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 pesticide
FIFRA 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 a
FIFRA 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 of
FIFRA 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 this
FIFRA 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 be
FIFRA 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. Thank
FIFRA 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 are
FIFRA 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, the
FIFRA 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 my
FIFRA 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 have
FIFRA 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 one
FIFRA 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 there
FIFRA 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; density
FIFRA 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 subjective
FIFRA 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 actual
FIFRA 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 of
FIFRA 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 by
FIFRA 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 in
FIFRA 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 developmental
FIFRA 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 sure
FIFRA 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. The
FIFRA 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 group
FIFRA 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 eight
FIFRA 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 I
FIFRA 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 every
FIFRA 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 happens
FIFRA 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 the
FIFRA 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 Enoch
FIFRA 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 higher
FIFRA 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 of
FIFRA 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 to
FIFRA 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 us
FIFRA 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 beauty
FIFRA 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 circuits
FIFRA 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 that
FIFRA 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 lactational
FIFRA 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 weight
FIFRA 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 coming
FIFRA 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 of
FIFRA 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, so
FIFRA 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 know
FIFRA 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're
FIFRA 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 those
FIFRA 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 our
FIFRA 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 referring
FIFRA 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 studies
FIFRA 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 in
FIFRA 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 there
FIFRA 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 the
FIFRA 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 the
FIFRA 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 would
FIFRA 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 to
FIFRA 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 from
FIFRA 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 did
FIFRA 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 the
FIFRA 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 significant
FIFRA 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 does
FIFRA 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 differences
FIFRA 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 the
FIFRA 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 wrong
FIFRA 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 a
FIFRA 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 will
FIFRA 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 exists
FIFRA 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, thank
FIFRA 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 gland
FIFRA 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 pointed
FIFRA 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 into
FIFRA 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 ability
FIFRA 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 to
FIFRA 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 that
FIFRA 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 is
FIFRA 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 basically
FIFRA 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 after
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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,
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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 bud
FIFRA 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-dose
FIFRA 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.
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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. What
FIFRA 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 ovarian
FIFRA 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 the
FIFRA 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 not
FIFRA 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 middle
FIFRA 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 mediobasal
FIFRA 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 the
FIFRA 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 the
FIFRA 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, as
FIFRA 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 of
FIFRA 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 situation
FIFRA 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 at
FIFRA 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 that
FIFRA 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 also
FIFRA 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 increase
FIFRA 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 was
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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 first
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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 the
FIFRA 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 effectively
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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-adrenalectomized
FIFRA 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 I
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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 be
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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 levels
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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 we
FIFRA 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 this
FIFRA 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 as
FIFRA 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 proestrus
FIFRA 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 tremendous
FIFRA 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. I
FIFRA 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 the
FIFRA 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; so
FIFRA 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 what
FIFRA 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 we
FIFRA 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 previous
FIFRA 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 why
FIFRA 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 pharmacokinetic
FIFRA 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 also
FIFRA 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 covering
FIFRA 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 in
FIFRA 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 in
FIFRA 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 they
FIFRA 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 that
FIFRA 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 estrus
FIFRA 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 was
FIFRA 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 effect
FIFRA 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 LH
FIFRA 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 consider
FIFRA 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 pool
FIFRA 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 College
FIFRA 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 daily
FIFRA 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 going
FIFRA 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 why
FIFRA 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 7
FIFRA 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 of
FIFRA 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, if
FIFRA 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 about
FIFRA 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 water
FIFRA 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 really
FIFRA 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 to
FIFRA 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've
FIFRA 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 larynx
FIFRA 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 Academy
FIFRA 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 show
FIFRA 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 chemical
FIFRA 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 happens
FIFRA 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 are
FIFRA 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 make
FIFRA 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 their
FIFRA 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..."
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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, "Low
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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 very
FIFRA 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 genera
FIFRA 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, Kestemont
FIFRA 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.
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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 in
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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, now
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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 the
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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 would
FIFRA 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 mechanism
FIFRA 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 estrogen
FIFRA 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 get
FIFRA 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 that
FIFRA 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, Farmers
FIFRA 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 the
FIFRA 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 the
FIFRA 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 the
FIFRA 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 SAP
FIFRA 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-making
FIFRA 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 skunk
FIFRA 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 grower
FIFRA 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 little
FIFRA 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 have
FIFRA 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 started
FIFRA 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 repeating
FIFRA 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 one
FIFRA 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 they
FIFRA 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 distributed
FIFRA 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 show
FIFRA 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 the
FIFRA 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 associated
FIFRA 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 that
FIFRA 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 how
FIFRA 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 is
FIFRA 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 the
FIFRA 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 going
FIFRA 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 a
FIFRA 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 plants
FIFRA 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 lot
FIFRA 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, we
FIFRA 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 were
FIFRA 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 conventional
FIFRA 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're
FIFRA 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. farm
FIFRA 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 pretty
FIFRA 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 competing
FIFRA 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 the
FIFRA 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 will
FIFRA 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 means
FIFRA 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 things
FIFRA 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 point
FIFRA 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 that
FIFRA 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 should
FIFRA 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 to
FIFRA 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 is
FIFRA 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 the
FIFRA 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 the
FIFRA 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 redundant
FIFRA 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 or
FIFRA 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 collective
FIFRA 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, pesticide
FIFRA 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 intended
FIFRA 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 Safe
FIFRA 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 water
FIFRA 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 provide
FIFRA 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't
FIFRA 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 the
FIFRA 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 LH
FIFRA 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 may
FIFRA 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 the
FIFRA 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 it
FIFRA 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 we
FIFRA 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 understand
FIFRA 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 comparison
FIFRA 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 vehicle
FIFRA 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 during
FIFRA 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 given
FIFRA 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 after
FIFRA 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 the
FIFRA 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 surge
FIFRA 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 perhaps
FIFRA 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, dopaminergic
FIFRA 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 and
FIFRA 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 operates
FIFRA 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. Hovey
FIFRA 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 tomorrow
FIFRA 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.)

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FIFRA 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.

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FIFRA 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, 2010
FIFRA 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-day 78:9

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

139:19 185:25
FIFRA 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-day 136:18

133-day-old

137:14

13-week-old 87:7

14 127:8 127:20

128:2 130:16

138:4 237:17

244:16 272:24

298:11 302:6

14/10 313:21

314:1 314:10

144 66:14

14-day 134:10

15 2:3 16:14

29:17 29:17

31:10 31:10 48:5

75:4 147:10

156:9 176:19

176:24 177:6

237:7

15% 31:14 32:7

177:21 177:22

189:25

15,000 252:10

253:16

150 19:9 50:24

1500 15:8

15-minute 73:17

227:22

15-year 252:1

16 136:10 174:13

16% 18:16

17 29:17 29:17

31:10 31:10

45:12 195:24

270:3

1700 113:20

18 32:25 114:17

306:15

180,000 169:11

1800 13:9 13:11

1800-hour 236:18

1830 293:17

19 25:18 29:17

31:11 31:11

94:17 98:1

136:24 140:21

174:13 208:11

298:3

190,000 169:11

1965 198:15

1976 229:5

1980s 279:14

1986 241:10

303:10

1990s 254:25

259:17

1993 169:24 170:2

204:11

1994 75:20

79:24 171:15

218:14 224:16

251:21

1995 219:3

1996 242:3 251:20

1997 170:9

1s 57:11

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

177:6 200:23
FIFRA 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-hour 232:15

2-week 303:14

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

196:17 231:24
FIFRA 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

31st 219:17

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-day 315:11

39 185:24 199:10

3-day 29:16 29:21

30:9 30:13 30:18

30:20 31:11

68:17

3-hour 124:23

3-year 172:21

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-daily 142:20

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-hour 18:4

146:11

4-point 20:13
FIFRA 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

7

7 54:9 54:15

127:8 127:20

128:2 130:16

132:6 134:8

134:10 176:25

177:4 177:5

177:7 177:11

177:23 302:6

70 48:5 71:14

700 269:22

70s 20:5 252:21

71 13:5

72 99:16

7200 147:19

73 173:22 274:8

74 241:10

75 229:1

76 35:7

78 175:7

7-day 29:16 30:14

30:19 30:24

31:12 68:17

169:3 179:11

181:9 181:12

181:18

8

8 54:9 54:17

56:13 110:17

138:17 148:12

161:11 162:10

244:8 244:10

8.4-fold 210:3

8.73 35:3 35:7

35:24 37:7

8:00 65:20 157:2

8:30 323:1
FIFRA 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-week 237:4

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-day 89:5

303:15

90s 158:12 172:19

176:14

96 114:5

A

ability 94:21

94:25 138:19

139:1 189:18

243:22 257:2

282:1

able 16:6 16:8

49:24 55:14

68:24 77:19

82:13 85:16 97:2

118:5 130:25

144:23 161:1

168:8 194:20

195:11 206:8

206:11 207:13

231:5 231:13

252:18 254:13

254:17 255:22

256:3 256:5

256:23 257:1

257:16 278:9

291:18 291:22

313:1 316:11

abnormalities

25:8 28:19 187:7

abolished 117:14

abortion 215:14

abounds 266:17

Abraham 259:6

absence 132:16

190:20 190:20

201:8

absent 104:18

105:1 201:20

absolute 54:18

260:19 302:8

absolutely

95:10 96:25

160:17 165:6

227:24 246:15

288:6

absorb 185:7

absorbed 148:18

abundant 278:8

281:23

abyss 287:11

academic 267:9

Academies 6:6

Academy 188:5

188:25 190:24

accelerated 280:2

acceleration

114:16

accepted 34:22

access 14:5 35:25

278:7

accessory 238:22

acclimation 44:17

accompanied

125:15

accompanying 85:7

124:13

accomplished 95:6

accordance 219:23

according 75:4

217:18 268:22

268:24

account 34:8 93:3

94:1 95:4 97:2

98:9 310:1

accounted 96:13

accumulated 122:3

accumulating

172:12 173:12

accuracy 274:17

accurate 21:3

21:25 45:13

183:16 272:13

273:9 274:24
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 332

accurately 259:14

acetic 16:12

achieve 87:3 88:1

achieved 167:6

acid 16:13

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

Act 169:20

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

acting 8:12 74:12

128:21

action 41:13 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

activating 85:4

126:19 126:23

activation 90:3

123:17

active 224:25

actively 22:12

209:17

activism 287:12

activists 221:1

221:4 221:4

activities 248:19

activity 125:5

129:2 129:3

131:9 131:15

134:15 221:10

acts 211:6

actual 20:25 21:9

54:1 81:18

88:2 89:21

143:24 147:4

173:5 225:12

286:5 286:14

actually 10:22

12:3 14:6

19:15 28:6

42:6 43:2 43:7

45:23 47:3 48:12

50:19 51:1 52:10

53:16 57:9 58:15

61:16 62:3 74:11

76:7 77:4

77:21 80:7 83:11

84:17 85:7 85:22

87:16 89:2

89:9 92:5

92:18 95:4 96:10

97:13 103:12

119:10 119:16

124:15 127:9

128:8 137:24

138:4 138:5

138:15 138:19

138:20 141:16
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 333

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

acutely 85:10

85:10 128:18

131:21 139:2

a-day 25:17

Adcock 281:10

281:14 281:16

287:19 287:20

287:22 288:2

288:6 288:9

289:20

add 53:5 122:2

143:12 172:1

182:8 271:3

added 53:20

61:3 186:7

adding 85:18

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

addressing 171:20

184:15

adenocarcinoma

206:23

adequate 89:3

89:17 94:5 152:9

152:10 181:12

270:15 285:7

administer 127:16

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

adopting 285:2

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

adrenocorticotrop
FIFRA 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

adulthood 51:3

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

advancing 216:22

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

affect 14:22

24:16 24:24

36:21 36:23

36:24 63:18 96:4

163:7 220:6

308:16 313:23

affected 14:20

28:12 29:2 35:13

43:1 159:12

159:13 165:20

188:17 223:11

223:11 276:4

295:25

affecting 47:9

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

202:2

AfricanAmerican 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

ag 223:5 226:5

226:12 259:7

against 232:24

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

aged 23:11

agencies 186:6

219:8 269:9

272:12 272:17

273:4

Agency 7:18

76:1 88:15

155:25 196:25

219:7 220:19

223:22 224:11

224:19 225:2

229:9 273:3
FIFRA 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

aging 96:4

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

agonist 123:8

agreed 8:2 273:23

agreement 89:18

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-Women 219:1

Ah 191:25

ahead 8:9 65:5

143:15 144:5

aim 24:12

145:16 155:24

aimed 151:19

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

allotted 8:4

217:8 280:5

allow 87:16 125:5

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

ALPHA 119:24

already 49:20

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

altering 135:1

alternative

82:3 115:4 246:8

248:5 253:10

alternatives

250:18 266:9

266:9

Alum 16:16

alveolar 18:24
FIFRA 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

among 174:11

189:2 226:4

313:7

amongst 104:3

amount 19:1 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

analog 109:16

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

analyzed 61:14

62:3 94:6

97:11 99:20

103:23 234:2

295:7 297:2

analyzing 104:10
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 337

anatomy 4:12 83:1

ancillary 241:25

ANCOVAs 62:5

Andersen 87:21

144:14

androgen 43:20

130:15 130:19

134:16 159:7

165:20 202:18

androgendependent

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

Angela 28:15

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

306:13 307:21
FIFRA 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

answer 35:22 50:4

66:7 66:18 79:13

188:13 282:21

291:15 291:18

292:1 321:1

answered 9:12

321:17

answers 188:14

188:21

anterior 38:12

109:18 115:2

115:17 115:18

122:9

anti 17:3

antibodyforming 131:9

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

anything 8:24

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

anyway 271:22

anywhere 45:11

110:16 242:19

apart 52:1

apologize 183:4

271:19 292:24

apparent 38:18

39:12 101:25

appear 83:22

125:19 166:14

182:18 184:8

306:3

appearance

101:7 125:11

129:15 167:10

appeared 300:9

appearing 300:18

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

applying 126:15

216:16 251:23

252:19

appointment 91:11

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

approach 11:19

61:15 95:5

97:5 97:14

101:15 103:11

105:9 106:1

110:7 115:5

142:2 144:22
FIFRA 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

approving 280:10

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't 84:9 157:2

186:4 191:15

argue 319:8

argued 112:19

argument 112:4

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

arranged 217:18

arrival 314:2

arrive 288:11

article 275:2

275:7
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 340

artifact 194:8

artificial 150:3

artificially

280:4

ascending 119:21

aside 87:11

aspect 84:15 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

assessed 29:23

49:20

assessing 29:19

282:19

assessment 5:10

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

assigned 311:24

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

assuming 59:25

292:2 292:5

assumption 102:1

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

125:25 126:3
FIFRA 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

254:16 254:24
FIFRA 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

305:4

atrazineexposed 26:17

201:20 203:19

206:12

atrazine's 133:23

220:1 261:13

269:1 280:17

atrazinetreated 27:22

58:22 132:25

190:6 190:14

192:12 305:24

ATSDR 6:17 70:2

attached 272:25

attained 147:4

attempt 82:12

attempting 87:3

attempts 191:8

313:5

attended 196:6

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

auditing 233:12

August 220:23

269:20 269:25

Augustine 20:18

Austin 198:15

216:19

author 198:16

authors 197:10

275:11

authorship 315:7

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 78:9
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 343

171:14

averaging 169:4

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

bad 120:21

badly 241:20

bag 121:18

Bailar 6:4 6:4

53:8 53:9 54:6

Bailey 6:21

6:22 6:23 277:10

277:11

Baker 178:6

178:11

balance 5:14

balanced 270:20

Baldwin 259:6

ban 268:23

bar 260:10 260:15

barbiturate 112:8

112:10 116:25

barbiturateblocked 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

based 22:13

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

309:7
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 344

basing 60:18

basis 32:8

50:20 57:14

83:14 87:24

180:14 220:3

229:21 286:22

Baskin 5:5

bear 143:13

bearing 241:3

beautiful 119:24

beauty 45:25

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

beginning 18:3

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

believed 39:22

believes 286:16

bench 16:25

benchmark 88:13

274:3

benefit 262:17

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

best 17:17

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

better 45:9

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

bigger 179:13
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 345

biggest 205:18

billion 32:12

32:14 53:20

53:22 175:8

253:20 269:3

285:11 285:22

billion-dollar

254:19

binding 211:11

biological 161:16

214:7 214:11

265:4

biologists 20:2

20:4

biology 4:5

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

bit 7:7 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

blend 246:5

blinded 100:13

blinders 247:9

blindly 95:24

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

blocking 133:24

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

blood 12:1

86:11 107:21

110:9 111:3

116:20 187:23

193:3 193:7

296:21

blow 190:8 194:22

194:22

blowup 129:22

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 99:1
FIFRA 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

boring 110:3

born 96:9

102:15 104:25

105:18 105:24

106:3 164:23

165:8

bothered 197:2

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

box 186:21

boxed 95:20

Bradbury 8:12

8:16 74:9

Bradford 198:15

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

branch 13:20

21:22 21:22

52:23

branches 19:20

21:18

branching 19:1

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

BrdU 22:18

27:18 27:22

100:10 104:15

break 69:25 73:17

73:25 75:5

227:22

breaking 75:7

breast 14:13

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

bred 29:21

30:25 31:21

39:12
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 347

breed 31:1

68:25 164:19

breeders 164:20

164:21

breeding 201:21

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

briefly 2:14 6:19

9:5 91:24 100:18

199:10

bright 235:2

235:6 235:13

278:16 278:17

bring 29:7

37:13 41:16

41:25 74:17

94:10 95:15

162:21 234:19

290:7 322:3

bringing 13:17

303:1

broad 262:5

broke 29:16

broken 97:17

brought 33:5

60:21 71:14

73:14 128:5

156:6 232:24

Browner 219:15

Bucher 3:9 3:9

buckets 204:22

bud 18:23 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

budding 19:1

19:12 19:22

22:17 43:5

Budget 272:15

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

buffer 256:22

Bufonidae 199:7

build 153:3

Building 65:1

bulk 148:14

bullets 236:12

burden 226:20

Bureau 277:14

277:18 277:22

277:24 278:4

280:22

Bureaus 218:25

bursting 194:15

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

caiman 201:5

202:7

calculate

146:17 152:8

155:18

calculated

87:25 140:2

164:19

calculating 101:9

calculations

175:18 179:17

calibration

182:17

California 3:16

5:3 5:12 5:22

71:14 91:4
FIFRA 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

Canada 3:25 5:9

75:14

cancer 2:20 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

canula 123:5

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

carbon 243:19

243:20 245:13

246:7 246:12

248:4 248:9

248:13 264:16

280:20

carbon-neutral

264:13

carcinogen 23:4

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

cared 252:6

career 75:18

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

250:1 279:7
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 349

284:22 302:7

322:2

case-by 180:17

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

castration 191:1

catch 27:24 80:23

304:14

catecholamine

316:25

catecholaminergic

316:25

categorize 262:14

category 17:25

180:16

CaucasianAmericans

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

center 3:6 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

266:18
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 350

cessation 124:5

124:12 124:15

134:7 154:12

Cesta 48:14

cetera 175:3

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

changing 45:7

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

311:5 311:12
FIFRA 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

checking 9:7

checkout 268:16

chemical 4:23

40:11 178:2

179:5 183:25

190:25 212:7

chemically 204:20

204:22

chemicals 24:5

215:5

chemist 75:17

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

chosen 71:18

chromatography

130:9

chromosome 189:7

chromosomes

188:12

chronic 137:12

142:16 301:23

chronological

213:10

churning 221:16

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

cited 162:4

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

clarify 54:12

clarifying 8:20

clarity 80:16

class 200:3 212:9

267:8

classes 186:3

200:1 201:16

207:9 209:2

215:6
FIFRA 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

clearly 83:8

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

closely 139:11

141:25 142:6

closing 265:8

322:20

closure 73:19

clothe 277:25

cloudy 257:13

Cluster 241:15

Cmax 149:5

149:8 149:12

coalition 218:19

coat 16:25

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

coding 234:21

coefficient 20:14

152:24

coefficients

146:2 151:25

152:8

coffee 264:10

Cohort 135:23

cold 271:20

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

collect 147:16

174:3 175:1

284:2

collected

147:15 147:18

150:5 293:17

293:19

collection 17:3

246:19

collections

239:10

collective 281:25
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 353

College 2:24

121:15 171:25

175:23 259:6

colony 293:25

Colorado 4:7

87:20

colored 236:16

Columbia 203:21

204:17

column 176:23

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

combined 209:12

297:3

comes 56:5 179:14

197:2 205:9

243:11 243:25

261:23 297:18

322:14

comfortable 71:8

coming 25:15

51:25 58:14

58:18 70:17

168:3 248:14

249:5 268:2

291:11 292:15

300:4 304:7

commended 230:24

comment 7:6

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

commented 227:4

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

commenting 271:18

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

committed 78:20

Committee 218:2

221:19 228:20

commodities

218:20 218:22

commodity 255:6

255:9

common 14:15 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

compact 57:18

compaction 257:23
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 354

companies 281:17

company 78:19

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

compared 22:23

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

compelling 118:10

220:8

compensate 68:12

compete 253:4

competence 62:22

competing

261:25 262:1

competitiveness

278:14

complement 70:4

161:3 254:17

316:17

complete 115:15

190:25 201:8

208:7 209:1

217:3 273:9

312:1

completed 85:19

131:3 259:24

280:9 280:10

288:14

completely 193:23

193:24 233:11

308:23

completing 78:25

complex 146:24

174:2 230:16

269:24

complexity 81:15

compliance 240:25

255:1 255:3

256:1

compliant 312:8

complicated 53:14

113:25 139:16

246:18 270:10

complicates

237:12

complication

236:1

component 21:7

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

compound 50:22

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

comprising 108:5

compromised 95:2

computer 101:8

104:5

computergenerated 17:7

conceivable

311:20

conceivably 56:15

56:21 56:25
FIFRA 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

concept 20:1

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

concerned 182:2

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

conclusion 15:4

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

conclusory 81:20

concomitant 39:8

concordant 88:20

concurred 89:15

condemn 266:16

condition

129:18 139:7

conditions 88:2

129:6 186:23

conduct 79:11

80:2 284:19

conducted 76:21

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

conducting 259:18

cone 65:6

confer 216:23

confidence 168:11

171:3 171:7

183:8 266:8

270:21

confident 77:20

78:4

confidently 183:8

confined 283:21

286:11

confirm 63:1

confirmed 22:1

195:23 221:22

confound 138:22

confounded 303:4

confrere 240:3

confused 59:8

confusion 33:4

33:14 59:5 61:23

Congress 224:20

Congressional

277:14 277:18

conjugated 89:19

connect 292:21

connected 84:25

cons 96:20
FIFRA 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

considering 178:7

179:7

consistency 38:11

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

constant 10:13

102:5 113:15

301:4

constants 10:5

145:24

constituents

224:14 226:22

construct 110:23

constructed 87:18

315:11

construed 274:15

consultant 5:16

240:2

consume 264:8

consumed 98:4

284:8 286:15

310:24

consumers

253:22 258:9

262:19 264:7

283:23 284:4

consumes 283:17

consuming 283:3

consumption

286:14 310:25

contact 22:11

22:15 214:9

214:14

contain 148:15

containing 100:14

contaminant 53:19

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

content 211:15

context 81:6

81:15 83:9 88:14
FIFRA 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

continent 200:13

continents 185:25

continually 69:18

136:4

continue 80:18

119:21 144:16

219:10 228:9

246:1 304:3

continued 136:9

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

contrast 90:15

114:11 116:13

117:8 133:17

164:8

contribute 268:15

contributed

169:21

contributing 8:1

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

convened 269:21

convenience

320:20

convenient 221:13

conventional

256:25 257:15

conversation

73:15 212:15

conversations

25:14 289:14

conversion 148:20

155:10 183:3

184:10 187:15

212:19

converted

148:19 155:2
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 358

conveying 92:2

convinced 234:22

convincing

83:19 265:11

cool 173:8

Cooper 76:23

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

copulating 191:14

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

correct 9:19 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

cort 85:11

85:22 86:1

cortex 126:12

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

302:10

corticotropinreleasing 126:9

cortisol 126:13

cost 240:24

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

costly 263:18

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

counterpart 251:7

counterparts

193:5

counties 205:12

205:13 205:14
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 359

counting 20:25

countries 14:25

185:25

country 24:6

175:5 214:1

240:19 241:19

242:12 268:16

country's 277:23

County 277:21

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

coupling 88:22

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

Coursey 268:22

269:1

courtesy 321:9

Covance 146:8

covariant 62:12

94:3

cover 81:25 90:19

274:9

covered 268:7

covering 75:2

157:25

Covern 80:11

covers 225:20

CRE 273:20

create 181:2

224:3 289:19

created 89:14

credit 221:6

creek 174:4 177:2

CRF 294:14

CRH 126:21 126:21

128:24 294:3

294:4 294:7

294:8 294:9

Cricket 197:17

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

critically 282:4

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

cropping 175:4

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-fostering
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 360

311:4

cross-section

23:20

Crowley 118:19

Cruz 5:3

cumulative 32:9

32:11 63:16

219:21

curious 196:20

current 182:23

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

cut 23:14

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

319:18 320:6

cycledisrupting 301:2

cycledisruption 301:7

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

cycling 141:18

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

dampened 248:1

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

98:13 102:15
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 361

105:1 105:19

135:24

Dan 3:14

DANIEL 3:13

dark 22:4 190:12

darker 98:25

193:17

darkly 129:12

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

dataset 162:5

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 39:22
FIFRA 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

David 81:1 87:9

144:7 218:10

258:18 258:19

259:1 259:5

Davis 5:22 91:5

91:11

Dawley 127:7

131:8

day 2:5 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

dealing 218:14

255:17

dealkyated 146:15

dealkylates

147:25 151:2
FIFRA 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

decapping 65:6

December 304:8

decide 18:8 52:15

247:11 250:1

250:22

decided 11:19

15:3

decision 89:15

262:5 264:13

264:14 267:10

288:17 288:18

313:13

decision-making

220:20 223:25

decisions 243:9

249:19 260:6

265:9 265:11

267:6 270:7

270:22 270:23

decline 86:2

159:4 159:7

163:5 190:21

203:16 264:24

265:4

declined 171:15

declines 42:12

decrease 36:15

36:19 37:16

104:24 105:23

199:21 200:7

200:8 201:24

202:3 202:9

202:18 202:20

203:3 212:4

301:24 305:15

306:5 307:22

decreased 22:17

22:23 31:13

33:21 33:23

42:10 42:10

119:7 150:24

154:20 161:12

199:19 201:20

201:24 202:22

203:5 203:12

204:3 276:9

300:10

decreases 27:11

37:19 67:1

199:16 200:4

200:11 200:11

200:11

decreasing 199:25

decrements

50:23 50:23 51:1

69:8

dedicated 73:23

223:4 223:4

deemed 140:7

Deep 112:10

deeply 262:10

270:24 280:24

deer 252:14

default 153:6

defect 118:15

defer 184:22

288:18 307:1

310:14 311:16

deficiencies

118:23

deficit 37:17

deficits 31:16

31:21 278:14

define 17:18

24:12 40:10

176:6 292:7

defined 55:18

55:18 168:11

183:7

defining 168:16

definite 220:3

definitely

47:16 68:21

112:18 210:11

definition 264:21

definitions 56:14

57:4

degradation

148:23 150:11

degraded 195:14

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 33:18
FIFRA 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

delisted 256:1

delisting 255:24

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

densely 201:6

density 18:25

20:22 20:22

101:9 102:4

103:21

deny 221:3

depart 240:4

Department 3:5

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

dependent 159:8

165:21 207:5

depending 16:18

110:15 187:5

187:6

depends 281:24

depicted 95:13

158:19 159:10

162:6 163:22

depicting 102:24

depiction 92:20

104:1

depleted 187:3

depth 90:14

derivation 52:20

derivatization

62:14

derived 259:11

descending 119:23

descends 287:11

describe 25:25

91:25 97:2

122:21 135:2

136:19 138:6

138:10 149:10

232:4

described 86:6

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

design 63:6

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

6:24 277:10

322:5

designed 76:21

87:17 176:14

designs 78:1

destination

221:24 222:1

destroy 115:7

destroyed 116:3

destruction

202:15

destructor 40:9

detail 13:4

175:12 183:3

289:7

detailed 32:20

180:2

detectable 103:1

detected 104:18

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

developed 32:3

32:19 34:3

55:1 59:24 63:15

87:22 92:23

187:7 207:22

231:1

developing 43:4

144:16 190:12

201:3

development 14:23

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

diagnosed 14:14

14:19

diagram 317:3

Dick 20:18

dictate 284:3

286:17
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 366

dictates 116:12

die 214:5

died 14:22

diestrus 99:24

99:24

diet 139:11 143:5

147:4 149:4

153:19 155:5

163:6 166:18

308:16 308:21

310:23

dietary 87:1

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

differ 179:8

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

different 21:1

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

difficult 68:7

68:8 109:4

123:12 190:4

240:22 261:4

261:25 263:17

279:2 280:3

302:1 312:10
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 367

digest 289:3

dihydrotestostero

ne 130:16

dilated 200:20

201:8

dilute 204:21

dilution 174:6

dilutions 233:9

diminished 120:19

187:3

dioxin 57:10

direct 89:21

203:13

directed 222:2

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

disclosed 290:6

disclosure

186:8 230:3

disconnection

115:2 115:3

115:18

discontinue

245:19 245:25

246:5

discontinuous

228:1

discordant 51:20

discovered

192:8 200:16

213:11

discrepancies

153:23

discrepancy 314:7

discuss 83:8

109:6

discussed 34:18

172:7 275:7

discussing

39:20 81:13

81:16 89:9

discussion 8:25

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

dismay 280:23

disparities

205:21

display 85:9

displayed 86:1

161:19 190:19

disregarded 69:11

disrupted 161:13

disrupting 212:21

disruption 197:24

267:14

disruptors 15:5

15:14

dissect 193:16

dissected 187:4

dissecting 17:6

dissipation

146:14

distinguish

177:12
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 368

distinguishable

188:12

distorted 282:11

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

292:16

distributionsystem 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

dividing 27:24

104:3

division 3:5

184:4

DL6 123:8

DMBA-tumor(+

210:20

DMSO 149:25

DM-W 189:6

Docket 7:4 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

document 41:15

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

dog 251:9

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

140:23 141:2
FIFRA 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

dosed 29:18

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

dosing 37:5

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 11:15
FIFRA 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

157:17 157:20
FIFRA 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

313:16 313:17
FIFRA 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

draw 99:9 172:4

178:13

drink 60:24 60:25

61:4 86:24 284:4

drinking 2:9 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

driven 159:11

320:8

drivers 221:2

drives 107:11

107:12 111:3

117:22 120:10

126:10 159:21

driving 223:16

drop 10:20 141:15

298:19 299:8

299:25 299:25

300:5

Drug 259:13

dry 16:24

duct 18:23

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

304:2 304:3
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 373

313:4

durationindicated 303:7

during 24:8 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

easier 27:3

246:16 298:15

easily 108:19

234:11 234:15

238:2

easy 53:3

213:16 279:18

eat 310:9

Eco 172:6

174:23 175:23

176:16 176:20

177:13 178:3

198:23

ECOFRAM 176:12

ECOG 14:6

ecological 174:20

176:13 284:6

ecologically

188:3 199:20

208:15

economic 269:5

economies 262:11

economist 268:22

economy 205:6

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

effect 15:14 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

163:25 165:6
FIFRA 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

efficiency 253:11

282:1 306:8

efficient 179:6

278:19 279:2

effort 24:7 65:10

72:22 227:2

efforts 152:4

196:16

EGF 27:8 27:13

27:13

egg 206:2

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

either 24:1

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

303:13
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 375

elaborated 80:19

elaboration 87:16

electronic 192:10

312:9

elegantly 113:13

element 261:22

elements 48:22

169:19

elevated 24:4

85:12 245:13

301:22

elevating 122:17

elevation 86:2

elevations 127:17

131:1

eleventh 205:18

eliminating

318:19

elimination

9:18 11:1 281:1

Ellen 5:19 5:19

elongation

92:13 92:24

101:20

eloquently 161:10

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

embarked 126:1

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

employed 284:11

employee 28:16

209:14

employees

209:16 209:18

209:22

empty 190:15

190:18 201:3

emulated 86:13

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

endpoint 40:21

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

energy 5:14

277:25

enforce 8:10

enforceable

285:16 285:20

engineering 5:5

240:10

engineers 260:17

England 200:7

enhance 87:23

enhanced 242:6

enhancement 242:8

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

319:20
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 376

entirely 16:23

entity 218:19

environment 39:24

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

equally 72:11

232:10

equals 21:24

99:13

equation 205:25

equivalent 87:2

163:6 163:12

193:19

Ernest 151:7

erosion 257:6

264:25

errant 267:6

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 60:10
FIFRA 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

essentially 17:19

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

estimated 10:7

32:9 32:11

261:16

estimates

182:11 266:3

269:1 282:24

estimating 10:16

estimation 21:9

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 17:3

estrogeninduced 115:22

137:20 142:14

142:17 294:25

estrogen-positive

111:24

estrogens

130:17 159:11

estrogen-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

et 94:15 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

euthanasia 104:10

euthanize 65:12

evaluate 17:6

17:9 17:21 18:13

18:20 38:21

38:23 48:15
FIFRA 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

evaluated 20:23

29:18 33:2

38:5 38:16 40:21

72:9 72:12

243:12

evaluating 16:9

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

evenly 237:22

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

eventually 219:15

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

everything 8:7

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

evidenced 266:24

evidences 81:20

evident 102:2

102:18 166:17

evolved 120:17

254:23

exact 270:1

272:21

exactly 46:2 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

examined 100:10

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 170:10
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 379

176:7 176:24

177:5 291:20

exceedances 177:6

244:23

exceeded 176:8

176:24 176:25

249:3 286:7

exceeding 176:9

177:11 177:22

291:23

exceeds 266:21

excellent 258:5

except 188:10

exception 241:21

exceptional 169:7

excerpted 94:15

excess 88:9 160:5

161:15 162:3

162:16 162:19

exchange 8:6

322:9

excited 76:2

exciting 170:17

exclude 319:20

exclusively

111:16 255:7

Executive

217:19 218:3

251:15 277:11

exemplified

178:14

exempted 284:14

exercise 248:23

267:9

exerted 113:11

exerts 109:2

exist 107:2

existing 175:18

181:20 284:14

exists 88:25

125:22 248:25

exogenous 161:2

expect 34:5

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

expected 98:19

98:22 147:12

expediency 282:13

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

152:6 195:12

experimentparticular 56:14

experiments 54:20

191:5 198:10

232:5

expert 80:15

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

explained 15:13

36:7 96:10

171:15 276:16

explaining 53:14

explanation

11:4 212:20

306:3 309:19

exploring 235:19

Exponent 229:11
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 380

exported 253:25

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

expressed 101:8

123:19 123:21

129:7 164:7

expressible 200:9

expressing 206:17

206:24 207:16

expression 27:9

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

extended 23:5

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

extensively 25:23

81:25 254:10

extent 11:6

120:17 178:4

external 93:2

100:24

extra 297:5

extract 312:24

extrapolate 169:3

236:5

extrapolating

181:18

extrapolations

145:13

extreme 162:3

extremely 171:8
FIFRA 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

faced 266:15

faces 265:23

facilitate

312:6 312:19

facilities 248:6

facility 65:2

312:3 314:1

facing 265:18

265:20

fact 16:5 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

factor 12:9

118:12 211:10

factored 235:10

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

fairly 56:1 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

family 70:17

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

farmer 229:3
FIFRA 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

farming 258:11

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

fast 147:12

fat 15:4 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

fed 209:4

Federal 6:19 6:24

272:12 272:17

277:10 322:5

Federation 277:15

277:19 277:22

278:4

feed 253:24

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

feeding 50:15

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

fellow 79:7 79:23

168:4 228:17

felt 21:6 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

191:18 192:18
FIFRA 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

Fenner 51:14

Fenner-Crisp 5:15

5:16 227:3

Fenton 7:21 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

fertilizer 252:2

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

fidgeting 228:5

field 71:15 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

FIFRA 2:1 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

fighting 278:24

figure 13:4

13:5 33:10

147:23 207:21

236:4 249:19

figures 103:21

figuring 188:21

236:1

files 231:4

fill 16:25

filled 190:11

190:15

final 32:7 33:1

37:12 51:13
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 384

151:17 159:15

167:25 221:25

225:22 274:22

281:7

finally 39:2

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

finding 135:25

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

finish 157:6

166:19 243:23

243:24 247:4

247:18 250:7

285:25

finished 77:14

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

292:14

finished-wateronly 169:22

finishing 211:4

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

fit 10:1 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

fixed 44:15 96:14

314:22 314:24

flag 311:22

flashier 180:23

flashiness 175:18

178:10 178:14

180:22

flat 13:5

flow 175:3 175:24

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

flowing 171:2

171:21 174:13

179:9 179:16

179:22 180:11

180:19 181:6
FIFRA 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 47:7

170:14 219:25

220:25 241:12

286:19 288:16

focuses 273:7

folks 221:2 263:5

follicle 108:1

117:24 122:20

159:11 159:16

follicles 299:1

follicular

108:7 114:2

116:7 117:22

119:5 320:4

follow-up 9:8

313:18

food 25:16 42:4

140:3 205:9

253:24 259:13

264:11 277:24

278:9 279:22

281:23 305:19

309:2 310:10

footprint 264:16

forced 305:18

309:1

forebrain 118:13

forefront 265:18

foremost 247:16

form 21:23 149:18

151:3 151:3

151:11 151:15

151:16 197:15

224:12 243:1

formal 218:19

formally 274:13

formation

146:15 146:16

148:22 150:12

150:24 151:2

152:21 155:18

159:17

formations 25:8

formed 23:4

23:9 148:18

219:3

forming 147:25

formulation

273:13

forth 317:11

forward 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

foster 312:2

312:2 312:7

312:10 313:6

fostered 26:15

fostering

311:21 312:6

312:20 313:5

313:11

fosters 311:11

foundation 287:2

founder 240:8

four-day 2:5

fourfold 161:25

162:11 162:16

fourth 16:2

22:8 93:19

222:25 269:20

fourth-generation

277:19

Fox 198:23

fraction 162:8

framework 88:17

Frances 186:14

Francisco 5:13

40:2

frankly 224:15

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

frequent 77:25

78:7 119:22

124:22 170:14

frequently
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 386

133:2 240:14

fresh 55:17

Friday 225:12

226:6

Friedman 202:19

friends 268:7

frog 186:18

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

FSH 107:12 107:21

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-blown 124:11

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

funding 87:19

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

gaining 237:6

237:9

gap 11:7

gaps 145:20

Garnett 218:6

Gary 218:8

251:7 251:8

251:10 251:14

gasoline-type

254:1

gated 120:5

gates 120:9

gathered 44:25

174:23

gathering 93:11

gating 317:11
FIFRA 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

gender 110:15

gene 27:9 27:12

39:7 118:15

123:19 189:5

genera 199:5

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

generated 78:3

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

Georgetown 20:10

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

getting 179:6

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

301:14 306:22
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 388

307:6 310:25

gives 154:13

182:10 272:19

giving 21:21

136:13 236:24

glacial 16:12

glad 33:4 60:21

gland 4:5 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

God 225:17

gold 5:19 5:19

130:11

goldfish 199:19

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

117:17 117:23
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 389

117:25

gonadotropinreleasing 107:10

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

gotten 13:24

250:10

govern 271:24

Government 173:22

281:10

grabbed 192:21

graded 16:19

graduate 5:4

87:20 211:16

graduated 258:23

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

greatly 192:6

green 31:9 123:13

163:23

Greenwood 3:19

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

grooming 45:20

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

229:7 229:13
FIFRA 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

grow 22:9 22:10

194:2 277:24

grower 226:25

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

growing 104:14

170:14 194:14

212:5 277:20

grown 218:22

257:11

growth 18:24

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

Gynecology 4:8

H

H&E 17:11

habitat 258:4

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

299:12
FIFRA 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

hallway 227:4

haloacetic 242:25

244:11 244:17

Hamner 144:12

hand 75:3 234:14

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

handling 42:5

handout 179:17

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

happen 39:21

39:22 52:2

58:5 58:7 60:9

68:6 234:14

249:1 317:6

happened 34:15

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

harbor 253:5

Harbourt 168:6

hard 40:16

40:24 68:8 75:22

123:15 207:18

230:16 231:11

295:16

harder 239:9

harm 219:20

219:22

harmful 279:15

Harris 5:24 5:25

harvest 270:9

Harvey 144:13

haven't 53:6

250:10 292:12

294:9 294:17

having 12:1

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

185:14 185:17
FIFRA 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

head 3:4 6:9

20:10 48:6 75:12

229:6

heading 294:24

head-to-head

47:21

health 2:8 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

heard 7:16

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

hearing 79:9

79:12

heart 15:16

heartland 262:12

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

Heidelberg 171:25

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

helping 79:11

196:13

helps 27:17 184:2

218:17 258:11

Hendley 79:12

79:15 81:12

81:24 82:3

157:25 158:2

168:1 168:4

184:19 247:21

291:6 291:7

291:25 291:25
FIFRA 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

Herbert 5:2 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

higher 35:23

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

highest 98:3

140:23 141:7

161:24 164:14

183:8 195:7

220:19

high-exposure

249:14

highlight 95:20

148:11 149:9

149:18 175:22

highlighted 81:17

172:3 173:21

174:12

highlights 14:9

highly 23:12

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 93:21
FIFRA 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

history 47:21

170:3 174:9

261:12 292:4

292:6

hit 14:9 40:8

40:10 46:12

232:16 253:20

hoarseness 271:20

hoc 54:16 56:7

57:4 295:16

295:17

hold 8:3 106:10

156:22

holding 65:2

holds 155:8

Holiday 226:19

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

hoping 168:8

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

housing 191:6

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

HP 126:3

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

HPG 82:18 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

Huffington 221:9

huge 225:19 237:5
FIFRA 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

hunting 251:9

hurry 280:13

hybrid 168:20

181:20 182:22

184:7

hydrologic 174:14

hydrologically

172:23

hydrologist 5:1

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

120:15 121:1

hypothalamicpituitary 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

320:8

hypothalamuspituitary

112:3 116:11

hypothalamuspituitaryadrenal 126:7

hypothalamuspituitarygonadal 121:23

hypothesis

47:13 72:20

126:17 220:5

320:5

hypothesized 96:8

hysteria 279:13
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 396

I

ICI 20:19

I'd 2:13 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

Ideally 72:20

identical

201:15 302:5

309:2

identification

17:22

identified 187:13

193:22 194:22

244:6 294:9

identifier 61:21

identifies 78:22

identify 91:2

167:2 175:12

175:14 185:13

206:9 285:3

294:8 313:2

identifying 180:9

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

236:24 237:5
FIFRA 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

imaging 47:22

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

impact 46:16

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

impacted 262:14

262:19 270:25

impacting 279:21

impacts 51:7 80:9

81:6 261:10

262:13

impaired 23:7

123:17 215:22

impairment 24:9

69:1

impairs 215:17

imperative

93:22 95:10

96:25

impinge 260:9

implant 113:17

implanted 114:3

318:15

implanting 135:10

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

implying 213:8

importance 115:10

139:7

important 15:21

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

impression 67:14

improve 258:11

imprudent 270:6

inability 203:24

inappropriate
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 398

265:16

inborn 16:3

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

inclined 232:4

include 96:17

138:20 141:20

169:14

included 76:14

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

including 24:9

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

incoming 291:19

incomplete 216:20

261:6

inconsistent 38:2

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

increased 19:19

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

incubation 149:24

150:17 150:17

150:23

indeed 166:14

214:18 262:6

independent 198:8

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

304:18
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 399

indicated 9:18

74:16 80:12

118:1 184:20

238:8 243:14

indicating 162:19

indication

31:17 187:1

306:16

indications 86:7

indices 175:19

178:10

indirect 119:13

316:22

indirectly 126:23

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

inducing 161:5

induction

126:16 134:13

207:8 212:18

295:5

inefficient 306:4

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

influencing 247:2

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

infrequent 177:10

infundibular

109:17

infusion 118:2

139:6

ingenuity 282:2

Ingraham 206:4

207:5 208:11

211:12

inhibit 42:5

126:18 128:17

132:2 134:3

135:14 139:2

inhibited 123:2

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

inhibitory 133:21

138:13

inhibits 126:21

135:3
FIFRA 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

insight 154:13

292:19

insightful 196:15

insignificant

28:9

Insofar 84:16

inspection 25:17

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

intact 76:24 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

intended 283:25

intense 147:8

150:6

intensely 26:8

intensity 147:7

intensive 86:14

intent 303:11

interaction

5:14 8:19 84:11

interchange 5:8

interest 3:8 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

interesting 47:14

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-dose
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 401

145:5

interpolate 182:9

interpret 66:22

145:5 236:7

interpretation

62:20 62:23

229:19

interpreted

211:12 232:9

interrelationship

301:15

interrupt 115:9

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

involved 38:7

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

IQ 273:4 273:6

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 12:3
FIFRA 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

January 212:15
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 403

213:11

Jeffrey 146:20

151:18

Jepson 151:21

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

JOSEPH 6:22

Journal 34:20

journalism 282:12

judgment 220:3

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

junior 16:6

justice 205:24

justified 273:10

justify 269:16

K

Kaiser 40:1

Kannan 3:23

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

Karsch 113:13

KATHERINE 4:10

Kathy 4:10

Ken 2:19 20:18

290:1 290:4

KENNETH 2:18

291:10

Kenney 20:17

Kentucky 4:19

Kestemont 200:25

key 80:8 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

killer 131:8

killing 65:23

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

kisspeptin 317:17

317:19 317:24

318:16 318:23
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 404

318:25 319:6

319:8 319:10

319:11

knew 46:4

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

KOW 118:15

kriging 182:20

Krishnan 3:23

3:24 62:17 62:18

63:4 63:23

302:15 302:17

302:22

Krishnan's 184:16

Krista 186:13

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

laboratory 36:2

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

lactating 70:23

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

laid 224:17

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

land 205:7 245:12

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

largely 166:3

171:16 265:20

larger 28:8

177:15 192:17

192:18 192:25

193:1 195:17

243:4 248:2

264:16

largest 177:5

177:21 181:7

205:5 205:15

205:20 277:23

larval 186:22
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 405

197:20

larynx 186:22

186:25 187:17

202:1 202:3

last 9:20 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

lastly 142:24

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

latest 242:21

Latino 205:1

latter 38:22

laughing 259:16

Laughter 74:14

221:14 230:5

launched 280:1

Laura 277:11

law 240:11 240:11

285:4 286:17

Laws 38:14

lawyers 221:11

221:12 225:25

lay 55:22

layers 261:5

lays 189:23

LC/MS/MS 134:18

LE 25:11

lead 23:6 24:8

42:9 106:18

143:2 158:21

211:14 211:25

309:2

leading 79:8

86:10 202:14

211:7

leads 113:22

114:16 241:1

265:13

learn 16:7

learned 154:25

322:10

learning 183:20

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

leaving 228:5

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

led 31:21 95:25
FIFRA 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

length 56:2

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

leptin 50:14

50:17 51:6

lesion 115:5

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

letter 195:24

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

165:20 187:23
FIFRA 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

Leydig 159:23

LH 13:8 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

licking 45:19

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/dark 112:15

113:7 313:21

313:22

lighter 49:12
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 408

lightly 223:12

lights 293:24

likelihood 50:1

321:2

likely 67:4

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

limiting 223:20

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

list 224:22

listed 55:8 111:9

127:11 185:13

186:4 224:25

231:15 231:20

234:7

listen 260:4

listening 78:20

291:14

listing 233:3

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

litigation 226:2

litter 26:14

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

Load 249:21

loaded 185:14

loading 265:3
FIFRA 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

log 10:11

logical 75:6

Lombardi 20:10

long 47:20

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

longer 22:12

39:16 39:18 68:6

85:9 116:24

177:23 262:23

longest 270:9

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

losing 201:2

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

lost 263:7 265:6

lot 8:20 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

Loudon 277:20

Louisiana

174:14 209:9

love 76:14

low 33:19 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

lowering 114:23

lowest 12:10

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

159:18
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 410

luteinization

122:19

luteinizing 122:9

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

mainly 312:16

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

makeup 80:21

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

312:19

maledetermining

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

mammary 4:4 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 57:23
FIFRA 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

management 171:16

248:22 248:24

255:23 256:23

256:23 257:5

266:24 272:15

managing 254:24

mandated 170:7

287:3

mandates 242:11

250:15

manifest 120:7

158:25

manipulate 25:15

manner 16:9 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

margin 285:7

285:15

margins 263:6

263:6

mark 48:14 156:7

marked 148:24

192:9

marker 129:3

159:2 159:6

markers 189:3

market 213:17

213:18

marketing 213:2

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

matching 96:24

305:19

mate 189:18

mated 23:8 310:22

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

mating 136:1

matings 165:8

matter 72:8 72:12

179:23 186:8

203:11 232:8

260:23 284:12

321:21

matters 179:24

260:22 321:5

maturation 81:8

92:19 159:15

mature 30:15

99:22 237:10

maturity 69:16

188:24

Maumee 181:9
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 412

max 78:8

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

may 11:4 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

MBH 112:4

120:15 319:5

McCoy 186:13

McFarland 74:23

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

MCLG 285:4

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

meaning 62:22

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

measured 21:16

21:18 22:18 31:6

48:16 49:3 53:22

66:21 116:20

125:16 128:3
FIFRA 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

296:1

measurementmaking 60:17

measurements

48:11 170:10

measures 52:21

66:5 100:19

100:22 101:15

102:12 102:24

103:24 173:5

measuring 21:7

110:11 130:11

202:7

meat 279:21

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

median 111:15

116:19

mediate 133:15

mediated 134:22

134:23

mediating 84:15

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

meet 218:12 272:7

274:4 291:20

meeting 2:2 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

member 2:22 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

membership 226:16

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

mentioned 46:3

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

mentorship 87:21
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 414

mesenchyme 92:7

mesocosms 198:3

198:9

message 226:7

messed 34:14

met 101:5 258:19

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

149:5 149:12

Mexican/MexicanAmericans 213:22

Mexico 75:14

mg 310:22

mg/kg 29:14 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

MGH 118:20

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

micromolar 149:25

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

Midwest 171:9

292:16

migrate 118:12

migration 118:16

Mike 42:19

mil 148:8 150:20

miles 172:18
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 415

254:15

milieu 47:13

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

mind 192:17 291:2

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

missing 9:24 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

mix 17:21 55:19

72:23 124:5

174:12

mixed 60:5

mixing 18:10

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

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

modeling 83:13

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

modern 258:11

282:2

modified 76:12

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

moment 6:14

81:4 176:1

182:23 314:2

momentarily 83:14

moms 45:16 136:5

money 258:9

monitored 78:6

99:15 99:16

139:21 140:6

140:14

monitoring 2:9

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

monkey 106:24

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

monthly 173:6

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

morning 2:4

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 57:3
FIFRA 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

morphology 166:24

197:22

morphometric

20:14

morphometry 72:9

Morseth 138:11

303:10

mostly 277:20

mother 209:7

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

moved 65:4 195:14

234:9 259:22

moves 216:1

216:18

moving 57:19

82:17 224:8

234:13

mRNA 123:11

much-needed

278:16

multipage 276:25

multipart 75:1

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

NAFTA 75:14

namely 96:17

nanogram 148:8

150:20

Narotsky 42:19

narrowed 237:18

national 2:20

3:10 4:15 6:6

13:21 48:1 188:5

188:25 190:24

217:12 226:17

229:6 268:1

268:10 278:13

nationwide

250:6 254:19

natural 10:11

131:8 255:12

259:7

nature 52:23

194:10 194:24

248:7 260:17

270:23

NAWQA 176:1

NBH 318:11

NC 151:8

NCEA 15:2 15:3

NCGA 268:14

NCI 20:11

NCTR 48:14

nearby 245:23

Nearly 196:19

necessarily

53:4 80:21

138:10 222:5

235:24 286:13
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 418

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

Nelson 4:2 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

nest 312:19

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

y 4:20

neuron 124:2

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

nicely 137:3

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

NK 131:15

NOAEL 85:24

131:18 137:25
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 419

138:8

nobody 198:12

205:2

nobody's 308:24

node 16:3 23:19

no-effect 85:20

131:11

NOEL 166:8

NOELs 302:18

noise 65:11

non 77:14 169:10

non-cancer 2:8

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 99:12

normally 19:4

22:14 34:3

160:20 189:21

310:8

North 6:10 32:3

53:16 157:23

158:10 194:9

195:5

northern 197:21

197:25

Northwest 254:16

note 84:20 103:10

151:4 153:25

309:5

noted 24:5

27:19 28:20 29:5

36:1 41:6 167:15

258:7

notes 18:7 231:8

nothing 48:10

63:3 163:20

233:7 238:7

255:10 322:7

notice 20:7

161:23 164:4

190:8 307:2

noticed 58:15

141:7 303:21

no-till 280:19

noting 269:17

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

255:1
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 420

nursed 49:23

nursing 31:7

Nutrient 265:2

nutrition 93:6

93:8 308:16

O

Oakland 71:14

OB/GYN 106:23

Obama 222:15

objective 63:23

objectively

273:10

obligatory 117:9

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

obtained 64:13

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 110:18

Occupational 3:24

occupations

214:13

occur 67:15

100:21 122:14

125:1 131:13

133:2 171:9

194:6 194:19

211:1 241:4

246:16 265:22

283:22 285:14

292:16

occurred 131:12

132:15 136:1

209:19 225:12

322:22

occurrence 198:24

occurring 150:8

158:18 201:15

248:1

occurs 43:11

92:18 114:17

179:18 199:25

200:1 284:13

285:7

o'clock 157:2

October 219:17

222:22 223:15

odd 180:16

of1.0 152:9

offended 240:12

offer 8:25 120:20

182:15 184:8

offers 212:12

offhand 316:20

office 2:21 8:3

8:13 73:22 74:11

75:5 196:13

217:18 251:13

272:15

Officer 251:15

Official 6:20

6:24 277:10

322:5

offspring 24:14

28:3 28:4

29:11 29:12

29:19 29:23 31:3

50:24 69:2

96:5 215:24

oh 9:6 34:14

56:18 65:15

244:24 247:8

294:11 307:1

Ohio 121:21

Oka 208:14

okay 9:4 10:10

10:24 11:13

11:16 12:5 48:24

49:10 52:12

54:14 58:9 60:15

61:1 61:12 63:23

66:1 66:19 67:13

73:8 73:11 75:11

90:25 106:14

134:24 143:16

143:23 144:4

144:7 156:15

168:1 185:18

271:11 277:5
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 421

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

old 68:4

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-day 44:24

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-way 295:18

on-farm 264:15

ongoing 185:21

191:3 226:3

251:17

online 14:6

onset 41:25 92:18

99:14

onsite 36:4

Ontario 6:1

onto 205:16

onward 80:24

oocyte 159:16

159:16

oocytes 194:23

207:16 207:22

208:1

open 8:6 44:2

120:9 199:18

225:16 289:2

290:24 320:16

322:14

opening 8:14 8:20

27:6 29:20 30:23

37:21 96:4

96:9 96:18 99:14

99:21 103:5

105:6 106:2

136:8 136:12

159:1 163:21

164:7 307:19

307:25

operate 246:2

246:17

operates 319:25

operating 19:14

19:15 176:21

196:10 196:24

operation 278:3

operational 120:1

operator 100:12

opinion 205:24

301:14 301:16

opportunities

268:17

opportunity 8:7

8:21 13:15 49:21

50:17 73:13

74:18 80:14

130:8 184:24

185:19 218:12

252:7 268:11

278:5 278:9

281:2 281:15

321:1

opposed 57:4

150:2 246:17

opposite 212:7

optic 109:10

109:11 116:1

116:5 317:21

318:5

optimization

147:17

optimizing 145:11

option 248:13

249:6

options 175:16

248:5 248:22

248:24

oral 141:8 146:6

orange 31:10

order 10:3 44:7

65:22 73:21

125:4 132:7

149:3 149:14

168:25 248:13

282:7 288:25

289:20 290:19
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 422

313:11

ordered 286:8

286:9

orders 286:5

ordinary 53:11

organ 92:15

organics 283:20

organism 214:18

organisms 3:17

organization

277:23

organizations

227:9

orient 82:25

146:23

orientate 84:7

original 187:20

307:2 309:22

312:18

originally 92:3

242:7 258:23

311:4

Orton 186:14

oscillation

155:13

others 16:8

21:4 21:6 151:22

169:16 178:12

225:23 259:13

262:2 265:18

273:20

Otondras 48:15

Ottawa 5:8

ought 163:10

250:11 250:21

ours 34:1

ourselves 81:24

82:25 183:21

269:11 269:19

278:24 282:5

outcome 15:13

41:4 219:4

outcomes 24:9

40:24

Outdoor 198:3

outline 107:1

outlining 190:10

outside 28:20

56:24 109:24

ova 160:25 161:3

ovarian 81:7

92:18 102:2

108:16 108:25

108:25 112:25

ovariectomized

113:14 123:2

125:3 125:3

132:6 142:15

ovariectomy

108:20 135:6

136:13

ovaries 187:10

187:18 188:9

ovary 107:6

107:12 107:13

108:16 160:10

197:15

ov'eced 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

overly 267:5

overnight 290:25

over-predict

178:23

overriding 278:22

overseeing 36:5

overseen 219:14

oversight 250:15

overtopped 179:12

overused 23:21

oviduct 193:18

oviducts 194:2

ovulate 160:25

161:1 298:25

ovulated 161:20

ovulation

108:12 112:1

117:25 119:6

122:19 158:22

158:23 159:16

161:3 161:7

238:13 238:21

ovulatory 117:8

162:14

oxidative 147:24

oxytocin 41:18
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 423

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

packet 103:22

pad 16:20 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-fed 95:5

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-feeding 95:4

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

Panelist 270:3

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

195:10 199:18
FIFRA 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

parent 70:4 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

participated 24:7

80:2 256:12

322:9

participation

322:25

particular 2:16

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

past 31:22

38:23 134:2

178:10 223:23

225:24 254:8

256:13 259:12

259:21

patent 270:12

pathologist 17:20

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

pathway 126:14

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

paved 222:1

paw 46:5
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 425

pay 93:14 223:9

226:8

pays 253:21

PBPK 81:3 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

PDN 294:3

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

pellet 135:10

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

percent 13:8

21:19 94:20

160:24

percentage 53:2

58:20 160:11

263:8

percentages

32:8 58:20

perfect 241:25

perfectly 59:6

245:5

perform 70:9

145:12 192:15

performed 48:9

63:11 99:11

100:6 100:12

134:1 285:25

performing 189:13

perfuse 125:17

perfusion 160:10

perhaps 48:19

80:16 83:11 84:7

84:9 86:19

120:19 138:21

139:10 143:10

186:6 222:6

253:8 300:9

303:6 305:17

314:25

peri 142:17

period 7:23

7:25 8:4 13:16

23:5 29:16 29:21

31:8 31:12 31:12

31:18 31:19

31:22 37:5

38:4 38:22 39:18

43:5 44:18 46:14

46:15 46:20

64:21 68:15

68:24 73:19

73:21 74:21

86:15 94:18

98:15 113:6
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 426

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

permanent 2:22

3:2 3:11 3:18

6:12 68:10 69:15

Permanente 40:2

permanently 16:24

permeable 214:23

permissible

285:17

permissive 118:2

permit 14:1 121:2

320:17

perpetuated 197:7

perplexing 303:24

Perry 172:17

179:11 180:15

314:20

persistence 68:19

persistent

30:10 31:20 69:6

69:16

person 65:8 70:25

personally 223:11

persons 285:6

perspective 51:25

72:22

pest 256:22

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

phenomenon 109:6

phenotypic 97:3

100:20

phosphodiesterase

211:6

photomicrograph

129:8

photoperiod 120:6
FIFRA 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

physiology 4:18

83:1 91:10

pick 18:2 55:23

228:1

picked 221:8

221:8 233:9

233:10

picking 322:11

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

Pittsburgh 106:18

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

PK 10:3 81:2

87:12 146:6

placed 7:8 117:13

226:21

placement 260:14

places 195:21

234:6 234:25

plan 26:10 146:17

224:17

plane 23:14

304:14

planned 98:21

Plant 80:15 82:19

83:6 106:18

106:22 106:23

121:6 121:22

135:11 159:21

166:21 315:18

315:19 317:14

317:23 318:13

318:24 319:3

319:6 319:24

320:10 320:14

320:20 321:1

321:11

plants 252:25

Plant's 82:24

122:11

plasma 10:11

126:16 127:17

127:22 127:23

128:3 130:4

130:8 139:8

147:9 147:18

147:22 148:7

148:14 149:1

149:2 153:19

153:24 155:4

200:7

plastic 65:6

Platte 195:5

play 236:7 260:14

305:17 308:11

please 73:15 91:6

144:5 168:2

310:17 315:19

320:19

pleasure 230:7

plexi 109:23

plexus 109:21

109:22

plot 10:7 10:11

24:21 113:12

205:15 213:9

233:23

plotted 13:6

149:8 302:18

plowing 264:24

plug 135:25

plumes 173:9

plus 231:19
FIFRA 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

pointing 158:15

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

policy 248:17

250:8 268:10

274:15 274:17

political 282:12

politics 287:12

pollutants 250:3

polygonal 101:3

polyunsaturated

20:12

pond 179:15

195:11

ponds 179:18

pool 170:6 170:25

180:7

pools 169:10

poor 269:17

poorest 17:24

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

port 43:9

portal 109:21
FIFRA 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

Portsmouth 3:20

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

positivity 104:15

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

post 54:16 56:7

57:4 117:15

127:19 140:12

221:9 295:16

295:17

posted 91:7

posting 225:10

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

potent 123:8

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

poultry 264:9

pound 252:21

pound-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

preceded 167:9

precedent-setting

270:23
FIFRA 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

predict 178:22

183:8 238:12

predicted 164:5

prediction 163:9

predictions

181:24

predominantly

109:1 127:24

predominates

149:20

preeminent 220:18

prefer 149:18

151:3 151:3

151:15 151:15

289:13

preferred 145:15

pregnancies

164:21

pregnancy 24:2

44:9 161:21

pregnant 44:7

70:22 97:23

161:21 203:25

215:12 215:15

preliminary 180:2

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

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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

166:24 319:19

pre-ovulatorylike 113:22

preparation

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224:21

prepare 322:15

prepared 9:1 27:9

54:22 72:1 226:8

prepuberty 92:10

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

present 8:8

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

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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

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77:9 90:17

106:11 157:7

157:14 157:16

227:23 228:9
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 431

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321:19

presented 32:1

41:15 44:4 58:11

80:23 83:24

84:12 89:25

91:15 121:25

124:3 124:20

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140:25 144:18

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188:5 260:11

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289:8 290:21

299:20 314:18

322:17

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74:24 90:20

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288:18

presenting 76:3

144:8 145:9

145:17 146:1

148:3 186:6

President

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press 34:21 34:22

151:7

pressure 221:17

presumably 308:19

presumed 187:19

pretty 8:10 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

prevent 212:4

216:17 313:1

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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

previously 45:3

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

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primacy 182:10

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108:1 111:12

111:18 118:19

144:20 145:21

241:12

primary 14:17

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

priming 124:9

137:17

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principal

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principally

219:18

principle 262:15

printout 173:7

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

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291:23 292:13

probably 7:7

12:16 35:25

41:18 53:13

68:12 73:3 84:25

85:23 89:21
FIFRA 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

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196:10 196:24

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121:9

proceeding 2:6

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

produced 53:15

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

product 226:23

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 5:3
FIFRA 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

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262:5 262:9

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96:14 96:16 99:8

99:17 102:15

103:12 105:22

106:4

progesterone

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118:1 123:1

124:9 127:23

127:23 128:11

132:18 159:15

159:18 160:13

160:16 162:14

235:10 235:11

progesteroneinduced 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

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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

project 80:6 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

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211:22

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190:2 273:25

281:22

properties 212:21

307:10

proportion 70:8

101:10 187:5

187:7 208:24

210:18

proposal 157:5

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propose 156:16

proposed 76:25

128:20 128:21

130:22 130:24

187:11 229:20

pros 96:20

prostate 14:3

28:4 28:10 28:14
FIFRA 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/

mammary 215:10

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276:3 276:10

prostatitis 38:18

209:6 209:6

prosthetic 36:7

prostrate 24:25

protect 214:21

214:24 241:18

262:22 282:3

protected 208:5

protection 7:17

74:23 76:1 229:9

274:14 281:19

290:22

protective 46:21

protocol 99:19

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proudly 281:18

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

provided 82:9

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

Pruitt 130:22

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

pubertally 142:18

puberty 15:1 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

publish 272:17

published 20:15

72:14 117:12

165:13 178:10

188:1 188:4

188:24 189:8
FIFRA 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

publishing 189:3

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

319:25

pulsegenerating 117:2

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

purview 279:1

push 75:7

putting 200:14

312:23

PVN 129:2 129:7

129:9

Q

qualifies 239:18

qualitative 52:19

quality 71:1

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

155:17

quantitativeminded 149:17

quarter 227:21

quarterly 286:2

question 9:11

13:7 44:19 45:17

47:3 48:25 49:10
FIFRA 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

quickly 15:20

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

quoting 276:5

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

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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

237:8 237:18
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 437

299:18 302:12

302:14

ranges 66:14

86:21

ranging 31:14

127:2 197:24

ranid 197:23

Ranidae 199:7

ranked 59:6 61:13

rapid 9:25 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

rapidly 27:24

123:19 148:18

148:19 155:2

rat 15:23 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

rather 81:25 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

raw 77:14 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

Rayner 26:3

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

reaching 267:11

reaction 224:3

reading 67:14

ready 13:19 54:23
FIFRA 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

reality 182:11

224:4 282:24

realize 33:6 77:1

252:16 262:15

Realizing 86:22

really 10:15 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

reappearing 82:24

reason 14:12

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

Rebeckah 281:9

281:14 281:16

287:22 288:2

288:6 288:9

recall 49:11

receive 96:23

251:11

received 30:3

251:13 287:6

306:23 309:16

recent 14:21 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

recessed 323:2

recession 278:13

recognition

231:11

recognize 217:22

recognized 303:3

recognizes 283:5

recoil 262:5

recommend 17:2

184:4

recommendation

182:21

recommendations

287:1 287:13

recommended 23:12

recommending

230:10

reconsider 18:14

reconstructed
FIFRA 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

recorded 51:13

169:24 169:24

275:15

records 226:2

recover 203:10

recovering 195:13

recovers 84:22

203:8

recovery 84:23

84:24 124:14

203:7 303:16

red 31:11 104:3

148:25 150:18

163:24 195:6

214:1 311:22

redrew 317:3

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

reducing 119:10

144:25

reduction 88:7

99:5 131:11

159:24 159:25

160:1 187:22

266:25 305:13

reductions 256:16

redundant 279:7

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

referencing 68:20

referring 62:1

63:25 292:24

refined 168:22

184:8

refinement 178:18

reflect 98:17

reflection 105:7

reflex 41:20

refused 196:4

197:5

refuses 195:22

Reg 287:23

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

regarded 15:5

regarding 61:13

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

region 75:14

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

165:11
FIFRA 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

regulated 78:11

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

regulatory 5:9

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

reject 220:5

rejoin 157:6

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

relating 106:16

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

released 34:20

42:3 70:24

71:2 88:8 269:21

270:10 274:13

relevance 53:10

120:22

relevant 24:23

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

reliant 263:12

relied 269:7

269:16

religiously 235:8

remaining 30:16

73:4 99:17

189:16 244:21

313:12

remains 278:18

317:10

remarkable 167:11

remarks 224:11

322:20

remember 50:25
FIFRA 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

repeat 18:9 49:21

59:5 191:7 266:1

307:11

repeated 85:14

123:4 198:12

repeating 191:5

231:25

repeats 118:2

replace 153:6

180:2

replicate 82:12

replied 196:22

report 18:17

51:13 53:4 64:11

85:7 86:17

87:5 141:15

165:13 220:25

221:3 230:14

239:15 307:4

reported 28:2

28:23 33:9 36:17

42:19 61:24

125:22 163:3

178:6 212:20

230:14 314:4

314:4

reportedly 205:6

reporter 196:19

reporting 40:4

62:10

reports 14:21

98:21 220:1

220:12 223:16

represent 18:19

135:16 140:10

140:20 147:6

218:20 218:24

223:9 227:1

274:15 278:2

representation

11:1 89:17

309:23

re-presentation

162:23

representative

283:16

represented

84:9 129:17

133:9 307:4

representing

185:11 217:22

228:15 252:10

281:16

represents

13:10 148:25

149:2 150:18

152:13 265:18

268:14 271:14

285:12

reproducible

272:13 273:22

273:24

reproduction 4:13

25:6 106:25

122:5 229:7

reproductive 4:20

5:23 25:6 30:4

30:6 34:24 38:10

40:14 40:21

40:24 41:3 46:17

92:15 93:8 93:24

96:7 96:17 99:23

109:8 158:14

158:17 163:11

163:13 164:6

164:11 165:9

166:17 167:3

167:16 185:22

186:2 188:23

190:1 197:10

198:6 199:3

205:2 220:1

229:4 252:5

310:20

reptiles 199:12

201:17 204:5

207:10 208:1

208:18 208:22

210:14 217:2

repudiated 269:15

request 265:25

requested 273:21

require 178:18

179:1 199:13

270:3 272:11

320:5

required 93:23

160:16 182:23
FIFRA 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-review 78:24

219:17 225:5

269:12 269:16

280:1 286:20

research 4:15

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

resolution 152:18

175:4 175:6

resolve 89:12

resolved 105:22

152:16

Resources

255:12 259:7

respect 47:19

57:22 58:10

89:24 95:8 102:9

102:23 103:3

103:25 104:22

222:20 263:14

respected 269:8

respectfully

260:5

respective

98:15 241:17

respectively

234:1

respond 85:10

117:16 222:23

225:19 270:17

responding 83:25

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

rest 26:11 52:4

147:14 247:10
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 443

275:11 300:10

restraint 129:14

restrict 305:18

restricted 209:21

restricting

305:21

restriction 25:16

42:4 308:3

308:21 309:2

restrictions

280:25

result 96:6

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

resulted 255:23

resulting 160:1

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 6:4

return 75:8

86:3 90:9 134:24

217:16

returned 26:7

returning 73:6

145:6

returns 133:7

reunited 49:2

reversal 208:8

reverse 264:18

289:20

reversed 134:6

290:19

reverses 84:17

review 2:8 7:15

61:18 74:7 91:18

93:16 121:25

186:1 219:4

219:11 220:13

222:24 223:14

224:16 224:20

224:24 225:3

225:4 229:14

230:25 231:2

251:19 270:9

270:20 273:17

282:8 287:8

287:14 322:16

reviewed 15:2

168:22 199:10

199:18 231:14

236:9

reviewing 199:17

reviews 196:15

revising 286:22

revisit 153:9

revisiting 94:7

286:22

revolve 171:21

reweighed 49:4

rewritten 15:1

rhythm 310:9

rhythms 125:20

Rica 251:13

Richard 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

rigidly 8:10

113:5

rigorous 284:23

287:15

rinse 16:15 16:18

rise 264:11

rising 122:17

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

265:15 265:18
FIFRA 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

road 248:15

Robert 121:11

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

robust 77:13

77:21 116:22

252:13

robustness 77:19

Roby 4:10 4:11

Rock 177:2

Rod 217:11 217:14

217:14 267:25

268:3 268:6

268:9 271:6

271:10

rodent 80:13

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

rolling 78:9

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

rotating 65:22

roughly 46:19

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

row 295:24

rubbing 312:22

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

running 141:5

143:10 156:14

250:25 278:14
FIFRA 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

sad 311:10

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

safety 79:25

261:2 269:9

285:8 285:15

sake 55:15 60:12

sales 195:7

saline 151:20

152:2 152:11

salmon 199:20

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

sampling 82:1

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

319:4 319:23
FIFRA 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

sat 216:16 222:16

satisfactory

90:20

satisfied 74:16

321:16

save 90:24 289:13

saves 258:9 258:9

saw 26:24 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

scaling 11:6

54:16 54:17

152:23 153:7

Scandinavian

14:24

scans 17:7

scattered 60:6

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

scheduled 7:20

45:1 73:22 74:22

75:3 217:11

217:17 224:21

277:5 281:8

288:14

schedules 280:4

scheduling 217:18

schema 120:4

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

265:11 270:7
FIFRA 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

220:17 273:10

scientificbased 287:14

scientist 6:1

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

SCN 317:11

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

scoring 20:1

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

scratch 18:11

18:12

screen 35:1

236:15

SDWA 170:10

se 12:14 306:9

searched 160:3

season 170:15

seat 225:18

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

secreted 108:1

108:2 109:21

122:12 127:24

162:17

secretes 126:9

secreting 46:20

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

159:22 159:22
FIFRA 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

seeding 221:7

seeing 28:14

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

selected 21:2

314:22

selecting 11:20

self 97:15 103:23

105:23 313:2

selfproliferation

97:6 97:10

100:10 104:8

104:22 105:12

self-serving

195:18

sell 213:6

selling 213:15

sending 226:7

Senior 79:7 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

separated 49:2

separately 236:23

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 236:3
FIFRA 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

serving 2:12

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

sex 188:12

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 133:11

shamadrenalectomized

132:10 132:25

Shanna 203:20

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

Shelley 5:24 5:24

shift 45:10

248:17 250:9

shifting 250:7

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

shortly 136:2

277:9 293:5

short-term 78:5

142:13

short-tern 175:14

showed 9:17

9:17 31:1

32:15 38:2 110:3

115:21 123:9

123:10 135:11

149:8 164:15
FIFRA 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

showing 41:10

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

significant 24:16

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

273:12
FIFRA 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

simply 62:22

81:23 105:7

162:19 162:23

166:2 167:16

213:6 218:19

222:16 247:25

250:22

simulationfitting 148:6

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

sit 16:22 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

sitting 225:17

227:21 228:25

situation 17:17

72:10 120:24

120:25 301:17

312:8

situations 39:6

243:6 250:1

six 15:25 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

sized 179:18

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 17:1
FIFRA 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

slight 30:22 37:8

slightly 22:13

141:17 148:22

slope 10:7 10:12

slowed 27:12

slower 148:22

slowly 139:17

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

smallest 181:6

243:5

smear 232:18

296:17

smeared 296:16

smooth 41:21

snafu 34:19

snapping 208:19

snippet 23:23

snout 312:25

Snyder 217:12

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-called 187:2

198:16

Society 2:20

software 47:23

176:14 176:15

183:24

soil 175:5

257:6 257:24

264:25 280:20

soils 175:4

solely 299:25

solid 182:16

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

somehow 222:14

239:10

someone 54:24

55:1 56:5

somewhat 47:15

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

sort 46:8 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

sought 97:15 98:8

sound 265:11
FIFRA 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

Southeast 254:14

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

speaking 121:16

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

speed 10:20

spend 121:24

spending 121:15

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

spleen 131:9

split 45:3 256:17

spoken 74:9

spontaneous

25:7 115:19

115:20 119:3

spontaneously

319:19

spot 278:16

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

spreading 212:5

spring 71:4

square 172:18

squares 62:10

squint 123:15

St 209:9

stab 131:4
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 454

stack 17:23

18:1 18:2

55:23 55:23

stacking 217:1

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

staggered 313:9

stain 16:16 17:11

stained 129:12

129:15

staining 22:4

stains 22:2

stake 268:20

270:18 287:9

stakeholder

226:22

stakeholders

219:2 225:17

270:1 270:21

stand 223:6 223:6

226:8 267:13

standard 46:18

88:14 130:11

196:10 196:23

285:16

standarddeviation 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

starting 18:10

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

statement 20:21

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

309:7
FIFRA 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

statutorily 272:8

stay 57:13 248:12

314:16

steady 12:14

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

Steven 2:4 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

sticking 217:8

stimulate 122:8

124:6

stimulated 210:19

stimulates

41:21 111:25

126:12

stimulation 41:20

117:20 117:22

119:4

stimulatory 109:2

stimulus 113:16

119:11 119:18

stock 280:17

Stoker 38:14

Stoker's 89:10

165:23

stomach 50:2

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

straight 195:19

197:3

strain 25:9 55:13
FIFRA 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

street 264:10

strength 114:3

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

stressed 42:22

stressing 64:9

stressor 126:15

126:15 128:22

129:13

stress-responsive

128:6

stretch 49:2

stretches 29:17

strict 100:14

strips 256:22

strive 167:6

stroma 23:18

strong 199:1

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

student 87:20

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

285:10 290:21
FIFRA 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

studying 41:14

83:12 120:22

stuff 173:8

318:16 318:17

subcomponent

89:13

subduing 192:19

sub-fertile

203:24

subfield 175:7

subject 82:15

88:24 174:5

222:9 241:22

subjective

19:25 47:19

95:23 96:20

96:22

subjectively

97:10

subjectivescoring 72:10

subjects 118:14

209:15

submit 88:21

132:20 138:9

281:3

submits 230:11

submitted 40:18

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

subunit 119:24

success 198:2

278:8

successful

162:2 164:21

successive 284:17

suckling 50:8

suffer 216:15

suffers 216:4

sufficient 300:12

sugar 279:20

sugarcane

218:22 261:19

263:19 264:8

269:4

suggest 27:12

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

suggested 47:14

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

summarizes 170:17

summarizing

81:2 145:20

166:19

summary 15:19

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

summer 16:6

268:25

super-physiologic

114:15

supplement 183:25

supplied 283:13

supplier 284:13

suppliers 284:9

286:1 287:5

supplies 246:4

248:22 283:5

supply 174:7

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

support 94:21

94:24 95:1 106:5

112:25 145:9

155:23 210:1

215:24 225:24

supported 81:18

91:20

supporting 285:10

supports 119:17

177:16 299:21

299:22

suppose 241:22

supposed 243:5

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

116:16 117:3
FIFRA 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

surgically 114:25

surplus 88:5

surprise 221:24

245:16

surprising 303:20

Surprisingly

173:19

surrogate 159:1

159:6

surrounding

92:6 92:13

Survey 4:22

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

sustained 267:1

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 62:25
FIFRA 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

Suzawa 206:4

207:5 208:11

211:12

Swan 203:20

SWAT 178:21

178:25

switch 253:10

253:16

switching 249:7

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

taking 39:16 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

232:13 236:12
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 461

315:23

talking 169:18

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

Tanner 15:12

target 83:22

targeted 128:8

225:25

Targets 14:4

task 224:13 261:3

261:4 261:25

tasks 70:9

tattoo 46:5

tattooed 26:6

26:20 46:1

TCDD 21:5 21:10

TCT 184:16

teach 16:8

teaching 267:8

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

technology 242:11

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

tend 109:8 240:13

245:17 245:18

246:10 246:12

tended 210:18

tends 246:16

tenfold 149:4

155:5

tentatively 87:22

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

316:11
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 462

test 31:22

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

testicular 190:10

190:13 194:23

200:20 201:8

202:16 207:16

207:22 208:1

testified 224:19

testify 268:11

testifying

226:5 226:12

testing 138:22

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

109:11 114:18
FIFRA 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

thereafter 102:3

thereby 126:19

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

third 31:24

43:4 129:11

160:15 167:11

177:4 246:11

272:2 274:25

thorough 23:2

58:17 182:16

thoughts 37:12

47:9 47:15 62:23

261:10

thousand 107:9

thousandfold

78:10

thousands

234:13 251:25

256:12
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 464

three-block

230:15 231:18

three-fourths

261:20

threshold 176:7

176:8 176:9

177:11 177:20

177:22

thresholds 177:7

thriftiness 50:7

throughout 56:2

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

tightly 112:16

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

Tillit 207:20

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 48:7

Tom 196:6

196:17 196:22

tomorrow 260:21

289:2 290:8

290:15 291:1

320:22 321:5

321:14 322:12

322:25

tonic 108:6

108:14 110:1

110:14 117:17

tonight 157:2

291:3 321:1

Tony 106:17

106:22 106:23

317:14 317:23

318:13 318:24

319:3 319:6

319:24 320:10

tool 178:7 183:24

184:11 281:1

tools 176:2
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 465

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

totally 119:14

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

tox 30:4 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

toxicology 3:10

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 25:21

training 28:16

28:17

transcription

211:10

transfer 16:20

transient 37:17

38:3 42:12 67:16

68:1 69:22 161:8

transitory

85:23 134:6

translate 69:4

translated 87:4

translation 54:1

transparency

282:7

transparent 224:9

225:16 270:12

272:14 284:23

287:14

transparently

273:9

transport 4:23

transverse 23:21

trapezoidal 9:17

tray 55:21

treat 179:20

213:14

treated 21:11

28:6 29:13

60:8 65:24 65:24

118:23 127:2

132:17 133:5

135:22 135:24

136:4 136:6

136:15 136:17

136:20 164:17

165:1 189:24

191:8 229:24

236:22 261:19

293:12 302:4

306:1 306:4

308:1

treating 104:9

treatment 29:4

30:1 32:24

33:1 49:6

98:15 99:4

102:10 102:11
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 466

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

trend 264:19

trending 166:2

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

tried 47:21

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

try 8:9 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

trying 27:24

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

Tuesday 225:14

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

117:3 149:21
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 467

185:16 189:16

193:12 193:24

206:1 220:24

227:12 260:21

281:12 322:4

turned 85:2

189:10 189:12

191:15 211:14

turning 280:7

turns 138:14

212:8 295:14

turtles 207:25

208:19 208:23

twice 25:16 44:21

45:1 45:7

45:14 45:16

twofold 149:6

149:14 155:6

two-generation

164:11

two-way 295:17

Tyler 277:13

277:16 277:17

289:21

type 72:19

76:19 76:20 79:4

89:17 93:15

93:22 95:17

96:25 122:16

139:5 139:9

200:12 201:5

241:21 247:21

248:6 321:25

types 97:1 122:12

138:23 139:14

139:25 180:24

242:13 256:15

typical 25:17

35:15 58:12

58:24 66:8

124:25 132:23

193:8 193:10

typically 25:23

34:5 34:5

35:14 52:1 65:19

65:20 169:24

175:21 193:1

223:22 225:20

Tyree 83:23

Tyrone 185:11

185:18 185:20

196:7 196:21

196:23 290:16

U

U.S 4:25 14:18

14:24 75:14

195:9 229:8

259:15 259:25

261:18 262:7

272:15 274:14

277:25 278:23

283:4

U.S.A 175:8

U.S.'s 205:9

UC 91:11

Ueda 210:17

Ug/g 302:11

uh-huh 48:23

49:13 50:9 50:19

54:11 61:11

64:19 69:12

293:22 300:16

308:7 308:18

317:22 318:12

319:23 320:9

ultimately

122:8 144:22

145:8 145:12

147:25 179:16

187:16 253:21

299:23 317:5

unable 123:24

unaffected 28:11

unanswered 188:8

unbiased 57:14

unborn 215:3

uncertain 261:7

261:8

uncertainty 78:22

144:25 265:12

266:16

unclear 11:25

61:14 110:21

112:21

underestimate

12:17 262:4

undergoes 147:24

undergoing 24:3

306:11

undergone 42:18

92:23

underlying 76:7

110:25 115:10

212:20

underneath 48:17

undersized 19:18

understand

11:23 12:22 14:4

14:10 15:21 26:4

43:21 49:1 51:25

63:19 64:9
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 468

67:2 74:10 91:14

101:1 110:24

145:5 150:7

153:4 168:17

171:8 171:12

173:13 173:14

173:17 173:25

174:6 174:18

178:17 183:11

183:17 184:1

196:14 216:2

224:15 231:6

233:11 260:4

260:19 265:24

289:6 301:22

303:25 304:14

317:1

understanding

75:24 113:4

145:2 145:20

146:3 174:21

180:3 181:2

264:4 266:13

287:23 313:22

understood 11:8

265:19 292:17

321:8

undertake 261:24

undertaken 284:23

undetectable

117:18

unemployment

278:13

unequivocally

116:17

unexplained 272:4

unexposed 187:25

unfamiliar 234:21

unfinished 170:5

unfortunate 80:20

unfortunately

39:21 68:7 131:3

173:9 240:14

259:22 270:13

288:23 312:3

312:7

unhelpful 279:5

unintended 267:4

uninterrupted

319:18

Union 219:1

unique 101:24

240:17

unit 16:2 33:3

33:8 33:12 61:20

61:25 62:11

116:10 116:10

120:15 173:17

250:20

United 4:22

253:18 256:25

258:8 267:16

university 2:10

2:25 3:7 3:16

3:20 3:25 4:3

4:7 4:11 4:19

5:3 5:8 5:12

5:21 5:25 6:5

6:11 15:8 40:1

79:10 87:20 91:4

106:18 106:24

121:14 146:19

151:8 151:18

157:23 158:10

255:14 258:22

268:23

unjustified

280:25

unknown 265:20

unless 201:14

272:7 297:19

unlikely 179:11

unnamed 229:9

unnecessary 261:6

unplanned 269:12

unprecedented

267:14

unpublished

202:25

unrealistic

265:23

unrelated 226:2

316:18

unsupported

282:11 287:12

unsurprising

170:22

untreated 241:21

unusual 174:15

269:12

unwavering 262:2

upcoming 203:1

upon 8:2 54:17

87:24 164:5

198:18 216:23

220:16 223:13

268:21 269:16

upper 123:13

124:24 132:23

135:23 140:1

upregulated
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 469

187:14

upregulates

211:18

upregulation

211:7

ups 8:15

upset 212:11

216:22

upstream 83:25

84:6 124:2

211:14

uptake 97:7 97:11

100:11 154:8

155:9

upwards 189:22

urge 286:25

urine 203:23

204:16 204:21

USDA 255:13

259:13

useful 23:11

178:17 223:25

234:1 273:11

USEPA's 15:2

USGS 32:2

169:14 172:17

173:2 175:2

182:14 182:17

283:9 283:11

315:7

usually 18:16

44:16 53:5

55:3 55:21

62:8 204:18

uterine 41:21

235:2 235:7

utero 27:1

91:16 94:8 95:15

102:20 105:16

106:6 308:1

utero-exposed

26:25

uterus 162:14

193:19

utilize 256:4

256:25 258:10

utilized 97:6

127:6 256:10

utilizing 128:17

UV-related 246:18

V

vacuum 260:7

vaginal 27:5

29:20 30:23

37:21 96:4

96:9 96:18 99:14

99:21 103:5

105:5 106:2

135:25 136:8

136:12 159:1

163:21 164:7

307:19 307:25

valid 103:11

validate 101:15

183:1 183:13

184:12

validated 47:20

106:1

validating 180:15

validity 282:10

valuable 153:2

171:11 183:13

267:17

value 182:5 182:9

210:23 233:6

233:21 259:14

260:12 269:2

values 10:5

146:18 152:3

152:5 154:17

155:15 162:7

173:5 182:4

182:4 182:11

302:8

vanilla 312:24

variability 35:23

161:17

variable 62:12

248:3 248:4

variance 15:13

18:14 295:18

295:18

variation 105:6

166:3

varies 64:20

variety 93:2

93:11 100:16

158:17 158:22

163:21 202:23

266:25

various 8:2 75:19

97:18 100:9

102:12 175:16

175:19 185:12

232:7 239:6

240:23 242:19

256:15

vary 52:6 52:9

110:15

varying 22:13
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 470

31:17 127:2

vasculature 122:8

vegetables 218:21

vehicle 97:24

150:3 302:4

305:5 305:6

307:25

vehicle-exposed

102:16 103:9

ventral 35:6

38:25 38:25

58:14 58:16

58:19 59:2

275:17 275:21

275:24 276:1

276:3 276:9

ventricle 129:11

verbally 151:15

verified 85:8

152:25

verify 233:18

versus 10:12

47:22 70:7

83:2 107:3 107:4

143:5 145:23

151:20 153:24

161:24 163:1

165:3 167:13

236:6 243:24

304:3 304:19

304:21 305:13

305:24 306:17

313:2 313:21

vertebrate

186:2 200:1

200:3 201:16

207:9 209:2

212:9 215:6

vertebrates 208:3

vessels 109:24

vested 219:9

veterinary 2:24

3:6 28:17

via 100:10

104:9 196:20

viable 189:13

Victor 202:25

view 13:19 71:8

110:1 148:6

235:18 279:4

282:9

views 278:10

violation 244:9

244:10 273:22

violations

244:9 244:16

Virginia 5:17

277:21

virtually 12:1

virtue 307:21

visible 39:3

visibly 201:21

visit 252:8

visual 19:25

20:15

visualize 125:5

132:16

vital 278:8

vitellogenin

194:1

vitro 125:16

125:18 146:13

149:22 155:1

160:9

vivo 146:6 146:24

154:25 212:22

VMP 174:10

292:3 292:15

VO 30:20

voice 186:21

volume 225:20

volumes 179:15

voluntarily 77:24

77:25 78:22

305:21

Voluntary 170:1

voted 30:4

vulnerability

173:14 180:4

180:5 180:22

183:19

vulnerable 47:1

175:13 214:21

214:25 215:2

W

wait 296:18 297:5

walk 65:5

Waring's 200:6

Washington 6:6

Washington's

278:22

washout 146:12

146:12 146:25

wasn't 35:18 53:6

68:5 89:3 102:18

172:23 182:7

186:5 212:14
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 471

235:14 302:19

303:7

wastewater 240:17

watch 34:25

water 2:9 4:25

53:17 53:18 54:4

60:18 60:24 74:8

77:12 77:15

77:15 77:17

77:18 81:13

86:24 90:10

154:6 156:12

156:19 158:1

158:3 168:13

168:25 169:8

169:10 169:10

169:11 169:12

169:13 169:14

169:14 169:17

169:18 169:20

169:21 170:3

170:4 170:9

170:22 171:1

171:2 171:21

171:22 171:22

172:3 172:4

172:8 172:16

172:22 173:12

173:16 173:16

173:20 173:23

174:4 174:5

174:24 175:13

179:9 179:10

179:12 179:14

179:16 179:19

179:21 180:8

180:9 180:11

180:17 181:4

181:25 183:15

183:18 183:18

210:24 214:22

240:2 241:2

241:7 241:21

241:22 242:5

243:17 243:18

243:23 243:23

243:25 244:2

244:6 244:12

245:11 245:20

246:4 247:3

247:4 247:17

247:18 247:25

248:18 248:21

249:20 250:8

250:14 255:24

256:8 257:13

257:19 282:18

282:20 282:22

283:1 283:3

283:5 283:10

283:10 283:11

283:11 283:14

283:15 283:16

283:17 283:21

283:22 283:24

284:3 284:4

284:5 284:7

284:9 284:10

284:12 284:13

284:18 284:25

285:1 285:3

285:12 285:24

285:25 285:25

286:1 286:7

286:12 286:14

286:19 286:19

286:23 287:2

287:4 287:5

287:16 291:8

291:19 291:20

292:2

Waterborne 168:6

water-quality

175:2 247:2

255:7 255:10

waters 265:3

water-sampling

90:21

watershed

172:18 174:4

174:8 174:18

174:22 176:22

177:6 177:12

178:5 178:19

180:5 181:25

183:19 184:5

watersheds 168:25

172:4 172:7

174:24 177:15

177:21 177:24

178:3 248:20

292:17

water-supply

248:22 249:17

water-treatment

248:6

ways 169:1 178:18

198:19 221:4

297:2 303:5

weak 130:19

266:15

weakly 112:16

weaned 99:13

136:5

weaning 53:3

136:16 137:2

137:7

weapon 263:10

weather 182:1
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 472

292:10

website 220:10

221:6 225:11

we'd 26:23

74:25 225:8

258:17 315:14

Wednesday 74:4

weed 254:10 263:1

weed-control

263:2

weeds 253:3 253:4

254:8 254:13

254:21 263:11

263:16 263:18

week 16:7 237:7

251:12 303:23

weekly 78:7

weeks 16:8

86:15 136:7

136:10 136:18

137:19 139:19

139:22 164:3

164:17 237:14

237:17 269:21

303:21

Wegmeyer 277:13

277:16 277:17

281:5 289:21

weighed 265:15

weight 24:15

24:16 24:16

24:19 24:21

25:20 28:5

28:7 28:7

28:10 30:21

30:23 31:3

31:7 31:13 31:15

34:7 36:14 36:16

36:19 36:20

36:21 36:23

36:24 37:2

37:9 37:11 37:15

37:17 38:12

39:11 45:4

49:5 49:12 49:15

50:6 50:11 50:23

50:25 51:2

51:4 62:11

63:7 63:10

69:1 69:10

71:6 76:16

94:3 94:5

94:14 94:19

94:24 95:6 98:12

98:14 98:18

98:20 98:23 99:1

99:3 99:6 131:10

131:11 131:12

131:17 131:18

131:19 132:14

137:6 140:5

142:19 147:5

152:13 153:7

162:15 182:19

192:20 198:18

203:3 203:8

203:12 235:3

235:7 237:6

237:9 237:24

238:23 260:11

267:3 293:11

304:18 305:15

306:12 307:23

308:3 308:23

309:3 309:6

309:8 309:23

weights 42:12

159:7 160:2

165:20 306:5

308:20 309:18

Welch 20:5

welcome 2:5

6:25 7:11 74:3

157:11 185:15

217:25 228:12

281:13

welcomes 278:4

we'll 6:14 7:7

7:23 13:15 51:12

55:9 55:9

57:16 73:18

90:19 143:22

144:4 157:3

157:5 157:6

157:7 157:18

157:25 169:5

175:11 185:7

217:16 222:6

227:10 228:2

228:8 281:6

288:2 288:7

291:3 303:24

322:13 322:18

322:19 322:22

322:25

well-developed

17:16

well-known 20:3

wells 149:23

well-versed 41:19

we're 7:15 9:1

9:7 11:20

12:13 13:18

18:21 23:15 35:2

42:24 43:17 48:4

48:6 48:6

48:13 48:18 52:1

55:22 55:25 56:1
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 473

62:6 74:21

76:3 78:11 78:17

79:9 81:15 81:23

83:12 90:13

111:5 150:1

157:22 168:8

168:10 168:13

169:17 172:12

177:9 183:19

183:20 191:4

200:12 201:12

207:8 210:14

212:6 218:18

221:4 221:24

223:10 224:7

225:1 242:13

249:11 252:17

252:17 252:24

254:10 255:19

257:25 258:3

260:17 267:22

271:21 292:1

307:13 308:20

321:16

Wes 4:21

WESLEY 4:21

western 277:20

we've 31:2

37:13 38:19

38:20 39:7 39:10

63:2 63:13 78:24

81:1 91:13

95:3 106:10

122:2 125:16

128:3 131:21

134:1 147:19

153:20 154:25

163:23 172:13

174:19 174:23

174:23 175:6

176:2 180:14

185:25 191:12

192:8 192:9

193:21 194:1

194:5 194:16

194:18 194:22

194:24 195:3

201:18 204:4

207:12 208:7

208:10 210:13

218:13 222:16

223:5 224:6

225:9 227:4

230:6 232:12

254:4 256:3

256:12 257:5

257:7 257:16

282:6 294:7

whatever 33:25

55:11 68:12

71:24 85:21

182:24 263:23

299:8 299:25

wheat 258:20

whenever 252:21

whereas 54:16

84:19 94:18

133:12 134:22

139:10 163:6

177:23 189:23

190:13 193:24

246:24 305:3

305:20

whereby 95:5

100:8

WHEREUPON 74:2

157:10 228:11

323:2

wherever 317:5

whether 35:20

62:19 66:22 72:9

72:10 76:10

76:12 94:8 97:19

112:4 112:20

116:15 131:23

137:22 141:15

183:10 194:6

194:8 194:18

196:21 203:4

216:20 229:24

235:25 236:2

238:3 239:2

243:18 248:8

248:25 273:8

282:17 287:10

287:13 291:19

303:14 304:1

whichever 317:6

white 15:9

60:16 75:3

174:12 217:19

217:25 218:1

218:3 221:15

227:15 227:16

227:19 227:24

228:2 228:6

228:10 228:15

228:16 228:18

228:23 239:22

239:23 243:12

251:5 251:6

258:16 258:17

267:20 269:21

269:24 270:10

289:25 290:5

whitepaper

172:3 173:21

Whitman 219:19

whole 15:19
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 474

16:4 20:22 21:24

41:17 43:15

49:15 68:7

83:3 92:20

95:8 95:18 100:7

100:15 127:10

180:21 242:12

243:24 280:14

303:11 306:15

309:24 311:22

312:12

whole-mount 23:15

wholly 279:25

whom 144:14

who's 80:15 202:6

whose 170:9

210:23

wide 66:14

widely 96:15 97:5

wider 276:2

widespread 279:16

width 181:9

wife 23:1

WIL 91:21

121:20 146:7

310:14 310:18

wild 194:19

wildlife 53:17

53:23 198:9

258:4 258:4

willing 45:6

227:22 274:20

274:21

window 39:14 78:5

windows 29:8

29:13 40:5

232:15

wing-shaped

129:10

wire-bottom 42:4

wise 161:9 278:19

279:6

wisely 8:5

wish 267:18 277:8

Wistar 132:5

132:22

withdrawal

124:7 154:15

154:18 155:15

wives 203:25

Wolf 28:15

women 5:23

14:15 14:16

14:18 14:22

106:20 118:22

119:3 119:8

210:23 213:3

319:17

wonder 54:8

227:17 227:21

228:25 233:24

280:12 280:16

wondered 64:10

66:19

wondering 46:15

52:20 58:24

64:18 309:19

314:23

work 7:19 11:25

14:8 14:9

14:12 15:16

20:11 20:15 21:5

21:5 25:10 37:14

63:14 72:14 75:6

75:23 75:25 76:2

79:1 79:3 79:5

79:18 81:1

81:3 81:3

82:13 83:20

84:20 87:19

91:13 91:14

91:18 91:20

93:17 93:22 94:4

94:11 96:23

96:25 97:8

97:8 117:10

144:16 151:21

153:1 155:24

160:18 171:17

174:19 179:1

182:18 186:6

186:10 186:17

188:1 191:4

194:5 194:10

195:8 195:15

195:18 195:21

197:10 198:4

198:4 198:12

200:6 200:6

200:22 200:25

202:17 204:25

206:25 207:2

212:23 214:13

214:17 215:4

215:18 216:20

216:21 222:21

224:17 227:8

230:13 230:17

230:23 231:12

240:1 253:11

255:22 256:3

262:18 273:19

280:9 281:20

287:9 312:20

312:24 313:2
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 475

313:11 318:19

worked 20:17

75:18 186:15

229:9 231:1

240:1 255:4

259:12

workers 204:14

205:10 213:22

working 7:18

47:13 48:13

48:18 72:21 78:1

79:23 83:17

126:18 128:20

183:19 186:20

191:22 201:5

201:12 209:17

229:3 230:7

255:10

works 120:9

225:15 255:7

257:3 258:7

workshop 72:4

world 14:16 14:16

71:19 205:6

205:15 205:20

252:19 253:25

265:13 269:9

278:1 282:1

317:16

world's 267:15

worry 206:4

279:23

worse 27:1

31:16 38:22

42:22

worsen 38:20

worst 39:6

worst-case

17:19 60:1 172:9

249:8 249:8

249:11

worth 252:19

255:16 255:21

280:9

wrap 142:12

143:12 156:17

157:16

wrap-up 156:8

157:24

write 212:23

writing 233:7

written 209:10

225:13 272:22

272:23 272:24

272:25 274:10

275:15 287:24

wrong 85:25 234:7

234:8 234:9

281:5 292:25

wrote 195:23

196:7 198:17

198:23 209:11

209:14 209:16

209:18 212:17

216:19

X

Xenopus 186:18

191:1 197:14

xylene 16:20

16:22

Y

Y-chromosome

208:6

year's 292:6

yelled 235:4

yellow 31:10

104:4

Yep 277:1

yesterday 7:2

9:11 9:16

13:25 21:17 77:7

77:11 86:20 88:9

89:2 89:19

90:1 135:20

144:18 145:14

160:5 160:8

162:5 171:5

171:13 184:16

226:10 298:19

yesterday's

8:15 8:19 8:25

yet 134:10

191:4 221:10

269:11 278:24

290:11 292:13

303:23 308:15

319:17

yield 263:3

yields 263:7

yoke 310:11

yoked 98:2 98:4

305:3

yolked 194:14

York 196:19 221:5

221:7

you'll 18:18

19:19 20:7 20:20

33:11 78:23 79:4

79:9 82:23 83:13

90:6 106:12

190:8 321:4
FIFRA SCIENTIFIC ADVISORY PANEL 09/15/10 CCR#15732-6 476

young 39:16

87:7 94:24 132:5

135:4 137:18

139:19 142:18

304:1

younger 137:10

yourselves 220:18

you've 9:19

10:4 11:3 64:8

117:16 180:20

180:22 233:21

239:5 264:5

291:13 301:15

Yup 12:7

Z

zebrafish 206:5

208:12