approach. As you can 16 see on the top left, this is the measure of ductal 17 length over time in different stages of postnatal 18 development. 19 As we would expect, there is an increase 20 in ductal elongation and extension over time, and this 21 is consistent with comparable changes in both ductal 22 area and epithelial area within the mammary glands. 23 The end bud structure, as was mentioned 24 previously, is a very unique and important structure in 25 the mammary gland, and it became apparent only afterFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 102

1 postnatal day 21, consistent with the assumption of 2 ovarian cyclicity, and was evident at all stages 3 thereafter. 4 And epithelial density, as we would 5 expect, maintained a relatively constant level 6 throughout the different stages, because it's a 7 function of epithelial area within the overall mammary 8 gland. 9 So with respect to our analysis of the 10 different treatment groups, this is now looking at the 11 different treatment groups across the X axis and the 12 various measures we made on the Y axis. We saw at 13 postnatal day 1 there is a small but significant 14 increase in the ductal length in the mammary glands of 15 progeny born to dams exposed with either 50 or 100 16 mg/kg of atrazine compared to the vehicle-exposed 17 controls. 18 And this wasn't evident in the pair-fed 19 group, suggesting that this may have been a response to 20 atrazine exposure in utero; however, there was no 21 effect in ductal length across any of the other stages 22 examined. 23 With respect to end bud incidence within 24 the mammary glands, this is depicting those measures at 25 postnatal day 21 through to adult; as I mentioned,FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 103

1 these were not detectable at postnatal day 1. There 2 was no difference in any of the treatment groups with 3 respect to the incidence of end buds at either PND 21 4 or 33. 5 What we saw is that at vaginal opening, 6 there was a significant increase in the number of end 7 bud structures in the atrazine 50 group that was not 8 present in the atrazine 100 group relative to the 9 vehicle-exposed controls. 10 This is where it is important to note, 11 however, that our pair-feeding approach was valid, 12 because we actually saw that those progeny also had a 13 significant increase in the number of end bud 14 structures per gland. And then in the adult females we 15 did not see any treatment effect. 16 Likewise, we saw no difference in ductal 17 network area. This is the overall network area in any 18 of the treatment groups of any of the ages, nor did we 19 see any difference across any of the treatment groups 20 at any of the ages for either mean epithelial area or 21 mean epithelial density. And those figures are 22 available in the Docket packet. 23 Likewise, I mentioned we analyzed self24 proliferation measures, and we classified that both 25 with respect to lobular structures, terminal end budFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 104

1 structures and ducts. And this is a depiction of the 2 image analysis, and hopefully what you can see here is 3 that the red cells are specifically dividing in amongst 4 all of these negative yellow cells; so these have all 5 been automatically tagged by the computer. 6 And the terminal end bud structure here, 7 which is highly proliferative, you can see, as we would 8 expect, there is a lot more self-proliferation. And 9 this was determined by treating animals via tube 2 10 hours prior to euthanasia and then analyzing samples by 11 invasive chemistry. 12 In the control animals, as we would 13 expect, there was maximal proliferation at postnatal 14 day 21 when the mammary glands were growing; this is in 15 terms of BrdU positivity from the ductal structures in 16 the overall mammary gland. Similarly, a high level of 17 proliferation in all the end bud structures that were 18 detected at different stages of development absent at 19 postnatal day 1, and then subsequently there was also 20 proliferation detected within the lobular structures at 21 different stages of development. 22 With respect to self-proliferation in 23 the ductal structures, at PND 1 we saw that there was a 24 small but significant decrease in the ductal structure 25 proliferation in the animals only born to the high-doseFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 105

1 atrazine dams. It was absent in the pair-fed group and 2 no difference at any of the stages of development. 3 In terms of end bud proliferation, 4 again, no significant difference in the proliferation 5 of end bud structures at postnatal day 21, 33, vaginal 6 opening. And then the variation we see in the 7 incidence of end buds here is simply a reflection of 8 the fact that those glands are so thick in those adult 9 animals that a histological approach failed to randomly 10 capture a lot of end bud structures through that 11 sampling method. 12 In terms of self-proliferation within 13 lobules, again, no significant difference at any of the 14 stages or in any of the treatment groups examined. 15 So in summary, our findings from the in 16 utero exposure to atrazine and its effects on the 17 mammary gland, we found no effect on any of the mammary 18 gland parameters examined when daughters were born to 19 dams exposed to 6.5 mg/kg/d. 20 We did observe a small increase in 21 ductal length at postnatal day 1 in the 50 and 100 22 mg/kg/d progeny that had resolved by PND 21; and that 23 this matched a small but significant decrease in self24 proliferation at PND 1 in the daughters born to the 25 high-dose group, but again had disappeared by PND 21.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 106

1 Our approach by pair-feeding was validated by 2 the fact that the increase we saw at vaginal opening in 3 the daughters born to the 50 mg/kg group was also seen 4 in the pair-fed progeny, and in conclusion our data do 5 not support previous suggestions in terms of atrazine 6 exposure in utero on an effect or delay of mammary 7 gland development in the daughters. 8 DR. STEVEN HEERINGA: Thank you very 9 much, Dr. Hovey. And at this point, again, we will 10 hold questions until we've heard the sequence of 11 presentations. 12 But, Dr. Breckenridge, if you'll 13 introduce your next speaker. 14 DR. CHARLES BRECKENRIDGE: Okay, so we 15 will proceed with our next speaker, and now we are into 16 the main core of our presentation relating to LH surge 17 and adverse effects relating to that, and Dr. Tony 18 Plant from the University of Pittsburgh will lead us 19 through some discussion on the differences between 20 rodent, non-human, primate and women. 21 DR. STEVEN HEERINGA: Thank you. 22 DR. TONY PLANT: So thank you, yeah. My 23 name is Tony Plant, I'm a Professor of OB/GYN at the 24 University of Pittsburgh, and I have used the monkey as 25 a model for human reproduction for all my career. WhatFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 107

1 I would like to do today is outline to you some of the 2 differences that exist between the regulation of the 3 pre-ovulatory surge in the rodent versus the monkey 4 versus the human. 5 So this is a schematic of the 6 neuroendocrine axis regulating the ovary, which I think 7 you're all familiar with. I'm going to focus on the 8 hypothalamus. As you know, the hypothalamus, there 9 maybe one or two thousand neurons in there that secrete 10 GnRH, gonadotropin-releasing hormone, which in turn 11 drives the pituitary to secrete the gonadotropins, LH 12 and FSH, which in turn drives the ovary, the 13 steroidogenic functions of the ovary and also the 14 gonadogenic functions. 15 So we first look at the endocrine 16 changes in at least the pituitary-ovarian components in 17 the human shown here on the left; for the monkey shown 18 in the center and for the rodent on the right-hand 19 side. 20 What is shown in the top panel of all of 21 these is the time course of LH and FSH in blood; 22 throughout the first two panels, the menstrual cycle, 23 which in the human and the monkey on average is about 24 28 days; and then for the rat, which the estrus cycle 25 is 4 or 5 days. And then the gonadal steroids below:FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 108

1 estradiol secreted primarily by the follicle, and 2 progesterone secreted by the corpus luteum. 3 So if we look at gonadotropin secretion 4 throughout the cycle, in all three species you can 5 conceptualize this as comprising a basal or steady6 state or tonic secretions through the greater part of 7 the cycle, through the greater part of the follicular 8 phase and through the greater part of the luteal phase. 9 And this is interrupted, again in all three species, by 10 this massive discharge of gonadotropin at midcycle. 11 This is the pre-ovulatory gonadotropin surge, and as 12 you know it eventuates in ovulation, again in all three 13 species. 14 The tonic secretion is regulated in all 15 three species by a negative feedback control from the 16 ovary, and the principal ovarian component in the three 17 species is estradiol; there are other hormonal factors, 18 but estradiol is the principal. This is a negative 19 feedback action, and that can be easily demonstrated by 20 ovariectomy at this stage of the cycle, which will 21 result in a profound hypersecretion of the 22 gonadotropins in all three species. 23 The positive feedback, or I should say, 24 the regulation of the gonadotropin surge, again 25 involves an ovarian component, and that ovarianFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 109

1 component again in all three species is predominantly 2 estradiol. And estradiol exerts a stimulatory or a 3 positive feedback action at the hypothalamic-pituitary 4 level. It's somewhat difficult to conceptualize how a 5 steroid has both effects, and we really don't have the 6 time to discuss that; but it is a phenomenon. 7 Now to look at the hypothalamus. So the 8 reproductive neuroendocrinologists tend to divide the 9 hypothalamus into a rostral component, termed the 10 preoptic area, which sits here above the optic chiasm; 11 so that's where the optic nerves come into the brain. 12 And then if you move back caudally into the 13 hypothalamus, you come to what we call the mediobasal 14 hypothalamus. 15 And there's a nuclear group in that, the 16 arcuate nucleus or, in the human, the analog is known 17 as the infundibular nucleus. And as you know, the link 18 between the hypothalamus and the anterior pituitary is 19 an endocrine link. 20 And the GnRH from the hypothalamus is 21 secreted into this primary plexus of a portal 22 circulation and as a secondary plexus in the pituitary, 23 and these two plexi are linked by what are known as 24 caudal vessels, which run down the outside of the 25 skull.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 110

1 So if we first view tonic secretion, 2 it's not, as you would expect from most composite data 3 that I showed you, continuous and boring. In fact, 4 it's episodic. And this is shown here not for a 5 primate, not for a rodent; this is data from the sheep. 6 And the reason I show that is that the sheep lends 7 itself to an experimental approach where the 8 experimentalist can relate directly what GnRH is doing 9 in portal blood, shown here on the lower panel, and 10 correlate that to what the pituitary is doing by 11 measuring in this case LH in the peripheral 12 circulation. 13 Now, you can see that the secretion of 14 tonic gonadotropin is characterized by these dramatic 15 episodes of secretion, which vary depending on gender 16 and hormonal status and species anywhere between 20 to 17 30 minutes to 4 or 8 hours. But they are all 18 occasioned by this discharge or GnRH from the brain. 19 Now, the mechanisms that generate this 20 pulsatile GnRH release, the neurobiology of that is 21 unclear. And we talk about the GnRH pulse generator; I 22 think I've heard that term in the last couple of days. 23 This is really a physiological construct, but we really 24 don't understand the fundamental neurobiology 25 underlying that pulsatility.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 111

1 But it is the GnRH pulse generator that 2 generates these intermittent secretions of GnRH into 3 the portal blood, which then drives the pituitary to 4 secrete the gonadotropins. And from what we know, 5 we're not aware of major species differences across 6 mammals in the mechanisms that generate this 7 pulsatility. 8 Now, let's look at the surge. And here 9 I've listed on the left the processes involved in the 10 control of the surge in some species, and here the 11 corresponding parameter for rodents, non-human 12 primates, primarily the monkey, and the human female. 13 So if you first look at the location of 14 GnRH cell bodies or the cell bodies, GnRH cells that 15 project to the median eminence and are known as 16 neuroendocrine cells, these are exclusively in the rat 17 brain in the preoptic area. In the monkey and the 18 human, they are primarily in the mediobasal 19 hypothalamus. 20 In the role of the preoptic area, so the 21 rostral aspect of the hypothalamus, it's essential in 22 the rodents, it's non-essential in monkeys, and it's 23 non-essential in the human female. 24 The site of the estrogen-positive 25 feedback -- this is the feedback that stimulates theFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 112

1 gonadotropin surge of events in ovulation -- it's in 2 the preoptic area of the rodent, it's in the mediobasal 3 hypothalamus-pituitary of the monkey, and there is some 4 argument in the human female whether the MBH is even 5 involved at all, but certainly pituitary feedback. 6 Another hallmark, a classical hallmark 7 of the LH surge in the rodent is that it can be blocked 8 by anesthesia, particularly barbiturate administered 9 just before the surge on the afternoon of proestrus. 10 This is not the case in the monkey. Deep barbiturate 11 anesthesia during the duration of the surge and before 12 does not block, and we don't know in the human; 13 experiment hasn't been done. 14 Now, the relationship to the 15 photoperiodic control in the light/dark cycle, it's 16 tightly coupled in the rodent, and it's weakly coupled 17 in both the monkey and the human. Is it associated 18 with the GnRH surge? Most definitely in the rat; also 19 true in the monkey, although it was argued for many 20 years, but it's certainly there. Whether it's present 21 in the human female is unclear. 22 And then the last aspect here, the 23 sexual differentiation of this preoptic area takes 24 place in the rodent such that the male hypothalamus of 25 the rat cannot support an ovarian cycle. This is notFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 113

1 true in the monkey -- it's not differentiated to that 2 degree -- and probably not in the human. 3 So these are some of the axioms on which 4 our understanding of the rodent surge is based: it's 5 rigidly timed, as I said, by a daily neural signal that 6 is tightly coupled to a critical period during 24-hour 7 light/dark cycle; it's relayed to the pituitary by 8 discharge of GnRH in the hypophysial portal 9 circulation; it's generated in the preoptic area or the 10 rostral part of the hypothalamus; and the positive 11 feedback action of estradiol is exerted on the POA. 12 This 24-hour plot in the rodent brain 13 was elegantly demonstrated by Legan and Karsch Sandy 14 is a Panel member here -- where she took ovariectomized 15 animals and gave them a constant level of a 16 physiological stimulus for estradiol. 17 And this estradiol implant was 18 maintained for 12 days here, and you can see that each 19 day -- this is a morning sample, a noon sample, this is 20 a sample at 1700 hours -- you can see that every day 21 the rat hypothalamus fires its 24-hour signal and it 22 leads to a discharge, a pre-ovulatory-like discharge of 23 LH. 24 This is not the case in the monkey. 25 It's a complicated slide; but if you look on the middleFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 114

1 panel here, where this is Knobil and his colleagues, 2 they have taken early follicular phase female monkeys 3 and implanted a physiological strength of estradiol 4 for, in this case -- I can't see from here -- but it's 5 12, I think, 24, 36 and 96 hours. So they're looking 6 at the effect of duration, and you can see that for a 7 surge to be induced in the monkey you have to maintain 8 this estradiol signal at a physiological level of 350 9 pg/ml for about 48 hours, and then all the animals 10 surge. 11 Now, in contrast to the rat, if you 12 increase the magnitude of this estradiol signal as 13 shown in this top left-hand panel, so now the estradiol 14 is only being imposed for 24 hours but the amount of 15 estradiol is super-physiologic, and you can see that 16 this leads to an acceleration in the surge and it 17 occurs 12 to 18 hours earlier. So it's not timed by 18 this 24-hour clock in the preoptic area that's linked 19 to the circadian system. 20 The role of the preoptic area now, and 21 that has been addressed in both rodents and monkeys by 22 a technique known as surgical deafferentation; it 23 involves the lowering of a surgical knife, known as a 24 Halasz knife after the Hungarian who introduced this, 25 so that you can surgically isolate the mediobasalFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 115

1 hypothalamus from the more rostral preoptic area. You 2 can do this either an anterior disconnection, or you 3 can make it a 360 disconnection. 4 The alternative or an additional 5 approach to study the preoptic area is, you can lesion 6 it. And here you place stereotactically radiofrequency 7 lesion into the preoptic area and destroy the preoptic 8 area in that manner. Both these procedures in the rat 9 will interrupt cyclicity and block the positive 10 feedback action of estradiol, underlying the importance 11 of this preoptic area in the rodent brain. 12 In the monkey, that's not the case. In 13 these four studies -- or, the consensus of the evidence 14 is that it's not the case, and there are four studies 15 here. The first one used a Halasz knife and a complete 16 deafferentation of the mediobasal hypothalamus from the 17 anterior; this one used a preoptic lesion; this one an 18 anterior disconnection; and here, a preoptic lesion. 19 And in three of the four studies spontaneous LH surges 20 were observed, and in those animals that spontaneous 21 surges weren't observed, many of them showed an 22 estrogen-induced surge. 23 I just show you one for time, and this 24 is a preoptic lesion. The lesion is being 25 reconstructed here on the parasagittal section of theFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 116

1 hypothalamus; so here's the landmark, the optic chiasm, 2 remember, above that lies the preoptic area, and this 3 lesion destroyed a large portion of the preoptic area, 4 including the suprachiasmatic nucleus, which sits just 5 on the optic chiasm. And you can see here, this lesion 6 had no effect on the cyclicity of this monkey LH 7 kinetic surges, follicular genesis and corpus luteum 8 and menstruation. 9 So that's led to the concept in the 10 monkey that this unit, neuroendocrine unit known as the 11 mediobasal hypothalamus-pituitary, is the control 12 system which dictates the control of the menstrual 13 cycle. And in contrast to the rodent, this region of 14 the hypothalamus is not involved. 15 So the question of whether there is a 16 GnRH surge in the primate has been now, I think, 17 unequivocally demonstrated by Steve and his colleagues, 18 and that's shown here, where they correlated GnRH 19 release in the median eminence on the top with LH 20 secretion measured in peripheral blood below. 21 And clearly, you can see there's a major 22 robust discharge of GnRH in the monkey, just as there 23 is in the rat. The duration, of course, in the monkey 24 is much longer. And this phenomena cannot be blocked 25 by barbiturate in the monkey; of course, it is in theFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 117

1 rat. 2 Now, the GnRH pulse-generating mechanism 3 in the monkey appears to turn off during the surge mode 4 of GnRH secretion. And you need to remember that 5 because the human female appears to be further removed 6 from the monkey in that regard. 7 Now, the other aspect about the pre8 ovulatory GnRH surge in the monkey is that in contrast 9 to the rodent, it's not obligatory for a menstrual 10 cycle. And that was shown here initially by the work 11 of Knobil. 12 Again, this was published a long time 13 ago. Here, a lesion has been placed into the 14 hypothalamus of a monkey that's just abolished GnRH 15 release. And so post lesion this animal doesn't 16 respond to estrogen with a surge, although you've got a 17 nice estrogen signal, and tonic levels of gonadotropin 18 are undetectable. 19 And then investigators instituted an 20 invariant pulsatile stimulation of one pulse of GnRH 21 per hour for several months, and you can see that this 22 invariant intermittent stimulation drives follicular 23 genesis and, you know, so the increase in gonadotropin. 24 The follicle here causes positive feedback and you get 25 a gonadotropin surge and you get ovulation, asFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 118

1 indicated by the pattern of progesterone, and this 2 cycle repeats until you stop the permissive infusion of 3 GnRH. 4 So here essentially there is no brain, 5 no neuroendocrine brain, in this animal; yes, it's able 6 to cycle. So you have to conclude that the site of the 7 negative and the positive feedback in this model is at 8 the level of the pituitary. There's no surge here. 9 Now, the human experiment is even more 10 compelling, because there are cases where the GnRH 11 neurons, which during embryonic development they might 12 migrate from the olfactory factor into the brain, 13 forebrain and into the hypothalamus. 14 In subjects such as Coleman's, which 15 have a genetic defect in a gene known as KOW, well, 16 this interferes with the migration of neurons; so the 17 neurons never get to the hypothalamus. So this is a 18 cleaner model than the monkey, and in several of these 19 studies -- and they are primarily by Crowley and Janet 20 Hall) in MGH, and this is some of their data -- those 21 look very similar to the Knobil study in the monkey. 22 These women that have hypogonadotropic, 23 hypogonadism due to GnRH deficiencies are treated in 24 the control group with an invariant -- and this is even 25 better studied in the monkey, because these doses ofFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 119

1 GnRH mimic the physiological GnRH and LH pulses. 2 And you can see -- I won't go over the 3 data -- but clearly, these women show spontaneous 4 cycles with this invariant stimulation; no GnRH surge 5 at midcycle, but clearly LH surges and follicular 6 genesis in ovulation. 7 In the other group, they decreased the 8 amount of GnRH being given to these women during this 9 period of -4 to 1 day around the surge, and you can see 10 that that has no impact. So they're actually reducing 11 the hypophysiotropic stimulus to the pituitary. 12 And they did that, because they had some 13 evidence based on indirect pharmacological data that 14 suggested in the human female, totally 15 counterintuitive, that the amount of GnRH during the LH 16 and FSH surge was actually reduced,. And certainly, 17 this data supports the idea that you can reduce the 18 GnRH stimulus without interfering with the cycle. 19 And then the other aspect about the 20 human female is that this pulse-generating mechanism 21 appears to continue through -- so this is the ascending 22 phase of a pre-ovulatory surge, very frequent sampling, 23 and this is the descending phase. And you can see 24 there is the beautiful pulses of LH and ALPHA subunit, 25 which indicate that this hypothalamic GnRH pulse-FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 120

1 generating mechanism is still operational during the 2 surge. 3 So just to conclude, this is my sort of 4 schema of the rodent system. So the preoptic area is 5 critical. You have this 24-hour signal gated to the 6 photoperiod, which is relayed to the suprachiasmatic 7 nucleus, and for that to be manifest you need a 8 positive feedback action of estrogen here. In the 9 presence of estrogen the gates open, the clock works 10 and drives this system every 24 hours. 11 In the monkey and, as far as we know, 12 the human, of course, the preoptic area is not 13 involved. You don't have this positive feedback to 14 that area, and that positive feedback now in the 15 primate is in this MBH hypothalamic pituitary unit. 16 And you conceptualize that the human female may have 17 evolved even further and that the extent of positive 18 feedback of GnRH surge generation in the human female 19 is diminished and perhaps is not present. 20 So I would offer you that I'm not saying 21 that the rat is a bad model; but I think the mode of 22 secretion that you are studying for human relevance, 23 the LH surge in the rodent is not relevant to the human 24 situation. 25 What is relevant to the human situationFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 121

1 is this hypothalamic GnRH pulse-generating mechanism, 2 which will permit the pituitary-ovarian axis to cycle 3 28 days and with it a pre-ovulatory surge. 4 Thanks. 5 DR. STEVEN HEERINGA: Thank you very 6 much, Dr. Plant. 7 Dr. Breckenridge? 8 DR CHARLES BRECKENRIDGE: Yes, thank you 9 very much; we will now proceed with going back to the 10 rodent model with Dr. Handa. 11 DR. ROBERT HANDA: Good morning; if we 12 could get that slide back up. 13 I'm Bob Handa, I'm a Professor in Basic 14 Medical Science and Neuroscience at the University of 15 Arizona College of Medicine. And I'll be spending my 16 time today speaking to you about our studies regarding 17 the mechanism of action of atrazine on regulating the 18 LH secretory patterns in the bag model of LH secretion 19 in the rodent model. These are studies that are in 20 collaboration between my laboratory, Syngenta and WIL 21 Research Laboratories in Ohio. 22 Basically, Dr. Plant has described the 23 hypothalamus-pituitary-gonadal axis, and so I won't 24 spend much time with that. What I would like to do is 25 review with you some of the data that I presented atFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 122

1 the April SAP and do this relatively quickly and then 2 add on to that data some of the new datasets that we've 3 accumulated over the last several months. 4 So we know that the hypothalamus5 pituitary-gonadal axis regulates reproduction in the 6 rodent. We know that this is due to a group of neurons 7 that synthesize and secrete GnRH into the portal 8 vasculature and ultimately stimulate the secretion of 9 luteinizing hormone from the anterior pituitary 10 gonadotropes. 11 And we also know based on Dr. Plant's 12 presentation earlier that LH is secreted in two types 13 of patterns, a pulsatile or episodic release where 14 increases occur regularly throughout the day in the 15 rodent -- this is approximately every 30 minutes -- as 16 well as an LH surge type of pattern, and this surge is 17 a dramatic increase in response to elevating or rising 18 levels of estrogen and, as a result, this precedes and 19 is the cause of ovulation and luteinization of the 20 follicle. 21 So our studies that I will describe to 22 you today examine the mechanism of action of atrazine, 23 and from our previous studies we have known for several 24 decades now that atrazine can reduce the LH surge. 25 These are data taken from my laboratory, showing thatFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 123

1 estrogen- or progesterone- induced surges of LH in 2 ovariectomized female rats is inhibited by several 3 different doses of atrazine given for 4 days prior to 4 examination of the LH surge using repeated sampling 5 using a jugular canula to capture the peak of the LH 6 surge. These studies also show that in a series of 7 studies looking at pituitary sensitivity, we examined 8 pituitary sensitivity to a potent GnRH agonist, DL6 9 GnRH, which showed no effect of atrazine on that part 10 of the HPG axis, and we also showed that there were no 11 effects of atrazine on GnRH mRNA levels. 12 This is very difficult to see; 13 hopefully, you can see in the upper panel some green 14 neurons as well as some red-stained nuclei, if you 15 squint real hard. This is another group of studies in 16 which we examined the possibility that GnRH neuronal 17 activation was impaired by atrazine treatment, and what 18 you can see is that we used c-Fos, which is an 19 immediate early gene that is rapidly expressed by 20 neurons when they are activated, and we can demonstrate 21 that c-Fos is expressed in GnRH neurons, about 80% of 22 GnRH neurons in control animals; and that in the 23 presence of atrazine administration for 4 days, that 24 during the LH surge GnRH neurons are unable to express 25 c-Fos, suggesting that they are less activated and alsoFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 124

1 suggesting that the site of atrazine action inhibiting 2 the HPG axis may lie upstream of the GnRH neuron. 3 Again, we also presented data at the 4 last SAP to show that if we remove atrazine from the 5 mix here and after treatment cessation and then try to 6 stimulate an LH surge, that within 2 days following 7 atrazine withdrawal that we can start to see the 8 reappearance of an LH surge in following estrogen or 9 progesterone priming, and that within 4 days following 10 removal of atrazine we can see the reappearance of a 11 full-blown LH surge, and that's shown on the left panel 12 here after 4 days of treatment cessation, and 13 accompanying that is the expression of C-Fos in those 14 GnRH neurons. And this pattern of recovery following 15 treatment cessation actually fits with the 16 pharmacodynamics of atrazine which Dr. Kim will address 17 in the next presentation. 18 Now, as I promised, I'll tell you a 19 little bit about pulsatile hormone secretion, and 20 again, as I presented at the last SAP, we can see 21 pulsatile hormone secretion, pulsatile LH secretion, in 22 the rodent by doing frequent sampling; these are 23 samples taken every 5 minutes over a 3-hour period. 24 And what you can see in the upper left 25 panel is a typical pattern of LH pulses in a rodent,FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 125

1 and what you can see is that they occur approximately 2 every 30 minutes throughout the day. These are 3 ovariectomized female rats. We ovariectomized the rats 4 in order to release that estrogen negative feedback and 5 allow us to visualize those pulses for the activity of 6 the GnRH pulse generator better. 7 And what you can see is as we increase 8 the doses of atrazine, what you can see is that the 9 pulse characteristics begin to change such that by 200 10 mg/kg atrazine doses we find that in fact the pulses 11 are delayed in their appearance, they have a period of 12 over an hour now and that in fact they are increased in 13 amplitude. 14 And these characteristics of these LH 15 pulses are accompanied by similar changes in GnRH 16 secretion, and we've measured that using an in vitro 17 system where we perfuse hypothalami and examine the 18 secretion of GnRH from these hypothalami in vitro, and 19 again the same pattern appear in those GnRH secretory 20 rhythms. 21 So based on a number of studies that 22 have been reported showing that the possibility exists 23 that other hormones may impact the HPG axis and recent 24 studies from Ralph Cooper's lab and Steve Pruitt's lab 25 that suggest that atrazine might increaseFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 126

1 corticosterone in the rodent, we embarked on a series 2 of studies to determine in fact if the effects of 3 atrazine on HP -axis function might be secondary to the 4 effects on HPA axis. 5 So at this time, then, I need to 6 introduce a second and parallel neuroendocrine axis; 7 this is the hypothalamus-pituitary-adrenal axis where, 8 very similar to the HPG axis on the right, the HPA axis 9 secretes a neuropeptide, corticotropin-releasing 10 hormone, which drives the pituitary to synthesize and 11 secrete ACTH, or adrenocorticotropic hormone, and that 12 stimulates the adrenal cortex secretion of 13 corticosterone in the rat or cortisol in the human. 14 Now, this pathway is very responsive to 15 a stressor; so applying a stressor, you see a rapid 16 induction or increase in plasma levels of 17 corticosterone. And the hypothesis is then that 18 atrazine may be working to inhibit the HPG axis by 19 activating this neuroendocrine axis and thereby 20 inhibiting this through either corticosterone, which we 21 know inhibits HPG axis, or CRH, which we know CRH 22 neurons project the GnRH neurons and have been 23 implicated indirectly in activating GnRH neuronal 24 function. 25 The design of this experiment wasFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 127

1 described again in the last SAP, and that is animals 2 were treated with varying doses of atrazine ranging 3 from 6.5 to 100 mg/kg/d, and then they were sacrificed 4 by decapitation within 30 minutes of atrazine 5 administration by gavage. 6 In this study we utilized male Sprague7 Dawley rats, and they were sacrificed after either 1 8 dose, 7 doses, 14 doses or 28 daily doses of atrazine. 9 And this allowed us actually to examine not only the 10 levels of corticosterone but a whole series of other 11 hormones, and these are listed here. I will focus on 12 the corticosterone changes today; we went over many of 13 those other changes in the last SAP. 14 So these are the results of those 15 studies looking at corticosterone, and again I will 16 just remind you that when we administer atrazine and 17 look 30 minutes later, we can see elevations in plasma 18 corticosterone after the first administration by gavage 19 of atrazine, and that this is a 30-minute period post 20 gavage. What we see is after 7, 14 or 28 daily doses 21 of atrazine that this response has disappeared. 22 Now, we see a similar response in plasma 23 progesterone in males. Plasma progesterone is 24 predominantly secreted by the adrenal in males, and see 25 a response at the higher doses following the firstFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 128

1 administration of atrazine; but again, it's gone after 2 the 7, 14 or 28 doses of atrazine. 3 We've also measured plasma prolactin in 4 the same paradigm and we see no changes in prolactin, 5 suggesting that, as we brought up earlier, prolactin is 6 a stress-responsive hormone, and this suggests that 7 this is not a generalized stress response but is 8 actually targeted to somewhere in the HPA axis. 9 Then this is data from females following 10 28 daily doses by gavage, and what you can see is there 11 are no changes in corticosterone or progesterone; so 12 again, in females it appears that that rapid response 13 following the first exposure to atrazine has 14 disappeared by the 28th exposure to atrazine. 15 So this raises the question as to if 16 atrazine is regulating the HPA axis, and certainly it 17 could be utilizing corticosterone secretion to inhibit 18 the HPG axis acutely. 19 Where in the HPA axis might atrazine be 20 working, and I proposed a number of sites again at the 21 last SAP, in which we proposed that it could be acting 22 directly on the hypothalamus as a generalized stressor 23 might activate the HPA axis; and that if it did, that 24 it would activate these CRH neurons, which are found 25 within the paraventricular nucleolus of theFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 129

1 hypothalamus, and thus we embarked on a series of 2 studies to test the activity of the PVN neurons, again 3 using c-Fos as a marker of cellular activity. 4 And I want to present the first of these 5 studies to you today, and that is that we know that 6 under non-stress conditions that there is very little 7 c-Fos expressed by neurons in the PVN. So in this 8 photomicrograph up here, you can see this is a section 9 taken through the PVN; the paraventricular nucleus is 10 this wing-shaped structure right here, this is the 11 third ventricle right there, and you can see very few 12 darkly stained nuclei in this preparation. 13 One hour following a stressor -- in this 14 case, it was a restraint stress -- what you can see is 15 the appearance of a number of darkly stained nuclei 16 within the paraventricular nucleus suggesting that 17 those neurons are activated, and this is represented 18 graphically over here in the non-stressed condition and 19 following stress. 20 And what you can see is 1 hour following 21 atrazine administration, you can see now this is a 22 blowup of that same area, the paraventricular nucleus 23 is here. And you can see a few c-Fos-positive neurons; 24 but in fact, there is no significant increase compared 25 to the 0 mg/kg treatment group.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 130

1 At the same time you can see that both 2 of the 50 mg/kg doses and 200 mg/kg doses increased 3 corticosterone secretion, and what this data suggests 4 is that if atrazine is increasing plasma corticosterone 5 levels, it is doing it downstream from the 6 hypothalamus. 7 Now, as I said earlier, we also had the 8 opportunity to measure a number of plasma steroid 9 hormones, and we did this using liquid chromatography 10 and a mass spectrometry, which is considered by many to 11 be the gold standard for measuring steroid hormones at 12 this time. 13 And what we saw was, in fact, no effect 14 of atrazine on a number of different hormones. In the 15 males, the androgen, androstenedione, testosterone and 16 dihydrotestosterone were not changed following 1, 7, 14 17 or 28 doses of atrazine. In females, the estrogens, 18 estrone and estradiol were measurable, as well as the 19 weak androgen, androstenedione, and none of those were 20 changed by atrazine administration. 21 In addition, at last April's SAP, Dr. 22 Steven Pruitt proposed that corticosterone can be 23 implicated in regulating a number of functions, and one 24 of these was immunological function; and he proposed 25 that, in fact, we would be able to very effectivelyFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 131

1 examine the consequences of elevations in 2 corticosterone by monitoring immune function, and those 3 studies have been completed. Unfortunately, Dr. Pruitt 4 is not here to present them; so I'll take a stab at 5 that, although I'm not an immunologist. 6 But basically the results can be 7 summarized in a couple of statements. In male Sprague8 Dawley rats, we see no suppression of natural killer9 cell activity or spleen antibody-forming cell responses 10 at the 100 mg/kg body weight dose. We can establish a 11 no-effect level based on thymus weight reduction, which 12 occurred at the 100 mg/kg body weight dose but did not 13 occur at the 25 mg/kg dose. 14 And in female Sprague-Hawley rats, we 15 similarly see no suppression of NK activity or 16 antibody-forming cell responses at the 100 mg/kg body 17 weight dose, nor was there an effect of this dose on 18 thymus weight, establishing the NOAEL at 100 mg/kg 19 body weight. 20 So this raises the question of in our 21 studies that although we've seen increases acutely in 22 corticosterone and that still may drive the acute 23 inhibition of atrazine on the LH surge of whether or 24 not in fact it truly is involved, and we did the study 25 to test this and that is to remove the adrenal glands,FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 132

1 the source of corticosterone, and then determine if 2 atrazine can still inhibit LH secretion either at the 3 pulsatile or the surge, the secretory patterns. 4 This is the experimental design for the 5 study we used. We had young adult female Wistar rats. 6 They were ovariectomized, and then 7 days later they 7 were cannulated in order for us to determine the 8 dynamics of LH secretion. 9 At the same time they were 10 adrenalectomized or sham-adrenalectomized, and then 3 11 days later at the same time as the adrenalectomy and 12 cannulation, we began then on a paradigm of atrazine 13 administration by gavage, and you can see 200 mg/kg 14 body weight or 50 mg/kg. 15 Sampling occurred then 3 days later, and 16 in the absence of estradiol-priming to visualize pulses 17 of LH or we treated them for 3 days with estradiol and 18 then examined estradiol and progesterone, and then 19 examined the LH surge in these animals. 20 So I'll submit to you the effects of 21 adrenalectomy on pulsatile hormone secretion in these 22 ov'eced female Wistar rats. What you can see is in the 23 upper left-hand panel, the typical pattern of LH pulses 24 that you see following atrazine administration, and 25 this is in the atrazine-treated, sham-adrenalectomizedFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 133

1 animal, and you can see these high-amplitude pulses, 2 which occur less frequently than normal. 3 And when we do the same examination in 4 animals that were adrenalectomized and atrazine5 treated, what you see is that atrazine has very little 6 effect on those animals and that, in fact, the 7 adrenalectomy returns the pattern of LH pulses back to 8 that of the control. 9 This is represented graphically down 10 here, in which you can see an increase in pulse 11 amplitude and an increase in pulse period in the sham 12 animals, whereas this is reduced to the control levels 13 in adrenalectomized animals, suggesting that at least 14 for pulsatile hormone secretion, corticosterone levels 15 may in fact mediate the effects of atrazine on LH 16 secretory patterns. 17 In contrast, if we look at the estrogen18 and progesterone-induced LH surge, again, treatment 19 with atrazine reduces the LH surge, the peak of the LH 20 surge, in a dose-responsive fashion, and adrenalectomy 21 has no effect on that inhibitory effect of atrazine 22 administration, suggesting that corticosterone or 23 products of HPA axis are not involved in atrazine's 24 effects in blocking the LH surge. 25 So a few key points to remember before IFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 134

1 go into some of the newer studies that we've performed 2 over the past few months, we know that high doses of 3 atrazine can inhibit the HPG axis and at the same time 4 that they can activate the HPA axis. 5 We know that the HPG axis effects of 6 atrazine are transitory, and they're reversed after 7 cessation of treatment. And similarly, we know that 8 the HPA axis effects disappear by 7 days of exposure in 9 the male and by 28 days of exposure in the female; we 10 have yet to do the 7- and 14-day doses in the female. 11 We also know that some effects of the 12 HPG axis are secondary to changes in the HPA axis, such 13 as the pulsatile secretion of LH. But the induction of 14 the LH surge does not seem to be one of these that are 15 a consequence of changing HPA axis activity. We also 16 know that there are no effects of atrazine on androgen 17 levels in males or on estrogen levels in females, again 18 using LC/MS/MS. 19 We know that there no effects of 20 atrazine on immune function in males or females, and we 21 believe that the effects of atrazine on the HPG axis 22 are mediated centrally, whereas the effects on the HPA 23 axis seem to be mediated peripherally. 24 Okay. So let's return to examining the 25 HPG axis and some parameters of how atrazine might beFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 135

1 altering LH surge. This study is here just to remind 2 me to tell you or to remind me to describe the way that 3 atrazine inhibits the LH surge. These are animals, 4 young adult female Sprague-Dawley rats. 5 We in this case have induced an LH surge 6 by ovariectomy and then hormone-priming, in this case 7 with just estrogen, and you can see there is very nice 8 increase in LH in the afternoon following 3 days of 9 estrogen administration. In this case, estrogen was 10 administered by implanting a pellet of estradiol 11 similar to that that Dr. Plant showed you where we find 12 a daily afternoon increase in LH. 13 If we administer atrazine for 4 days 14 prior to sampling, what we see is that it can inhibit 15 the LH surge, as shown in the blue bars; and again, we 16 can represent this by examining the peak LH regardless 17 of time or the area under the curve, and in both cases 18 they're significantly suppressed. 19 So we embarked on a series of studies. 20 This was described yesterday in one of the talks, and 21 this is a series of studies in which animals were 22 treated for prolonged periods of time with atrazine. 23 The upper panel shows the treatment design for Cohort 24 I, in which dams were treated with atrazine the 25 beginning of the day after finding a vaginal plug,FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 136

1 which suggests that mating has occurred; so this 2 atrazine was begun at the time of conception or shortly 3 after. 4 And they were treated continually up 5 until the time animals, these moms, were weaned, and 6 then the pups were individually treated for 2 to 7 3 weeks following until the time of puberty until the 8 time of vaginal opening. 9 Another group of animals was continued 10 on for another 16 weeks up to 133 days of age, so these 11 were extensive periods of exposure to atrazine. 12 Animals were sampled at the time of vaginal opening 13 here by giving estrogen to induce -- by ovariectomy 14 followed by estrogen treatment to induce an LH surge. 15 Another group of animals was treated from the time of 16 weaning up to the same period of time, the peripubertal 17 period. And the last group of animals was treated for 18 2 weeks' time preceding the 133-day range. 19 What I want to first describe to you are 20 these groups that were treated up till puberty, and 21 then we induced an LH surge with an estrogen capsule, 22 and this will be followed then by examination of LH 23 surges in these animals at 133 days of age. I should 24 point out there were approximately 19 to 20 animals per 25 group in each one of these treatment groups and doses.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 137

1 Basically, what you see is animals dosed 2 from conception until weaning, shown on the left panel. 3 We can see that estrogen can very nicely induce an LH 4 surge in these animals, and there is no effect of 5 atrazine on any parameters of the LH surge up to 50 6 mg/kg body weight. 7 Similarly, animals dosed from weaning 8 until the peri-pubescent period also show very dramatic 9 increases in LH and there is no effects of atrazine 10 administration, suggesting at least in these younger 11 animals that they seem to be somewhat resistant to the 12 effects of chronic atrazine treatment on LH surge 13 suppression. 14 Similarly if we look at 133-day-old 15 animals, we find that the atrazine exposure from 16 conception to 133 days of age, we find nice surges in 17 response to estrogen priming but no effect of atrazine; 18 and similarly if we look at these young adult females 19 following 2 weeks of exposure to atrazine, we find no 20 effects of atrazine on the estrogen-induced LH surge. 21 So this raises the question as to 22 whether or not these animals are not responsive to the 23 LH surge-suppressing effects of atrazine. And this is 24 a slide that was actually produced by Charles 25 Breckenridge some time ago looking at the NOAEL levelsFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 138

1 on the left on the Y axis, and duration of exposure on 2 the X axis. 3 And if we put in the 50 mg/kg dose for 4 14 days, we actually fit that line pretty well. This 5 was used, actually presented in EPA's presentation in 6 the April SAP to describe this exposure duration, which 7 we thought was exposure-duration function as a result 8 of a NOAEL and exposure duration. 9 What we would submit was that in fact 10 this does not necessarily describe the long-term 11 effects of atrazine, and if we look at this Morseth 12 paper, what we find, in fact six months of atrazine 13 exposure, they had responses or inhibitory effects at 14 fairly low doses; but, in fact, it turns out that these 15 animals were actually 9 months of age by the time they 16 were sampled, and what we know from other studies is 17 that animals at 8 to 10 months of age have reached a 18 middle-aged period where in fact the LH surge and the 19 ability to generate an LH surge is actually 20 deteriorating; so what we can actually include in here 21 perhaps is a consideration of age of animal at the time 22 of testing, which may in fact confound the results of 23 these types of approaches or modeling. 24 So the last series of studies, what I 25 want to do is back up a little bit. We know that if weFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 139

1 look at gavage dosing and we look at the ability of 2 atrazine acutely to inhibit the LH surge using a gavage 3 method, we know that in fact there does seem to be a 4 dose-response. 5 But we also know that this type of bolus 6 infusion of atrazine is probably not of physiological 7 importance when we consider the human condition, and as 8 a result we would see the plasma levels of atrazine or 9 chlorotriazines that would show this type of pattern, 10 whereas distributed dosing of the animal perhaps 11 through the diet may more closely mimic that which the 12 human is exposed to. 13 So we embarked on a series of studies to 14 examine and to compare these types of administration 15 paradigms on the LH surge in intact female rats. This 16 is the experimental design, it's very complicated; I'll 17 try and go over this with you slowly. But basically 18 what we did was used intact females that were 19 approximately 12 weeks of age, so they were young 20 adults. 21 They were monitored for estrus cyclicity 22 for at least two weeks prior to their use, and we only 23 used animals then that were showing regular 4-day 24 estrus cycles. At the day of estrus, then they began a 25 number of types of doses and routes of administration.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 140

1 The upper four groups show dietary administration at 2 three different doses of atrazine and the calculated 3 exposure level based on their food intake. And the 4 lower panels here show the doses of exposure by gavage: 5 0.75, 1.5, 3, 6, 10 and 50 mg/kg body weight. 6 Animals were monitored throughout this 7 period, and 4 days later when they were deemed to be in 8 the proestrus phase, they were sampled for LH using a 9 jugular puncture technique at four different times, two 10 that would represent, hopefully capture the peak of the 11 LH surge and one that would capture the baseline levels 12 and the post surge levels. 13 And some of these animals were then 14 continued to be monitored for use in the 15 immunotoxicology study that I presented to you earlier 16 in this presentation. 17 These are the results of those studies 18 looking at the effects of gavage treatment of atrazine 19 on the proestrus LH surge in these intact female 20 Sprague-Dawley rats. These numbers represent 21 approximately 19 to 21 animals per group, and what you 22 can see: there are significant increases over time, 23 and the highest dose of atrazine suppresses the LH 24 surge. 25 This is presented graphically in thisFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 141

1 histogram, again showing peak LH amplitude is 2 suppressed only at the 50 mg/kg dose; an area under the 3 curve similarly is suppressed only at the 50 mg/kg 4 dose. 5 Now, in the course of running these 6 studies, animals of course I told you were 4-day 7 cyclers. What we noticed is that in the highest dose 8 of atrazine administration by oral gavage, we saw a 9 significant increase in the number of animals that 10 became 5-day cyclers, and this suggested that in fact 11 we were not only inhibiting the LH surge but we were 12 having a physiological effect, in that the estrus cycle 13 was being prolonged. 14 And this raises the question as to 15 whether the drop in the LH surge that we report was 16 actually due to the fact that this group of animals 17 might have been slightly different, because they were 18 cycling at a 5-day interval. And as a result we 19 removed those and reanalyzed the data, and what you can 20 see is that in fact if we only include the 5-day 21 cycling animals, that in fact we still show the same 22 pattern of LH surge inhibition by atrazine. 23 Now, again, I told you earlier that we 24 also included a group of animals of which dietary 25 atrazine was included to try and match as closely asFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 142

1 possible the levels that we used in the gavage 2 approach, and what you can see is when we did this and 3 we examined the LH surge in the dietary atrazine group, 4 we find no effect of atrazine on the proestrus LH surge 5 in these intact female rats. 6 And this matches very closely the 7 pharmacodynamics of atrazine, and Dr. Kim will again 8 show you some of these data in the next presentation. 9 And again, examining peak LH surge regardless of time 10 and area under the curve, we find no effect of dietary 11 atrazine administration on any of these parameters. 12 So some key few points to wrap up my 13 presentation, we know that short-term administration of 14 atrazine by gavage can reduce the estrogen-induced LH 15 surge in ovariectomized females, female rats. We know 16 that chronic atrazine treatment does not seem to alter 17 the estrogen-induced LH surge when tested peri18 pubertally or as young adults, at least at doses as 19 high as 50 mg/kg body weight. 20 But we know that 4-daily doses of 21 atrazine by gavage can produce the proestrus surge in 22 intact female rats, and it can increase the incidence 23 of 5-day estrus cycles, suggesting a prolongation of 24 the cyclicity. And lastly, we know that dietary 25 atrazine exposure does not seem to alter the proestrusFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 143

1 surge of LH. 2 And all these lead to the conclusion 3 that we may need to be very careful in terms of length 4 of atrazine exposure, patterns of atrazine exposure in 5 terms of diet versus gavage when we try to infer what 6 atrazine might be doing to the LH surge. 7 DR. STEVEN HEERINGA: Thank you very 8 much, Dr. Handa. 9 DR. CHARLES BRECKENRIDGE: Mr. Chairman, 10 I believe we are perhaps running a few minutes behind; 11 but we do have one more presentation that will kind of 12 wrap up and add a pharmacokinetic component, if you 13 would bear with us to go -- 14 DR. STEVEN HEERINGA: Yes, let's go 15 ahead and do that before lunch. 16 DR. CHARLES BRECKENRIDGE: Okay, thank 17 you very much. 18 DR. STEVEN HEERINGA: Mr. Breckenridge, 19 I have a question for you. Will your full team be here 20 later this afternoon? 21 DR. CHARLES BRECKENRIDGE: Yes, sir, 22 we'll be here all day. 23 DR. STEVEN HEERINGA: Okay, because what 24 I may do is move some of the actual questioning from 25 the Panel for clarification. There is a tremendousFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 144

1 amount of scientific information that is being put out 2 here, but 3 DR. CHARLES BRECKENRIDGE: Yes, sir. 4 Okay, we'll be back. 5 DR. STEVEN HEERINGA: please go ahead, 6 Dr. Kim. 7 DR. DAVID KIM: Okay. So what I'll be 8 doing is presenting some results from three studies 9 that we conducted to characterize the pharmacokinetic 10 profile of atrazine and its chlorinated metabolites. 11 These studies were done in collaboration with 12 colleagues from the Hamner Institutes for Health 13 Sciences, and specifically Dr. Harvey Clewell and Mel 14 Andersen, both of whom were involved in the study 15 design as well as the analysis of the data and will 16 continue to work with us in developing PBPK model that 17 was referenced earlier. 18 So Dr. Rodriguez yesterday presented 19 some information, some data, on analysis of internal 20 dose, primarily total radiolabeled levels after 21 atrazine exposure at high doses, and we feel that this 22 is the right approach to take because ultimately by 23 looking at internal doses, what we are able to do is 24 better characterize the dose-response relationships, 25 and as well as reducing uncertainty in our risk-FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 145

1 assessment processes. 2 By understanding pharmacokinetics, we 3 can also explain what the internal dose is under 4 different exposure scenarios as well as use that 5 internal-dose metric profile to understand or interpret 6 toxicodynamics, which I'll be returning to later on in 7 this presentation. 8 Ultimately, all this data that I'll be 9 presenting today can be used to support PBPK model 10 development, both in terms of parameterizing the PBPK 11 model as well as optimizing the PBPK model, and 12 ultimately using that PBPK model to perform animal-to13 human extrapolations on. 14 And it was referenced yesterday that a 15 PBPK model would be the preferred approach; we agree, 16 and we will aim to have a PBPK model based on new data 17 that we are presenting here available by early part of 18 2011. 19 So the studies that I'm going to be 20 summarizing address several gaps in our understanding 21 of atrazine pharmacokinetics, primarily with regard to 22 low-dose kinetics, different routes of different 23 mechanisms of exposure, gavage versus dietary, as well 24 as the metabolic rate constants that can be used to 25 parameterize the PBPK model.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 146

1 I'll be presenting data from rat and 2 human hepatocytes; and finally partition coefficients, 3 which give us some quantitative understanding of 4 distribution of atrazine in different compartments. 5 The three studies that I mentioned are 6 as follows. The first one is an oral in vivo PK study, 7 which was conducted at WIL Research Laboratories, and 8 the analysis was done at Covance Laboratories. This 9 study dosed at three different levels by gavage and 10 dietary, female Sprague-Dawley rats, and followed the 11 internal dose over a 4-hour treatment period and 4 days 12 of washout, 4 days of treatment and 4 days of washout. 13 The second study is an in vitro 14 metabolism study where we characterize the dissipation 15 curves of atrazine formation of its mono dealkyated 16 metabolites as well as DACT formation in rat and human 17 hepatocytes, and we plan to use this data to calculate 18 clearance values. 19 Study No. 3 was conducted at University 20 of Georgia in Dr. Jeffrey Fisher's lab, where we 21 measured the distribution of atrazine in different 22 tissues, and I will present that at the end. 23 So Study No. 1, I just want to orient 24 you to this fairly complex in vivo pharmacokinetic 25 study. We had 4 days of treatment, 4 days of washout.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 147

1 During the treatment days we gave animals dietary and 2 gavage relative administration, 3, 10 and 50 mg/kg. 3 The comparable doses are 30 ppm, 100 ppm, 500 ppm for 4 the diet. We attained an actual daily dose of 3, 9 and 5 43 mg/kg body weight over the treatment day period. 6 The black dots here represent the 7 intensity of the sampling schedule. And what you can 8 see here is that on day 1 we have a very intense 9 sampling schedule; we measured plasma levels every the 10 time points were something like 5, 10, 15, 20, 30, 45 11 minutes, and we did that so that we could best 12 characterize the fast kinetics that we expected to 13 observe in atrazine. 14 On days 2, 3 and 4, the rest of the days 15 we collected, we relaxed the sampling schedule; but we 16 did collect a lot of data, and all this data will be 17 used for optimization and evaluation of the model. 18 In total, we collected 1,800 plasma 19 samples, and if you multiply by 4 we've got over 7200 20 data points that we can use for PBPK modeling. 21 The four compounds that we traced in 22 plasma over the time course are as follows; this is the 23 figure that was presented previously where the atrazine 24 undergoes oxidative metabolism into its mono 25 dealkylates, DEA, DIA and ultimately forming DACT. IFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 148

1 do appreciate and acknowledge the fact that there are 2 other metabolites; but for the purpose of this study, 3 I'll be presenting results from these four compounds. 4 So this is the raw data. There's a lot 5 of data. These curves are data points; they are not 6 model simulation-fitting data. So what we view or see 7 here is on the Y axis f plasma concentrations in 8 nanogram per mil at three different dose levels -- 3 9 mg/kg, 10, 50 mg/kg -- and then for four different 10 compounds. 11 I do want to highlight that the Y axis 12 differs by dose; it increases from 8 ng/ml to about 50 13 ng/ml, and it also increases as you go from atrazine to 14 DACT, suggesting that atrazine, the bulk of the plasma 15 samples contain DACT. 16 What we observed from these kinetic 17 curves is that atrazine DEA and DIA have very similar 18 kinetic profiles; they're rapidly formed, or absorbed 19 in the case of atrazine; rapidly converted to DEA; the 20 rapid metabolism with conversion into DACT. DACT also 21 has a similar profile, but the shape of the curve is 22 slightly different because of its slower formation and 23 degradation rates. 24 We see marked differences between gavage 25 and dietary doses. The red line here represents theFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 149

1 plasma profile from gavage; the blue line here 2 represents the plasma profiles from dietary dosing. 3 The atrazine, DEA, DIA concentrations are in the order 4 of tenfold difference between gavage and diet dosing 5 both in terms of Cmax and AUC summary dose metrics. 6 But for DACT, the difference is approximately twofold. 7 To summarize the raw data that I've 8 showed you, I have plotted here Cmax and AUC by dose 9 and we have three doses, and what I want to highlight 10 here is that four different compounds that describe -- 11 there is great difference in the concentration, the 12 dose metrics, Cmax and AUC you see between atrazine, 13 DEA and DIA; and likewise for DACT, but the difference 14 is on the order of twofold difference. 15 So I am not going to dwell on this; but 16 you have this in your handouts, and for those of you 17 who are quantitative-minded, here you go. But I do 18 want to highlight that the rats prefer to form DIA -- 19 so the concentrations of DIA are higher than DEA -- and 20 that DACT predominates in terms of mass. 21 So I want to turn your attention to the 22 second study that we conducted. This was an in vitro 23 hepatocyte study where we, on wells we introduced 24 atrazine at two different incubation concentrations, 25 0.5 and 1.0 micromolar, not in the presence of DMSO; soFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 150

1 we're looking at a system that is much more 2 physiologically relevant, as opposed to using an 3 artificial vehicle to introduce atrazine into the 4 hepatocytes. 5 We collected hepatocytes at different 6 time points. We had an intense sampling schedule early 7 on, and we relaxed it because we wanted to understand 8 the kinetic processes that are occurring, because we 9 expect atrazine to change its kinetic behavior very 10 quickly early on. 11 We compared the rates of degradation of 12 atrazine and formation of the metabolites for female 13 Sprague-Dawley rats, and we also obtained human 14 hepatocytes from a single female donor to do the 15 animal-to-human comparison. 16 So here are the results. This is for 17 0.5 m atrazine incubation, 1.0 m atrazine incubation; 18 the red line here represents data from the rat, the 19 time course profile for the rat; blue for the human; 20 you got a nanogram per mil on the Y axis and time on 21 the X axis. 22 You see that rats and humans at both 23 concentrations, incubation concentrations, atrazine 24 concentrations decreased very quickly. DACT formation 25 rates are comparable between the two species, and whatFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 151

1 we find is that there is interspecies differences in 2 terms of formation of the mono dealkylates where humans 3 prefer to form DEA, and rats prefer to form DIA. 4 And the results here, I do note that the 5 results from the human metabolism study are from one 6 individual; but the results here are comparable to a 7 recent publication that is in press by Professor Ernest 8 Hotchkins from NC State University, where he looked at 9 10 different individuals, and he looked at microsomes 10 not human hepatocytes; but he did find similar patterns 11 in form as we are observing here. 12 So again, this is a summary of the 13 metabolism study; I won't do all this, let's move on. 14 But what I do want to point out is that, as I said 15 verbally, that humans prefer to form DEA; rats prefer 16 to form DIA. 17 The final study was conducted at 18 University of Georgia in Dr. Jeffrey Fisher's lab, and 19 this study aimed to quantify the ratio of atrazine in 20 tissues versus saline solution. And this experimental 21 design was modified from previous work done by Jepson, 22 et al., and others, and it was based on a solid-phase 23 microextraction technique that really gave us better 24 analytical sensitivity. 25 Here are the partition coefficients weFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 152

1 measured. These are the ratios of the concentration in 2 the tissue of interest relative to saline solution. 3 And what I want to point out here is that the values 4 that were used in previous PBPK modeling efforts by 5 Tami McMullin are consistent with the values that we 6 determined experimentally. 7 She used a model-fitting procedure to 8 calculate partition coefficients and found that a body9 to-plasma ratio of1.0 or 1.1 was adequate to fit the 10 data, and a liver-to-plasma ratio of 2.3 was adequate 11 to fit her data. We have measured a liver to saline 12 concentration ratio of 3.3, and for other muscle, which 13 represents a large portion of that body weight, has a 14 ratio of 1. 15 So what are the implications for PBPK 16 modeling? I have presented to you highly resolved, 17 time-resolved data for atrazine and its chlorinated 18 metabolites, high temporal resolution and 19 differentiating with four different compounds. I've 20 also shown you data that allows us to quantify the 21 rates of disappearance of atrazine formation 22 metabolites for rats and for humans that allow us to do 23 human interspecies scaling. 24 And finally, the partition coefficient 25 experiment that we conducted verified the previousFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 153

1 modeling work done by Tami McMullin. 2 All this information is very valuable, 3 and we will be using this information to build a PBPK 4 model that will allow us to understand the internal 5 dosimetrics following different exposure scenarios and 6 also to scale between humans and replace the default 7 approaches of scaling by body weight. 8 I want to end with a few slides, just 9 three slides, that revisit the issue of how 10 pharmacokinetics can inform toxicodynamics. And we 11 never really do pharmacokinetics alone, although 12 interesting in and of itself. The purpose of our study 13 was to inform the findings from Dr. Handa's laboratory. 14 Just to summarize what Dr. Handa found, 15 at 4 days of treatment he found that levels of LH were 16 suppressed in the high-dose group, the 50 mg/kg gavage 17 dosing group; however, he did not find any difference 18 from controls when the rats were given atrazine by 19 diet. This is consistent with the plasma profiles 20 we've generated in our study. 21 Here concentrations of atrazine, DEA, 22 DIA and DACT, during the treatment we find large 23 discrepancies in both the maximum concentration and the 24 area under the plasma curve for gavage versus dietary. 25 And I do want to note here that one of the reasons whyFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 154

1 we conducted this comparison -- and I should have 2 stated this earlier -- was that we want to compare a 3 gavage dosing at a controlled laboratory experiment 4 with distributed feeding behavior or pattern, which is 5 more realistic when we talk about human exposure 6 patterns from drinking water exposures. 7 What we observed is that during the 4 8 days of treatment we see rapid uptake of atrazine; 9 large differences between gavage and dietary; and 10 likewise for DACT. 11 We also followed the concentration of 12 atrazine and its metabolites for 4 days after cessation 13 of treatment. And this gives us insight into what Dr. 14 Handa presented with regard to peak LH levels after 15 atrazine withdrawal, and what he found was that LH 16 levels increased back to control levels, levels that 17 are comparable to controlled values, within 4 days of 18 withdrawal of atrazine. 19 And we see that atrazine concentrations 20 and its metabolites decreased very quickly, and within 21 2 days they reached levels that were below the limit of 22 quantitation; by days 3 and 4, all concentrations of 23 these four are below the limits of quantitation. 24 So I want to summarize. In summary, 25 what we've learned from these in vivo pharmacokineticFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 155

1 and in vitro hepatocyte metabolism studies is that, 2 one, atrazine is rapidly metabolized; it's converted 3 into DEA, DIA, and there are interspecies differences 4 there; the peak plasma concentrations from gavage and 5 diet are very different, tenfold different for 6 atrazine, DEA, DIA, twofold different for DACT. 7 Peak concentrations are similar from the 8 gavage dosing from days 1 to 4. This holds true for 9 all four compounds, suggesting that is rapid uptake and 10 rapid conversion; however, for a dietary dosing, we 11 find that it takes a while for DACT levels to reach 12 what is called the pseudo-steady state. At days 3 and 13 4, you see less oscillation of that concentration. 14 Atrazine, DEA, DIA and DACT concentrations all are 15 below the LOQ values within 2 days of withdrawal. 16 From the human hepatocyte study, I just 17 want to point out that we have quantitative information 18 that allows us to calculate rates of formation and 19 disappearance of these compounds. We have results from 20 two different species, rats and humans, and we have 21 quantified animal-to-human differences. 22 And what this data will allow us to do 23 is, like I've said, support the PBPK modeling, which we 24 aim to work on the next few months here and provide 25 that to the Agency by 2011.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 156

1 Thank you very much. 2 DR. STEVEN HEERINGA: Thank you very 3 much, Dr. Kim. 4 DR. CHARLES BRECKENRIDGE: Mr. Chairman, 5 I appreciate the rapidity with which Dr. Kim was 6 speaking, and he was brought us quite up to the 12:30 7 mark. 8 We have one wrap-up to do, and we can 9 probably do that after; it would take about 15 10 minutes, so it's your call. 11 DR. STEVEN HEERINGA: And then we also 12 have the water. 13 DR. CHARLES BRECKENRIDGE: That is 14 correct, sir, so we are running a little bit behind. 15 DR. STEVEN HEERINGA: Okay. So let me 16 propose this. Let's take 45 minutes for lunch today, 17 and we will reconvene at 1:15. We will hear the wrap18 up from the Syngenta public commenters and also the 19 presentation on water sampling. 20 At that point in time, I'm going to move 21 on to the other public commenters, just to make sure 22 that it's going to be a long day, and that we will hold 23 comments for the Syngenta team. Again, a tremendous 24 amount of information here, I'm sure there's a lot of 25 interest. And I want to focus the time, but I alsoFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 157

1 want to make sure that the other public presenters 2 aren't doing this at 8:00 o'clock tonight. 3 So we'll handle it. It might mean that 4 Dr. Breckenridge is going to do it; I don't believe 5 we'll be there. So that's the proposal at this point, 6 so let's rejoin at 1:15 and we'll finish up with the 7 presentations from the Syngenta team, and then we'll 8 move on to the other public commenters. 9 Thank you. 10 (WHEREUPON, a luncheon recess was taken.) 11 DR. STEVEN HEERINGA: Welcome back, 12 everyone. We are in the process of the period of 13 public comment for this FIFRA SAP meeting, and we have 14 heard a number of the component presentations from 15 Syngenta scientists and we have a few more 16 presentations to wrap up here. 17 And Dr. McFarland, if you would like to 18 introduce that, we'll try to move it along on time; 19 but, thank you. 20 DR. JANIS MCFARLAND: Thank you very 21 much. 22 We're happy to have Dr. Jim Simpkins 23 from the University of North Texas, who is going to 24 give the wrap-up in the toxicology section, and then 25 we'll follow right after that with Dr. Hendley coveringFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 158

1 the water monitoring. 2 And Dr. Hendley, there are some other 3 water experts that will be available for questions 4 later at the time, if the Panel has them. 5 DR. STEVEN HEERINGA: Thank you very 6 much. 7 Dr. Simpkins. 8 DR. JIM SIMPKINS: I'm Jim Simpkins, 9 Professor of Pharmacology and Neuroscience at the 10 University of North Texas Health Science Center. I've 11 been involved with the atrazine team since the early 12 '90s in an advisory capacity. 13 My charge today is to try to relate key 14 early events with adverse reproductive effects, and I 15 would like to start by pointing out that LH suppression 16 is not an adverse effect; it's a key early event that 17 may help us explain a variety of adverse reproductive 18 effects that may be occurring in animal models. 19 Those adverse events are depicted in 20 this slide in females only; that is, female rodents. 21 Effects on LH surge can lead to a change in fertility 22 by affecting ovulation and a variety of processes 23 related to ovulation. 24 In addition to that, changes in 25 pulsatile LH secretion can manifest themselves inFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 159

1 females as a delay in vaginal opening, their surrogate 2 marker for puberty, or in adults in hypogonadism; in 3 males, the same kinds of changes and pulsatile LH 4 secretion result in a decline in testosterone 5 production that delays preputial separation, their 6 surrogate marker for puberty, and in adulthood reduce 7 sperm count and then a decline in weights of androgen8 dependent tissues. So those are the kinds of adverse 9 events that we will be looking at. 10 The pre-ovulatory LH surge depicted here 11 is driven by estrogens from the follicle and results in 12 a number of processes that could be affected if the 13 pre-ovulatory LH surge is affected. 14 Included in that is a pre-ovulatory 15 increase in progesterone, final maturation of the 16 oocyte, ovulation of the follicle or of the oocyte and 17 then formation of the corpus luteum, which maintains 18 progesterone secretion during the luteal phase of the 19 menstrual cycle. 20 In males, pulsatile GnRH secretion 21 drives, as Dr. Plant points out, pulsatile LH 22 secretion, and then that regulates secretion of 23 testosterone from the Leydig cells of the testis. A 24 reduction in pulse, amplitude or frequency can result 25 in a reduction in serum testosterone, a change inFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 160

1 intratesticular testosterone and a resulting reduction 2 in the weights of androgen-dependent tissues. 3 Now, we searched the literature trying 4 to find scientific documentation of what Dr. Legan 5 mentioned yesterday, and that is the very large excess 6 capacity of the pre-ovulatory LH surge. And I will 7 present to you a few examples to put a context on the 8 statement that she made yesterday. 9 Here is an example of an in vitro 10 perfusion system of the ovary where the question being 11 asked is: What is the amount or the percentage of the 12 pre-ovulatory LH surge needed to produce full 13 progesterone production? 14 And in this study, Dr. Paluzzi 15 demonstrated that only about a third of that LH surge 16 is required to produce progesterone secretion that's 17 absolutely normal for this system. 18 In addition to that, these are work from 19 Dr. Ishikawa showing that in the barbiturate-blocked 20 rat -- and these are normally cycling rats in which the 21 pre-ovulatory LH surge is blocked with phenobarbital, 22 or pentobarbital in this case. 23 And then he doses with luteinizing 24 hormone and asks the question: What's the percent of 25 animals dosed that ovulate, and how many ova do theyFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 161

1 ovulate? What he was able to show is that a very short 2 LH surge induced by administration of exogenous LH is 3 needed for full ovulation and a full complement of ova. 4 I will point out to you the surge that 5 he is inducing with his injection of LH lasts much less 6 than an hour; the normal rodent pre-ovulatory LH surge 7 goes 4 to 6 hours, so full ovulation with a very 8 transient LH surge. 9 Dr. Phyllis Wise has demonstrated very 10 eloquently that as rodents, in this case Sprague-Dawley 11 rats, approach middle age, 8 to 10 months, the 12 amplitude of their pre-ovulatory LH surge is decreased 13 by half, and this was associated with disrupted estrus 14 in these middle-aged female Sprague-Dawley rats. 15 Another way to get at this excess 16 capacity of the LH surge is to look at biological 17 variability in normal pre-ovulatory surges, and we have 18 here two of many examples. This happens to be a study 19 in pigs, in which each of these animals displayed a 20 pre-ovulatory LH surge, each of them ovulated, became 21 pregnant and had a normal pregnancy and delivery. 22 So this is for that animal a normal LH 23 surge, and what you notice is the animal that has the 24 lowest surge versus the animal with the highest surge, 25 there is a fourfold difference in the amplitude of thatFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 162

1 surge. 2 All of them are successful surges, so 3 there is extreme excess capacity. These are the 4 results from a study that was cited several times 5 yesterday. This is Dr. Cooper's 2010 dataset. These 6 are the control-dosed animals, and what's depicted here 7 are the values: this is peak amplitude for the LH 8 surge, and this is fraction of the animals that are 9 showing that peak amplitude. And what we see is that 10 animals that have a surge of 8 ng/mL and animals that 11 have surges of 32 ng/mL, this is a fourfold difference 12 between the low and the high. 13 All these animals show evidence of pre14 ovulatory LH surge, progesterone secretion, uterus 15 weight increase; so these are having normal surges. So 16 there appears to be at least a fourfold excess of LH 17 that's being secreted in both of these examples. 18 Now, this is a summary of all that 19 information, simply indicating that there is excess 20 reserve on that pre-ovulatory LH surge. 21 Now I will bring you back to the data 22 that Dr. Handa presented earlier today, and this is 23 simply a re-presentation of the effects of bolus 24 exposure of animals to atrazine in response to gavage 25 administration for 4 days during their normal estrusFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 163

1 cycle versus a distributed dose of atrazine, again over 2 4 days in normal estrus cycles. 3 And what he reported was high-dose 4 gavage administration of 50 mg/kg causes a significant 5 decline in peak amplitude and also area under the LH 6 curve, whereas an equivalent dose given in the diet, 7 and therefore a distributed dose, does not affect LH 8 secretion. 9 Now, a prediction from these data is 10 that gavage administration of atrazine ought to result 11 in high-dose reproductive toxicity but not lower doses, 12 and that distributed dose administration of equivalent 13 amounts of atrazine should be without reproductive 14 toxicity effects. And the next few slides that I will 15 show you I think demonstrate that point. 16 In female rats, what we have done is 17 taken a number of studies -- and I won't point them out 18 individually, but rather just talk about the patterns - 19 - taken a number of studies; in this case, this is the 20 Handa gavage LH data with a high-dose effect, nothing 21 at lower doses; and a variety of vaginal opening 22 studies -- I think five or six are depicted here -- and 23 we've put tick marks in green where there was no 24 treatment effect or pluses in red where there is a 25 treatment effect.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 164

1 And those are associated with the dose 2 of atrazine given by gavage, and the treatment period 3 is about 2 weeks in all these studies. 4 What you notice is that gavage 5 treatment, as predicted based upon the Handa gavage LH 6 data, results in high-dose reproductive effects 7 expressed as delays in vaginal opening, which is going 8 to be in contrast to the data that I show you in the 9 next slide, where dietary or distributed dose atrazine 10 was administered. 11 This is a two-generation reproductive 12 study conducted some time ago where the 0 generation 13 was exposed to atrazine 0, 10, 50 or 500 ppm, which 14 relate to the doses in the bottom left of highest 40 15 mg/kg; so about that dose that showed up in the Handa 16 study. 17 Animals were treated for 10 weeks, males 18 and females both, and then they were put together, 19 allowed to breed and the fertility index was calculated 20 -- that is, the number of breeders -- and the ratio of 21 successful pregnancies to breeders was determined. 22 And then gestation happened with 23 continued dosing. Pups were born, the number of pups 24 were counted, and then the F0 generation continued 25 treatment during lactation. The F1 generation then wasFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 165

1 treated, and went through the same procedure to look 2 for F1 fertility effects and number of live births 3 versus the number of pups. 4 Shown here again are the results of that 5 study. This is the Handa distributed dose or dietary 6 LH data with no effect on LH, and there was absolutely 7 no effect on F0 or F1 fertility index or on number of 8 pups born to those matings, suggesting that this 9 distributed dose was without reproductive toxicity. 10 Similar kinds of studies have been done 11 in male rats; regrettably, we don't have distributed 12 dose or feeding studies that have been done. So the 13 gavage studies, this is a Trentacoste published report 14 showing that with gavage treatment with atrazine -- 15 these are from postnatal day 22 to postnatal day 47 -- 16 there is a high-dose suppression of LH secretion; 17 similarly, high-dose suppressions in both serum 18 testosterone and intratesticular testosterone. 19 And then at the same doses that 20 testosterone levels were affected, weights of androgen21 dependent tissues were also less. 22 This is a series of studies also in 23 males using gavage -- and this is Tammy Stoker's data - 24 - that assess a number of atrazine and three 25 metabolites, DIA, DEA and DACT, which shows no effectFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 166

1 on LH secretion. Although in each of these studies LH 2 was trending down, it simply was not significant, 3 largely because of variation in the data. 4 But what was observed with gavage 5 administration was significant effects on preputial 6 separation beyond puberty with atrazine and with all 7 three of the metabolites of atrazine. 8 A subsequent study was done because NOEL 9 was established in this study: 6.25 mg/kg/d had no 10 effect on preputial separation with any of the 11 compounds. And this is the dose of atrazine that's 12 used for acute LH suppression regulation. 13 Now, the summary of these data are here. 14 It does indeed appear that there is a large reserve in 15 the pre-ovulatory LH surge in a number of species. It 16 also is true that bolus dosing with atrazine shows 17 high-dose reproductive toxicity that is not evident 18 with distributed or diet dosing with atrazine. 19 Now, let me just finish by summarizing what you heard 20 late this morning and since lunch. 21 It appears, as Dr. Plant has pointed 22 out, that the rodent is not a good model for human risk 23 assessment related to events coupled to the 24 pre-ovulatory LH surge: the morphology is different, 25 the regulation is different; however, pulsatile LHFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 167

1 secretion in all species may be relevant. 2 In addition to that, we need to identify 3 the key events that result in reproductive toxicity. 4 LH secretory events are clearly key events, 5 particularly pulsatile LH secretion. And I think we 6 need to strive for what was achieved in the cancer 7 assessment of atrazine, and that is that effects of 8 atrazine on LH secretion were preceding and related to 9 effects of atrazine on estrus cycle, which preceded the 10 appearance of tumors in those animals. 11 Third, there is a remarkable difference 12 in internal dosing that's seen with gavage 13 administration versus dietary administration of 14 atrazine, and we need to be aware of that in doing our 15 assessments. And it's noted that dietary 16 administration simply doesn't show reproductive 17 toxicity. 18 And then finally, PBPK modeling is going 19 to be critical for establishing internal doses that 20 allow us then to do comparison between rodents and 21 humans for exposure to atrazine. 22 I thank you. 23 DR. STEVEN HEERINGA: Thank you very 24 much; Dr. Simpkins' presentation, and I believe there 25 is one final presentation.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 168

1 DR. PAUL HENDLEY: Okay, if we can have 2 the slides, please. 3 While that's coming up, my name is Paul 4 Hendley. I'm a Senior Syngenta Fellow with Syngenta. 5 My colleagues from Syngenta are with me in the 6 audience, as is Dr. Harbourt from Waterborne 7 Environmental. 8 What I'm hoping we're going to be able 9 to see by the end of the presentation is four key 10 things. We're going to show that the magnitude of 11 atrazine residues are defined with high confidence, as 12 well as the distribution of those residues. 13 We're going to see that community water 14 systems can be characterized; they're highly site15 specific, each one is individual. We think there are 16 some additional approaches to defining chemograph shape 17 that are important to actually help us understand the 18 questions before the Panel. 19 There's also a couple of models about 20 SEAWAVE and the PRZM hybrid approach that are really 21 going to be very suitable to address the Question 4.3, 22 and they should be reviewed and refined. 23 Four key areas of the presentation: the atrazine 24 monitoring database; how to characterize community 25 water systems and their watersheds in order to considerFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 169

1 program design; ways of thinking about chemograph shape 2 analysis in regard to sampling programs; and the 3 question of how do you extrapolate from 7-day data to 4 shorter-term averaging periods. 5 We'll start with the atrazine monitoring 6 database. And this is a slide showed in the April SAP. 7 It talks about the exceptional scope of the atrazine 8 surface water monitoring data. 9 Essentially, you can consider surface 10 water in two pools, the drinking water and the non11 drinking water. There's about 180,000 to 190,000 12 atrazine samples in the non-drinking water part, which 13 looks at water bodies, streams, rivers, lakes, the raw 14 water from the community water systems; it include USGS 15 programs, Syngenta programs, State programs and many 16 others. 17 In the drinking water area, we're 18 talking about finished water, and that's better 19 characterized if we consider three key elements: the 20 Safe Drinking Water Act, where over 4,400 community 21 water systems have contributed samples to the database. 22 There are finished-water-only samples, 23 and that makes up about 50,000 samples from that source 24 in the database recorded since 1993, typically recorded 25 at 4 samples a year.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 170

1 The Syngenta Voluntary Monitoring 2 Program, which ran from 1993 to 2003, looked at 3 community water systems with an atrazine history, and 4 over 130 or so community water systems were involved. 5 The key point here, raw or unfinished samples taken, 6 about 45,000 samples in the pool. 7 Since 2003, a mandated program, the 8 Atrazine Monitoring Program, has included every 9 community water system since 1997 to the present whose 10 annual average SDWA measurements exceed 1.6 ppb in 11 atrazine. 12 So everything up to 2003 and beyond has 13 been included that's been roughly over half the MCL -- 14 again, very frequent monitoring focused on the growing 15 season, both raw and finished samples, and probably 16 27,000 raw and 27,000 finished. 17 This exciting table of statistics summarizes those 18 results. 19 They are in your record, we won't dwell 20 on them. The key point to think about here, this is 21 high frequency monitoring data. You can see some 22 unsurprising results: raw water residues are higher 23 than finished, for example. 24 But the key point here is that the 25 sample sizes are so large, and both for the entire poolFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 171

1 and also for the sub-pools of static community water 2 systems and flowing community water systems, that the 3 confidence around what we know about the high centiles 4 and also, of course, in the light of the questions that 5 Dr. Portier asked yesterday about the distribution of 6 those residues, the entire distribution. 7 So the confidence we have on that is 8 extremely high. We understand the magnitude of peaks 9 that occur in the Midwest and the distribution of them, 10 as well. 11 The database is also valuable to 12 understand the sort of comments that Dr. Coupe made 13 yesterday about the trends with time. For example, the 14 data show us that the measured annual averages have 15 declined since 1994, and we explained last time that 16 was largely due to stewardship, best management 17 practices and label changes, with the good work done by 18 the farmers. 19 Importantly for what the Panel is 20 addressing, there are daily datasets. There are three 21 that all revolve around flowing water. There is a 22 community water system in Missouri that takes water 23 from the Missouri River that has good high sample 24 frequency. 25 You heard about the Heidelberg CollegeFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 172

1 data. The only thing I'd add to what Nelson said about 2 that is it's very relevant, because in fact 4 of the 44 3 community water systems highlighted in the whitepaper 4 actually draw their water from within those watersheds. 5 And in addition to that, we have the 6 Syngenta Eco Monitoring Program. Of course, as we 7 discussed last time, the size of those watersheds is 8 smaller than almost every community water system; but 9 they are a very good worst-case model to consider, 10 because they are so small because of the spikiness of 11 the residue pattern. 12 And of course, we're accumulating more 13 data all the time; since last April, we've got another 14 30 site years of daily data. 15 There is a dataset I think the Panel 16 needs to consider. It's a static water high frequency 17 dataset. It is a USGS dataset at Perry Lake in Kansas. 18 It's 1100 square miles, it's a big watershed in a big 19 lake. The daily sampling was done in the '90s. 20 It was about 5,000 samples were taken 21 over a 3-year period. The key thing here, these were 22 composite water samples; they were daily when something 23 interesting was happening hydrologically. It wasn't 24 every day; but the quality of the data is comparable to 25 Heidelberg, which is similarly not precisely dailyFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 173

1 sampling. 2 USGS did a bootstrap analysis along with 3 EPA on this, and they came to the conclusion that 4 looking at sampling at different interval frequencies, 5 reasonable measures of the actual high centile values 6 could be determined using a monthly sampling frequency, 7 and I have included a relevant table in your printout. 8 They did also some very cool stuff about the way the 9 plumes move through the reservoirs, and unfortunately 10 we don't have time to dwell on that. 11 So let's consider characterizing 12 community water systems. And Syngenta is accumulating 13 site-specific data to help us understand the 14 vulnerability and understand these systems. 15 There are two things to think about. The first one is: 16 what's the primary water system for a community water 17 system unit? If you are going to understand what the 18 residue patterns look like, you need to know that. 19 Surprisingly, it is not as simple as it 20 sounds. For those 44 community water systems 21 highlighted in the whitepaper, if you look at the 22 Government data, there are 73 potential sources of 23 water. So it requires careful data-mining and 24 interviewing and talking to the people who are involved 25 at the ground level to really understand what's goingFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 174

1 on at these locations. 2 And some of this can be complex, as I 3 showed last time. In some cases, you may collect the 4 water from a watershed, a creek; but they may store the 5 water in large reservoirs, which is subject for 6 dilution. So you really need to understand the true 7 role with a supply point, as well as the source 8 watershed. 9 The history of data-gathering in the AMP 10 and the VMP Program tell us an awful lot about these 11 site-specific phenomena. Among the 44 sites 12 highlighted in the white paper, it's a fairly good mix: 13 about 16 statics, 19 flowing, 3 very interesting 14 hydrologic ones in Louisiana where the hydrology is a 15 little unusual; and 6 of these pumped and stored 16 systems. 17 So the other thing you need to 18 understand is the watershed environment. And the good 19 news here is we've been doing a lot of work because of 20 the Atrazine Ecological Monitoring Program, and we have 21 a lot of data to help us through understanding the 22 environmental characteristics of the watershed. 23 In addition to what we've gathered for Eco, we've 24 delineated the watersheds for the community water 25 systems.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 175

1 We collect, of course, all the AMP 2 water-quality data and a lot of information from USGS 3 on flow information, et cetera, in addition to the very 4 high resolution, cropping, soils and PRZM modeling for 5 atrazine that's done for every soil in the country. 6 And we've shown you before the very high resolution 7 subfield scale: in fact, 10-meter grids, these 78 8 billion points across the U.S.A. 9 So what we will talk about now is the 10 chemograph shape analysis. And that phrase has been 11 used and mentioned, so we'll talk about it in a little 12 bit more detail. Our goal is to find, identify 13 community water systems that are possibly vulnerable to 14 short-tern atrazine peaks and identify where 15 appropriate sampling regimes apply. 16 There are various technical options for 17 that: you can look at empirical data; you can do some 18 theoretical calculations; there's existing flashiness 19 indices; and there's various models. 20 We talked about some of the empirical 21 datasets; typically, they are the daily ones. The 22 thing I would like to highlight here is that the 23 Heidelberg College and the Eco Monitoring Program have 24 not only chemistry data; they have flow data available 25 for the same periods, and I'm going to sort of show whyFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 176

1 that's important in a moment. NAWQA has some good 2 data, and also we've got tools for looking at local 3 rainfall with NEXRAD. 4 So if we are going to talk about what 5 does a chemograph shape look like, if you're going to 6 define that, we believe you need to think about the 7 number of peaks that exceed some threshold of X, how 8 long that threshold is exceeded, how big the peak gets 9 while it's exceeding the threshold and, in some 10 circumstances, you'd be interested in the interval to 11 the next peak. 12 And interestingly, under the ECOFRAM 13 process for ecological risk assessment that was set up 14 in the late '90s, software was designed specifically 15 for that purpose. And we have applied that software to 16 look at the Eco and the Heidelberg data with a range of 17 atrazine concentrations. 18 I'm going to show you an example with 19 one range: 15 parts ppb. And what you can see here is 20 that there are some Eco sites, then Heidelberg sites. 21 We have the number of years it was operating. We have 22 the area of the watershed, which goes from very small 23 to pretty large. And what this column says is 20 24 events exceeded 15 ppb at this site: 9 of those exceed 25 for 2 days, 4 of those exceeded for 3 days, and 1 for 7FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 177

1 days. 2 For Rock Creek, there were 90 events 3 across 25 years, which is approximately 3.5 event a 4 year; but of those, about a third continued for 7 days 5 and continued to exceed for 7 days. The very largest 6 watershed had roughly 2.5 exceedances a year of the 15 7 ppb thresholds, but half of those continued for over 7 8 days. 9 So what we're seeing is that the 10 atrazine peaks are infrequent. The numbers of events 11 exceeding the threshold for 7 days or more increased 12 with watershed area, and we couldn't really distinguish 13 between the Eco scale and the small scale of 14 Heidelberg. And other data show that the magnitudes 15 are reduced for larger watersheds. That data shows 16 some very interesting data that supports the comment on 17 magnitude. 18 We don't have time to dwell on this; but 19 we did precisely the same analysis using the 80th 20 centile of flow as a threshold, and what that showed 21 again is the two largest watersheds, about 15%, 11% to 22 15% of their flow events exceeding that threshold 23 lasted longer than 7 days, whereas for the smaller 24 watersheds only 2% of the events had an extended 25 period.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 178

1 In other words, what these analyses has 2 showed is that both the chemical peak behavior and the 3 flow behavior for the Heidelberg and the Eco watersheds 4 to some extent show similar relationships between 5 duration and the watershed area. This isn't new; it 6 was reported by Baker in 2000. What that means is we 7 have a new tool available to us for considering peak 8 shape by using flow data. 9 Other approaches on chemograph shape, 10 flashiness indices have been published in the past; 11 Richards and Baker have them, there's a number of 12 others out there in the hydrology literature. All we 13 really need to draw from that is that the concept of 14 flashiness based on area has been exemplified in quite 15 a lot of cases as a way of looking at the question. 16 There are models. We have had a look at 17 them. We feel to be useful to understand chemograph 18 shape will require refinement in many ways to get it 19 down to a daily temporal scale and to a small watershed 20 scale. We don't think it's ideal for this purpose. 21 PRZM and SWAT are much cleverer models, 22 and they predict edge-of-field quite well; but PRZM has 23 been shown to over-predict drinking-water 24 concentrations, publications by Jackson, et al. And 25 SWAT does a much better job on hydrology, but both ofFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 179

1 their models require an awful lot of work, including 2 flow data, to parameterize the models. 3 So what we suggest is that empirical 4 analysis by the daily monitoring data or flow data, 5 which is much more commonly available than chemical 6 monitoring, is probably an efficient way of getting 7 into considering chemograph shape. 8 So the chemograph shapes differ 9 fundamentally between static and flowing water bodies. 10 We have shown that missing a peak in static water 11 bodies with 7-day sampling from Lake Perry is unlikely. 12 But some static water bodies can be overtopped by a 13 bigger event. 14 If so much water comes through that 15 there's multiple pond volumes, it will behave 16 ultimately like a flowing water body, and in your 17 handout there are some theoretical calculations that 18 show for different sized ponds where this occurs. Our 19 point is, if you look at static water bodies, you need 20 to treat one individually to see is it going to behave 21 like a static water body, or is it going to behave like 22 a flowing one. 23 And why does this matter? Why it 24 matters is, we tried to come up with a general 25 flowchart to help people think, pegs for thought, ifFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 180

1 you like, for thinking about chemograph shape. And 2 it's a preliminary guide, it won't replace detailed 3 individual understanding, and you will still have to 4 think about vulnerability in terms of environmental 5 vulnerability, the scale of the watershed and atrazine 6 use. 7 But imagine if you have a pool of 8 community water systems. You can say first which ones 9 are static by identifying the primary water source. Of 10 those, which are going to behave like true statics, and 11 which have the potential to behave like flowing water 12 bodies. 13 The true statics can be investigated on 14 the basis of size, and in fact we've already got the 15 data from Perry Lake validating the large series. 16 There's this odd category of the ones that store the 17 water in reservoirs, they are a separate group case-by18 case. 19 But for the flowing ones, we have a 20 concept or, if you like, a continuum: you've got area 21 going from very small to the whole of Mississippi; 22 you've got vulnerability towards flashiness going this 23 way, so it gets flashier as it gets smaller; and you 24 can place on this different types of hydrology, you can 25 place the daily datasets we have so we can think aboutFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 181

1 the main context and put the results we get from the 2 data analysis of those to create an understanding 3 across the scale. 4 Here is the community water system, here 5 is the big Heidelberg and the small ones. EPA's 6 smallest flowing one is about here from that 44, and 7 their largest is here. 8 And imagine that we know something about 9 the 7-day peak width of this Maumee Reservoir. With 10 data-mining -- and this is an example -- you can put a 11 divider that says: on this side of the line, we know 12 7-day sampling is more than adequate; on this side, 13 what you need to do is a case-by-case analysis to think 14 about where the sampling and what regimes are 15 appropriate. And obviously, this requires data-mining 16 based on the available data. 17 Finally, the last question is about 18 extrapolating from 7-day sampling to shorter-term 19 averaging periods: two approaches, modeling and using 20 the existing daily data. PRZM hybrid approach was 21 presented to an SAP in 2007. 22 We won't dwell on the modeling; the 23 modeling essentially is parameterized to scenarios that 24 mean the edge-of-field predictions match what goes on 25 in a particular watershed for the community waterFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 182

1 system: you use local weather data for the year you 2 are looking at the peaks concerned and you have a rule3 based system, and the rule-based system takes your 4 measured values and your model values and it says, "Do 5 I have a measured value today? 6 If so, I'll use it. If I don't, was it 7 an event today? And if it wasn't an event, I will use 8 that number and add it to the science areas. If there 9 was no event, I interpolate the value for that day". 10 The important thing for that is it gives primacy to 11 measured values, it resets the estimates to reality, 12 and it will always increase the average concentrations. 13 So the other models, there is PRZM 14 modeling for atrazine everywhere. The USGS SEAWAVE 15 model appears to offer a lot of potential. It's very 16 thorough. It's based on some really solid research and 17 data from USGS. It requires flow data for calibration, 18 probably won't work for statics; but it does appear to 19 have a lot more potential because of the weight of 20 evidence behind it and some of the kriging approaches. 21 So our recommendation would be that we 22 need to fine-tune both PRZM hybrid and SEAWAVE for the 23 purpose required at the moment for EPA's current 24 purpose. But whatever model is used, the daily 25 datasets should be used with bootstrapping to reallyFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 183

1 validate the approaches. 2 So I won't talk through this slide; we 3 did talk about conversion factors in great detail at 4 the April SAP. I apologize for those who weren't 5 there. 6 And I'll move to the key points. The 7 magnitude of atrazine residues are defined with high 8 confidence. We can confidently predict the highest 9 centiles and also address the question that the 10 probability of distribution for any peaks, whether they 11 are sampled or not sampled; we understand those very 12 well because of the size of the database. We have very 13 valuable daily data that can help us validate new 14 approaches. 15 A community water system 16 characterization requires accurate data-mining, because 17 each one is individual. It's critical to understand 18 the primary water sources and how water is handled. 19 But watershed vulnerability we're working on on two 20 fronts, and we're learning all the time between EPA and 21 ourselves. 22 There are some more approaches to think 23 about when you consider chemograph shape. There's 24 actually a software tool to do it, and we think that 25 daily flow data can supplement the chemical data toFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 184

1 actually help understand the chemograph shape. 2 There's a flowchart that helps provide a 3 way of looking at the questions before the Panel, and 4 we would recommend that division into flowing and 5 static primary sources and watershed size is a good way 6 to start thinking. 7 PRZM hybrid and SEAWAVE approaches 8 should be refined for the purpose but appear to offer 9 great potential, and the daily datasets with their 10 bootstrap approach can come up with conversion factors 11 if needed, but probably most importantly as a tool to 12 validate any new models we develop. 13 And thank you for your time. And Mr. 14 Chairman, just for your information, if the questions 15 do come up, we do have some data addressing Dr. 16 Krishnan's question yesterday about TCT that we can 17 present, if asked. 18 DR. STEVEN HEERINGA: Thank you very 19 much, Dr. Hendley. 20 And again, as I indicated this morning, 21 in the interest of keeping our public comment on a 22 schedule, we will defer questions from the Panel to the 23 end of the public comment period, and I'll make sure 24 that everybody has an opportunity to present during the 25 afternoon here.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 185

1 DR. JANIS MCFARLAND: Thank you very 2 much. 3 DR. STEVEN HEERINGA: Thank you very 4 much, Dr. McFarland. 5 A lot of information, a lot of data 6 presented, and I think the Panel will take a little 7 time to absorb this; so hopefully, we'll get a chance 8 to study this, too. 9 At this point in time, I would like to 10 invite up our second public commenter, which is Dr. 11 Tyrone Hayes, and he is on behalf of and representing 12 himself and "other various scientists" is the way it's 13 listed, and I'll let him identify his colleagues. 14 Is Dr. Hayes' presentation loaded? 15 You're welcome. 16 Be sure to turn the microphone on, too, 17 Dr. Hayes. 18 DR. TYRONE HAYES: Okay. First of all, 19 I'd like to thank the Panel for the opportunity. My 20 name is Tyrone, and what I'm going to do today first of 21 all is talk a little bit about my ongoing research that 22 looks at reproductive effects of atrazine on 23 amphibians. 24 But then I've recently been joined by 39 25 scientists from 12 countries on 6 continents, and we'veFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 186

1 done an extensive review of the available literature on 2 the reproductive effects of atrazine across vertebrate 3 classes. 4 Three of those coauthors aren't listed 5 here, because I wasn't sure about the approval with 6 their Agencies for presenting this work; but perhaps 7 those names can be added later. 8 First of all, as a matter of disclosure, 9 I want to make clear where my funding sources have been 10 for my research on atrazine and for this work and, in 11 particular, point out that a little over ten years ago 12 I was funded by Novartis/Syngenta/EcoRisk; and to my 13 knowledge, at least two of my coauthors, Krista McCoy 14 and Frances Orton, were also either funded for or 15 funded by or worked in a laboratory that was funded by 16 Novartis/Syngenta. 17 The primary work that I've done on 18 atrazine has been on the African clawed frog, Xenopus 19 laevis. And a few years ago, actually initially while 20 working with Novartis and then Syngenta, we showed that 21 atrazine inhibited growth of the voice box or the 22 larynx in males that were exposed throughout the larval 23 period, which is roughly 2 months under the conditions 24 that we used. 25 This inhibition of growth of the larynxFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 187

1 was an indication that the animals were demasculinized 2 or that their testosterone, the so-called male hormone, 3 was diminished or depleted. And we later on went on to 4 show that, in fact, when we dissected the animals, a 5 proportion, depending on the dose -- actually, 6 depending on the dose and the population -- but a 7 proportion developed gonadal abnormalities, including 8 hermaphroditism, such as the example shown here of an 9 animal that has at least three testis and three 10 separate ovaries. 11 We proposed at that time that the 12 mechanism of atrazine, a mechanism which had been 13 identified previously in other animals, was that 14 atrazine induced or upregulated aromatase, resulting in 15 the conversion of testosterone into estrogen, 16 ultimately resulting in the demasculinization effects, 17 such as the growth in the larynx, and the feminization 18 effects, such as the development of the ovaries in what 19 we presumed to be genetic males. 20 We showed in our original publication 21 that in fact when adult male African clawed frogs were 22 exposed to atrazine, there was a significant reduction 23 in blood levels of testosterone such that exposed males 24 had testosterone levels that were not statistically 25 different from unexposed females.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 188

1 And we published that work in a paper, 2 "Hermaphroditic, demasculinized frogs after exposure to 3 the herbicide atrazine at low ecologically relevant 4 doses". That was published in Proceedings of the 5 National Academy of Sciences, and in fact I presented 6 some of those data in the 2003 SAP on amphibians. 7 That paper left two questions 8 unanswered: one, were the hermaphrodites males with 9 ovaries or females with testis, which sounds like a 10 silly question except that African clawed frogs, like 11 most amphibians, don't have morphologically 12 distinguishable sex chromosomes. 13 So we didn't have the answer to that 14 question. They still don't, but we have some answers 15 now. And we also didn't know what happened to the 16 animals when they became adults, if they were 17 functionally affected or if, for example, 18 hermaphrodites went on to become females or if they 19 went on to become males or if they maintained 20 themselves as hermaphrodites. 21 Figuring those answers out, however, was 22 a project that would take 3 to 4 years, because that's 23 about how long it takes to get them to reproductive 24 maturity. We conducted that project and published it 25 recently, again in Proceedings of the National AcademyFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 189

1 of Sciences. 2 And among other things by the time we 3 got to publishing the paper, there are genetic markers 4 now that are available for identifying males and 5 females. So, for example, females express a gene 6 called DM-W that is only present on the W of a female 7 chromosome. In this particular population in the study 8 we just published, we found that a portion of the 9 males, once they reached adulthood, even though they 10 were genetic male, 10% of them turned into females. 11 So this is one example, and they really 12 turned into females. So these males, genetic males, 13 are capable of producing viable eggs and performing 14 just like a female would. 15 We went on in this paper to test the 16 remaining 90% of the animals that did not turn into 17 females. And in those cases we looked at a number of 18 things, such as their ability to mate with females, 19 which was significantly reduced. 20 We also showed that their fertility was 21 severely reduced. So control males normally will 22 fertilize upwards of 80% of a female's eggs -- each 23 female lays about 2,000 eggs -- whereas our atrazine24 treated animals have fertility rates that are as low as 25 15%, some 0, in part because they don't showFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 190

1 reproductive behavior, but also in part because their 2 testis don't develop properly. 3 So, for example, this is a control -- 4 and the room is a little light, so it's more difficult 5 to see -- but actually it's probably pretty obvious the 6 differences between the control and atrazine-treated 7 animals. 8 What you'll notice -- and I'll blow up 9 this section for you -- is that in the controls, the 10 testicular tubules -- I'm outlining one for you here 11 and one for you there -- are filled with all of these 12 dark areas, are the sperm that are developing inside 13 the testicular tubules, whereas if you look in the 14 atrazine-treated animals the majority of their tubules 15 are empty and just filled with cellular debris. 16 So there are maybe three tubules there 17 with observable sperm; but most of the tubules are, as 18 you can see, empty like these. So even if the animals 19 displayed the behavior, the fertility is low because of 20 an absence of sperm, most likely because of an absence 21 or a severe decline in testosterone, which we also 22 measured and showed in this paper. 23 Again, that was published in Proceedings 24 of the National Academy of Sciences just this year: 25 "Atrazine induces complete feminization and chemicalFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 191

1 castration in male African clawed frogs (Xenopus 2 laevis)". 3 The next two slides are some ongoing 4 work that is not yet published, but we're nearing 5 publication. In that, in repeating these experiments 6 that we just published, we were housing animals 7 together to repeat controls compared for animals with 8 animals treated with atrazine, and our attempts were to 9 look at differences between lineages, or families, if 10 you will, because we found that there are some 11 sensitivity differences between lineages of animals. 12 What we've now found is that there is a frequency of -- 13 and here, I'll show you some more -- something that 14 I've never seen before: males actually copulating with 15 other males. So these aren't males that have turned 16 into females; these are genetic males -- well, I'll 17 show you that -- that still had testis, but they 18 behaved like females. 19 So just to show you how we have 20 characterized that for one group of animals I'm showing 21 you now, so this is one tub of 40 animals. My students 22 working on this project will just go down each day and 23 count the number of homosexual pairs, the number of 24 copulating males. So here is one day, here is the next 25 day, here is the next day. Ah, so sometimes it happensFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 192

1 in controls. 2 And now, again, there are differences 3 between lineages. So some families have a background 4 of this behavior, and some don't. Of those families 5 that have some background, the incidence of male-male 6 copulations is greatly increased, significantly 7 increased when the animals are exposed to atrazine. 8 The other thing we've discovered is that 9 in these control groups, we've marked the animals with 10 electronic IDs. These are just random pairs of animals 11 that occasionally end up together in these tubs of 40 12 animals. In these atrazine-treated tanks, for example, 13 there are 40 animals in this tank. The ones that are 14 on the bottom are always the same. So there are about 15 12 males that always perform as the female. 16 Now, one other thing that may come to 17 your mind is that maybe it's larger males -- you know, 18 there are no females in the tank, so maybe it's larger 19 male subduing smaller males in the tank -- and in fact 20 that's not the case. So if you look at body weight for 21 these pairs -- and this is just one day, we grabbed all 22 the pairs out -- there are the animals that were on 23 top, and here are the animals that they were paired 24 with. The ones that are on the bottom are always 25 larger, which is interesting because females areFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 193

1 typically larger than males in this species. 2 What's also interesting is if you take 3 blood samples from those animals, the ones that are on 4 the top have higher testosterone levels than their 5 counterparts on the bottom. But probably more 6 significantly, the ones on the top have no estrogen or 7 non-detectable estrogen in their blood, but the ones on 8 the bottom express estrogen levels that are not typical 9 of a female; but the estrogen-to-testosterone ratio is 10 typical of what you'd find in a female. 11 So in essence, we think what's happened 12 is these particular animals that didn't turn into 13 females made enough estrogen that their brains and 14 their behaviors were feminized; so they think, if you 15 will, that they're females. What's more is for some of 16 the animals when we dissect them -- and I'm sorry the 17 room is not darker -- these are testis, so these are 18 males, and all this is oviduct. So this is the 19 equivalent of a male with hypertrophied uterus, 20 something that I'd never seen in this species before. 21 So, again, we think what we've 22 identified now is within a population some males are 23 completely susceptible and make enough estrogen that 24 they completely turn into females, whereas other 25 genetic males are partially susceptible, they makeFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 194

1 enough estrogen to make vitellogenin -- in fact we've 2 shown -- to grow oviducts and did the female-typical 3 behaviors. 4 So to give you an idea of some of the 5 other work that we've done in this area, we have asked 6 whether or not these effects occur in other species of 7 frogs; so, in other words, we have asked questions like 8 whether or not this was a laboratory artifact. 9 In looking at North American leopard 10 frogs -- this was work that we published in Nature a 11 few years ago -- we showed again this partial 12 feminization as well; so this is the testis of an 13 animal exposed to atrazine in the lab, and these are 14 yolked eggs that are growing in this animal's testis 15 and bursting through the surface of the testis, an 16 effect that we've never seen in control animals in the 17 laboratory. 18 We've also asked questions like whether 19 or not the effects occur in the wild. And again we 20 have been able to show, if I can just show you the 21 histological section here; so I pulled out a section, 22 I'll blow it up and blow it up. We've identified 23 testicular oocytes in field-collected animals. And 24 we've also shown, in a paper we published in Nature 25 again, that these feminized males with eggs in theirFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 195

1 testis are 100% of the time associated with atrazine 2 contamination. 3 And just following up on that, we've 4 done an extensive 10-year study now where we followed 5 the North Platte, the Missouri, the Mississippi River 6 and some other sites of interest. The red shows the 7 areas of highest atrazine use based on sales. 8 And I've done this work in collaboration 9 with the U.S. Geological Survey, and we have three 10 papers in preparation now, including one that follows a 11 large pond that we were able to contaminate 12 experimentally and follow the population being 13 feminized and then recovering after the atrazine 14 degraded them and moved on, so to speak. 15 Now, that's all I want to say about my work and about 16 frogs. 17 But before I move on to the larger body 18 of work, I do want to do one sort of self-serving 19 thing. I want to set the record straight on one thing. 20 This is a quote actually from Alex Avery; but I've seen 21 it in many, many, many places, talking about my work: 22 " given the fact that Hayes refuses to share his 23 data," he wrote, " as EPA most recently confirmed in a 24 May 17, 2010 letter from Donald Brady, Director of 25 EPA..."FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 196

1 This statement is not based in fact. In 2 fact, to my knowledge, I've never had any 3 communications with Donald Brady, and I certainly have 4 never refused to share data or make data available. 5 In fact, in 2003, or 2002 just before I 6 attended the SAP in 2003, Tom Steeger, who was in 7 charge of that SAP, wrote to me: "Tyrone, although 8 you're not required to provide EPA with any information 9 you have been very cooperative and have shared both the 10 raw data and standard operating procedures from your 11 research. 12 Additionally, you have spent a 13 (significant) amount of time helping the office of 14 pesticide(s) program(s) to understand the significance 15 of your data, and you have provided insightful reviews 16 of similar research efforts." 17 In fact, Tom Steeger spent 3 days in my 18 laboratory examining my samples. 19 Nearly a year later, a reporter from the New York Times 20 asked via email: "but one thing I am curious about is 21 whether or not Tyrone did provide the raw data." And 22 Tom Steeger, again a year later, replied: " 23 Tyrone did provide the EPA his data and standard 24 operating procedures. He has been very cooperative 25 with the Agency."FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 197

1 So I'm not sure really where that 2 statement comes from; but I have been bothered by it, 3 and I wanted to set that record straight. Since 2003, 4 EPA has asked me for no SOPs and no raw data and no 5 other information. So I've never refused to share 6 anything. I am not really sure how or why that got 7 perpetuated. 8 What's more, what I want to point out is 9 that since, before and during my paper, a number of 10 authors had published work showing adverse reproductive 11 effects in frogs. And I want to read to you some of 12 the titles. 13 The first is "Response of the Amphibian 14 Tadpole Xenopus laevis to Atrazine During Sexual 15 Differentiation of the Ovary". The next one is "Form 16 and Prevalence of Intersexuality and Effects of 17 Environmental Contaminants on Sexuality in Cricket 18 Frogs". 19 The next one is "Effects of Nitrate and 20 Atrazine on Larval Development and Sexual 21 Differentiation in the Northern Leopard Frog"; 22 "Atrazine concentrations, gonadal gross morphology and 23 histology in ranid frogs"; "Potential endocrine 24 disruption of sexual development in free ranging male 25 northern leopard frogs"; and as recently as 2010, "LowFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 198

1 Levels of Herbicide Atrazine Alter Sex Ratios and 2 Reduce Metamorphic Success in Rana pipiens Tadpoles 3 Raised in Outdoor Mesocosms". 4 So my work is not the only work that's 5 shown; in fact, we weren't the first to show that 6 atrazine adversely affects reproductive development and 7 feminizes frogs. You can see that there are multiple 8 independent laboratories that in everything from 9 wildlife observations to mesocosms to laboratory 10 experiments, and at least four species have shown these 11 effects. 12 So while nobody has repeated my work 13 directly, similar and consistent effects have been 14 shown across independent laboratories in studies. I 15 quote Sir Austin Bradford Hill here, who in 1965, the 16 author of the so-called Bradford-Hill criteria for 17 establishing cause and effect, wrote: "I would myself 18 put a good deal of weight upon similar results reached 19 in quite different ways". 20 And that's what has happened with 21 atrazine in looking at the effects on amphibian sex 22 development. 23 What's more is Glenn Fox wrote in Eco24 Epidemiology: "The occurrence of an association in 25 more than one species and species population is veryFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 199

1 strong evidence for causation." 2 What I've just told you is that the 3 reproductive effects, the impact on sexual 4 differentiation by atrazine, has been shown not just in 5 multiple species of frogs but in multiple genera and 6 multiple families, including the Acridae the Hylidae, 7 the Bufonidae and the Ranidae; so at least five 8 families, not just species. 9 What's more is, I'm going to show you 10 briefly that my 39 colleagues and I have reviewed the 11 literature and shown consistent effects in fish and 12 reptiles; there are effects in birds, but they're not 13 strong effects and they require higher doses; and also 14 in mammals. 15 First off, I'd like to show you the 16 evidence that atrazine decreases testosterone and sperm 17 production, and this is after reviewing over 250 peer18 reviewed published papers in the open literature. So 19 here's testosterone decreased, in this case in goldfish 20 and here's a salmon. And these are ecologically 21 relevant doses, and you see a dose-dependent decrease 22 in testosterone levels in salmon. 23 So what we have seen now is that this 24 effect that I described to you in frogs of testosterone 25 decreasing not only occurs across species and generaFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 200

1 and family, but it occurs across vertebrate classes. 2 So multiple independent laboratories in every 3 vertebrate class examined has shown that atrazine 4 decreases the male hormone testosterone. 5 What's more is if you look at Moore and 6 Waring's work on salmon -- and this is work that's done 7 in England -- the decrease in plasma testosterone seen 8 in salmon is associated with a decrease in the 9 expressible milk or sperm in response to female salmon. 10 So the same effect that we saw in frogs -- testosterone 11 decreases, sperm decreases, fertility decreases -- 12 we're now seeing that same type of effect in fish by an 13 independent laboratory on another continent, in fact. 14 What's more is while putting this paper 15 together with my colleagues, even though I thought I 16 knew the atrazine literature very well, we discovered 17 something quite interesting. 18 So here's what I just showed you that we 19 just published. Here is a testes that's packed with 20 sperm. Here's a testes with dilated testicular tubules 21 and just cellular debris. That's the African clawed 22 frog work that I just showed you -- and this effect, by 23 the way, was produced at 2.5 ppb, animals exposed 24 throughout life. 25 This is work from my coauthor, KestemontFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 201

1 in Belgium, showing a very similar effect, in this case 2 in fish testis, where you're losing tissue and getting 3 empty spaces developing in the testis. 4 This is from my colleague in South 5 America working on caiman, so a type of crocodile, 6 where again you see densely packed sperm in the testis; 7 but when they're exposed to atrazine, you see these 8 dilated testicular tubules with a complete absence of 9 sperm. 10 And then finally multiple laboratories - 11 - this is one from Europe and one that's in Brazil, and 12 again coauthors on the paper we're working on -- showed 13 in rats, mammals, the same thing: sperm in the testis 14 unless they're exposed to atrazine. 15 So here you have an almost identical effect occurring 16 across vertebrate classes: from fish, amphibians, 17 reptiles and mammals. 18 What's more is we've shown in our most 19 recent paper that other androgen-dependent features are 20 absent or decreased in the atrazine-exposed frogs; so 21 the breeding glands, which you can see visibly or 22 histologically, are reduced in size. These are 23 androgen-dependent, and in the presence of atrazine the 24 decreased testosterone, you get a decrease in these 25 androgen-dependent glands.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 202

1 You see the larynx, so this is from our 2 paper again in African clawed frogs. You see a 3 decrease and an approach to a female-type larynx in 4 these animals exposed to atrazine. 5 This is from my colleague in South 6 America, again who's joined me on the paper, and here 7 he is measuring the clitoral penis length in caiman, or 8 crocodiles, that have been exposed to atrazine. 9 And again, you see this decrease in the 10 size of the androgen-dependent structure so that it's 11 intermediate between what you would find in an exposed 12 male and female; so again, consistent effects on 13 androgen-dependent secondary sex characteristics 14 following atrazine exposure, leading to this loss in 15 testosterone production and the destruction of 16 testicular tissue. 17 This is some work that was published on 18 rats showing a decrease in androgen, again in response 19 to atrazine. This is an independent study by Friedman, 20 et al., in 2002 showing a similar decrease. 21 And multiple papers have shown that 22 androgens are decreased in rats exposed to atrazine by 23 a variety of different mechanisms. And that literature 24 is all there, which I can make available for you. 25 This is unpublished data from Victor-FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 203

1 Costa, one of my coauthors on this upcoming paper, and 2 what they're showing here is that atrazine exposure 3 causes a decrease in weight in the rats, and so there 4 is some debate about whether or not the smaller testis 5 was a result of the animal just being decreased in 6 size; but in this particular experiment, they've 7 allowed a recovery period free of atrazine. 8 So you can see the body weight recovers, 9 but the testis size -- and you can see what the testis 10 looks like there -- the testis size does not recover. 11 So it's not just a matter of the animals having a 12 decreased body weight, and that's why you see the 13 smaller testis; there's a direct sort of toxic effect 14 on the testis in these animals. 15 Here's other data from all the way back 16 in 2000 showing a decline in sperm number in rats that 17 are exposed to atrazine. So again, that is consistent 18 with the demasculinization or the loss of androgens in 19 atrazine-exposed animals. 20 Shanna Swan showed that in humans in 21 Columbia, Missouri that there is a statistically 22 significant relationship between the amount of atrazine 23 in the urine and low sperm count, low fertility and 24 inability of what she called sub-fertile men to get 25 their wives pregnant.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 204

1 Now, again, correlation does not equal 2 causation; but my point is that when you look at the 3 loss of testosterone, the loss of sperm and decreased 4 fertility that we've seen in fish, in frogs, 5 amphibians, in reptiles and in laboratory rodents, that 6 makes me think that there's probably a little something 7 to this finding that we should look at more carefully. 8 What I've done now is change the axes, 9 because what you're looking at now are the atrazine 10 levels in men in California who apply atrazine in a 11 paper published in 1993. 12 What you're looking at now are the 13 levels of atrazine for men who apply atrazine; so this 14 was just the field workers, these are the men who 15 actually apply it. These men have 24,000 times the 16 atrazine in their urine than is associated with low 17 fertility in men in Columbia, Missouri. 18 Of course, I usually tell my public 19 audiences when I speak these men have 24,000 times the 20 atrazine that we use to chemically castrate and make 21 hermaphrodite frogs. I could dilute their urine 24,000 22 times and use it to chemically castrate 24,000 buckets 23 of 30 tadpoles each. 24 I am particularly concerned, of course, 25 because most of the men who work in agriculture inFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 205

1 California are Latino, 90%, some with life expectancies 2 of 50; so nobody knows anything about the reproductive 3 health of these men. 4 I'm particularly concerned, because if 5 you look at California, where we have the fifth largest 6 economy in the world, or at least reportedly, 1 in 10 7 jobs are in agriculture, 30% of the land is in 8 agriculture, we produce 350 agricultural products, 50% 9 of the U.S.'s food comes from California. We use more 10 pesticides than any other state, and 90% of the workers 11 are Hispanic. 12 If you look at the top 10 counties for 13 agriculture, the top 10 counties from pesticide use, 14 these are effectively the counties that make us the 15 fifth largest economy in the world. But if you plot 16 onto that the 30 poorest towns in California, look 17 where most of them fall -- and there's one in the 18 eleventh biggest agriculture count. 19 So the people who make us the fifth 20 largest economy in the world have the jobs and the 21 healthcare disparities, likely in part because they're 22 exposed to hazards -- not just atrazine, but other 23 pesticides as well. It becomes an environmental 24 justice issue, in my opinion. 25 So the other half of the equation --FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 206

1 does atrazine turn on aromatase and induce estrogen, 2 which causes egg-yolk production and egg production in 3 frogs, and might that be associated with other things 4 that we worry about in mammals -- Suzawa and Ingraham 5 showed in 2008 that zebrafish exposed to atrazine 6 express aromatase and make estrogen in a dose-dependent 7 manner. 8 We have now been able to show, because 9 now we can identify genetic males and females in frogs, 10 that females express aromatase in their gonads, and 11 part of the reason why we were never able to find this 12 before is because if you look at the atrazine-exposed 13 animals, the genetic males that are still males don't 14 express aromatase; but the genetic males that are 15 either feminized or partially feminized express 16 aromatase as if they're real females, even though, as 17 you can see, that's a genetic male that's expressing 18 aromatase. 19 And I've showed you that they have 20 circulating estrogen levels, but only those that are 21 showing the feminized behavior. 22 Sanderson, et al., in a number of papers 23 show that if you take an adenocarcinoma cell and expose 24 it to atrazine, it will start expressing aromatase and 25 making estrogen. Similar work has been shown by Fan,FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 207

1 et al. 2 This was a work that I coauthored in 3 another human cell line that if exposed to atrazine, 4 they express aromatase and make estrogen in a dose5 dependent manner. And Suzawa and Ingraham showed in a 6 number of other human cancer cell lines that they 7 express aromatase when exposed to atrazine as well. 8 So we're seeing an induction of 9 aromatase by atrazine across vertebrate classes: in 10 fish, in frogs, in reptiles, and now in mammals 11 including human cell lines. 12 The other interesting thing that we've 13 been able to show -- again, this has been in getting 14 this big paper together with my colleagues -- is that 15 here's my amphibians. These are leopard frogs with 16 testicular oocytes expressing eggs in their testis, an 17 effect that we never see in controls. 18 Now, people have given me a hard time 19 about using the word "never"; but here is my colleague, 20 Tillit, who did not coauthor the paper for us but 21 provided a figure. This is now in fish; so exposed to 22 atrazine, testicular oocytes developed in his recently 23 published study, and he never saw it in controls. 24 And now here's a colleague who joined me 25 on the paper, de Solla, who showed in turtles, nowFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 208

1 reptiles, testicular oocytes develop only when the 2 animals are exposed to atrazine; so again, similar 3 effects across vertebrates and, in this case, an effect 4 that you wouldn't expect to see in mammals, because a 5 mammal's gonads are sort of protected, if you will, by 6 the Y-chromosome in a very strong genetic mechanism. 7 And again, we've shown complete sex 8 reversal in genetic males exposed to atrazine, as I 9 pointed out earlier. And other colleagues -- and this 10 is from a second paper that we've all published 11 together now, 19 of us -- Suzawa and Ingraham showed a 12 dose-dependent loss of males in zebrafish exposed to 13 atrazine. 14 My colleagues, Oka and Iguchi, showed a 15 dose-dependent loss in males at ecologically relevant 16 doses; so you get more and more females as you're 17 exposed to atrazine. That's also been shown in 18 reptiles. de Solla showed that a male-determining 19 temperature in snapping turtles, you expose them to 20 atrazine and you start to get females when they should 21 all be male. 22 And another study in reptiles and 23 painted turtles shows the same thing at two different 24 temperatures: you increase the proportion of females 25 when animals are exposed to atrazine across theFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 209

1 eggshell; so again, partial feminization and complete 2 feminization across multiple vertebrate classes. 3 In the case of prostate cancer, there 4 are at least studies that show that atrazine, when fed 5 to the mothers, will increase the incidence of 6 prostatitis and the severity of prostatitis when the 7 mother is exposed to atrazine. 8 You may know about the study that was 9 done in St. Gabriel, Louisiana at Syngenta, and I want 10 to read to you some things that were written in that 11 paper with regards to prostate cancer. They wrote: 12 "The increase in all cancers combined seen in the 13 overall study group was concentrated in the company 14 employee group." They wrote: "The increase in 15 prostate cancer in male subjects was concentrated in 16 company employees." They wrote: "The prostate cancer 17 increase was further concentrated in actively working 18 company employees." They wrote: "All but one of the 19 cases occurred in men with 10 or more years since 20 hire." 21 And finally: "Analyses restricted to 22 company employees also found that the prostate cancer 23 increase was limited to men under 60 years of age." 24 And again, correlation doesn't equal causation; but 25 when you have a model experimental system that wouldFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 210

1 support atrazine as a possible cause, it would raise 2 concern for me. 3 That increase was 8.4-fold and concerns 4 me, because it's in an area known as Cancer Alley where 5 much of the neighborhood, so to speak, looks like this: 6 80% African-American. 7 With regards to breast or mammary 8 cancer, I was interested today to hear that 9 testosterone doesn't go down in rats, because that's 10 been shown before in other studies, and that E1 and E2 11 don't go up, because E2 and E1 definitely went up in at 12 least some studies in the published literature; so 13 there's an increase in estrogen just like we've seen in 14 fish, frogs, reptiles, now we're on to rodents. 15 I'm sure you know some studies have 16 shown an increase in the incidence of mammary tumors in 17 rats, and at least one study by Ueda showed that 18 "Atrazine treatment tended to increase the proportion 19 of estrogen receptor positive tumors and stimulated 20 cell proliferation in the DMBA-tumor(+) group". So 21 there's a mechanism there, an important mechanism. 22 A single study that I know of showed 23 with a P value less than 0.0001 that women whose well 24 water is contaminated with atrazine are more likely to 25 develop breast cancer. And again, there's a mechanismFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 211

1 by which that might occur, because we know that at 2 least in some human cell lines, atrazine increases 3 aromatase expression and estrogen production. 4 And I'm finishing up here on this one. 5 In fact, Fan, et al., a paper that I coauthored, show 6 that atrazine acts on phosphodiesterase to increase 7 cycle gain P, leading to upregulation of aromatase. 8 That was shown by Sanderson, et al., before; but Fan, 9 et al., in two papers suggested that atrazine also 10 increases SF-1, another important transcription factor 11 binding in the nucleus. 12 Suzawa and Ingraham have interpreted 13 this differently and think that there are other 14 upstream genes that are turned on that lead to the 15 increase in SF-1 content. 16 My current graduate student has shown 17 that in breast cancer cells, some cell lines, atrazine 18 upregulates aromatase. And that's a significant 19 concern, because the local expression of aromatase is 20 very important in breast cancer. 21 Local expression of aromatase and 22 estrogen production may promote or will promote already 23 damaged cells; so while atrazine might not be a 24 carcinogen itself, by increasing aromatase expression 25 it potentially could lead to this increase in estrogenFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 212

1 receptor positive tumors. 2 In fact, as you may know, the treatment 3 of choice right now for breast cancer is letrozole, 4 which blocks aromatase to decrease estrogen to prevent 5 those damaged cells from growing and spreading. It 6 doesn't make much sense when we're using 80 million 7 pounds a year of a chemical that does the opposite, 8 that turns on aromatase and increases estrogen in every 9 vertebrate class examined. 10 And I know that the Registrant gets 11 upset when I point this out, but Novartis Oncology 12 offers treatments for cancers that range from breast 13 cancer. 14 I can't imagine that there wasn't some 15 conversation when in January of 2000 a paper was 16 published that included one of Syngenta's funded 17 scientists, John Giesy, where he wrote: "The observed 18 induction of aromatase, the rate-limiting enzyme in 19 the conversion of androgens to estrogen, may be an 20 underlying explanation for some of the reported 21 hormonal disrupting and tumor-promoting properties of 22 these herbicides in vivo". 23 I didn't write that; that was work that 24 was done by one of the Syngenta scientists, Sanderson, 25 et al.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 213

1 Then in that same year in July 2000, a 2 marketing application for first-line letrozole 3 treatment of postmenopausal women was applied for by 4 Novartis. And then in November of 2000, that same 5 year, as you can see here, by November of 2000 Syngenta 6 simply does not manufacture or sell pharmaceutical 7 products. 8 And I'm not implying that there's any 9 kind of sinister plot or anything like that; but we 10 have this interesting chronological relationship where 11 in January of 2000 they discovered that atrazine 12 induces aromatase and potentially promotes breast 13 cancer; in July 2000, they at least apply for an 14 aromatase blocker to treat breast cancer; in November 15 2000, they stop selling atrazine, and then Syngenta 16 starts. I guess all I'm saying is it should be as easy 17 to get an aromatase inducer off the market as it is to 18 get an aromatase blocker on the market. 19 I want to end by pointing out, well, one 20 of the reasons that I feel passionate about this issue, 21 and one of the reasons that I point out is that 90% of 22 agricultural workers are Mexican/Mexican-Americans and 23 that the company that manufactures atrazine is in a 24 community that's 80% African-American. 25 These are the top 13 cancers that we getFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 214

1 in this country. The ones in red now, 11 of the 13, 2 are the ones that African-Americans are more likely to 3 get relative to Caucasian-Americans. What I am going 4 to show you now, out of these 13, the ones that 5 African-Americans are more likely to die from relative 6 to Caucasian-Americans. 7 Is there a biological difference, or is 8 it that African-Americans are more likely to live in 9 communities where they come into contact with these 10 kind of environmental hazards? 11 Is it a biological difference, or is it 12 more likely that African-Americans and Hispanic13 Americans are more likely to work in occupations where 14 we come in contact with these hazards that are having 15 consistent effects in everything from fish all the way 16 up to human cell lines? 17 I think that my work on this aquatic 18 organism is indeed telling me something about this one, 19 and I think what we should be learning is that we 20 should use more sensitive model systems if we want to 21 protect the most vulnerable. Frogs may be more 22 sensitive because they live in the water and they have 23 permeable skin; but by using amphibian data, then you 24 protect the animals that are less sensitive and less 25 vulnerable.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 215

1 And in the same case, I think we need to 2 focus on more vulnerable components of our own species: 3 the unborn fetus and the minorities who live in and 4 work in areas where they are more likely to be exposed 5 to chemicals that are having, in this case, consistent 6 effects across vertebrate classes. 7 I didn't go into it because I knew Dr. 8 Fenton would go into it, but there are many other 9 effects in rats. There's the immune failure effects, 10 the prostate/mammary cancer effects that have already 11 been described. Atrazine causes neural damage when 12 pregnant mothers are exposed, and there are several 13 papers showing that. Atrazine has been shown to induce 14 abortion in rats that are exposed when they're 15 pregnant. Atrazine has been shown to cause prostate 16 disease in the pups when the mothers are exposed. 17 And as you just heard, atrazine impairs 18 mammary development, Dr. Fenton's work, which it's 19 interesting that there are studies that would suggest 20 now that there are no mammary problems, because if 21 that's the case, then why is it that in the second 22 generation you get impaired growth and development 23 because the mother that has been exposed is incapable 24 of making enough milk to support their offspring? 25 In fact, this is one of the studies thatFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 216

1 concerns me the most and that moves me the most, 2 because this particular animal, if I understand the 3 study correctly, was never exposed to atrazine. This 4 particular animal suffers from atrazine that his 5 grandmother was exposed to. 6 When I think about my little daughter, 7 and when I think about the fact that studies in Europe 8 now are showing that even after 10 years that atrazine 9 levels have not changed in the aquifers and in the 10 groundwater, that means that not only have we already 11 been exposed; our children will be exposed, our 12 grandchildren will be exposed. 13 And so when I think that there's even a 14 remote possibility that studies are suggesting to me 15 that my granddaughter's granddaughter could suffer from 16 atrazine that we are applying today, and we sat here 17 and didn't do something to prevent that from happening, 18 it moves me. 19 Sir Austin Bradford Hill also wrote: 20 "All scientific work is incomplete, whether it be 21 observational or experimental. All scientific work is 22 liable to be upset or modified by advancing knowledge. 23 That does not confer upon us a freedom to ignore the 24 knowledge we already have or to postpone the action 25 that it appears to demand at a given time."FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 217

1 The data is stacking up: amphibians, 2 fish, reptiles, rodents, human epidemiology and cell 3 studies. It's getting pretty complete. And I would 4 suggest that it's time for action. 5 Thank you. 6 DR. STEVEN HEERINGA: Thank you very 7 much, Dr. Hayes, and I especially appreciate your 8 sticking to the allotted time. It's appreciated by the 9 Panel. 10 At this point in time, I'd like to move 11 to the next scheduled public commenter, who is Rod 12 Snyder, who is Director of the National Corn Growers 13 Association. 14 Rod? Rod Snyder here? 15 I guess he's not here. Let me move on, 16 then. We'll return if Mr. Snyder shows up. 17 The next scheduled public commenter, 18 according to scheduling arranged by the SAP Office, is 19 Jere White, who is the Executive Director of the Kansas 20 Corn Growers Association and the Kansas Grain & Sorghum 21 Producers Association. And I think Jere there -- I 22 recognize you -- is representing on behalf of the 23 Triazine Network, and the handouts are on their way to 24 the Panel members. 25 Mr. White, welcome.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 218

1 MR. JERE WHITE: Thank you, Chairman 2 Heeringa and members of the Committee. My name is Jere 3 White. I am the Executive Director of the Kansas Grain 4 & Sorghum Producers Association; also the Kansas Corn 5 Growers Association in central Kansas in a small 6 community called Garnett. 7 With me here today as part of our 8 Network panel is Dr. James Lamb, John Hall, Gary 9 Marshall from the Missouri Corn Growers Association and 10 Dr. David Bridges, and I'll start out our comments. 11 A little bit about the Triazine Network, 12 and certainly I have had the opportunity to meet a lot 13 of you in previous SAPs. I think we've been certainly 14 present at every SAP since 1994 dealing with atrazine 15 and always look forward to the experience. 16 We do believe that it is the SAP that 17 helps sort things out scientifically in the end, and 18 that's really what we're all about. The Network is 19 just simply a coalition, it's not a formal entity, and 20 we represent commodities including certainly corn and 21 grain sorghum but also citrus, tree fruit, vegetables, 22 grapes, sugarcane -- over 30 commodities grown in over 23 40 states. 24 We also represent general farm groups, 25 including Farm Bureaus at the State level, FarmersFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 219

1 Union, American Agri-Women, a number of different 2 stakeholders and, of course, individual producers. We 3 were formed in 1995 to secure a scientifically based 4 outcome to what was in the EPA Special Review of the 5 triazine herbicides. 6 And in that capacity, we serve as sort 7 of a liaison between growers and the Agency and other 8 Agencies and also with the Registrant. So we take our 9 issues all directions and certainly have a vested 10 interest in doing so and continue to do so at this day. 11 A quick review of what I'd call triazine 12 in the new millennium, although obviously the 13 millennium isn't so new now. 14 June 27th, 2000 SAP, overseen by Clinton 15 EPA Administrator Carol Browner, eventually found that 16 atrazine is not likely to cause cancer in humans. 17 The Re-Review concluded on October 31st 18 in 2003, again in this case conducted principally under 19 Bush EPA Administrator Whitman, found a reasonable 20 certainty of no harm. 21 A Cumulative Risk Assessment on June 22, 22 2006 also found a reasonable certainty of no harm 23 associated with the use of atrazine in accordance with 24 EPA guidelines. 25 2003 SAP proceeding focused on theFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 220

1 reports of atrazine's effects on amphibian reproductive 2 development and found that evidence submitted provided 3 an insufficient basis for any definite judgment. 4 And finally in 2007, EPA concluded that 5 it was reasonable to reject the 2003 hypothesis that 6 atrazine exposure can affect amphibian gonadal 7 development. The EPA also determined that there was no 8 compelling reason to pursue additional testing. 9 Let's move forward a little bit, July of 10 2009. If you were to go to the EPA website in 2009, 11 you would find -- and again, this was six months into 12 the current Administration -- that EPA reports to the 13 public that based on review of available scientific 14 studies, EPA has determined that atrazine is not likely 15 to cause cancer in humans. 16 This determination was based upon "the 17 best scientifically available data" and allowed 18 preeminent independent scientists, such as yourselves, 19 to ensure that the Agency was using the highest quality 20 data in its decision-making process. And for that, we 21 thank you. 22 Then things started to change. In 23 August of 2009, we were in a phase of what I would 24 characterize as the machinery beginning to turn. It 25 started with an NRDC report that focused on theFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 221

1 activists' claims -- and certainly, I don't think that 2 the folks that were quoted and drivers of a lot of the 3 information in that report would deny that they were 4 activists; in some ways, we're all activists. It was 5 seeded to the New York Times. 6 NRDC takes credit on their website of 7 seeding the stories that New York Times ran, and 8 subsequently picked up or almost simultaneously picked 9 up by the Huffington Post. 10 Yet in that time, the activity of trial 11 lawyers -- and I couldn't find a good graphic for trial 12 lawyers, so I just used a skunk because it was 13 convenient 14 (Laughter.) 15 MR. JERE WHITE: --and you have all the 16 same churning and feeding off each other, and obviously 17 the EPA was under a lot of pressure. 18 Dr. Hayes just gave comments before the 19 Committee; but I'd like to share an email that he 20 shared with members of Syngenta's team the day before 21 the April SAP, and this is a quote from that. 22 He confirmed they'd entered Phase 5 -- 23 and I'm not sure what that means, but I guess that's 24 where we're at. "Our destination will surprise you -- 25 we enter our final approach." He chose theFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 222

1 destination, he set the course, he paved the way, he 2 set the pace, and most importantly, he directed the 3 traffic. 4 Make no mistake about it. He did this. 5 Now, I don't necessarily agree, I don't even know what 6 the heck it means; but perhaps we'll sort that out in a 7 future SAP. 8 I would know that a lot of the things 9 that Dr. Hayes shared with you were the subject of 10 previous SAPs, by Panels very much like those that 11 you're part of today. In fact, some of you likely were 12 part of those Panels. 13 And even though some people might try to 14 suggest that somehow a Bush SAP was different than a 15 Clinton SAP, which is different than an Obama SAP, from 16 where we've sat over these years, the SAP was simply a 17 group of scientists trying to do the best they could 18 with the information that was made available to them. 19 I trust you're the same as they were under previous 20 Administrations; and again, we respect and applaud you 21 for your work in that area. 22 Then in October of 2009, EPA began to 23 respond to this machinery that I referenced earlier. 24 They announced a comprehensive scientific review with 25 four SAPs in FY10 -- and this in fact is the fourth SAPFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 223

1 -- and two more announced in 2011. 2 I would point out, I guess based on the 3 previous presentation, it's good that one of those is 4 dedicated to amphibians, and the other is dedicated to 5 ag health. And certainly, we've made the point before 6 and I stand by it and my growers stand by it that if 7 there's a legitimate issue at the farm level, it's 8 certainly a legitimate issue for the people that I 9 represent and pay my way to be here. 10 We care about these things. We're 11 affected by it personally; my family has been affected 12 by some of these things. We don't take it lightly. 13 Upon consideration of the studies, EPA 14 referenced to initiate the new review of atrazine. So 15 if you go back to last October and you look at what 16 they said was driving it -- the media reports and some 17 of the studies that were there -- the fact is that the 18 February SAP dealt with the majority of those studies 19 and concluded that the overall quality of these studies 20 was relatively low, thus limiting their applicability. 21 But then if you take it a step further, 22 had the Agency followed its own process, typically in 23 the past before providing the information to other SAPs 24 to consider, it would have known that the new studies 25 were not useful on the regulatory decision-makingFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 224

1 process. 2 We believe that. There was a rush to 3 create a reaction to what was happening in the media, 4 and the reality is as we look at it at the end of the 5 process or towards the end of the process, at least for 6 the first year, it's good that we've done that because 7 you have addressed those issues, and in fact we're 8 moving on. 9 But what about this transparent process? 10 If you go back to the last SAP, Dr. Lowit at the tail 11 end of the Agency remarks made a comment that said that 12 they had been directed to form a small army with a very 13 large task in a very short timeframe. 14 When my constituents see that, quite 15 frankly, they don't understand. It's been part of a 16 special review since 1994. We didn't see the immediacy 17 of it. In fact, the work plan that's been laid out 18 does not suggest any immediacy. 19 The Agency has also testified before 20 Congress that the new review is being used in its 21 preparation for the scheduled 2013 re-registration of 22 atrazine. It's on a very long list of products, and in 23 fact if you look at, which I did just last night, the 24 Pesticide Registration Review Status, neither atrazine 25 nor triazines are listed as currently active.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 225

1 So where does this process fit? We're 2 not sure, but the Agency maintains that what it's doing 3 today is certainly not part of special review. Special 4 review is not concluded, but this isn't part of it. 5 The actions of a rush re-review process do not align 6 with the Agency's position on a re-registration process 7 that is still three years away. 8 We'd also say that if you look at this 9 specific SAP, we've had an extremely short timeframe 10 between the posting of questions on the Docket or on 11 the website and this meeting, and if you look at the 12 actual posting, which I believe occurred on a Friday -- 13 the date escapes me -- the written responses were due 14 into the Docket the following Tuesday. 15 I'm not sure how that works for a 16 transparent and open process that invites all 17 stakeholders to participate. Thank God I'm sitting in 18 my seat and not in your seat. I can't imagine that you 19 don't feel very challenged to respond to the huge 20 volume of science that typically covers very different 21 disciplines. 22 I also want to share my final comments 23 that growers and others that have provided comments to 24 the SAP in the past in support of atrazine are now 25 being targeted by these trial lawyers -- that skunkFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 226

1 from the previous slide -- through subpoenas for 2 massive records unrelated to any litigation that's 3 ongoing. 4 And in fact, among the group's 5 testifying before you today, three of those ag groups 6 have been served subpoenas since Friday. It's clear, 7 sending a message; we think it's very clear: if you 8 stand up for atrazine, you best be prepared to pay a 9 price. 10 And again, I did a slide yesterday 11 afternoon, I guess it was; it's out of date. One more 12 of the ag groups testifying today have been subpoenaed 13 since then. 14 And it's not just about what do you know 15 about something to do with the case. It has to do 16 with, for instance, any membership record between 17 Kansas Corn Growers and National Corn Growers. Doesn't 18 have anything to do with atrazine. Doesn't have 19 anything to do with any case in Holiday Shores. 20 But again, it is a burden that's being 21 placed on people that think they want to get into the 22 arena as a stakeholder on behalf of their constituents 23 in agriculture and on behalf of this product, and it is 24 obscene. 25 Finally, on behalf of the growerFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 227

1 community that I represent, we do want to thank the 2 members of the SAP for your time and your effort. It's 3 been a long process. Ran into Dr. Fenner-Crisp in the 4 hallway the other day, and we commented that we've been 5 doing this a long time: her in different capacities, I 6 guess me in the same capacity. 7 It's been a tough job, there is still 8 work to do; but I can assure you that besides the 9 intimidation that agricultural organizations are 10 getting right now, beyond that, we'll see you next 11 time. We will be back. 12 With that, I'd like to turn it over to 13 the next presenter in our group, which is Dr. James 14 Lamb, and I'll let -- 15 DR. STEVEN HEERINGA: Mr. White? 16 MR. JERE WHITE: Yes, sir. 17 DR. STEVEN HEERINGA: I wonder if I 18 could suggest something. 19 MR. JERE WHITE: Sure. 20 DR. STEVEN HEERINGA: People have been 21 sitting since a quarter after 1:00. I wonder, would 22 you be willing to take a 15-minute break and then come 23 back and do the three presentations? 24 MR. JERE WHITE: Absolutely. 25 DR. STEVEN HEERINGA: It's a littleFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 228

1 discontinuous, but you can pick up there and 2 MR. JERE WHITE: Yeah, we'll have four; 3 but, yes. 4 DR. STEVEN HEERINGA: so people won't 5 be fidgeting and leaving. 6 MR. JERE WHITE: That will be fine. 7 DR. STEVEN HEERINGA: So why don't we do 8 that, and we'll reconvene at ten minutes after 3:00 and 9 then continue with the presentations? 10 MR. JERE WHITE: Thank you. 11 (WHEREUPON , a recess was taken.) 12 DR. STEVEN HEERINGA: Welcome back, 13 everyone. At this point, we are in our period of 14 public comment for the FIFRA SAP meeting. We just 15 heard from Mr. Jere White representing the Triazine 16 Network; and I think, Mr. White, you are about to 17 introduce your fellow participants here. 18 MR. JERE WHITE: Thank you, Mr. 19 Chairman. At this point, I'd like to introduce 20 Dr. James Lamb. I'll let him brief the Committee on 21 his background. 22 DR. JAMES LAMB: Sure. 23 MR. JERE WHITE: And with that, Jim? 24 DR. JAMES LAMB: Hi. For those of you 25 who know me and wonder why I'm sitting here, we do haveFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 229

1 75 acres in production right now. For those of you who 2 don't me, I'm actually here as a toxicologist, not a 3 farmer. I've been working in toxicology, published in 4 reproductive and developmental toxicology, endocrine 5 tox and risk assessment since 1976. 6 I was Head of the National Toxicology 7 Program's Fertility and Reproduction Group for a few 8 years. I then came to the U.S. Environmental 9 Protection Agency, where I worked with some unnamed 10 people on this Panel. And I am currently the Center 11 Director at Exponent Center for Toxicological and 12 Mechanistic Biology. 13 So I was asked, actually, by this group 14 to talk about my review of some of the non-cancer 15 issues and, very specifically, it really came down to 16 talking about the EPA LH study that you heard about 17 earlier. 18 I'm going to talk a bit about the study 19 design and interpretation; an audit that we did of the 20 available data, which this is the study that's proposed 21 to be the basis for a change in the point of departure. 22 I'm going to talk about the levels of suppression 23 associated with adverse effects a little bit and 24 whether or not such changes should be treated as 25 adverse effects or not.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 230

1 Of course, what I'm talking about here 2 is the Cooper 2010, et al., paper. For full 3 disclosure, I've known Ralph for 30 years. He's much 4 older than I am. 5 (Laughter.) 6 DR. JAMES LAMB: And we've published 7 together, and I've had the pleasure of working with 8 him. I hope he talks to me after I'm done with this 9 talk, because there are certain things within the study 10 design that I think I'm recommending he go back and 11 take a look at before he submits it for peer-review 12 publication. 13 This is work that was done in 2003, 2004 14 and recently reported as an internal report. It is 15 described as a three-block study design. It is a 16 large, complex study; there was an awful lot of hard 17 work that went into generating the data. 18 They did administer atrazine by gavage. 19 It is looking for a potential sensitivity of a hormonal 20 change at the peak of the LH surge. It required, as 21 you can imagine, very precise timing of the animals; 22 and we can go through what he did to make sure that 23 that happened, and it was a lot of work and they are to 24 be commended for that. 25 What we did in our review is we startedFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 231

1 with the summary tables that they developed and worked 2 back to the handwritten data. Now, our review by 3 necessity was limited to the data submitted to the 4 Docket. So I think most of you have seen the files in 5 there. We were able to get our way back to handwritten 6 data that really helped us understand where the numbers 7 came from, from that summary table all the way back to 8 the handwritten notes. 9 There are still some questions we have 10 about that. That's not a criticism as much as it is a 11 recognition that it's hard to do this when you don't 12 really know exactly how to work your way through it, 13 and we weren't able to ask. 14 We reviewed a number of endpoints that 15 are listed here; you can read them, but it's the basic 16 endpoints of the study. But I'd like to talk a bit 17 about the design. 18 It's described as a three-block study. 19 There are eight dosing groups in these plus three sets 20 of controls; you can see them listed up here. There is 21 an overlapping approach to this. They started with 22 Block 1 with two dose groups. 23 Block 2 had three dose groups, which 24 included the lowest level in Block 1. And Block 3 had 25 three dose groups, which actually included repeatingFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 232

1 the lowest group in Block 2. So you had Blocks 1 and 2 2 with one dose-group overlap; Blocks 2 and 3 with one 3 dose-group overlap; Blocks 1 and 3 having no overlap. 4 I'm more inclined to describe this as 5 three separate experiments than I am a real block 6 design where you would have just distributed the dose 7 levels across the various blocks. It may or may not 8 matter to you. It seemed to make a difference even in 9 how some of the data might be interpreted, though. 10 Age, though, was not distributed equally 11 across the blocks or across the dose groups or the time 12 points. In addition to all these dose groups we've 13 talked about and the three blocks, there are also time 14 points because they're trying to time the LH surge 15 meticulously within 2-hour windows. 16 So they may not hit the peak exactly, 17 but they're trying to get it as close as they can based 18 on the previous day's estrus or proestrus smear; 19 however, in our audit of the data, I could not find 20 that they used the Block 3 controls in the analysis. 21 So I don't see anything that shows a pair-wise 22 comparison between the Block 3 controls compared to the 23 Block 3 animals, or that the Blocks 1, 2 and 3 controls 24 were brought together to compare against the dose 25 groups.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 233

1 There was a question I had about the LH 2 data. We could find the LH data for Block 3. There 3 are three columns listing LH data. The data, if you go 4 from the handwritten data up to the summary data, they 5 always come from one of those three columns or 6 occasionally a handwritten value. 7 There's nothing in writing that tells me 8 how. I am certain they had a rationale as to which 9 they picked. There were different dilutions, I can't 10 tell you really why they picked the numbers they did; 11 but I completely understand there's a reason why they 12 did. But you have three columns, so for auditing 13 purposes I can tell you the number is in one of those 14 three columns; but it's not always the same column. 15 We couldn't find the LH data, and I got 16 people with a lot better eyes than me. We couldn't 17 find the LH data for Block 1 or Block 2, so we couldn't 18 verify those raw data. The LH looks generally higher 19 in Block 1 than 2 or 3. 20 I don't think they're statistically 21 different because you've got one really low value in 22 that group, but they don't look the same across the 23 groups to my eye. So if you plot them, you might 24 wonder why then you would use all three controls 25 together and all three blocks together instead of oneFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 234

1 block at a time respectively. I think there's useful 2 data in there; I just don't think it's been analyzed 3 quite correctly at this point. 4 I found the number of data errors to be 5 quite low, and by that I mean there are some errors. 6 There are places where you can see in the summary table 7 the dose level is listed wrong for one of the time 8 points. It is wrong. When you go back to the raw 9 data, they moved it correctly to the wrong place. It's 10 included in the statistics. 11 It's an error. It's an easily corrected 12 error. There are things like that that you would 13 expect in moving thousands of data points around by 14 hand would happen; they're there, we saw probably less 15 than a dozen of these, but they're easily corrected. 16 There were three inclusion criteria that 17 we also looked at. Did they establish a 4-day 18 regular estrus cycle? We went back and looked at all 19 of these, which is why I had to bring my glasses today. 20 They did a great job of following the 21 estrus cycle. The coding was a bit unfamiliar to us, 22 but we ended up convinced that in almost every case 23 they had a 4-day estrus cycle. It was regular if they 24 included the animal in; but there are a couple of 25 places there where we think they made some errors,FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 235

1 including animals that shouldn't be included. 2 They also used a bright line for uterine 3 weight increase of about a half a gram. Somebody 4 yelled at me that it was greater than 0.5. I really 5 couldn't tell, because I'm not sure they had a 0.500 6 animal in there; but they used a bright line, the 7 uterine weight had to be greater than a half a gram, 8 they seemed to follow that religiously. 9 They said that they had increased 10 progesterone factored into the inclusion criteria. We 11 sorted all of the data by progesterone levels. 12 "Increased" implies more than one level; there isn't 13 more than one level. There is no bright line that 14 jumped out of us, so I wasn't so clear that they have 15 three inclusion criteria; they may only have two. But 16 the two that they have, we felt that they applied them 17 appropriately. 18 My view is this study is best suited 19 towards exploring a Mode of Action. This is not really 20 a risk-assessment or a regulatory study. The 4-day 21 gavage exposure to animals very precisely timed is 22 going to give you very precise information about the 23 amplitude of the LH curve, of the LH surge. 24 It's not necessarily going to tell you 25 whether or not you're into an adverse effect, and theyFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 236

1 do have the complication now, too, of figuring out 2 whether they really have a pseudo-steady state with 3 these gavage or do they have four sequential dosings, 4 and how do they figure out how to take that to 5 extrapolate to humans? 6 So I think the gavage versus humans is 7 going to play a significant role in how to interpret 8 these studies. 9 As I say, we reviewed the data in the 10 Docket, we went through a number of these things. I 11 have a couple of tables in here. The bottom, I've 12 talked about the first four of these bullets; but the 13 fifth one is the range in ages not distributed across 14 the groups, and I have a chart here, which if you can 15 see the little screen on the left you can see that 16 these are colored bars. 17 But the bottom line is this says the 18 number of animals at 1800-hour time point -- I'm only 19 showing one time point -- the number of animals in each 20 of the groups. Now, the groups are control, Block 1, 2 21 and 3, and then each of the dose groups with, for 22 example, the overlapping dose groups treated 23 separately. 24 I'm giving you a sense of what the age 25 of these animals is and how they were distributedFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 237

1 across the study, because we didn't see a pattern that 2 was very regular as far as the distribution across the 3 study. 4 In fact, there is an 8-week range in age 5 in this study. I'm not sure that's a huge problem, but 6 the animals are gaining weight; there's probably, what, 7 10 to 15 grams per week for these Long-Evans rats in 8 this age range. 9 So the gaining weight, the ones at the 10 beginning are going to be less mature and smaller than 11 the ones in the end; so comparing across these 12 complicates things a bit, I think. 13 It is interesting, though, the last 4 14 weeks really only came from the Block 1 group. So it 15 is an area where the Block 1 animals are very different 16 from the other animals. And there are, though, Block 1 17 animals in weeks 11, 12, 13 and 14, and it seemed like 18 they narrowed the age range as the study went on; it 19 got tighter as they did this more. 20 So in trying to think of this especially 21 as a block design, the dose levels are not really 22 evenly distributed across the blocks. The age is not 23 really evenly distributed across the blocks or even the 24 dose groups. Is there an effect of age or body weight 25 demonstrated in the control?FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 238

1 We didn't test it, but I think it's 2 something that could easily enough go back and be 3 tested to see whether or not that's part of what might 4 be observed here. 5 I think that they need to go back and 6 use the Block 3 controls. I don't think there's any 7 reason not to use them, and there was nothing in there 8 that indicated that that was purposeful. I'm not sure 9 what happened. 10 But bottom line really in this is I 11 think it's an interesting study into the Mode of 12 Action; but does it predict or is it an adverse effect 13 compared to effects like ovulation, estrus cycle, 14 fertility or effects seen in males as well? 15 I don't think it is by itself an adverse 16 effect. It takes a substantial suppression and a 17 statistically significant difference in LH levels by 18 itself I don't think gets you to adverse effects. You 19 should instead be looking at either very severe 20 suppression or severe suppression that result in 21 effects in ovulation cycle or the males' effects on 22 preputial separation testosterone, accessory sex-organ 23 weight. 24 There are other studies that have been 25 described that do get to other endpoints and do showFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 239

1 that I don't think anyone doubts their link between LH 2 and adverse effects. It's just whether or not it is by 3 itself such an effect. This is really more basic 4 research getting into time points. 5 So in the end you've got a large 6 assessment of atrazine looking at various hormones, 7 including the LH surge, at a particular time point. I 8 actually think the study would have been better -- it 9 might have been harder, but it would have been better 10 to have somehow done serial collections from the same 11 animal than to have done only terminal sampling. It's 12 not really a block design. 13 I think although there are relatively 14 few errors, there are things in the study as it is in 15 the internal report that I think need to be looked at 16 and corrected before it is submitted for publication. 17 And in the end I don't really think that the change 18 that they're describing qualifies as an adverse effect. 19 So, thank you for your attention. 20 DR. STEVEN HEERINGA: Thank you, Dr. 21 Lamb. 22 Mr. White. 23 MR. JERE WHITE: Thank you, Jim. 24 At this point, I'd like to introduce 25 John Hall. John is with Hall & Associates here in theFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 240

1 D.C. area. He has worked actually with my real work 2 back in Kansas over the years as a consultant on water 3 issues. And I think he probably is the only confrere 4 in our group that does need to depart after we get done 5 as a group today. 6 DR. JOHN HALL: Thank you, Chair, and 7 good afternoon, everyone. My name is John Hall, and 8 I'm the founder of Hall & Associates. 9 By way of a little bit of background, I 10 have degrees in mathematics, environmental engineering 11 and law. With regards to the law degree, I was not 12 offended in the least regarding the skunk that was put 13 up on the earlier slide. I in fact tend to agree with 14 that characterization, unfortunately more frequently 15 than I would like. 16 Our group at Hall & Associates is fairly 17 unique. We address drinking-water and wastewater 18 issues, treatment issues for municipal, agricultural 19 and commercial interests all over the country and have 20 over 30 years' experience in doing this. 21 Our approach is not to point fingers. 22 We try to get in there where there's a difficult 23 problem and seek to integrate the needs of the various 24 interest groups to see if we can come up with a cost25 effective solution to a regulatory compliance problem.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 241

1 And that's what leads me here today to talk Safe 2 Drinking Water Act requirements, how they're changing 3 and how in fact these changes have a bearing on what 4 human health exposures might or might not occur in the 5 very near future with regard to atrazine. 6 Now, a little bit of background, I'm 7 sure everybody knows that there's Safe Drinking Water 8 Act. It's gone through a series of amendments over its 9 many years of implementations. 10 It started in '74, and in 1986 there 11 were major amendments that were instituted. Those 12 amendments focused primarily on bacteriological issues 13 related to surface-water treatment and disinfection, 14 and EPA had a set of rules come out on what's known as 15 the Microbial and Disinfection Byproducts Cluster. 16 The issue is interesting. I mean from a 17 public-health respective, I think all of us would 18 probably agree that little has done more to protect 19 public health in this country than disinfection. I 20 mean, you can get sick very quickly and very badly with 21 any type of untreated water, with the exception I 22 suppose of well water, which is less subject to 23 bacterial infection. 24 With that said, disinfection is not 25 perfect. It has some ancillary negatives associatedFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 242

1 with it, and they come up with disinfection byproducts 2 and the concerns that come up there. 3 So in 1996 further amendments got put in 4 place, and there were basically two major rules that 5 came out. One was the long-term surface water and 6 enhanced surface-water treatment rule, because 7 originally there was a surface-water treatment rule; 8 this was enhancement number 1, and then enhancement 9 number 2 which came out in 2006. 10 The bottom line of all of this is that 11 treatment technology mandates are changing across the 12 whole country, and they are changing in particular for 13 the types of systems that we're concerned with at this 14 SAP. 15 Now, to give you an idea of how the 16 requirements on stage 2 of surface-water treatments are 17 changing with regard to disinfection byproducts, you 18 can see that there are some timelines applicable for 19 various sized communities, anywhere from 100,000 -- 20 they skipped the earlier states to start -- down to 21 10,000, they get the latest states to start. 22 Start doing what? Initiate 23 distribution-system evaluations: find out what kind of 24 problems they do or don't have with regard to 25 disinfecting byproducts, haloacetic acids, things thatFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 243

1 can form disinfection byproducts. 2 And then with regard to treatment 3 installation, there is a schedule here also. The 4 larger ones come in first April 2012, and then the 5 smallest communities are supposed to have their 6 situations dealt with by 2013. 7 The point I guess being right now it is 8 currently September 2010, and so these communities are 9 in the middle of their decisions as to what to do if 10 they have a disinfection byproduct-related problem. 11 Now, here's where the issue comes up. 12 As part of the white paper, we went back and evaluated 13 the systems that from 2002 to 2009 within EPA's 14 database that indicated there was an atrazine concern 15 related to the drinking-water source. 16 And let me explain this chart for a 17 second. This is the number of community water systems. 18 Community water systems that have what? Well, whether 19 or not they have packed carbon or granulated activated 20 carbon. Why are we looking at that? 21 Because we know if you have that in 22 place, it reduces the ability of atrazine, if it's in a 23 surface water, to get through to a finish water. So 24 this whole question of you look at raw versus finish 25 water comes up fairly importantly when you evaluate howFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 244

1 these systems are doing with regard to atrazine, 2 trihalomethanes or other Safe Drinking Water Act 3 requirements. 4 Let me just run a line through, so you get 5 the idea. There's approximately 44 systems I believe 6 that are identified as community water systems in high7 exposure areas. Only one of those systems in this 8 first 8 that has no PAC and no GAC, only one of those 9 systems was in violation; it had 4 violations. 10 However, 6 of the 8 systems are in violation of 11 trihalomethanes and haloacetic acids. And then there's 12 the same 6 have other surface water- treatment 13 problems. 14 Then you look at another 27 of the 15 systems, some that have PAC but no GAC. Two of those 16 27 had again 4 violations each; but 14 of the 27 had 17 haloacetic acid/trihalomethanes disinfection byproduct 18 issues. 19 Then when you go to these systems that 20 have GAC or GAC impact, you see no atrazine problems, 21 and still some remaining disinfection byproduct issues. 22 Well, what's the issue on all of this? 23 Well, by 2013, these exceedances have to be addressed. 24 And in my experience -- oh, a second point before we go 25 to that.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 245

1 The number of atrazine problems is small 2 compared to the number of trihalomethane and 3 disinfection byproduct issues these systems have. That 4 does not mean you ignore atrazine, I want to be 5 perfectly clear about that; but it does raise the 6 question of does the same solution that is going to 7 take care of this problem address any residual issue 8 that may be associated with atrazine? 9 In my experience, these communities are 10 going to do one of three things, the ones that have 11 significant issues with their surface water. I mean, 12 you are in an agricultural land; so it should not be a 13 shock to anyone that you have elevated carbon levels 14 getting into a system, which then can allow the system 15 if it is using chlorine to cause a disinfection 16 byproduct concern. That shouldn't be a surprise. 17 But what we tend to find with these 18 systems, because they tend to be the smaller ones, one, 19 the first thing they look at is can they discontinue 20 use of the water supply they currently have. Why? 21 It's expensive to put in some of these treatment 22 technologies. 23 So if there's a nearby system they can 24 tie into that doesn't have this problem, they 25 discontinue. It's way cheaper to run a pipe than it isFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 246

1 to put in a treatment technology and just continue to 2 operate all the time. 3 The next thing they look at is do they 4 have multiple water supplies. Is there another source 5 where they can blend or discontinue use of a particular 6 source under a period, say a high-runoff period when 7 you might get more of the carbon into the system, and 8 use an alternative source? It could be a well. Could 9 be just a better surface-water supply that's in the 10 area, the next thing that people tend to look at. 11 And then the third thing is they look at 12 carbon treatments. Why? These tend to be fairly 13 smaller systems. They're pretty much going to stick 14 with the chlorine-base disinfection. 15 It's not absolutely true, but by and 16 large it is what tends to occur. It's easier for them 17 to operate as opposed to going to any kind of 18 complicated UV-related system, which then doesn't leave 19 a residual within your collection line, which then 20 raises a concern to some people also. 21 So the bottom line is things are 22 changing and they're changing for the precise systems, 23 and there's only 3 out of the 44 have historically had 24 atrazine issues, whereas 22 out of the 44 have 25 trihalomethane issues.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 247

1 So the site-specific factors that one 2 would look at to influencing potable water-quality 3 supply in what's in the raw water and what's in the 4 finish water. These are the same factors that you 5 would have to evaluate to determine what is the most 6 cost-effective way to address the overall problem you 7 have in your system. 8 You don't say, "Oh, I just have an 9 atrazine problem; I'll put on my blinders and ignore 10 the rest of what's going on." You look at your overall 11 system and decide a solution. That's how you come up 12 with a cost-effective approach. 13 Well, some of the prior speakers, you 14 know have addressed a few of these issues; but they 15 deserve a little bit of re-emphasis. Surface-water 16 source, first and foremost, is the thing that causes 17 the quality of your raw water to be what it is, and 18 then that affects your finish water to a degree, to the 19 degree that you have no treatment in place. 20 The size of the drainage area, the 21 supply type, I think Dr. Hendley addressed the issue of 22 if you have a reservoir that has a considerable 23 detention time in it, you're not going to get as much 24 of a peak at all on any kind of atrazine exposure, 25 simply because you have a large water body that theFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 248

1 peak runoff, if it's occurring, has been dampened into 2 a larger system. If you have a riverine system, and 3 particularly a smaller one, more variable; also more 4 variable on carbon input, not a shock. 5 And then alternative source options. In 6 terms of water-treatment facilities, the type of 7 disinfection is going to drive things, the nature of 8 the supply, and again whether or not you're using 9 activated carbon. 10 And even if you're not using it right 11 now, I can assure you that most of these systems, if 12 they stay in place, will likely be having activated 13 carbon as their option of choice in the future in order 14 to address the group of chlorines that are coming down 15 the road. 16 So this is our just basic concern in 17 what I consider to be a significant policy shift in 18 what I'll say is just a focus on raw water without 19 looking at the overall cost-effective activities that 20 are going on in these watersheds of concern; that this 21 focus fails to consider the differences in the water 22 supplies and what their water-supply management options 23 are, because they will in fact exercise these 24 management options to address these other problems. 25 Regardless of whether atrazine even exists, it's goingFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 249

1 to happen. 2 The parameters, numerous other 3 parameters may be exceeded in the raw-water supply, 4 which makes you have to look at multiple integration of 5 all of these issues when you are coming up with your 6 cost-effective option. 7 I am concerned that we are switching to 8 a worst-case supply focus here, and worst-case supply 9 focus on a single parameter, when in fact these systems 10 have to deal with multiple parameters. And going to 11 the worst-case points farther, I mean, we're looking at 12 3 out of 44 systems to drive an entire approach? 13 I wouldn't think -- and those are 3 out 14 of 44 in high-exposure areas. It just seems a little 15 bit of overkill to me, and without integrating the 16 other things that need to be considered. 17 With regard to water-supply treatment 18 issues, you always look at the site-specific factors to 19 figure out the cost-effective treatment decisions. And 20 actually, I shouldn't limit it to water supply. EPA's 21 TMDL Program, Total Maximum Daily Load -- I'm sure all 22 of you have heard more than you would like to hear 23 about that program over your careers -- that analysis 24 is all site-specific. 25 Simple, you would look at the case-by-FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 250

1 case situations that are being encountered and decide 2 what is the particular solution, if it needs to be 3 implemented, to regulate the pollutants. You don't 4 apply one TMDL to all sources, it's just not done; it's 5 not the way the analysis goes forward. 6 So I think there is a nationwide impact 7 of shifting the regulatory focus from finish to raw 8 water. That's a major issue, it's a major policy 9 shift, and I would say that should be considered 10 carefully and I haven't really seen that it's gotten 11 the level of discussion maybe it ought to have. 12 And I guess I just want to end with the 13 last point, which is really maybe the first point. 14 Failure to integrate major changing Safe Drinking Water 15 Act mandates is a major oversight and where I see the 16 analyses are going. 17 I mean, really, if the treatment 18 technologies or other alternatives are going to come 19 into place regardless of what we are doing here today 20 with regard to this unit health exposure issue, we 21 really ought to know about that and integrate it into 22 our overall thinking before we decide that simply, for 23 example, more sampling is the solution to the problem, 24 when the solution to the problem, if you will, is 25 running off in a totally different direction.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 251

1 Thank you very much, and I appreciate 2 your attention. 3 DR. STEVEN HEERINGA: Thank you very 4 much, Mr. Hall. 5 Mr. White. 6 MR. JERE WHITE: I'd next like to 7 introduce my counterpart from Missouri, Gary Marshall. 8 Gary is not a scientist, but I believe he is going to 9 name his next hunting dog Data. 10 MR. GARY MARSHALL: That's probably 11 true, because I am one of the people that did receive a 12 subpoena last week. Even though technically I was in 13 Costa Rica, my office received the subpoena. 14 But my name is Gary Marshall, and I am 15 the Chief Executive Officer for the Missouri Corn 16 Growers Association. Mr. Chairman, good to see you and 17 members of the Panel. This is an ongoing process for 18 me, as well as for a number of you. 19 I've been involved in the special review 20 since 1996 and in the atrazine issue related to 21 Missouri since 1994 and prior to that, and in fact I 22 may have more experience in this room than probably 23 anyone else in actually applying the product afield. 24 So I in a previous life had a business 25 where we applied literally thousands of acres over aFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 252

1 15-year period with herbicides like atrazine with 2 fertilizer, and so we have a lot of practical 3 experience of using the product. And as Jere says, I'm 4 not a scientist; but I feel like I know more about a 5 lot of the reproductive Mode of Actions of rats and 6 mice than I ever cared to know. 7 But I appreciate the opportunity to 8 visit with you just a few minutes and talk a little bit 9 about what we do and our concerns. And I guess the 10 first thing I should say is representing the 15,000 11 corn growers that I do in Missouri, I think I can speak 12 for them in that we have what I consider to be very 13 robust populations today of fish, of frogs, of birds, 14 of deer, turkeys. 15 You know, 50 years of experience using 16 the product atrazine -- and I realize the science that 17 we're talking about here and the minutiae that we're 18 able to deal with today -- but I deal in the real 19 world, 50 years' worth of applying products. 20 We started at 4 pounds per acre 21 whenever I started back in the '70s to a pound, a 22 pound-and-a-half or less than that today, huge amounts 23 of atrazine in the environment out there that have been 24 used, and no problems at all that we're seeing 25 associated with any of the animals or any of the plantsFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 253

1 or the ecosystems that we deal with. 2 Again, the reason I'm here is because 3 this herbicide allows our farmers to control weeds in 4 their fields, the pests. These weeds not only compete 5 for moisture, but they also harbor insects and other 6 diseases; we don't want them in the fields. Atrazine 7 is a cost-effective measure. 8 Perhaps the best illustration of that 9 that I can give you is to a producer in Missouri to 10 switch to an alternative product, first of all, you 11 have less efficiency; it doesn't work as well. 12 Secondly, you have increased costs. You combine those, 13 it's over $30 an acre. 14 We produce over 3 million acres of corn 15 in Missouri. That's a $100 million cost to our growers 16 if we would have to switch products: those 15,000 17 growers, a $100 million increase in costs. If you 18 change that, take it all the way across the United 19 States, on 90 million acres of corn you're talking 20 about a $2.5 billion hit to growers. And who 21 ultimately pays the price for a higher cost that 22 growers have? The consumers do. 23 So although this product doesn't go 24 directly to human food, it does go to animal feed, it's 25 exported all over the world, and in fact we use a lotFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 254

1 of it today to help produce a gasoline-type product, 2 ethanol, that we use in our cars. So we have a lot -- 3 I think the growers do -- of reason to be here. 4 Another thing that we've seen in the 5 last few years, glyphosate technology. If you're not 6 familiar with it, it's a new technology that has 7 allowed us to go away from some of the herbicides we 8 used in the past to help control weeds; but it's got 9 one problem, and that is it's been used so much so 10 extensively that we're starting to see some weed11 resistant species that are out there. 12 So for us, we need a product like 13 atrazine to be able to deal with these problem weeds. 14 It started for us in Southeast Missouri, it's spread 15 across the state three or four hundred miles to 16 Northwest Missouri. We need a product like atrazine to 17 be able to complement products like glyphosate. 18 And again, if you think that's an issue 19 for us, it is. Nationwide that's a billion-dollar 20 cost, $10 to $20 an acre to control those resistant 21 weeds. So it's a huge cost, and I know that one of the 22 other speakers is going to address that issue. 23 But as the science has evolved, so have 24 the growers in managing the atrazine that they have. 25 In the 1990s when I first got started in Missouri, weFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 255

1 had numerous areas out of compliance for atrazine. In 2 fact, we had five major drinking-water reservoirs and 3 several streams out of compliance. 4 So we worked and we specifically put 5 together a group, and I think maybe we are one of only 6 two commodity associations that have a group like this 7 that works exclusively on water-quality issues. 8 We have ten people on staff, and that by 9 itself is a huge staff for commodity groups: ten 10 people doing nothing but working on water-quality 11 issues. So we put together projects with EPA funding, 12 with Department of Natural Resources in Missouri 13 funding, with USDA dollars. 14 We involve the University of Missouri, 15 and we put a number of grower dollars together to put 16 together ten years' worth of studies and of science. 17 Again, I'm not dealing in a laboratory 18 and looking at the probability of something happening 19 or using a model. We're looking at what actually 20 happens out in the streams, and I can tell you as a 21 result of those ten years' worth of studies, we were 22 able to work with the growers to help implement best 23 management practices on those fields, which resulted in 24 the delisting of every major water body, including the 25 Missouri and Mississippi Rivers in Missouri, that wereFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 256

1 out of compliance for atrazine. They're all delisted 2 today. 3 So we've been able to work with the 4 farmers, utilize the information, the best science, the 5 technology that we have, to be able to incorporate 6 things like conservation tillage, minimum tillage, no 7 till to help keep the products on the fields where 8 they're supposed to be and not get into the water 9 systems. 10 We utilized over 50 samplers, we had 11 dozens of fields, literally hundreds of producers 12 participated, and we've shown this data to thousands of 13 people, including one of the past EPA Administrators. 14 So we used and we not only looked at 15 various types of techniques; but we looked at rate 16 reductions, we looked at application of timing of 17 atrazine, tillage practices, split applications, a 18 number of different things. All of these helped us to 19 keep the product where it's supposed to be, which is on 20 the fields. 21 A part of conservation tillage allows us 22 to use things like buffer strips, integrated pest 23 management, better best management practices to be able 24 to keep those products there. Today, over 44 million 25 acres in the United States utilize conventionalFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 257

1 tillage. The reason they're able to do that, one of 2 the main reasons is the ability to use a product like 3 atrazine. It really works. 4 One of the results of using conservation 5 tillage and these best management practices, we've 6 reduced soil erosion. It was a huge problem in a state 7 like Missouri; we've reduced it by 90%. It's made a 8 significant difference. 9 A lot of the small streams that we deal 10 with in a state like Missouri -- and most of the corn 11 is grown along streams in our state -- but a lot of the 12 small streams have a lot more problem with turbidity, 13 with cloudy water, than they ever do with a product 14 like atrazine. 15 By using conventional tillage -- or by 16 conservation tillage, rather, we've been able to use 17 products like atrazine again to help keep those 18 products where they're supposed to be, on the fields. 19 They don't get into the water systems. We reduced that 20 turbidity and the problems in those streams. 21 For farmers, we also help reduce the 22 amount of fuel that we use, because we don't have to go 23 over the fields as often. So we reduce compaction on 24 the fields, the tilth of the soil is much better, 25 higher results there plus less expenses because we'reFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 258

1 not going over the fields quite as often as we did 2 before. 3 And besides that, we're providing great 4 habitat for wildlife; again, the fish and the wildlife 5 is excellent. 6 So I guess in conclusion with my short 7 presentation, I just want it noted that atrazine works 8 very, very well for growers across the United States. 9 It saves producers money, saves consumers dollars, and 10 it allows us to utilize conservation tillage and it 11 advances modern farming practices, and it helps improve 12 the environment. 13 Thank you. 14 DR. STEVEN HEERINGA: Thank you, Mr. 15 Marshall. 16 Mr. White. 17 MR. JERE WHITE: Lastly, we'd like to 18 introduce Dr. David Bridges. I need to make an 19 observation. I first met David probably a dozen years 20 ago at an SAP. He was a wheat scientist, and I was 21 doing exactly what I'm doing now. 22 He's now President of the university he 23 originally graduated from, and here I am in the same 24 role. So one of us did better with our career track 25 than the other, though without embellishing.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 259

1 DR. DAVID BRIDGES: Thank you, Jere. 2 Thank you for your time this afternoon, 3 and I will be judicious in my use of it; I know it's 4 been a long day. 5 My name is David Bridges. I'm President 6 of Abraham Baldwin Agricultural College and a Professor 7 in its School of Ag and Natural Resources and its 8 School of Science and Mathematics. 9 Much of my professional career was and 10 has been devoted to quantifying the impact of 11 pesticides, their use and the benefits derived from 12 such. Over the past 25 years I've worked with EPA, 13 USDA, Food and Drug Administration and many others to 14 try to accurately assess and value the use of 15 pesticides in the U.S. economy. 16 I don't have any slides (laughing). 17 In the early 1990s, a team of colleagues 18 and I began the process of conducting what was the most 19 comprehensive analysis of the use and benefits of the 20 triazine herbicides that had been conducted at that 21 time. Over the past six months, the team has 22 reassembled; unfortunately, many have moved on to other 23 things. But I chose to sign up for the fun again, and 24 we have almost completed another analysis of the use 25 and benefits of triazine herbicides in the U.S. farmFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 260

1 economy. 2 I am fully aware that your charge, your 3 primary charge and responsibility, is not to sit here 4 and listen to me talk about benefits. I understand 5 that. However, I suggest and respectfully suggest to 6 you that your decisions cannot and should not be made 7 in a vacuum. 8 There are many other important issues 9 that impinge on the process. While you have been 10 asked to set the bar, you will consider the data that 11 is presented to you and the weight of the evidence and 12 the value of the science that has been submitted to 13 you. There are many other things that I think can 14 serve to play a role in the relative placement of that 15 bar: how low, how high. 16 Many of us at this table are scientists 17 or engineers or we're both, and by nature we seek truth 18 and we seek knowledge. But we hopefully also 19 understand that absolute certainty is very elusive, 20 very elusive. And what we may think is certainty today 21 may turn out to be something quite different tomorrow. 22 But there are a few matters in the 23 matter before us that are really pretty certain. After 24 50 years of safe use, the benefits of the triazine 25 herbicides, and particularly atrazine, is prettyFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 261

1 certain. The benefits are certain. Most of us believe 2 the safety is certain. 3 Your task really becomes a very 4 difficult one. It is a task where you are asked to 5 trade certainty for multiple layers of certainty. And 6 incomplete science, should you make unnecessary 7 regulation, trade somewhat uncertain science for maybe 8 more uncertain science. 9 I want to share with you just a few 10 thoughts about use, reliance and potential impacts. 11 All of us know that atrazine is the most commonly used 12 herbicide in American history. 13 For more than 50 years since atrazine's 14 initial registration, atrazine has been used by more 15 American farmers than any other herbicide. It is 16 currently estimated that a half a million farmers a 17 year use triazine herbicides. 18 More than half of the U.S. corn crop is 19 treated annually, about 90% of the sugarcane crop and 20 three-fourths of the grain sorghum crop. Atrazine and 21 simazine have been used commonly on more than 30 crops 22 for more than 50 years. There is an element of 23 certainty that comes with time. 24 I'd also suggest that as you undertake 25 this very difficult task in a way that competingFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 262

1 interests and the competing points about how strong the 2 science is or how unwavering it may be where others 3 tell you it is not so strong, it is doubtful, I'll 4 suggest to you that you should not underestimate the 5 recoil and the profound broad impact that your decision 6 will have on American agriculture and, indeed, on the 7 U.S. economy. 8 And most importantly, it will have a 9 profound impact on rural America. Most of us here 10 today come from rural America and are deeply concerned 11 about the economies and what is going on in the 12 heartland of America. 13 Impacts will be felt, and we can 14 categorize those who will be impacted into three 15 principle groups. Growers or farmers, I fully realize 16 that less than 2% of America's population spends its 17 time on the farm; but we all benefit from the 2% who 18 work on our behalf. 19 Consumers will be impacted; and finally, 20 the greater public at large. Your charge is important, 21 but your charge is inclusive. Your charge is to 22 protect all. 23 For growers, should atrazine no longer 24 be available, the following effects are almost certain. 25 Farmers will lose the herbicide that has been theFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 263

1 mainstay of corn weed control for more than 50 years. 2 The combination of increased weed-control costs and 3 yield losses will seriously challenge profitability in 4 American farming. 5 To look at gross number, folks, the 6 margins in farming are small. The margins are small. 7 The increased costs and the lost yields will take a 8 large percentage of that profitability away. 9 Farmers will lose, at a time when they 10 can ill afford to do so, their most important weapon to 11 fight resistant weeds. Farmers will, at least in the 12 short term, become more reliant on glyphosate, a 13 product that is already seriously challenged with 14 respect to its future efficacy. 15 Farmers will face greater prevalence of, 16 like I say, resistant weeds, and they will do so 17 quickly. They will find it more difficult and more 18 costly to control those weeds in not corn and sorghum 19 and sugarcane but in the myriad of crops that they 20 rotate, too. 21 And I reiterate, should the product go 22 away, one thing is certain: farmers will use 23 herbicides. They will use whatever is available to 24 them, and in many cases those products will be less 25 effective, they will be more expensive, they willFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 264

1 almost all certainly come without the benefit of 50 2 years of experience. 3 And they will almost all certainly come 4 with much less study, much less understanding and much 5 less certainty about the things that you've been asked 6 to consider the last two days. 7 Consumers, you, I and everyone else in 8 the room, who consume corn, sorghum, sugarcane, pork, 9 poultry, beef, fish, dairy products, your favorite 10 coffee at Starbucks across the street, will face 11 without a doubt a rise in food costs; and finally, the 12 public at large. 13 Your decision is not a carbon-neutral 14 decision. The loss of atrazine to the American farmer 15 will result in increased on-farm petroleum use and 16 therefore result in a larger carbon footprint for 17 American agriculture. 18 The loss of atrazine will reverse a 30- 19 year continuous trend in the adoption of conservation 20 farming practices. America's farmers are, by 21 definition and by necessity, America's penultimate 22 environmentalists and conservationists; they have to 23 be. So if atrazine goes away, conservation tillage 24 will decline. That means plowing will increase. 25 Soil erosion will increase, which meansFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 265

1 siltation of streams will increase, which means 2 sedimentation of streams will increase. Nutrient 3 loading to our surface waters will increase. The 4 biological diversity of farms will decline when tillage 5 increases. And a conservative estimate suggests that 6 as many as 48,000 jobs will be lost just in corn 7 production. 8 In closing, I know you will make your 9 decisions based on science. Many of you here at this 10 table have been here before. You will make your 11 decisions based on sound and convincing science. 12 Obviously, uncertainty -- and there is clean evidence 13 in this world -- leads to caution and precaution. 14 But make sure that the amount of caution and precaution 15 you take is appropriately weighed relative to the risk 16 associated with inappropriate regulation. 17 Make no mistake: caution on one 18 forefront represents risk on others. Facing limited 19 and mechanistically understood risk is better than 20 facing largely but totally unknown risk. 21 These herbicides are essential for 22 agricultural production, and massive change will occur 23 if the farm community faces unrealistic regulation. 24 Make sure you understand that is my caution and my 25 request of you.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 266

1 I won't repeat the following points 2 about conservation tillage; I believe I have made them. 3 But my sense is our estimates are -- and we have data 4 to show that it happened over the last few years -- is 5 that more herbicides will be used. You take atrazine 6 away, you take the other triazines away, more will be 7 used. 8 Can you sit here and say with confidence 9 that the alternatives are safer? How many alternatives 10 have a 50-year track record of use? How many 11 pesticides, how many other herbicides that farmers 12 might choose to use, have the record of study and the 13 level of understanding about mechanism and effect with 14 that of atrazine? 15 When faced with weak, little or no 16 evidence to condemn a product, or when uncertainty 17 abounds on one front, always consider, always consider 18 that some degree of certainty does come with more than 19 50 years of use. 20 I would say to you that the stewardship 21 on this product exceeds the level of stewardship on any 22 other pesticide registered in America. The Registrant 23 has been its steward; the farmers have been its 24 steward, as evidenced by adoption of best management 25 practice, reduction in rates and a variety of thingsFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 267

1 that have sustained its use in the farm business for 2 many years. 3 Consider the weight of the other 4 evidence and the potential impact of unintended 5 consequences that could result from overly cautious and 6 errant decisions. 7 If I were in Georgia today, I would be 8 having a meeting or teaching a class. And I would say 9 to you this is far more than an academic exercise. It 10 is far more. The impact of your decision will be far11 reaching. 12 I think it is safe to say, and I will 13 stand behind this statement, that losing the triazine 14 herbicides will result in an unprecedented disruption 15 of the world's most productive agricultural system: 16 the production of corn in the United States of America. 17 Thank you for your valuable time, and I 18 wish you luck in your process. 19 DR. STEVEN HEERINGA: Thank you very 20 much, Dr. Bridges, the White and the Triazine Network 21 group. 22 We're going to move on to our next 23 public commenter. 24 And Mr. Snyder, we skipped over you 25 previously. Rod Snyder, are you here at this pointFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 268

1 from National Corn Growers Association? 2 Coming forward. So our next public 3 comment will be Rod Snyder, and comments are being 4 circulated to the Panel and will be available in the 5 Docket, too. 6 MR. ROD SNYDER: I will be fairly brief; 7 my good friends from Missouri and Kansas covered a lot 8 of ground here in the last few minutes. 9 My name is Rod Snyder, Director of 10 Policy for the National Corn Growers Association, and I 11 do appreciate the opportunity to testify before the SAP 12 today. 13 I am providing comments on behalf of 14 NCGA, which represents 36,000 members in 48 states and 15 more than 300,000 corn farmers that contribute to state 16 checkout programs across the country. These 17 opportunities to see about atrazine are important to 18 America's corn growers. 19 We are anxious to be heard, because so 20 much is at stake for our farmers and the rural 21 communities that depend upon the farm economy. 22 According to Don Coursey, an economist 23 at the University of Chicago, a ban on atrazine would 24 cost as many as 48,000 jobs, according to some new 25 research that came out this summer.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 269

1 Dr. Coursey also estimates atrazine's 2 annual production value to corn alone to be as high as 3 5 billion, not to mention losses for the growers of 4 sorghum and sugarcane. 5 Of course, no economic priority should 6 come before human health, we do all agree on that. 7 That is why EPA has relied on more than 6,000 studies 8 and the considered judgments of respected regulatory 9 agencies around the world to affirm the safety of 10 atrazine. 11 Yet, we find ourselves in the midst of 12 this very unusual, unplanned re-review of atrazine that 13 deviates considerably from EPA's longstanding 14 regulatory process. EPA and the Scientific Advisory 15 Panel have already repudiated the very studies EPA 16 relied upon to justify this re-review of atrazine, 17 noting that "The overall quality was relatively poor, 18 thus limiting their applicability". 19 Nonetheless, we find ourselves in the 20 fourth SAP in 12 months. On August 24th, just three 21 weeks before this SAP convened, EPA released a white 22 paper that was almost 700 pages long that included 23 summaries of more than 100 studies. 24 This white paper is complex and crosses 25 many disciplines. It was not until August 27th thatFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 270

1 EPA allowed stakeholders to know the exact questions 2 this Panel is being asked to consider. These questions 3 require a Panelist to make critiques of 17 preliminary 4 conclusions in questions that cross multiple 5 disciplines. 6 It seems imprudent to ask this Panel to 7 make rush decisions about science. For our part, it is 8 impossible for farmers and corn growers who are 9 currently in harvest to review one of the longest and 10 most complicated SAP white papers ever released. 11 We expect these scientific deliberations 12 to be both patent and transparent in a manner that 13 invites criticism. Unfortunately, this process has 14 been rushed, and we are concerned about the publication 15 of mountains of data and findings without adequate time 16 for the SAP, farmers or the general public to 17 intelligently analyze or respond. 18 So much is at stake here beyond just 19 atrazine, actually. We need EPA to maintain a fair and 20 balanced process for pesticide review so that all 21 stakeholders can have a high degree of confidence in 22 the resulting decisions. We hope you will consider the 23 precedent-setting nature of these decisions and the 24 American agricultural system that will be deeply 25 impacted.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 271

1 I thank you for your time. 2 DR. STEVEN HEERINGA: Thank you, Mr. 3 Snyder, and I will just add a comment that the Panel 4 sees the questions at the same time the public does, be 5 it the Docket. It's just a 6 MR. ROD SNYDER: It's good to know that. 7 I thought that. 8 DR. STEVEN HEERINGA: That's probably 9 neither here nor there for you, but it's 10 MR. ROD SNYDER: Thank you. 11 DR. STEVEN HEERINGA: Okay, thank you 12 very much, Mr. Snyder. 13 At this point in time, our next public 14 commenter is Mr. Scott Slaughter, who represents the 15 Center for Regulatory Effectiveness. 16 Scott? 17 MR. SCOTT SLAUGHTER: I'm Scott 18 Slaughter, and I am commenting today on behalf of the 19 Center for Regulatory Effectiveness -- and I apologize 20 for my cold and my hoarseness. 21 Sure, we got a subpoena, too; but we're 22 going to talk anyway. 23 Our comments address three points: 24 first, there are quality standards that govern EPA's 25 use of scientific studies and data; second, EPA shouldFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 272

1 not use its draft 2000 BMD Guidance Document, because 2 the document says don't use it; third, EPA should not 3 use the 2007 and 2010 Fenton male rat studies, because 4 so many of the controls have unexplained prostate 5 inflammation. 6 With regard to the first issue, EPA 7 cannot use scientific data and studies unless they meet 8 certain statutorily required quality standards. Many 9 of these standards are required by something called the 10 Information Quality Act Guidelines. 11 These IQA Guidelines require that 12 studies and data used by EPA and other Federal Agencies 13 generally be accurate, reliable, reproducible and 14 transparent. 15 The U.S. Office of Management and Budget 16 is required under statute to ensure that EPA and other 17 Federal Agencies publish and implement these IQA 18 Guidelines. OMB has asked EPA to incorporate its IQA 19 Guideline standards into the charges that EPA gives to 20 expert peer-review panels like this one. 21 Let me read OMB's exact language to EPA. 22 This is in Appendix A to our written comments on -- 23 yeah, go to page 3 of my written comments, series 24 written comments. I'm sorry, no, it's page 14, 25 Appendix 1, attached to my written comments.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 273

1 OMB told EPA, not for this SAP but in 2 the context of charges to another peer-review panel: 3 "Since the development of Agency Information Quality 4 (IQ) Guidelines required by statute, many Agencies have 5 been using charge language that tracks with the 6 standards of their own IQ Guidelines. 7 For example, such language often focuses 8 on whether or not the information in question is 9 accurate, clear, complete, transparently and 10 objectively described and scientifically justified." 11 We believe it may be useful for EPA to 12 follow a similar approach and incorporate some of the 13 language from your IQ Guidelines into the formulation 14 of the Charge Questions. We believe that EPA has not 15 done that for this SAP, so in our comments we have 16 tried to incorporate the IQA Quality Standards into the 17 review that you're doing right here. 18 Let me give you an example of how the 19 IQA Guidelines work in a context, in fact in a prior 20 SAP on atrazine. A few years ago, CRE and others 21 requested EPA not to use Dr. Hayes' atrazine studies 22 because they were not reproducible, in violation of the 23 IQA Guidelines. EPA and two SAPs eventually agreed 24 that the Hayes studies were not reproducible, and EPA 25 is not using them, is properly not using them toFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 274

1 regulate atrazine. 2 We move on to our second issue. EPA's 3 Draft 2000 Benchmark Dosing Guidance Document is 4 another example of something that does not meet IQA 5 Guidelines. Therefore, EPA should not use it to 6 regulate atrazine. 7 However, EPA's cites the 2000 draft BMD 8 guidance Document, page 73 of its Issue Paper. This 9 draft document says on its front page, its cover page - 10 - and that's on page 3 of my written comments -- and I 11 quote; it says on the front: "Draft EPA. Do not site 12 or quote." "This document is a preliminary draft. 13 It has not been formally released by the 14 U.S. Environmental Protection Agency and should not at 15 this stage be construed to represent Agency policy. It 16 is being circulated for comment on its technical 17 accuracy and policy implications." 18 That, the document, speaks for itself 19 and should not be used in this context for any 20 regulatory purpose until EPA is willing to take the 21 caveats off the document and until EPA is willing to 22 designate it to be a final document and until EPA 23 itself is certain that the document is technically 24 accurate. 25 Third and finally, Dr. Fenton isFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 275

1 coauthor of a 2007 Rayner study on rat prostates. The 2 Rayner article had significant prostate contamination 3 with regard to control prostate inflammation. In fact, 4 80% of the controls in some groups had prostate 5 inflammation. 6 That inflammation was not caused by 7 atrazine. The 2010 Fenton article that she discussed 8 today had control prostate inflammation; half the 9 controls had it. 10 Let me read to you what Dr. Fenton and 11 the rest of her authors said in 2007 about the control 12 prostate contamination in the controls and the general 13 summary they had in the 2007 study on the prostate14 inflammation issue. 15 This is recorded on page 5 of my written 16 comments at the bottom, and I quote: "The background 17 incidence of inflammation in the ventral prostate was 18 fairly high in that eight of 10 control animals 19 presented evidence of inflammation at PND120." 20 Eighty-percent is fairly high. 21 "Neutrophils were more prominent in the ventral 22 prostate in all dose groups, and were associated with 23 the higher overall incidence of inflammation in the 24 ventral prostate. 25 The incidence of inflammation in theFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 276

1 ventral prostate was not treatment related and 2 presented a wider tissue distribution than the lateral 3 prostates. The severity of inflammation in the ventral 4 prostate was also not affected by atrazine exposure." 5 I'm still quoting: "At PND220, no 6 significant increases in prostate inflammation were 7 detected relative to controls, however, the incidence, 8 distribution, and severity of inflammation in the 9 ventral prostate were decreased compared to PND120. 10 The lateral prostates were not different from control. 11 There was no increase in incidence or severity of 12 prostate inflammation over time following atrazine 13 exposure." 14 I really think that the control 15 contamination and the control inflammation needs to be 16 explained before anyone uses this document for any 17 purposes or those studies for any purposes with regards 18 to regulation of atrazine. 19 That was it, and I will be happy to -- 20 well, I guess I want to ask you a question now; but I 21 will later. 22 Thank you very much. 23 DR. STEVEN HEERINGA: Thank you very 24 much, Mr. Slaughter; and the Panel, in the Docket there 25 is a multipage document with appendices that--FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 277

1 MR. SLAUGHTER: Yep. 2 DR. STEVEN HEERINGA: --was distributed 3 on behalf of Mr. Slaughter and the Center for 4 Regulatory Effectiveness. 5 Okay, we have two more scheduled public 6 commenters. In anticipation of the end of the 7 afternoon, if there are any other members of the public 8 who wish to make a public comment before this meeting, 9 I would encourage you very shortly to see the 10 Designated Federal Official, Joe Bailey, or the 11 Executive Secretary of the SAP, Ms. Laura Bailey. 12 At this point in time, I would like to 13 invite up Tyler Wegmeyer, who is Director of 14 Congressional Relations for the American Farm Bureau 15 Federation. 16 MR. TYLER WEGMEYER: Good afternoon. My 17 name is Tyler Wegmeyer, and I am the Director of 18 Congressional Relations for the American Farm Bureau 19 Federation. I am also a fourth-generation farmer 20 growing mostly specialty crops in western Loudon 21 County, Virginia. 22 The American Farm Bureau Federation is 23 the country's largest general farm organization. Farm 24 Bureau members grow, produce and raise the food, fiber 25 and energy sources that feed, clothe and fuel the U.S.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 278

1 and the world. Our farms and ranches are found in all 2 50 states as well as Puerto Rico, and we represent 3 producers of every size and scale of operation. 4 American Farm Bureau Federation welcomes 5 this opportunity to speak up on behalf of the benefits 6 of atrazine and what it means to American farmers. 7 Having access to important crop-protection products is 8 vital to the success of providing safe and abundant 9 food supply. I appreciate this opportunity to be able 10 to express our views before this Scientific Advisory 11 Panel. 12 At this time of continuing high 13 unemployment and national recession, when America is 14 running enormous trade deficits and our competitiveness 15 in manufacturing is being challenged, the American 16 farmer is providing a much-needed bright spot in our 17 economy. One reason for this bright spot, why American 18 agriculture remains so amazingly productive and 19 efficient, is the wise application of technology by 20 American farmers to agriculture. 21 You would think that at a time like 22 this, Washington's overriding interest would be to do 23 anything and everything to bolster the U.S. farm 24 economy. And yet, we keep finding ourselves fighting 25 off ill-considered proposals, such as the one in theFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 279

1 purview of this Panel, that have the potential of 2 making farming more difficult, less efficient and more 3 expensive. 4 In our view, no move has been more 5 unhelpful than what appears to be a campaign against 6 the wise and appropriate use of agriculture technology. 7 The redundant re-evaluation against atrazine is a case 8 in point. 9 The campaign against this crop input 10 appears predicated on a set of claims that have been 11 examined and re-examined, and in each instance the 12 Agency has found in favor of continued use of atrazine. 13 We all remember the hysteria that was generated against 14 Alar in the 1980s and the damage it caused. The 15 campaign against atrazine is potentially more harmful 16 and with more widespread impact on more crops than Alar 17 ever was. 18 It is easy to see why this is so. 19 Atrazine is essential to corn growers, as well as to 20 sorghum and sugar growers. And corn is an essential 21 staple of animal feeds, impacting meat prices, as well 22 as a multitude of secondary food products. We look at 23 what is going on here, and we worry for America's 24 farmers in the rural communities that depend on them. 25 We are concerned when a wholly redundantFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 280

1 regulatory re-review is launched against atrazine on 2 such an accelerated time scale. The stream of data 3 being poured out for this SAP is extremely difficult to 4 manage in the artificially compressed schedules you 5 have been allotted to carry out your meetings. 6 The members of this SAP are also being 7 asked to evaluate this new data while turning away from 8 the more than 6,000 studies that were considered by EPA 9 when it completed a dozen years' worth of work in 10 approving atrazine as safe to use, a process completed 11 just a few years ago in 2006. 12 We have to wonder why this Panel is 13 being asked to hurry up and make scientific judgments 14 under a whole new scientific terminology called points 15 of departure. 16 We also wonder why no one seems to be 17 taking stock of atrazine's documented benefits to the 18 environment. One of these clearly is in the increasing 19 amount of acres using no-till practices, a practice 20 that stores carbon in the soil and for which atrazine 21 is an important component. 22 Our Farm Bureau members in all 50 states 23 look at the EPA's recent actions with dismay and 24 frustration. Farmers are deeply concerned that this 25 process will result in unjustified restrictions orFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 281

1 elimination of an important crop-protection tool. 2 Again, we appreciate this opportunity to 3 submit our comments. Thank you. 4 DR. STEVEN HEERINGA: Thank you very 5 much, Mr. Wegmeyer. Sorry, I had your name wrong 6 before; that's the way I had it on my sheet. We'll 7 correct that in the final. 8 Finally, in terms of scheduled 9 presenters, I would like to invite up Rebeckah Freeman 10 Adcock, who is Director of Government Affairs for 11 CropLife America. 12 Turn on the mic. 13 Welcome. 14 MS. REBECKAH ADCOCK: Thank you to the 15 Panel and to EPA for the opportunity to comment. My 16 name is Rebeckah Adcock, here today representing 17 CropLife America. CropLife America's member companies 18 proudly manufacture, register and distribute crop19 protection products to American agriculture. Our 20 members work with farmers and ranchers every day to 21 ensure that crop-protection tools are registered 22 properly and used correctly. 23 America's abundant, affordable food 24 supply depends on the availability of safe, effective 25 crop-protection products. Moreover, our collectiveFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 282

1 ability to feed the world centers on the efficiency and 2 ingenuity of modern agricultural technologies like the 3 products used to protect crops and animals from pests. 4 It's critically important to remind 5 ourselves of these fundamental points, because in 6 recent months we've seen serious deviations from the 7 regular order, transparency and scientific integrity of 8 EPA's risk-based pesticide review process. 9 From CropLife America's point of view, 10 the legality and scientific validity of the Pesticide 11 Program has been profoundly distorted by unsupported 12 science, sensationalized journalism and political 13 expediency. 14 Even so, in the interest of science and 15 process, CropLife America would like to address one of 16 the EPA's charges to the SAP; specifically, the 17 question of whether the Agency should consider 18 monitoring end results for raw surface water when 19 assessing the potential human health effects associated 20 with exposure to pesticides in finished drinking water. 21 We believe the answer is no, it is not 22 appropriate to use pesticide levels in raw water for 23 this purpose. While monitoring data can be an 24 effective reality check for modeled estimates of 25 residue potential in surface and groundwater, pesticideFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 283

1 concentrations in raw water are not an effective 2 measure of the potential for risk to humans from 3 exposures to pesticides from consuming drinking water. 4 To that point, the U.S. Geological 5 Service also recognizes that finished water supplies 6 are the best measure of pesticide concentrations for 7 evaluating human exposures. 8 In a joint monitoring program conducted 9 by USGS and EPA investigating pesticide concentrations 10 in raw water and finished drinking water from surface 11 water sources, USGS concluded that "Finished water 12 samples provide the best practical measure of pesticide 13 concentrations that a supplied population is exposed to 14 in drinking water". 15 The Safe Drinking Water Act requires 16 monitoring of drinking water that is representative of 17 the water that the public actually consumes. For that 18 reason, the Act in its implementing regulations 19 expressly provide that monitoring for the health 20 effects of synthetic organics like atrazine should be 21 confined to finished water and that sampling should 22 occur within the community water systems that actually 23 serve consumers. 24 Safe Drinking Water Act regulations also 25 set out monitoring and sampling requirements intendedFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 284

1 to ensure that the best scientific methods are used to 2 collect and analyze the drinking-water data. Again, 3 the regulations dictate that sampled water should come 4 from water that consumers actually drink. 5 Raw water, again, while potentially 6 important to study for residue modeling and ecological 7 considerations, is not drinking water. And it is 8 neither consumed by nor provided to the public by 9 community water suppliers. 10 Monitoring of raw surface water is 11 employed only in limited circumstances under the Safe 12 Drinking Water Act. As a matter of fact, raw-water 13 monitoring occurs only when a community water supplier 14 seeks to be exempted from existing monitoring 15 requirements for a particular contaminant. 16 Specifically, where regular monitoring has over 17 successive periods consistently shown no detection of 18 the contaminant in the samples taken, a community water 19 system may conduct monitoring of the surface raw-water 20 sources as evidence that further monitoring for the 21 contaminant is not necessary. 22 In the case of atrazine, EPA has 23 undertaken a rigorous, transparent and comprehensive 24 human health risk analysis, including the adoption of 25 drinking water standards as required under the SafeFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 285

1 Drinking Water Act. 2 In adopting health-based standards for 3 drinking water, EPA is required to identify a Maximum 4 Contaminant Level Goal, or MCLG, and the law requires 5 that the MCLG must be set "at a level at which no known 6 or anticipated adverse affects on the health of persons 7 occurs" and "which allows for an adequate margin of 8 safety inputs". 9 Using the best available science, 10 supporting studies and data, EPA has concluded that an 11 annual average of 3 parts per billion of atrazine in 12 drinking water represents the appropriate MCLG. In 13 other words, that's the level at which no known or 14 anticipated adverse effects on human health will occur, 15 factoring in a large margin of safety. 16 EPA next sets an enforceable standard 17 for a permissible level of a contaminant that is set as 18 close to the MCLG as is feasible. This is called the 19 Maximum Contaminant Level, or MCL. 20 For atrazine, the enforceable MCL is set 21 at the same level as the MCLG, an annual average of 3 22 parts per billion. 23 Data-collection regulations provide that 24 monitoring of drinking water for atrazine may be 25 performed on finish water within community waterFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 286

1 systems, and to that end public water suppliers are 2 required to do quarterly monitoring for atrazine down 3 to its level of detection. 4 That detection level is, as most of you 5 know, several orders of magnitude below the actual MCL 6 or MCLG. In the event that the MCL for the contaminant 7 is exceeded in finished drinking water, additional 8 monitoring can be ordered and has in some cases been 9 ordered by EPA. 10 In summary, the Charge Questions before 11 the SAP with regard to atrazine monitoring are confined 12 to the issues of drinking water quality, which is 13 necessarily an examination of human health effects that 14 flow from the actual consumption of finished water that 15 is consumed by the public. 16 CropLife America believes that science 17 and the law dictate the SAP's assessment of these 18 issues and that this assessment should necessarily be 19 focused on finished drinking water and not raw water. 20 To date, the re-review of atrazine has 21 provided neither a sound new process nor any 22 substantive basis for revisiting or revising EPA's 23 monitoring protocols or drinking water standards for 24 atrazine. 25 We strongly urge the SAP to provideFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 287

1 recommendations to EPA based on the sound science that 2 is already the foundation of the Safe Drinking Water 3 Act, including the mandated atrazine monitoring of 4 finished water at sampling points within the known 5 distribution centers of community water suppliers. 6 Our comments should also be received as 7 more than just concerns about the specific charges 8 within this special review of atrazine. Much more is 9 it stake. CropLife America knows that the work of this 10 SAP may well determine whether the Pesticide Program 11 further descends into the scientific abyss, regulating 12 based on unsupported science, activism and politics, or 13 whether your recommendations guide EPA back to the 14 light of FIFRA's transparent, scientific-based review 15 and the rigorous process and standards established by 16 the Safe Water Drinking Act. 17 Thank you. 18 DR. STEVEN HEERINGA: Thank you very 19 much, Ms. Freeman Adcock. 20 Ms. Freeman Adcock, will you be 21 providing copies of your comments to the Docket? 22 MS. REBECKAH ADCOCK: It is my 23 understanding that our Science and Reg Team is going to 24 actually provide more extensive written comments based 25 on my brief comments.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 288

1 DR. STEVEN HEERINGA: Okay, sure. 2 MS. REBECKAH ADCOCK: And we'll make 3 sure that we get something to you by the close. 4 DR. STEVEN HEERINGA: As long as they're 5 in before the close of the meeting 6 MS. REBECKAH ADCOCK: Absolutely. 7 DR. STEVEN HEERINGA: we'll be fine 8 with it. 9 MS. REBECKAH ADCOCK: Thank you. 10 DR. STEVEN HEERINGA: Thank you very 11 much; again just a technicality, things arrive after 12 the close of the meeting. 13 Okay. At this point in time, we have 14 completed public comment from all of the scheduled 15 public commenters, and I want to thank everyone for 16 being so focused in their presentations. 17 We made the decision, I made the 18 decision to defer Panel questions to the presenters. 19 What I'd like to do at this point, we have at least 30 20 to 45 minutes that we can use to address comments or 21 questions of clarification to any of the public 22 commenters that we heard this afternoon; some of them 23 may have had to leave already. I think unfortunately 24 Dr. Handa may have had to leave. 25 But I would like to do it in an order.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 289

1 I am not going to close the period for public comments 2 this afternoon; I will leave it open until tomorrow 3 morning, because I know there's a lot to digest. 4 But if you have something that is 5 specifically related, a question or clarification, 6 something you didn't understand or you wanted to 7 explain in a little more detail for one of the public 8 commenters who presented this afternoon and 9 particularly if it relates, of course, to our Charge 10 Questions. 11 There are a lot of interesting issues of 12 general science or related science that I'm sure we 13 could get into, but I would prefer that you save those 14 for separate conversations and focus on questions that 15 would relate specifically to the Panel's deliberation 16 on the Charge Questions. 17 Any members of the Panel, I guess you 18 would have to indicate who you'd like to call up, and 19 rather than create a round-robin, let me start in 20 reverse order. Any questions for Ms. Adcock? 21 For Tyler Wegmeyer? 22 For Mr. Slaughter, the Center for 23 Regulatory Effectiveness? 24 Any questions for the Triazine Network 25 team, Mr. White and colleagues?FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 290

1 Ken, Dr. Portier, has a question for Mr. 2 Hall. Mr. Hall, are you still here? 3 He may have been in town okay. This is 4 I think it's well, what I will ask Ken to do is maybe 5 to speak with Mr. White, and if it's again something 6 that needs to be fully disclosed to the Panel, he'll 7 bring it back and mention it publicly during the 8 meeting tomorrow. 9 Any questions for Mr. Snyder? 10 Questions for Dr. Hayes? 11 Dr. Hayes here yet? 12 Very good. Okay, any questions for Dr. 13 Hayes on his presentation? 14 Dr. Hayes, are you going to be here 15 tomorrow morning first thing? 16 DR. TYRONE HAYES: I will. 17 DR. STEVEN HEERINGA: Okay. Thank you 18 very much. 19 Any questions for the reversed order, 20 and again probably in terms of new information 21 presented to the Panel in terms of studies and data, 22 the Syngenta Crop Protection Group, questions for any 23 members of the Syngenta panel? 24 And again, I'll leave this open 25 overnight. I know all of the public commenters can'tFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 291

1 be back here tomorrow; but if there are questions or 2 issues that come to mind as you study the materials 3 tonight, we'll have a chance to ask those first thing 4 in the morning. 5 Dr. Portier has a question for Dr. 6 Hendley. 7 Paul Hendley? 8 This would relate to the water sampling 9 and monitoring. 10 DR. KENNETH PORTIER: Thank you for 11 coming up, Paul. 12 In looking at your presentation, there's 13 so much data here and you've been doing a lot of 14 modeling, and as I was listening to your presentation I 15 was trying to answer some of my think of the question, 16 and that is with all of the information you have. 17 All the models you have, are you at the 18 point where you'd be able to answer a question for a 19 particular community water system whether the incoming 20 water supply would meet a criteria that it would exceed 21 a certain level? Say we set a certain level for a 22 certain number of days. Would the models be able to 23 estimate the probability of exceeding that kind of a 24 duration amount event? 25 DR. PAUL HENDLEY: This is Paul Hendley.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 292

1 I think the answer is we're getting 2 there. I think assuming it's a community water system 3 from the -- I'm from the VMP Program, for which we have 4 a lot of history. 5 Assuming we have the information from 6 the current day history and this year's data, I believe 7 that if you look at the fact, we can very well define 8 what the maximum event peak that we might not have 9 sampled would be and what the distribution of those 10 peaks might be in the context of the weather and the 11 environment and stream flow; we have the tools to do 12 that. I think the dots haven't quite been joined up 13 yet to do that, but the probability is there. 14 With 50,000 sort of raw and finished 15 samples coming from the VMP and AMP Program, the 16 distribution of residues that will occur in Midwest 17 watersheds is well understood. 18 The knowledge we have about and this is 19 where I think the important insight that came recently 20 is thinking about using the flow rather more, the flow 21 that's happening at the site will connect those two 22 pieces of information. 23 DR. STEVEN HEERINGA: Thank you, Dr. 24 Hendley, and again I apologize for referring to you by 25 the wrong name.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 293

1 Dr. Akana. 2 DR. SUSAN AKANA: I'm sorry, did you say 3 Dr. Robert Handa is here? 4 DR. STEVEN HEERINGA: I believe that Dr. 5 Handa is here; but he needs to leave shortly, so if you 6 have a question for Dr. Handa, I'll -- 7 DR. SUSAN AKANA: Only quick questions. 8 Dr. Handa, as you know, I'm very 9 interested in the adrenal response that you see with 10 the atrazine. Do you know anything about the adrenal 11 weight or machinery of the adrenal gland that's been 12 treated with atrazine? 13 DR. ROBERT HANDA: I don't believe we 14 measured the adrenals; I would have to ask Charles, 15 Charles Breckenridge. 16 DR. SUSAN AKANA: Also in your studies 17 with the GnRH neurons, that was collected at 1830, 18 something like that? 19 DR. ROBERT HANDA: That was collected at 20 about the time of the peak of the LH surge. Now, we 21 had to guess on that. 22 DR. SUSAN AKANA: Uh-huh. 23 DR. ROBERT HANDA: So I believe it was 24 about an hour before lights out, which is about the 25 time, give or take an hour, that our colony shows theFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 294

1 peak of the LH surge. 2 DR. SUSAN AKANA: I was quite taken with 3 the very small response of the CRH rats in the PDN. By 4 any chance, did you look at any other CRH bodies in the 5 mediobasal hypothalamus? 6 DR. ROBERT HANDA: No, we didn't. We 7 went on to another study where we've looked at CRH 8 heteronuclear RNA to try and identify CRH cells 9 specifically and haven't identified any increased CRH 10 heteronuclear RNA. 11 DR. SUSAN AKANA: Oh, I'm thinking 12 specifically in brain sense, like amygdala or BNST? 13 DR. ROBERT HANDA: No. 14 DR. SUSAN AKANA: The distributed CRF 15 system. 16 DR. ROBERT HANDA: Right. No, we 17 haven't. 18 DR. SUSAN AKANA: Thank you. 19 DR. STEVEN HEERINGA: Dr. Handa, I 20 believe there's also a question from Dr. LeBlanc and 21 then a question from Dr. Legan. 22 DR. GERALD LEBLANC: I have a question 23 regarding a couple of slides you had up there. I'm 24 just going to read the heading for the first one -- 25 that is, "Atrazine does not alter estrogen-induced LHFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 295

1 surge in the peripubescent animal" -- and then the 2 following slide was the same thing but in the adult 3 animal. And I assume that your conclusion that there 4 was no effect was based on that total profile of the 5 induction of LH over that time course. 6 DR. ROBERT HANDA: Right, and we also 7 analyzed the data in terms of peak amplitude, 8 irrespective of when the peak was, as well as area 9 under the curve. 10 DR. GERALD LEBLANC: But looking at 11 specific time points, there seems to be in many 12 instances in both slides where there's a nice dose13 response of LH suppression with atrazine dose. 14 DR. ROBERT HANDA: So as it turns out, 15 there is an occasional point that may have been 16 different by post hoc. It's kind of hard to say that 17 we should analyze by post hoc. If the two-way analysis 18 is at variance or one-way analysis is at variance, it 19 doesn't show up significant overall. 20 DR. GERALD LEBLANC: Thank you. 21 DR. STEVEN HEERINGA: Dr. Legan. 22 DR. SANDRA LEGAN: I have a question 23 about a study that you did with the intact breast you 24 gave atrazine 4 days in a row starting on one day of 25 the cycle and then to see if it affected cyclicity,FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 296

1 was it? And you measured the LH surge? 2 DR. ROBERT HANDA: Right. 3 DR. SANDRA LEGAN: The LH 4 concentrations, and then you mentioned you had a graph 5 with bars. As the dose increased to the 50 mg/kg dose, 6 you had about 25% of the animals in that group had 7 delayed their cycle to go to well 8 DR. ROBERT HANDA: Exactly. 9 DR. SANDRA LEGAN: they were a 5-day 10 cycle instead of a 4-day cycle. 11 DR. ROBERT HANDA: A 5-day cycle, right. 12 So -- 13 DR. SANDRA LEGAN: And that was 14 determined how? 15 DR. ROBERT HANDA: On every morning the 16 animal is smeared. If they showed a proestrus surge or 17 a proestrus smear, they would be sampled for LH. If 18 they did not, we would wait till the next day and then 19 they would be sampled. And that's the only group, in 20 fact, where a significant number of animals we had to 21 delay the taking of the blood samples till the 22 following day. 23 DR. SANDRA LEGAN: And did you combine 24 the LH levels from the 4- and the 5-day rats in all 25 your data?FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 297

1 DR. ROBERT HANDA: We did that in two 2 ways. We analyzed the data for the 4 and 5 days 3 combined, and that was the following slide after that, 4 as well as the 4-day cyclers only to see if there was 5 an impact of having to wait the extra day on the 6 effective averaging, and there was no difference in 7 terms of their profiles. 8 DR. SANDRA LEGAN: So there was no 9 difference in the LH profiles between the animals that 10 had 4-day cycles and the animals that had 5-day cycles 11 DR. HANDA: Well, we only had a few. We 12 only had -- 13 DR. SANDRA LEGAN: Yeah, 5 animals out 14 of 20, maybe? 15 DR. ROBERT HANDA: Yeah, so we compared 16 4- and 5-day cyclers with 4-day cyclers alone. 17 DR. SANDRA LEGAN: I see, because so 18 that it comes up to mind that I guess if I were doing 19 it, I might not combine the 4- and 5-day cyclers unless 20 I could statistically determine that they were not 21 different. 22 DR. ROBERT HANDA: Right. 23 DR. SANDRA LEGAN: And there's an end of 24 maybe if you had 20 per group, which you started 25 with...FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 298

1 DR. ROBERT HANDA: Right, there were -- 2 DR. SANDRA LEGAN: there would be -- 3 DR. ROBERT HANDA: -- about 19 in that 4 group at the end, and so I believe there were 5, 5 -- 5 DR. SANDRA LEGAN: Five that -- 6 DR. ROBERT HANDA: -- that were delayed 7 and became 5-day cyclers. 8 DR. SANDRA LEGAN: -- delayed and -- 9 DR. ROBERT HANDA: -- and became 5-day 10 cyclers. 11 DR. SANDRA LEGAN: -- 14. 12 DR. ROBERT HANDA: Right. 13 DR. SANDRA LEGAN: You could still do a 14 DR. ROBERT HANDA: We could do an 15 analysis on those alone, you know; it was much easier 16 to do the 4 days alone and see if there was in fact any 17 difference. 18 DR. SANDRA LEGAN: So the reason I'm 19 asking is because yesterday I mentioned that this drop 20 in the this effect of atrazine in attenuating the 21 amplitude in the LH surge is maybe only critical if the 22 LH surge amplitude is low enough to have adverse 23 sequelae, such as lengthening cycle. 24 So if the animal has too low an amount 25 of LH, obviously, they will not ovulate, and they mayFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 299

1 you know, the follicles are still producing estrogen 2 and they may have an LH surge the next day, which you 3 saw. 4 DR. ROBERT HANDA: Right. 5 DR. SANDRA LEGAN: So I guess your data, 6 would you say that your data indicate that in the LH 7 surge attenuation that you saw in that dose group was 8 about a 50% drop? If you look at the numbers, whatever 9 the LH peak was in the one group, it was about half of 10 that. 11 DR. ROBERT HANDA: It was, it was a 12 little over half. 13 DR. SANDRA LEGAN: Okay. So 55- 14 DR. ROBERT HANDA: 50% -- 15 DR. SANDRA LEGAN: 60%, so you could 16 go 60? 17 DR. ROBERT HANDA: -- yeah, somewhere in 18 that range. 19 DR. SANDRA LEGAN: So we have a 40% -- 20 and there's been data presented and you know well that 21 that's enough for fertility in the rat so that supports 22 do you think that supports the possibility that 23 atrazine might have another effect that ultimately is 24 deleterious than only, maybe including even, but not 25 solely the drop, the 50%, say, drop or whatever in theFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 300

1 LH surge amplitude? 2 DR. ROBERT HANDA: Well, I've thought 3 about that a lot in terms of what that would mean. And 4 again, coming into mind the fact that we don't see a 5 tremendous drop in the surge and why that some animals 6 would be delayed. 7 And frankly, I don't know for sure why 8 they would be delayed in their cycle; I could only 9 guess. They appeared to have normal, perhaps, you 10 know, decreased in amplitude like the rest of the 11 group. 12 But certainly they were sufficient 13 enough that you would expect they would be on the 14 physiological end of things that they would show normal 15 cycles. 16 DR. SANDRA LEGAN: Uh-huh. 17 DR. ROBERT HANDA: So again, there may 18 be something else appearing; we don't know. 19 DR. SANDRA LEGAN: Thank you. 20 DR. STEVEN HEERINGA: Thank you very 21 much. 22 Dr. Breckenridge, I just acknowledge 23 you. 24 DR. CHARLES BRECKENRIDGE: Thank you 25 very much; Charles Breckenridge, Syngenta.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 301

1 There is rather extensive literature on 2 the cycle-disrupting effects of atrazine as it 3 progresses through to mammary tumor development in a 4 constant estrus state; so clearly, high doses of 5 atrazine will lengthen the cycle, and so it may well be 6 that these animals in this duration are actually on the 7 edge of the cycle-disruption effect. 8 I mean, we don't this certainly is 9 consistent with those other studies both by Dr. Cooper 10 and by us. 11 DR. STEVEN HEERINGA: Dr. Cooper has a 12 question for Dr. Handa. 13 DR. RALPH COOPER: Yes, I just wanted to 14 I guess get your opinion, given all the studies that 15 you've done looking at the interrelationship of the HPA 16 axis and atrazine and stress, and what's your opinion 17 of the possibility that the situation in an 18 experimental study where there is higher levels of 19 stress where the effects of atrazine might in fact be 20 blunted? Do you think that's possible? 21 DR. ROBERT HANDA: I am not sure I 22 understand your thinking; there may be in fact elevated 23 levels of stress, which the chronic atrazine would then 24 decrease. 25 DR. RALPH COOPER: Or it would make itFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 302

1 more difficult to see the effects of atrazine. 2 DR. ROBERT HANDA: You would expect, 3 then, that you would see a difference compared to the 4 vehicle treated controls, and we don't see a 5 difference, in fact. So they're almost identical after 6 7, 14 and 28 days of administration of atrazine. So I 7 would expect that would not be the case. 8 We can also look at the absolute values 9 of corticosterone, and we know from a number of studies 10 historically where the levels of corticosterone should 11 be approximately, about 2 to 5 Ug/g. And they seemed 12 to be in that range for both males; and the females are 13 always a little higher, and they seemed to be in the 14 normal range for females as well. 15 DR. STEVEN HEERINGA: Dr. Krishnan, do 16 you have a comment for Dr. Handa, a question? 17 DR. KANNAN KRISHNAN: In the slide where 18 you plotted the NOELs for atrazine, the Cooper study, 19 et al., from Cooper 2010 wasn't there; it doesn't fit 20 the pattern. Do you want to comment on that? 21 DR. STEVEN HEERINGA: Dr. Breckenridge? 22 DR. KANNAN KRISHNAN: Yes. 23 DR. CHARLES BRECKENRIDGE: Charles 24 Breckenridge, Syngenta. 25 That was more like a historical slide weFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 303

1 were bringing up in the context of the design for the 2 developmental study. That was really the reason why we 3 did the developmental study, because we recognized that 4 the duration of treatment was confounded with age. 5 And so in some ways, that slide is 6 perhaps needing a bit of clarification. It really 7 wasn't duration-indicated. In the higher dose groups, 8 those are really short duration, 2, 3 days. 9 And as you went on in fact, in the 10 Morseth 1986 was in fact continuous dosing for at least 11 six months. So the whole intent of the study that we 12 did with the developmental effects or investigating 13 potential developmental effects was to elaborate 14 whether in fact at a particular age a 2-week exposure 15 would produce the same effect as a 90-day consecutive 16 exposure, and that's effectively why we had recovery 17 groups in there. 18 We were fully anticipating to see a 19 response at 90 days and we did not, and that was 20 somewhat surprising to us. In fact, we didn't see, as 21 you might have noticed, 2 weeks of dosing at 90 days 22 didn't produce an effect. 23 Yet, 1 week of dosing at that same age 24 did. And so that is a bit perplexing to us, and we'll 25 be doing some investigations to further understandFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 304

1 whether in fact there is a falloff, especially in young 2 animals, of duration of treatment as you first 3 introduce the compound versus continue that duration 4 for some time. 5 So, in fact, we didn't put Dr. Cooper's 6 data on that slide. We didn't put our data on that 7 slide, either. But it was more historical slide coming 8 from the December SAP and I think reiterated by the EPA 9 in one of the early ones this year. 10 DR. STEVEN HEERINGA: Dr. McManaman. 11 DR. JAMES MCMANAMAN: I'll let Dr. Handa 12 go away. I have a question for Dr. Hovey. 13 DR. STEVEN HEERINGA: Thank you, Dr. 14 Handa. I understand you have a plane to catch, so 15 DR. ROBERT HANDA: Thank you. 16 DR. JAMES MCMANAMAN: Yeah, I need some 17 clarification. It's slide 12, it's the maternal body 18 weight change. There are asterisks indicate two 19 different things on this slide, so the pair-fed versus 20 the control, or is it statistically significant, or is 21 it the pair-fed versus the 100 mg/kg/d? Which one is 22 it, because it's not clear? 23 DR. RUSS HOVEY: Yeah, sure. So the 24 question relates to significant difference associated 25 with the pair-fed group. And so that was a comparisonFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 305

1 of the pair-fed animals to the 100 mg/kg group. 2 The reason we made that comparison was 3 because that was what they were yoked to, whereas the 4 atrazine-dosed females were compared against the 5 vehicle dose control. And in addition, the pair-fed 6 group was significantly different from the vehicle 7 exposed control group as well. 8 DR. JAMES MCMANAMAN: And that was both 9 during lactation and during gestation? 10 DR. RUSS HOVEY: No, so during gestation 11 there was a -- let's pull the slide up. 12 So during gestation, there was a 13 significant reduction versus the high-dose atrazine. 14 So the question becomes why was there even a more 15 pronounced decrease in body weight gain. 16 What we think was going on there is that 17 there perhaps is a different mechanism at play in terms 18 of these animals that are being forced to restrict 19 their food intake by matching them to the atrazine 20 group, whereas the atrazine animals are, if you will, 21 voluntarily restricting their intake. 22 DR. JAMES MCMANAMAN: So is there any 23 concern about difference in metabolism between the 24 atrazine-treated group versus the control group? 25 DR. RUSS HOVEY: Between the atrazine-FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 306

1 treated group and the control group? 2 DR. JAMES MCMANAMAN: Right. It would 3 appear that one explanation would be it's the atrazine4 treated group are more metabolically inefficient; 5 therefore, their weights did not decrease as much as 6 the pair-fed. 7 DR. RUSS HOVEY: Yes, so I don't think I 8 can comment on any sort of metabolic efficiency of 9 those animals, per se. I think we were looking at it 10 the other way, and that is that both animals are 11 undergoing a metabolic stress, if you will, obviously 12 not demonstrating as much maternal body weight gain as 13 the control animals would. 14 DR. JAMES MCMANAMAN: One more question. 15 This is on slide 18, and that is the whole mount 16 analysis. There's an indication that the pair-fed 17 versus the atrazine 100 are significantly different. 18 The atrazine 100 have fewer end buds than the pair-fed 19 group, is that correct? 20 DR. RUSS HOVEY: That's correct. 21 DR. JAMES MCMANAMAN: Okay. The 22 analysis that was given, provided by Syngenta in the 23 papers that we received, the statistician said that 24 there was no difference. Does your conclusion differ 25 from his, or is there a mistake there?FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 307

1 DR. RUSS HOVEY: Oh, I'd have to defer 2 to the original analysis on that. We didn't notice 3 that, so we certainly will check if we do have an error 4 in that report; but I believe as we represented it here 5 is correct. 6 DR. JAMES MCMANAMAN: Okay. So given 7 that there is a statistically significant difference in 8 the number of end buds, would you then conclude that at 9 the 100 mg/kg atrazine that there is an effect on the 10 mammary gland properties? 11 DR. RUSS HOVEY: Now, can you repeat the 12 question in terms of which treatment you're comparing? 13 DR. JAMES MCMANAMAN: Well, if we're 14 comparing the pair-fed, which I agree with you is an 15 appropriate control; but if you compare that with the 16 100 mg/kg atrazine, which would be the proper 17 comparison, then you see a statistically significant 18 difference in the number of terminal end buds at the 19 date of vaginal opening. 20 DR. RUSS HOVEY: So I guess my comment 21 would be that in fact the pair-fed animals, by virtue 22 of them having a dam that was matched for a decrease in 23 maternal body weight gain during gestation, the fact 24 that they demonstrated an increase in end bud number at 25 the time of vaginal opening relative to the vehicleFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 308

1 treated controls suggests that there was a in utero 2 effect, if you will, or a carryover effect from that 3 maternal treatment due to body weight restriction. 4 DR. JAMES MCMANAMAN: Well, I would 5 agree with that. But also, then you're leaving out the 6 comparison to the pair-feds. 7 DR. RUSS HOVEY: Uh-huh. 8 DR. JAMES MCMANAMAN: And that would 9 seem to me the more appropriate comparison. 10 DR. RUSS HOVEY: So it suggests that 11 there is potentially a different mechanism at play in 12 terms of the fact that the 100 and the 50 mg/kg doses, 13 I'm not showing a dose-dependent response. 14 DR. JAMES MCMANAMAN: Well, clearly, 15 there was not a dose-dependent response on this yet. 16 But you did mention that diet and nutrition can affect 17 mammary gland development. 18 DR. RUSS HOVEY: Uh-huh. 19 DR. JAMES MCMANAMAN: And presumably if 20 we're factoring in body weights here, that they've had 21 the same restriction of diet because they've reduced 22 their intake; therefore, it would seem that it can't 23 completely explain everything by reduced weight. 24 DR. RUSS HOVEY: Right, nobody's 25 consistent with even, you know, our observation duringFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 309

1 gestation in terms of the fact that the forced 2 restriction of food intake did not lead to an identical 3 maternal body weight change. 4 DR. JAMES MCMANAMAN: I have one more 5 question, sorry. So you note -- I think it's back on 6 that previous -- about weight that the 50 mg/kg 7 atrazine was statistically different, basically lower 8 in body weight compared to the control. 9 DR. STEVEN HEERINGA: Dr. McManaman, 10 which slide are you looking at? 11 DR. JAMES MCMANAMAN: This is slide 12. 12 DR. STEVEN HEERINGA: 12, thank you. 13 DR. JAMES MCMANAMAN: Yeah. 14 So is that consistent finding in all the 15 studies, because I believe in one of the other studies 16 that we received -- I know it by I think it's Coder A, 17 I believe, or Coder I can't remember which one it was; 18 but there was no difference in the weights of the 50 19 mg/kg. So I'm wondering, is there some explanation for 20 why this one was different and the other one was not? 21 DR. RUSS HOVEY: Without going back to 22 the original data, one suggestion is that this is a 23 representation of the maternal body weight change 24 during the whole dosing period. 25 DR. JAMES MCMANAMAN: Okay.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 310

1 DR. RUSS HOVEY: And that may account 2 for your question. 3 DR. JAMES MCMANAMAN: Right. Thank you. 4 DR. STEVEN HEERINGA: Thank you, Dr. 5 McManaman and Dr. Hovey. 6 Dr. Akana. 7 DR. SUSAN AKANA: On the same slide, I'm 8 interested in their pair-fed controls. Rats normally 9 eat in a diurnal rhythm; so with pair-fed control, how 10 did you give them their food, diurnally or in one lot, 11 or did you yoke it to a diurnal pattern of the 12 controls? 13 DR. RUSS HOVEY: So if I may, I will 14 defer to Dr. Coder from WIL Research, who conducted the 15 animal side of things. 16 DR. STEVEN HEERINGA: Sure. Dr. Coder, 17 your full name for the record, please. 18 DR. PRAGATI CODER: Pragati Coder, WIL 19 Research. I am a Senior Toxicologist in the 20 Developmental and Reproductive Toxicology Department. 21 The pair-fed group was one day behind in 22 gestation, so they were mated a day after the 100 mg 23 group and were pair-fed the diet the 100 mg/kg group, 24 the mean amount that they consumed on the previous day. 25 But the diurnal consumption was not 100. It was givenFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 311

1 to them as a lump amount at the beginning of the day. 2 DR. SUSAN AKANA: Okay. And then a 3 general question to this data, is this a study that 4 originally had a design of cross-fostering? 5 DR. CHARLES BRECKENRIDGE: That's 6 correct, there's two additional groups that were 7 maintained as separate groups going into the study. 8 So -- 9 DR. SUSAN AKANA: And this is the one 10 where there was a sad failure of survival of the cross11 fosters, is that correct? 12 DR. CHARLES BRECKENRIDGE: Correct. 13 DR. SUSAN AKANA: Did this take place in 14 the same experimental room as the other dose studies, 15 the atrazine? 16 DR. CHARLES BRECKENRIDGE: I will defer 17 to Dr. Coder on that. 18 DR. PRAGATI CODER: Yes, it was. 19 DR. SUSAN AKANA: And if you rack your 20 brain, do you see any conceivable reason for the 21 failure for fostering, because I would consider that a 22 red flag for the housing for the whole entire room. 23 DR. PRAGATI CODER: They were housed in 24 the same room. Animals were initially assigned to the 25 same control in high-dose group. It was afterFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 312

1 parturition was complete on lactation day 0 that we 2 tried to foster the pups. We routinely foster rats in 3 our facility and unfortunately don't do it as often 4 with Long-Evans. 5 We tried several different things to 6 facilitate the fostering. Initially, what we tried to 7 do was foster the entire litter. Unfortunately, in a 8 GLP compliant situation, we have to record observations 9 on every pup, and in an electronic database system it's 10 difficult to foster a half-and-half model that was done 11 on previous studies. 12 So when the whole litter was taken, it 13 was quite obvious within minutes that the dam would 14 immediately begin to cannibalize the pups. 15 So the next thing we tried was since we 16 were mainly interested in the female pups in this 17 study, we tried to maintain the male pups with the 18 original dam and tried to put the female pups in the 19 nest, laid them with the male pups to facilitate maybe 20 a better chance of fostering. That didn't work, 21 either. 22 We even tried things like rubbing the 23 pups against the dam prior to putting them in the cage, 24 which didn't work. We tried even vanilla extract on 25 the snout of the dam to see if that might remove theFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 313

1 scent of the pups or prevent them from being able to 2 identify self versus non-self, but that didn't work, 3 either. 4 DR. SUSAN AKANA: What was the duration 5 of time over the fostering attempts? Like were you 6 trying to foster over, say, three or four days, you 7 know, among the gestation dates or 8 DR. PRAGATI CODER: The entire study I 9 believe was staggered maybe over five or seven days. 10 Pretty much by the end of the second day we knew the 11 fostering was not going to work, and in order to 12 conserve the remaining groups and group sizes, we had 13 to make a terminal decision about those groups. 14 DR. STEVEN HEERINGA: Thank you very 15 much, Dr. Coder, Dr. Akana. 16 Yes, Dr. McManaman. 17 DR. JAMES MCMANAMAN: So I have a 18 question as a follow-up of Dr. Akana's question. One 19 difference between the Syngenta study and Dr. Fenton's 20 study was that the animals are housed in Dr. Fenton's 21 study on a 14/10 light/dark cycle versus the 12/12. 22 It's my understanding that differences in light/dark 23 cycles can significantly affect responses, and I would 24 like to get your response to that concern. 25 DR. PRAGATI CODER: All the LH surgeFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 314

1 studies were on a 14/10 light cycle in our facility, 2 too. From the moment of animal arrival. 3 DR. JAMES MCMANAMAN: Okay, but that's 4 not what's reported. It's reported as a 12/12, I 5 believe. 6 DR. PRAGATI CODER: I will have to look 7 into the discrepancy-- 8 DR. JAMES MCMANAMAN: Okay. 9 DR. PRAGATI CODER: --but I am 100% sure 10 they were 14/10. 11 DR. JAMES MCMANAMAN: Right. 12 DR. STEVEN HEERINGA: Dr. Lee. 13 DR. HERBERT LEE: I have a question for 14 Dr. Hendley. 15 DR. STEVEN HEERINGA: Yes, Paul Hendley. 16 You should let him stay up front, I guess. 17 DR. HERBERT LEE: So you sort of glossed 18 over this, but you presented it in the materials for 19 the Docket. There is a summary of results for the 20 Perry Lake sampling frequency analysis in terms of 21 looking at different -- it says "10,000 trials of 22 selected fixed frequency sampling" right here; this is 23 slide 11. I was wondering how you did the sampling? 24 "Fixed frequency" implies something to me that I don't 25 think you can do 10,000 trials of, so I'm perhapsFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 315

1 misunderstanding. 2 DR. PAUL HENDLEY: Well, Paul Hendley 3 speaking. 4 So this is actually from a 2001 5 publication; this is not analysis Syngenta did. This 6 is a publication that I believe actually was a 7 combination of authorship from USGS and EPA. 8 I believe that they used some Monte 9 Carlo-style approach to pull the 10,000 sets of samples 10 from what, as far as I can tell from the literature, 11 were constructed 365-day time series. 12 DR. HERBERT LEE: Okay, thanks, I'll 13 follow up with the reference. 14 DR. PAUL HENDLEY: We'd be happy to 15 supply that. 16 DR. STEVEN HEERINGA: Dr. Legan. 17 DR. SANDRA LEGAN: Thank you. I have a 18 question for Dr. Plant. 19 DR. STEVEN HEERINGA: Dr. Plant, please. 20 DR. SANDRA LEGAN: My question relates 21 to your last slide. At the end of your talk, you put 22 the control mechanisms up and how estrogen feeds back 23 to the hypothalamus. On one side you talked about the 24 rat; on the other side about the primate, possibly 25 human.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 316

1 And my question is you have estrogen 2 positive feedback in the rat going to the preoptic area 3 where the GnRH neuron cell bodies are. And of course 4 in the monkey it goes to the mediobasal area of the 5 hypothalamus. 6 And that was kind of your main summary 7 point, along with all your other data, that kind of led 8 to the conclusion that the LH surge -- the positive 9 feedback, actually, of estrogen on the LH surge is 10 probably not the best or maybe not be the best endpoint 11 to look at in terms of being able to take this forward 12 and extend our conclusions to adverse possible effects 13 in humans. 14 And I just want to ask if you looked at 15 it a little differently and estrogen, since the GnRH 16 neurons, they have only estrogen receptor data, and 17 changes in the complement of those receptors are really 18 unrelated to either negative or positive feedback 19 actions of estradiol in the rodent; I don't know about 20 the primate offhand. 21 So estrogen positive feedback isn't 22 directly probably on the GnRH neurons. It's indirect 23 through any number of other areas of the brain, and 24 there in the background Draft Paper it alludes to the 25 catecholamine, catecholaminergic neurons, dopaminergicFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 317

1 neurons. And as many of us understand, there's a 2 number of neurotransmitter systems involved. 3 So if you redrew your diagram and you 4 had estrogen positive feedback from higher centers 5 feeding ultimately to wherever the GnRH neurons are in 6 whichever species you happen to be looking at, do you 7 think it could be possible that the rat is an okay 8 model? 9 I mean, and that main difference that 10 remains would be the clock, you know, the time-of-day 11 gating of the surge through from the SCN and so forth. 12 So what do you think about that? Is that a 13 possibility? 14 DR. TONY PLANT: I think it's possible, 15 but I think that at the contemporary thinking of the 16 rodent world -- and I don't study the rodent -- but 17 that is that the kisspeptin and the tachykinin-b story 18 where people like Robert Steiner, Janice Simpair and 19 Cordova, the kisspeptin neurons mainly in the brain 20 generally are located in the AVPV, which is an area 21 above the optic chiasm here. 22 DR. SANDRA LEGAN: Uh-huh. 23 DR. TONY PLANT: They have estrogen 24 receptors, and there's also kisspeptin neurons in the 25 arcuate nucleus. They express also tachykinin-B andFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 318

1 dynorphin; they're called candy neurons. Bob Goodman, 2 your colleague, characterized the term there. 3 But these neurons have estrogen 4 receptors, and all the data in the rodent suggests that 5 these neurons in the AVPV above the optic chiasm are 6 the site or a major site of the positive feedback 7 action of estradiol. 8 That fits very nicely with Goodman's 9 classical studies in the rodent, where you put 10 estradiol either in this region of the preoptic area or 11 in the NBH. 12 DR. SANDRA LEGAN: Uh-huh. 13 DR. TONY PLANT: And he found that the 14 only sort of surges in the rat when estradiol was 15 implanted here and not in the mediobasal hypothalamus. 16 So the contemporary stuff on the kisspeptin story fits 17 very nicely with the classical stuff. 18 And in the context of the primate, all 19 the classical work there eliminating the preoptic area 20 suggests that that is not involved in the regulations 21 of surge. 22 DR. SANDRA LEGAN: Right. But are there 23 kisspeptin neurons -- 24 DR. TONY PLANT: No, no, there are 25 kisspeptin neurons.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 319

1 DR. SANDRA LEGAN: Then where are they 2 in the primate? 3 DR. TONY PLANT: As I say, they're -- 4 DR. SANDRA LEGAN: They're inside the 5 MBH? 6 DR. TONY PLANT: No, the kisspeptin 7 neurons are in the preoptic area; now, my colleagues 8 will argue that the kisspeptin neurons in the primate 9 brain may not be homologous to the AVP in the rodent 10 brain. But there are kisspeptin neurons in the 11 preoptic area. There's also kisspeptin neurons in the 12 arcuate nucleus. 13 But I think the fundamentally important 14 studies are the studies in the human female, where the 15 GnRH neurons in the Coleman's patients never get into 16 the hypothalamus. 17 And yet, those women, if you give them 18 this uninterrupted intermittent GnRH drive, will cycle 19 spontaneously, will have normal pre-ovulatory surges. 20 And therefore, you have to exclude the entire 21 hypothalamus as being a site of positive feedback; it 22 has to be the pituitary. 23 DR. SANDRA LEGAN: Uh-huh. 24 DR. TONY PLANT: And coupled with Janet 25 Hall's data that the pulse generator still operatesFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 320

1 during the midcycle surge, and her pharmacological data 2 which suggests the amount of GnRH during the surge, the 3 LH surge in the human female, is actually less than 4 during the follicular phase, the most parsimonious 5 hypothesis is that in the human female all you require 6 and all you have for running the menstrual cycle is 7 this intermittent pulsatile pattern of GnRH, which is 8 driven by the mediobasal hypothalamus. 9 DR. SANDRA LEGAN: Uh-huh. Thank you. 10 DR. TONY PLANT: Probably by the candy 11 neurons. 12 DR. SANDRA LEGAN: Okay, thanks. 13 DR. STEVEN HEERINGA: Okay. Well, thank 14 you very much, Dr. Legan and Dr. Plant. 15 At this point in time, I think that I 16 will leave the period of public comment open. 17 Dr. Breckenridge, I will permit you a 18 comment here. 19 DR. CHARLES BRECKENRIDGE: Please. Just 20 for convenience, Dr. Plant would like to leave 21 early morning, and also I think Dr. Handa leaves 22 tomorrow as well, plus I believe the topics are breast 23 bud development. 24 So if there could be any questions 25 relating to that, we would like to give them, Dr. HoveyFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 321

1 and Dr. Plant, an opportunity to answer them tonight, 2 or if you think it's a high likelihood -- 3 DR. STEVEN HEERINGA: Right. 4 DR. CHARLES BRECKENRIDGE: -- you'll 5 have a discussion on these matters tomorrow, I don't 6 believe Dr. Handa can be here at all. Dr. Hovey, it 7 would inconvenience him for sure. 8 DR. STEVEN HEERINGA: Understood. I 9 think that as a courtesy here, looking at the Panel 10 members, are there other critical questions of 11 clarification for Dr. Plant or Dr. Hovey? 12 FEMALE: Dr. Kim? 13 DR. STEVEN HEERINGA: Dr. Kim will be 14 here tomorrow, is that correct? Okay. 15 I guess I would say that looking around 16 the room that we're satisfied that the key questions 17 that we feel need to be answered from those 18 presentations have been addressed, and we do have the 19 presentations and the information. 20 I assume, Dr. Breckenridge, if there's a 21 critical matter of fact that we could come back through 22 you and before the close of the proceedings. 23 DR. CHARLES BRECKENRIDGE: That's 24 correct, and I have Dr. Simpkins to help me with any 25 particular neuroendocrine type of question.FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 322

1 Okay, thank you. 2 DR. STEVEN HEERINGA: In that case, what 3 I'd like to do today is bring the proceedings to a 4 close; but before I do that, I'll turn to the 5 Designated Federal Official. 6 Joe, do you have anything to say? 7 Okay, nothing today. 8 Again, I want to thank everyone who 9 participated today. A tremendous exchange of 10 information; as I always say, I learned a tremendous 11 amount and look forward again to picking this up 12 tomorrow morning. 13 We'll leave the period of public comment 14 open so that if the Panel comes up with any other 15 critical questions, if you prepare your responses to 16 the Charge Questions or review some of the information 17 that's been presented in the public comment period, 18 we'll have a chance to address that. 19 I think we'll also have a chance for the 20 EPA to provide any closing remarks or summaries, 21 including any rejoinder to things that may have 22 occurred in the public comment period, and then we'll 23 move on to the Charge Questions. 24 And so thank you, everyone, for your 25 participation today, and we'll see everyone tomorrowFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 323

1 morning at 8:30. 2 (WHEREUPON, the proceedings recessed at 5:12 p.m.) 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 324

1 CAPTION 2 3 The foregoing matter was taken on the date, and at the 4 time and place set out on the Title page hereof. 5 6 It was requested that the matter be taken by the 7 reporter and that the same be reduced to typewritten 8 form. 9 10 Further, as relates to depositions, it was agreed by 11 and between counsel and the parties that the reading 12 and signing of the transcript, be and the same is 13 hereby waived. 14 15 16 17 18 19 20 21 22 23 24 25FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 325

1 CERTIFICATE OF REPORTER 2 COMMONWEALTH OF VIRGINIA 3 AT LARGE: 4 I do hereby certify that the witness in the foregoing 5 transcript was taken on the date, and at the time and 6 place set out on the Title page hereof by me after 7 first being duly sworn to testify the truth, the whole 8 truth, and nothing but the truth; and that the said 9 matter was recorded stenographically and mechanically 10 by me and then reduced to typewritten form under my 11 direction, and constitutes a true record of the 12 transcript as taken, all to the best of my skill and 13 ability. 14 I further certify that the inspection, reading and 15 signing of said deposition were waived by counsel for 16 the respective parties and by the witness. 17 I certify that I am not a relative or employee of 18 either counsel, and that I am in no way interested 19 financially, directly or indirectly, in this action. 20 21 22 23 24 MARK REIF, COURT REPORTER / NOTARY 25 SUBMITTED ON SEPTEMBER 15, 2010FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 326 $ $10 254:20 $100 253:15 253:17 $2.5 253:20 $20 254:20 $30 253:13

0 0 129:25 164:12 164:13 189:25 312:1 0.0001 210:23 0.09 32:17 54:4 62:21 0.5 149:25 150:17 235:4 0.500 235:5 0.7 20:13 0.75 86:16 140:5 0.87 32:17 35:2 35:7 35:23 0.9 20:13 35:2 35:6 35:22 62:21 04 67:14

1 1 17:19 17:24 18:11 18:15 19:16 55:19 55:21 59:11 60:2 60:13 99:21 100:2 102:13 103:1 104:19 104:23 105:21 105:24 119:9 127:7 129:20 130:16 146:23 147:8 152:14 155:8 176:25 205:6 231:22 231:24 232:1 232:3 232:23 233:17 233:19 236:20 237:14 237:15 237:16 242:8 272:25 303:23 1,000 53:25 54:1 1,800 147:18 1.0 149:25 150:17 1.1 152:9 1.5 14:14 86:16 140:5 1.6 170:10 1:00 227:21 1:15 156:17 157:6 1:6 20:6 10 32:25 33:11 33:16 44:17 46:19 50:13 78:24 86:17 86:18 87:3 99:12 99:13 138:17 140:5 147:2 147:10 148:9 151:9 161:11 164:13 164:17 205:6 205:12 205:13 209:19 216:8 237:7 275:18 10% 50:23 96:1 189:10 10,000 53:25 54:2 54:3 242:21 314:21 314:25 315:9 10:00 57:19 73:18 100 17:1 29:14 36:14 37:4 38:12 53:25 54:1 54:5 64:4 71:21 72:13 87:5 94:18 95:7 98:1 102:15 103:8 105:21 127:3 131:10 131:12 131:16 131:18 147:3 269:23 304:21 305:1 306:17 306:18 307:9 307:16 308:12 310:22 310:23 310:25 100% 16:19 195:1 314:9 100,000 242:19 100-dose 67:13 10-day78:9 10-meter 175:7 10-year 195:4 11 29:24 31:4 31:15 45:12 46:13 46:19 214:1 237:17 314:23 11% 177:21 1100 172:18 12 46:19 113:18 114:5 114:17 139:19 185:25FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 327

192:15 237:17 269:20 304:17 309:11 309:12 12% 31:14 12/12 313:21 314:4 12:30 156:6 120 19:8 28:3 28:5 28:24 38:18 13 29:17 31:10 31:11 94:17 98:1 213:25 214:1 214:4 237:17 13% 18:16 31:16 130 170:4 133 136:10 136:23 137:16 133-day136:18 133-day-old 137:14 13-week-old

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2 2 18:3 18:4 18:5 19:19 55:25 55:25 75:4 84:22 104:9 124:6 136:6 136:18 137:19 147:14 154:21 155:15 164:3 176:25 186:23 231:23 232:1 232:1 232:2 232:23 233:17 233:19 236:20 242:9 242:16 302:11 303:8 303:21 2% 177:24 262:16 262:17 2,000 189:23 2.3 152:10 2.5 32:17 34:6 177:6 200:23FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 328

2:00 65:21 20 31:8 37:9 49:4 50:2 61:8 65:7 65:9 66:14 110:16 136:24 147:10 176:23 297:14 297:24 20% 32:6 61:8 200 50:24 125:9 130:2 132:13 2000 178:6 203:16 212:15 213:1 213:4 213:5 213:11 213:13 213:15 219:14 272:1 274:3 274:7 2001 315:4 2002 196:5 202:20 243:13 2003 78:2 170:2 170:7 170:12 188:6 196:5 196:6 197:3 219:18 219:25 220:5 230:13 2004 26:3 44:24 230:13 2005 41:6 64:12 68:15 94:15 97:23 2006 14:21 89:14 219:22 242:9 280:11 2007 28:2 58:15 62:24 181:21 220:4 272:3 275:1 275:11 275:13 2008 206:5 2009 220:10 220:10 220:23 222:22 243:13 2010 2:3 14:13 76:23 162:5 195:24 197:25 230:2 243:8 272:3 275:7 302:19 2011 145:18 155:25 223:1 2012 243:4 2013 224:21 243:6 244:23 21 12:1 35:9 42:16 72:6 99:13 99:21 102:1 102:25 103:3 104:14 105:5 105:22 105:25 140:21 22 30:11 165:15 219:21 246:24 220 28:3 38:23 23% 15:9 24 12:3 12:5 75:16 114:5 114:14 120:10 24,000 204:15 204:19 204:21 204:22 24-hour 113:6 113:12 113:21 114:18 120:5 24th 269:20 25 16:16 32:10 32:13 32:18 35:4 35:9 37:4 53:19 53:22 64:3 73:18 85:24 99:14 131:13 177:3 259:12 25% 31:17 32:6 61:9 61:10 296:6 250 32:18 199:17 27 244:14 244:16 244:16 27,000 170:16 170:16 27th 219:14 269:25 28 85:8 107:24 121:3 127:8 127:20 128:2 128:10 130:17 134:9 302:6 28th 128:14 2-hour232:15 2-week303:14

3 3 18:1 19:21 49:2 55:24 55:25 86:16 87:3 132:10 132:15 132:17 135:8 136:7 140:5 146:19 147:2 147:4 147:14 148:8 154:22 155:12 174:13 176:25 188:22 196:17 231:24FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 329

232:2 232:3 232:20 232:22 232:23 232:23 233:2 233:19 236:21 238:6 246:23 249:12 249:13 253:14 272:23 274:10 285:11 285:21 303:8 3.2 34:6 3.3 152:12 3.5 34:6 177:3 3:00 65:21 228:8 30 16:22 65:7 87:5 110:17 122:15 125:2 127:4 127:17 147:3 147:10 172:14 204:23 205:16 218:22 230:3 240:20 261:21 264:18 288:19 30% 15:13 205:7 300,000 77:14 82:1 268:15 30-minute 127:19 31st219:17 32 162:11 33 27:3 33:25 34:6 34:10 57:23 99:21 103:4 105:5 350 114:8 205:8 36 114:5 36,000 268:14 360 115:3 365-day315:11 39 185:24 199:10 3-day 29:16 29:21 30:9 30:13 30:18 30:20 31:11 68:17 3-hour124:23 3-year172:21

4 4 17:24 18:1 18:11 21:11 29:23 46:13 46:19 55:16 55:16 55:19 55:21 55:24 56:17 57:12 59:9 59:16 59:23 60:9 60:13 84:23 86:8 86:12 107:25 110:17 119:9 123:3 123:23 124:9 124:12 135:13 140:7 146:11 146:12 146:12 146:25 146:25 147:14 147:19 153:15 154:7 154:12 154:17 154:22 155:8 155:13 161:7 162:25 163:2 169:25 172:2 176:25 188:22 237:13 244:9 244:16 252:20 295:24 296:24 297:2 297:16 297:19 298:16 4,400 169:20 4.0 96:23 4.3 168:21 40 17:12 65:9 164:14 191:21 192:11 192:13 218:23 40% 299:19 400 14:21 43 147:5 44 172:2 173:20 174:11 181:6 244:5 246:23 246:24 249:12 249:14 256:24 45 72:7 147:10 156:16 288:20 45,000 170:6 47 165:15 48 114:9 268:14 48% 35:4 35:5 58:11 48,000 265:6 268:24 4-daily142:20 4-day 76:24 78:8 139:23 141:6 234:17 234:23 235:20 296:10 297:4 297:10 297:16 4-hour18:4 146:11 4-point20:13FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 330

20:24 4s 58:1 59:17

5 5 29:6 107:25 124:23 147:10 221:22 269:3 275:15 297:2 297:13 298:4 298:4 302:11 5% 32:6 37:15 37:19 5,000 172:20 5.8 13:4 5:12 323:2 50 17:12 37:4 64:3 85:24 86:17 87:4 94:4 94:20 98:1 99:16 102:15 103:7 105:21 106:3 130:2 132:14 137:5 138:3 140:5 141:2 141:3 142:19 147:2 148:9 148:12 153:16 163:4 164:13 205:2 252:15 252:19 256:10 260:24 261:13 261:22 263:1 264:1 266:19 278:2 280:22 296:5 308:12 309:6 309:18 50% 15:10 205:8 299:8 299:14 299:25 50,000 78:3 169:23 292:14 500 87:5 87:6 147:3 164:13 50-year 266:10 55 299:13 58 67:9 67:18 99:25 5-day 141:10 141:18 141:20 142:23 296:9 296:11 296:24 297:10 297:16 297:19 298:7 298:9

6 6 76:10 86:16 140:5 161:7 174:15 185:25 244:10 244:12 6% 37:16 37:19 6,000 269:7 280:8 6.25 78:12 166:9 6.5 97:25 105:19 127:3 60 209:23 299:16 60% 299:15 61 9:16 67 29:20 30:15 30:17 67% 35:6 67-day-old

68:18

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8 8 54:9 54:17 56:13 110:17 138:17 148:12 161:11 162:10 244:8 244:10 8.4-fold210:3 8.73 35:3 35:7 35:24 37:7 8:00 65:20 157:2 8:30 323:1FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 331

80 94:17 212:6 80% 35:7 123:21 189:22 210:6 213:24 275:4 80s 20:5 41:24 80th 177:19 81% 35:9 87 37:24 8-week237:4

9 9 15:9 15:10 15:11 32:18 138:15 147:4 176:24 9:00 65:20 90 68:4 68:8 177:2 253:19 303:19 303:21 90% 189:16 205:1 205:10 213:21 257:7 261:19 90-day89:5 303:15 90s 158:12 172:19 176:14 96 114:5

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122:3 accumulating 172:12 173:12 accuracy 274:17 accurate 21:3 21:25 45:13 183:16 272:13 273:9 274:24FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 332

accurately259:14 acetic 16:12 achieve 87:3 88:1 achieved167:6 acid16:13 acid/ trihalomethanes 244:17 acids 242:25 244:11 acknowledge 72:19 73:15 148:1 300:22 acknowledged 94:23 acquire 89:22 acre 252:20 253:13 254:20 acres 229:1 251:25 253:14 253:19 256:25 280:19 Acridae 199:6 across 24:6 38:13 49:6 65:3 65:5 74:18 102:11 102:21 103:19 111:5 175:8 177:3 181:3 186:2 198:14 199:25 200:1 201:16 207:9 208:3 208:25 209:2 215:6 232:7 232:11 232:11 233:22 236:13 237:1 237:2 237:11 237:22 237:23 242:11 253:18 254:15 258:8 264:10 268:16 Act169:20 241:2 241:8 244:2 250:15 272:10 283:15 283:18 283:24 284:12 285:1 287:3 287:16 ACTH 85:6 126:11 acting8:12 74:12 128:21 action41:13 76:5 77:2 79:2 83:17 108:19 109:3 113:11 115:10 120:8 121:17 122:22 124:1 216:24 217:4 235:19 238:12 318:7 actions 225:5 252:5 280:23 316:19 activate 90:4 128:23 128:24 134:4 activated 123:20 123:25 129:17 243:19 248:9 248:12 activating85:4 126:19 126:23 activation90:3 123:17 active 224:25 actively 22:12 209:17 activism

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168:17 172:4 183:24 184:1 186:19 187:5 190:5 191:14 195:20 204:15 229:2 229:13 231:25 239:8 240:1 249:20 251:23 255:19 270:19 283:17 283:22 284:4 287:24 301:6 315:4 315:6 316:9 320:3 acute 42:3 78:12 89:6 131:22 166:12 acutely85:10 85:10 128:18 131:21 139:2 a-day 25:17 Adcock281:10 281:14 281:16 287:19 287:20 287:22 288:2 288:6 288:9 289:20 add53:5 122:2 143:12 172:1 182:8 271:3 added53:20 61:3 186:7 adding85:18 addition 62:10 87:15 88:11 130:21 158:24 160:18 167:2 172:5 174:23 175:3 232:12 305:5 additional 8:24 76:15 98:6 115:4 168:16 220:8 286:7 311:6 Additionally 196:12 additive 72:21 address 50:5 77:10 124:16 145:20 168:21 183:9 240:17 245:7 247:6 248:14 248:24 254:22 271:23 282:15 288:20 322:18 addressed 114:21 224:7 244:23 247:14 247:21 321:18 addressing171:20 184:15 adenocarcinoma 206:23 adequate 89:3 89:17 94:5 152:9 152:10 181:12 270:15 285:7 administer127:16 135:13 230:18 administered 69:18 70:7 112:8 135:10 164:10 administration 123:23 127:5 127:18 128:1 129:21 130:20 132:13 132:24 133:22 135:9 137:10 139:14 139:25 140:1 141:8 142:11 142:13 147:2 161:2 162:25 163:4 163:10 163:12 166:5 167:13 167:13 167:16 220:12 259:13 302:6 Administrations 222:20 Administrator 219:15 219:19 Administrators 256:13 adopting285:2 adoption 264:19 266:24 284:24 adrenal 5:14 84:12 85:3 85:6 90:3 90:4 126:12 127:24 131:25 293:9 293:10 293:11 adrenalectomized 132:10 133:4 133:13 adrenalectomy 84:17 132:11 132:21 133:7 133:20 adrenal-pituitary 46:15 adrenals 293:14 adrenocorticotropFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 334

ic 126:11 adult 50:21 81:9 87:7 102:25 103:14 105:8 132:5 135:4 137:18 187:21 295:2 adulthood51:3 67:17 159:6 189:9 adults 99:22 139:20 142:18 159:2 188:16 advance 92:12 advancements 79:8 advances 258:11 advancing216:22 adverse 5:23 24:8 25:1 31:15 39:11 69:5 80:9 81:6 88:23 106:17 158:14 158:16 158:17 158:19 159:8 197:10 229:23 229:25 235:25 238:12 238:15 238:18 239:2 239:18 285:6 285:14 298:22 316:12 adversely 198:6 advice 76:14 76:15 78:20 78:21 advise 79:11 advisory 2:1 2:6 74:5 75:25 78:21 158:12 269:14 278:10 Affairs 75:13 281:10 affect14:22 24:16 24:24 36:21 36:23 36:24 63:18 96:4 163:7 220:6 308:16 313:23 affected14:20 28:12 29:2 35:13 43:1 159:12 159:13 165:20 188:17 223:11 223:11 276:4 295:25 affecting47:9 158:22 affects 37:21 198:6 247:18 285:6 affiliation 2:15 affirm 269:9 afford 263:10 affordable 281:23 afield 251:23 African 186:18 187:21 188:10 191:1 200:21 202:2AfricanAmerican 210:6 213:24 African-Americans 214:2 214:5 214:8 214:12 afternoon 65:21 86:12 112:9 135:8 135:12 143:20 184:25 226:11 240:7 259:2 277:7 277:16 288:22 289:2 289:8 ag223:5 226:5 226:12 259:7 against232:24 279:5 279:7 279:9 279:13 279:15 280:1 305:4 312:23 age 15:9 15:10 15:11 17:14 17:18 96:14 136:10 136:23 137:16 138:15 138:17 138:21 139:19 161:11 209:23 232:10 236:24 237:4 237:8 237:18 237:22 237:24 303:4 303:14 303:23 aged23:11 agencies 186:6 219:8 269:9 272:12 272:17 273:4 Agency7:18 76:1 88:15 155:25 196:25 219:7 220:19 223:22 224:11 224:19 225:2 229:9 273:3FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 335

274:14 274:15 279:12 282:17 Agency's 225:6 ages 46:19 103:18 103:20 236:13 aging96:4 ago 15:3 42:20 75:17 94:4 117:13 137:25 164:12 186:11 186:19 194:11 258:20 273:20 280:11 agonist123:8 agreed 8:2 273:23 agreement89:18 agricultural 205:8 213:22 227:9 240:18 245:12 259:6 265:22 267:15 270:24 282:2 agriculture 204:25 205:7 205:8 205:13 205:18 226:23 262:6 264:17 278:18 278:20 279:6 281:19 Agri-Women219:1 Ah191:25 ahead8:9 65:5 143:15 144:5 aim 24:12 145:16 155:24 aimed151:19 aims 24:12 air 16:25 Akana 5:11 5:11 13:2 13:3 13:12 13:13 13:17 44:5 44:6 44:11 44:19 45:6 45:15 46:10 47:18 48:19 48:24 49:10 49:14 49:18 49:25 50:9 50:12 293:1 293:2 293:7 293:16 293:22 294:2 294:11 294:14 294:18 310:6 310:7 311:2 311:9 311:13 311:19 313:4 313:15 Akana's 313:18 al 94:15 97:23 151:22 178:24 202:20 206:22 207:1 211:5 211:8 211:9 212:25 230:2 302:19 Alar 279:14 279:16 alcohol 16:19 Alex 195:20 align 225:5 Alley 210:4 allotted8:4 217:8 280:5 allow87:16 125:5 152:22 153:4 155:22 167:20 245:14 allowed

16:22 49:3 127:9 164:19 203:7 220:17 254:7 270:1 allows 152:20 155:18 253:3 256:21 258:10 285:7 alludes 316:24 alone 25:12 153:11 269:2 297:16 298:15 298:16 ALPHA119:24 already49:20 180:14 211:22 215:10 216:10 216:24 263:13 269:15 287:2 288:23 alter 142:16 142:25 198:1 294:25 altered

24:10 altering135:1 alternative 82:3 115:4 246:8 248:5 253:10 alternatives 250:18 266:9 266:9 Alum 16:16 alveolar 18:24FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 336

am 3:7 6:7 14:5 32:21 41:19 70:1 73:1 149:15 196:20 197:6 204:24 214:3 218:3 229:10 230:4 232:5 233:8 249:7 251:11 251:14 258:23 260:2 268:13 271:18 277:17 277:19 289:1 301:21 310:19 314:9 amazingly 278:18 amendments 241:8 241:11 241:12 242:3 America 201:5 202:6 262:9 262:10 262:12 266:22 267:16 278:13 281:11 281:17 282:15 286:16 287:9 American 2:20 194:9 219:1 261:12 261:15 262:6 263:4 264:14 264:17 270:24 277:14 277:18 277:22 278:4 278:6 278:15 278:17 278:20 281:19 Americans 214:13 America's 262:16 264:20 264:21 268:18 279:23 281:17 281:23 282:9 AMM 37:7 among174:11 189:2 226:4 313:7 amongst104:3 amount19:1 49:15 50:6 58:25 114:14 119:8 119:15 144:1 156:24 160:11 196:13 203:22 257:22 265:14 280:19 291:24 298:24 310:24 311:1 320:2 322:11 amounts 163:13 252:22 AMP 174:9 175:1 292:15 amphibian 197:13 198:21 214:23 220:1 220:6 amphibians 185:23 188:6 188:11 201:16 204:5 207:15 217:1 223:4 amplitude 88:7 125:13 133:11 141:1 159:24 161:12 161:25 162:7 162:9 163:5 235:23 295:7 298:21 298:22 300:1 300:10 amygdala 294:12 analog109:16 analyses 24:19 24:22 33:1 33:12 62:5 62:12 77:6 95:23 97:1 178:1 209:21 250:16 analysis 11:20 20:14 48:20 61:25 62:15 88:17 91:21 91:22 93:15 93:19 93:21 93:23 95:9 96:20 97:7 100:6 100:8 102:9 104:2 144:15 144:19 146:8 169:2 173:2 175:10 177:19 179:4 181:2 181:13 232:20 249:23 250:5 259:19 259:24 284:24 295:17 295:18 298:15 306:16 306:22 307:2 314:20 315:5 analytical 151:24 analyze 270:17 284:2 295:17 analyzed61:14 62:3 94:6 97:11 99:20 103:23 234:2 295:7 297:2 analyzing104:10FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 337

anatomy4:12 83:1 ancillary 241:25 ANCOVAs 62:5 Andersen 87:21 144:14 androgen 43:20 130:15 130:19 134:16 159:7 165:20 202:18androgendependent 160:2 201:19 201:23 201:25 202:10 202:13 androgenic 17:4 androgens 43:7 43:8 202:22 203:18 212:19 androstenedione 130:15 130:19 anesthesia 112:8 112:11 Angela28:15 animal 24:18 40:10 47:12 60:23 65:2 68:11 91:10 91:20 117:15 118:5 133:1 138:21 139:10 158:18 161:22 161:23 161:24 187:9 194:13 203:5 216:2 216:4 234:24 235:6 239:11 253:24 279:21 295:1 295:3 296:16 298:24 310:15 314:2 animals 23:12 25:19 25:21 25:21 26:1 26:12 26:17 26:24 27:5 27:6 27:10 27:22 29:3 29:13 29:21 30:16 30:19 30:20 30:21 30:24 30:25 35:4 35:4 35:10 35:13 35:21 37:3 42:17 45:4 46:5 46:5 46:6 50:7 50:17 51:2 51:4 58:21 59:8 60:8 64:10 65:4 65:6 65:12 65:22 68:4 68:18 68:23 70:23 81:9 87:7 87:11 94:5 96:18 98:7 98:10 99:15 101:13 104:9 104:12 104:25 105:9 113:15 114:9 115:20 123:22 127:1 132:19 133:4 133:6 133:12 133:13 135:3 135:21 136:5 136:9 136:15 136:17 136:23 136:24 137:1 137:4 137:7 137:11 137:15 137:22 138:15 138:17 139:23 140:13 140:21 141:6 141:9 141:16 141:21 141:24 147:1 160:25 161:19 162:6 162:8 162:10 162:10 162:13 162:24 167:10 187:1 187:4 187:13 188:16 189:16 189:24 190:7 190:14 190:18 191:6 191:7 191:8 191:11 191:20 191:21 192:7 192:9 192:10 192:12 192:13 192:22 192:23 193:3 193:12 193:16 194:16 194:23 200:23 202:4 203:11 203:14 203:19 206:13 208:2 208:25 214:24 230:21 232:23 235:1 235:21 236:18 236:19 236:25 237:6 237:15 237:16 237:17 252:25 275:18 282:3 296:6 296:20 297:9 297:10 297:13 300:5 301:6 304:2 305:1 305:18 305:20 306:9 306:10 306:13 307:21FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 338

313:20 animal's 194:14 Animals 136:12 140:6 164:17 311:24 animal-to 145:12 animal-to-human 150:15 155:21 announced 222:24 223:1 annual 170:10 171:14 269:2 285:11 285:21 annually 261:19 ANOVAs 62:4 62:8 answer35:22 50:4 66:7 66:18 79:13 188:13 282:21 291:15 291:18 292:1 321:1 answered9:12 321:17 answers 188:14 188:21 anterior 38:12 109:18 115:2 115:17 115:18 122:9 anti 17:3antibodyforming131:9 131:16 anticipated

285:6 285:14 anticipating 303:18 anticipation 277:6 anxious 268:19 anyone 70:19 239:1 245:13 251:23 276:16 anything8:24 9:11 30:22 31:5 52:23 53:5 197:6 205:2 213:9 226:18 226:19 232:21 278:23 293:10 322:6 anyway271:22 anywhere 45:11 110:16 242:19 apart 52:1 apologize 183:4 271:19 292:24 apparent38:18 39:12 101:25 appear83:22 125:19 166:14 182:18 184:8 306:3 appearance 101:7 125:11 129:15 167:10 appeared300:9 appearing300:18 appears 85:13 117:3 117:5 119:21 128:12 162:16 166:21 182:15 216:25 279:5 279:10 appendices 276:25 Appendix 272:22 272:25 applaud

222:20 applicability 223:20 269:18 applicable 242:18 application 213:2 256:16 278:19 applications 256:17 applied

2:21 5:6 176:15 213:3 235:16 251:25 apply 175:15 204:10 204:13 204:15 213:13 250:4 applying126:15 216:16 251:23 252:19 appointment91:11 appreciate 8:21 148:1 156:5 217:7 251:1 252:7 268:11 278:9 281:2 appreciated

217:8 appreciation 75:22 approach11:19 61:15 95:5 97:5 97:14 101:15 103:11 105:9 106:1 110:7 115:5 142:2 144:22FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 339

145:15 161:11 168:20 181:20 184:10 202:3 221:25 231:21 240:21 247:12 249:12 273:12 315:9 approaches 100:7 100:17 138:23 153:7 168:16 178:9 181:19 182:20 183:1 183:14 183:22 184:7 appropriate 77:3 83:13 88:12 175:15 181:15 279:6 282:22 285:12 307:15 308:9 appropriately 235:17 265:15 approval 186:5 approving280:10 approximately 61:6 79:24 82:2 86:15 122:15 125:1 136:24 139:19 140:21 149:6 177:3 244:5 302:11 April 80:12 80:23 83:19 122:1 138:6 169:6 172:13 183:4 221:21 243:4 April's 130:21 aquatic 3:17 214:17 aquifers 216:9 arcuate 109:16 317:25 319:12 area 3:22 4:22 5:17 6:11 12:17 13:9 19:6 43:9 76:13 84:8 100:25 101:3 101:9 101:10 101:22 101:22 102:7 103:17 103:17 103:20 109:10 111:17 111:20 112:2 112:23 113:9 114:18 114:20 115:1 115:5 115:7 115:8 115:11 116:2 116:3 120:4 120:12 120:14 129:22 135:17 141:2 142:10 153:24 163:5 169:17 176:22 177:12 178:5 178:14 180:20 194:5 210:4 222:21 237:15 240:1 246:10 247:20 295:8 316:2 316:4 317:20 318:10 318:19 319:7 319:11 areas 21:2 28:19 47:1 76:4 78:21 79:2 79:2 95:20 168:23 182:8 190:12 195:7 215:4 244:7 249:14 255:1 316:23 arena 226:22 aren't84:9 157:2 186:4 191:15 argue 319:8 argued 112:19 argument112:4 arise 92:5 Arizona 121:15 army 224:12 aromatase 26:3 27:8 27:11 27:15 89:25 187:14 206:1 206:6 206:10 206:14 206:16 206:18 206:24 207:4 207:7 207:9 211:3 211:7 211:18 211:19 211:21 211:24 212:4 212:8 212:18 213:12 213:14 213:17 213:18 arrange 44:12 arranged217:18 arrival 314:2 arrive 288:11 article 275:2 275:7FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 340

artifact194:8 artificial 150:3 artificially 280:4 ascending119:21 aside 87:11 aspect84:15 88:8 111:21 112:22 117:7 119:19 aspects 75:2 75:19 78:25 86:3 100:15 100:20 assess 17:14 17:17 22:8 29:10 29:12 40:24 49:24 165:24 259:14 assessed29:23 49:20 assessing29:19 282:19 assessment5:10 5:18 6:3 6:17 17:10 52:25 57:15 59:20 63:17 71:13 71:15 71:16 71:21 76:9 76:11 79:25 80:17 85:19 93:23 95:12 95:17 100:9 101:3 145:1 166:23 167:7 176:13 219:21 229:5 239:6 286:17 286:18 assessments 77:6 100:18 167:15 assessors 71:6 assigned311:24 associate 3:10 5:4 5:25 28:12 91:8 associated

80:9 112:17 161:13 164:1 195:1 200:8 204:16 206:3 219:23 229:23 241:25 245:8 252:25 265:16 275:22 282:19 304:24 Associates 77:7 91:23 239:25 240:8 240:16 association 198:24 217:13 217:20 217:21 218:4 218:5 218:9 251:16 268:1 268:10 associations 255:6 assume 44:8 295:3 321:20 assuming59:25 292:2 292:5 assumption102:1 assurance 71:2 assure 227:8 248:11 asterisks 304:18 Atlanta 2:21 atrazine 2:8 13:7 14:4 24:11 24:12 24:24 25:2 26:16 27:7 28:22 28:23 29:3 29:8 29:14 31:25 32:6 34:11 35:8 35:18 35:24 36:15 36:18 36:21 37:4 37:5 37:14 37:18 37:18 37:20 37:23 41:18 42:8 42:15 43:1 45:9 48:10 50:21 53:21 54:2 58:5 61:7 63:6 63:12 63:15 64:2 68:2 69:18 71:21 71:21 72:5 72:14 74:7 75:20 75:25 76:11 76:16 77:2 77:16 79:24 83:22 84:18 84:21 85:4 86:1 86:10 86:23 87:6 87:12 88:15 89:1 91:16 94:13 94:19 95:7 95:15 96:4 96:10 97:25 98:3 98:19 98:24 102:16 102:20 103:7 103:8 105:1 105:16 106:5 121:17 122:22 122:24 123:3 123:9 123:11 123:17 123:23 124:1 124:4 124:7 124:10 124:16 125:8 125:10 125:25 126:3FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 341

126:18 127:2 127:4 127:8 127:16 127:19 127:21 128:1 128:2 128:13 128:14 128:16 128:19 129:21 130:4 130:14 130:17 130:20 131:23 132:2 132:12 132:24 133:4 133:5 133:15 133:19 133:21 134:3 134:6 134:16 134:20 134:21 134:25 135:3 135:13 135:22 135:24 136:2 136:11 137:5 137:9 137:12 137:15 137:17 137:19 137:20 137:23 138:11 138:12 139:2 139:6 139:8 140:2 140:18 140:23 141:8 141:22 141:25 142:3 142:4 142:7 142:11 142:14 142:16 142:21 142:25 143:4 143:4 143:6 144:10 144:21 145:21 146:4 146:15 146:21 147:13 147:23 148:13 148:14 148:17 148:19 149:3 149:12 149:24 150:3 150:9 150:12 150:17 150:17 150:23 151:19 152:17 152:21 153:18 153:21 154:8 154:12 154:15 154:18 154:19 155:2 155:6 155:14 158:11 162:24 163:1 163:10 163:13 164:2 164:9 164:13 165:14 165:24 166:6 166:7 166:11 166:16 166:18 167:7 167:8 167:9 167:14 167:21 168:11 168:23 169:5 169:7 169:12 170:3 170:8 170:11 174:20 175:5 175:14 176:17 177:10 180:5 182:14 183:7 185:22 186:2 186:10 186:18 186:21 187:12 187:14 187:22 188:3 189:23 190:25 191:8 192:7 194:13 195:1 195:7 195:13 197:14 197:20 197:22 198:1 198:6 198:21 199:4 199:16 200:3 200:16 201:7 201:14 201:23 202:4 202:8 202:14 202:19 202:22 203:2 203:7 203:17 203:22 204:9 204:10 204:13 204:13 204:16 204:20 205:22 206:1 206:5 206:24 207:3 207:7 207:9 207:22 208:2 208:8 208:13 208:17 208:20 208:25 209:4 209:7 210:1 210:18 210:24 211:2 211:6 211:9 211:17 211:23 213:11 213:15 213:23 215:11 215:13 215:15 215:17 216:3 216:4 216:8 216:16 218:14 219:16 219:23 220:6 220:14 223:14 224:22 224:24 225:24 226:8 226:18 230:18 239:6 241:5 243:14 243:22 244:1 244:20 245:1 245:4 245:8 246:24 247:9 247:24 248:25 251:20 252:1 252:16 252:23 253:6 254:13 254:16 254:24FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 342

255:1 256:1 256:17 257:3 257:14 257:17 258:7 260:25 261:11 261:14 261:20 262:23 264:14 264:18 264:23 266:5 266:14 268:17 268:23 269:10 269:12 269:16 270:19 273:20 273:21 274:1 274:6 275:7 276:4 276:12 276:18 278:6 279:7 279:12 279:15 279:19 280:1 280:10 280:20 283:20 284:22 285:11 285:20 285:24 286:2 286:11 286:20 286:24 287:3 287:8 293:10 293:12 294:25 295:13 295:24 298:20 299:23 301:2 301:5 301:16 301:19 301:23 302:1 302:6 302:18 305:13 305:19 305:20 305:25 306:3 306:17 306:18 307:9 307:16 309:7 311:15 atrazine-atrazine 26:18 28:5 29:4 45:22 atrazineatrazine-exposed 27:7 atrazine-dosed 305:4atrazineexposed

26:17 201:20 203:19 206:12 atrazine's 133:23 220:1 261:13 269:1 280:17atrazinetreated

27:22 58:22 132:25 190:6 190:14 192:12 305:24 ATSDR6:17 70:2 attached272:25 attained147:4 attempt82:12 attempting87:3 attempts 191:8 313:5 attended196:6 attention 33:5 41:16 93:14 94:10 95:16 99:9 149:21 239:19 251:2 attenuating 298:20 attenuation 13:8 299:7 AUC 149:5 149:8 149:12 audience 168:6 audiences 204:19 audit 229:19 232:19 auditing233:12 August220:23 269:20 269:25 Augustine 20:18 Austin198:15 216:19 author198:16 authors 197:10 275:11 authorship315:7 automatically 101:7 104:5 availability 281:24 available 7:4 7:9 14:6 34:23 34:24 103:22 145:17 158:3 175:24 178:7 179:5 181:16 186:1 189:4 196:4 202:24 220:13 220:17 222:18 229:20 262:24 263:23 268:4 285:9 average 12:9 12:19 18:17 34:4 34:4 52:6 107:23 170:10 182:12 285:11 285:21 averages 78:9FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 343

171:14 averaging169:4 181:19 297:6 Avery 195:20 AVP 319:9 AVPV 317:20 318:5 aware 81:19 111:5 167:14 260:2 away 225:7 254:7 263:8 263:22 264:23 266:6 266:6 280:7 304:12 awful 174:10 179:1 230:16 axes 204:8 axioms 113:3 axis 5:14 13:6 13:7 46:15 82:18 84:11 84:12 86:4 90:3 90:4 93:9 98:14 98:16 102:11 102:12 107:6 121:2 121:23 122:5 123:10 124:2 125:23 126:3 126:4 126:6 126:7 126:8 126:8 126:18 126:19 126:21 128:8 128:16 128:18 128:19 128:23 133:23 134:3 134:4 134:5 134:8 134:12 134:12 134:15 134:21 134:23 134:25 138:1 138:2 148:7 148:11 150:20 150:21 301:16

B background

5:9 7:5 7:19 39:1 58:16 58:18 75:16 77:10 192:3 192:5 228:21 240:9 241:6 275:16 316:24 bacterial 241:23 bacteriological 241:12 bad120:21 badly 241:20 bag121:18 Bailar6:4 6:4 53:8 53:9 54:6 Bailey6:21 6:22 6:23 277:10 277:11 Baker 178:6 178:11 balance 5:14 balanced270:20 Baldwin 259:6 ban 268:23 bar 260:10 260:15 barbiturate 112:8 112:10 116:25barbiturateblocked 160:19 Barry 4:14 4:14 41:8 bars 98:17 98:25 135:15 236:16 296:5 basal 108:5 base 28:6 57:11 based22:13 45:3 54:17 60:22 60:23 62:22 63:17 65:7 69:3 69:10 91:14 94:4 94:10 96:23 113:4 119:13 122:11 125:21 131:11 140:3 145:16 151:22 164:5 178:14 181:16 182:3 182:16 195:7 196:1 219:3 220:13 220:16 223:2 232:17 265:9 265:11 287:1 287:12 287:24 295:4 baseline 140:11 basic 76:4 76:18 77:2 78:15 78:17 79:1 83:16 121:13 231:15 239:3 248:16 basically 100:25 121:22 131:6 137:1 139:17 242:4 309:7FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 344

basing60:18 basis 32:8 50:20 57:14 83:14 87:24 180:14 220:3 229:21 286:22 Baskin5:5 bear 143:13 bearing241:3 beautiful 119:24 beauty45:25 became 28:9 101:25 141:10 161:20 188:16 298:7 298:9 become 87:24 188:18 188:19 263:12 becomes 205:23 261:3 305:14 beef 264:9 begin 2:17 125:9 312:14 beginning18:3 18:4 86:10 135:25 220:24 237:10 311:1 begun 136:2 behalf 75:21 185:11 217:22 226:22 226:23 226:25 262:18 268:13 271:18 277:3 278:5 behave 179:15 179:20 179:21 180:10 180:11 behaved

191:18 behavior 31:6 41:22 42:1 42:21 150:9 154:4 178:2 178:3 190:1 190:19 192:4 206:21 behaviors 193:14 194:3 behind 143:10 156:14 182:20 267:13 310:21 Belgium

201:1 believe 73:21 74:25 82:2 83:19 87:8 87:23 87:25 89:12 89:18 90:5 134:21 143:10 157:4 167:24 176:6 218:16 224:2 225:12 244:5 251:8 261:1 266:2 273:11 273:14 282:21 292:6 293:4 293:13 293:23 294:20 298:4 307:4 309:15 309:17 313:9 314:5 315:6 315:8 320:22 321:6 believed39:22 believes 286:16 bench 16:25 benchmark 88:13 274:3 benefit262:17 264:1 benefits 259:11 259:19 259:25 260:4 260:24 261:1 278:5 280:17 besides 38:10 227:8 258:3 best17:17 17:24 30:3 55:1 59:24 147:11 171:16 220:17 222:17 226:8 235:18 253:8 255:22 256:4 256:23 257:5 266:24 283:6 283:12 284:1 285:9 316:10 316:10 best-looking 17:15 Bette 5:7 5:7 better45:9 118:25 125:6 144:24 151:23 169:18 178:25 233:16 239:8 239:9 246:9 256:23 257:24 258:24 265:19 312:20 beyond 63:14 85:2 166:6 170:12 227:10 270:18 bias 57:2 bigger179:13FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 345

biggest205:18 billion 32:12 32:14 53:20 53:22 175:8 253:20 269:3 285:11 285:22 billion-dollar 254:19 binding211:11 biological 161:16 214:7 214:11 265:4 biologists 20:2 20:4 biology4:5 4:12 71:16 229:12 biomonitoring 32:2 biostatistician 2:21 biphasic 11:3 birds 199:12 252:13 Birnbaum's 25:22 Biro 15:7 birth 25:16 29:24 41:21 42:5 42:11 42:19 43:6 43:12 94:24 births 165:2 bit7:7 10:4 35:23 80:20 124:19 138:25 156:14 175:12 185:21 218:11 220:9 229:18 229:23 231:16 234:21 237:12 240:9 241:6 247:15 249:15 252:8 303:6 303:24 black 15:10 147:6 blend246:5 blinded

100:13 blinders 247:9 blindly95:24 block 30:2 46:8 62:6 62:7 112:12 115:9 231:22 231:23 231:24 231:24 232:1 232:5 232:20 232:22 232:23 233:2 233:17 233:17 233:19 234:1 236:20 237:14 237:15 237:16 237:21 238:6 239:12 blocked

112:7 116:24 160:21 blocker 213:14 213:18 blocking133:24 blocks 29:25 32:23 212:4 232:1 232:2 232:3 232:7 232:11 232:13 232:23 233:25 237:22 237:23 blood12:1 86:11 107:21 110:9 111:3 116:20 187:23 193:3 193:7 296:21 blow190:8 194:22 194:22 blowup129:22 blue 31:10 135:15 149:1 150:19 blunted

301:20 BMD 272:1 274:7 BNST 294:12 Board-certified 36:4 Bob 121:13 318:1 bodies 111:14 111:14 169:13 179:9 179:11 179:12 179:19 180:12 294:4 316:3 body 15:4 15:11 24:15 24:15 24:16 24:19 24:21 28:7 28:7 30:21 30:23 36:14 36:16 36:19 36:20 37:1 37:9 37:11 37:15 39:11 42:12 45:4 60:23 62:11 69:10 93:3 94:3 94:5 94:14 94:19 95:5 98:12 98:14 98:17 98:20 98:23 99:1FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 346

99:3 99:5 131:10 131:12 131:16 131:19 132:14 137:6 140:5 142:19 147:5 152:8 152:13 153:7 179:16 179:21 192:20 195:17 203:8 203:12 237:24 247:25 255:24 304:17 305:15 306:12 307:23 308:3 308:20 309:3 309:8 309:23 bolster 278:23 bolus 86:23 139:5 162:23 166:16 book 15:1 bootstrap 173:2 184:10 bootstrapping 182:25 boring110:3 born 96:9 102:15 104:25 105:18 105:24 106:3 164:23 165:8 bothered197:2 bottom 21:10 36:10 36:11 83:3 83:10 164:14 192:14 192:24 193:5 193:8 236:11 236:17 238:10 242:10 246:21 275:16 box186:21 boxed95:20 Bradbury 8:12 8:16 74:9 Bradford198:15 216:19 Bradford-Hill 198:16 Brady 195:24 196:3 brain 46:23 50:16 84:8 109:11 110:18 111:17 113:12 115:11 118:4 118:5 118:12 294:12 311:20 316:23 317:19 319:9 319:10 brains 193:13 branch13:20 21:22 21:22 52:23 branches 19:20 21:18 branching19:1 19:4 19:22 21:15 27:17 33:22 33:23 34:12 38:7 43:10 43:11 43:16 92:17 92:24 Brazil 201:11 BrdU22:18 27:18 27:22 100:10 104:15 break 69:25 73:17 73:25 75:5 227:22 breaking75:7 breast14:13 14:14 14:17 14:19 14:22 14:23 15:6 15:10 15:11 15:14 15:15 24:9 39:24 79:1 80:6 82:8 82:14 210:7 210:25 211:17 211:20 212:3 212:12 213:12 213:14 295:23 320:22 breasts 39:17 39:19 Breckenridge 79:7 79:17 79:20 79:22 90:13 90:25 106:12 106:14 121:7 121:8 137:25 143:9 143:16 143:18 143:21 144:3 156:4 156:13 157:4 293:15 300:22 300:24 300:25 302:21 302:23 302:24 311:5 311:12 311:16 320:17 320:19 321:4 321:20 321:23 bred29:21 30:25 31:21 39:12FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 347

breed31:1 68:25 164:19 breeders 164:20 164:21 breeding201:21 Bridges 218:10 258:18 259:1 259:5 267:20 brief 31:18 31:19 80:21 93:15 228:20 268:6 287:25 briefly2:14 6:19 9:5 91:24 100:18 199:10 bright235:2 235:6 235:13 278:16 278:17 bring29:7 37:13 41:16 41:25 74:17 94:10 95:15 162:21 234:19 290:7 322:3 bringing13:17 303:1 broad262:5 broke 29:16 broken97:17 brought33:5 60:21 71:14 73:14 128:5 156:6 232:24 Browner 219:15 Bucher3:9 3:9 buckets 204:22 bud18:23 18:24 19:10 39:15 40:5 79:1 80:6 82:8 82:14 101:5 101:23 102:23 103:7 103:13 103:25 104:6 104:17 105:3 105:5 105:10 307:24 320:23 budding19:1 19:12 19:22 22:17 43:5 Budget272:15 buds 19:7 19:20 22:16 22:22 22:23 22:25 23:2 23:5 23:8 30:16 30:18 40:12 52:22 52:22 53:2 68:17 68:22 97:20 103:3 105:7 306:18 307:8 307:18 buffer256:22 Bufonidae 199:7 build153:3 Building65:1 bulk 148:14 bullets 236:12 burden226:20 Bureau277:14 277:18 277:22 277:24 278:4 280:22 Bureaus 218:25 bursting194:15 Bush 219:19 222:14 business 251:24 267:1 busy 8:9 byproduct 244:17 244:21 245:3 245:16 byproduct-related 243:10 byproducts 241:15 242:1 242:17 242:25 243:1

C caffeine 20:6 cage 26:8 26:12 26:13 312:23 cages 25:16 42:4 caiman201:5 202:7 calculate 146:17 152:8 155:18 calculated 87:25 140:2 164:19 calculating101:9 calculations 175:18 179:17 calibration 182:17 California3:16 5:3 5:12 5:22 71:14 91:4FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 348

204:10 205:1 205:5 205:9 205:16 campaign 279:5 279:9 279:15 Canada3:25 5:9 75:14 cancer2:20 6:1 14:13 14:15 14:15 14:17 14:19 14:22 15:15 20:10 24:10 39:24 91:11 167:6 207:6 209:3 209:11 209:15 209:16 209:22 210:4 210:8 210:25 211:17 211:20 212:3 212:13 213:13 213:14 215:10 219:16 220:15 cancers 209:12 212:12 213:25 candidate 43:19 candy 318:1 320:10 cannibalism

25:19 98:10 cannibalize 312:14 cannulated

132:7 cannulation 132:12 canula123:5 capable 189:13 capacities 227:5 capacity 74:12 88:5 88:9 158:12 160:6 161:16 162:3 219:6 227:6 capsule 136:21 capture 100:20 101:10 105:10 123:5 140:10 140:11 carbon243:19 243:20 245:13 246:7 246:12 248:4 248:9 248:13 264:16 280:20 carbon-neutral 264:13 carcinogen23:4 23:7 40:9 211:24 carcinogenesis 4:16 carcinogenicity 88:16 carcinogens 40:11 care 6:1 25:24 66:22 223:10 245:7 cared252:6 career75:18 106:25 258:24 259:9 careers 249:23 careful 143:3 173:23 carefully 95:10 204:7 250:10 Carey 3:3 3:4 59:4 59:14 59:18 59:21 60:15 61:1 61:5 61:9 61:12 62:1 62:13 Carlo-style 315:9 Carmine 16:16 Carnoy's 16:12 Carol 219:15 Carolina 6:10 32:3 53:16 carried

26:4 68:4 70:20 carry 280:5 carryover 308:2 cars 254:2 cartoon 82:23 85:25 case 26:19 38:8 49:22 60:2 97:7 110:11 112:10 113:24 114:4 115:12 115:14 129:14 135:5 135:6 135:9 148:19 160:22 161:10 163:19 180:18 192:20 199:19 201:1 208:3 209:3 215:1 215:5 215:21 219:18 226:15 226:19 234:22 250:1 279:7FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 349

284:22 302:7 322:2 case-by180:17 249:25 case-by-case 181:13 cases 37:8 118:10 135:17 174:3 178:15 189:17 209:19 263:24 286:8 castrate 204:20 204:22 castration191:1 catch 27:24 80:23 304:14 catecholamine 316:25 catecholaminergic 316:25 categorize 262:14 category 17:25 180:16CaucasianAmericans 214:3 214:6 caudal 109:24 caudally 109:12 causation 199:1 204:2 209:24 cause 14:17 30:10 34:8 36:15 42:10 42:16 50:22 50:25 63:22 122:19 198:17 210:1 215:15 219:16 220:15 245:15 caused 31:20 44:25 45:10 275:6 279:14 causes 42:14 42:15 117:24 163:4 203:3 206:2 215:11 247:16 caution 265:13 265:14 265:17 265:24 cautious 267:5 caveats 274:21 CDC 70:2 70:25 71:1 cell 4:12 111:14 111:14 131:9 131:9 131:16 206:23 207:3 207:6 207:11 210:20 211:2 211:17 214:16 217:2 316:3 cells 92:5 104:3 104:4 111:14 111:16 159:23 211:17 211:23 212:5 294:8 cellular 13:20 129:3 190:15 200:21 center3:6 4:11 4:15 4:25 20:10 39:25 91:11 107:18 158:10 229:10 229:11 271:15 271:19 277:3 289:22 centers 39:25 282:1 287:5 317:4 centile 77:22 173:5 177:20 centiles 171:3 183:9 central 218:5 centrally 134:22 certain 56:1 81:14 95:21 230:9 233:8 260:23 261:1 261:1 261:2 262:24 263:22 272:8 274:23 291:21 291:21 291:22 certainly 60:9 112:5 112:20 119:16 128:16 196:3 218:12 218:13 218:20 219:9 221:1 223:5 223:8 225:3 264:1 264:3 300:12 301:8 307:3 certainty 219:20 219:22 260:19 260:20 261:5 261:5 261:23 264:5 266:18FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 350

cessation 124:5 124:12 124:15 134:7 154:12 Cesta 48:14 cetera175:3 c-fos 124:13 c-Fos 123:18 123:21 123:25 129:3 129:7 c-Fos-positive 129:23 Chair 2:11 5:20 240:6 chaired

71:12 Chairman 75:12 91:1 143:9 156:4 184:14 218:1 228:19 251:16 challenge 31:4 49:1 263:3 challenged

48:2 225:19 263:13 278:15 Chambers 2:23 2:23 57:20 57:21 58:9 58:23 chance 185:7 291:3 294:4 312:20 322:18 322:19 change 28:21 30:20 30:21 31:5 31:7 37:10 45:1 69:11 98:12 98:14 98:18 99:1 99:3 100:21 125:9 150:9 158:21 159:25 204:8 220:22 229:21 230:20 239:17 253:18 265:22 304:18 309:3 309:23 changed

26:7 130:16 130:20 216:9 changes 24:7 24:15 24:15 24:16 27:8 28:25 29:22 31:20 33:24 39:3 39:8 39:9 39:9 67:15 68:11 80:20 83:25 93:9 97:3 97:5 100:3 101:11 101:14 101:21 107:16 125:15 127:12 127:13 128:4 128:11 134:12 158:24 159:3 171:17 229:24 241:3 316:17 changing45:7 47:11 47:12 134:15 241:2 242:11 242:12 242:17 246:22 246:22 250:14 characteristics 20:23 84:4 86:7 125:9 125:14 174:22 202:13 characterization 90:10 183:16 240:14 characterize 144:9 144:24 146:14 147:12 168:24 220:24 characterized 82:2 85:11 100:25 110:14 168:14 169:19 191:20 318:2 characterizes 20:21 characterizing 84:3 87:12 173:11 charge 8:22 27:19 51:14 74:19 76:8 76:10 82:5 158:13 196:7 260:2 260:3 262:20 262:21 262:21 273:5 273:14 286:10 289:9 289:16 322:16 322:23 charges 272:19 273:2 282:16 287:7 Charles 25:5 79:20 79:22 90:25 106:14 121:8 137:24 143:9 143:16 143:21 144:3 156:4 156:13 293:14 293:15 300:24 300:25 302:23 302:23 311:5 311:12FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 351

311:16 320:19 321:4 321:23 Charlottesville 5:17 chart 32:20 236:14 243:16 cheaper 245:25 check 71:2 282:24 307:3 checking9:7 checkout268:16 chemical 4:23 40:11 178:2 179:5 183:25 190:25 212:7 chemically204:20 204:22 chemicals 24:5 215:5 chemist75:17 chemistry 104:11 175:24 chemograph 81:23 168:16 169:1 175:10 176:5 178:9 178:17 179:7 179:8 180:1 183:23 184:1 CHESTER

10:6 10:10 10:15 10:22 10:25 11:11 11:15 11:18 12:3 12:12 12:20 13:10 chiasm 109:10 116:1 116:5 317:21 318:5 Chicago 6:5 268:23 Chief 251:15 children 216:11 chlorinated 144:10 152:17 chlorine 245:15 chlorine-base 246:14 chlorines 248:14 chloroform

16:13 chlorotriazine 24:24 53:21 70:11 70:13 89:16 chlorotriazines 139:9 choice 212:3 248:13 choose 266:12 chose 25:9 221:25 259:23 chosen71:18 chromatography 130:9 chromosome 189:7 chromosomes 188:12 chronic 137:12 142:16 301:23 chronological 213:10 churning221:16 Cincinnati 4:3 15:8 40:1 circadian 114:19 circuits 46:25 50:16 circulated 268:4 274:16 circulating 206:20 circulation 109:22 110:12 113:9 circumstances 176:10 284:11 cited162:4 cites 274:7 citrus 218:21 claims 221:1 279:10 clarification 7:23 9:12 13:3 13:14 44:3 51:18 57:22 74:19 143:25 288:21 289:5 303:6 304:17 321:11 clarify54:12 clarifying8:20 clarity80:16 class 200:3 212:9 267:8 classes 186:3 200:1 201:16 207:9 209:2 215:6FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 352

classic 47:22 classical 112:6 318:9 318:17 318:19 classified

103:24 clawed 186:18 187:21 188:10 191:1 200:21 202:2 clean 265:12 cleaned

54:23 cleaner 118:18 clear 9:16 12:23 16:23 41:12 61:17 61:17 62:6 63:24 64:8 68:9 186:9 226:6 226:7 235:14 245:5 273:9 304:22 clearance 146:18 clearly83:8 116:21 119:3 119:5 167:4 280:18 301:4 308:14 clears 16:20 cleverer 178:21 Clewell 144:13 Cliff 20:5 clinical 6:17 Clinton 219:14 222:15 clitoral 202:7 clock 114:18 120:9 317:10 close 57:18 81:10 232:17 285:18 288:3 288:5 288:12 289:1 321:22 322:4 closed 65:3 closely139:11 141:25 142:6 closing265:8 322:20 closure 73:19 clothe 277:25 cloudy257:13 Cluster 241:15 Cmax 149:5 149:8 149:12 coalition 218:19 coat16:25 coauthor 200:25 207:20 275:1 coauthored 207:2 211:5 coauthors 186:4 186:13 201:12 203:1 Coder 309:16 309:17 310:14 310:16 310:18 310:18 311:17 311:18 311:23 313:8 313:15 313:25 314:6 314:9 coding234:21 coefficient20:14 152:24 coefficients 146:2 151:25 152:8 coffee 264:10 Cohort135:23 cold271:20 Coleman's 118:14 319:15 collaboration 121:20 144:11 195:8 collaborative 91:19 colleague 201:4 202:5 207:19 207:24 318:2 colleagues 114:1 116:17 144:12 168:5 185:13 199:10 200:15 207:14 208:9 208:14 259:17 289:25 319:7 collect147:16 174:3 175:1 284:2 collected 147:15 147:18 150:5 293:17 293:19 collection17:3 246:19 collections 239:10 collective 281:25FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 353

College 2:24 121:15 171:25 175:23 259:6 colony293:25 Colorado 4:7 87:20 colored

236:16 Columbia 203:21 204:17 column176:23 233:14 columns 233:3 233:5 233:12 233:14 combination 48:21 263:2 315:7 combine 253:12 296:23 297:19 combined209:12 297:3 comes 56:5 179:14 197:2 205:9 243:11 243:25 261:23 297:18 322:14 comfortable 71:8 coming25:15 51:25 58:14 58:18 70:17 168:3 248:14 249:5 268:2 291:11 292:15 300:4 304:7 commended230:24 comment7:6 7:24 7:25 8:4 13:16 45:7 46:3 46:11 47:6 50:12 73:20 74:21 157:13 177:16 184:21 184:23 224:11 228:14 268:3 271:3 274:16 277:8 281:15 288:14 302:16 302:20 306:8 307:20 320:16 320:18 322:13 322:17 322:22 commented227:4 commenter 74:22 185:10 217:11 217:17 267:23 271:14 commenters 156:18 156:21 157:8 277:6 288:15 288:22 289:8 290:25 commenting271:18 comments 8:14 73:15 73:22 90:15 156:23 171:12 218:10 221:18 225:22 225:23 268:3 268:13 271:23 272:22 272:23 272:24 272:25 273:15 274:10 275:16 281:3 287:6 287:21 287:24 287:25 288:20 289:1 commercial 240:19 committed78:20 Committee 218:2 221:19 228:20 commodities 218:20 218:22 commodity 255:6 255:9 common14:15 70:5 89:14 commonly 179:5 261:11 261:21 communications 196:3 communities 214:9 242:19 243:5 243:8 245:9 268:21 279:24 community 168:13 168:24 169:14 169:20 170:3 170:4 170:9 171:1 171:2 171:22 172:3 172:8 173:12 173:16 173:20 174:24 175:13 180:8 181:4 181:25 183:15 213:24 218:6 227:1 243:17 243:18 244:6 265:23 283:22 284:9 284:13 284:18 285:25 287:5 291:19 292:2 compact57:18 compaction257:23FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 354

companies 281:17 company78:19 209:13 209:16 209:18 209:22 213:23 comparable 66:9 87:11 98:23 101:21 147:3 150:25 151:6 154:17 172:24 compare 24:22 47:24 57:25 139:14 154:2 232:24 307:15 compared22:23 46:6 62:9 102:16 129:24 150:11 191:7 232:22 238:13 245:2 276:9 297:15 302:3 305:4 309:8 comparing 237:11 307:12 307:14 comparison 47:21 48:7 62:8 79:3 150:15 154:1 167:20 232:22 304:25 305:2 307:17 308:6 308:9 compartments 48:20 97:18 146:4 compelling118:10 220:8 compensate 68:12 compete 253:4 competence 62:22 competing 261:25 262:1 competitiveness 278:14 complement70:4 161:3 254:17 316:17 complete 115:15 190:25 201:8 208:7 209:1 217:3 273:9 312:1 completed85:19 131:3 259:24 280:9 280:10 288:14 completely193:23 193:24 233:11 308:23 completing78:25 complex146:24 174:2 230:16 269:24 complexity81:15 compliance 240:25 255:1 255:3 256:1 compliant312:8 complicated

53:14 113:25 139:16 246:18 270:10 complicates 237:12 complication 236:1 component21:7 108:16 108:25 109:1 109:9 143:12 157:14 280:21 components 21:8 63:20 107:16 215:2 composite 110:2 172:22 compound50:22 69:6 70:22 71:22 79:25 84:23 100:4 304:3 compounds 17:4 24:10 34:2 70:6 71:20 147:21 148:3 148:10 149:10 152:19 155:9 155:19 166:11 comprehensive 76:16 77:20 222:24 259:19 284:23 compressed

280:4 comprising108:5 compromised

95:2 computer 101:8 104:5computergenerated17:7 conceivable 311:20 conceivably56:15 56:21 56:25FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 355

concentrated 92:11 209:13 209:15 209:17 concentration 10:12 60:18 61:6 149:11 152:1 152:12 153:23 154:11 155:13 concentrations 60:19 70:8 148:7 149:3 149:19 149:24 150:23 150:23 150:24 153:21 154:19 154:22 155:4 155:7 155:14 176:17 178:24 182:12 197:22 283:1 283:6 283:9 283:13 296:4 concept20:1 84:10 116:9 178:13 180:20 conception 136:2 137:2 137:16 conceptualize 108:5 109:4 120:16 concern 45:20 210:2 211:19 243:14 245:16 246:20 248:16 248:20 305:23 313:24 concerned182:2 204:24 205:4 242:13 249:7 262:10 270:14 279:25 280:24 concerns 210:3 216:1 242:2 252:9 287:7 conclude 118:6 120:3 307:8 concluded 219:17 220:4 223:19 225:4 283:11 285:10 conclusion15:4 67:24 106:4 143:2 173:3 258:6 295:3 306:24 316:8 conclusions 14:11 81:17 270:4 316:12 conclusory81:20 concomitant39:8 concordant88:20 concurred89:15 condemn 266:16 condition 129:18 139:7 conditions 88:2 129:6 186:23 conduct79:11 80:2 284:19 conducted76:21 78:24 81:1 83:16 84:21 86:8 86:14 87:1 87:10 87:17 89:5 89:6 89:8 91:21 95:14 100:8 144:9 146:7 146:19 149:22 151:17 152:25 154:1 164:12 188:24 219:18 259:20 283:8 310:14 conducting259:18 cone 65:6 confer216:23 confidence 168:11 171:3 171:7 183:8 266:8 270:21 confident77:20 78:4 confidently183:8 confined283:21 286:11 confirm

63:1 confirmed22:1 195:23 221:22 confound138:22 confounded

303:4 confrere 240:3 confused59:8 confusion 33:4 33:14 59:5 61:23 Congress 224:20 Congressional 277:14 277:18 conjugated

89:19 connect292:21 connected84:25 cons 96:20FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 356

consecutive 303:15 consensus 115:13 consequence 88:6 134:15 consequences 131:1 267:5 conservation 256:6 256:21 257:4 257:16 258:10 264:19 264:23 266:2 conservationists 264:22 conservative 265:5 conserve 313:12 consider 31:15 47:5 62:11 139:7 168:25 169:9 169:19 172:9 172:16 173:11 183:23 223:24 248:17 248:21 252:12 260:10 264:6 266:17 266:17 267:3 270:2 270:22 282:17 311:21 considerable 84:2 247:22 considerably 269:13 consideration 69:14 94:3 138:21 223:13 considerations 284:7 considered

28:8 47:3 130:10 249:16 250:9 269:8 280:8 considering178:7 179:7 consistency38:11 52:4 consistency's 55:15 60:12 consistent 16:10 17:10 18:16 33:21 53:5 56:1 97:16 98:21 101:21 102:1 152:5 153:19 198:13 199:11 202:12 203:17 214:15 215:5 301:9 308:25 309:14 consistently 33:19 284:17 constant10:13 102:5 113:15 301:4 constants 10:5 145:24 constituents 224:14 226:22 construct110:23 constructed

87:18 315:11 construed274:15 consultant5:16 240:2 consume 264:8 consumed98:4 284:8 286:15 310:24 consumers 253:22 258:9 262:19 264:7 283:23 284:4 consumes 283:17 consuming283:3 consumption 286:14 310:25 contact22:11 22:15 214:9 214:14 contain 148:15 containing100:14 contaminant53:19 284:15 284:18 284:21 285:4 285:17 285:19 286:6 Contaminants 197:17 contaminate 195:11 contaminated 210:24 contamination 195:2 275:2 275:12 276:15 contemporary 317:15 318:16 content211:15 context81:6 81:15 83:9 88:14FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 357

90:6 160:7 181:1 273:2 273:19 274:19 292:10 303:1 318:18 continent200:13 continents 185:25 continually69:18 136:4 continue 80:18 119:21 144:16 219:10 228:9 246:1 304:3 continued136:9 140:14 164:23 164:24 177:4 177:5 177:7 279:12 continuing 78:14 78:16 278:12 continuous 110:3 264:19 303:10 continuum

180:20 contractions 41:21 contralateral 22:3 27:10 contrast90:15 114:11 116:13 117:8 133:17 164:8 contribute 268:15 contributed 169:21 contributing8:1 contributory 86:19 control 13:8 21:10 22:24 26:15 26:18 29:15 29:15 30:13 30:17 31:9 32:16 32:17 33:22 34:3 34:13 36:9 45:21 49:24 50:7 55:3 56:11 57:12 57:12 57:25 58:2 58:24 62:9 80:14 82:21 83:5 94:16 95:25 97:25 100:14 101:13 104:12 108:15 111:10 112:15 116:11 116:12 118:24 123:22 133:8 133:12 154:16 189:21 190:3 190:6 192:9 194:16 236:20 237:25 253:3 254:8 254:20 263:1 263:18 275:3 275:8 275:11 275:18 276:10 276:14 276:15 304:20 305:5 305:7 305:24 306:1 306:13 307:15 309:8 310:9 311:25 315:22 control-dosed 162:6 controlled

98:4 99:22 154:3

154:17 controls 17:14 26:14 26:15 27:24 35:2 35:3 54:24 54:25 55:18 57:24 58:12 59:9 59:16 65:23 65:24 65:24 67:11 102:17 103:9 153:18 190:9 191:7 192:1 207:17 207:23 231:20 232:20 232:22 232:23 233:24 238:6 272:4 275:4 275:9 275:12 276:7 302:4 308:1 310:8 310:12 convened269:21 convenience 320:20 convenient221:13 conventional 256:25 257:15 conversation 73:15 212:15 conversations 25:14 289:14 conversion148:20 155:10 183:3 184:10 187:15 212:19 converted 148:19 155:2FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 358

conveying92:2 convinced234:22 convincing 83:19 265:11 cool 173:8 Cooper76:23 83:24 86:6 230:2 301:9 301:11 301:13 301:25 302:18 302:19 cooperative 196:9 196:24 Cooper's 25:10 90:5 125:24 162:5 304:5 coordinate 74:24 coordinated

92:16 copies 287:21 copulating191:14 191:24 copulations 192:6 Cordova 317:19 core 106:16 corn 217:12 217:20 218:4 218:9 218:20 226:17 226:17 251:15 252:11 253:14 253:19 257:10 261:18 263:1 263:18 264:8 265:6 267:16 268:1 268:10 268:15 268:18 269:2 270:8 279:19 279:20 corpus 108:2 116:7 159:17 correct9:19 9:21 11:10 11:12 12:2 12:12 33:9 33:14 49:7 49:8 49:25 156:14 281:7 306:19 306:20 307:5 311:6 311:11 311:12 321:14 321:24 corrected 234:11 234:15 239:16 correctly 11:8 49:1 49:11 90:1 216:3 234:3 234:9 281:22 correlate 110:10 correlated 15:12 23:3 116:18 correlation 20:14 204:1 209:24 corresponding 96:24 111:11 cort85:11 85:22 86:1 cortex126:12 corticosterone 46:21 46:24 85:5 85:12 126:1 126:13 126:17 126:20 127:10 127:12 127:15 127:18 128:11 128:17 130:3 130:4 130:22 131:2 131:22 132:1 133:14 133:22 302:9 302:10corticotropinreleasing126:9 cortisol 126:13 cost240:24 253:15 253:21 254:20 254:21 268:24 Costa 203:1 251:13 cost-effective 247:6 247:12 248:19 249:6 249:19 253:7 costly263:18 costs 253:12 253:17 263:2 263:7 264:11 count 19:10 52:22 65:8 159:7 191:23 203:23 205:18 counted

101:7 164:24 counterintuitive 119:15 counterpart251:7 counterparts 193:5 counties 205:12 205:13 205:14FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 359

counting20:25 countries 14:25 185:25 country24:6 175:5 214:1 240:19 241:19 242:12 268:16 country's 277:23 County277:21 Coupe 4:24 4:24 171:12 couple 15:3 21:8 46:11 51:17 80:3 99:9 110:22 131:7 168:19 234:24 236:11 294:23 coupled

112:16 112:16 113:6 166:23 319:24 coupling88:22 course 45:16 46:23 80:3 83:17 93:7 107:21 116:23 116:25 120:12 141:5 141:6 147:22 150:19 171:4 172:6 172:12 175:1 204:18 204:24 219:2 222:1 230:1 269:5 289:9 295:5 316:3 Coursey268:22 269:1 courtesy 321:9 Covance 146:8 covariant62:12 94:3 cover 81:25 90:19 274:9 covered

268:7 covering75:2 157:25 Covern80:11 covers 225:20 CRE 273:20 create 181:2 224:3 289:19 created

89:14 credit221:6 creek 174:4 177:2 CRF294:14 CRH126:21 126:21 128:24 294:3 294:4 294:7 294:8 294:9 Cricket197:17 criteria 18:21 54:18 56:16 57:9 57:9 57:11 100:9 101:6 198:16 234:16 235:10 235:15 291:20 critical 15:5 23:24 29:7 41:20 42:1 43:22 46:14 68:14 68:24 88:12 113:6 120:5 167:19 183:17 298:21 321:10 321:21 322:15 critically282:4 criticism 231:10 270:13 critiques 270:3 crocodile 201:5 crocodiles 202:8 Croik 20:18 crop 74:23 261:18 261:19 261:20 279:9 281:18 290:22 CropLife 281:11 281:17 281:17 282:9 282:15 286:16 287:9 cropping175:4 crop-protection 278:7 281:1 281:21 281:25 crops 261:21 263:19 277:20 279:16 282:3 cross 23:16 26:14 270:4 311:10 crossed

26:5 26:19 crosses 269:24 cross-foster 26:2 26:5 26:13 36:8 37:16 45:18 98:8 cross-fostered 26:16 45:23 cross-fosteringFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 360

311:4 cross-section 23:20 Crowley118:19 Cruz 5:3 cumulative 32:9 32:11 63:16 219:21 curious 196:20 current182:23 211:16 220:12 292:6 currently 78:11 91:18 224:25 229:10 243:8 245:20 261:16 270:9 curve 12:17 13:9 135:17 141:3 142:10 148:21 153:24 163:6 235:23 295:9 curves 10:19 146:15 148:5 148:17 cut23:14 cycle 22:14 68:12 88:18 93:25 107:22 107:24 108:4 108:7 108:20 112:15 112:25 113:7 116:13 117:10 118:2 118:6 119:18 121:2 141:12 159:19 163:1 167:9 211:7 234:18 234:21 234:23 238:13 238:21 295:25 296:7 296:10 296:10 296:11 298:23 300:8 301:5 313:21 314:1 319:18 320:6cycledisrupting301:2cycledisruption301:7 cyclers 141:7 141:10 297:4 297:16 297:16 297:19 298:7 298:10 cycles 119:4 139:24 142:23 163:2 297:10 297:10 300:15 313:23 cyclicity 25:5 29:20 38:16 99:17 102:2 115:9 116:6 139:21 142:24 295:25 cycling141:18 141:21 160:20

D D.C 240:1 DACT 32:7 90:4 146:16 147:25 148:14 148:15 148:20 148:20 149:6 149:13 149:20 150:24 153:22 154:10 155:6 155:11 155:14 165:25 daily 44:21 44:21 45:2 45:14 78:6 78:7 78:8 113:5 127:8 127:20 128:10 135:12 147:4 171:20 172:14 172:19 172:22 172:25 175:21 178:19 179:4 180:25 181:20 182:24 183:13 183:25 184:9 249:21 dairy 264:9 dam 25:18 26:6 33:3 33:7 33:15 61:20 61:21 61:25 62:10 93:5 94:23 307:22 312:13 312:18 312:23 312:25 damage 215:11 279:14 damaged

211:23 212:5 dampened248:1 dams 26:19 30:1 32:24 32:25 36:16 36:22 36:24 62:2 62:5 94:16 94:18 95:5 95:6 96:9 98:13 102:15FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 361

105:1 105:19 135:24 Dan 3:14 DANIEL3:13 dark 22:4 190:12 darker98:25 193:17 darkly129:12 129:15 data 9:22 14:21 29:23 32:2 33:3 33:16 41:15 53:15 58:8 58:11 61:13 61:15 61:24 62:3 62:20 66:22 70:24 78:15 81:18 82:1 82:15 88:25 89:3 89:9 106:4 110:2 110:5 118:20 119:3 119:13 119:17 121:25 122:2 122:25 124:3 128:9 130:3 141:19 142:8 144:15 144:19 145:8 145:16 146:1 146:17 147:16 147:16 147:20 148:4 148:5 148:5 148:6 149:7 150:18 152:10 152:11 152:17 152:20 155:22 162:21 163:9 163:20 164:6 164:8 165:6 165:23 166:3 166:13 169:3 169:8 170:21 171:14 172:1 172:13 172:14 172:24 173:13 173:22 174:21 175:2 175:17 175:24 175:24 176:2 176:16 177:14 177:15 177:16 178:8 179:2 179:4 179:4 180:15 181:2 181:16 181:20 182:1 182:17 182:17 183:13 183:25 183:25 184:15 185:5 188:6 195:23 196:4 196:4 196:10 196:15 196:21 196:23 197:4 202:25 203:15 214:23 217:1 220:17 220:20 229:20 230:17 231:2 231:3 231:6 232:9 232:19 233:2 233:2 233:3 233:3 233:4 233:4 233:15 233:17 233:18 234:2 234:4 234:9 234:13 235:11 236:9 251:9 256:12 260:10 266:3 270:15 271:25 272:7 272:12 280:2 280:7 282:23 284:2 285:10 290:21 291:13 292:6 295:7 296:25 297:2 299:5 299:6 299:20 304:6 304:6 309:22 311:3 316:7 316:16 318:4 319:25 320:1 database 62:7 76:17 77:16 168:24 169:6 169:21 169:24 171:11 183:12 243:14 312:9 databases 77:21 Data-collection 285:23 data-gathering 174:9 data-mining 173:23 181:10 181:15 183:16 dataset162:5 172:15 172:17 172:17 datasets 122:2 171:20 175:21 180:25 182:25 184:9 data-specific 67:4 date 44:13 60:1 225:13 226:11 286:20 307:19 dates 313:7 daughter 39:22FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 362

216:6 daughters 96:16 99:20 105:18 105:24 106:3 106:7 David81:1 87:9 144:7 218:10 258:18 258:19 259:1 259:5 Davis 5:22 91:5 91:11 Dawley127:7 131:8 day2:5 7:12 8:20 8:22 16:7 16:11 16:15 16:17 21:11 27:3 30:11 30:15 31:4 31:15 37:9 38:18 42:16 45:2 46:13 46:19 48:5 48:5 50:13 55:12 57:23 62:14 64:21 64:22 64:23 65:4 65:18 65:25 67:9 67:18 72:6 72:7 73:7 73:10 73:11 86:10 86:11 98:1 99:13 99:14 99:16 99:16 99:21 99:25 100:2 102:1 102:13 102:25 103:1 104:14 104:19 105:5 105:21 113:19 113:20 119:9 122:14 125:2 135:25 139:24 143:22 147:5 147:8 156:22 165:15 165:15 172:24 182:9 191:22 191:24 191:25 191:25 192:21 219:10 221:20 227:4 259:4 281:20 292:6 295:24 296:18 296:22 297:5 299:2 310:21 310:22 310:24 311:1 312:1 313:10 days 2:12 8:9 28:3 28:3 28:5 28:24 29:20 29:24 29:24 30:17 38:23 44:16 68:4 68:8 79:18 84:22 84:24 85:8 86:8 86:12 94:17 99:21 107:24 107:25 110:22 113:18 121:3 123:3 123:23 124:6 124:9 124:12 132:6 132:11 132:15 132:17 134:8 134:9 135:8 135:13 136:10 136:23 137:16 138:4 140:7 146:11 146:12 146:12 146:25 146:25 147:1 147:14 147:14 153:15 154:8 154:12 154:17 154:21 154:22 155:8 155:12 155:15 162:25 163:2 176:25 176:25 177:1 177:4 177:5 177:8 177:11 177:23 196:17 264:6 291:22 295:24 297:2 298:16 302:6 303:8 303:19 303:21 313:6 313:9 day's 232:18 DDT 41:7 de 20:18 207:25 208:18 DEA 32:7 147:25 148:17 148:19 149:3 149:13 149:19 151:3 151:15 153:21 155:3 155:6 155:14 165:25 deafferentation 114:22 115:16 deal 72:22 82:15 198:18 249:10 252:18 252:18 253:1 254:13 257:9 dealing218:14 255:17 dealkyated

146:15 dealkylates 147:25 151:2FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 363

dealt 51:20 223:18 243:6 Dean 5:4 dear 15:16 death 14:18 debate 203:4 debris 190:15 200:21 decades 122:24 decapitated

65:7 decapitation 127:4 decapping65:6 December 304:8 decide 18:8 52:15 247:11 250:1 250:22 decided

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55:18 55:18 168:11 183:7 defining168:16 definite 220:3 definitely 47:16 68:21 112:18 210:11 definition264:21 definitions 56:14 57:4 degradation 148:23 150:11 degraded195:14 degree 113:2 240:11 247:18 247:19 266:18 270:21 degrees 240:10 delay 22:20 22:21 27:4 30:11 33:18FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 364

72:13 82:14 96:8 96:11 106:6 159:1 296:21 delayed

27:6 30:13 30:23 35:21 35:24 42:14 42:15 42:16 67:17 125:11 296:7 298:6 298:8 300:6 300:8 delays 39:12 72:5 159:5 164:7 Delclos 4:14 4:14 41:8 deleterious 299:24 deliberation 75:23 289:15 deliberations 79:19 270:11 delineated

174:24 delisted256:1 delisting255:24 deliveries 44:16 delivery 161:21 demand 216:25 demasculinization 187:16 203:18 demasculinized 187:1 188:2 demonstrate 82:14 85:1 85:16 123:20 163:15 demonstrated 108:19 113:13 116:17 160:15 161:9 237:25 307:24 demonstrating 26:23 306:12 densely201:6 density18:25 20:22 20:22 101:9 102:4 103:21 deny 221:3 depart240:4 Department3:5 3:15 4:8 4:12 5:20 6:9 75:13 255:12 310:20 departure 76:25 77:4 229:21 280:15 depend 71:6 268:21 279:24 dependence 64:21 dependent159:8 165:21 207:5 depending16:18 110:15 187:5 187:6 depends 281:24 depicted95:13 158:19 159:10 162:6 163:22 depicting102:24 depiction 92:20 104:1 depleted187:3 depth 90:14 derivation52:20 derivatization 62:14 derived

259:11 descending119:23 descends 287:11 describe 25:25 91:25 97:2 122:21 135:2 136:19 138:6 138:10 149:10 232:4 described86:6 96:12 121:22 127:1 135:20 199:24 215:11 230:15 231:18 238:25 273:10 describing 12:13 239:18 description 21:3 82:9 deserve 247:15 design63:6 77:3 77:6 97:21 99:7 126:25 132:4 135:23 139:16 144:15 151:21 169:1 229:19 230:10 230:15 231:17 232:6 237:21 239:12 303:1 311:4 designate 274:22 Designated

6:19FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 365

6:24 277:10 322:5 designed76:21 87:17 176:14 designs 78:1 destination 221:24 222:1 destroy115:7 destroyed116:3 destruction 202:15 destructor40:9 detail 13:4 175:12 183:3 289:7 detailed32:20 180:2 detectable 103:1 detected104:18 104:20 276:7 detection 284:17 286:3 286:4 detention 247:23 deteriorating 138:20 determination 76:10 220:16 determine 17:15 19:23 24:23 126:2 132:1 132:7 247:5 287:10 297:20 determined

17:5 104:9 152:6 164:21 173:6 220:7 220:14 296:14 develop 39:16 43:3 43:9 184:12 190:2 208:1 210:25 developed32:3 32:19 34:3 55:1 59:24 63:15 87:22 92:23 187:7 207:22 231:1 developing43:4 144:16 190:12 201:3 development14:23 15:10 15:11 15:15 18:22 20:7 22:8 23:17 23:25 24:2 24:8 24:17 25:9 26:22 27:13 27:15 27:25 29:22 30:13 33:18 39:2 39:10 39:15 39:17 39:18 40:6 40:23 43:21 46:22 47:20 51:8 63:12 67:10 67:16 69:9 79:1 80:6 81:3 82:8 82:14 88:18 91:9 91:17 92:1 92:9 92:11 92:15 92:22 93:4 93:7 93:9 93:24 94:9 94:22 96:11 96:21 100:21 101:18 104:18 104:21 105:2 106:7 118:11 145:10 187:18 197:20 197:24 198:6 198:22 215:18 215:22 220:2 220:7 273:3 301:3 308:17 320:23 developmental 14:3 15:6 17:4 20:11 24:25 30:5 30:6 30:10 39:12 72:13 229:4 303:2 303:3 303:12 303:13 310:20 developmentally 50:14 develops 92:4 deviates 269:13 deviations 282:6 devoted

259:10 DIA 32:6 147:25 148:17 149:3 149:13 149:18 149:19 151:3 151:16 153:22 155:3 155:6 155:14 165:25 diagnosed14:14 14:19 diagram

317:3 Dick 20:18 dictate 284:3 286:17FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 366

dictates 116:12 die 214:5 died14:22 diestrus 99:24 99:24 diet139:11 143:5 147:4 149:4 153:19 155:5 163:6 166:18 308:16 308:21 310:23 dietary87:1 140:1 141:24 142:3 142:10 142:24 145:23 146:10 147:1 148:25 149:2 153:24 154:9 155:10 164:9 165:5 167:13 167:15 differ179:8 306:24 difference 44:20 49:5 56:11 67:10 94:25 97:9 97:14 99:2 103:2 103:16 103:19 105:2 105:4 105:13 149:4 149:6 149:11 149:13 149:14 153:17 161:25 162:11 167:11 214:7 214:11 232:8 238:17 257:8 297:6 297:9 298:17 302:3 302:5 304:24 305:23 306:24 307:7 307:18 309:18 313:19 317:9 differences 34:7 46:8 69:4 80:13 80:16 82:20 82:25 106:19 107:2 111:5 148:24 151:1 154:9 155:3 155:21 190:6 191:9 191:11 192:2 248:21 313:22 different21:1 34:2 38:17 38:19 44:22 47:16 48:22 49:5 49:6 53:20 54:13 56:12 59:2 75:2 75:18 92:12 93:2 93:13 98:15 99:3 99:10 100:7 100:16 101:17 102:6 102:10 102:11 104:18 104:21 123:3 130:14 140:2 140:9 141:17 145:4 145:22 145:22 146:4 146:9 146:21 148:8 148:9 148:22 149:10 149:24 150:5 151:9 152:19 153:5 155:5 155:5 155:6 155:20 166:24 166:25 173:4 179:18 180:24 187:25 198:19 202:23 208:23 219:1 222:14 222:15 225:20 227:5 233:9 233:21 237:15 250:25 256:18 260:21 276:10 295:16 297:21 304:19 305:6 305:17 306:17 308:11 309:7 309:20 312:5 314:21 differential 89:24 90:2 differentiate 22:11 differentiated 22:16 113:1 differentiating 152:19 differentiation 43:13 68:16 68:23 112:23 197:15 197:21 199:4 differently 211:13 316:15 differs 148:12 difficult68:7 68:8 109:4 123:12 190:4 240:22 261:4 261:25 263:17 279:2 280:3 302:1 312:10FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 367

digest289:3 dihydrotestostero ne 130:16 dilated

200:20 201:8 dilute 204:21 dilution 174:6 dilutions 233:9 diminished

120:19 187:3 dioxin57:10 direct89:21 203:13 directed222:2 224:12 direction 250:25 directions 219:9 directly 50:4 110:8 128:22 198:13 253:24 316:22 Director 2:19 3:10 8:12 74:11 74:13 195:24 217:12 217:19 218:3 229:11 268:9 277:13 277:17 281:10 disappear 85:13 134:8 disappearance 152:21 155:19 disappeared

37:17 105:25 127:21 128:14 discharge 108:10 110:18 113:8 113:22 113:22 116:22 disciplines 225:21 269:25 270:5 disclosed290:6 disclosure 186:8 230:3 disconnection 115:2 115:3 115:18 discontinue 245:19 245:25 246:5 discontinuous 228:1 discordant51:20 discovered 192:8 200:16 213:11 discrepancies 153:23 discrepancy314:7 discuss 83:8 109:6 discussed34:18 172:7 275:7 discussing 39:20 81:13 81:16 89:9 discussion8:25 80:11 82:19 83:3 83:10 85:18 86:4 86:20 88:10 88:25 96:19 97:17 106:19 250:11 321:5 disease 14:20 50:21 215:16 diseases 253:6 disinfecting 242:25 disinfection 241:13 241:15 241:19 241:24 242:1 242:17 243:1 243:10 244:17 244:21 245:3 245:15 246:14 248:7 dismay280:23 disparities 205:21 display85:9 displayed86:1 161:19 190:19 disregarded

69:11 disrupted161:13 disrupting212:21 disruption197:24 267:14 disruptors 15:5 15:14 dissect193:16 dissected187:4 dissecting17:6 dissipation 146:14 distinguish 177:12FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 368

distinguishable 188:12 distorted282:11 distribute 281:18 distributed

86:24 139:10 154:4 163:1 163:7 163:12 164:9 165:5 165:9 165:11 166:18 232:6 232:10 236:13 236:25 237:22 237:23 277:2 294:14 distribution 29:1 146:4 146:21 168:12 171:5 171:6 171:9 183:10 237:2 276:2 276:8 287:5 292:9 292:16distributionsystem 242:23 distributor 55:13 diurnal 310:9 310:11 310:25 diurnally 310:10 diversity 265:4 divide 90:23 109:8 divider 181:11 dividing27:24 104:3 division 3:5 184:4 DL6 123:8 DMBA-tumor(+ 210:20 DMSO 149:25 DM-W189:6 Docket7:4 7:8 77:7 77:8 103:22 225:10 225:14 231:4 236:10 268:5 271:5 276:24 287:21 314:19 document41:15 61:19 272:1 272:2 274:3 274:8 274:9 274:12 274:18 274:21 274:22 274:23 276:16 276:25 documentation 160:4 documented

280:17 dog251:9 dollars 255:13 255:15 258:9 Don 268:22 Donald 195:24 196:3 done 11:3 12:16 26:23 29:11 32:23 35:15 36:2 36:3 37:2 38:19 41:24 48:10 55:22 56:1 60:14 61:25 62:8 83:20 83:21 86:13 91:13 91:22 94:11 95:3 96:15 96:15 112:13 144:11 146:8 151:21 153:1 163:16 165:10 165:12 166:8 171:17 172:19 175:5 186:1 186:17 194:5 195:4 195:8 200:6 204:8 209:9 212:24 224:6 230:8 230:13 239:10 239:11 240:4 241:18 250:4 273:15 301:15 312:10 donor 150:14 door 65:4 dopaminergic 316:25 dose 11:9 12:2 12:6 12:10 13:7 17:18 24:12 28:13 37:3 37:7 37:20 37:24 42:15 45:3 53:10 54:2 54:4 55:2 56:11 59:10 62:22 63:7 67:11 70:7 85:20 86:20 86:21 87:24 88:2 88:20 98:3 98:5 127:8 131:10 131:12 131:13 131:17 131:17 138:3 140:23 141:2FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 369

141:4 141:7 144:20 145:3 146:11 147:4 148:8 148:12 149:5 149:8 149:12 163:1 163:6 163:7 163:12 164:1 164:9 164:15 165:5 165:9 165:12 166:11 187:5 187:6 207:4 231:22 231:23 231:25 232:6 232:11 232:12 232:24 234:7 236:21 236:22 237:21 237:24 275:22 295:12 295:13 296:5 296:5 299:7 303:7 305:5 311:14 dosed29:18 30:1 32:16 32:25 86:9 94:17 95:6 96:10 97:24 137:1 137:7 146:9 160:25 dose-dependent 199:21 206:6 208:12 208:15 308:13 308:15 dose-group 232:2 232:3 dose-response 63:5 63:8 63:10 63:11 85:19 86:14 139:4 144:24 dose-responsive 133:20 doses 33:19 33:20 33:23 50:22 55:18 60:10 62:21 64:1 86:16 86:18 86:23 86:24 87:2 87:3 87:3 97:25 98:19 118:25 123:3 125:8 125:10 127:2 127:8 127:8 127:8 127:20 127:25 128:2 128:10 130:2 130:2 130:17 134:2 134:10 136:25 138:14 139:25 140:2 140:4 142:18 142:20 144:21 144:23 147:3 148:25 149:9 160:23 163:11 163:21 164:14 165:19 167:19 188:4 199:13 199:21 208:16 301:4 308:12 dosimetrics 153:5 dosimetry 70:19 70:21 dosing37:5 45:1 85:14 94:13 94:18 96:3 139:1 139:10 149:2 149:4 153:17 154:3 155:8 155:10 164:23 166:16 166:18 167:12 231:19 274:3 303:10 303:21 303:23 309:24 dosings 236:3 dots 147:6 292:12 double-blind 20:24 71:17 doubt 10:5 264:11 doubtful 262:3 doubts 239:1 downstream

130:5 dozen 234:15 258:19 280:9 dozens 256:11 Dr 2:4 2:17 2:18 2:23 3:3 3:9 3:13 3:19 3:23 4:2 4:6 4:10 4:14 4:17 4:21 4:24 5:2 5:7 5:11 5:15 5:19 5:24 6:4 6:8 6:13 6:14 6:16 6:18 6:23 7:12 7:13 7:21 8:12 8:16 8:16 9:1 9:4 9:6 9:7 9:10 9:13 9:14 9:15 9:23 10:6 10:9 10:10 10:14 10:15 10:17 10:22 10:24 10:25 11:2 11:11 11:13 11:15FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 370

11:17 11:18 11:22 12:3 12:5 12:8 12:12 12:15 12:20 12:22 12:25 12:25 13:1 13:2 13:3 13:10 13:12 13:13 13:13 13:16 13:17 13:19 13:22 13:23 15:7 43:24 43:24 44:5 44:6 44:10 44:11 44:15 44:19 44:23 45:6 45:8 45:15 45:25 46:10 47:2 47:18 47:25 48:19 48:23 48:24 49:8 49:10 49:13 49:14 49:17 49:18 49:19 49:25 50:3 50:9 50:10 50:12 50:19 51:11 51:11 51:13 51:15 51:16 51:22 52:5 52:7 52:8 52:10 52:12 52:13 52:15 52:17 52:18 52:24 53:7 53:8 53:8 53:9 53:12 54:6 54:7 54:7 54:8 54:11 54:12 54:14 54:15 54:21 55:4 55:6 56:9 56:18 56:20 56:22 56:23 56:25 57:2 57:5 57:6 57:8 57:16 57:20 57:20 57:21 58:1 58:9 58:13 58:23 59:1 59:3 59:3 59:4 59:12 59:14 59:15 59:18 59:19 59:21 59:22 60:15 60:20 61:1 61:2 61:5 61:8 61:9 61:10 61:12 61:16 62:1 62:4 62:13 62:16 62:17 62:17 62:18 62:25 63:4 63:9 63:23 64:3 64:5 64:5 64:7 64:8 64:19 64:20 64:24 65:14 65:15 65:17 65:18 66:1 66:4 66:11 66:17 66:19 66:20 66:24 67:3 67:5 67:6 67:7 67:20 67:22 67:25 68:1 68:3 69:12 69:13 69:17 69:20 69:21 69:24 69:25 70:1 70:10 71:5 71:11 72:16 72:18 72:25 73:1 73:2 73:5 73:7 73:8 73:9 73:11 74:3 74:15 74:23 75:9 75:11 79:6 79:12 79:15 79:17 79:20 80:4 80:11 80:15 80:18 80:22 81:1 81:5 81:12 81:24 82:3 82:6 82:8 82:13 82:14 82:19 82:24 83:6 83:16 83:23 83:23 83:24 84:2 84:12 84:20 86:3 86:6 87:9 87:13 87:17 88:3 88:8 88:24 89:10 90:5 90:12 90:12 90:25 91:1 91:3 91:4 91:15 93:10 94:2 106:8 106:9 106:12 106:14 106:17 106:21 106:22 121:5 121:6 121:7 121:8 121:10 121:11 121:22 122:11 124:16 130:21 131:3 135:11 142:7 143:7 143:8 143:9 143:14 143:16 143:18 143:21 143:23 144:3 144:5 144:6 144:7 144:13 144:18 146:20 151:18 153:13 153:14 154:13 156:2 156:3 156:4 156:5 156:11 156:13 156:15 157:4 157:11 157:17 157:20FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 371

157:22 157:25 158:2 158:5 158:7 158:8 159:21 160:4 160:14 160:19 161:9 162:5 162:22 166:21 167:23 167:24 168:1 168:6 171:5 171:12 184:15 184:18 184:19 185:1 185:3 185:4 185:10 185:14 185:17 185:18 215:7 215:18 217:6 217:7 218:8 218:10 221:18 222:9 224:10 227:3 227:13 227:15 227:17 227:20 227:25 228:4 228:7 228:12 228:20 228:22 228:24 230:6 239:20 239:20 240:6 247:21 251:3 258:14 258:18 259:1 267:19 267:20 269:1 271:2 271:8 271:11 273:21 274:25 275:10 276:23 277:2 281:4 287:18 288:1 288:4 288:7 288:10 288:24 290:1 290:10 290:11 290:12 290:14 290:16 290:17 291:5 291:5 291:10 291:25 292:23 292:23 293:1 293:2 293:3 293:4 293:4 293:6 293:7 293:8 293:13 293:16 293:19 293:22 293:23 294:2 294:6 294:11 294:13 294:14 294:16 294:18 294:19 294:19 294:20 294:21 294:22 295:6 295:10 295:14 295:20 295:21 295:21 295:22 296:2 296:3 296:8 296:9 296:11 296:13 296:15 296:23 297:1 297:8 297:11 297:13 297:15 297:17 297:22 297:23 298:1 298:2 298:3 298:5 298:6 298:8 298:9 298:11 298:12 298:13 298:14 298:18 299:4 299:5 299:11 299:13 299:14 299:15 299:17 299:19 300:2 300:16 300:17 300:19 300:20 300:22 300:24 301:9 301:11 301:11 301:12 301:13 301:21 301:25 302:2 302:15 302:15 302:16 302:17 302:21 302:21 302:22 302:23 304:5 304:10 304:10 304:11 304:11 304:12 304:13 304:13 304:15 304:16 304:23 305:8 305:10 305:22 305:25 306:2 306:7 306:14 306:20 306:21 307:1 307:6 307:11 307:13 307:20 308:4 308:7 308:8 308:10 308:14 308:18 308:19 308:24 309:4 309:9 309:9 309:11 309:12 309:13 309:21 309:25 310:1 310:3 310:4 310:4 310:5 310:6 310:7 310:13 310:14 310:16 310:16 310:18 311:2 311:5 311:9 311:12 311:13 311:16 311:17 311:18 311:19 311:23 313:4 313:8 313:14 313:15 313:15 313:16 313:17FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 372

313:18 313:19 313:20 313:25 314:3 314:6 314:8 314:9 314:11 314:12 314:12 314:13 314:14 314:15 314:17 315:2 315:12 315:14 315:16 315:16 315:17 315:18 315:19 315:19 315:20 317:14 317:22 317:23 318:12 318:13 318:22 318:24 319:1 319:3 319:4 319:6 319:23 319:24 320:9 320:10 320:12 320:13 320:14 320:14 320:17 320:19 320:20 320:21 320:25 321:1 321:3 321:4 321:6 321:6 321:8 321:11 321:11 321:12 321:13 321:13 321:20 321:23 321:24 322:2 draft 272:1 274:3 274:7 274:9 274:11 274:12 316:24 drainage 247:20 dramatic 68:16 110:14 122:17 137:8 dramatically 58:21 drank 49:16 draw99:9 172:4 178:13 drink 60:24 60:25 61:4 86:24 284:4 drinking2:9 74:8 77:15 77:15 77:17 77:18 154:6 169:10 169:11 169:17 169:20 241:2 241:7 244:2 250:14 282:20 283:3 283:10 283:14 283:15 283:16 283:24 284:7 284:12 284:25 285:1 285:3 285:12 285:24 286:7 286:12 286:19 286:23 287:2 287:16 drinking-water 178:23 240:17 243:15 255:2 284:2 drive 131:22 248:7 249:12 319:18 driven159:11 320:8 drivers 221:2 drives 107:11 107:12 111:3 117:22 120:10 126:10 159:21 driving223:16 drop 10:20 141:15 298:19 299:8 299:25 299:25 300:5 Drug259:13 dry16:24 duct18:23 18:24 18:25 23:17 ductal 19:1 23:20 92:10 92:13 92:17 92:24 100:15 100:22 100:24 101:3 101:4 101:10 101:16 101:20 101:21 102:14 102:21 103:16 104:15 104:23 104:24 105:21 ducts 18:25 19:2 19:12 97:19 104:1 due 29:3 118:23 122:6 141:16 171:16 225:13 308:3 duration 76:19 76:20 76:22 78:5 78:5 112:11 114:6 116:23 138:1 138:6 138:8 178:5 291:24 301:6 303:4 303:8 304:2 304:3FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 373

313:4durationindicated303:7 during24:8 24:25 30:9 37:5 73:25 92:4 92:9 92:16 94:18 94:21 94:22 95:1 98:13 98:14 98:18 99:1 99:3 99:4 99:6 100:21 112:11 113:6 117:3 118:11 119:8 119:15 120:1 123:24 147:1 153:22 154:7 159:18 162:25 164:25 184:24 197:9 197:14 290:7 305:9 305:9 305:10 305:12 307:23 308:25 309:24 320:1 320:2 320:4 dwell 149:15 170:19 173:10 177:18 181:22 dynamics 132:8 dynorphin 318:1

E E1 210:10 210:11 E2 210:10 210:11 Earl 25:22 earlier 38:22 59:5 114:17 122:12 128:5 130:7 140:15 141:23 144:17 154:2 162:22 208:9 222:23 229:17 240:13 242:20 early 20:2 20:8 21:5 21:6 24:1 24:1 25:2 25:10 29:20 33:21 38:15 39:10 39:17 40:3 67:17 68:13 97:7 97:11 114:2 123:19 145:17 150:6 150:10 158:11 158:14 158:16 259:17 304:9 320:21 easier27:3 246:16 298:15 easily108:19 234:11 234:15 238:2 easy 53:3 213:16 279:18 eat310:9 Eco 172:6 174:23 175:23 176:16 176:20 177:13 178:3 198:23 ECOFRAM

176:12 ECOG14:6 ecological 174:20 176:13 284:6 ecologically 188:3 199:20 208:15 economic 269:5 economies 262:11 economist268:22 economy205:6 205:15 205:20 259:15 260:1 262:7 268:21 278:17 278:24 ecosystems 253:1 EDC 23:7 edge 301:7 edge-of-field 178:22 181:24 effect15:14 17:5 24:5 26:22 26:23 27:1 29:5 31:23 37:15 37:24 37:25 38:9 38:15 38:17 38:23 46:7 46:8 62:6 62:7 63:2 63:22 68:2 69:5 78:11 81:6 84:18 84:21 85:2 85:13 85:16 85:22 87:6 88:24 94:8 94:21 102:21 103:15 105:17 106:6 114:6 116:6 123:9 130:13 131:17 133:6 133:21 133:21 137:4 137:17 141:12 142:4 142:10 158:16 163:20 163:24 163:25 165:6FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 374

165:7 165:25 166:10 194:16 198:17 199:24 200:10 200:12 200:22 201:1 201:15 203:13 207:17 208:3 235:25 237:24 238:12 238:16 239:3 239:18 266:13 295:4 298:20 299:23 301:7 303:15 303:22 307:9 308:2 308:2 effective 240:25 263:25 281:24 282:24 283:1 297:6 effectively 130:25 205:14 303:16 Effectiveness 271:15 271:19 277:4 289:23 effects 2:8 2:9 3:17 5:23 24:14 25:1 26:24 27:21 29:2 30:2 34:11 36:1 37:1 37:23 39:5 39:11 41:14 43:20 63:1 64:1 68:16 69:2 69:15 74:6 74:7 80:9 84:5 84:7 86:18 90:18 91:16 94:14 95:22 105:16 106:17 109:5 123:11 126:2 126:4 132:20 133:15 133:24 134:5 134:8 134:11 134:16 134:19 134:21 134:22 137:9 137:12 137:20 137:23 138:11 138:13 140:18 158:14 158:18 158:21 162:23 163:14 164:6 165:2 166:5 167:7 167:9 185:22 186:2 187:16 187:18 194:6 194:19 197:11 197:16 197:19 198:11 198:13 198:21 199:3 199:11 199:12 199:13 202:12 208:3 214:15 215:6 215:9 215:9 215:10 220:1 229:23 229:25 238:13 238:14 238:18 238:21 238:21 239:2 262:24 282:19 283:20 285:14 286:13 301:2 301:19 302:1 303:12 303:13 316:12 efficacy 263:14 efficiency253:11 282:1 306:8 efficient179:6 278:19 279:2 effort24:7 65:10 72:22 227:2 efforts 152:4 196:16 EGF27:8 27:13 27:13 egg206:2 eggs 189:13 189:22 189:23 194:14 194:25 207:16 eggshell 209:1 egg-yolk 206:2 EHP 40:18 eight 14:18 29:25 42:19 231:19 275:18 Eighty-percent 275:20 either24:1 37:3 37:8 38:2 43:8 70:8 77:16 97:24 102:15 103:3 103:20 115:2 126:20 127:7 132:2 186:14 206:15 238:19 304:7 312:21 313:3 316:18 318:10 ejection 41:20 elaborate 83:7 85:11 88:3 303:13FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 375

elaborated

80:19 elaboration 87:16 electronic 192:10 312:9 elegantly 113:13 element261:22 elements 48:22 169:19 elevated24:4 85:12 245:13 301:22 elevating122:17 elevation 86:2 elevations 127:17 131:1 eleventh205:18 eliminating 318:19 elimination 9:18 11:1 281:1 Ellen 5:19 5:19 elongation 92:13 92:24 101:20 eloquently161:10 else 22:19 60:6 251:23 264:7 300:18 elucidate 87:13 elusive 260:19 260:20 email 196:20 221:19 embargo 34:20 embarked126:1 129:1 135:19 139:13 embellishing 258:25 embryogenesis 92:4 embryonic 118:11 eminence 111:15 116:19 emphasis 3:1 93:20 empirical 175:17 175:20 179:3 employed284:11 employee 28:16 209:14 employees 209:16 209:18 209:22 empty 190:15 190:18 201:3 emulated86:13 86:25 encountered

250:1 encourage 277:9 endocrine 6:11 15:4 15:14 40:9 93:9 107:15 109:19 197:23 229:4 endogenous 27:16 endpoint40:21 41:11 71:10 85:17 88:13 93:13 316:10 endpoints 40:14 41:3 48:15 83:9 87:14 231:14 231:16 238:25 energy5:14 277:25 enforce 8:10 enforceable 285:16 285:20 engineering5:5 240:10 engineers 260:17 England

200:7 enhance 87:23 enhanced242:6 enhancement242:8 242:8 Enoch 32:20 36:25 41:5 57:22 Enoch's 61:14 enormous 278:14 ensure 220:19 272:16 281:21 284:1 enter 221:25 entered

221:22 entire 16:2 17:22 18:9 23:19 55:20 61:22 62:7 101:4 170:25 171:6 249:12 311:22 312:7 313:8 319:20FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 376

entirely 16:23 entity218:19 environment39:24 174:18 252:23 258:12 280:18 292:11 environmental 3:14 3:15 3:21 3:24 6:9 7:17 13:21 20:3 24:5 40:3 76:1 168:7 174:22 180:4 197:17 205:23 214:10 229:8 240:10 274:14 environmentalists 264:22 environmentally 24:23 63:17 enzyme 212:18 EPA 7:2 8:13 19:15 50:20 65:1 74:16 76:9 76:15 78:2 78:12 78:16 78:22 89:3 89:7 89:14 173:3 183:20 195:23 195:25 196:8 196:23 197:4 219:4 219:15 219:19 219:24 220:4 220:7 220:10 220:12 220:14 221:17 222:22 223:13 229:16 241:14 255:11 256:13 259:12 269:7 269:14 269:15 269:21 270:1 270:19 271:25 272:2 272:6 272:12 272:16 272:18 272:19 272:21 273:1 273:11 273:14 273:21 273:23 273:24 274:5 274:11 274:20 274:21 274:22 280:8 281:15 283:9 284:22 285:3 285:10 285:16 286:9 287:1 287:13 304:8 315:7 322:20 EPA's 83:21 138:5 181:5 182:23 243:13 249:20 269:13 271:24 274:2 274:7 280:23 282:8 282:16 286:22 epidemic 14:25 epidemiological 39:19 epidemiologist 6:2 epidemiology 5:20 5:22 198:24 217:2 epidermis 92:4 92:6 epididymal 36:6 episodes 110:15 episodic 45:13 110:4 122:13 epithelial 92:5 100:25 101:2 101:9 101:9 101:22 102:4 102:7 103:20 103:21 epithelium

22:4 43:5 43:10 43:13 EPL 28:15 28:16 35:15 36:4 91:22 EPL's 83:21 equal 204:1 209:24 equalize 25:23 equally72:11 232:10 equals 21:24 99:13 equation 205:25 equivalent87:2 163:6 163:12 193:19 Ernest151:7 erosion 257:6 264:25 errant267:6 error 18:17 234:11 234:12 307:3 errors 234:4 234:5 234:25 239:14 escapes 225:13 especially 14:24 53:2 60:10FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 377

81:7 82:21 217:7 237:20 304:1 essence 92:14 97:22 193:11 essential 111:21 265:21 279:19 279:20 essentially17:19 19:16 31:5 53:17 53:23 118:4 169:9 181:23 establish 77:4 131:10 234:17 established

166:9 287:15 establishes 41:22 establishing 131:18 167:19 198:17 estimate 10:3 11:3 13:24 65:9 77:19 77:21 265:5 291:23 estimated10:7 32:9 32:11 261:16 estimates 182:11 266:3 269:1 282:24 estimating10:16 estimation21:9 88:1 estimations 45:11 estradiol 108:1 108:17 108:18 109:2 109:2 113:11 113:16 113:17 114:3 114:8 114:12 114:13 114:15 115:10 130:18 132:17 132:18 135:10 316:19 318:7 318:10 318:14 estradiol-priming 132:16 estro 22:14 estrogen 20:19 20:19 27:16 117:16 117:17 120:8 120:9 122:18 123:1 124:8 125:4 133:17 134:17 135:7 135:9 135:9 136:13 136:14 136:21 137:3 137:17 187:15 193:6 193:7 193:8 193:13 193:23 194:1 206:1 206:6 206:20 206:25 207:4 210:13 210:19 211:3 211:22 211:25 212:4 212:8 212:19 299:1 315:22 316:1 316:9 316:15 316:16 316:21 317:4 317:23 318:3 estrogenic 17:3estrogeninduced

115:22 137:20 142:14

142:17 294:25 estrogen-positive 111:24 estrogens 130:17 159:11estrogen-totestosterone 193:9 estrone 130:18 estrus 86:10 93:25 99:17 99:25 107:24 139:21 139:24 139:24 141:12 142:23 161:13 162:25 163:2 167:9 232:18 234:18 234:21 234:23 238:13 301:4 et94:15 97:23 151:22 175:3 178:24 202:20 206:22 207:1 211:5 211:8 211:9 212:25 230:2 302:19 ethanol 16:13 254:2 Europe 201:11 216:7 euthanasia104:10 euthanize 65:12 evaluate 17:6 17:9 17:21 18:13 18:20 38:21 38:23 48:15FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 378

51:23 61:15 70:15 70:21 71:19 71:24 71:25 243:25 247:5 280:7 evaluated20:23 29:18 33:2 38:5 38:16 40:21 72:9 72:12 243:12 evaluating16:9 17:23 20:2 40:2 85:3 283:7 evaluation 20:15 23:15 58:18 71:13 72:4 147:17 evaluations 19:25 72:2 242:23 evaluators 72:7 72:8 evenly237:22 237:23 event 67:4 88:23 158:16 177:3 179:13 182:7 182:7 182:9 286:6 291:24 292:8 events 88:19 112:1 158:14 158:19 159:9 166:23 167:3 167:4 167:4 176:24 177:2 177:10 177:22 177:24 eventually219:15 273:23 eventuates 108:12 everybody 80:23 184:24 241:7 everyone 2:5 6:23 6:25 7:11 13:24 40:23 72:12 74:4 80:22 157:12 228:13 240:7 264:7 288:15 322:8 322:24 322:25 everyone's 41:16 everything8:7 57:13 60:6 170:12 198:8 214:15 278:23 308:23 everywhere 182:14 evidence 71:6 76:16 76:24 76:24 83:4 83:19 83:23 84:13 86:19 89:21 89:22 115:13 119:13 162:13 182:20 199:1 199:16 220:2 260:11 265:12 266:16 267:4 275:19 284:20 evidenced266:24 evidences 81:20 evident102:2 102:18 166:17 evolved

120:17 254:23 exact 270:1 272:21 exactly46:2 46:4 46:4 48:6 231:12 232:16 258:21 296:8 examination 51:18 123:4 133:3 136:22 286:13 examine 100:3 122:22 125:17 127:9 131:1 139:14 examined100:10 102:22 105:14 105:18 123:7 123:16 132:18 132:19 142:3 200:3 212:9 279:11 examiners 51:20 examining 134:24 135:16 142:9 196:18 example 19:13 23:2 28:11 28:14 36:11 93:6 94:16 100:5 160:9 170:23 171:13 176:18 181:10 187:8 188:17 189:5 189:11 190:3 192:12 236:22 250:23 273:7 273:18 274:4 examples 30:12 36:10 42:7 160:7 161:18 162:17 exceed 170:10FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 379

176:7 176:24 177:5 291:20 exceedances 177:6 244:23 exceeded176:8 176:24 176:25 249:3 286:7 exceeding176:9 177:11 177:22 291:23 exceeds 266:21 excellent258:5 except188:10 exception 241:21 exceptional 169:7 excerpted94:15 excess 88:9 160:5 161:15 162:3 162:16 162:19 exchange 8:6 322:9 excited

76:2 exciting170:17 exclude 319:20 exclusively 111:16 255:7 Executive 217:19 218:3 251:15 277:11 exemplified 178:14 exempted284:14 exercise 248:23 267:9 exerted 113:11 exerts 109:2 exist 107:2 existing175:18 181:20 284:14 exists 88:25 125:22 248:25 exogenous 161:2 expect34:5 34:5 75:7 101:19 102:5 104:8 104:13 110:2 150:9 208:4 234:13 270:11 300:13 302:2 302:7 expectancies 205:1 expected98:19 98:22 147:12 expediency282:13 expenses 257:25 expensive 16:5 245:21 263:25 279:3 experience 218:15 240:20 244:24 245:9 251:22 252:3 252:15 264:2 experiment 54:16 55:5 55:7 56:10 56:17 57:3 57:10 112:13 118:9 126:25 152:25 154:3 203:6 experimental 63:6 97:21 99:7 99:10 110:7 132:4 139:16 151:20 209:25 216:21 301:18 311:14 experimentalist 110:8 experimentally 152:6 195:12experimentparticular56:14 experiments 54:20 191:5 198:10 232:5 expert80:15 272:20 expertise 2:15 3:8 3:16 3:21 4:4 4:9 4:13 4:19 5:17 5:22 6:2 6:11 experts 71:14 93:11 158:3 explain 34:17 34:25 145:3 158:17 243:16 289:7 308:23 explained15:13 36:7 96:10 171:15 276:16 explaining53:14 explanation 11:4 212:20 306:3 309:19 exploring235:19 Exponent229:11FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 380

exported253:25 expose 206:23 208:19 exposed

23:4 26:25 27:2 27:7 28:25 30:18 30:19 30:20 30:24 37:3 53:18 53:24 68:23 102:15 105:19 139:12 164:13 186:22 187:22 187:23 192:7 194:13 200:23 201:7 201:14 202:4 202:8 202:11 202:22 203:17 205:22 206:5 207:3 207:7 207:21 208:2 208:8 208:12 208:17 208:25 209:7 215:4 215:12 215:14 215:16 215:23 216:3 216:5 216:11 216:11 216:12 283:13 305:7 exposure 6:2 20:6 20:8 24:13 30:9 30:14 30:14 37:19 38:15 41:2 68:17 68:17 76:19 76:22 77:12 78:5 79:2 79:14 86:9 88:3 91:16 94:8 95:15 98:9 100:4 102:20 105:16 106:6 128:13 128:14 134:8 134:9 136:11 137:15 137:19 138:1 138:6 138:8 138:13 140:3 140:4 142:25 143:4 143:4 144:21 145:4 145:23 153:5 154:5 162:24 167:21 188:2 202:14 203:2 220:6 235:21 244:7 247:24 250:20 276:4 276:13 282:20 303:14 303:16 exposure-duration 138:7 exposures 20:3 20:12 20:12 25:1 25:2 40:4 53:11 63:18 69:22 70:21 79:4 154:6 241:4 283:3 283:7 express 75:22 123:24 189:5 193:8 206:6 206:10 206:14 206:15 207:4 207:7 278:10 317:25 expressed101:8 123:19 123:21 129:7 164:7 expressible 200:9 expressing206:17 206:24 207:16 expression27:9 27:12 39:8 124:13 211:3 211:19 211:21 211:24 expressly 283:19 extemporize 82:7 extend 87:23 316:12 extended23:5 39:14 40:5 80:24 177:24 extension 21:19 88:18 92:17 101:20 extensive 82:1 136:11 186:1 195:4 287:24 301:1 extensively25:23 81:25 254:10 extent11:6 120:17 178:4 external 93:2 100:24 extra 297:5 extract312:24 extrapolate 169:3 236:5 extrapolating 181:18 extrapolations 145:13 extreme 162:3 extremely 171:8FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 381

225:9 280:3 eye 39:3 233:23 eyes 233:16

F F0 164:24 165:7 F1 29:11 37:15 99:8 164:25 165:2 165:7 F2 29:12 39:11 42:13 49:9 49:11 69:8 face 263:15 264:10 faced266:15 faces 265:23 facilitate 312:6 312:19 facilities 248:6 facility 65:2 312:3 314:1 facing265:18 265:20 fact16:5 25:6 50:5 70:4 78:23 84:5 84:13 85:8 85:15 85:19 86:17 87:5 88:13 88:21 89:4 89:7 90:1 95:16 95:21 96:3 105:8 106:2 110:3 125:10 125:12 126:2 129:24 130:13 130:25 131:24 133:6 133:15 138:9 138:12 138:14 138:18 138:22 139:3 141:10 141:16 141:20 141:21 148:1 172:2 175:7 180:14 187:4 187:21 188:5 192:19 194:1 195:22 196:1 196:2 196:5 196:17 198:5 200:13 211:5 212:2 215:25 216:7 222:11 222:25 223:17 224:7 224:17 224:23 226:4 237:4 240:13 241:3 248:23 249:9 251:21 253:25 255:2 273:19 275:3 284:12 292:7 296:20 298:16 300:4 301:19 301:22 302:5 303:9 303:10 303:14 303:20 304:1 304:5 307:21 307:23 308:12 309:1 321:21 factor12:9 118:12 211:10 factored235:10 factoring 285:15 308:20 factors 27:14 93:8 108:17 183:3 184:10 247:1 247:4 249:18 failed 105:9 fails 248:21 failure 215:9 250:14 311:10 311:21 fair 63:4 65:9 270:19 fairly56:1 73:23 83:19 138:14 146:24 174:12 240:16 243:25 246:12 268:6 275:18 275:20 fall 9:25 205:17 falloff 304:1 familiar 66:16 107:7 254:6 families 191:9 192:3 192:4 199:6 199:8 family70:17 200:1 223:11 Fan 206:25 211:5 211:8 farm 218:24 218:25 223:7 259:25 262:17 265:23 267:1 268:21 277:14 277:18 277:22 277:23 277:23 278:4 278:23 280:22 farmer229:3FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 382

264:14 277:19 278:16 farmers 171:18 218:25 253:3 256:4 257:21 261:15 261:16 262:15 262:25 263:9 263:11 263:15 263:22 264:20 266:11 266:23 268:15 268:20 270:8 270:16 278:6 278:20 279:24 280:24 281:20 farming258:11 263:4 263:6 264:20 279:2 farms 265:4 278:1 farther 249:11 fashion 71:24 86:16 100:13 133:20 fast147:12 fat15:4 15:11 16:20 20:12 22:5 22:10 36:6 36:12 51:8 68:9 92:13 fate 3:17 favor 279:12 favorite 264:9 FDA's 4:15 feasible 285:18 features 201:19 February 223:18 fed209:4 Federal 6:19 6:24 272:12 272:17 277:10 322:5 Federation277:15 277:19 277:22 278:4 feed253:24 277:25 282:1 feedback 46:22 46:24 108:15 108:19 108:23 109:3 111:25 111:25 112:5 113:11 115:10 117:24 118:7 120:8 120:13 120:14 120:18 125:4 316:2 316:9 316:18 316:21 317:4 318:6 319:21 feeding50:15 79:4 87:1 87:4 154:4 165:12 221:16 317:5 feeds 279:21 315:22 feel 66:10 70:6 76:6 76:23 77:3 77:20 78:3 144:21 178:17 213:20 225:19 252:4 321:17 fellow79:7 79:23 168:4 228:17 felt21:6 57:10 76:13 96:24 235:16 262:13 female 4:13 4:20 24:14 31:13 38:9 40:15 111:12 111:23 112:4 112:21 114:2 117:5 119:14 119:20 120:16 120:18 123:2 125:3 131:14 132:5 132:22 134:9 134:10 135:4 139:15 140:19 142:5 142:15 142:22 146:10 150:12 150:14 158:20 161:14 163:16 189:6 189:14 189:23 192:15 193:9 193:10 200:9 202:12 312:16 312:18 319:14 320:3 320:5 321:12 females 81:8 85:9 85:10 85:17 85:20 85:25 86:9 87:7 99:23 103:14 128:9 128:12 130:17 134:17 134:20 137:18 139:18 142:15 158:20 159:1 164:18 187:25 188:9 188:18 189:5 189:5 189:10 189:12 189:17 189:18 191:16 191:18 192:18FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 383

192:25 193:13 193:15 193:24 206:9 206:10 206:16 208:16 208:20 208:24 302:12 302:14 305:4 female's 189:22 female-type 202:3 female-typical 194:2 feminization 187:17 190:25 194:12 209:1 209:2 feminized 193:14 194:25 195:13 206:15 206:15 206:21 feminizes 198:7 Fenner51:14 Fenner-Crisp 5:15 5:16 227:3 Fenton7:21 13:19 13:22 13:23 43:25 44:10 44:15 44:23 45:8 45:25 47:2 47:25 48:23 49:8 49:13 49:17 49:19 50:3 50:10 50:19 51:12 51:22 52:7 52:10 52:13 52:17 52:24 53:12 54:11 54:14 54:21 55:6 56:18 56:22 56:25 57:5 57:8 58:1 58:13 59:1 59:12 59:15 59:19 59:22 60:20 61:2 61:8 61:10 61:16 62:4 62:16 62:25 63:9 64:3 64:8 64:19 64:24 65:15 65:18 66:4 66:17 66:20 67:3 67:6 67:20 67:25 68:3 69:13 69:20 70:10 71:11 72:25 73:2 73:5 73:7 73:9 82:8 82:13 91:15 93:10 94:2 215:8 272:3 274:25 275:7 275:10 Fenton's 9:2 9:13 215:18 313:19 313:20 fertility 158:21 164:19 165:2 165:7 189:20 189:24 190:19 200:11 203:23 204:4 204:17 229:7 238:14 299:21 fertilize 189:22 fertilizer252:2 fetal 14:2 25:2 37:9 43:21 47:8 47:10 47:10 50:20 63:7 63:10 94:22 94:24 fetus 43:4 215:3 fetuses 37:2 fewer 22:16 306:18 fiber 277:24 fidgeting228:5 field71:15 80:15 93:12 96:15 204:14 field-collected 194:23 fields 253:4 253:6 255:23 256:7 256:11 256:20 257:18 257:23 257:24 258:1 FIFRA2:1 2:6 6:20 8:3 74:5 157:13 228:14 FIFRA's 287:14 fifth 16:2 22:8 205:5 205:15 205:19 236:13 fight 263:11 fighting278:24 figure 13:4 13:5 33:10 147:23 207:21 236:4 249:19 figures 103:21 figuring188:21 236:1 files 231:4 fill 16:25 filled 190:11 190:15 final 32:7 33:1 37:12 51:13FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 384

151:17 159:15 167:25 221:25 225:22 274:22 281:7 finally39:2 41:12 69:17 81:5 84:10 86:3 88:4 97:4 146:2 152:24 167:18 181:17 201:10 209:21 220:4 226:25 262:19 264:11 274:25 281:8 finding135:25 204:7 278:24 309:14 findings 14:10 26:21 105:15 153:13 270:15 fine 228:6 288:7 fine-tune 182:22 fingers 240:21 finish157:6 166:19 243:23 243:24 247:4 247:18 250:7 285:25 finished77:14 77:18 169:18 170:15 170:16 170:23 282:20 283:5 283:10 283:11 283:21 286:7 286:14 286:19 287:4 292:14finished-wateronly 169:22 finishing211:4 fires 113:21 first 8:20 10:2 10:20 11:5 11:10 17:14 26:23 44:23 57:10 65:23 73:23 74:22 80:4 81:22 82:18 91:6 94:12 99:24 99:24 107:15 107:22 110:1 111:13 115:15 127:18 127:25 128:13 129:4 136:19 146:6 173:15 180:8 185:18 185:20 186:8 197:13 198:5 199:15 224:6 236:12 243:4 244:8 245:19 247:16 250:13 252:10 253:10 254:25 258:19 271:24 272:6 290:15 291:3 294:24 304:2 first-line 213:2 first-order 9:18 first-time 44:9 Fischer 42:20 fish 199:11 200:12 201:2 201:16 204:4 207:10 207:21 210:14 214:15 217:2 252:13 258:4 264:9 Fisher's 146:20 151:18 fit10:1 17:25 71:25 138:4 152:9 152:11 225:1 302:19 fits 124:15 318:8 318:16 five 15:25 26:6 26:12 72:6 83:17 94:9 163:22 199:7 255:2 298:5 313:9 fixative 16:12 fixed44:15 96:14 314:22 314:24 flag311:22 flashier 180:23 flashiness 175:18 178:10 178:14 180:22 flat13:5 flow175:3 175:24 177:20 177:22 178:3 178:8 179:2 179:4 182:17 183:25 286:14 292:11 292:20 292:20 flowchart 179:25 184:2 flowing171:2 171:21 174:13 179:9 179:16 179:22 180:11 180:19 181:6FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 385

184:4 focal 28:19 foci 36:7 focus 21:12 107:7 127:11 156:25 215:2 248:18 248:21 249:8 249:9 250:7 289:14 focused

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8:23 47:4 73:14 78:14 78:16 78:18 79:18 218:15 220:9 250:5 268:2 316:11 322:11 foster312:2 312:2 312:7 312:10 313:6 fostered26:15 fostering 311:21 312:6 312:20 313:5 313:11 fosters 311:11 foundation287:2 founder 240:8 four-day 2:5 fourfold161:25 162:11 162:16 fourth16:2 22:8 93:19 222:25 269:20 fourth-generation 277:19 Fox198:23 fraction 162:8 framework 88:17 Frances 186:14 Francisco 5:13 40:2 frankly224:15 300:7 free 197:24 203:7 freedom

216:23 Freeman 281:9 287:19 287:20 frequencies 173:4 frequency 2:9 74:8 159:24 170:21 171:24 172:16 173:6 191:12 314:20 314:22 314:24 frequent77:25 78:7 119:22 124:22 170:14 frequentlyFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 386

133:2 240:14 fresh 55:17 Friday225:12 226:6 Friedman 202:19 friends 268:7 frog186:18 197:21 200:22 frogs 187:21 188:2 188:10 191:1 194:7 194:10 195:16 197:11 197:18 197:23 197:25 198:7 199:5 199:24 200:10 201:20 202:2 204:4 204:21 206:3 206:9 207:10 207:15 210:14 214:21 252:13 front 15:24 35:1 66:18 68:21 266:17 274:9 274:11 314:16 fronts 183:20 fruit 218:21 frustration 280:24 FSH107:12 107:21 119:16 fuel 257:22 277:25 full 39:18 84:24 87:16 143:19 160:12 161:3 161:3 161:7 230:2 310:17 full-blown124:11 fully 23:9 92:23 260:2 262:15 290:6 303:18 fun 259:23 function 10:17 81:7 92:18 93:4 96:7 102:7 126:3 126:24 130:24 131:2 134:20 138:7 functionality 83:1 functionally 188:17 functions 107:13 107:14 130:23 fundamental 110:24 282:5 fundamentally 179:9 319:13 funded 186:12 186:14 186:15 186:15 212:16 funding87:19 186:9 255:11 255:13 funds 39:23 future 51:10 222:7 241:5 248:13 263:14 FY10 222:25

G Gabriel 209:9 GAC 244:8 244:15 244:20 244:20 gain 31:7 31:13 31:16 36:16 36:19 36:20 36:21 36:23 36:24 38:12 39:11 49:5 50:11 51:2 51:4 69:1 94:19 95:6 98:20 98:23 99:6 211:7 305:15 306:12 307:23 gained 49:15 50:5 94:17 gaining237:6 237:9 gap 11:7 gaps 145:20 Garnett218:6 Gary 218:8 251:7 251:8 251:10 251:14 gasoline-type 254:1 gated120:5 gates 120:9 gathered44:25 174:23 gathering93:11 gating317:11FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 387

gavage 44:21 44:24 79:3 87:2 127:5 127:18 127:20 128:10 132:13 139:1 139:2 140:4 140:18 141:8 142:1 142:14 142:21 143:5 145:23 146:9 147:2 148:24 149:1 149:4 153:16 153:24 154:3 154:9 155:4 155:8 162:24 163:4 163:10 163:20 164:2 164:4 164:5 165:13 165:14 165:23 166:4 167:12 230:18 235:21 236:3 236:6 gender110:15 gene 27:9 27:12 39:7 118:15 123:19 189:5 genera199:5 199:25 general 3:22 27:21 179:24 218:24 270:16 275:12 277:23 289:12 311:3 generalized

128:7 128:22 generally 44:12 66:7 233:18 272:13 317:20 generate 110:19 111:6 138:19 generated78:3 113:9 153:20 279:13 generates 111:2 generating 120:1 230:17 generation 82:22 84:3 120:18 164:12 164:24 164:25 215:22 generator 110:21 111:1 125:6 319:25 genes 39:9 43:19 211:14 genesis 116:7 117:23 119:6 genetic 118:15 187:19 189:3 189:10 189:12 191:16 193:25 206:9 206:13 206:14 206:17 208:6 208:8 genistein 20:12 41:7 genotype 48:21 gentleman 80:4 Geological 4:22 4:25 195:9 283:4 Georgetown20:10 Georgia 146:20 151:18 267:7 GERALD 6:8 51:16 52:5 52:8 52:12 52:15 52:18 53:7 294:22 295:10 295:20 Gerry 6:8 51:16 gestation 24:1 30:9 37:9 42:16 44:17 48:5 98:1 98:13 98:18 99:5 164:22 305:9 305:10 305:12 307:23 309:1 310:22 313:7 gestational 43:5 44:13 gets 176:8 180:23 180:23 212:10 238:18 getting179:6 201:2 207:13 217:3 227:10 239:4 245:14 292:1 Giesy 212:17 girls 14:24 15:8 15:9 15:11 39:16 39:21 40:3 40:7 given 26:17 45:3 64:22 76:16 119:8 123:3 153:18 163:6 164:2 195:22 207:18 216:25 301:14 306:22FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 388

307:6 310:25 gives 154:13 182:10 272:19 giving21:21 136:13 236:24 glacial 16:12 glad33:4 60:21 gland4:5 4:9 14:3 15:19 16:2 16:21 19:25 20:2 20:4 21:1 21:9 21:19 22:9 22:22 23:9 23:14 23:16 23:22 23:25 24:3 24:14 24:17 24:18 24:25 25:1 26:22 27:14 27:15 27:16 28:12 29:22 30:10 31:2 31:20 33:18 38:11 39:2 39:4 39:13 39:15 40:13 40:19 40:20 40:23 40:25 41:1 41:11 42:25 43:3 43:17 43:20 43:21 47:10 47:20 51:7 54:22 57:23 59:24 63:12 63:18 64:1 67:10 67:16 69:9 71:13 71:15 85:6 91:9 91:17 91:25 92:3 92:14 92:21 92:23 93:1 93:4 93:7 93:12 94:9 95:9 96:7 96:11 96:21 97:19 100:3 101:25 102:8 103:14 104:16 105:17 105:18 106:7 293:11 307:10 308:17 glands 15:25 18:20 19:7 21:11 22:3 27:4 27:10 38:8 43:8 55:1 67:19 72:9 93:20 95:11 95:17 101:11 101:22 102:14 102:24 104:14 105:8 131:25 201:21 201:25 glasses 234:19 Glenn 198:23 global 14:13 glossed

314:17 gloves 26:8 GLP 312:8 GLV 25:18 glyphosate 254:5 254:17 263:12 GnRH 84:6 107:10 109:20 110:8 110:18 110:20 110:21 111:1 111:2 111:14 111:14 112:18 113:8 116:16 116:18 116:22 117:2 117:4 117:8 117:14 117:20 118:3 118:10 118:23 119:1 119:1 119:4 119:8 119:15 119:18 119:25 120:18 121:1 122:7 123:8 123:9 123:11 123:16 123:21 123:22 123:24 124:2 124:14 125:6 125:15 125:18 125:19 126:22 126:23 159:20 293:17 316:3 316:15 316:22 317:5 319:15 319:18 320:2 320:7 goal 29:10 175:12 285:4 God225:17 gold5:19 5:19 130:11 goldfish199:19 gonadal 107:25 187:7 197:22 220:6 gonadogenic 107:14 gonadotropes 122:10 gonadotropin 108:3 108:10 108:11 108:24 110:14 112:1 117:17 117:23FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 389

117:25gonadotropinreleasing107:10 gonadotropins 107:11 108:22 111:4 gonads 206:10 208:5 gone 38:23 40:19 82:9 128:1 241:8 Goodman 318:1 Goodman's 318:8 gotten13:24 250:10 govern271:24 Government173:22 281:10 grabbed

192:21 graded 16:19 graduate 5:4 87:20 211:16 graduated258:23 grain 217:20 218:3 218:21 261:20 gram 235:3 235:7 grams 94:17 237:7 grandchildren 216:12 granddaughter 216:15 granddaughters 31:19 granddaughter's 216:15 grandmother 216:5 grandsons 31:19 granulated

243:19 grapes 218:22 graph 296:4 graphic 221:11 graphically 129:18 133:9 140:25 grateful 79:6 79:10 Gray 25:22 great 33:15 46:10 53:14 71:5 72:20 72:22 74:1 149:11 183:3 184:9 234:20 258:3 greater 32:24 33:11 52:9 52:14 108:6 108:7 108:8 235:4 235:7 262:20 263:15 greatly192:6 green 31:9 123:13 163:23 Greenwood3:19 3:20 9:14 9:15 9:23 10:9 10:14 10:17 10:24 11:2 11:13 11:17 11:22 12:5 12:8 12:15 12:22 13:1 13:16 grids 175:7 grooming45:20 gross 197:22 263:5 ground 53:16 54:4 173:25 268:8 groundwater 32:4 32:5 216:10 282:25 group 17:14 17:18 18:19 20:17 25:22 28:5 28:8 28:23 28:25 29:4 30:1 32:24 33:1 33:25 34:4 34:6 34:9 35:5 35:6 35:7 35:8 35:23 37:19 49:24 55:10 56:12 58:2 58:2 58:4 59:10 60:9 89:14 96:17 97:17 98:2 98:5 98:22 98:24 99:4 102:19 103:7 103:8 105:1 105:25 106:3 109:15 118:24 119:7 122:6 123:15 129:25 136:9 136:15 136:17 136:25 140:21 141:16 141:24 142:3 153:16 153:17 180:17 191:20 209:13 209:14 210:20 222:17 227:13 229:7 229:13FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 390

232:1 233:22 237:14 240:4 240:5 240:16 248:14 255:5 255:6 267:21 290:22 296:6 296:19 297:24 298:4 299:7 299:9 300:11 304:25 305:1 305:6 305:7 305:20 305:24 305:24 306:1 306:1 306:4 306:19 310:21 310:23 310:23 311:25 313:12 groups 9:22 23:1 26:13 26:18 28:6 31:17 34:11 34:12 35:10 45:23 49:6 57:12 57:25 58:22 67:11 96:24 98:7 98:8 98:11 98:16 99:4 102:10 102:11 103:2 103:18 103:19 105:14 136:20 136:25 140:1 192:9 218:24 226:5 226:12 231:19 231:22 231:23 231:25 232:11 232:12 232:25 233:23 236:14 236:20 236:20 236:21 236:22 237:24 240:24 255:9 262:15 275:4 275:22 303:7 303:17 311:6 311:7 313:12 313:13 group's 226:4 grow22:9 22:10 194:2 277:24 grower226:25 255:15 growers 217:12 217:20 218:5 218:9 219:7 223:6 225:23 226:17 226:17 251:16 252:11 253:15 253:17 253:20 253:22 254:3 254:24 255:22 258:8 262:15 262:23 268:1 268:10 268:18 269:3 270:8 279:19 279:20 growing104:14 170:14 194:14 212:5 277:20 grown 218:22 257:11 growth18:24 18:25 19:22 21:20 27:4 27:14 39:10 186:21 186:25 187:17 215:22 growths 19:6 guarantee 56:10 guess 10:1 11:6 11:25 64:13 82:11 213:16 217:15 221:23 223:2 226:11 227:6 243:7 250:12 252:9 258:6 276:20 289:17 293:21 297:18 299:5 300:9 301:14 307:20 314:16 321:15 guidance 272:1 274:3 274:8 guide 180:2 287:13 Guideline 272:19 guidelines 219:24 272:10 272:11 272:18 273:4 273:6 273:13 273:19 273:23 274:5 Gynecology4:8

H H&E 17:11 habitat258:4 Halasz 114:24 115:15 half 26:14 26:16 26:19 74:4 161:13 170:13 177:7 205:25 235:3 235:7 261:16 261:18 275:8 299:9 299:12FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 391

half-and-half 312:10 half-doses 45:1 45:14 half-life 45:9 45:11 45:12 half-litters 26:5 hall 65:3 65:5 118:20 218:8 239:25 239:25 240:6 240:7 240:8 240:16 251:4 290:2 290:2 hallmark 48:21 112:6 112:6 hallmarks 54:22 Hall's 319:25 hallway227:4 haloacetic 242:25 244:11 244:17 Hamner144:12 hand75:3 234:14 Handa 80:18 80:22 83:16 83:23 84:2 84:12 84:20 86:3 121:10 121:11 121:13 143:8 153:14 154:14 162:22 163:20 164:5 164:15 165:5 288:24 293:3 293:5 293:6 293:8 293:13 293:19 293:23 294:6 294:13 294:16 294:19 295:6 295:14 296:2 296:8 296:11 296:15 297:1 297:11 297:15 297:22 298:1 298:3 298:6 298:9 298:12 298:14 299:4 299:11 299:14 299:17 300:2 300:17 301:12 301:21 302:2 302:16 304:11 304:14 304:15 320:21 321:6 Handa's 153:13 handle 45:16 57:24 71:7 75:1 157:3 handled

183:18 handling42:5 handout179:17 handouts 7:7 13:24 40:17 149:16 217:23 hands 82:12 handwritten 231:2 231:5 231:8 233:4 233:6 happen39:21 39:22 52:2 58:5 58:7 60:9 68:6 234:14 249:1 317:6 happened34:15 58:6 68:12 72:3 164:22 188:15 193:11 198:20 230:23 238:9 266:4 happens 33:25 41:10 42:6 43:5 161:18 191:25 255:20 happy 157:22 276:19 315:14 harbor253:5 Harbourt168:6 hard40:16 40:24 68:8 75:22 123:15 207:18 230:16 231:11 295:16 harder239:9 harm 219:20 219:22 harmful 279:15 Harris 5:24 5:25 harvest270:9 Harvey144:13 haven't53:6 250:10 292:12 294:9 294:17 having12:1 23:4 38:25 46:1 66:17 85:22 92:25 141:12 162:15 203:11 214:14 215:5 232:3 248:12 267:8 278:7 297:5 307:22 Hayes 185:11 185:14 185:17FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 392

185:18 195:22 217:7 221:18 222:9 273:21 273:24 290:10 290:11 290:13 290:14 290:16 hazard 83:9 90:9 hazards 205:22 214:10 214:14 head3:4 6:9 20:10 48:6 75:12 229:6 heading294:24 head-to-head 47:21 health2:8 3:6 3:25 5:8 5:21 5:23 13:21 72:22 74:6 144:12 158:10 205:3 223:5 241:4 241:19 250:20 269:6 282:19 283:19 284:24 285:6 285:14 286:13 health-based 285:2 healthcare 205:21 hear 8:7 67:23 156:17 210:8 249:22 heard7:16 83:18 85:4 89:2 90:4 106:10 110:22 157:14 166:19 171:25 215:17 228:15 229:16 249:22 268:19 288:22 hearing79:9 79:12 heart 15:16 heartland262:12 heck 222:6 Heeringa 2:4 2:10 6:13 6:18 6:23 7:12 7:13 8:17 9:4 9:10 12:25 13:13 43:24 51:11 53:8 54:7 57:16 59:3 62:17 64:5 69:24 72:16 73:1 73:8 73:11 74:3 74:15 90:12 106:8 106:21 121:5 143:7 143:14 143:18 143:23 144:5 156:2 156:11 156:15 157:11 158:5 167:23 184:18 185:3 217:6 218:2 227:15 227:17 227:20 227:25 228:4 228:7 228:12 239:20 251:3 258:14 267:19 271:2 271:8 271:11 276:23 277:2 281:4 287:18 288:1 288:4 288:7 288:10 290:17 292:23 293:4 294:19 295:21 300:20 301:11 302:15 302:21 304:10 304:13 309:9 309:12 310:4 310:16 313:14 314:12 314:15 315:16 315:19 320:13 321:3 321:8 321:13 322:2 Heidelberg171:25 172:25 175:23 176:16 176:20 177:14 178:3 181:5 he'll 290:6 help 8:23 54:18 158:17 168:17 173:13 174:21 179:25 183:13 184:1 254:1 254:8 255:22 256:7 257:17 257:21 321:24 helped 231:6 256:18 helping79:11 196:13 helps 27:17 184:2 218:17 258:11 Hendley79:12 79:15 81:12 81:24 82:3 157:25 158:2 168:1 168:4 184:19 247:21 291:6 291:7 291:25 291:25FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 393

292:24 314:14 314:15 315:2 315:2 315:14 hepatocyte 79:5 149:23 155:1 155:16 hepatocytes 146:2 146:17 150:4 150:5 150:14 151:10 Herbert5:2 5:2 314:13 314:17 315:12 herbicide 70:16 188:3 198:1 253:3 261:12 261:15 262:25 herbicides 70:13 212:22 219:5 252:1 254:7 259:20 259:25 260:25 261:17 263:23 265:21 266:5 266:11 267:14 here's 30:12 30:13 116:1 199:19 199:20 200:18 200:20 203:15 207:15 207:24 243:11 hermaphrodite 204:21 hermaphrodites 188:8 188:18 188:20 Hermaphroditic 188:2 hermaphroditism 187:8 he's 50:24 217:15 230:3 258:22 heteronuclear 294:8 294:10 Hi 5:24 228:24 high 16:5 17:17 37:7 37:20 50:22 54:2 55:2 55:18 56:11 58:15 58:25 59:10 64:17 82:11 85:20 97:25 98:4 98:19 104:16 134:2 142:19 144:21 152:18 162:12 168:11 170:21 171:3 171:8 171:23 172:16 173:5 175:4 175:6 183:7 244:6 260:15 269:2 270:21 275:18 275:20 278:12 301:4 321:2 high-amplitude 133:1 high-dose 59:25 98:24 104:25 105:25 153:16 163:3 163:11 163:20 164:6 165:16 165:17 166:17 305:13 311:25 higher35:23 38:25 51:24 53:25 54:3 54:5 127:25 149:19 170:22 193:4 199:13 233:18 253:21 257:25 275:23 301:18 302:13 303:7 317:4 highest98:3 140:23 141:7 161:24 164:14 183:8 195:7 220:19 high-exposure 249:14 highlight95:20 148:11 149:9 149:18 175:22 highlighted

81:17 172:3 173:21 174:12 highlights 14:9 highly23:12 104:7 152:16 168:14 high-runoff 246:6 Hilakivi-Clarke 20:9 Hill 198:15 216:19 hire 209:20 Hispanic 205:11 214:12 histogram

141:1 histological 51:18 93:21FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 394

105:9 194:21 histologically 201:22 histology 197:23 historical 302:25 304:7 historically 20:1 246:23 302:10 history47:21 170:3 174:9 261:12 292:4 292:6 hit14:9 40:8 40:10 46:12 232:16 253:20 hoarseness 271:20 hoc 54:16 56:7 57:4 295:16 295:17 hold8:3 106:10 156:22 holding65:2 holds 155:8 Holiday226:19 Holland

48:4 homologous 319:9 homosexual 191:23 honestly 58:3 honor 75:14 hooded 25:4 hope 13:24 39:3 40:17 65:8 230:8 270:22 hopefully 15:23 71:3 104:2 123:13 140:10 185:7 260:18 hoping168:8 horizontal 23:13 hormonal 47:13 108:17 110:16 212:21 230:19 hormone 42:3 64:14 64:16 64:18 107:10 122:9 124:19 124:21 126:10 126:11 128:6 132:21 133:14 160:24 187:2 200:4 hormone-priming 135:6 hormones 37:25 125:23 127:11 130:9 130:11 130:14 239:6 Horseman 4:2 4:3 54:7 54:8 54:12 54:15 55:4 56:9 56:20 56:23 57:2 57:6 Hotchkins 151:8 hour 117:21 125:12 129:13 129:20 161:6 293:24 293:25 hour-and-a-half 17:1 hours 11:9 12:2 12:4 12:5 13:11 17:8 45:12 75:4 104:10 110:17 113:20 114:5 114:9 114:14 114:17 120:10 161:7 housed 311:23 313:20 housing191:6 311:22 Hovey 80:4 82:7 82:15 91:2 91:3 91:4 106:9 304:12 304:23 305:10 305:25 306:7 306:20 307:1 307:11 307:20 308:7 308:10 308:18 308:24 309:21 310:1 310:5 310:13 320:25 321:6 321:11 HP126:3 HPA 82:18 126:4 126:8 128:8 128:16 128:19 128:23 133:23 134:4 134:8 134:12 134:15 134:22 301:15 HPG82:18 86:4 123:10 124:2 125:23 126:8 126:18 126:21 128:18 134:3 134:5 134:12 134:21 134:25 Huffington221:9 huge 225:19 237:5FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 395

252:22 254:21 255:9 257:6 human 2:7 53:11 74:6 79:25 80:13 83:13 88:1 88:2 106:25 107:4 107:17 107:23 109:16 111:12 111:18 111:23 112:4 112:12 112:17 112:21 113:2 117:5 118:9 119:14 119:20 120:12 120:16 120:18 120:22 120:23 120:25 126:13 139:7 139:12 145:13 146:2 146:16 150:13 150:19 151:5 151:10 152:23 154:5 155:16 166:22 207:3 207:6 207:11 211:2 214:16 217:2 241:4 253:24 269:6 282:19 283:7 284:24 285:14 286:13 315:25 319:14 320:3 320:5 humans 86:23 150:22 151:2 151:15 152:22 153:6 155:20 167:21 203:20 219:16 220:15 236:5 236:6 283:2 316:13 hundred 254:15 hundreds 256:11 Hungarian 114:24 hunting251:9 hurry 280:13 hybrid 168:20 181:20 182:22 184:7 hydrologic 174:14 hydrologically 172:23 hydrologist5:1 hydrology 174:14 178:12 178:25 180:24 hydroxyatrazine 32:6 60:16 61:3 61:6 Hylidae 199:6 hypersecretion 108:21 hypertrophied 193:19 hypogonadism 118:23 159:2 hypogonadotropic 118:22 hypophysial 113:8 hypophysiotropic 119:11 hyporesponsive 46:14 hypothalami 125:17 125:18 hypothalamic 46:25 119:25 120:15 121:1hypothalamicpituitary 5:13 84:11 109:3 hypothalamus 42:3 42:9 47:1 107:8 107:8 109:7 109:9 109:13 109:14 109:18 109:20 111:19 111:21 112:24 113:10 113:21 115:1 115:16 116:1 116:14 117:14 118:13 118:17 122:4 128:22 129:1 130:6 294:5 315:23 316:5 318:15 319:16 319:21 320:8hypothalamuspituitary 112:3 116:11hypothalamuspituitaryadrenal 126:7hypothalamuspituitarygonadal 121:23 hypothesis 47:13 72:20 126:17 220:5 320:5 hypothesized96:8 hysteria 279:13FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 396

I ICI 20:19 I'd2:13 8:11 9:15 13:3 44:1 59:4 73:16 75:21 90:16 91:12 91:24 94:10 95:15 98:6 99:9 100:1 100:18 101:12 172:1 185:19 193:20 199:15 217:10 219:11 221:19 227:12 228:19 231:16 239:24 251:6 261:24 288:19 307:1 322:3 ID 18:6 idea 10:21 21:21 58:4 66:2 119:17 194:4 242:15 244:5 ideal 178:20 Ideally72:20 identical 201:15 302:5 309:2 identification 17:22 identified

187:13 193:22 194:22 244:6 294:9 identifier61:21 identifies 78:22 identify 91:2 167:2 175:12 175:14 185:13 206:9 285:3 294:8 313:2 identifying180:9 189:4 IDs 192:10 ignore 216:23 245:4 247:9 Iguchi 208:14 ill 263:10 I'll 2:16 7:12 8:9 73:9 75:9 90:11 91:1 121:15 124:18 131:4 132:20 139:16 144:7 145:6 145:8 146:1 148:3 182:6 183:6 184:23 185:13 190:8 191:13 191:16 194:22 218:10 227:14 228:20 247:9 248:18 262:3 290:24 293:6 304:11 315:12 322:4 ill-considered 278:25 Illinois 32:2 53:15 illustrate 87:9 illustration 253:8 I'm 2:10 2:11 2:19 2:21 2:23 2:24 2:25 3:2 3:4 3:9 3:9 3:11 3:14 3:18 3:19 3:20 3:23 3:25 4:3 4:6 4:18 5:1 5:5 5:7 5:16 5:19 5:19 5:24 5:25 6:1 6:8 6:12 6:16 8:3 11:24 14:2 15:20 15:24 25:25 33:4 33:13 34:14 40:16 46:11 46:15 48:1 48:25 56:21 58:24 59:8 59:13 59:18 60:21 62:1 64:18 66:6 66:16 68:21 74:12 75:12 75:12 79:16 79:22 79:24 81:16 91:8 91:10 106:23 107:7 120:20 121:13 121:13 131:5 145:19 156:20 156:24 158:8 168:4 168:8 175:25 176:18 185:20 190:10 191:20 193:16 197:1 199:9 205:4 210:15 211:4 213:8 213:16 221:23 225:15 225:17 228:25 229:2 229:18 229:22 230:1 230:8 230:10 232:4 235:5 236:18 236:24 237:5FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 397

238:8 240:8 241:6 249:21 252:3 253:2 255:17 258:21 259:5 271:17 272:24 276:5 289:12 292:3 293:2 293:8 294:11 294:23 298:18 308:13 309:19 310:7 314:25 image 104:2 images 95:13 imagine 180:7 181:8 212:14 225:18 230:21 imaging47:22 immediacy 224:16 224:18 immediate 123:19 immediately 26:7 85:5 312:14 immune 85:16 85:24 131:2 134:20 215:9 immunogenicity 89:7 immunohistochemic al 22:2 immunological 130:24 immunologist 131:5 immunotoxicology 79:2 140:15 impact46:16 84:19 89:20 119:10 125:23 199:3 244:20 250:6 259:10 262:5 262:9 267:4 267:10 279:16 297:5 impacted262:14 262:19 270:25 impacting279:21 impacts 51:7 80:9 81:6 261:10 262:13 impaired23:7 123:17 215:22 impairment24:9 69:1 impairs 215:17 imperative 93:22 95:10 96:25 impinge 260:9 implant113:17 implanted114:3 318:15 implanting135:10 implement 255:22 272:17 implementations 241:9 implemented

97:22 250:3 implementing 283:18 implicated

126:23 130:23 implications 152:15 274:17 implies 235:12 314:24 implying213:8 importance 115:10 139:7 important15:21 22:7 24:19 25:14 27:14 40:6 40:7 42:2 43:7 50:15 50:15 60:21 63:19 69:14 77:1 90:6 93:3 95:18 97:18 101:24 103:10 168:17 176:1 182:10 210:21 211:10 211:20 260:8 262:20 263:10 268:17 278:7 280:21 281:1 282:4 284:6 292:19 319:13 importantly 171:19 184:11 222:2 243:25 262:8 imposed

114:14 impossible 270:8 impression67:14 improve 258:11 imprudent270:6 inability 203:24 inappropriateFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 398

265:16 inborn16:3 incapable 215:23 incidence 35:3 102:23 103:3 105:7 142:22 192:5 209:5 210:16 275:17 275:23 275:25 276:7 276:11 inclined232:4 include 96:17 138:20 141:20 169:14 included76:14 141:24 141:25 159:14 170:8 170:13 173:7 212:16 231:24 231:25 234:10 234:24 235:1 269:22 including24:9 89:16 116:4 179:1 187:7 195:10 199:6 207:11 218:20 218:25 235:1 239:7 255:24 256:13 284:24 287:3 299:24 322:21 inclusion 234:16 235:10 235:15 inclusive 262:21 incoming291:19 incomplete 216:20 261:6 inconsistent38:2 inconvenience 321:7 incorporate 256:5 272:18 273:12 273:16 Incorporation 22:18 27:18 27:22 increase 19:21 22:21 22:25 25:20 27:21 27:21 28:4 28:9 28:18 29:3 30:22 35:12 35:17 36:5 40:11 51:2 68:22 101:19 102:14 103:6 103:13 105:20 106:2 114:12 117:23 122:17 125:7 125:25 126:16 129:24 133:10 133:11 135:8 135:12 141:9 142:22 159:15 162:15 182:12 208:24 209:5 209:12 209:14 209:17 209:23 210:3 210:13 210:16 210:18 211:6 211:15 211:25 235:3 253:17 264:24 264:25 265:1 265:2 265:3 276:11 307:24 increased19:19 22:17 22:24 23:6 35:11 38:12 40:8 51:3 125:12 130:2 154:16 177:11 192:6 192:7 235:9 235:12 253:12 263:2 263:7 264:15 294:9 296:5 increases 36:20 37:9 66:25 122:14 131:21 137:9 140:22 148:12 148:13 211:2 211:10 212:8 265:5 276:6 increasing 16:19 130:4 211:24 280:18 incredible 50:13 50:16 incubation149:24 150:17 150:17 150:23 indeed 166:14 214:18 262:6 independent198:8 198:14 200:2 200:13 202:19 220:18 index 22:18 22:24 24:4 164:19 165:7 indicate 119:25 289:18 299:6 304:18FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 399

indicated9:18 74:16 80:12 118:1 184:20 238:8 243:14 indicating162:19 indication 31:17 187:1 306:16 indications 86:7 indices 175:19 178:10 indirect119:13 316:22 indirectly126:23 individual 62:22 63:20 151:6 168:15 180:3 183:17 219:2 individually 136:6 163:18 179:20 individuals 151:9 induce 24:14 86:2 136:13 136:14 137:3 206:1 215:13 induced

114:7 123:1 135:5 136:21 161:2 187:14 inducer 213:17 induces 190:25 213:12 inducing161:5 induction 126:16 134:13 207:8 212:18 295:5 inefficient306:4 infection 241:23 infer 143:5 inflammation 29:1 35:5 35:7 35:11 35:17 35:19 36:11 38:24 39:1 58:12 58:16 58:21 58:25 272:5 275:3 275:5 275:6 275:8 275:14 275:17 275:19 275:23 275:25 276:3 276:6 276:8 276:12 276:15 influence 73:14 influenced

93:5 93:8 influences 93:2 influencing247:2 inform 153:10 153:13 information 12:21 32:21 35:3 36:17 43:18 44:25 45:9 71:3 73:13 77:1 77:9 77:10 81:13 89:11 89:24 144:1 144:19 153:2 153:3 155:17 156:24 162:19 175:2 175:3 184:14 185:5 196:8 197:5 221:3 222:18 223:23 235:22 256:4 272:10 273:3 273:8 290:20 291:16 292:5 292:22 321:19 322:10 322:16 infrequent177:10 infundibular 109:17 infusion 118:2 139:6 ingenuity 282:2 Ingraham

206:4 207:5 208:11 211:12 inhibit42:5 126:18 128:17 132:2 134:3 135:14 139:2 inhibited123:2 186:21 inhibiting 124:1 126:20 141:11 inhibition 22:11 22:15 46:25 131:23 141:22 186:25 inhibitor 20:20 inhibitory133:21 138:13 inhibits 126:21 135:3FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 400

initial 10:13 60:13 77:5 90:17 261:14 initially 117:10 186:19 311:24 312:6 initiate 223:14 242:22 injection 41:25 161:5 input 248:4 279:9 inputs 285:8 insects 253:5 inside 190:12 319:4 insight154:13 292:19 insightful 196:15 insignificant 28:9 Insofar 84:16 inspection25:17 installation 243:3 instance 81:22 226:16 279:11 instances 52:3 53:6 295:12 instead

20:25 233:25 238:19 296:10 Institute 13:21 instituted

117:19 241:11 Institutes 144:12 insufficient 220:3 intact76:24 86:9 95:19 100:23 139:15 139:18 140:19 142:5 142:22 295:23 intake 77:17 98:3 140:3 305:19 305:21 308:22 309:2 integrate 240:23 250:14 250:21 integrated

256:22 integrating 249:15 integration 249:4 integrity 282:7 intelligently 270:17 intended283:25 intense 147:8 150:6 intensely 26:8 intensity 147:7 intensive 86:14 intent303:11 interaction 5:14 8:19 84:11 interchange 5:8 interest3:8 51:6 51:9 74:20 82:4 91:9 152:2 156:25 184:21 195:6 219:10 240:24 278:22 282:14 interested

6:17 18:21 46:12 48:25 176:10 210:8 293:9 310:8 312:16 interesting47:14 153:12 172:23 174:13 177:16 192:25 193:2 200:17 207:12 213:10 215:19 237:13 238:11 241:16 289:11 interestingly 27:8 176:12 interests 240:19 262:1 interfere 42:8 interferes 118:16 interfering 119:18 interlay 41:7 intermediate 78:13 202:11 intermittent 111:2 117:22 319:18 320:7 internal 70:19 87:24 88:2 144:19 144:23 145:3 146:11 153:4 167:12 167:19 230:14 239:15 internal-doseFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 401

145:5 interpolate 182:9 interpret66:22 145:5 236:7 interpretation 62:20 62:23 229:19 interpreted 211:12 232:9 interrelationship 301:15 interrupt115:9 interrupted

108:9 Intersexuality 197:16 interspecies 151:1 152:23 155:3 interval 141:18 173:4 176:10 interviewing 173:24 intimidation 227:9 intratesticular 160:1 165:18 introduce 2:14 6:15 106:13 126:6 150:3 157:18 228:17 228:19 239:24 251:7 258:18 304:3 introduced

114:24 149:23 introduction 74:24 invaginate 92:6 invariant 117:20 117:22 118:24 119:4 invasive 104:11 investigated 180:13 investigating 283:9 303:12 investigations 303:25 investigators 117:19 invite 80:14 185:10 277:13 281:9 invites 225:16 270:13 involve 255:14 involved38:7 39:10 43:19 75:19 87:19 98:7 100:7 111:9 112:5 116:14 120:13 131:24 133:23 144:14 158:11 170:4 173:24 251:19 317:2 318:20 involves 108:25 114:23 IQ273:4 273:6 273:13 IQA 272:11 272:17 272:18 273:16 273:19 273:23 274:4 Irma 23:1 irrespective 295:8 Ishikawa 160:19 isn't 12:9 63:20 69:18 178:5 219:13 225:4 235:12 316:21 isolate 114:25 issue 7:18 13:5 34:19 37:11 40:5 44:4 90:22 153:9 205:24 213:20 223:7 223:8 241:16 243:11 244:22 245:7 247:21 250:8 250:20 251:20 254:18 254:22 272:6 274:2 274:8 275:14 issues 29:9 38:7 51:5 61:19 219:9 224:7 229:15 240:3 240:18 240:18 241:12 244:18 244:21 245:3 245:11 246:24 246:25 247:14 249:5 249:18 255:7 255:11 260:8 286:12 286:18 289:11 291:2 it's 10:15 10:18 12:3FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 402

12:6 12:16 13:4 14:15 15:21 16:12 17:15 27:3 27:19 34:1 40:16 40:24 41:9 42:1 42:3 46:21 47:8 47:16 50:14 52:10 52:13 52:19 53:5 54:1 58:6 61:17 63:19 64:8 64:12 67:4 68:7 68:8 68:8 68:18 69:14 72:20 72:20 72:22 75:14 77:7 80:19 82:25 85:22 85:23 92:23 93:3 95:9 95:17 102:6 109:4 110:2 110:4 111:21 111:22 111:22 112:1 112:2 112:15 112:16 112:20 112:20 113:1 113:4 113:7 113:9 113:25 114:4 114:17 115:14 117:9 118:5 128:1 139:16 155:2 156:10 156:22 158:16 167:15 172:2 172:16 172:18 172:18 174:12 176:9 178:20 180:2 182:15 182:16 183:17 185:12 190:4 190:5 192:17 192:18 202:10 203:11 210:4 215:18 217:3 217:4 217:8 218:19 223:3 223:7 224:6 224:15 224:22 225:2 226:6 226:7 226:11 226:14 227:2 227:7 227:25 231:11 231:15 231:18 233:14 234:2 234:9 234:11 234:11 235:24 238:1 238:11 239:2 239:11 241:8 243:22 245:21 245:25 246:15 246:16 248:1 248:25 250:4 250:4 250:8 250:10 253:13 253:24 254:6 254:8 254:9 254:14 254:21 256:19 257:7 259:3 271:5 271:6 271:9 272:24 282:4 290:4 290:5 292:2 295:16 304:17 304:17 304:22 306:3 309:5 309:16 312:9 313:22 314:4 316:22 317:14 321:2 I've 39:3 48:2 90:16 110:22 111:9 149:7 152:19 155:23 158:10 185:24 186:17 191:14 195:8 195:20 196:2 197:5 199:2 204:8 206:19 229:3 230:3 230:7 236:11 251:19 259:12 300:2

J Jackson 178:24 James 4:6 218:8 227:13 228:20 228:22 228:24 230:6 304:11 304:16 305:8 305:22 306:2 306:14 306:21 307:6 307:13 308:4 308:8 308:14 308:19 309:4 309:11 309:13 309:25 310:3 313:17 314:3 314:8 314:11 Jan 2:23 Janet 118:19 319:24 Janice 2:23 57:21 58:9 58:23 317:18 Janis 74:23 75:11 75:12 79:21 157:20 185:1 January212:15FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 403

213:11 Jeffrey146:20 151:18 Jepson151:21 Jere 217:19 217:21 218:1 218:2 221:15 227:16 227:19 227:24 228:2 228:6 228:10 228:15 228:18 228:23 239:23 251:6 252:3 258:17 259:1 Jim 4:7 81:5 157:22 158:8 158:8 228:23 239:23 job 53:14 178:25 227:7 234:20 jobs 205:7 205:20 265:6 268:24 Joe 6:20 6:23 7:14 277:10 322:6 John 3:9 3:9 6:4 6:4 48:15 50:20 53:9 54:6 212:17 218:8 239:25 239:25 240:6 240:7 join 81:4 joined 185:24 202:6 207:24 292:12 joint 283:8 Jose 23:1 JOSEPH6:22 Journal 34:20 journalism

282:12 judgment220:3 judgments 269:8 280:13 judicious 259:3 jugular 123:5 140:9 July 34:21 213:1 213:13 220:9 jumped 235:14 June 219:14 219:21 junior16:6 justice 205:24 justified273:10 justify269:16

K Kaiser40:1 Kannan3:23 3:23 62:18 302:17 302:22 Kansas 4:11 172:17 217:19 217:20 218:3 218:4 218:5 226:17 240:2 268:7 Karsch113:13 KATHERINE 4:10 Kathy 4:10 Ken 2:19 20:18 290:1 290:4 KENNETH2:18 291:10 Kenney20:17 Kentucky 4:19 Kestemont200:25 key80:8 88:19 88:22 133:25 142:12 158:13 158:16 167:3 167:4 168:9 168:23 169:19 170:5 170:20 170:24 172:21 183:6 321:16 kill 65:21 killer131:8 killing65:23 Kim 81:1 87:9 87:13 88:3 124:16 142:7 144:6 144:7 156:3 156:5 321:12 321:13 kinds 159:3 159:8 165:10 kinetic 84:25 87:8 116:7 148:16 148:18 150:8 150:9 kinetics 87:12 90:6 145:22 147:12 kisspeptin317:17 317:19 317:24 318:16 318:23FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 404

318:25 319:6 319:8 319:10 319:11 knew46:4 200:16 215:7 313:10 knife 114:23 114:24 115:15 Knobil 114:1 117:11 118:21 knowledge 186:13 196:2 216:22 216:24 260:18 292:18 known 39:9 40:11 43:16 43:18 109:16 109:23 111:15 114:22 114:23 116:10 118:15 122:23 210:4 223:24 230:3 241:14 285:5 285:13 287:4 KOW118:15 kriging182:20 Krishnan 3:23 3:24 62:17 62:18 63:4 63:23 302:15 302:17 302:22 Krishnan's 184:16 Krista186:13

L lab 16:6 25:11 41:14 44:8 44:12 44:14 83:21 90:5 125:24 125:24 146:20 151:18 194:13 label 171:17 laboratories 121:21 146:7 146:8 198:8 198:14 200:2 201:10 laboratory36:2 121:20 122:25 153:13 154:3 186:15 194:8 194:17 196:18 198:9 200:13 204:5 255:17 labs 24:6 24:6 71:18 71:23 83:21 lack 68:22 lactating70:23 lactation 23:7 69:1 91:10 94:22 95:1 98:13 99:1 99:3 99:6 164:25 305:9 312:1 lactational 24:9 31:3 31:21 48:25 69:2 98:9 lactationally 26:25 27:2 27:6 28:25 laevis 186:19 191:2 197:14 laid224:17 312:19 lake 172:17 172:19 179:11 180:15 314:20 lakes 169:13 Lamb 218:8 227:14 228:20 228:22 228:24 230:6 239:21 land205:7 245:12 landmark 116:1 language 272:21 273:5 273:7 273:13 large 21:13 25:11 64:15 66:2 66:15 116:3 152:13 153:22 154:9 160:5 166:14 170:25 174:5 176:23 180:15 195:11 224:13 230:16 239:5 246:16 247:25 262:20 263:8 264:12 285:15 largely166:3 171:16 265:20 larger28:8 177:15 192:17 192:18 192:25 193:1 195:17 243:4 248:2 264:16 largest177:5 177:21 181:7 205:5 205:15 205:20 277:23 larval 186:22FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 405

197:20 larynx186:22 186:25 187:17 202:1 202:3 last9:20 9:20 11:9 43:4 50:12 61:12 67:8 69:24 71:12 80:3 80:12 80:19 84:12 85:4 85:18 86:6 89:25 110:22 112:22 122:3 124:4 124:20 127:1 127:13 128:21 130:21 136:17 138:24 171:15 172:7 172:13 174:3 181:17 223:15 224:10 224:23 237:13 250:13 251:12 254:5 264:6 266:4 268:8 315:21 lasted 177:23 lastly142:24 258:17 lasts 161:5 latch 49:3 late 30:9 43:3 49:20 51:3 51:3 75:20 166:20 176:14 later 29:24 29:24 63:25 67:18 85:1 86:12 127:17 132:6 132:11 132:15 140:7 143:20 145:6 158:4 186:7 187:3 196:19 196:22 276:21 lateral 18:25 19:4 28:4 28:10 35:5 38:24 39:1 58:19 276:2 276:10 latest242:21 Latino 205:1 latter38:22 laughing259:16 Laughter 74:14 221:14 230:5 launched280:1 Laura 277:11 law240:11 240:11 285:4 286:17 Laws 38:14 lawyers 221:11 221:12 225:25 lay55:22 layers 261:5 lays 189:23 LC/MS/MS 134:18 LE 25:11 lead23:6 24:8 42:9 106:18 143:2 158:21 211:14 211:25 309:2 leading79:8 86:10 202:14 211:7 leads 113:22 114:16 241:1 265:13 learn 16:7 learned

154:25 322:10 learning183:20 214:19 least 33:15 40:15 81:20 84:15 107:16 133:13 137:10 139:22 142:18 162:16 186:13 187:9 198:10 199:7 205:6 209:4 210:12 210:17 211:2 213:13 224:5 240:12 263:11 288:19 303:10 leave 25:12 42:23 246:18 288:23 288:24 289:2 290:24 293:5 320:16 320:20 322:13 leaves 40:7 320:21 leaving228:5 308:5 LeBlanc 6:8 6:8 51:15 51:16 51:16 52:5 52:8 52:12 52:15 52:18 53:7 294:20 294:22 295:10 295:20 led31:21 95:25FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 406

98:10 98:19 116:9 316:7 Lee 5:2 5:2 83:23 314:12 314:13 314:17 315:12 Leena 20:8 left-hand 114:13 132:23 legality 282:10 Legan 4:17 4:18 64:5 64:7 64:20 65:14 65:17 66:1 66:11 66:19 66:24 67:5 67:7 67:22 68:1 69:12 69:17 69:21 88:8 113:13 160:4 294:21 295:21 295:22 296:3 296:9 296:13 296:23 297:8 297:13 297:17 297:23 298:2 298:5 298:8 298:11 298:13 298:18 299:5 299:13 299:15 299:19 300:16 300:19 315:16 315:17 315:20 317:22 318:12 318:22 319:1 319:4 319:23 320:9 320:12 320:14 legends 33:10 legitimate 223:7 223:8 lends 110:6 length56:2 100:22 101:17 102:14 102:21 105:21 143:3 202:7 lengthen 301:5 lengthening 298:23 lengths 52:23 leopard

194:9 197:21 197:25 207:15 leptin50:14 50:17 51:6 lesion115:5 115:7 115:17 115:18 115:24 115:24 116:3 116:5 117:13 117:15 less 16:7 21:14 22:5 27:12 45:13 50:11 52:6 52:11 123:25 133:2 155:13 161:5 165:21 210:23 214:24 214:24 234:14 237:10 241:22 252:22 253:11 257:25 262:16 263:24 264:4 264:4 264:5 279:2 320:3 letrozole 212:3 213:2 let's 111:8 134:24 143:14 151:13 156:16 157:6 173:11 220:9 305:11 letter195:24 level 32:9 32:11 32:13 42:9 48:3 82:11 85:20 102:5 104:16 109:4 113:15 114:8 118:8 131:11 140:3 173:25 218:25 223:7 231:24 234:7 235:12 235:13 250:11 266:13 266:21 285:4 285:5 285:13 285:17 285:19 285:21 286:3 286:4 291:21 291:21 levels 53:10 64:14 64:16 66:8 66:8 77:12 77:24 78:8 78:9 78:11 87:4 117:17 122:18 123:11 126:16 127:10 130:5 133:12 133:14 134:17 134:17 137:25 139:8 140:11 140:12 142:1 144:20 146:9 147:9 148:8 153:15 154:14 154:16 154:16 154:16 154:21 155:11 165:20 187:23FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 407

187:24 193:4 193:8 198:1 199:22 204:10 204:13 206:20 216:9 229:22 232:7 235:11 237:21 238:17 245:13 282:22 296:24 301:18 301:23 302:10 Levine 9:6 9:7 Leydig159:23 LH13:8 13:8 13:9 80:8 80:10 81:6 82:22 83:5 83:7 83:11 84:4 84:15 84:16 84:18 84:19 85:3 86:11 86:18 87:6 87:11 88:5 88:7 88:8 88:17 88:23 89:20 89:23 106:16 107:11 107:21 110:11 112:7 113:23 115:19 116:6 116:19 119:1 119:5 119:15 119:24 120:23 121:18 121:18 122:12 122:16 122:24 123:1 123:4 123:5 123:24 124:6 124:8 124:11 124:21 124:25 125:14 131:23 132:2 132:8 132:17 132:19 132:23 133:7 133:15 133:18 133:19 133:19 133:24 134:13 134:14 135:1 135:3 135:5 135:8 135:12 135:15 135:16 136:14 136:21 136:22 137:3 137:5 137:9 137:12 137:20 137:23 138:18 138:19 139:2 139:15 140:8 140:11 140:19 140:23 141:1 141:11 141:15 141:22 142:3 142:4 142:9 142:14 142:17 143:1 143:6 153:15 154:14 154:15 158:15 158:21 158:25 159:3 159:10 159:13 159:21 160:6 160:12 160:15 160:21 161:2 161:2 161:5 161:6 161:8 161:12 161:16 161:20 161:22 162:7 162:14 162:16 162:20 163:5 163:7 163:20 164:5 165:6 165:6 165:16 166:1 166:1 166:12 166:15 166:24 166:25 167:4 167:5 167:8 229:16 230:20 232:14 233:1 233:2 233:3 233:15 233:17 233:18 235:23 235:23 238:17 239:1 239:7 293:20 294:1 294:25 295:5 295:13 296:1 296:3 296:17 296:24 297:9 298:21 298:22 298:25 299:2 299:6 299:9 300:1 313:25 316:8 316:9 320:3 liable 216:22 liaison 219:7 licking45:19 lie 124:2 lies 116:2 life 20:3 20:8 24:1 40:3 51:3 68:10 68:13 69:19 72:19 72:23 200:24 205:1 251:24 lifetime 14:17 47:11 light 98:17 171:4 190:4 287:14 314:1 light/dark112:15 113:7 313:21 313:22 lighter 49:12FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 408

lightly223:12 lights 293:24 likelihood

50:1 321:2 likely67:4 75:1 89:20 190:20 205:21 210:24 214:2 214:5 214:8 214:12 214:13 215:4 219:16 220:14 222:11 248:12 likewise 89:18 93:7 103:16 103:23 149:13 154:10 limb 52:22 limit 53:19 154:21 249:20 limited

209:23 231:3 265:18 284:11 limiting223:20 269:18 limits 154:23 Linda 25:22 line 10:8 10:13 83:3 83:10 99:9 138:4 148:25 149:1 150:18 181:11 207:3 235:2 235:6 235:13 236:17 238:10 242:10 244:4 246:19 246:21 lineages 191:9 191:11 192:3 lines 62:24 207:6 207:11 211:2 211:17 214:16 link 109:17 109:19 239:1 linked 109:23 114:18 links 8:2 lipomas 36:7 Lippman 20:9 liquid 130:9 list224:22 listed 55:8 111:9 127:11 185:13 186:4 224:25 231:15 231:20 234:7 listen260:4 listening78:20 291:14 listing233:3 literally 251:25 256:11 literature 32:10 40:20 45:18 94:23 160:3 178:12 186:1 199:11 199:18 200:16 202:23 210:12 301:1 315:10 litigation226:2 litter26:14 26:16 26:19 45:22 45:22 45:23 46:2 46:6 46:19 49:4 49:14 99:20 312:7 312:12 litters 25:11 25:24 42:18 49:6 99:12 little 10:4 11:25 23:22 27:3 28:8 35:22 37:14 37:25 38:9 40:16 47:15 49:15 53:9 58:19 71:8 80:16 80:20 82:23 124:19 129:6 133:5 138:25 156:14 174:15 175:11 185:6 185:21 186:11 190:4 204:6 216:6 218:11 220:9 227:25 229:23 236:15 240:9 241:6 241:18 247:15 249:14 252:8 266:15 289:7 299:12 302:13 316:15 live 165:2 214:8 214:22 215:3 liver 152:11 liver-to-plasma 152:10 Load249:21 loaded 185:14 loading265:3FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 409

lobular 92:21 103:25 104:20 lobules 22:17 22:23 97:20 105:13 local 176:2 182:1 211:19 211:21 located

317:20 location 10:19 111:13 locations 174:1 log10:11 logical 75:6 Lombardi 20:10 long47:20 73:23 76:24 76:24 117:12 156:22 176:8 188:23 224:22 227:3 227:5 259:4 269:22 288:4 longer22:12 39:16 39:18 68:6 85:9 116:24 177:23 262:23 longest270:9 Long-Evans 25:4 86:9 91:17 97:24 237:7 312:4 longitudinal 18:24 19:5 21:20 22:6 23:13 longstanding 269:13 long-term 138:10 242:5 look-see 60:13 LOQ 155:15 lose 34:8 42:17 262:25 263:9 losing201:2 267:13 loss 25:20 25:20 202:14 203:18 204:3 204:3 208:12 208:15 264:14 264:18 losses 263:3 269:3 lost263:7 265:6 lot8:20 24:6 36:13 41:17 43:2 43:15 46:12 49:23 53:3 55:8 64:15 76:4 93:13 104:8 105:10 147:16 148:4 156:24 174:10 174:19 174:21 175:2 178:15 179:1 182:15 182:19 185:5 185:5 218:12 221:2 221:17 222:8 230:16 230:23 233:16 252:2 252:5 253:25 254:2 257:9 257:11 257:12 268:7 289:3 289:11 291:13 292:4 300:3 310:10 Loudon277:20 Louisiana 174:14 209:9 love 76:14 low33:19 46:20 57:23 57:25 58:4 97:25 138:14 162:12 188:3 189:24 190:19 197:25 203:23 203:23 204:16 223:20 233:21 234:5 260:15 298:22 298:24 low-dose 36:20 63:2 145:22 lower 51:24 62:21 78:10 86:19 110:9 140:4 163:11 163:21 309:7 lowering114:23 lowest12:10 12:18 37:23 54:4 60:10 161:24 231:24 232:1 Lowit 224:10 luck 267:18 lump 311:1 lunch 75:5 75:5 75:8 90:22 143:15 156:16 166:20 luncheon 157:10 luteal 108:8 159:18FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 410

luteinization 122:19 luteinizing122:9 160:23 luteum 108:2 116:7 159:17 lymph 16:3 23:19 lymphoma 23:19

M machinery 220:24 222:23 293:11 macroscope 17:6 17:8 magnitude 114:12 168:10 171:8 177:17 183:7 286:5 magnitudes 177:14 main 24:12 29:10 106:16 181:1 257:2 316:6 317:9 mainly312:16 317:19 mainstay 263:1 maintain 114:7 270:19 312:17 maintained 102:5 113:18 188:19 311:7 maintains 159:17 225:2 maintenance 81:9 major 23:24 26:21 30:8 33:17 89:22 111:5 116:21 241:11 242:4 250:8 250:8 250:14 250:15 255:2 255:24 318:6 majority 32:7 190:14 223:18 makeup80:21 male 9:21 12:7 28:3 31:13 36:1 43:8 112:24 127:6 131:7 134:9 165:11 187:2 187:21 189:10 191:1 192:19 193:19 197:24 200:4 202:12 206:17 208:21 209:15 272:3 312:17 312:19maledetermining 208:18 male-male 192:5 males 28:1 28:22 34:17 81:8 85:8 85:10 85:17 85:24 127:23 127:24 130:15 134:17 134:20 159:3 159:20 164:17 165:23 186:22 187:19 187:23 188:8 188:19 189:4 189:9 189:12 189:12 189:21 191:14 191:15 191:15 191:16 191:24 192:15 192:17 192:19 193:1 193:18 193:22 193:25 194:25 206:9 206:13 206:13 206:14 208:8 208:12 208:15 238:14 238:21 302:12 mammal 60:24 mammals 111:6 199:14 201:13 201:17 206:4 207:10 208:4 mammal's 208:5 mammary4:4 4:9 14:3 15:19 19:25 20:2 20:4 21:1 21:3 21:11 22:9 23:14 23:16 23:25 24:14 24:17 24:18 24:25 25:1 25:7 25:8 26:22 27:14 27:15 29:8 29:22 30:10 31:2 31:20 33:18 38:11 39:2 39:13 39:15 40:13 40:19 40:20 40:23 40:25 41:1 41:10 42:25 43:3 43:8 43:17 43:20 43:21 47:10 47:20 51:7 51:8 54:22 57:23FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 411

63:12 63:18 64:1 67:10 67:15 67:19 69:8 71:13 71:15 91:9 91:17 91:25 92:3 92:13 92:14 92:20 92:23 93:1 93:4 93:7 93:12 93:20 94:9 95:9 95:11 95:17 95:22 96:7 96:11 96:21 97:19 100:3 101:11 101:22 101:25 102:7 102:14 102:24 104:14 104:16 105:17 105:17 106:6 210:7 210:16 215:18 215:20 301:3 307:10 308:17 manage 280:4 managed

90:16 management171:16 248:22 248:24 255:23 256:23 256:23 257:5 266:24 272:15 managing254:24 mandated170:7 287:3 mandates 242:11 250:15 manifest120:7 158:25 manipulate 25:15 manner16:9 18:16 115:8 206:7 207:5 270:12 manually 101:5 manufacture 213:6 281:18 manufactures 213:23 manufacturing 278:15 Marc 20:9 margin285:7 285:15 margins 263:6 263:6 mark 48:14 156:7 marked 148:24 192:9 marker129:3 159:2 159:6 markers 189:3 market213:17 213:18 marketing213:2 marks 163:23 Marshall 218:9 251:7 251:10 251:14 258:15 mass 130:10 149:20 massed 32:8 massive 108:10 226:2 265:22 match 141:25 181:24 matched

87:2 105:23 307:22

matches 142:6 matching96:24 305:19 mate 189:18 mated23:8 310:22 material 44:3 63:25 materials 7:5 291:2 314:18 maternal 31:5 41:22 42:1 42:21 94:13 94:14 94:16 96:3 98:12 98:20 304:17 306:12 307:23 308:3 309:3 309:23 mathematics 240:10 259:8 mating136:1 matings 165:8 matter72:8 72:12 179:23 186:8 203:11 232:8 260:23 284:12 321:21 matters 179:24 260:22 321:5 maturation81:8 92:19 159:15 mature 30:15 99:22 237:10 maturity 69:16 188:24 Maumee 181:9FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 412

max78:8 maximal 104:13 maximum

32:9 32:11 53:18 77:24 78:4 78:8 153:23 249:21 285:3 285:19 292:8 may11:4 15:18 16:18 17:7 18:1 23:3 38:6 39:15 39:17 42:11 42:18 42:18 43:19 47:9 51:5 51:14 60:8 67:16 69:22 70:16 75:5 83:12 96:10 102:19 120:16 124:2 125:23 126:18 131:22 133:15 138:22 139:11 143:3 143:24 158:17 158:18 167:1 174:3 174:4 192:16 195:24 209:8 211:22 212:2 212:19 214:21 232:7 232:7 232:16 235:15 245:8 249:3 251:22 260:20 260:21 262:2 273:11 284:19 285:24 287:10 288:23 288:24 290:3 295:15 298:25 299:2 300:17 301:5 301:22 310:1 310:13 319:9 322:21 maybe 16:17 41:16 67:18 107:9 190:16 192:17 192:18 250:11 250:13 255:5 261:7 290:4 297:14 297:24 298:21 299:24 312:19 313:9 316:10 MBH112:4 120:15 319:5 McCoy 186:13 McFarland74:23 75:9 75:11 75:12 157:17 157:20 185:1 185:4 MCL 170:13 285:19 285:20 286:5 286:6 MCLG285:4 285:5 285:12 285:18 285:21 286:6 McManaman 4:6 4:7 304:10 304:11 304:16 305:8 305:22 306:2 306:14 306:21 307:6 307:13 308:4 308:8 308:14 308:19 309:4 309:9 309:11 309:13 309:25 310:3 310:5 313:16 313:17 314:3 314:8 314:11 McMullin 87:17 152:5 153:1 mean 12:18 18:19 19:23 34:4 39:5 42:8 46:25 47:4 51:5 52:2 56:23 68:4 68:24 103:20 103:21 157:3 181:24 234:5 241:16 241:20 245:4 245:11 249:11 250:17 300:3 301:8 310:24 317:9 meaning62:22 means 11:20 178:6 216:10 221:23 222:6 264:24 264:25 265:1 278:6 meant 32:12 measurable 130:18 measure 10:18 19:8 22:19 33:8 50:17 52:19 52:22 61:20 62:11 66:12 70:19 101:8 101:16 130:8 253:7 283:2 283:6 283:12 measured21:16 21:18 22:18 31:6 48:16 49:3 53:22 66:21 116:20 125:16 128:3FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 413

146:21 147:9 152:1 152:11 171:14 182:4 182:5 182:11 190:22 293:14 296:1measurementmaking60:17 measurements 48:11 170:10 measures 52:21 66:5 100:19 100:22 101:15 102:12 102:24 103:24 173:5 measuring21:7 110:11 130:11 202:7 meat279:21 mechanism

41:13 46:22 89:14 117:2 119:20 120:1 121:1 121:17 122:22 187:12 187:12 208:6 210:21 210:21 210:25 266:13 305:17 308:11 mechanisms 46:22 80:14 82:21 83:5 110:19 111:6 145:23 202:23 315:22 mechanistic 42:24 47:4 229:12 mechanistically 265:19 media 223:16 224:3 median111:15 116:19 mediate 133:15 mediated134:22 134:23 mediating84:15 Medical 4:11 121:14 Medicine 2:24 121:15 mediobasal 109:13 111:18 112:2 114:25 115:16 116:11 294:5 316:4 318:15 320:8 medium 97:25 Meek 5:7 5:7 meet218:12 272:7 274:4 291:20 meeting2:2 2:7 6:20 6:24 7:5 8:8 74:5 80:8 80:12 157:13 225:11 228:14 267:8 277:8 288:5 288:12 290:8 meetings 90:16 280:5 Mel 87:21 144:13 member2:22 3:2 3:11 3:18 6:12 73:12 113:14 281:17 members 2:14 6:14 9:5 9:11 41:8 89:3 90:21 217:24 218:2 221:20 227:2 251:17 268:14 277:7 277:24 280:6 280:22 281:20 289:17 290:23 321:10 membership226:16 men 14:20 14:21 203:24 204:10 204:13 204:14 204:15 204:17 204:19 204:25 205:3 209:19 209:23 menstrual 107:22 116:12 117:9 159:19 320:6 menstruation 116:8 mention 55:8 57:17 69:7 269:3 290:7 308:16 mentioned46:3 51:19 66:13 92:10 93:10 94:2 94:12 96:3 96:6 98:2 100:13 101:23 102:25 103:23 146:5 160:5 175:11 296:4 298:19 mentorship87:21FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 414

mesenchyme 92:7 mesocosms 198:3 198:9 message 226:7 messed 34:14 met101:5 258:19 metabolic 93:5 94:5 145:24 306:8 306:11 metabolically 306:4 metabolism 75:17 146:14 147:24 148:20 151:5 151:13 155:1 305:23 metabolite 31:25 32:8 36:18 36:21 54:2 60:17 70:4 77:12 79:14 90:2 metabolites 24:24 53:21 70:5 70:12 70:13 70:14 87:13 89:5 89:8 89:12 89:20 89:23 144:10 146:16 148:2 150:12 152:18 152:22 154:12 154:20 165:25 166:7 metabolized

155:2 metal-bottom 25:16 metallic 24:4 Metamorphic 198:2 method 20:4 21:4 47:22 105:11 139:3 methods 20:20 97:2 284:1 meticulously 232:15 metric 145:5 metrics 87:24 149:5 149:12Mexican/MexicanAmericans 213:22 Mexico 75:14 mg310:22 mg/kg29:14 32:17 32:18 32:18 36:15 37:4 37:24 38:12 50:24 62:21 71:21 72:13 78:12 85:24 85:25 86:18 87:4 94:19 95:7 102:16 106:3 125:10 129:25 130:2 130:2 131:10 131:12 131:13 131:16 131:18 132:13 132:14 137:6 138:3 140:5 141:2 141:3 142:19 147:2 147:5 148:9 148:9 153:16 163:4 164:15 296:5 305:1 307:9 307:16 308:12 309:6 309:19 310:23 mg/kg/d

98:1 105:19 105:22 127:3 166:9 304:21 MGH118:20 mic 7:12 281:12 mice 71:20 71:22 72:6 72:7 72:13 252:6 Michigan 2:11 Microbial 241:15 microextraction 151:23 micromolar149:25 microns 19:9 microphone 185:16 microscope 18:4 microsomes 151:9 midcycle 108:10 119:5 320:1 middle 113:25 161:11 243:9 middle-aged 138:18 161:14 mid-July 34:23 midst 269:11 Midwest171:9 292:16 migrate 118:12 migration 118:16 Mike 42:19 mil 148:8 150:20 miles 172:18FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 415

254:15 milieu47:13 milk 41:20 42:11 49:16 50:1 100:5 200:9 215:24 millennium

219:12 219:13 million 14:14 32:10 32:12 32:17 32:18 32:19 212:6 253:14 253:15 253:17 253:19 256:24 261:16 mimic 119:1 139:11 mind192:17 291:2 297:18 300:4 mindful 80:11 86:5 88:22 mine 24:6 minimal 19:19 minimize 65:13 minimum

24:13 32:13 256:6 minorities 215:3 minutes 16:14 16:16 16:22 31:8 49:4 50:2 73:18 75:4 110:17 122:15 124:23 125:2 127:4 127:17 143:10 147:11 156:10 156:16 228:8 252:8 268:8 288:20 312:13 minutiae 252:17 misconception 33:13 misconceptions 14:7 mislabeled

74:10 missed 51:19 missing9:24 76:8 179:10 Mississippi 2:25 180:21 195:5 255:25 Missouri 171:22 171:23 195:5 203:21 204:17 218:9 251:7 251:15 251:21 252:11 253:9 253:15 254:14 254:16 254:25 255:12 255:14 255:25 255:25 257:7 257:10 268:7 mistake 222:4 265:17 306:25 mistakes 14:7 misunderstanding 315:1 misunderstood 59:13 mix17:21 55:19 72:23 124:5 174:12 mixed60:5 mixing18:10 72:19 mixture 24:23 31:25 32:1 32:3 36:21 37:7 37:8 53:12 54:3 60:18 60:22 61:3 62:19 63:15 70:15 70:22 mixtures 36:18 63:21 mode 76:4 77:2 79:1 83:17 117:3 120:21 235:19 238:11 252:5 model 10:2 11:21 25:4 50:21 71:9 71:22 81:3 83:5 84:16 87:17 87:18 87:22 106:25 118:7 118:18 120:21 121:10 121:18 121:19 144:16 145:9 145:11 145:11 145:12 145:15 145:16 145:25 147:17 148:6 153:4 166:22 172:9 182:4 182:15 182:24 209:25 214:20 255:19 312:10 317:8 modeled

282:24 model-fitting 152:7FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 416

modeling83:13 86:21 138:23 147:20 152:4 152:16 153:1 155:23 167:18 175:4 181:19 181:22 181:23 182:14 284:6 291:14 models 64:11 158:18 168:19 175:19 178:16 178:21 179:1 179:2 182:13 184:12 291:17 291:22 moderate 19:22 19:22 19:22 modern258:11 282:2 modified76:12 151:21 216:22 modifiers 15:5 moisture 253:5 Moiz 6:16 6:16 70:1 70:1 71:5 72:18 Molecular 6:10 13:20 molecules 89:16 mom 45:18 49:1 49:3 moment6:14 81:4 176:1 182:23 314:2 momentarily83:14 moms 45:16 136:5 money 258:9 monitored78:6 99:15 99:16 139:21 140:6 140:14 monitoring2:9 74:8 76:12 77:25 77:25 78:2 78:7 131:2 158:1 168:24 169:5 169:8 170:1 170:8 170:14 170:21 172:6 174:20 175:23 179:4 179:6 282:18 282:23 283:8 283:16 283:19 283:25 284:10 284:13 284:14 284:16 284:19 284:20 285:24 286:2 286:8 286:11 286:23 287:3 291:9 monkey106:24 107:3 107:17 107:23 111:12 111:17 112:3 112:10 112:17 112:19 113:1 113:24 114:7 115:12 116:6 116:10 116:22 116:23 116:25 117:3 117:6 117:8 117:14 118:18 118:21 118:25 120:11 316:4 monkeys 111:22 114:2 114:21 mono 146:15 147:24 151:2 Monte 315:8 monthly173:6 months 117:21 122:3 134:2 138:12 138:15 138:17 155:24 161:11 186:23 220:11 259:21 269:20 282:6 303:11 Montreal 3:25 Moore 200:5 Moreover 281:25 morning2:4 2:19 3:3 3:13 4:2 4:6 4:10 4:17 4:21 6:22 7:1 7:21 13:22 13:23 34:16 45:4 65:20 74:4 91:3 91:12 91:15 92:10 93:11 113:19 121:11 166:20 184:20 289:3 290:15 291:4 296:15 320:21 322:12 323:1 morphogenesis 27:17 34:13 38:7 43:11 43:16 92:17 92:24 morphological 39:9 57:3FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 417

93:21 93:23 95:9 95:11 100:8 100:17 morphologically 188:11 morphology166:24 197:22 morphometric 20:14 morphometry72:9 Morseth138:11 303:10 mostly277:20 mother209:7 215:23 mothers 25:12 209:5 215:12 215:16 mount 16:4 16:24 40:1 68:7 92:20 100:8 306:15 mountains 270:15 mounts 15:19 100:15 mouse 15:23 43:10 48:11 58:6 92:20 move 7:23 8:23 9:1 9:13 13:16 74:21 109:12 143:24 151:13 156:20 157:8 157:18 173:9 183:6 195:17 217:10 217:15 220:9 267:22 274:2 279:4 322:23 moved65:4 195:14 234:9 259:22 moves 216:1 216:18 moving57:19 82:17 224:8 234:13 mRNA 123:11 much-needed 278:16 multipage 276:25 multipart75:1 multiple 13:6 23:1 40:24 179:15 198:7 199:5 199:5 199:6 200:2 201:10 202:21 209:2 246:4 249:4 249:10 261:5 270:4 multiply 147:19 multitude 279:22 Mumtaz 6:14 6:16 6:16 69:25 70:1 70:1 71:5 72:18 municipal 240:18 muscle 41:21 152:12 myriad 263:19 myself 39:23 198:17

N NAFTA75:14 namely96:17 nanogram

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286:18 necessary 284:21 necessity 231:3 264:21 necropsy 16:11 28:18 36:2 36:2 36:3 36:5 64:13 64:22 65:5 67:4 necrosis 36:6 negative 29:15 32:16 104:4 108:15 108:18 118:7 125:4 316:18 negatives 241:25 neighborhood 210:5 neither 224:24 271:9 284:8 286:21 Nelson4:2 4:3 54:8 54:12 54:15 55:4 56:9 56:20 56:23 57:2 57:6 172:1 neonatal 20:19 25:2 nerves 109:11 nest312:19 network 95:18 100:25 101:4 103:17 103:17 217:23 218:8 218:11 218:18 228:16 267:20 289:24 neural 113:5 215:11 neurobiology 110:20 110:24 neuroendocrine 107:6 111:16 116:10 118:5 126:6 126:19 321:25 neuroendocrinolog ists 109:8 neuroendocrinolog y4:20 neuron124:2 316:3 neuronal 82:21 123:16 126:23 neurons 84:3 84:6 107:9 118:11 118:16 118:17 122:6 123:14 123:20 123:21 123:22 123:24 124:14 126:22 126:22 128:24 129:2 129:7 129:17 129:23 293:17 316:16 316:22 316:25 317:1 317:5 317:19 317:24 318:1 318:3 318:5 318:23 318:25 319:7 319:8 319:10 319:11 319:15 320:11 neuropeptide 126:9 Neuroscience 121:14 158:9 neurotox 3:7 neurotoxicology 3:1 neurotransmitter 317:2 Neutrophils 275:21 newborns 25:17 newer 134:1 news 174:19 NEXRAD 176:3 ng/ml 148:12 148:13 162:10 162:11 nice 65:2 89:8 117:17 135:7 137:16 295:12 nicely137:3 318:8 318:17 Nick 20:17 NIEHS 3:11 20:18 35:15 35:16 39:23 48:1 48:14 night 224:23 nipple 19:6 43:9 43:9 92:11 100:23 Nitrate 197:19 NK131:15 NOAEL 85:24 131:18 137:25FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 419

138:8 nobody198:12 205:2 nobody's 308:24 node 16:3 23:19 no-effect85:20 131:11 NOEL 166:8 NOELs 302:18 noise 65:11 non 77:14 169:10 non-cancer2:8 74:7 229:14 non-compartmental 11:19 non-detectable 193:7 non-drinking 169:12 none 19:17 19:17 38:16 130:19 non-essential 111:22 111:23 Nonetheless 269:19 non-human 82:20 106:20 111:11 non-progression 39:20 40:4 non-self 313:2 non-stress 129:6 non-stressed 129:18 noon 113:19 nor 103:18 131:17 224:25 271:9 284:8 286:21 normal 25:5 37:5 42:18 47:12 66:9 66:10 66:13 66:23 67:19 94:24 133:2 160:17 161:6 161:17 161:21 161:22 162:15 162:25 163:2 300:9 300:14 302:14 319:19 normalization 62:14 normalized

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58:15 141:7 303:21 no-till 280:19 noting269:17 Novartis 186:20 212:11 213:4 Novartis/Syngenta 186:16 Novartis/ Syngenta/EcoRisk 186:12 November 71:12 213:4 213:5 213:14 nowadays 47:23 NRDC 220:25 221:6 nuclear 109:15 nuclei 123:14 129:12 129:15 nucleolus 128:25 nucleus 109:16 109:17 116:4 120:7 129:9 129:16 129:22 211:11 317:25 319:12 numerous 30:18 39:19 249:2 255:1FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 420

nursed 49:23 nursing31:7 Nutrient265:2 nutrition 93:6 93:8 308:16

O Oakland

71:14 OB/GYN106:23 Obama 222:15 objective 63:23 objectively 273:10 obligatory117:9 obscene 226:24 observable 190:17 observation 36:6 258:19 308:25 observational 216:21 observations 51:12 198:9 312:8 Obstetrics 4:8 obtained64:13 150:13 obvious 190:5 312:13 obviously 31:1 81:17 85:25 89:24 181:15 219:12 221:16 265:12 298:25 306:11 occasional 295:15 occasionally 192:11 233:6 occasioned

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288:1 288:13 290:3 290:12 290:17 299:13 306:21 307:6 309:25 311:2 314:3 314:8 315:12 317:7 320:12 320:13 321:14 322:1 322:7 Oklahoma 3:6 old68:4 older 61:23 230:4 olfactory 118:12 OMB 272:18 273:1 OMB's 272:21 omission 95:21 96:1 98:10 once-a-day44:24 Oncology 212:11 ones 62:21 174:14 175:21 180:8 180:16 180:19 181:5 192:13 192:24 193:3 193:6 193:7 214:1 214:2 214:4 237:9 237:11 243:4 245:10 245:18 304:9 one-way295:18 on-farm

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313:11 ordered

286:8 286:9 orders 286:5 ordinary 53:11 organ 92:15 organics 283:20 organism

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132:22 overall 102:7 103:17 104:16 209:13 223:19 247:6 247:10 248:19 250:22 269:17 275:23 295:19 overkill 249:15 overlap 232:2 232:3 232:3 overlapping 231:21 236:22 overly267:5 overnight290:25 over-predict 178:23 overriding278:22 overseeing36:5 overseen 219:14 oversight250:15 overtopped

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41:19 41:25 42:2 42:6 42:8 42:10

P p.m 323:2 PAC 244:8 244:15 pace 17:4 22:8 222:2 packed 200:19 201:6 243:19 packet103:22 pad16:20 22:5 22:10 51:8 68:9 92:13 page 13:5 90:14 272:23 272:24 274:8 274:9 274:9 274:10 275:15 pages 269:22 painted

208:23 paired 192:23 pair-fed95:5 98:2 98:22 99:4 102:18 105:1 106:4 304:19 304:21 304:25 305:1 305:5 306:6 306:16 306:18 307:14 307:21 310:8 310:9 310:21 310:23 pair-feds 308:6 pair-feeding95:4 103:11 106:1 pairs 191:23 192:10 192:21 192:22 pair-wise 232:21 Paluzzi 160:14 panel 2:1 2:6 2:11 2:14 2:16 2:22 3:2 3:12 3:18 6:12 6:13 7:1 7:8 8:6 8:18 9:3 9:5 9:10 15:3 41:8 44:2 73:2 73:12 74:5 76:15 80:20 81:23 89:4 90:21 107:20 110:9 113:14 114:1 114:13 123:13 124:11 124:25 132:23 135:23 137:2 143:25 158:4 168:18 171:19 172:15 184:3 184:22 185:6 185:19 217:9 217:24 218:8 229:10 251:17 268:4 269:15 270:2 270:6 271:3 273:2 276:24 278:11 279:1 280:12 281:15 288:18 289:17 290:6 290:21 290:23 321:9 322:14 Panelist270:3 Panelists 77:11 panels 36:10 36:10 75:25 78:21 107:22 140:4 222:10 222:12 272:20 Panel's 7:22 289:15 paper 7:18 20:21 28:2 29:7 29:9 30:3 30:4 32:20 33:2 33:4 33:7 33:9 33:14 33:18 34:19 35:25 36:8 36:25 37:1 40:18 41:5 41:6 44:4 44:24 57:22 58:14 58:15 60:16 61:14 61:17 61:18 61:24 64:12 66:13 67:13 68:19 75:3 77:8 138:12 174:12 188:1 188:7 189:3 189:15 190:22 194:24 197:9 200:14 201:12 201:19 202:2 202:6 203:1 204:11 207:14 207:20 207:25 208:10 209:11 211:5 212:15 230:2 243:12 269:22 269:24 274:8 316:24 papers 14:5 30:5 36:17 37:10 41:5 41:6 63:11 67:8 67:14 195:10 199:18FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 424

202:21 206:22 211:9 215:13 270:10 306:23 paradigm

128:4 132:12 paradigms 139:15 parallel 126:6 parameter 10:2 10:16 41:3 111:11 249:9 parameterize 145:25 179:2 parameterized 181:23 parameterizing 145:10 parameters 10:3 10:18 24:13 85:24 87:9 105:18 134:25 137:5 142:11 249:2 249:3 249:10 parasagittal 115:25 paraventricular 128:25 129:9 129:16 129:22 parent70:4 70:22 parsimonious 320:4 partial 84:23 194:11 209:1 partially 82:25 193:25 206:15 participants 228:17 participate 225:17 participated24:7 80:2 256:12 322:9 participation 322:25 particular2:16 4:4 28:13 55:5 71:9 80:11 93:14 93:20 181:25 186:11 189:7 193:12 203:6 216:2 216:4 239:7 242:12 246:5 250:2 284:15 291:19 303:14 321:25 particularly 62:20 90:18 112:8 167:5 204:24 205:4 248:3 260:25 289:9 partition 146:2 151:25 152:8 152:24 parturition 42:14 42:15 42:17 312:1 pass 95:25 100:14 passionate 213:20 past31:22 38:23 134:2 178:10 223:23 225:24 254:8 256:13 259:12 259:21 patent270:12 pathologist17:20 28:15 28:16 28:17 36:4 48:13 48:14 pathologists 35:14 35:15 58:17 pathology 13:20 17:10 17:12 23:22 28:24 35:16 36:3 91:21 pathway126:14 patients 319:15 pattern 33:22 33:23 38:2 118:1 122:16 124:14 124:25 125:19 132:23 133:7 139:9 141:22 154:4 172:11 237:1 302:20 310:11 320:7 patterns 25:5 25:6 121:18 122:13 132:3 133:16 143:4 151:10 154:6 163:18 173:18 Paul 81:12 168:1 168:3 291:7 291:11 291:25 291:25 314:15 315:2 315:2 315:14 paved222:1 paw46:5FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 425

pay93:14 223:9 226:8 pays 253:21 PBPK81:3 87:16 87:18 144:16 145:9 145:10 145:11 145:12 145:15 145:16 145:25 147:20 152:4 152:15 153:3 155:23 167:18 PDN294:3 peak 13:8 13:11 77:19 77:22 78:4 123:5 133:19 135:16 140:10 141:1 142:9 154:14 155:4 155:7 162:7 162:9 163:5 176:8 176:11 178:2 178:7 179:10 181:9 230:20 232:16 247:24 248:1 292:8 293:20 294:1 295:7 295:8 299:9 peaks 171:8 175:14 176:7 177:10 182:2 183:10 292:10 pediatric 39:19 Pediatricians 14:25 peer 199:17 peer-review 230:11 272:20 273:2 pegs 179:25 pellet135:10 PENELOPE 5:15 penis 202:7 Penny 5:15 pentobarbital 160:22 penultimate 264:21 people 8:1 14:14 173:24 179:25 205:19 207:18 222:13 223:8 226:21 227:20 228:4 229:10 233:16 246:10 246:20 251:11 255:8 255:10 256:13 317:18 per 12:14 30:1 32:10 32:13 32:17 32:18 32:19 32:24 53:19 53:22 57:3 103:14 117:21 136:24 140:21 148:8 150:20 237:7 252:20 285:11 285:22 297:24 306:9 percent13:8 21:19 94:20 160:24 percentage 53:2 58:20 160:11 263:8 percentages 32:8 58:20 perfect241:25 perfectly 59:6 245:5 perform

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119:9 124:23 125:11 127:19 133:11 136:16 136:17 137:8 138:18 140:7 146:11 147:5 157:12 164:2 172:21 177:25 184:23 186:23 203:7 228:13 246:6 246:6 252:1 289:1 309:24 320:16 322:13 322:17 322:22 periods 23:24 38:21 135:22 136:11 169:4 175:25 181:19 284:17 peripheral 110:11 116:20 peripherally 134:23 peripubertal 136:16 peripubescent 295:1 peri-pubescent 137:8 permanence 17:5 permanent2:22 3:2 3:11 3:18 6:12 68:10 69:15 Permanente 40:2 permanently16:24 permeable 214:23 permissible 285:17 permissive 118:2 permit14:1 121:2 320:17 perpetuated

197:7 perplexing303:24 Perry 172:17 179:11 180:15 314:20 persistence 68:19 persistent 30:10 31:20 69:6 69:16 person65:8 70:25 personally223:11 persons 285:6 perspective 51:25 72:22 pest256:22 pesticide 2:25 6:2 8:13 74:11 205:13 224:24 266:22 270:20 282:8 282:10 282:22 282:25 283:6 283:9 283:12 287:10 pesticide(s 196:14 pesticides 3:17 75:18 205:10 205:23 259:11 259:15 266:11 282:20 283:3 pests 253:4 282:3 petroleum 264:15 pg/ml 114:9 pharmaceutical 213:6 pharmacodynamics 124:16 142:7 pharmacokinetic 79:3 143:12 144:9 146:24 154:25 pharmacokinetics 3:22 145:2 145:21 153:10 153:11 pharmacological 119:13 320:1 Pharmacology 158:9 phase 11:1 11:4 108:8 108:8 114:2 119:22 119:23 140:8 159:18 220:23 221:22 320:4 phenobarbital 160:21 phenomena 116:24 174:11 phenomenon109:6 phenotypic 97:3 100:20 phosphodiesterase 211:6 photomicrograph 129:8 photoperiod

120:6FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 427

photoperiodic 112:15 phrase 175:10 Phyllis 161:9 physician 6:7 physiological 3:5 110:23 113:16 114:3 114:8 119:1 139:6 141:12 300:14 physiologically 150:2 physiologist 4:4 5:12 physiology4:18 83:1 91:10 pick 18:2 55:23 228:1 picked 221:8 221:8 233:9 233:10 picking322:11 picture 19:3 21:25 pictures 18:18 18:18 pieces 292:22 pigs 161:19 pile 54:24 55:2 59:9 59:17 pipe 245:25 pipiens 198:2 Pittsburgh106:18 106:24 pituitary 38:12 83:22 83:24 84:1 107:11 109:18 109:22 110:10 111:3 112:5 113:7 118:8 119:11 120:15 122:9 123:7 123:8 126:10 319:22 pituitary-gonadal 122:5 pituitary-ovarian 107:16 121:2 PK10:3 81:2 87:12 146:6 placed 7:8 117:13 226:21 placement260:14 places 195:21 234:6 234:25 plan 26:10 146:17 224:17 plane 23:14 304:14 planned

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13:6 149:8 302:18 plowing264:24 plug135:25 plumes 173:9 plus 231:19FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 428

257:25 320:22 pluses 163:24 PNAS 20:16 PND 34:6 103:3 104:23 105:22 105:24 105:25 PND1 26:6 PND120 275:19 276:9 PND220 276:5 PND4 25:24 31:14 37:16 42:12 99:12 POA 113:11 pockets 16:25 point 6:18 8:11 9:16 10:20 11:10 11:16 11:24 12:10 12:18 12:18 13:15 13:18 15:24 25:19 27:23 30:22 44:1 60:3 60:16 60:21 69:4 73:16 73:18 74:15 74:17 75:7 76:25 77:4 81:18 84:5 92:1 92:22 93:20 95:8 98:6 100:1 106:9 136:24 151:14 152:3 155:17 156:20 157:5 161:4 163:15 163:17 170:5 170:20 170:24 174:7 179:19 185:9 186:11 197:8 204:2 212:11 213:21 217:10 223:2 223:5 228:13 228:19 229:21 234:3 236:18 236:19 239:7 239:24 240:21 243:7 244:24 250:13 250:13 267:25 271:13 277:12 279:8 282:9 283:4 288:13 288:19 291:18 295:15 316:7 320:15 pointed

92:25 93:12 166:21 208:9 pointing158:15 213:19 points 9:19 9:20 9:22 9:25 10:2 10:4 10:25 11:5 11:7 11:8 17:2 19:24 21:22 29:19 33:20 34:10 60:4 61:23 74:17 93:16 94:10 133:25 142:12 147:10 147:20 148:5 150:6 159:21 175:8 183:6 232:12 232:14 234:8 234:13 239:4 249:11 262:1 266:1 271:23 280:14 282:5 287:4 295:11 policy248:17 250:8 268:10 274:15 274:17 political 282:12 politics 287:12 pollutants 250:3 polygonal 101:3 polyunsaturated 20:12 pond179:15 195:11 ponds 179:18 pool 170:6 170:25 180:7 pools 169:10 poor 269:17 poorest17:24 205:16 Pope 3:3 3:4 57:20 59:3 59:4 59:14 59:18 59:21 60:15 61:1 61:5 61:9 61:12 62:1 62:13 population 47:11 187:6 189:7 193:22 195:12 198:25 262:16 283:13 populations 252:13 pork 264:8 port43:9 portal 109:21FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 429

110:9 111:3 113:8 122:7 Portier 2:17 2:18 2:19 171:5 290:1 291:5 291:10 portion 116:3 152:13 189:8 portrayal 48:12 Portsmouth3:20 position 225:6 positioned

92:12 positive 29:15 32:16 55:2 108:23 109:3 113:10 115:9 117:24 118:7 120:8 120:13 120:14 120:17 210:19 212:1 316:2 316:8 316:18 316:21 317:4 318:6 319:21 positivity104:15 possibility 123:16 125:22 216:14 299:22 301:17 317:13 possible 23:8 49:22 68:18 69:14 88:1 91:15 142:1 210:1 301:20 316:12 317:7 317:14 possibly 175:13 315:24 post54:16 56:7 57:4 117:15 127:19 140:12 221:9 295:16 295:17 posted 91:7 posting225:10 225:12 postmenopausal 213:3 postnatal 21:11 24:2 27:3 30:11 31:4 31:15 33:24 38:18 46:13 46:19 64:22 67:9 69:19 92:9 99:13 99:14 99:16 99:21 99:25 100:2 100:21 101:17 102:1 102:13 102:25 103:1 104:13 104:19 105:5 105:21 165:15 165:15 postpone 216:24 potable 247:2 potent123:8 potential 47:8 97:5 173:22 180:11 182:15 182:19 184:9 197:23 230:19 261:10 267:4 279:1 282:19 282:25 283:2 303:13 potentially 14:7 17:3 42:13 70:16 96:8 211:25 213:12 279:15 284:5 308:11 poultry264:9 pound252:21pound-and-ahalf 252:22 pounds 212:7 252:20 poured 280:3 ppb 170:10 176:19 176:24 177:7 200:23 ppm 87:5 87:6 147:3 147:3 147:3 164:13 practical 252:2 283:12 practice 266:25 280:19 practices 171:17 255:23 256:17 256:23 257:5 258:11 264:20 280:19 Pragati 310:18 310:18 311:18 311:23 313:8 313:25 314:6 314:9 pre 117:7 162:13 precaution 65:12 265:13 265:14 preceded167:9 precedent-setting 270:23FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 430

precedes 122:18 preceding 136:18 167:8 precise 230:21 235:22 246:22 precisely 172:25 177:19 235:21 precocious 14:23 15:1 predicated

279:10 predict178:22 183:8 238:12 predicted164:5 prediction163:9 predictions 181:24 predominantly 109:1 127:24 predominates 149:20 preeminent220:18 prefer149:18 151:3 151:3 151:15 151:15 289:13 preferred145:15 pregnancies 164:21 pregnancy 24:2 44:9 161:21 pregnant44:7 70:22 97:23 161:21 203:25 215:12 215:15 preliminary180:2 270:3 274:12 prenatal 20:6 20:8 preoptic 84:8 109:10 111:17 111:20 112:2 112:23 113:9 114:18 114:20 115:1 115:5 115:7 115:7 115:11 115:17 115:18 115:24 116:2 116:3 120:4 120:12 316:2 318:10 318:19 319:7 319:11 pre-ovulatory 107:3 108:11 119:22 121:3 159:10 159:13 159:14 160:6 160:12 160:21 161:6 161:12 161:17 161:20 162:20 166:15 166:24 319:19pre-ovulatorylike 113:22 preparation 129:12 195:10 224:21 prepare 322:15 prepared9:1 27:9 54:22 72:1 226:8 prepuberty92:10 preputial 28:21 35:21 35:24 37:22 78:13 159:5 166:5 166:10 238:22 presence 120:9 123:23 149:25 201:23 present8:8 23:9 31:21 38:24 39:16 40:12 53:16 63:13 80:5 82:15 93:17 103:8 112:20 120:19 129:4 131:4 146:22 160:7 170:9 184:17 184:24 189:6 218:14 presentation 7:2 7:3 7:20 7:22 9:2 9:13 13:19 44:3 73:2 75:2 82:24 106:16 122:12 124:17 138:5 140:16 142:8 142:13 143:11 145:7 156:19 167:24 167:25 168:9 168:23 185:14 223:3 258:7 290:13 291:12 291:14 presentations 7:16 73:20 77:9 90:17 106:11 157:7 157:14 157:16 227:23 228:9FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 431

288:16 321:18 321:19 presented32:1 41:15 44:4 58:11 80:23 83:24 84:12 89:25 91:15 121:25 124:3 124:20 138:5 140:15 140:25 144:18 147:23 152:16 154:14 162:22 181:21 185:6 188:5 260:11 275:19 276:2 289:8 290:21 299:20 314:18 322:17 presenter 227:13 presenters 8:4 74:24 90:20 157:1 281:9 288:18 presenting76:3 144:8 145:9 145:17 146:1 148:3 186:6 President 258:22 259:5 press 34:21 34:22 151:7 pressure 221:17 presumably308:19 presumed187:19 pretty8:10 10:11 58:21 138:4 176:23 190:5 217:3 246:13 260:23 260:25 313:10 prevalence 197:16 263:15 prevent212:4 216:17 313:1 prevents 84:18 previous 29:11 55:10 55:11 91:14 94:11 95:14 96:19 96:23 97:8 98:21 106:5 122:23 151:21 152:4 152:25 218:13 222:10 222:19 223:3 226:1 232:18 251:24 309:6 310:24 312:11 previously45:3 94:13 96:2 96:6 96:11 96:15 97:8 101:24 147:23 187:13 267:25 price 226:9 253:21 prices 279:21 primacy182:10 primarily 43:12 108:1 111:12 111:18 118:19 144:20 145:21 241:12 primary14:17 18:25 21:18 109:21 173:16 180:9 183:18 184:5 186:17 260:3 primate 80:13 82:20 82:21 84:9 106:20 110:5 116:16 120:15 315:24 316:20 318:18 319:2 319:8 primates 83:2 83:6 111:12 priming124:9 137:17 primiparas 44:9 principal 108:16 108:18 principally 219:18 principle 262:15 printout173:7 prior 43:6 78:1 104:10 123:3 135:14 139:22 247:13 251:21 273:19 312:23 priori 54:17 57:4 priority 269:5 private 5:16 probability 183:10 255:18 291:23 292:13 probably 7:7 12:16 35:25 41:18 53:13 68:12 73:3 84:25 85:23 89:21FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 432

90:11 90:22 113:2 139:6 156:9 170:15 179:6 182:18 184:11 190:5 193:5 204:6 234:14 237:6 240:3 241:18 251:10 251:22 258:19 271:8 290:20 316:10 316:22 320:10 problem

14:13 23:18 40:22 50:8 237:5 240:23 240:25 243:10 245:7 245:24 247:6 247:9 250:23 250:24 254:9 254:13 257:6 257:12 problems 215:20 242:24 244:13 244:20 245:1 248:24 252:24 257:20 procedure 16:4 19:14 19:15 88:21 152:7 165:1 procedures 99:10 115:8 196:10 196:24 proceed

106:15 121:9 proceeding2:6 219:25 proceedings 7:16 8:15 188:4 188:25 190:23 321:22 322:3 323:2 process 18:9 80:17 92:12 157:12 176:13 220:20 223:22 224:1 224:5 224:5 224:9 225:1 225:5 225:6 225:16 227:3 251:17 259:18 260:9 267:18 269:14 270:13 270:20 280:10 280:25 282:8 282:15 286:21 287:15 processes 83:7 83:11 111:9 145:1 150:8 158:22 159:12 produce 70:12 142:21 160:12 160:16 205:8 253:14 254:1 277:24 303:15 303:22 produced53:15 137:24 200:23 producer 253:9 producers 217:21 218:4 219:2 256:11 258:9 278:3 produces 27:16 60:23 70:13 producing 189:13 299:1 product226:23 251:23 252:3 252:16 253:10 253:23 254:1 254:12 254:16 256:19 257:2 257:13 263:13 263:21 266:16 266:21 production 42:11 159:5 160:13 199:17 202:15 206:2 206:2 211:3 211:22 229:1 265:7 265:22 267:16 269:2 productive 267:15 278:18 products 133:23 205:8 213:7 224:22 252:19 253:16 254:17 256:7 256:24 257:17 257:18 263:24 264:9 278:7 279:22 281:19 281:25 282:3 proestrus 86:12 112:9 140:8 140:19 142:4 142:21 142:25 232:18 296:16 296:17 professional 259:9 Professor 2:24 3:4 3:14 3:20 3:24 4:18 5:3FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 433

5:20 5:25 6:9 91:8 106:23 121:13 151:7 158:9 259:6 profile 144:10 145:5 148:21 149:1 150:19 295:4 profiles 79:14 84:25 148:18 149:2 153:19 297:7 297:9 profitability 263:3 263:8 profound108:21 262:5 262:9 profoundly282:11 progeny93:6 96:9 96:14 96:16 99:8 99:17 102:15 103:12 105:22 106:4 progesterone 85:12 108:2 118:1 123:1 124:9 127:23 127:23 128:11 132:18 159:15 159:18 160:13 160:16 162:14 235:10 235:11progesteroneinduced

133:18 program

3:11 48:1 169:1 170:2 170:7 170:8 172:6 174:10 174:20 175:23 249:21 249:23 282:11 283:8 287:10 292:3 292:15 program(s 196:14 programming 47:8 50:15 programs 8:13 47:22 74:12 78:2 169:2 169:15 169:15 169:15 268:16 Program's 229:7 progress 76:4 78:15 78:16 progressed

75:24 progresses 301:3 project80:6 82:8 111:15 126:22 188:22 188:24 191:22 projects 255:11 prolactin 38:6 64:11 64:16 64:17 66:2 66:5 66:7 66:8 66:12 67:1 67:1 67:2 85:13 128:3 128:4 128:5 proliferating 22:12 proliferation 24:4 97:16 97:18 103:24 104:13 104:17 104:20 104:25 105:3 105:4 105:24 210:20 proliferative 22:18 22:24 104:7 prolongation 142:23 prolonged 135:22 141:13 prominent275:21 promised124:18 promote 211:22 211:22 promotes 213:12 prone 25:7 pronounced

305:15 proper307:16 properly 92:2 190:2 273:25 281:22 properties 212:21 307:10 proportion70:8 101:10 187:5 187:7 208:24 210:18 proposal 157:5 proposals 278:25 propose 156:16 proposed76:25 128:20 128:21 130:22 130:24 187:11 229:20 pros 96:20 prostate 14:3 28:4 28:10 28:14FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 434

28:18 28:20 35:6 36:1 38:25 42:25 43:2 43:16 43:18 47:10 58:10 58:14 58:16 58:19 63:1 63:2 209:3 209:11 209:15 209:16 209:22 215:15 272:4 275:2 275:3 275:4 275:8 275:12 275:13 275:17 275:22 275:24 276:1 276:4 276:6 276:9 276:12 prostate/ mammary215:10 prostates 275:1 276:3 276:10 prostatitis 38:18 209:6 209:6 prosthetic 36:7 prostrate 24:25 protect214:21 214:24 241:18 262:22 282:3 protected208:5 protection7:17 74:23 76:1 229:9 274:14 281:19 290:22 protective 46:21 protocol 99:19 protocols 286:23 proudly281:18 provide 81:19 82:19 155:24 184:2 196:8 196:21 196:23 283:12 283:19 285:23 286:25 287:24 322:20 provided82:9 196:15 207:21 220:2 225:23 284:8 286:21 306:22 provides 77:1 providing 223:23 258:3 268:13 278:8 278:16 287:21 Pruitt130:22 131:3 Pruitt's 125:24 PRZM 168:20 175:4 178:21 178:22 181:20 182:13 182:22 184:7 pseudo-steady 12:13 155:12 236:2 pubertal 24:2 28:22 pubertally142:18 puberty15:1 15:9 22:15 22:20 92:16 136:7 136:20 159:2 159:6 166:6 public 5:21 7:1 7:4 7:6 7:9 7:23 7:25 8:4 13:16 72:21 73:20 73:22 74:21 74:22 90:15 156:18 156:21 157:1 157:8 157:13 184:21 184:23 185:10 204:18 217:11 217:17 220:13 228:14 241:19 262:20 264:12 267:23 268:2 270:16 271:4 271:13 277:5 277:7 277:8 283:17 284:8 286:1 286:15 288:14 288:15 288:21 289:1 289:7 290:25 320:16 322:13 322:17 322:22 publication 62:24 63:1 151:7 187:20 191:5 230:12 239:16 270:14 315:5 315:6 publications 178:24 public-health 241:17 publicly 34:23 34:23 290:7 publish272:17 published20:15 72:14 117:12 165:13 178:10 188:1 188:4 188:24 189:8FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 435

190:23 191:4 191:6 194:10 194:24 197:10 199:18 200:19 202:17 204:11 207:23 208:10 210:12 212:16 229:3 230:6 publishing189:3 Puerto 278:2 pull 305:11 315:9 pulled 194:21 pulsatile 82:22 83:7 84:16 84:18 110:20 117:20 122:13 124:19 124:21 124:21 132:3 132:21 133:14 134:13 158:25 159:3 159:20 159:21 166:25 167:5 320:7 pulsatility 110:25 111:7 pulse 110:21 111:1 117:20 119:25 125:6 125:9 133:10 133:11 159:24 319:25pulsegenerating117:2 119:20 121:1 pulses 119:1 119:24 124:25 125:5 125:10 125:15 132:16 132:23 133:1 133:7 pumped 174:15 puncture 140:9 pup 25:20 33:9 39:11 42:5 46:20 49:1 312:9 pups 25:15 25:18 26:6 26:7 26:11 26:18 26:20 31:7 31:13 33:11 36:24 37:15 37:16 45:18 45:19 45:20 46:1 46:2 49:9 49:11 49:15 49:23 61:22 62:2 69:8 94:21 95:1 136:6 164:23 164:23 165:3 165:8 215:16 312:2 312:14 312:16 312:17 312:18 312:19 312:23 313:1 purple 22:4 98:17 purpose 89:4 148:2 153:12 176:15 178:20 182:23 182:24 184:8 274:20 282:23 purposeful 238:8 purposes 233:13 276:17 276:17 pursue 220:8 purview279:1 push 75:7 putting200:14 312:23 PVN129:2 129:7 129:9 Q qualifies 239:18 qualitative 52:19 quality71:1 95:25 100:14 172:24 220:19 223:19 247:17 269:17 271:24 272:8 272:10 273:3 273:16 286:12 quantified 97:13 155:21 quantify 97:15 151:19 152:20 quantifying 259:10 quantitation 154:22 154:23 quantitative 52:21 93:22 95:23 97:1 100:9 100:17 146:3 155:17quantitativeminded 149:17 quarter 227:21 quarterly 286:2 question 9:11 13:7 44:19 45:17 47:3 48:25 49:10FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 436

57:7 58:10 64:6 64:24 64:25 65:16 69:24 70:11 71:12 76:7 82:18 88:4 88:12 89:13 94:7 116:15 128:15 131:20 137:21 141:14 143:19 160:10 160:24 168:21 169:3 178:15 181:17 183:9 184:16 188:10 188:14 233:1 243:24 245:6 273:8 276:20 282:17 289:5 290:1 291:5 291:15 291:18 293:6 294:20 294:21 294:22 295:22 301:12 302:16 304:12 304:24 305:14 306:14 307:12 309:5 310:2 311:3 313:18 313:18 314:13 315:18 315:20 316:1 321:25 questioning 143:24 questions 7:22 8:21 8:22 9:8 13:14 44:2 46:11 47:19 51:14 51:17 57:17 57:21 70:3 73:3 73:4 74:19 76:8 79:13 82:5 90:19 90:22 106:10 158:3 168:18 171:4 184:3 184:14 184:22 188:7 194:7 194:18 225:10 231:9 270:1 270:2 270:4 271:4 273:14 286:10 288:18 288:21 289:10 289:14 289:16 289:20 289:24 290:9 290:10 290:12 290:19 290:22 291:1 293:7 320:24 321:10 321:16 322:15 322:16 322:23 quick 16:4 51:17 70:3 77:12 219:11 293:7 quickly15:20 65:11 84:22 122:1 150:10 150:24 154:20 241:20 263:17 quiet 26:9 65:3 quite 7:7 35:18 156:6 178:14 178:22 198:19 200:17 224:14 234:3 234:5 258:1 260:21 292:12 294:2 312:13 quote 195:20 198:15 221:21 274:11 274:12 275:16 quoted 221:2 quoting276:5

R rack 311:19 radiofrequency 115:6 radiolabeled 144:20 rainfall 176:3 raise 210:1 245:5 277:24 Raised 198:3 raises 128:15 131:20 137:21 141:14 246:20 Ralph 25:10 125:24 230:3 301:13 301:25 ran 170:2 221:7 227:3 Rana 198:2 ranchers 281:20 ranches 278:1 random 62:12 86:16 192:10 randomly 21:2 105:9 range 64:16 64:17 66:2 66:10 66:11 66:15 66:23 136:18 176:16 176:19 212:12 236:13 237:4 237:8 237:18FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 437

299:18 302:12 302:14 ranges 66:14 86:21 ranging31:14 127:2 197:24 ranid197:23 Ranidae 199:7 ranked 59:6 61:13 rapid9:25 24:3 27:13 41:25 78:12 85:6 126:15 128:12 148:20 154:8 155:9 155:10 rapidity 156:5 rapidly27:24 123:19 148:18 148:19 155:2 rat15:23 15:24 25:4 25:11 29:23 38:20 40:6 42:20 46:18 48:4 50:13 55:13 86:9 89:6 91:17 92:21 107:24 111:16 112:18 112:25 113:21 114:11 115:8 116:23 117:1 120:21 126:13 146:1 146:16 150:18 150:19 160:20 272:3 275:1 299:21 315:24 316:2 317:7 318:14 rate 10:5 10:13 14:25 145:24 256:15 rate-limiting 212:18 rates 148:23 150:11 150:25 152:21 155:18 189:24 266:25 rather81:25 86:2 163:18 257:16 289:19 292:20 301:1 ratio 32:5 151:19 152:9 152:10 152:12 152:14 164:20 193:9 rationale 45:7 233:8 ratios 152:1 198:1 rats 25:13 44:8 56:15 71:19 71:22 72:6 72:13 97:24 123:2 125:3 125:3 127:7 131:8 131:14 132:5 132:22 135:4 139:15 140:20 142:5 142:15 142:22 146:10 149:18 150:13 150:22 151:3 151:15 152:22 153:18 155:20 160:20 161:11 161:14 163:16 165:11 201:13 202:18 202:22 203:3 203:16 210:9 210:17 215:9 215:14 237:7 252:5 294:3 296:24 310:8 312:2 raw77:14 77:16 148:4 149:7 169:13 170:5 170:15 170:16 170:22 196:10 196:21 197:4 233:18 234:8 243:24 247:3 247:17 248:18 250:7 282:18 282:22 283:1 283:10 284:5 284:10 286:19 292:14 raw-water 249:3 284:12 284:19 Rayner26:3 28:2 36:8 36:25 41:6 44:24 58:14 58:15 68:15 94:15 97:23 275:1 275:2 reach 39:18 155:11 reached

138:17 154:21 189:9 198:18 reaching267:11 reaction 224:3 reading67:14 ready 13:19 54:23FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 438

74:21 real 72:19 72:23 123:15 206:16 232:5 240:1 252:18 realistic 72:21 154:5 reality182:11 224:4 282:24 realize 33:6 77:1 252:16 262:15 Realizing86:22 really10:15 12:9 18:21 21:12 21:24 21:25 23:23 25:7 25:14 29:10 34:14 45:10 47:2 64:15 66:15 69:13 71:17 76:2 82:7 95:22 109:5 110:23 110:23 151:23 153:11 168:20 173:25 174:6 177:12 178:13 182:16 182:25 189:11 197:1 197:6 218:18 229:15 231:6 231:12 233:10 233:21 235:4 235:19 236:2 237:14 237:21 237:23 238:10 239:3 239:12 239:17 250:10 250:13 250:17 250:21 257:3 260:23 261:3 276:14 303:2 303:6 303:8 316:17 reanalyzed

141:19 reappearance 124:8 124:10 reappearing82:24 reason14:12 33:25 34:7 46:2 110:6 206:11 220:8 233:11 238:7 253:2 254:3 257:1 278:17 283:18 298:18 303:2 305:2 311:20 reasonable 67:23 173:5 219:19 219:22 220:5 reasons 25:9 26:4 70:14 153:25 213:20 213:21 257:2 reassembled 259:22 Rebeckah281:9 281:14 281:16 287:22 288:2 288:6 288:9 recall 49:11 receive 96:23 251:11 received30:3 251:13 287:6 306:23 309:16 recent14:21 15:7 63:1 93:11 125:23 151:7 201:19 280:23 282:6 recently 185:24 188:25 195:23 197:25 207:22 230:14 292:19 receptor 27:9 27:13 27:13 47:11 210:19 212:1 316:16 receptors 316:17 317:24 318:4 recess 74:2 157:10 228:11 recessed323:2 recession 278:13 recognition 231:11 recognize 217:22 recognized

303:3 recognizes 283:5 recoil 262:5 recommend17:2 184:4 recommendation 182:21 recommendations 287:1 287:13 recommended

23:12 recommending 230:10 reconsider18:14 reconstructedFIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 439

115:25 reconvene 73:17 156:17 228:8 record 18:6 170:19 195:19 197:3 226:16 266:10 266:12 310:17 312:8 recorded51:13 169:24 169:24 275:15 records 226:2 recover 203:10 recovering195:13 recovers 84:22 203:8 recovery 84:23 84:24 124:14 203:7 303:16 red31:11 104:3 148:25 150:18 163:24 195:6 214:1 311:22 redrew317:3 red-stained 123:14 reduce 119:17 122:24 142:14 159:6 198:2 257:21 257:23 reduced

119:16 133:12 177:15 189:19 189:21 201:22 257:6 257:7 257:19 308:21 308:23 reduces 133:19 243:22 reducing119:10 144:25 reduction 88:7 99:5 131:11 159:24 159:25 160:1 187:22 266:25 305:13 reductions 256:16 redundant279:7 279:25 re-emphasis 247:15 re-evaluate 18:2 re-evaluation 2:7 74:6 279:7 re-examined 279:11 reference 59:24 60:4 315:13 referenced

144:17 145:14 222:23 223:14 referencing68:20 referring62:1 63:25 292:24 refined

168:22 184:8 refinement178:18 reflect98:17 reflection105:7 reflex41:20 refused

196:4 197:5 refuses 195:22 Reg287:23 regard 64:10 88:15 90:3 117:6 145:21 154:14 169:2 241:5 242:17 242:24 243:2 244:1 249:17 250:20 272:6 275:3 286:11 regarded15:5 regarding61:13 62:18 70:3 95:14 121:16 240:12 294:23 regardless 135:16 142:9 248:25 250:19 regards 52:18 209:11 210:7 240:11 276:17 regimes 175:15 181:14 region75:14 100:24 116:13 318:10 regions 84:8 register 281:18 registered

266:22 281:21 Registrant 73:24 212:10 219:8 266:22 registration 224:24 261:14 regrettably 165:11FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 440

Regrown 29:9 regular 139:23 234:18 234:23 237:2 282:7 284:16 regularly 122:14 regulate 250:3 274:1 274:6 regulated78:11 88:15 108:14 regulates 122:5 159:22 regulating 107:6 121:17 128:16 130:23 287:11 regulation 43:19 75:20 107:2 108:24 166:12 166:25 261:7 265:16 265:23 276:18 regulations 283:18 283:24 284:3 285:23 318:20 regulatory5:9 75:13 88:14 223:25 235:20 240:25 250:7 269:8 269:14 271:15 271:19 274:20 277:4 280:1 289:23 reiterate 263:21 reiterated

304:8 reject220:5 rejoin157:6 rejoinder 322:21 relate 80:17 82:5 85:15 110:8 158:13 164:14 289:15 291:8 related

87:8 90:18 158:23 166:23 167:8 241:13 243:15 251:20 276:1 289:5 289:12 relates 82:22 88:25 289:9 304:24 315:20 relating106:16 106:17 320:25 relation 2:16 Relations 277:14 277:18 relationship 86:20 87:14 112:14 203:22 213:10 relationships 144:24 178:4 relative 20:22 86:1 89:23 103:8 147:2 152:2 214:3 214:5 260:14 265:15 276:7 307:25 relatively 102:5 122:1 223:20 239:13 269:17 relaxed

147:15 150:7

relayed

113:7 120:6 release 42:6 42:8 85:5 110:20 116:19 117:15 122:13 125:4 released34:20 42:3 70:24 71:2 88:8 269:21 270:10 274:13 relevance 53:10 120:22 relevant24:23 63:21 93:17 120:23 120:25 150:2 167:1 172:2 173:7 188:3 199:21 208:15 reliable 272:13 reliance 261:10 reliant263:12 relied 269:7 269:16 religiously235:8 remaining30:16 73:4 99:17 189:16 244:21 313:12 remains 278:18 317:10 remarkable 167:11 remarks 224:11 322:20 remember 50:25FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 441

66:12 67:12 116:2 117:4 133:25 279:13 309:17 remind 81:24 89:4 127:16 135:1 135:2 282:4 remote 216:14 removal 25:18 42:5 84:22 124:10 remove 124:4 131:25 312:25 removed

16:1 26:6 26:12 95:24 117:5 141:19 repeat18:9 49:21 59:5 191:7 266:1 307:11 repeated85:14 123:4 198:12 repeating191:5 231:25 repeats 118:2 replace 153:6 180:2 replicate 82:12 replied

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269:15 request265:25 requested273:21 require 178:18 179:1 199:13 270:3 272:11 320:5 required93:23 160:16 182:23FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 442

196:8 230:20 272:8 272:9 272:16 273:4 284:25 285:3 286:2 requirements 24:13 241:2 242:16 244:3 283:25 284:15 requires 173:23 181:15 182:17 183:16 283:15 285:4 re-registration 224:21 225:6 re-review78:24 219:17 225:5 269:12 269:16 280:1 286:20 research4:15 4:16 5:5 5:12 6:17 39:25 76:4 76:18 77:2 78:15 78:17 79:1 80:5 80:19 82:10 83:16 86:5 86:6 89:10 91:21 121:21 146:7 182:16 185:21 186:10 196:11 196:16 239:4 268:25 310:14 310:19 researchers 21:6 re-sectioning 22:2 reserve 162:20 166:14 reservoir 181:9 247:22 reservoirs 173:9 174:5 180:17 255:2 resets 182:11 Residence 6:6 residual 245:7 246:19 residue 172:11 173:18 282:25 284:6 residues 168:11 168:12 170:22 171:6 183:7 292:16 resistant 137:11 254:11 254:20 263:11 263:16 resolution152:18 175:4 175:6 resolve 89:12 resolved105:22 152:16 Resources 255:12 259:7 respect47:19 57:22 58:10 89:24 95:8 102:9 102:23 103:3 103:25 104:22 222:20 263:14 respected269:8 respectfully 260:5 respective 98:15 241:17 respectively 234:1 respond

85:10 117:16 222:23 225:19 270:17 responding83:25 response 37:4 62:23 84:14 84:14 85:3 85:6 85:9 85:11 85:23 86:21 102:19 122:17 127:21 127:22 127:25 128:7 128:12 137:17 162:24 197:13 200:9 202:18 293:9 294:3 295:13 303:19 308:13 308:15 313:24 responses 131:9 131:16 138:13 225:13 313:23 322:15 responsibility 260:3 responsible 79:24 89:13 responsive 93:1 96:7 126:14 137:22 responsivity 47:12 rest26:11 52:4 147:14 247:10FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 443

275:11 300:10 restraint129:14 restrict305:18 restricted

209:21 restricting 305:21 restriction 25:16 42:4 308:3 308:21 309:2 restrictions 280:25 result96:6 108:21 122:18 138:7 139:8 141:18 159:4 159:24 163:10 167:3 203:5 238:20 255:21 264:15 264:16 267:5 267:14 280:25 resulted255:23 resulting160:1 187:14 187:16 270:22 results 28:24 33:8 46:12 46:17 49:20 51:20 101:13 127:14 131:6 138:22 140:17 144:8 148:3 150:16 151:4 151:5 151:6 155:19 159:11 162:4 164:6 165:4 170:18 170:22 181:1 198:18 257:4 257:25 282:18 314:19 retired

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3:19 3:19 4:24 4:24 9:15 9:23 10:9 10:14 10:17 10:24 11:2 11:13 11:17 11:22 12:5 12:8 12:15 12:22 Richards 178:11 Rico 278:2 right-hand

107:18 rigidly8:10 113:5 rigorous 284:23 287:15 rinse 16:15 16:18 rise 264:11 rising122:17 risk 5:10 5:18 6:17 63:16 71:5 71:13 71:15 76:11 80:17 89:17 144:25 166:22 176:13 219:21 229:5 265:15 265:18FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 444

265:19 265:20 283:2 284:24 risk-assessment 235:20 risk-based

282:8 River 25:5 171:23 195:5 riverine 248:2 rivers 169:13 255:25 Riverside 3:16 RNA 294:8 294:10 road248:15 Robert121:11 293:3 293:13 293:19 293:23 294:6 294:13 294:16 295:6 295:14 296:2 296:8 296:11 296:15 297:1 297:15 297:22 298:1 298:3 298:6 298:9 298:12 298:14 299:4 299:11 299:14 299:17 300:2 300:17 301:21 302:2 304:15 317:18 robust77:13 77:21 116:22 252:13 robustness 77:19 Roby 4:10 4:11 Rock 177:2 Rod217:11 217:14 217:14 267:25 268:3 268:6 268:9 271:6 271:10 rodent80:13 82:20 83:5 83:12 89:5 106:20 107:3 107:18 110:5 112:2 112:7 112:16 112:24 113:4 113:12 115:11 116:13 117:9 120:4 120:23 121:10 121:19 122:6 122:15 124:22 124:25 126:1 161:6 166:22 316:19 317:16 317:16 318:4 318:9 319:9 rodents 83:2 88:18 111:11 111:22 114:21 158:20 161:10 167:20 204:5 210:14 217:2 Rodriguez 10:6 10:10 10:15 10:22 10:25 11:11 11:15 11:18 12:3 12:12 12:20 13:1 13:10 144:18 Rogers 50:20 role 2:12 43:7 84:13 111:20 114:20 174:7 236:7 258:24 260:14 roles 50:15 rolling78:9 room 26:9 44:17 65:3 65:3 190:4 193:17 251:22 264:8 311:14 311:22 311:24 321:16 rostral 109:9 111:21 113:10 115:1 rotate 263:20 rotating65:22 roughly46:19 61:7 90:8 170:13 177:6 186:23 round-robin 71:16 72:4 97:17 289:19 routes 139:25 145:22 routinely 312:2 row295:24 rubbing312:22 rule 9:17 182:2 242:6 242:7 rule-based

182:3 rules 241:14 242:4 run 62:8 109:24 244:4 245:25 running141:5 143:10 156:14 250:25 278:14FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 445

320:6 runoff 248:1 runs 54:19 rural 262:9 262:10 268:20 279:24 rush 224:2 225:5 270:7 rushed 270:14 Russ 80:4 82:6 91:1 91:3 91:4 304:23 305:10 305:25 306:7 306:20 307:1 307:11 307:20 308:7 308:10 308:18 308:24 309:21 310:1 310:13 Russo 23:1

S sacrificed 127:3 127:7 sad311:10 safe 169:20 241:1 241:7 244:2 250:14 260:24 267:12 278:8 280:10 281:24 283:15 283:24 284:11 284:25 287:2 287:16 safer 266:9 safety79:25 261:2 269:9 285:8 285:15 sake 55:15 60:12 sales 195:7 saline 151:20 152:2 152:11 salmon199:20 199:22 200:6 200:8 200:9 sample 12:11 56:17 64:15 95:10 96:14 96:16 96:18 113:19 113:19 113:20 170:25 171:23 sampled

100:2 136:12 138:16 140:8 183:11 183:11 284:3 292:9 296:17 296:19 samplers 256:10 samples 12:1 64:13 77:14 77:15 77:15 78:3 82:1 95:25 96:1 96:22 100:13 104:10 124:23 147:19 148:15 169:12 169:21 169:22 169:23 169:25 170:5 170:6 170:15 172:20 172:22 193:3 196:18 283:12 284:18 292:15 296:21 315:9 sampling82:1 86:11 99:8 99:19 99:23 105:11 119:22 123:4 124:22 132:15 135:14 147:7 147:9 147:15 150:6 156:19 169:2 172:19 173:1 173:4 173:6 175:15 179:11 181:12 181:14 181:18 239:11 250:23 283:21 283:25 287:4 291:8 314:20 314:22 314:23 San 5:13 40:2 Sanderson 206:22 211:8 212:24 SANDRA 4:17 64:7 64:20 65:14 65:17 66:1 66:11 66:19 66:24 67:5 67:7 67:22 68:1 69:12 69:17 69:21 295:22 296:3 296:9 296:13 296:23 297:8 297:13 297:17 297:23 298:2 298:5 298:8 298:11 298:13 298:18 299:5 299:13 299:15 299:19 300:16 300:19 315:17 315:20 317:22 318:12 318:22 319:1 319:4 319:23FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 446

320:9 320:12 Sandy 4:18 113:13 Santa 5:3 SAP 8:3 41:8 75:4 82:4 122:1 124:4 124:20 127:1 127:13 128:21 130:21 138:6 157:13 169:6 181:21 183:4 188:6 196:6 196:7 217:18 218:14 218:16 219:14 219:25 221:21 222:7 222:14 222:15 222:15 222:16 222:25 223:18 224:10 225:9 225:24 227:2 228:14 242:14 258:20 268:11 269:20 269:21 270:10 270:16 273:1 273:15 273:20 277:11 280:3 280:6 282:16 286:11 286:25 287:10 304:8 SAPs 218:13 222:10 222:25 223:23 273:23 SAP's 286:17 sat216:16 222:16 satisfactory 90:20 satisfied74:16 321:16 save 90:24 289:13 saves 258:9 258:9 saw26:24 27:8 27:11 28:4 28:18 29:1 29:3 29:22 30:12 30:16 30:17 31:23 33:21 35:4 35:8 35:12 35:24 36:5 36:8 36:11 36:12 36:19 37:8 37:15 37:20 37:24 38:3 39:23 42:12 51:1 51:3 58:23 59:2 71:25 72:12 102:12 103:5 103:12 103:16 104:23 106:2 130:13 141:8 200:10 207:23 234:14 299:3 299:7 scale 19:23 20:6 20:13 20:24 20:25 21:14 57:13 59:7 96:22 153:6 175:7 177:13 177:13 178:19 178:20 180:5 181:3 278:3 280:2 scaling11:6 54:16 54:17 152:23 153:7 Scandinavian 14:24 scans 17:7 scattered60:6 scenario 17:19 39:6 60:1 scenarios 145:4 153:5 181:23 scent 313:1 schedule 14:1 147:7 147:9 147:15 150:6 184:22 243:3 scheduled7:20 45:1 73:22 74:22 75:3 217:11 217:17 224:21 277:5 281:8 288:14 schedules 280:4 scheduling217:18 schema120:4 schematic 107:5 Schlenk 3:13 3:14 Scholar 6:5 school 5:5 16:6 259:7 259:8 Sci 30:4 science 2:6 3:21 4:25 74:5 75:19 75:23 75:24 76:17 91:10 121:14 158:10 182:8 225:20 252:16 254:23 255:16 256:4 259:8 260:12 261:6 261:7 261:8 262:2 265:9 265:11 270:7FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 447

282:12 282:14 285:9 286:16 287:1 287:12 287:23 289:12 289:12 Sciences 3:5 3:6 3:15 5:21 13:21 91:19 144:13 188:5 189:1 190:24 scientific 2:1 7:17 73:19 78:21 79:8 144:1 160:4 216:20 216:21 220:13 222:24 269:14 270:11 271:25 272:7 278:10 280:13 280:14 282:7 282:10 284:1 287:11 scientifically 218:17 219:3 220:17 273:10scientificbased287:14 scientist6:1 251:8 252:4 258:20 scientists 40:19 79:10 80:2 157:15 185:12 185:25 212:17 212:24 220:18 222:17 260:16 SCN317:11 scope 17:7 48:13 48:17 169:7 score 18:7 18:8 18:10 18:19 18:20 39:5 52:4 52:20 53:6 56:4 96:23 scored 29:6 51:24 55:11 55:12 60:3 scorers 18:15 scores 15:12 17:24 18:13 18:14 18:17 52:5 52:8 55:21 57:23 scoring20:1 35:14 47:19 52:19 54:9 54:18 54:19 59:6 60:12 Scott 271:14 271:16 271:17 271:17 scratch18:11 18:12 screen35:1 236:15 SDWA 170:10 se 12:14 306:9 searched160:3 season170:15 seat225:18 225:18 seated 6:15 SEAWAVE 168:20 182:14 182:22 184:7 second 2:5 11:3 56:4 65:16 74:4 80:4 126:6 146:13 149:22 185:10 208:10 215:21 243:17 244:24 271:25 274:2 313:10 secondary 92:14 109:22 126:3 134:12 202:13 279:22 Secondly 80:7 82:6 253:12 seconds 65:7 65:9 Secretary 277:11 secrete 107:9 107:11 111:4 122:7 126:11 secreted108:1 108:2 109:21 122:12 127:24 162:17 secretes 126:9 secreting46:20 46:23 secretion 108:3 108:14 110:1 110:13 110:15 116:20 117:4 120:22 121:18 122:8 124:19 124:21 124:21 125:16 125:18 126:12 128:17 130:3 132:2 132:8 132:21 133:14 134:13 158:25 159:4 159:18 159:20 159:22 159:22FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 448

160:16 162:14 163:8 165:16 166:1 167:1 167:5 167:8 secretions 108:6 111:2 secretory 121:18 125:19 132:3 133:16 167:4 section 23:17 23:21 26:3 29:9 30:6 115:25 129:8 157:24 190:9 194:21 194:21 sections 17:10 17:11 22:6 23:13 28:15 secure 219:3 sedimentation 265:2 seeded 221:5 seeding221:7 seeing28:14 177:9 200:12 207:8 252:24 seek 240:23 260:17 260:18 seeks 284:14 seem 38:20 40:13 42:25 48:11 84:19 134:14 134:23 137:11 139:3 142:16 142:25 308:9 308:22 seemed 54:15 56:10 232:8 235:8 237:17 302:11 302:13 seems 9:23 37:22 54:13 66:15 83:24 84:13 92:2 249:14 270:6 280:16 295:11 seen 98:24 106:3 131:21 167:12 191:14 193:20 194:16 195:20 199:23 200:7 204:4 209:12 210:13 231:4 238:14 250:10 254:4 282:6 SEER 14:21 sees 271:4 selected21:2 314:22 selecting11:20 self 97:15 103:23 105:23 313:2selfproliferation 97:6 97:10 100:10 104:8 104:22 105:12 self-serving 195:18 sell 213:6 selling213:15 sending226:7 Senior79:7 79:23 168:4 310:19 sensationalized 282:12 sense 59:6 212:6 236:24 266:3 294:12 sensitive 14:3 37:23 40:14 40:25 41:2 41:11 43:1 214:20 214:22 214:24 sensitivities 90:2 sensitivity 29:8 123:7 123:8 151:24 191:11 230:19 separate 22:9 37:2 98:7 98:11 180:17 187:10 232:5 289:14 311:7 separated49:2 separately236:23 separation 28:21 35:21 35:24 37:22 78:13 159:5 166:6 166:10 238:22 September 2:3 243:8 sequelae 298:23 sequence 106:10 sequential 236:3FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 449

serial 239:10 series 90:19 123:6 126:1 127:10 129:1 135:19 135:21 138:24 139:13 165:22 180:15 241:8 272:23 315:11 serious 69:2 282:6 seriously 263:3 263:13 serum 37:25 64:11 159:25 165:17 serve 77:17 219:6 260:14 283:23 served 226:6 Service 283:5 serving2:12 session 7:6 18:5 71:13 73:23 73:23 74:5 79:15 81:10 sets 18:13 71:23 78:7 231:19 285:16 315:9 seven 71:18 71:23 72:6 72:6 72:7 72:8 72:8 313:9 several 15:1 29:19 33:10 41:6 117:21 118:18 122:3 122:23 123:2 145:20 162:4 215:12 255:3 286:5 312:5 severe 190:21 238:19 238:20 severely 95:1 189:21 severity 29:2 29:3 29:6 35:12 35:13 35:17 35:19 209:6 276:3 276:8 276:11 sex188:12 198:1 198:21 202:13 208:7 sex-organ 238:22 sexual 69:16 81:8 92:19 112:23 197:14 197:20 197:24 199:3 Sexuality 197:17 SF-1 211:10 211:15 sham 133:11shamadrenalectomized 132:10 132:25 Shanna203:20 shape 148:21 168:16 169:1 175:10 176:5 178:8 178:9 178:18 179:7 180:1 183:23 184:1 shapes 179:8 share 195:22 196:4 197:5 221:19 225:22 261:9 shared 196:9 221:20 222:9 sheep 110:5 110:6 sheet 281:6 Shelley5:24 5:24 shift 45:10 248:17 250:9 shifting250:7 shipped

44:12 shock 245:13 248:4 Shores 226:19 short 45:11 73:19 85:9 86:15 161:1 224:13 225:9 258:6 263:12 303:8 shorter 29:13 41:2 76:19 76:20 76:21 shorter-term 169:4 181:18 shortly136:2 277:9 293:5 short-term

78:5 142:13 short-tern175:14 showed 9:17 9:17 31:1 32:15 38:2 110:3 115:21 123:9 123:10 135:11 149:8 164:15FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 450

169:6 174:3 177:20 178:2 186:20 187:20 189:20 190:22 194:11 200:18 200:22 201:12 203:20 206:5 206:19 207:5 207:25 208:11 208:14 208:18 210:17 210:22 296:16 showing41:10 41:24 81:21 122:25 125:22 139:23 141:1 160:19 162:9 165:14 191:20 197:10 201:1 202:18 202:20 203:2 203:16 206:21 215:13 216:8 236:19 308:13 shown 15:25 19:7 19:13 22:5 22:25 27:10 30:15 31:9 36:9 37:10 38:13 39:3 39:7 39:11 41:1 66:25 72:5 84:17 92:9 107:17 107:17 107:20 110:4 110:9 114:13 116:18 117:10 124:11 135:15 137:2 152:20 165:4 175:6 178:23 179:10 187:8 194:2 194:24 198:5 198:10 198:14 199:4 199:11 200:3 201:18 202:21 206:25 208:7 208:17 210:10 210:16 211:8 211:16 215:13 215:15 256:12 284:17 shows 135:23 165:25 166:16 177:15 195:6 208:23 217:16 232:21 293:25 siblings 30:25 39:13 68:25 sick 241:20 Sielken 77:7 91:22 sign 259:23 signal 113:5 113:21 114:8 114:12 117:17 120:5 signed 19:14 significance 34:9 196:14 significant24:16 27:11 27:20 28:25 29:2 29:5 31:8 33:8 34:11 35:18 36:15 41:4 69:9 72:5 80:25 94:14 94:20 97:9 97:13 98:20 99:2 99:5 100:4 102:13 103:6 103:13 104:24 105:4 105:13 105:23 129:24 140:22 141:9 163:4 166:2 166:5 187:22 196:13 203:22 211:18 236:7 238:17 245:11 248:17 257:8 275:2 276:6 295:19 296:20 304:20 304:24 305:13 307:7 307:17 significantly 31:12 35:10 135:18 189:19 192:6 193:6 305:6 306:17 313:23 silly 188:10 siltation 265:1 simazine 261:21 similar 32:1 32:4 35:8 50:6 50:7 65:19 70:12 70:14 83:8 118:21 125:15 126:8 127:22 135:11 148:17 148:21 151:10 155:7 165:10 178:4 196:16 198:13 198:18 201:1 202:20 206:25 208:2 273:12FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 451

similarities 43:2 43:14 similarly 104:16 131:15 134:7 137:7 137:14 137:18 141:3 165:17 172:25 Simpair 317:18 Simpkins 81:5 157:22 158:7 158:8 158:8 167:24 321:24 Simpkins's 88:24 simple 173:19 249:25 simply62:22 81:23 105:7 162:19 162:23 166:2 167:16 213:6 218:19 222:16 247:25 250:22simulationfitting148:6 simultaneously 221:8 Sinai 40:1 sincere 75:22 single 17:25 48:11 78:4 78:8 150:14 210:22 249:9 sinister 213:9 sir 60:20 62:16 62:25 91:7 143:21 144:3 156:14 198:15 216:19 227:16 sit16:22 51:22 52:14 260:3 266:8 site 111:24 118:6 124:1 168:14 172:14 176:24 274:11 292:21 318:6 318:6 319:21 sites 128:20 174:11 176:20 176:20 195:6 site-specific 173:13 174:11 247:1 249:18 249:24 sits 109:10 116:4 sitting225:17 227:21 228:25 situation 17:17 72:10 120:24 120:25 301:17 312:8 situations 39:6 243:6 250:1 six15:25 18:21 32:24 138:12 163:22 220:11 259:21 303:11 sixth 15:25 size 19:8 19:9 101:6 172:7 180:14 183:12 184:5 201:22 202:10 203:6 203:9 203:10 247:20 278:3 sized179:18 242:19 sizes 170:25 313:12 skin 214:23 skipped

242:20 267:24 skull 109:25 skunk 221:12 225:25 240:12 Slaughter 271:14 271:17 271:18 276:24 277:1 277:3 289:22 sliced 17:10 slide 9:16 16:21 17:23 18:6 56:13 63:16 77:9 91:6 92:2 92:8 113:25 121:12 137:24 158:20 164:9 169:6 183:2 226:1 226:10 240:13 295:2 297:3 302:17 302:25 303:5 304:6 304:7 304:7 304:17 304:19 305:11 306:15 309:10 309:11 310:7 314:23 315:21 slides 7:3 16:9 16:12 16:15 16:19 16:24 17:1FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 452

17:9 17:16 17:18 17:21 17:21 17:24 18:10 51:19 54:9 55:9 55:19 56:5 58:11 60:3 60:5 71:19 71:23 71:24 72:1 72:1 153:8 153:9 163:14 168:2 191:3 259:16 294:23 295:12 slight30:22 37:8 slightly 22:13 141:17 148:22 slope 10:7 10:12 slowed 27:12 slower148:22 slowly139:17 small 23:23 36:20 50:23 68:11 99:5 102:13 104:24 105:20 105:23 172:10 176:22 177:13 178:19 180:21 181:5 218:5 224:12 245:1 257:9 257:12 263:6 263:6 294:3 smaller 21:14 24:17 24:18 69:11 78:7 172:8 177:23 180:23 192:19 203:4 203:13 237:10 245:18 246:13 248:3 smallest181:6 243:5 smear 232:18 296:17 smeared

296:16 smooth41:21 snafu 34:19 snapping208:19 snippet23:23 snout 312:25 Snyder217:12 217:14 217:16 267:24 267:25 268:3 268:6 268:9 271:3 271:6 271:10 271:12 290:9 so-called187:2 198:16 Society2:20 software 47:23 176:14 176:15 183:24 soil 175:5 257:6 257:24 264:25 280:20 soils 175:4 solely299:25 solid182:16 solid-phase 151:22 Solla 207:25 208:18 solution 151:20 152:2 240:25 245:6 247:11 250:2 250:23 250:24 Somebody 235:3 somehow222:14 239:10 someone 54:24 55:1 56:5 somewhat47:15 109:4 137:11 261:7 303:20 somewhere 34:5 128:8 299:17 SOPs 197:4 sorghum

217:20 218:4 218:21 261:20 263:18 264:8 269:4 279:20 sorry 13:25 21:17 32:11 33:13 34:15 40:16 56:8 59:13 65:15 68:21 193:16 272:24 281:5 293:2 309:5 sort46:8 75:6 90:14 120:3 171:12 175:25 195:18 203:13 208:5 218:17 219:6 222:6 292:14 306:8 314:17 318:14 sorted 235:11 sought97:15 98:8 sound265:11FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 453

286:21 287:1 sounds 54:17 173:20 188:9 source 132:1 169:23 174:7 180:9 243:15 246:4 246:6 246:8 247:16 248:5 sources 173:22 183:18 184:5 186:9 250:4 277:25 283:11 284:20 South 201:4 202:5 Southeast254:14 spaces 201:3 speak 26:9 73:13 91:13 195:14 204:19 210:5 252:11 278:5 290:5 speaker 81:11 82:19 106:13 106:15 speakers 81:19 247:13 254:22 speaking121:16 156:6 315:3 speaks 274:18 special 25:24 219:4 224:16 225:3 225:3 251:19 287:8 specialty 30:6 277:20 species 53:17 53:23 71:7 108:4 108:9 108:13 108:15 108:17 108:22 109:1 110:16 111:5 111:10 150:25 155:20 166:15 167:1 193:1 193:20 194:6 198:10 198:25 198:25 199:5 199:8 199:25 215:2 254:11 317:6 specific 2:15 19:8 48:2 91:9 101:6 168:15 225:9 287:7 295:11 specifically 37:1 66:18 93:17 97:15 99:22 100:2 100:20 104:3 144:13 176:14 229:15 255:4 282:16 284:16 289:5 289:15 294:9 294:12 spectrometry 130:10 speed10:20 spend121:24 spending121:15 spends 262:16 spent 84:2 196:12 196:17 sperm 159:7 190:12 190:17 190:20 199:16 200:9 200:11 200:20 201:6 201:9 201:13 203:16 203:23 204:3 spike 50:13 spikiness 172:10 spleen131:9 split 45:3 256:17 spoken74:9 spontaneous 25:7 115:19 115:20 119:3 spontaneously 319:19 spot278:16 278:17 Sprague 127:6 131:7 Sprague-Dawley 48:4 135:4 140:20 146:10 150:13 161:10 161:14 Sprague-Hawley 131:14 spread 254:14 spreading212:5 spring71:4 square 172:18 squares 62:10 squint123:15 St209:9 stab 131:4FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 454

stack 17:23 18:1 18:2 55:23 55:23 stacking217:1 stacks 55:20 60:8 60:11 staff 7:17 255:8 255:9 stage 18:22 22:14 86:4 93:25 108:20 242:16 274:15 stages 33:21 91:25 101:17 102:2 102:6 102:21 104:18 104:21 105:2 105:14 stage-specific 101:14 staggered313:9 stain 16:16 17:11 stained

129:12 129:15 staining22:4 stains 22:2 stake 268:20 270:18 287:9 stakeholder 226:22 stakeholders 219:2 225:17 270:1 270:21 stand223:6 223:6 226:8 267:13 standard46:18 88:14 130:11 196:10 196:23 285:16standarddeviation 88:7 standards 271:24 272:8 272:9 272:19 273:6 273:16 284:25 285:2 286:23 287:15 staple 279:21 Starbucks 264:10 start 10:20 18:12 39:17 74:19 80:4 80:10 124:7 158:15 169:5 184:6 206:24 208:20 218:10 242:20 242:21 242:22 289:19 started

65:19 75:16 77:24 78:24 79:3 220:22 220:25 230:25 231:21 241:10 252:20 252:21 254:14 254:25 297:24 starting18:10 254:10 295:24 starts 56:6 213:16 state 2:15 2:25 3:7 6:10 12:14 12:14 22:13 33:2 76:17 87:20 93:5 96:17 99:23 108:6 151:8 155:12 169:15 205:10 218:25 236:2 254:15 257:6 257:10 257:11 268:15 301:4 stated 90:1 154:2 state-level 32:2 statement20:21 160:8 196:1 197:2 267:13 statements 89:19 131:7 states 4:22 33:9 218:23 242:20 242:21 253:19 256:25 258:8 267:16 268:14 278:2 280:22 static 22:13 171:1 172:16 179:9 179:10 179:12 179:19 179:21 180:9 184:5 statics 174:13 180:10 180:13 182:18 statistical 61:15 77:13 77:18 79:14 91:22 statistically 187:24 203:21 233:20 238:17 297:20 304:20 307:7 307:17 309:7FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 455

statistician 5:6 6:7 306:23 statistics 2:20 5:4 170:17 234:10 status 110:16 224:24 statute 272:16 273:4 statutorily272:8 stay 57:13 248:12 314:16 steady12:14 108:5 Steeger 196:6 196:17 196:22 Steiner 317:18 step 82:17 86:22 223:21 stereotactically 115:6 steroid

109:5 130:8 130:11 steroidogenesis 81:9 steroidogenic 107:13 steroids 107:25 Steve 2:10 74:9 116:17 125:24 Steven2:4 6:13 6:18 7:13 8:12 8:16 9:4 9:10 12:25 13:13 43:24 51:11 53:8 54:7 57:16 59:3 62:17 64:5 69:24 72:16 73:1 73:8 73:11 74:3 74:15 90:12 106:8 106:21 121:5 130:22 143:7 143:14 143:18 143:23 144:5 156:2 156:11 156:15 157:11 158:5 167:23 184:18 185:3 217:6 227:15 227:17 227:20 227:25 228:4 228:7 228:12 239:20 251:3 258:14 267:19 271:2 271:8 271:11 276:23 277:2 281:4 287:18 288:1 288:4 288:7 288:10 290:17 292:23 293:4 294:19 295:21 300:20 301:11 302:15 302:21 304:10 304:13 309:9 309:12 310:4 310:16 313:14 314:12 314:15 315:16 315:19 320:13 321:3 321:8 321:13 322:2 Steve's 74:10 steward

266:23 266:24 stewardship 75:20 171:16 266:20 266:21 stick 246:13 sticking217:8 stimulate 122:8 124:6 stimulated

210:19 stimulates 41:21 111:25 126:12 stimulation 41:20 117:20 117:22 119:4 stimulatory109:2 stimulus 113:16 119:11 119:18 stock 280:17 Stoker38:14 Stoker's 89:10 165:23 stomach50:2 Stone 4:21 4:22 stop 90:11 118:2 213:15 store 174:4 180:16 stored 174:15 stores 280:20 stories 221:7 story 317:17 318:16 straight195:19 197:3 strain25:9 55:13FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 456

strategies 82:3 stream 280:2 292:11 streams 169:13 255:3 255:20 257:9 257:11 257:12 257:20 265:1 265:2 street264:10 strength114:3 stress 25:13 25:19 26:1 42:2 42:4 64:17 65:11 65:13 65:13 84:14 84:14 128:7 129:14 129:19 301:16 301:19 301:23 306:11 stressed42:22 stressing64:9 stressor 126:15 126:15 128:22 129:13 stress-responsive 128:6 stretch49:2 stretches 29:17 strict100:14 strips 256:22 strive 167:6 stroma23:18 strong199:1 199:13 208:6 262:1 262:3 strongly 38:6 286:25 structural 95:18 structure 21:13 21:14 101:23 101:24 104:6 104:24 129:10 202:10 structures 21:1 21:21 23:20 100:15 101:5 103:7 103:14 103:25 104:1 104:15 104:17 104:20 104:23 105:5 105:10 student87:20 211:16 students 191:21 studied

45:4 118:25 studies 5:4 13:6 15:2 23:12 24:11 25:3 25:18 34:1 36:14 36:16 36:25 37:2 37:6 38:13 38:14 38:17 38:19 38:21 39:20 40:15 40:25 41:1 41:9 41:10 41:24 42:25 44:7 44:20 44:22 47:4 48:8 50:20 55:3 58:5 58:6 58:6 59:2 61:21 64:25 65:19 66:21 66:25 70:18 70:20 77:20 78:23 78:25 79:11 80:2 87:15 89:6 89:6 89:7 89:8 95:14 115:13 115:14 115:19 118:19 121:16 121:19 122:21 122:23 123:6 123:7 123:15 125:21 125:24 126:2 127:15 129:2 129:5 131:3 131:21 134:1 135:19 135:21 138:16 138:24 139:13 140:17 141:6 144:8 144:11 145:19 146:5 155:1 163:17 163:19 163:22 164:3 165:10 165:12 165:13 165:22 166:1 198:14 209:4 210:10 210:12 210:15 215:19 215:25 216:7 216:14 217:3 220:14 223:13 223:17 223:18 223:19 223:24 236:8 238:24 255:16 255:21 269:7 269:15 269:23 271:25 272:3 272:7 272:12 273:21 273:24 276:17 280:8 285:10 290:21FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 457

293:16 301:9 301:14 302:9 309:15 309:15 311:14 312:11 314:1 318:9 319:14 319:14 studying41:14 83:12 120:22 stuff 173:8 318:16 318:17 subcomponent 89:13 subduing192:19 sub-fertile 203:24 subfield175:7 subject82:15 88:24 174:5 222:9 241:22 subjective 19:25 47:19 95:23 96:20 96:22 subjectively 97:10subjectivescoring72:10 subjects 118:14 209:15 submit88:21 132:20 138:9 281:3 submits 230:11 submitted40:18 63:11 63:14 220:2 231:3 239:16 260:12 subpoena 251:12 251:13 271:21 subpoenaed

226:12 subpoenas 226:1 226:6 sub-pools 171:1 subsequent 91:16 94:9 166:8 subsequently 97:12 99:15 104:19 221:8 substantial 8:1 83:4 238:16 substantially 86:5 substantive 286:22 substitute 11:21 subunit119:24 success 198:2 278:8 successful 162:2 164:21 successive 284:17 suckling50:8 suffer216:15 suffers 216:4 sufficient300:12 sugar 279:20 sugarcane 218:22 261:19 263:19 264:8 269:4 suggest27:12 82:3 83:4 84:24 94:4 125:25 179:3 215:19 217:4 222:14 224:18 227:18 260:5 260:5 261:24 262:4 suggested47:14 97:9 119:14 141:10 211:9 suggesting 27:23 102:19 123:25 124:1 128:5 129:16 133:13 133:22 137:10 142:23 148:14 155:9 165:8 216:14 suggestion 83:14 309:22 suggestions 106:5 suggests 128:6 130:3 136:1 265:5 308:1 308:10 318:4 318:20 320:2 suitable 168:21 suited 235:18 sum 21:23 summaries 14:8 41:15 269:23 322:20 summarize 83:18 149:7 153:14 154:24 summarized

131:7FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 458

summarizes 170:17 summarizing 81:2 145:20 166:19 summary15:19 61:18 77:12 105:15 149:5 151:12 154:24 162:18 166:13 231:1 231:7 233:4 234:6 275:13 286:10 314:19 316:6 summer16:6 268:25 super-physiologic 114:15 supplement183:25 supplied283:13 supplier 284:13 suppliers 284:9 286:1 287:5 supplies 246:4 248:22 283:5 supply174:7 245:20 246:9 247:3 247:21 248:8 249:3 249:8 249:8 249:20 278:9 281:24 291:20 315:15 support94:21 94:24 95:1 106:5 112:25 145:9 155:23 210:1 215:24 225:24 supported81:18 91:20 supporting285:10 supports 119:17 177:16 299:21 299:22 suppose 241:22 supposed243:5 256:8 256:19 257:18 suppressed

135:18 141:2 141:3 153:16 suppresses 94:19 140:23 suppression 80:10 81:7 84:4 84:16 88:17 88:23 98:20 98:23 131:8 131:15 137:13 158:15 165:16 166:12 229:22 238:16 238:20 238:20 295:13 suppressions 165:17 suprachiasmatic 116:4 120:6 sure 8:5 14:9 18:3 25:25 29:14 45:8 45:8 51:12 53:12 54:21 55:11 55:24 66:6 71:2 74:12 156:21 156:24 157:1 184:23 185:16 186:5 197:1 197:6 210:15 221:23 225:2 225:15 227:19 228:22 230:22 235:5 237:5 238:8 241:7 249:21 265:14 265:24 271:21 288:1 288:3 289:12 300:7 301:21 304:23 310:16 314:9 321:7 surface 53:17 54:4 169:8 169:9 194:15 242:5 243:23 244:12 245:11 265:3 282:18 282:25 283:10 284:10 284:19 surface-water 241:13 242:6 242:7 242:16 246:9 247:15 surge 13:8 13:11 80:9 80:10 82:22 83:5 83:11 84:4 84:19 84:21 86:18 87:6 87:11 88:7 89:20 89:23 106:16 107:3 108:11 108:24 111:8 111:10 112:1 112:7 112:9 112:11 112:18 113:4 114:7 114:10 114:16 115:22 116:16 117:3FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 459

117:8 117:16 117:25 118:8 119:4 119:9 119:16 119:22 120:2 120:18 120:23 121:3 122:16 122:16 122:24 123:4 123:6 123:24 124:6 124:8 124:11 131:23 132:3 132:19 133:18 133:19 133:20 133:24 134:14 135:1 135:3 135:5 135:15 136:14 136:21 137:4 137:5 137:12 137:20 138:18 138:19 139:2 139:15 140:11 140:12 140:19 140:24 141:11 141:15 141:22 142:3 142:4 142:9 142:15 142:17 142:21 143:1 143:6 158:21 159:10 159:13 160:6 160:12 160:15 160:21 161:2 161:4 161:6 161:8 161:12 161:16 161:20 161:23 161:24 161:24 162:1 162:8 162:10 162:14 162:20 166:15 166:24 230:20 232:14 235:23 239:7 293:20 294:1 295:1 296:1 296:16 298:21 298:22 299:2 299:7 300:1 300:5 313:25 316:8 316:9 317:11 318:21 320:1 320:2 320:3 surges 115:19 115:21 116:7 119:5 123:1 136:23 137:16 161:17 162:2 162:11 162:15 318:14 319:19 surge-suppressing 137:23 surgical 114:22 114:23 surgically114:25 surplus 88:5 surprise 221:24 245:16 surprising303:20 Surprisingly 173:19 surrogate 159:1 159:6 surrounding 92:6 92:13 Survey4:22 4:25 195:9 survival 311:10 Susan 5:11 5:11 13:3 13:12 38:14 44:6 44:11 44:19 45:6 45:15 46:10 47:18 48:19 48:24 49:10 49:14 49:18 49:25 50:9 50:12 293:2 293:7 293:16 293:22 294:2 294:11 294:14 294:18 310:7 311:2 311:9 311:13 311:19 313:4 susceptibility 23:6 24:10 40:8 susceptible 40:7 193:23 193:25 sustained267:1 Suzanne 7:21 13:19 13:23 44:10 44:15 44:23 45:8 45:25 47:2 47:25 48:23 49:8 49:13 49:17 49:19 50:3 50:10 50:19 51:22 52:7 52:10 52:13 52:17 52:24 53:12 54:11 54:14 54:21 55:6 56:18 56:22 56:25 57:5 57:8 58:1 58:13 59:1 59:12 59:15 59:19 59:22 60:20 61:2 61:8 61:10 61:16 62:4 62:16 62:25FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 460

63:9 64:3 64:19 64:24 65:15 65:18 66:4 66:17 66:20 67:3 67:6 67:20 67:25 68:3 69:13 69:20 70:10 71:11 72:25 73:7 73:9 Suzawa206:4 207:5 208:11 211:12 Swan 203:20 SWAT 178:21 178:25 switch253:10 253:16 switching249:7 Syngenta 73:24 74:22 75:13 75:21 79:8 79:23 81:2 81:12 81:25 87:19 91:20 121:20 156:18 156:23 157:7 157:15 168:4 168:4 168:5 169:15 170:1 172:6 173:12 186:20 209:9 212:24 213:5 213:15 290:22 290:23 300:25 302:24 306:22 313:19 315:5 Syngenta's 212:16 221:20 synthesis 85:5 synthesize 122:7 126:10 synthetic 283:20 system 21:7 54:10 54:19 57:3 57:7 85:3 114:19 116:12 120:4 120:10 125:17 150:1 160:10 160:17 170:9 171:22 172:8 173:16 173:17 181:4 182:1 182:3 182:3 183:15 209:25 245:14 245:14 245:23 246:7 246:18 247:7 247:11 248:2 248:2 267:15 270:24 284:19 291:19 292:2 294:15 312:9 systems 168:14 168:25 169:14 169:21 170:3 170:4 171:2 171:2 172:3 173:12 173:14 173:20 174:16 174:25 175:13 180:8 214:20 242:13 243:13 243:17 243:18 244:1 244:5 244:6 244:7 244:9 244:10 244:15 244:19 245:3 245:18 246:13 246:22 248:11 249:9 249:12 256:9 257:19 283:22 286:1 317:2

T table 2:13 81:4 170:17 173:7 231:7 234:6 260:16 265:10 tables 231:1 236:11 tachykinin-b 317:17 317:25 Tadpole 197:14 tadpoles 198:2 204:23 tagged 101:5 104:5 tail 16:1 224:10 taking39:16 66:6 94:2 97:1 280:17 296:21 talk 14:2 14:5 31:24 36:13 38:1 51:23 52:14 100:18 101:12 110:21 154:5 163:18 175:9 175:11 176:4 183:2 183:3 185:21 229:14 229:18 229:22 230:9 231:16 241:1 252:8 260:4 271:22 315:21 talked 48:9 65:1 88:9 175:20 232:13 236:12FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 461

315:23 talking169:18 173:24 195:21 229:16 230:1 252:17 253:19 talks 135:20 169:7 230:8 tall 13:5 Tami 87:17 152:5 153:1 Tammy 38:14 89:10 165:23 tank 192:13 192:18 192:19 tanks 192:12 Tanner15:12 target83:22 targeted128:8 225:25 Targets 14:4 task 224:13 261:3 261:4 261:25 tasks 70:9 tattoo 46:5 tattooed26:6 26:20 46:1 TCDD 21:5 21:10 TCT 184:16 teach 16:8 teaching267:8 team 30:7 35:16 36:3 36:3 73:24 80:1 143:19 156:23 157:7 158:11 221:20 259:17 259:21 287:23 289:25 technical 65:8 175:16 274:16 technicality 288:11 technically 251:12 274:23 technique 15:18 16:7 17:13 114:22 140:9 151:23 techniques 256:15 technologies 245:22 250:18 282:2 technology242:11 246:1 254:5 254:6 256:5 278:19 279:6 temperature 208:19 temperatures 208:24 temporal 152:18 178:19 ten 14:16 42:20 78:1 186:11 228:8 255:8 255:9 255:16 255:21 tend109:8 240:13 245:17 245:18 246:10 246:12 tended 210:18 tends 246:16 tenfold 149:4 155:5 tentatively87:22 term 85:10 110:22 263:12 318:2 termed 109:9 terminal 18:22 18:23 18:23 19:7 19:10 21:21 22:16 22:22 22:25 23:2 23:5 23:8 30:16 30:18 39:14 40:5 40:12 52:22 53:1 53:2 68:16 68:22 97:19 103:25 104:6 239:11 307:18 313:13 terminology 280:14 terms 70:7 93:15 94:7 95:11 96:21 97:4 97:10 97:11 99:2 99:7 100:14 101:6 104:15 105:3 105:12 106:5 143:3 143:5 145:10 149:5 149:20 151:2 180:4 248:6 281:8 290:20 290:21 295:7 297:7 300:3 305:17 307:12 308:12 309:1 314:20 316:11FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 462

test31:22 45:23 72:19 129:2 131:25 189:15 238:1 tested 31:23 46:8 46:9 85:21 142:17 238:3 testes 200:19 200:20 testicular190:10 190:13 194:23 200:20 201:8 202:16 207:16 207:22 208:1 testified224:19 testify268:11 testifying 226:5 226:12 testing138:22 220:8 testis 159:23 187:9 188:9 190:2 191:17 193:17 194:12 194:14 194:15 195:1 201:2 201:3 201:6 201:13 203:4 203:9 203:9 203:10 203:13 203:14 207:16 testosterone 130:15 159:4 159:23 159:25 160:1 165:18 165:18 165:20 187:2 187:15 187:23 187:24 190:21 193:4 199:16 199:19 199:22 199:24 200:4 200:7 200:10 201:24 202:15 204:3 210:9 238:22 Texas 157:23 158:10 TGF-alpha 20:19 thank 2:18 6:13 7:13 8:16 8:18 8:25 12:24 12:25 13:12 13:17 43:23 43:24 44:6 46:3 47:5 47:17 51:11 53:7 54:6 64:7 67:7 69:23 72:16 72:23 72:25 73:2 75:11 79:17 79:20 90:12 90:25 106:8 106:21 106:22 121:5 121:8 143:7 143:16 156:1 156:2 157:9 157:19 157:20 158:5 167:22 167:23 184:13 184:18 185:1 185:3 185:19 217:5 217:6 218:1 220:21 225:17 227:1 228:10 228:18 239:19 239:20 239:23 240:6 251:1 251:3 258:13 258:14 259:1 259:2 267:17 267:19 271:1 271:2 271:10 271:11 276:22 276:23 281:3 281:4 281:14 287:17 287:18 288:9 288:10 288:15 290:17 291:10 292:23 294:18 295:20 300:19 300:20 300:24 304:13 304:15 309:12 310:3 310:4 313:14 315:17 320:9 320:13 322:1 322:8 322:24 thanks 11:13 121:4 315:12 320:12 that's 6:20 9:2 9:11 10:21 11:10 11:18 12:13 12:20 15:16 17:11 19:13 33:11 40:22 45:10 45:15 46:4 46:10 47:2 47:10 47:13 49:22 54:1 57:7 59:7 59:19 60:21 61:2 63:7 65:3 65:8 65:9 67:5 67:22 70:10 70:14 71:5 71:11 72:23 73:14 75:23 84:25 88:21 90:8 94:11 94:20 97:5 109:11 114:18FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 463

115:12 116:9 116:18 117:14 124:11 157:5 160:16 162:17 166:11 167:12 168:3 169:18 170:13 175:5 176:1 188:22 192:20 195:15 198:4 198:20 200:6 200:19 200:21 201:11 203:12 206:17 206:17 208:17 210:9 211:18 213:24 215:21 218:18 221:23 224:17 226:2 226:20 229:20 231:10 237:5 238:3 241:1 246:9 247:11 250:8 251:10 253:15 254:18 254:19 271:8 274:10 281:6 285:13 292:21 293:11 296:19 299:21 301:20 303:16 306:20 311:5 314:3 321:23 322:17 theme 80:8 themes 20:7 81:20 themselves 2:14 158:25 188:20 theoretical 175:18 179:17 thereafter102:3 thereby126:19 there'd

56:10 therefore 24:19 163:7 264:16 274:5 306:5 308:22 319:20 there's 9:24 11:5 11:7 27:4 57:2 62:7 62:13 62:19 63:7 67:2 67:10 73:13 93:13 94:8 94:9 97:9 109:15 116:21 118:8 148:4 156:24 168:19 169:11 175:18 175:19 178:11 179:15 180:16 183:23 184:2 203:13 204:6 205:17 210:13 210:21 210:25 213:8 215:9 216:13 223:7 233:7 233:11 234:1 237:6 238:6 240:22 241:7 244:5 244:11 245:23 246:23 289:3 291:12 294:20 295:12 297:23 299:20 306:16 311:6 317:1 317:24 319:11 321:20 they'd 74:17 221:22 they're 16:23 22:14 23:8 25:12 27:23 55:12 60:14 114:5 119:10 134:6 135:18 148:18 168:14 193:15 199:12 201:7 201:14 203:2 205:21 206:16 215:14 232:14 232:17 233:20 234:14 234:15 239:18 241:2 246:13 246:22 256:1 256:8 257:1 257:18 288:4 302:5 318:1 319:3 319:4 they've 203:6 308:20 308:21 thick 105:8 thickness 16:18 third31:24 43:4 129:11 160:15 167:11 177:4 246:11 272:2 274:25 thorough23:2 58:17 182:16 thoughts 37:12 47:9 47:15 62:23 261:10 thousand107:9 thousandfold 78:10 thousands 234:13 251:25 256:12FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 464

three-block 230:15 231:18 three-fourths 261:20 threshold176:7 176:8 176:9 177:11 177:20 177:22 thresholds 177:7 thriftiness 50:7 throughout56:2 61:22 69:18 75:17 93:2 102:6 107:22 108:4 122:14 125:2 140:6 186:22 200:24 thus 129:1 223:20 269:18 thymus 131:11 131:18 tick 163:23 tie 245:24 tighter 237:19 tightly112:16 113:6 till 136:20 256:7 296:18 296:21 tillage 256:6 256:6 256:17 256:21 257:1 257:5 257:15 257:16 258:10 264:23 265:4 266:2 Tillit207:20 tilth 257:24 timeframe 224:13 225:9 timelines 242:18 time-of-day 317:10 time-resolved 152:17 TINA 9:7 tissue 16:18 22:3 29:9 30:17 95:22 101:1 152:2 201:2 202:16 276:2 tissues 38:10 43:1 43:6 43:7 146:22 151:20 159:8 160:2 165:21 title 74:10 titles 197:12 TMDL 249:21 250:4 today 2:13 7:7 8:1 8:10 14:2 14:6 14:9 15:20 18:19 20:5 31:25 36:14 38:1 39:4 48:9 57:19 63:13 65:1 69:7 73:5 75:15 76:3 77:8 78:18 78:23 80:1 85:7 86:17 93:18 107:1 121:16 122:22 127:12 129:5 145:9 156:16 158:13 162:22 182:5 182:7 185:20 210:8 216:16 218:7 222:11 225:3 226:5 226:12 234:19 240:5 241:1 250:19 252:13 252:18 252:22 254:1 256:2 256:24 260:20 262:10 267:7 268:12 271:18 275:8 281:16 322:3 322:7 322:9 322:25 to-head

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281:21 292:11 top 12:8 30:11 36:9 81:23 92:3 99:8 101:16 107:20 114:13 116:19 192:23 193:4 193:6 205:12 205:13 213:25 topic 2:7 70:5 74:6 75:3 94:11 topics 81:15 320:22 to-plasma 152:9 Toronto 6:1 total 21:1 45:2 144:20 147:18 249:21 295:4 totally119:14 250:25 265:20 tough 227:7 toward 48:18 towards 9:1 180:22 224:5 235:19 town 290:3 towns 205:16 tox30:4 30:5 30:6 85:17 93:13 229:5 toxic 203:13 toxicity 163:11 163:14 165:9 166:17 167:3 167:17 toxicodynamics 145:6 153:10 toxicological 4:15 87:14 90:18 229:11 toxicologist 3:1 3:7 4:1 229:2 310:19 toxicology3:10 3:15 3:22 4:16 5:9 5:18 6:10 6:12 34:24 48:1 79:7 91:18 157:24 229:3 229:4 229:6 310:20 traced 147:21 track 8:8 258:24 266:10 tracks 273:5 trade 261:5 261:7 278:14 traditional 88:16 traffic 222:3 trained

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103:2 103:15 103:18 103:19 105:14 123:17 124:5 124:12 124:15 129:25 133:18 134:7 135:23 136:14 136:25 137:12 140:18 142:16 146:11 146:12 146:25 147:1 147:5 153:15 153:22 154:8 154:13 163:24 163:25 164:2 164:5 164:25 165:14 210:18 212:2 213:3 240:18 241:13 242:6 242:7 242:11 243:2 244:12 245:21 246:1 247:19 249:17 249:19 250:17 276:1 303:4 304:2 307:12 308:3 treatments 212:12 242:16 246:12 tree 21:3 218:21 tremendous 143:25 156:23 300:5 322:9 322:10 trend264:19 trending166:2 trends 171:13 Trentacoste 165:13 trial 221:10 221:11 225:25 trials 314:21 314:25 triazine 89:15 217:23 218:11 219:5 219:11 228:15 259:20 259:25 260:24 261:17 267:13 267:20 289:24 triazines 224:25 266:6 tried47:21 63:2 65:21 179:24 273:16 312:2 312:5 312:6 312:15 312:17 312:18 312:22 312:24 trihalomethane 245:2 246:25 trihalomethanes 244:2 244:11 true 33:3 33:8 33:11 40:16 45:15 70:11 87:24 112:19 113:1 155:8 166:16 174:6 180:10 180:13 246:15 251:11 truly 131:24 trust 222:19 truth 260:17 try8:9 57:13 66:21 77:9 80:22 81:5 81:16 91:14 98:9 100:2 100:19 101:1 101:10 124:5 139:17 141:25 143:5 157:18 158:13 222:13 240:22 259:14 294:8 trying27:24 56:21 160:3 222:17 232:14 232:17 237:20 291:15 313:6 tub 191:21 tube 104:9 tubs 192:11 tubules 190:10 190:13 190:14 190:16 190:17 200:20 201:8 Tuesday225:14 tumor 25:8 301:3 tumor-promoting 212:21 tumors 23:3 40:12 88:19 167:10 210:16 210:19 212:1 turbidity 257:12 257:20 turkeys 252:14 turn 6:19 7:12 8:11 38:8 73:20 75:9 79:16 80:7 80:25 82:6 83:15 88:4 88:11 90:21 107:10 107:12 117:3 149:21FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 467

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19:18 understand 11:23 12:22 14:4 14:10 15:21 26:4 43:21 49:1 51:25 63:19 64:9FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 468

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