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 U.S. ENVIRONMENTAL PROTECTION AGENCY (EPA)

 + + + + +

 FEDERAL INSECTICIDE, FUNGICIDE AND RODENTICIDE

 ACT SCIENTIFIC ADVISORY PANEL (FIFRA SAP)

 + + + + +

 REEVALUATION OF THE HUMAN HEALTH EFFECTS OF

 ATRAZINE: REVIEW OF EXPERIMENTAL ANIMAL AND IN

 VITRO STUDIES AND DRINKING WATER MONITORING

 FREQUENCY

 + + + + +

 DOCKET NO.: EPA-HQ-OPP-2010-0125

 + + + + +

 MONDAY,

 APRIL 26, 2010

 + + + + +

 The Panel convened at 1:00 p.m. in the

Hamilton Ballroom of the Hamilton Crowne Plaza

Hotel, located at 1001 14th Street, N.W.,

Washington, D.C., Steven G. Heeringa, Ph.D.,

Chair, and Kenneth M. Portier, Ph.D., Session

Chair, presiding.

FIFRA SAP MEMBERS PRESENT:

STEVEN G. HEERINGA, Ph.D., Chair

KENNETH M. PORTIER, Ph.D., Session Chair

JOHN R. BUCHER, Ph.D., DABT

JANICE E. CHAMBERS, Ph.D., DABT, ATS

GERALD A. LeBLANC, Ph.D.

DANIEL SCHLENK, Ph.D.
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FQPA SCIENCE REVIEW BOARD MEMBERS PRESENT:

SUSAN F. AKANA, Ph.D.

RICHARD H. COUPE, Ph.D.

KENNETH BARRY DELCLOS, Ph.D.

PENELOPE A. FENNER-CRISP, Ph.D., DABT

ROBERT J. GILLIOM, Ph.D.

RICHARD GREENWOOD, Ph.D.

WILLIAM L. HAYTON, Ph.D.

STEVEN D. HOLLADY, Ph.D.

TERESA H. HORTON, Ph.D.

KANNAN KRISHNAN, Ph.D.

HERBERT K.H. LEE, Ph.D.

KEVIN T. O'BYRNE, Ph.D.

NU-MAY RUBY REED, Ph.D., DABT

JEAN F.L. REGAL, Ph.D.

DANIEL J. SELVAGE, Ph.D.

CARMEN J. WILLIAMS, M.D., Ph.D.

LINDA J. YOUNG, Ph.D.

ALSO PRESENT:

JOSEPH E. BAILEY, Designated Federal Official
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 C-O-N-T-E-N-T-S

 Page

Opening of Meeting & Admin Procedures 4

Introduction & Identification of 6

 Panel Members

Welcome & Opening Remarks 12

Welcome & Introductions 30

Intro: Status of Reevaluation of the 34

 Health Effects of Atrazine

Reevaluation of Human Effects of 43

 Atrazine

Proposed MOA for Atrazine & Atrazine 53

 Metabolites

Review of Atrazine Immunotoxicity 134

Neurological Effects of Atrazine 171

Summary of Non-Cancer Mammalian 199

 Toxicity Reevaluation

Approaches to Evaluating Water Sampling 217

 Strategies & Frequency of Monitoring

Adjournment 261
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1 P-R-O-C-E-E-D-I-N-G-S

2 1:09 p.m.

3 MR. BAILEY: Good afternoon, everyone. 

4 My name is Joe Bailey, and I'm with the FIFRA

5 Scientific Advisory Panel staff. I'll be serving

6 as the Designated Federal Official for this

7 meeting, and I want to welcome everyone, this

8 afternoon. 

9 We have a three and a half day meeting

10 set up here, and I'm very pleased to kick this

11 meeting off this morning -- this afternoon, and

12 get it underway.

13 As the DFO, I serve as a coordinator

14 between the Panel, the Agency and the public, in

15 putting this meeting together.

16 The FIFRA Scientific Advisory Panel

17 only provides advice and recommendations to the

18 Agency. All decision making and regulatory

19 decisions are left up to the Agency, and they

20 take the advice and recommendations as they see

21 fit.

22 We have worked with all of the Panel
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1 members, in reviewing ethics requirements. They

2 have all submitted financial disclosure

3 information that we, at the Agency, have reviewed

4 and made sure that we -- that all of the ethics

5 requirements have been met.

6 Part of the requirements, under the

7 Federal Advisory Committee Act, is that this is a

8 public meeting. We do provide an opportunity for

9 public comment, and the -- that is set aside for

10 tomorrow morning. 

11 So, if anyone has a desire to present

12 public comments, please, let me know. If you

13 haven't registered ahead of time, I ask that you

14 keep your comments to five minutes or less.

15 There is a public docket that we've

16 set up for the meeting. It should be on the

17 agenda, the docket number. Everything that is

18 presented in this meeting will be in the docket.

19 The presentations that EPA will be

20 putting forward today are current -- they should

21 be available in the docket, as of now, and any

22 public -- any additional public comments or other
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1 materials that come of -- become available during

2 the meeting will also be placed in that docket.

3 I'm very pleased to introduce Dr. Ken

4 Portier, sitting to my right, who will be serving

5 as the Chair for this meeting, and without any

6 further adieu, I'll turn the mic over to Dr.

7 Portier.

8 SESSION CHAIR PORTIER: Good afternoon. 

9 I want to welcome all of you to this meeting of

10 the FIFRA Scientific Advisory Panel on the

11 Reevaluation of the Human Health Effects of 

12 Atrazine Review of Experimental Animal and In

13 Vitro Studies and Drinking Water Monitoring

14 Frequency.

15 I'll give a special thanks to our

16 audience. I think they have ordered a few more

17 chairs. We're going to accommodate everyone.

18 As many of you know, this is kind of

19 the second in a series of three meetings that the

20 Panel is having on atrazine this year. 

21 We've put together -- the SAP staff

22 has put together a very good panel of experts, a
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1 mixture of experienced panelists, with some new

2 people, some new voices. 

3 So, at this point, I'd like to

4 introduce the Panel. I'll start with myself. I

5 am the Director of Statistics with the American

6 Cancer Society National Office in Atlanta. I'm a

7 bio-statistician and a permanent member of the

8 SAP Panel, and I'll move to Dr. Heeringa here, on

9 my right.

10 CHAIR HEERINGA: Good afternoon,

11 everyone. I'm Steve Heeringa of the University

12 of Michigan. I'm presently the Chair of the

13 permanent FIFRA SAP and look forward to this

14 three and a half day session, and I want to thank

15 my colleague, Ken Portier, for agreeing to Chair

16 this.

17 DR. KRISHNAN: Good afternoon. I'm

18 Kannan Krishnan from the University of Montreal.

19 SESSION CHAIR PORTIER: What's your

20 expertise?

21 DR. KRISHNAN: I'm an agriculturist and

22 toxicologist by training. My expertise is in
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1 PBPK modeling, risk assessment of drinking water

2 contaminants and chemical mixtures.

3 DR. GREENWOOD: I'm Richard Greenwood

4 from University of Portsmouth in the United

5 Kingdom, and I've got a broad background in

6 pesticide toxicology and also in

7 pharmacokinetics.

8 DR. FENNER-CRISP: I'm Penny Fenner9 Crisp. I'm currently a consultant and live in

10 Charlottesville, Virginia, a one-time employee of

11 EPA, including the Office of Pesticide Programs

12 for a few years, and the newest member of

13 Virginia's Pesticide Control Board. So, I'm back

14 in the regulatory milieu.

15 DR. REED: I'm Nu-may Ruby Reed from

16 California Environmental Protection Agency. I do

17 pesticide risk assessment and address pesticide

18 risk assessment issues for our group.

19 DR. LEE: I'm Herbert Lee. I'm a

20 statistician at the University of California,

21 Santa Cruz.

22 DR. YOUNG: I'm Linda Young. I'm
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1 Professor and Associate Chair of the Department

2 of Statistics, University of Florida.

3 DR. COUPE: Richard Coupe, I'm with the

4 U.S. Geological Survey. I've worked on fate and

5 transport of pesticides or agricultural

6 chemicals.

7 SESSION CHAIR PORTIER: Dr. Selvage?

8 DR. SELVAGE: Yes, I'm Dan Selvage,

9 Idaho State University, specializing in HPA axis

10 and how gonadal hormones affect it.

11 DR. O'BYRNE: My name is Kevin O'Byrne

12 and I'm from King's College London and my

13 interests are in the effect of stress on

14 fertility.

15 DR. AKANA: I'm Susan Akana. I'm from

16 the University of California, San Francisco. I'm

17 a physiologist and my area is the stress axis and

18 its interaction with energy balance.

19 DR. HORTON: I'm Theresa Horton. I'm

20 from the Department of Neurobiology and

21 Physiology at Northwestern University in

22 Evanston, Illinois. My specialty is reproductive
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1 neuroendocrinology and maternal fetal

2 interactions in the developing neuroendocrine

3 system.

4 DR. DELCLOS: I'm Barry, or Kenneth

5 Delclos from the FDA's National Center of

6 Toxicological Research and I'm working on

7 reproductive and chronic toxic effects of

8 endocrine-active agents.

9 DR. WILLIAMS: I'm Carmen Williams. 

10 I'm at the National Institute of Environmental

11 Health Sciences in North Carolina, and I'm in a

12 reproductive endocrinology and infertility

13 training position. I do research on reproductive

14 track development.

15 DR. REGAL: Jean Regal, Professor of

16 Pharmacology, University of Minnesota Medical

17 School, Duluth, Immunotoxicology and Allergy.

18 DR. HOLLADAY: I'm Steve Holladay. I'm

19 from the University of Georgia. I'm an

20 immunotoxicologist. Most of what we've done is

21 developmental immunotoxicology.

22 DR. LEBLANC: I'm Gerry LeBlanc and I'm
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1 head of the Department of Environmental and

2 Molecular Toxicology at North Carolina State

3 University and my area of interest is in

4 endocrine-toxicology.

5 DR. SCHLENK: Good morning. I'm Dan

6 Schlenk. I'm a Professor of Aquatic Eco7 Toxicology in Department of Environmental

8 Sciences, University of California, Riverside. 

9 I'm a member of the permanent Panel and my

10 expertise is on fate and effects of pesticides on

11 aquatic organisms.

12 DR. BUCHER: I'm John Bucher. I'm the

13 Associate Director of the National Toxicology

14 Program. I'm a member of the permanent Panel and

15 with a background in general toxicology.

16 DR. CHAMBER: I'm Jan Chambers. I'm a

17 Professor in the College of Veterinary Medicine

18 at Mississippi State University. I'm a pesticide

19 toxicologist with emphasis on neurotoxicology and

20 metabolism, and I'm a member of the permanent

21 Panel.

22 SESSION CHAIR PORTIER: Thank all of
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1 you for being here. A couple of, kind of, notes.

2 The agenda has been published, but

3 just note that the times that are published are

4 approximate. We're going to proceed through the

5 agenda as it goes, and my goal today is to get

6 through the EPA presentations before we leave

7 this evening, hopefully, depending on the number

8 of questions the Panel has on the presentations.

9 The second thing is, tomorrow morning,

10 we're going to have a session on public

11 commenters and if anyone wishes to speak before

12 the Panel tomorrow, please, let Joe Bailey know,

13 at this point, so we can schedule you in. If you

14 have any materials for that public presentation

15 that you want to make before the Panel, give it

16 to Joe. It will get onto the docket.

17 All of the public commenters, as well

18 as the EPA presentations are on the meeting

19 docket on the internet.

20 At this point, I'm going to turn it

21 over to Steven Bradbury, the Acting Director,

22 Office of Pesticide Programs, to make his opening
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1 remarks. Steve.

2 DR. BRADBURY: Thank you, Ken. I'd

3 like to start off, first, by thanking the Panel,

4 all the members, the standing permanent members

5 of the Panel, as well as all the ad hoc Panel

6 members for this week's peer review. 

7 I greatly appreciate the time and

8 effort it takes in preparing for these meetings,

9 the time it takes while you're at the meeting and

10 then, preparing the report, following the

11 deliberations, and the Agency greatly appreciates

12 your investment of your time and efforts and

13 talents in our peer review process. 

14 So, ahead of the week, thank you very

15 much and again, I'll be thanking you, as we

16 finish the week.

17 I'd also like to thank Joe Bailey and

18 the staff that -- the Designated Federal Official

19 who helped make these meetings happen. It takes

20 a lot of work to prepare for the meetings and get

21 all the logistics in place and I want to thank

22 Joe Bailey and his colleagues, in all the work
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1 that they've been undertaking to get ready for

2 this meeting, as well as the previous meeting

3 that we already had with atrazine.

4 I'd also like to, in advance, thank

5 the public for their participation in the

6 deliberations. 

7 As Ken Portier indicated, tomorrow

8 morning is our time for public input into this

9 peer review process and we take the input of the

10 public very seriously and it's a very important

11 part of the overall peer review process that

12 we're going forward with, and I can't stress

13 enough, the importance of the public

14 participation and transparency that an SAP review

15 brings to the decision making process that we do

16 in the Agency.

17 And it's a concept of public

18 participation, transparency and the quality of

19 science in the Agency's decision making

20 processes. There are a couple of the very

21 important principles that Administrator Jackson

22 brings to the Agency.
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1 And so, as we go through the Science

2 Advisory Panel process, which our program has

3 done for many, many years, it reinforces these

4 important concepts of the new administration, in

5 terms of ensuring that the science that we do

6 that's a foundation of all the decision making

7 that we make in the pesticide program is based on

8 the best available information and the highest

9 quality science that we can bring to bear, and

10 that includes the very important part of peer

11 review, to ensure that we're getting input from

12 our colleagues in the scientific community, as we

13 look at some very complex issues.

14 The other important aspect of a

15 meeting like this is the openness and the public

16 participation process, so that the public can

17 participate and provide input to the

18 deliberations and that the proceedings of the

19 meetings and the notes from the meetings are all

20 open and transparent, so that as people see us

21 moving forward in our decision making process,

22 the various components that are important to that
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1 process aren't mysterious. It's not a black box. 

2 In fact, it's quite the opposite, very open

3 process with a lot of lights shining on it, so

4 everyone can see how we're integrating very

5 complex scientific issues with the regulatory

6 decision making that we need to do.

7 And in that context of sound science,

8 high quality science and public participation,

9 chemical safety also reflects one of the areas of

10 emphasis of the administration, in both

11 industrial chemicals, as well as with pesticides.

12 And so, ensuring, as we go forward in

13 our pesticide decision making, that our decisions

14 are those kinds of decisions that ensure safety

15 to human health and the environment, as we go

16 forward with our decision making process.

17 I'd like to spend just a couple of

18 minutes reviewing the processes that we go

19 through, in making our regulatory decisions and

20 then how that connects with the efforts that

21 we're undertaking with atrazine.

22 As we make decisions about new
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1 pesticide products and whether or not they should

2 be allowed to go on the market, there's a very

3 extensive amount of scientific information that's

4 required by the registrants, so that companies

5 that own the products, need to bring quite a

6 large amount of information to the Agency,

7 everything from the fate and transport properties

8 of the chemical, human toxicology, ecological

9 effects, a wide variety of information needed to

10 ensure that any decisions we make about the

11 registration of a pesticide will ensure, again,

12 protection of human health and the environment,

13 including worker protection, including

14 protection, if the product is in the food source,

15 including that dietary exposures are safe, as

16 well as any drinking water exposures.

17 The information that is brought to

18 bear in the processes that we use are, in many

19 ways, similar to activities undertaken around the

20 globe. Much of the information and scientific

21 processes that we use have been developed in

22 concert with the European Union, our colleagues
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1 to the north in Canada, as well as in Australia.

2 So, the information base and the

3 processes that we use, while unique to our

4 statutes and our approach, as also integrated or

5 collaborative in nature in many ways, with our

6 colleagues around the globe, at the federal

7 level, and as well as with our collaboration with

8 our partners in the state governments, that also

9 undertake risk assessments and regulatory review

10 steps.

11 So, the importance of science starts

12 at the beginning of the life of the chemical, in

13 terms of when we decide whether or not we're

14 going to register a chemical.

15 We also have, through our statutes, a

16 requirement that we periodically reevaluate all

17 pesticides that are on the market, to ensure over

18 time, that as the science change or policies

19 change, in terms of the law or the science, that

20 all the pesticides are current, in terms of the

21 state of the science and the state of scientific

22 approaches and policy.
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1 And we have one system that we used in

2 reevaluating pesticides, that ended in the

3 2006/2008 time frame and that reevaluation

4 program, we termed the `re-registration program',

5 and that's when we completed, between 2006 and

6 2008, a reevaluation of all the pesticides that

7 were registered prior to 1984.

8 In 2007, we started our next round of

9 reevaluation, which we call the registration

10 review program, in which we're looking at all

11 currently registered pesticides, to ensure that

12 they're meeting the current scientific standards

13 and policy standards.

14 In the case of atrazine, it completed

15 its re-registration process in 2003, was the last

16 time that atrazine went through its formal step

17 of re-registration.

18 But I want to stress an important

19 concept, in terms of the process that starts the

20 chemical or a pesticide, in determining whether

21 or not it would be registered and in this

22 reevaluation process, which is on a specific time
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1 frame, is that the Agency is always looking at

2 all the pesticides, all the time, to ensure that

3 if any new information comes to light, or new

4 perspectives in interpreting the toxicology or

5 the ecological effects of a pesticide, that at

6 any time, the Agency can pause, take a look at

7 the compound and ensure that the current science

8 is such that it meets our continued requirements

9 for safety, in terms of human health and the

10 environment.

11 Now, in the case of atrazine and many

12 other products, as these products went through

13 re-registration, we required additional data or

14 confirmatory data to come in after the re15 registration decision, and in the case of

16 atrazine, in particular, we were focused on

17 drinking water and ensuring that we would have a

18 system in place that would allow us to keep track

19 of what was going on in drinking water sources,

20 to ensure the concentrations of atrazine weren't

21 exceeding our level of protection or our

22 benchmark for protection of human health.
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1 Just an example of many times

2 activities that are going on with a pesticide on

3 a periodic, sort of regular basis, a dynamic

4 process, in terms of tracking the science and the

5 status of a pesticide.

6 Now, as I mentioned before, atrazine

7 completed its re-registration in 2003, and over

8 the course of the last seven years, there's been

9 quite a bit of research done on atrazine, looking

10 at mode of action, looking at dosimetry. 

11 There's also been a lot of information

12 coming into the Agency, as a condition of re13 registration, which is in part, a significant

14 amount of drinking water monitoring data required

15 of the registrant.

16 So, the Agency felt that over -- a

17 year or so ago, that the time was right to take a

18 look at the new science that had been emerging

19 with atrazine and the context of the very full

20 monitoring information that we had for drinking

21 water sources, to do a check-in, to ensure that

22 our science is current, that our risk assessment
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1 of 2003 is still reasonable, in light of the new

2 information, and to see if whether or not we need

3 to make any adjustments in our current risk

4 assessment for atrazine, in light of the new

5 information that's come out over the last seven

6 or so years.

7 And this Science Advisory Panel

8 meeting is one of several, in which we're

9 systematically taking a look at the scientific

10 information regarding atrazine, as well as some

11 underlying methodology, to ensure that we're

12 current, in terms of the state of the science and

13 our underlying risk assessment.

14 So, back in February, we had our first

15 Science Advisory Panel meeting, which was

16 actually broader than atrazine. It was looking

17 at a number of issues, some of which are very

18 relevant to our work with atrazine, and the

19 February Science Advisory Panel meeting was

20 taking a look at epidemiology data, incidence

21 data, and asking some questions and getting some

22 feedback from the Panel, in terms of a framework,
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1 is how do you approach an integration of

2 experimental toxicology data with epidemiology

3 data, as one prepares a risk characterization, as

4 one starts to understand and better express what

5 the uncertainties may be, with the risk

6 assessment.

7 And we brought forward some example

8 atrazine epidemiology studies, as part of that

9 process of understanding, getting some feedback,

10 as to how to approach different kinds of

11 epidemiology studies and to get some initial

12 feedback, as to how to best integrate

13 experimental data with epidemiology data.

14 The Panel's report was made available

15 late last week, and we thank the Panel for their

16 efforts in working on that first peer review that

17 we had and getting the report out, and we're, of

18 course, looking at it over the weekend and

19 appreciate the input that we received thus far.

20 Today's or this week's Science

21 Advisory Panel, as you know, is focusing on

22 primarily experimental toxicology information,
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1 both in vivo and in vitro, and taking a look at

2 the non-cancer effects associated with atrazine,

3 everything from mode of action to dosimetry, as

4 well as beginning to get some feedback around

5 that transition from understanding the dosimetry

6 around the toxicology and how do you translate

7 that into monitoring frequencies in drinking

8 water, to understand what's the right time frame,

9 in terms of looking at drinking water exposures

10 in the context of the dosimetry evaluations

11 coming out of the toxicology work, so that our

12 exposure and that our effects information are

13 properly integrated.

14 In today's -- this week's peer review

15 panel will give us some important feedback, as we

16 make a progress towards our September peer

17 review, which will be taking a look, with a

18 little modification that we had to do last week,

19 will be focusing on non-cancer effects and

20 looking at experimental toxicology, as well as

21 epidemiology information in the context of non22 cancer effects, and again, taking a look at
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1 drinking water, sampling designs and frequency of

2 sampling, to ensure that our interpretation of

3 what's going on in drinking water sources can be

4 properly interpreted, in terms of the risk

5 assessment.

6 We originally had hoped to be able to

7 also take a look at cancer effects, both

8 experimental toxicology and epidemiology data in

9 September and our goal for the September

10 assessment was based on the National Cancer

11 Institute completing some key studies that

12 they've been doing in the agricultural health

13 study, and our hope that it would be at -- those

14 studies would be available during the spring, so

15 that we could have a fall review on those

16 studies.

17 Our colleagues at NCI haven't been

18 able to hit that target, so, we're looking

19 towards 2011, when the NCI studies would be

20 available and then the 2011 time frame, we'll

21 focus on cancer, looking at experimental

22 toxicology information and epidemiology data, and
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1 take a look at the cancer issue in 2011.

2 In the coming months, we'll be able to

3 give you all a better handle on the time frame

4 for taking on that specific task.

5 So, one other sort of broad comment,

6 as I wrap up, is that clearly, the information

7 that we're providing you all, and information we

8 get from the public and then the feedback we'll

9 get through the peer review process will be

10 critical for our ongoing evaluation of atrazine

11 and ensuring that our regulatory decisions are

12 based on the most current and sound science.

13 But I want to point out that a lot of

14 the topics that we'll be talking about over the

15 course of the week, also, are very important for

16 our broader program, in terms of how we undertake

17 the emerging fields or issues in toxicology and

18 risk assessment and exposure assessment.

19 And so, taking a look at mode of

20 action and understanding toxicity pathways, how

21 to understand relationships of perturbations

22 across different levels of biological
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1 organization, while clearly, very relevant to our 

2 discussions on atrazine, those concepts also play

3 out in many of our risk assessments, and as we

4 move forward in the context of the National

5 Academy of Sciences report on toxicology testing

6 in the 21st century and the use of toxicity

7 pathways, to better understand what adverse

8 outcomes may be associated with perturbations in

9 biological systems, the feedback we get on

10 atrazine will also be very helpful, as we think

11 about frameworks and approaches for other kinds

12 of chemicals.

13 As we learn more about how to

14 integrate epidemiological information and

15 experimental toxicology information with

16 atrazine, we're assuming, and I'm confident we

17 will, learn ideas and concepts that will be

18 broadly applicable to the other types of

19 chemicals we deal with and the broad activities

20 that we do in our risk assessment process.

21 Looking at life stage susceptibility,

22 obviously, critical for atrazine, but also
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1 critical for many of our risk assessments in the

2 scenarios that we deal with.

3 So, a number of broad range of

4 applicability of the work we're going to be

5 doing, and in the context of drinking water and

6 looking at monitoring frequencies and

7 understanding how to better capture information

8 in source water and drinking water systems and

9 how do you interpret that in the context of a

10 risk assessment, it's not only very important for

11 the pesticide program, but also, very important

12 for our colleagues in the office of water, who

13 implement the Safe Drinking Water Act.

14 And so, as we move forward in ensuring

15 protection of source water and drinking water

16 sources, the lessons that we'll learn today and

17 tomorrow and over the course of the next year or

18 so, are also very important for how we move

19 forward as an Agency, in terms of drinking water

20 protection and moving forward, both in monitoring

21 designs, as well as in the science of doing

22 toxicology and risk assessments.
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1 So, not surprisingly, many of the

2 individuals that you'll be hearing from over the

3 course of the week aren't just from the Office of

4 Pesticide Program and our Health Effects Division

5 and our Environmental Fate and Effects Division,

6 but also, you'll be hearing from our colleagues

7 from the Office of Research and Development, who

8 back in 2000, were instrumental in our thinking

9 about atrazine and how to move forward in our

10 understanding of mode of action, back in the

11 early 2000s, but you'll also be hearing from a

12 colleague from the Office of Water, in reflecting

13 the interaction that we had with our colleagues

14 in the Safe Drinking Water Office, in terms of

15 how to advance the science, in terms of

16 monitoring and linking that into risk assessments

17 and toxicological interpretation.

18 So, while it's OPP and we're looking

19 at issues of our statutes and how to ensure that

20 our decisions around atrazine are bringing the

21 best science to the table, again, the principles

22 that we're learning broadly applicable and
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1 reflect sort of, a broad Agency perspective, as

2 we move forward with the state of the science.

3 So, with that, unless there's any

4 specific questions, I'd like to turn it over to

5 Dr. Tina Levine, who can introduce the whole team

6 and provide some more detailed introduction into

7 the activities over the next week. Thanks.

8 DR. LEVINE: Thank you, Steve. I'm

9 Tina Levine and I'm the Director of the Health

10 Effects Division in the Office of Pesticide

11 Programs, a job that I will point out, Penny

12 Fenner-Crisp used to have, when she worked in the

13 Office of Pesticide Programs, and I would like to

14 add my welcome and my thanks to everybody that

15 Steve welcomed and thanked, including the SAP

16 Panel, certainly, and the staff of the SAP, Joe

17 Bailey, and the public, who are going to come

18 here -- who are coming here to observe and

19 comment.

20 Particularly to the Panel, we greatly

21 appreciate your time and efforts. Your feedback

22 is an important component of improving the
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1 scientific foundation for our regulatory

2 decisions, and we're particularly appreciative of

3 your commitment this year, especially the

4 permanent Panel, as we've been working hard to

5 prepare for multiple SAP meetings on atrazine,

6 and we understand the large amount of material

7 you need to consider and we appreciate your

8 commitment to the high quality science.

9 I want to acknowledge a number of

10 people who have helped work -- are presenting

11 today and have worked -- or have worked behind

12 the scenes, the OPP team, first of all, Dr. Anna

13 Lowit, who is the overall lead for our atrazine

14 efforts, Dr. Elizabeth Mendez, Dr. John Liccione,

15 Dr. Marquea King and Jessica Kidwell, among many

16 toxicologists in HED who reviewed close to 100

17 new atrazine studies.

18 I also want to thank, from the

19 Environmental Fate and Effects Division, Mary

20 Frankenberry and Nelson Thurman, and from the

21 Office of Water, Michael Messner. I don't know

22 if they're doctors or not, I'm sorry, if I've
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1 cited somebody without giving the proper titles. 

2 I should have stopped, and I'm just going to give

3 people's names from now on.

4 Nelson Thurman and Mary Frankenberry,

5 and perhaps, Michael Messner too, developed the

6 paper and will be presenting the drinking water

7 aspect of the meeting today.

8 I want, of course, to thank the Office

9 of Research and Development, our ORD team, Ralph

10 Cooper, Susan Laws, Tammy Stoker and Bob Luebke. 

11 Both Ralph and Bob will be speaking today. Our

12 colleagues at ORD are vital to this ongoing

13 reevaluation and we truly appreciate their time

14 and talent.

15 As Steve said, the Agency signed the

16 RED for atrazine in 2003. The human health risk

17 assessment that supported the RED was based on

18 the best available science at that time. 

19 The science which supports the

20 previous risk assessment, was reviewed by the SAP

21 on at least three occasions and we relied heavily

22 on your input to improve the science in our risk
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1 assessments and to inform our decisions.

2 In this current year-long review, we

3 are conducting an objective and thorough review

4 of new science. 

5 In this process, we continue to build

6 on our belief, that by understanding how a

7 chemical works in the body, its mode of action,

8 we can better interpret dose response data and

9 better understand life stage susceptibility, and

10 that factors that lead to susceptibility.

11 In this SAP, we will also discuss the

12 connection between atrazine's dosimetry revealed

13 by the toxicological analysis and its -- the

14 connection between this and potential exposure to

15 atrazine, as revealed by drinking water

16 monitoring.

17 We plan to use this information to

18 determine the frequency of water monitoring

19 necessary to ensure the continued protection of

20 public health.

21 As you will hear from the next

22 speakers, the literature review contained in our
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1 draft issue paper represents a moment in time

2 with respect to the state of the science. 

3 We are aware of important new studies,

4 which further elucidate the mode of action for

5 atrazine, that are not yet available for review.

6 We expect some of these studies to

7 become available, as we move toward preparing

8 materials for the September SAP. We believe

9 these new data will provide information to more

10 confidentially establish the causal links between

11 key events in the pathway to toxicity for the

12 hypothalamic-pituitary-adrenal axis and the dose

13 response of these key events.

14 Dr. Mendez will mention some of these

15 key ongoing studies in her presentation later

16 this afternoon.

17 So, I would like again, to thank you

18 all for your commitment and your efforts, on our

19 behalf. We look forward to your thoughtful

20 deliberations over the next few days, and I would

21 like to introduce our next speaker, Dr. Anna

22 Lowit.
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1 DR. LOWIT: The large green button,

2 yes. 

3 We're going to spend the next few days

4 talking about a lot of very detailed, very

5 technical, very sophisticated, very exciting

6 science, about some fairly diverse topics, from

7 drinking water statistics, all the way down to

8 hormone regulation, which on the surface, could

9 be -- you would not expect to talk about those

10 same things at the same meeting.

11 But what I wanted to do, before we get

12 into the technical presentations, is just take a

13 few minutes and sort of start from the beginning,

14 start from -- talk about where we need to be, how

15 we're getting there, and really, what the goal

16 is, over the next -- that we're in the middle of,

17 and we'll keep working.

18 The 2009 science and decisions report

19 from the NAS, one of the key messages in that

20 report is that the Agency needs to do a better

21 job at aligning risk assessment and risk

22 management, and specifically, putting more
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1 emphasis on problem formulation, at the very

2 beginning of the process, beginning of analysis

3 for the risk assessors and risk managers, to sit

4 down and have very detailed dialogue about the

5 goal of the analysis, what the purpose is, what

6 the scope is, what the data available for

7 analysis is, and what the risk management

8 possibilities are, so that the risk assessors can

9 work with those possibilities in mind, to put

10 together a risk assessment that the risk managers

11 can use, to make them much more -- improve

12 utility.

13 In this example of what we're going to

14 talk about today, and what this atrazine effort

15 is really about, is exactly what the NAS wants us

16 to be doing. 

17 It's about taking a risk management

18 need, which is drinking water monitoring, and

19 ensuring safe drinking water and aligning that

20 with a lot of very sophisticated science to get

21 there. That's exactly what we're going to talk

22 about.
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1 So, the risk management goal here is

2 really to have safe drinking water, whether it's

3 all over the country or just in the Midwest. So,

4 we're going to talk about two major topics.

5 We're going to talk about hazard

6 assessments and the basic goals of hazard

7 assessment are to think about sensitive

8 populations and life stages, thinking about

9 durations of exposure and dose response

10 relationships.

11 In exposure assessment, we really want

12 to think about the residues in the drinking water

13 and how confident or uncertain we are about those

14 values, because the relative confidence and

15 uncertainty gets at how much monitoring we need

16 to be doing.

17 So, we're on a very long process, you

18 know, it's a very big process, it's accelerated. 

19 We started the SAP process in February. Some of

20 you were at that meeting. 

21 As Steve said, the report from that

22 meeting just came out a few days ago, and I would
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1 say my first read of the report is that the

2 report is very consistent with what we heard of

3 the meeting, that the Panel was overall, very

4 supportive of the approach we're proposing, with

5 some very appropriate versions, I think, in fact,

6 they've already started making.

7 So, to the -- the meeting this week is

8 about thinking about animal toxicology, in vitro

9 toxicology and drinking water monitoring.

10 Originally, we had hoped in September,

11 to do a cancer/non-cancer harmonization, in a

12 weight of the evidence analysis, and to take that

13 and to merge it with drinking water and have a

14 new proposal, but as you heard from Dr. Bradbury,

15 our friends at the National Cancer Institute will

16 not have their studies from the Agricultural

17 Health Study ready in time for that. So, that's

18 been postponed. The cancer component has been

19 postponed to 2011.

20 However, we are maintaining the

21 schedule for September, on the non-cancer effects

22 and largely, as I said at the beginning, this is
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1 really the rubber meets the road analysis. At

2 the end of the day, this is about drinking water

3 monitoring and is the drinking water adequate,

4 and largely we believe that that's going to be

5 driven by the non-cancer effects, as they tend to

6 be shorter duration.

7 The longer term cancer outcomes are

8 much longer in duration, which would be less

9 frequent monitoring.

10 Okay, so, a lot of what we're going to

11 talk about over the next few days is about the

12 hazard assessment component. 

13 As you will hear from Dr. Mendez, this

14 is -- what we're going to talk about today and

15 what's in the Agency's issue paper is really a

16 snapshot in time.

17 People are doing atrazine work all

18 over the world, all over the country. People

19 that are in labs are continuing atrazine work. 

20 It's really a snapshot in time, of where the

21 state of the science was at the end of January.

22 We know that between now and the
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1 summer, there are going to be more studies, and

2 in fact, probably some important studies to think

3 about dose response and life stages, and Dr.

4 Mendez will talk to you about those later.

5 But our goal for September is to take

6 our current issue paper with the revisions that

7 we hear from all of you, the suggestions that we

8 get, the comments we get from the public, and to

9 blend in that new analysis with all the new data

10 and to do a formal weight of the evidence

11 analysis, like that we proposed back in February,

12 at the February meeting.

13 Where we will take the animal

14 toxicology data, the in vitro, the modeling, the

15 epidemiology and put it together in a mode of

16 action framework, to think about key events

17 leading to toxicity, dose response and temporal

18 concordance, do explicit evaluation of life

19 stages pre, post and perinatal effects, and we're

20 going to talk about human relevance of those

21 effects, that the qualitative and the

22 quantitative difference between the animals,
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1 particularly rodents and humans, and all these

2 effects, and that's largely where the

3 epidemiology will come in.

4 On the exposure side, on the drinking

5 water, you will hear us talk almost exclusively

6 about drinking water, because that is the pathway

7 of concern for this chemical, and as we talk

8 about the rubber hitting the road, on this

9 analysis, it's the thinking about the duration,

10 the temporal aspects of the toxicology, that will

11 drive those frequencies, and there are a variety

12 of ways to think about this, single day peaks, or

13 you can do multiple day averages of any of

14 duration you choose, basically.

15 I believe we'll show some examples of

16 shorter ones, maybe three to seven days. The 90

17 day rolling average, it was done in the last 2003

18 risk assessment.

19 A large component of the drinking

20 water analysis has to do with really

21 understanding the confidence and the data, the

22 data that we have and the data that could be
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1 collected if there was a different frequency.

2 It's important to think about it, both

3 temporally and spatially, and you'll hear Nelson

4 Thurman talking about that later.

5 You'll also see this map later. 

6 Nelson will talk about it quite a bit in a little

7 while, but I think it's a nice illustration that,

8 as you look at the blue and the dark-blue and the

9 red areas, that the areas in the middle part of

10 the country, particularly those where large row

11 crops are grown, are really the areas where

12 levels of atrazine -- we're concerned about in

13 drinking water.

14 Okay, so, in light of the new science

15 that we'll talk about, particularly on the hazard

16 assessment, in the feedback we hear from you, the

17 feedback we get from the public, we're going to

18 do two things.

19 We're going to decide if a full-blown

20 risk assessment has to be done, and what that

21 means in practice is that right now, the focus is

22 on updating the literature review, deciding of
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1 the points of departure, i.e., the line in the

2 sand where the assessment needs to move. The

3 uncertainty factors need to be changed. The

4 duration needs to be changed.

5 If one or all of those need to change,

6 based on the new science, we'll think about that,

7 if a new risk assessment needs to be done, and

8 we'll also decide if the drinking water

9 monitoring requirements for Syngenta need to be

10 changed, and that's all I've got.

11 SESSION CHAIR PORTIER: Before we go on

12 to Dr. Mendez's presentation, are there any

13 questions from the Panel, any clarifying

14 questions?

15 (No audible response.)

16 SESSION CHAIR PORTIER: Okay, we'll

17 move on. Dr. Mendez is going to be talking on

18 the human health effects.

19 DR. MENDEZ: Good afternoon. Before I

20 get started, I want to apologize. I started

21 coming down with a cold over the weekend. So, if

22 my voice breaks in and out, or if I start
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1 coughing, I apologize for that.

2 So, the goal of this presentation is

3 really to give you a very brief overview of the

4 review of the mammalian toxicity data that's been

5 conducted, as part of this reevaluation.

6 I'm going to talk a little bit about

7 our peer review history. I'm going to talk a

8 little bit about the 2003 risk assessment, to put

9 this evaluation into context, and then talk a

10 little bit about the current reevaluation.

11 I'm going to defer the really

12 technical talks to our colleagues from the Office

13 of Research and Development, but I just wanted to

14 set the stage, so you know what's coming, over

15 the next few hours.

16 Atrazine is very widely used in the

17 United States. It's approximately 70 million

18 pounds of the active ingredient per year. It's

19 used primarily on corn. It has been registered

20 in the U.S. since the 1950s, and it has been the

21 subject of numerous SAPs over the years, both on

22 topics relating to human health and ecological
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1 effects.

2 Today, what we'll be doing is, we'll

3 be concentrating on human health effects. Review

4 evaluation of ecological effects will be coming

5 in the next year.

6 All right, so, a little bit about the

7 peer review history. We had first review of the

8 rat mammary gland tumors. We were seeing tumors

9 in the Sprague Dawley rats and so, we came to the

10 SAP, the first time around, to talk about that.

11 The SAP, at that point, pointed to the

12 Agency, that we should consider the possibility

13 that there was an endocrine component to this,

14 and to try to further evaluate what the mode of

15 action for this might be.

16 Back in 2000, the SAP evaluated the

17 mode of action on mammary gland tumors,

18 reproductive and developmental findings in the

19 rat, and also weighed in on the human relevance.

20 In 2003, we had the evaluation of the

21 prostate cancer and the epi studies and the

22 relationship between atrazine exposure and
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1 prostate cancer in workers at an atrazine

2 manufacturing plant, and as Dr. Lowit just

3 mentioned, in 2009, we had a very brief meeting

4 for the permanent members of the Panel, telling

5 you about our plans to re-open or to start the

6 evaluation of the atrazine human health effects

7 evaluation and in February 2010, we had -- we

8 presented to the Panel a draft framework for

9 incorporating epidemiology and human incident

10 data into the risk assessment using a couple of

11 epidemiology studies from atrazine as part of our

12 case studies.

13 So, very briefly, the 2003 human

14 health risk assessment, and the points of

15 departure for the 2003 risk assessment are based

16 primarily on our understanding of the mode of

17 action at the time, the perturbation of the

18 hypothalamic-pituitary-gonadal axis.

19 In 2003, there were a series of key

20 events that were identified, the hypothalamic

21 effects resulting in changes in catecholamine

22 function and regulation of the pulsatile release
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1 of GnRH, leading to the attenuation of the LH

2 surge, sensation of ovulation with ensuing

3 persistent release of estrogen, increased

4 prolactin release of the pituitary as a secondary

5 consequence, resulting from the elevated estrogen

6 levels, and the prolactin in estrogen induced

7 proliferative processes in the mammary gland

8 leading to tumorigenesis.

9 So, basically, what the HPG axis

10 perturbation told us is, we had attenuation of

11 the LH surge, which led to our mammary gland

12 tumorigenesis that we were seeing in the rats, as

13 well as the delayed puberty onset.

14 When we came to the SAP back in 2000,

15 what their -- the recommendations of the Panel,

16 or what the input of the Panel was, that these

17 mammary tumors were not relevant for humans, and

18 the reason for that is that the processes that

19 lead to these tumorigenesis in the rats are very

20 different from what would happen in the human.

21 What we are seeing with the LH surge

22 is that we have a constant stimulate, with the
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1 attenuation of the LH surge, is that we have a

2 constant stimulation of the mammary gland by the

3 elevated levels of estrogen and prolactin, and

4 that is what leads us to that mammary tumor

5 development.

6 In turn, in the humans, that's -- this

7 entire process of reproductive senescence, which

8 is what's happening in the rat, is not happening

9 in the humans.

10 However, the Panel also recognized

11 that these effects may be relevant to assess

12 potential non-cancer adverse reproductive effects

13 in the humans, and that's how our 2003 risk

14 assessment is based on.

15 So, these are the non-cancer effects. 

16 The acute exposure, which for the Agency is one

17 day exposure, is based on delayed ossification in

18 rat fetuses and decreased body weight gain in

19 dams. We do not believe that that is the result

20 of the LH attenuation. 

21 It has an NOAEL and an LOAEL of 10 and

22 70 milligrams per kilogram per day. These short
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1 exposures are based on the delayed puberty onset

2 in males, with an NOAEL of 6.25 and LOAEL of 12.5

3 milligrams per kilogram, and the intermediate and

4 long-term exposures are based on the attenuation

5 of the luteinizing hormone surge.

6 Okay, so, our current analysis, what

7 are the objectives? And some of these, Dr. Lowit

8 had mentioned.

9 We wanted to conduct an objective and

10 thorough review of the new data, integrate new

11 information with existing data, to evaluate the

12 hazard ID and the dose response relationship,

13 determine the extent to which this new science

14 leads us to believe that we may need to develop a

15 new risk assessment, and reconsider, if

16 appropriate, the frequency of drinking water

17 monitoring conducted by Syngenta, with the

18 atrazine registrar.

19 The scope of the current analysis, we

20 restricted this analysis to mammalian toxicity

21 and in vitro studies. Three databases were

22 searched, EMBASE, PubMed and Medline, and we
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1 actually cast a very wide net in an attempt to

2 collect all relevant information generated since

3 the IRED was signed in 2003.

4 A database query yielded close to 300

5 articles. However, some 200 were excluded

6 because either the studies were conducted on non7 mammalian species, the articles were commentaries

8 or letters to the editor, they were abstracts

9 that lacked sufficient detail in methods and

10 results, or they were topic reviews that did not

11 present original work, or they were epidemiology

12 studies that we will be looking at, as part of

13 our epidemiology data analyses.

14 In addition to all of that, we also --

15 of the peer reviewed articles, we've also

16 included some studies submitted by the atrazine

17 registrant, and those have been placed in the

18 docket.

19 So, now, to give you sort of an

20 "upcoming attractions". The presentations that

21 you will hear this afternoon, Dr. Ralph Cooper

22 will be speaking about the mode of action
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1 analysis. Dr. Bob Luebke will be talking about

2 the immunotoxicity analysis. Dr. John Liccione

3 will be speaking about the neurotoxicity

4 analysis.

5 At the end of their presentations,

6 I'll be coming back to sort of give you a summary

7 of what that -- those analysis lead us. 

8 Then, our colleagues from EFED and the

9 Office of Water will be coming in. Dr. Nelson

10 Thurman will be talking about a purchase to

11 evaluating water sampling strategies. 

12 Dr. Mary Frankenberry will be talking

13 about evaluating the performance of sampling

14 strategies, and Dr. Michael Messner will be

15 speaking about artificial neural network

16 modeling, and one little bullet that's not

17 included there is, at the end of the day, Dr.

18 Lowit will come back and sort of, wrap mammalian

19 toxicology and the drinking water evaluations

20 together.

21 So, if there are no other questions,

22 I will turn the mic over to Dr. Cooper.
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1 SESSION CHAIR PORTIER: Dr. Chambers?

2 DR. CHAMBERS: Let me clarify one thing

3 that you said there. On slide eight, you talk

4 about the NOAEL and the LOAEL for acute. You

5 really mean just one exposure, don't you, and not

6 per day? That wasn't an extended exposure under

7 acute, was it?

8 DR. MENDEZ: No, for acute, we assumed

9 one exposure.

10 DR. CHAMBERS: One, so, it's not per

11 day, just -- 

12 DR. MENDEZ: But it's from a study that

13 has multiple exposures. It's a developmental

14 toxicity study on the rat, where animals are

15 exposed -- parental animals, maternal animals,

16 are exposed, typically from gestation day six

17 through gestation day 21. 

18 It is the Agency's policy that we

19 assume that developmental effects of that nature,

20 because of a rapidly changing environment during

21 development, may be the outcome of a single

22 exposure.
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1 SESSION CHAIR PORTIER: Dr. LeBlanc?

2 DR. LeBLANC: In your discussion of the

3 literature review, you mentioned that non4 mammalian studies were not included, and I was

5 wondering, were they excluded, with respect to

6 evaluating mode of action?

7 DR. MENDEZ: Well, we looked at them

8 briefly, but they were not -- to the extent that

9 they did inform the data, we considered them. 

10 But primarily, we were trying to concentrate on

11 the mammalian toxicity.

12 SESSION CHAIR PORTIER: Okay, let's

13 move on to Dr. Cooper, who will be talking on the

14 MOA of atrazine.

15 DR. COOPER: Thanks, Liz and Anna. My

16 presentation this afternoon is divided into,

17 essentially, three parts, where again, this time,

18 I'm going to do a little historical review of

19 what we considered the mode of action, back in

20 2003, that atrazine alters the hypothalamic21 pituitary-gonadal axis, and do a more pictorial

22 than Liz did, but with some added details that I
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1 think will help us interpret some of the more

2 recent findings.

3 The second part of this presentation

4 will look at the rationale and studies that we've

5 been looking at over the last several years,

6 indicating that atrazine may have an effect on

7 the hypothalamic-pituitary-adrenal axis, clearly

8 showing an activation of that axis, and trying to

9 fit that into the mode of action and then, the

10 last part is a brief attempt to do some synthesis

11 with the effects that we've observed and that

12 literature has reported of both these different

13 regulatory systems.

14 I put some background slides in here,

15 just to get everyone on the same track. This is

16 the way we look at the estrous cycle in the

17 female rat. 

18 Most of the studies, I'll talk about

19 in the adult animal are in the female, and the

20 regulation of the LH surge, of course, was the

21 key event, endocrine event, that was used for

22 interpreting the mode of action, back in the last
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1 Science Advisory meeting.

2 The rat has a four-day reproductive

3 cycle, four-to-five-day reproductive cycle that's

4 readily identifiable and measured by just simply

5 following the vaginal smear of the animals and

6 see if distinct changes take place over the

7 course of those four or five days.

8 The key day is, to us -- the

9 endocrinologically key day, anyway, is the day of

10 vaginal proestrus, which is right here, and I've

11 got in cartoon fashion, the indication that what 

12 happens on that day is in response to rising

13 levels of estrogen and subsequently, increases in

14 serum progesterone, coming from the ovary and

15 perhaps, the adrenal gland, there is a triggering

16 of a massive outpouring of luteinizing hormone

17 from the pituitary gland that occurs at a very

18 distinct time on the afternoon, approximate --

19 and peaks approximately two hours before dark.

20 That event is what then leads to

21 ovulation and over the evening hours, the animal

22 is sexually receptive. So, the timing of
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1 ovulation synchronized with the behavior of the

2 animal.

3 Because the rats are spontaneous

4 ovulators, there's a lot of homology between the

5 neuroendocrine regulation of the rodent

6 reproductive cycle, ovarian cycle, and the human.

7 This is another cartoon of how we see

8 the different parts, and again, to address the

9 mode of action of the HPG, I have the rat brain,

10 the hypothalamic, the hypothalamus, which is the

11 origin of the -- the neuropeptide is secreted

12 from the brain, through the portal system that

13 bathes the interior pituitary gland, GnRH

14 stimulates luteinizing hormone, luteinizing

15 hormone then stimulates the maturing follicle to

16 rupture.

17 Part of this whole system is that you

18 have other hormones, FSH and prolactin. We've

19 shown in the past that prolactin also appears to

20 be a target of atrazine disturbances, and then

21 this whole process involves feedback from the

22 ovary itself, the steroid hormones estrogen and
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1 progesterone, feeding back onto the brain, to

2 further regulate -- regulate regulation and

3 reproduction and behavior.

4 This is the kind of data that you see

5 when you measure luteinizing hormone on the

6 vaginal proestrus. 

7 This particular slide was taken from

8 a series of studies that we did, looking at the

9 intact female that was dosed with what I guess

10 now, we can -- based on the earlier work,

11 relatively low doses of atrazine, where we sought

12 to find a low LOAEL and NOAEL for this compound

13 in the intact animal, and you can see a dose14 dependent decrease in luteinizing hormone

15 occurring on the afternoon of proestrus at 1800

16 hours, which as I mentioned, was approximately --

17 is two hours prior to the time lights are out in

18 these studies, and that was the only time that

19 you see the suppression and importantly, the

20 suppression of the surge isn't a complete

21 blockade of the surge. It's lowered in a dose

22 response fashion. But these animals may, at this
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1 time, since they're young adults, still be able

2 to ovulate.

3 Again, by way of background, these are

4 data taken from an earlier study that we did,

5 showing that atrazine did block the LH surge, in

6 two different strains of animals, the Long-Evans

7 and the Sprague Dawley rat. 

8 This first slide makes the point that

9 in the Long-Evans rat, if we dose one day with

10 increasing concentrations of atrazine, this is

11 all by gavage, you can see that a single exposure

12 really doesn't do a whole lot to the secretion of

13 LH.

14 What I have here is the dose response

15 on the side. These are animals that received the

16 different doses at 16, 18 and an hour before and

17 an hour after lights out, and even up to 200

18 milligrams per kilogram per day, we're still

19 getting an LH surge in the animals, to 300. You

20 seem to see suppression.

21 If we dose those animals, however, for

22 three days in a row, you see a dramatic decrease
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1 in the amount of LH that's secreted, the control

2 animals here, being in the open bars and the

3 different doses you see there.

4 There was the lower dose, an apparent

5 delay in the peak, where it occurred at 2000

6 hours, an hour after lights out, and I should add

7 that other work we've done showed that those

8 higher doses, those animals don't peak, even if

9 you test them or evaluate them later on, in the

10 dark phase of the cycle.

11 If you look at that figure on the

12 right, the three day dosing in the Long-Evans

13 rat, it brings up another interesting thing.

14 First, of course, the main point I

15 wanted to make with this slide, is that as the

16 duration of the dosing increases, the effect that

17 the -- the effective dose decreases.

18 But the other point was that when you

19 compare strains, three days later, there's --

20 we've ran Sprague Dawley rats in the exact same

21 study that you're reviewing here with Long-Evans,

22 and you'll see that when you look at those
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1 animals, which I have plotted on the right figure

2 over here, there was still no effect in the

3 Sprague Dawleys, even after three days of dosing.

4 These are ovariectomized, estrogen5 primed animals, given the compound for three

6 days, whereas the Long-Evans were affected at

7 three days, the Spragues kept a pretty good size

8 LH surge.

9 However, if we continued dosing both

10 strains for a longer period of time, then

11 eventually, you would see that this compound had

12 an effect on the peak amplitude in all the

13 different doses in both strains, and the way this

14 works is that over here on the right panel, when

15 we dose for 21 days, we only looked at 1800

16 hours. We're pretty convinced that at those

17 doses, we'd see the peak there. 

18 So, these are animals that were killed

19 at that time, control animals at 1800 in both

20 strains, and then you dose response down.

21 So, again, the longer the duration of

22 dosing, the more effective the dose would be.
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1 Another series of studies that we did

2 back in 2000, were to look at whether or not the

3 disruption of the LH surge was dependent upon

4 changes that were occurring in the brain or the

5 pituitary or the broader axis itself, and in

6 those studies, we took apart the system,

7 essentially. 

8 First, ovariectomized the animals,

9 thus removed the ovary. We still saw effects on

10 the LH, so we sort of thought we were ruling out

11 the ovary at that time. 

12 Other studies we did is, we took the

13 pituitary out of the animal, that was dosed, and

14 looked at whether or not it could still release

15 luteinizing hormone the same way control animals

16 would do, and what you have here is a perifusion

17 system, where the animal's pituitaries were

18 placed in a bath where the medium was flowed over

19 the tissue for a period of time, went to

20 baseline, and then we dosed with gonadotropin21 releasing hormone, which is the peptide that

22 normally stimulates luteinizing hormone.
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1 Pulsed it once, saw a response, pulsed

2 it again, pulsed it -- I'm sorry, then we looked

3 at KCL, but the point is, is that there was no

4 difference there, which indicated to us that

5 these pituitaries taken out of animals that were

6 dosed for four days, were perfectly capable of

7 responding to the natural releasing factor.

8 Another study that was done by Dr. Lee

9 Tyrey, who was a visiting professor from Duke

10 OB/GYN, working in our lab, looked at the

11 pulsatile release of GnRH and here, what we have

12 is a 28 day ovariectomized animal who will start

13 to spontaneously surge -- show LH pulses that

14 occur at a frequency of about two per hour, and

15 in the control animals -- and these are mean

16 data, so they're not really as pretty as what we

17 really had, but he puts it together through a

18 program, and can show you the means.

19 But control animals, you'll see these

20 pulses, which reflects the activity of the GnRH

21 neurons in the brain. We can measure the LH and

22 every pulse of LH is reflective of increased
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1 activity in GnRH.

2 When we increase -- expose the animals

3 to 50 or 200 milligrams per kilogram -- I can't

4 read that, I hope it's 200 -- 50 and a higher

5 dose, from my eyes, I'm sorry, immediately prior

6 to this time, you can see that the 50 had a

7 little disruptive effect, but with the pulsar

8 analysis that they did, we didn't see any real

9 statistical difference, but that higher dose

10 totally flattened out the pulses.

11 What this meant to us is that

12 atrazine, in some way, was disrupting the brain's

13 control of the release of the hormone itself.

14 The next study, or in another study,

15 later on, in the same series of studies, where we 

16 were looking at the intact animal, we measured

17 the amount of GnRH in the basal part of the

18 brain, where the neurons -- or the basal part of

19 the brain, where you have gonadotropin releasing

20 hormone neurons, and we saw that the

21 concentration of GnRH tended to go up in the

22 atrazine-treated animals, which would be
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1 consistent, again, changes in the brain occurring

2 and would be consistent with the decreased pulses

3 that we saw when we looked at them in the longer 

4 ovariectomized model.

5 And then finally, we did a study where

6 we blocked the LH surge in ovariectomized animals

7 with a very high dose of atrazine and went in and

8 injected IV gonadotropin releasing hormone, and

9 it showed that the pituitary was perfectly

10 capable of responding to the neuropeptide, again.

11 So, these kinds of things told us that

12 it appears as though atrazine was working on the

13 central nervous system to disturb the pulsatile

14 release of GnRH, and I haven't showed it,

15 prolactin release, and in that way, we thought

16 that it was disrupting the ability of the animal

17 to maintain normal ovarian cycles.

18 Another key point, and again, Liz may

19 have touched on it, was, what's actually

20 happening is that as we dose these animals, we

21 were lowering the LH surge and, in a way, that

22 was analogous to what you see during the aging
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1 process of the animal.

2 Normally, the female rat, under a

3 four-day cycle, has an abundance of LH secreted

4 between -- just prior to time of lights out. But

5 actually, to get ovulation, you only need a small

6 amount of that.

7 Back with the old reference prep, it

8 was about 2,500 nanograms per mL for a peak, and

9 the people that work showed that you only needed

10 about 200, or less than a tenth of the LH, to

11 actually cause ovulation, which used to lead them

12 to speculate what the rest of that LH is doing.

13 But as the animal ages normally, or if 

14 the animal is treated with atrazine, sufficient

15 doses, what happens to the LH secretion is that

16 the peak lowers and actually, the onset of the

17 surge occurs a little bit later, sort of like

18 what we saw with that 50 milligram per kilogram

19 dose.

20 It can still cycle, again, because

21 just like those animals I showed, even though

22 they're statistically bound, they can still
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1 function to cause ovulation.

2 As the animal continues to age

3 further, it goes below that threshold. The

4 animal doesn't ovulate anymore, which I show up

5 here in this picture that everyone loves, my

6 symbol for ovulation. Those animal's eggs are

7 retained in the follicles and those follicles are

8 secreting estradiol only into the serum, but not

9 progesterone.

10 Another thing that happens, and again,

11 as Liz mentioned, because of that increased

12 estradiol, you end up with diurnal and a

13 nocturnal peak of prolactin being secreted. 

14 So, you have an endocrine milieu,

15 that's totally out of bounds with what it should

16 be, and the hypothesis that we worked with on

17 that MOA was that atrazine, like aging, causes a

18 decrease in this LH surge, which leads to an

19 early reproductive aging in the animals, and when

20 the animals show the persistent or constant

21 estrus then, it will lead to the early appearance

22 of mammary gland tumors.
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1 So, again, that's just it, in bullet

2 form. And the summary is that atrazine disrupts

3 hypothalamic control of gonadal function and it

4 contributes to early reproductive senescence,

5 producing that hormonal environment, and again, a

6 key point is, it's well known that reproductive

7 aging in the rat, as I have up there, is driven

8 by brain.

9 We could argue that. I know the work

10 of Tuck Finch and Brower argue that ultimately,

11 it's the amount of estrogen that that brain sees

12 over its lifetime, but really, the events taking

13 place within the central nervous system are

14 what's disrupting the ability of the animal to

15 produce the LH surge and it still has plenty of

16 follicles left in its ovary, so that when the

17 ovary stops cycling, there's lots of estradiol

18 that's put out there into the blood.

19 Reproductive aging in the human is

20 quite different. It's apparently driven by a

21 depletion of the follicles in the ovaries. 

22 In turn, you have a situation where
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1 with aging, you have a relatively low

2 concentration of estradiol and different

3 endocrine milieu altogether.

4 So, that's where the Agency concluded

5 that the mode of action for mammary gland tumors

6 in the rat was not relevant to, or would be

7 predictive of anything that would happen in

8 humans.

9 But what happened in those studies,

10 when we were doing that work, was, a number of

11 different outcomes showed that there were clear

12 other relevant reproductive effects that were

13 occurring when the animals were dosed with

14 estradiol.

15 Some of those are briefly mentioned

16 here, and we talk about different life stages and

17 that kind of thing. This is part of what was

18 driving some of that.

19 Atrazine will delay puberty in

20 animals. There was a study done by Tammy Stoker

21 and Susan Laws, in the male and female rats,

22 respectively. Those studies were replicated by
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1 other laboratories. Those studies were -- or

2 similar studies were conducted with the

3 validation of the pubertal assays in the -- for

4 the endocrine disrupting screening program.

5 So, it was a robust effect that was

6 repeatable, that delayed puberty does occur when

7 you dose animals with atrazine.

8 Other adverse outcomes -- and we know

9 the toxicity pathways for some of these were

10 prostate -- prostatitis, if the dam is dosed

11 during specific developmental periods. 

12 We know the disruption of ovarian

13 cycles occur, and I should mention that the

14 registrant did a very nice study, looking at the

15 age-dependent changes in ovarian cycle, or

16 estrous cycles in the rat and again, showed that

17 the reproductive cycle does decrease earlier. It

18 wasn't just a hypothesis, that in fact, these

19 things occur.

20 And more recently, there's been a

21 number of studies looking at testosterone

22 synthesis that I think again, are going to become
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1 -- maybe, we can interpret them easier, once we

2 understand what's going on with the adrenal axis,

3 but I think -- in the background paper that you

4 received, I think there was four or five studies

5 that have been published in different strains of

6 animals, saying that atrazine, for an extended

7 period of time, relatively high doses, will

8 impair testosterone synthesis in the developing -

9 - most of the studies, in the developing male

10 rat.

11 So, again, where we were with the 2003

12 SAP, there was general agreement that this

13 pesticide or herbicide was working through a

14 disruption of CNS-mediated decrease in LH and

15 that was the relevant mode of action, and the key

16 event in this whole process was a decrease in

17 luteinizing hormone that contributed to those

18 adverse outcomes, of course, with the exception

19 of the prostatitis studies, which were linked

20 more with changes in prolactin availability.

21 That's what the considered mode of

22 action was, but yet, there were still some
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1 nagging questions that existed, at least, in my

2 mind. One of them was that delay.

3 When you dose animals and you disrupt

4 the LH surge, we've worked with a number of

5 different environmental chemicals, and you do

6 this, usually, it's a very -- if it's working

7 through the brain, it's a very rapid, almost --

8 you know, within hours kind of effect that you

9 see, and that business where we saw, it took

10 several days to start to see, there is this

11 trade-off between dose and time that tended to

12 have an effect on the LH surge, always was kind

13 of intriguing to me, and I -- I just couldn't put

14 together what it was that was responsible for

15 that.

16 Secondly, in Dr. Stoker's study, where

17 she looked at everything that she could get her

18 hands on in the pubertal male, she looked at the

19 concentrations of estradiol that were present in

20 those animals, and found a significant increase

21 in the serum estradiol in the males treated for

22 21 days. That's peripubertally. They start the
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1 treatment on PMD-21 and kill on PMD-42.

2 Susan Laws -- we asked the question

3 whether or not that was true in adult animals as

4 well, because you really see, at the right dose

5 of atrazine, an increase in estrone and estradiol

6 in these animals, and Susan Laws replicated that

7 study here, with only a four-day exposure.

8 And what she found was an increase in

9 both those estrogens, in both the developing 

10 animal and in the adult, and you know, a high

11 dose and -- it was something that we, you know,

12 really didn't know what to make of, at the time.

13 But, at that time, there were a number

14 of other studies reported, either in vitro or in

15 vivo, looking at atrazine and the enzyme

16 aromatase, which was the enzyme that's

17 responsible for the production of estrogens from

18 androgens.

19 So, that led us to look at little more

20 closely at what might be going on, both in vitro

21 and in vivo, with aromatase and estrogen, and

22 whether or not that might be part of some of this
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1 -- something that we missed, in terms of the mode

2 of action.

3 So, at that time, because of the in

4 vitro studies, we were looking at -- we were

5 looking at aromatase or one of the cytochrome

6 P450s, which converts the androgens to estrogens.

7 Aromatase is present in a number of

8 different tissues in the body, some there 

9 listed, the brain, the gonads, fat and placenta. 

10 In the brain, it's responsible or plays a key

11 role in sexual differentiation of the rodent

12 brain.

13 Its regulation is different in the

14 different tissues looked at. You have different

15 promoters and other regulatory factors that are

16 involved, whether you look in the ovaries or the

17 placenta or the breast, and then there is

18 alterations in -- it's been shown that

19 alterations in gene expression that disrupt the

20 estrogen availability are going to eventually

21 impact not only reproductive development, but a

22 lot of other normal functioning of different
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1 tissues.

2 So what we want to do over the next

3 few slides is to review the evidence that

4 atrazine does alter aromatase activity, both in

5 vivo and in vitro, and I think set the stage for 

6 why a lot of the things that we're looking at, if

7 we stick with this one enzyme, wasn't really

8 necessarily making sense, that we may have to

9 broaden our scope of investigation a little bit

10 bigger, to look at the whole process of

11 steroidogenesis.

12 This is the study, including --

13 actually, the second in a series of studies by

14 Thomas Sanderson, that -- looking at the

15 chlorotriazines, and put everyone onto the idea

16 that atrazine and its metabolites might be

17 affecting the production of estrogens, and what

18 Sanderson did is he used this cell-line up here,

19 the H295R human adrenal carcinoma cell-line,

20 which is kind of a neat and unique cell-line

21 because it possesses all the key enzymes, P450s

22 that are necessary to produce a number of
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1 different steroids, right on out to estradiol. 

2 So, it does contain aromatase.

3 What Sanderson showed was that at, you

4 know, fairly decent concentrations, around three

5 micromolars -- decent, I'm saying compared to

6 what some of the studies I've seen in the

7 literature show, around three micromolars, you

8 start to see an increase in what he termed the

9 activity of that enzyme.

10 You saw an increase in the production

11 of either tritiated water or the estrone itself,

12 if -- in those cells.

13 But what was also interesting is that

14 he found that only atrazine, the two intermediate

15 metabolites that I call them, that's isopropyl

16 and desethylatrazine, increased aromatase

17 activity.

18 Sanderson also looked at the ability

19 of atrazine to change the message in these cells

20 and reported that there was a modest twofold

21 increase in the message, along with that,

22 indicating that exposure to these compounds, to
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1 these three metabolites, anyway, could increase

2 the overall production of estrogens. And

3 importantly, and we'll come back to it in a

4 moment, DACT had no effect on these endpoints,

5 and that's the one there in the square blocks, in

6 red, if you can see it.

7 So that's the -- one of the -- if you

8 look in the blood of the rat, anyway, that's one

9 of the really prominent metabolites, that that

10 had no real effect on aromatase activity in this

11 -- in the H295Rs, and one of his colleagues

12 replicated these studies, looking at the JEG

13 cells.

14 What that did for a time was put a lot

15 of focus on aromatase itself. The light was

16 shining there, and a number of different studies,

17 looking at changes in estrogen production, all

18 came to the conclusion that you could see

19 increased estrogen synthesis, and again, this

20 cell-line was used for the validation of some of

21 the in vitro tests, and I think nine labs

22 replicated the effects of atrazine on aromatase,
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1 so -- or, the production of estrogens.

2 But one of the interesting things that

3 we found was that in addition to just estradiol

4 alone or estrone alone in there, you could see

5 increases in other hormones, and recently, a

6 paper published by Higley said that not only does

7 atrazine increase estradiol or estrone, depending

8 on what you're measuring, it also increases

9 testosterone.

10 And in our own lab and others have

11 also shown that some of these other earlier

12 steroids in that pathway are increased when you

13 stimulate with atrazine, or certain of the

14 atrazine metabolites, which suggested to us that

15 it's not just aromatase that is the target here,

16 but in fact, increased steroidogenesis might be

17 really what the whole series of changes that are

18 taking place is.

19 There are some other studies focusing

20 on SF-1, as a target site for this SF-1, as a co21 factor involved in the regulation of aromatase. 

22 Others have said that that's not necessarily the
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1 case. You may see changes in SF-1, but in fact,

2 that's not necessarily the only target, that in

3 fact, you do see a broader increase in a number -

4 - activity of a number of different singling

5 pathways, and that's what these different studies

6 down here show, and again, these are in the

7 background document.

8 But the point is, is that in addition

9 to aromatase per se, there is this overall effect

10 on steroidogenesis that seems to be the "mode of

11 action" within the cell. We're not sure exactly

12 what all the molecular events are.

13 There is an argument that put forth,

14 actually earlier on, by Sanderson, that atrazine,

15 in some way, increases cyclic AMP activity,

16 perhaps through a decrease in phosphodiesterase. 

17 That's something that can be -- has been

18 substantiated by other labs, but the papers

19 aren't published yet.

20 There is a study that I just read,

21 where they block protein kinase activity and that

22 reversed the effects of atrazine on the
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1 activation of steroidogenesis in Leydig cells.

2 So, that paper is going to be out

3 shortly, so I guess it's okay if I tip my hat on

4 that one, but the point is again, somewhere

5 upstream, a broader effect on signal transduction

6 seems to be the cellular toxicity pathway and

7 that the aromatase per se is not necessarily the

8 sole target for these chemicals.

9 In vivo, again, as I mentioned, we

10 were interested in whether or not atrazine can

11 affect aromatase in vivo. 

12 Walter Modic, who was a student with

13 Dr. Laws' lab, did a series of studies looking at

14 male rats to see if he could identify changes in

15 aromatase activity or the message for aromatase,

16 after being treated with atrazine at relatively

17 high doses for -- in several different ways, and

18 to make a long story short, it's nice to have a

19 lot of slides, but when you get no effects, you

20 end up with a slide like this that says, "Yes,

21 you can induce increases in serum-estrone and

22 estradiol in the male rat." 
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1 This is a different study that we did,

2 showing that in the ovariectomized female, you

3 can see increases in estrone activity at

4 relatively high doses of atrazine, but nowhere

5 was there -- were they able to identify changes

6 in aromatase, either looking at microsomes taken

7 from testes of animals treated, or, could they

8 see changes in the message, looking in brain

9 testes or adipose tissue.

10 So, it just -- if it's there, it's

11 real difficult to find any specific change in

12 aromatase activity.

13 This summarizes that series of

14 studies, so we still have increases in those

15 hormones. It increases the estrogens. There was

16 little or no evidence to support the idea that it

17 was working specifically through aromatase,

18 either increasing the activity or the message.

19 What we had, and I don't want to get

20 into it, because there's a lot of controversy

21 over whether or not the adrenal hormones can

22 produce -- the rodent adrenals can produce
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1 androgens, such as androstenedione, and this

2 literature is -- depends on which side you want

3 to take, but the point is, is that these animals

4 did have increases of estrogen in them, and we

5 were thinking that perhaps one of the sources of

6 this was from the adrenal gland.

7 And that led us to ask the question

8 whether or not atrazine might have some kind of

9 direct effect on adrenal steroidogenesis. 

10 Here it is, 2007, and we've been

11 looking at this for all this time and it seemed a

12 little odd that no one else would have reported

13 that.

14 There were dribbles and drabs in the

15 literature and there was a couple of elegant

16 studies by Dr. Pruett's lab, that said in mice,

17 at the time, that atrazine does increase

18 steroidogenesis from the adrenals.

19 So, we decided to look into this axis,

20 arguing about whether or not the adrenal hormone

21 secretion would be altered by atrazine, whether

22 or not that effect would occur because of some
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1 kind of central targeting of the compound or

2 whether or not the adrenals may actually be

3 targets themselves, since we know in vitro, there

4 were effects on steroidogenesis.

5 So, Susan Laws published this study,

6 some time late last year, demonstrating that

7 there is really a clear effect of atrazine on

8 both ACTH secretion and corticosteroidal -- or I

9 should say ACTH secretion and a number of

10 different adrenal steroids, and this is from that

11 paper, where she gave doses ranging from five to

12 200 milligrams per kilogram orally, and looked at

13 the production of atrazine -- I'm sorry, the

14 production of ACTH and corticosterone at

15 different doses.

16 And I should just mention here that

17 these animals are all dosed for five days prior

18 to testing. They're dosed with the vehicle

19 carboxymethyl cellulose, that they're all dosed

20 at the same time of day, at the nadir, I think

21 it's nine o'clock in this study, when the

22 concentrations of corticosterone and ACTH are
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1 low, and so, when you look at the control animals

2 there, the actual dosing procedure itself seemed

3 to have minimal effects on the secretion of ACTH

4 or corticosterone, which speaks well for the

5 ability of that lab to conduct these studies.

6 But what happens is, as you increase

7 that dose though, there is a clear increase in

8 both ACTH and corticosterone, as well as

9 progesterone and we're -- I'm pretty confident

10 that this is adrenal-derived progesterone. 

11 It's in male rats, and if you look at

12 the testosterone that's being secreted, this is

13 probably from -- or more than likely from the

14 test, as you can see a significant increase

15 there, as well. The time course is a little

16 later. The dose required is a little higher.

17 Another important thing that Susan

18 found was that when you dose with DACT, you saw

19 no comparable increase in ACTH or corticosterone,

20 which was sort of like what Sanderson had

21 reported for the H295R cells.

22 Now, for some reason, that particular
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1 metabolite of atrazine wasn't active, in terms of

2 increasing the adrenal axis, and I have their

3 DACT and ACT and atrazine on the right side, just

4 so you can compare, there were significant

5 changes, if you, as Liz likes to say, worship at

6 the altar of the star, but I don't think they

7 were really as dramatic as what you see over here

8 with atrazine.

9 And the other thing is that the timing

10 there, I don't think there was a delayed response

11 in that, but again, nothing like what you see

12 with the parent compound itself.

13 Another thing that Melanie Fraites is

14 working on in our lab, did, was a series of

15 studies to further get at whether or not this was

16 a chemically specific activation of the pituitary

17 adrenal axis or it was still some artifact that

18 we were introducing, that we didn't know about,

19 and we thought every -- tried to think of

20 everything that we could to get at that, but up

21 to this point, what we've done so far is, Melanie

22 has shown that if you do things like cut the
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1 vagus nerve, it doesn't interfere with it.

2 So, it didn't look like atrazine was

3 getting down into the gut and causing some type

4 of intestinal distress that was going to feed

5 back. 

6 There didn't seem to be any change in

7 some of the endocrine components of feedback from

8 the gut to the brain, and I think, to me, anyway,

9 one of the most convincing things that you can

10 get around the -- any signals from the gut being

11 the cause -- the root-cause for this increase in

12 ACTH, is her observation that you can get the

13 same response if you give the chemical IV.

14 So here, you have an animal that's

15 sitting there with an in-dwelling catheter, you

16 dose with atrazine and you see the same immediate

17 15-minute increase in atrazine -- I mean, in ACTH

18 and corticosterone.

19 Another thing that Dr. Laws did was

20 look at not only atrazine in DACT, but the other

21 two intermediate metabolites, not shown here, is

22 DEA, but both atrazine and DIA do cause the same
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1 type of adrenal response.

2 In this case, I think it's important

3 to note that the LOEL for that study was 10

4 milligrams per kilograms, which is the equimolar

5 dose to 12 and a half milligrams per kilogram of

6 atrazine, and the other interesting thing in this

7 study was, it wouldn't go away. 

8 The increase in corticosterone -- now,

9 she only measured corticosterone in these

10 animals. She didn't measure ACTH here, but in

11 these animals, that response persisted. It was

12 there at the higher dose at four days and even

13 out to 21 days, there was a significant elevation

14 of corticosterone.

15 And this is something that was

16 indicated in the female, in a study by Dr.

17 Fraites, who showed that one dose of atrazine --

18 again, in this case, she used 75 equimolar dose

19 of DIA, caused an increase in both ACTH and in

20 corticosterone, but then, if she dosed for four

21 days, an interesting pattern was present there,

22 that we're still working on, in terms of
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1 interpreting it.

2 But if you look at this, this is a

3 single dose, and this is ACTH. The green here,

4 the darker green, is the same animals. This is

5 one dose; this is four doses. These are intact

6 animals that are dosed on the day of vaginal

7 estrus, diestrus one, diestrus two and the

8 morning of proestrus, and they're killed 15

9 minutes after dosing. So, that response, that

10 ACTH response there is markedly attenuated.

11 But if you look at the cort response

12 in these animals, it's almost the same as it was

13 on the first day. That's what you see when you

14 restraint-stress the animals.

15 So, it's a response that's seen, at

16 least in this case, to persist, and the other

17 thing is, in these animals, I wanted to point it

18 out, was that when she dosed with both DIA and

19 atrazine, that lower dose is 12 and a half

20 milligrams per kilogram, or 10 milligrams, the

21 equimolar dose for DIA, and again, there was no

22 real clear effect with this on -- with that. It
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1 didn't change the adrenal axis.

2 And in those animals -- or in another

3 population of animals treated the same way, she

4 looked at the LH surge and showed that again, as

5 we showed, I think, on the first slide, that 

6 there is a decrease in the LH in the afternoon at

7 the same dose as the 12 and a half milligrams per

8 kilogram for atrazine and the 10 milligrams for

9 DIA.

10 There was a suppression of the surge

11 with DACT. It wasn't significant in this figure;

12 it was significant in others. The point is, is

13 that DACT, I think you can get an effect, but you

14 have to go longer and higher, to see inhibition

15 of the surge, or a suppression.

16 So, in summary, in this series of

17 studies in the male, both ACTH and adrenal

18 steroid hormone production increased within -- as

19 early as 15 minutes following a single injection

20 of atrazine and DIA and DEA. 

21 The dose response for the male study,

22 at the moment, with that data that Dr. Laws had,
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1 the lowest dose was five. Her next highest was

2 50. So, it was somewhere between 50 and five,

3 but the LOEL that she found for DIA was at 10

4 milligrams per kilogram.

5 Compared to atrazine and DIA, the

6 increases in ACTH and the adrenal steroid

7 hormones is markedly less when you dose with DACT

8 in equimolar doses.

9 That, in the male, corticosterone

10 release was sustained for up to three weeks and

11 in the female, we only went out to four days, we

12 started to see a decline in the amount of ACTH

13 secreted in those animals, suggesting, again,

14 that there may be some direct effect of atrazine

15 on the pituitary gland itself, in addition to

16 that major increase in corticosterone release, in

17 response to ACTH after the first injection.

18 And again in the female, we have a low

19 or no NOEL, of 12 and a half milligrams there,

20 and it's important that I mention this, and we

21 just only have -- I'm already going on too long,

22 but atrazine also induces comparable changes in
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1 adrenal progesterone secretion in the female. 

2 Take the female's ovary out, you can see --

3 unmask those kinds of effects that are

4 significant, both at one and four days of

5 exposure.

6 Comparing those effects with what you

7 saw, and I'm going back to what we saw with the

8 effects on the LH surge, either in the

9 ovariectomized estrogen-primed animal or in the

10 intact animal, what we found was that in those

11 earlier studies, which is the first three bullets

12 there, with different LOELs, you have a single

13 dose. You needed more than 200. 

14 With three doses, we dropped it down

15 to 50 and in an intact animal, we could get it

16 down even lower.

17 It still indicated that you needed a

18 number of days to see an effect on the surge, and

19 we did a lot of studies early on, looking only on

20 the day of vaginal proestrus, trying to either

21 block ovulation or decrease the amplitude or

22 timing of the -- often, the timing of the LH
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1 surge, and we couldn't get anything, again, with

2 a single dose up to 200, and if we gave 300, the

3 animals went pseudo-pregnant on us. So they were

4 still ovulating, apparently, or appeared to be

5 ovulating.

6 So, the timing of this and the fact

7 that you see these instantaneous changes in the

8 pituitary adrenal axis, and given the literature,

9 arguing that the adrenal axis is involved in --

10 or could be, if there is hyperactivity in the

11 adrenal axis, could be involved in the disruption

12 of LH, it suggested to us that we see changes

13 that precede and may likely contribute to the

14 disruption of the LH surge.

15 And so, that's what I tried to put

16 together on this figure, where we have our

17 hypothalamic-pituitary-gonadal axis, wherein we

18 know that, time and again, people have published

19 that when you expose in vivo to atrazine, you get

20 a decrease in the amplitude of LH, you end up

21 with, eventually, acyclic animals and the

22 disruption of reproduction.
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1 I have over here, the adrenal axis,

2 where we know that -- and we're not clear,

3 exactly whether or not -- obviously, I think,

4 there's got to be a central effect, either

5 hypothalamus or pituitary, given the rapid

6 response that you see with AC -- and the response

7 that you see with ACTH.

8 However, you see that sustained

9 response in the adrenal. Whether that's due to

10 direct effect of atrazine on the adrenal in vivo,

11 we don't know, but I'd bet a dollar that you'd

12 see it in the primary adrenal cells. And, given

13 that effect and the speed with which we saw that

14 and the timing for the pituitary effects, and the

15 rich literature on this stuff, it argues that one

16 of the primary effectors in -- or one of the

17 events responsible for the decrease of the LH

18 surge, may be that feedback of the adrenal

19 steroids onto the brain and pituitary and the

20 ability of it to regulate the LH surge.

21 Another thing that I think this kind

22 of conceptual framework argues is that, if you
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1 look at the high dose 21-day exposure of male

2 studies, that seem to be popping up in the

3 literature time and again, that that decrease in

4 testosterone, in the gonads of the males exposed,

5 that that effect may be due to a direct action of

6 corticosterone on the Leydig cells.

7 Again, there is a literature, quite a

8 strong literature, that shows that Leydig cells

9 do have glucocorticoid receptors and when

10 activated, and they're regulated by a -- a

11 process within the Leydig cell itself.

12 But when there's over-stimulation of

13 those glucocorticoid receptors, there is actually

14 a down regulation of the enzymes involved in the

15 production of testosterone, including the key one

16 like STAR and some of the other CYPs, so -- and

17 that's well recognized.

18 So there is another pathway that may

19 explain the data that we see in the male rat, and

20 then, finally, there is the data that shows that

21 there is perhaps, a direct activation -- or I'm

22 sorry, a direct inhibition of the GnRH pulses by
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1 CRF in the brain, wherein, stress and other

2 events that increase the activity of that

3 neuropeptide, which acid increases CRF -- or, I'm

4 sorry, increases the activity of CRF and ACTH,

5 that you get a direct innovation -- inhibition on

6 the pulses.

7 So those things make me argue, or

8 feel, that a key part of this whole mode of

9 action on the gonadal axis is this increase, at

10 least early on, increase in the activity of the

11 pituitary adrenal axis, and that's what's

12 summarized here.

13 Again, it has a clear, acute effect on

14 the HPA. We just don't know, haven't well

15 characterized the longer-term effect, increasing

16 both ACTH in the adrenal steroid hormones, that

17 the temporal aspects of atrazine induce changes

18 in the pituitary adrenal axis, and the pituitary

19 gonadal axis, along with the similarities in the

20 dose response -- that's what I was trying to get

21 at there -- for four more days, suggest that the

22 changes in the adrenal axis contribute to the
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1 disruption of LH secretion and impairments in

2 reproductive function.

3 And so, the current studies broaden

4 our understanding of this mode of action for

5 atrazine, incorporating those changes that we've

6 already identified and others, in the pituitary

7 adrenal axis, and those that likely contribute to

8 the disruption of LH in the rat. Questions?

9 SESSION CHAIR PORTIER: At this point,

10 do we have any questions from the Panel? 

11 Comments? Yes, Dr. Horton?

12 DR. HORTON: Yes, actually, I have a

13 lot, but I'll save some.

14 I'll start with another possible

15 model, besides the reproductive aging and the

16 reduction of the LH surge, and ask, do you have

17 measures or does anyone have measures, on what

18 the LH levels look like on diestrus or metestrus,

19 for the rats?

20 DR. COOPER: Yes.

21 DR. HORTON: And what are they?

22 DR. COOPER: The one thing we've seen
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1 consistently, even on the morning of proestrus

2 too, is no change.

3 DR. HORTON: They're not elevated?

4 DR. COOPER: The majority of studies

5 that we've personally done, when we look at it,

6 it appears as though baseline hangs in there.

7 If we really increase the

8 concentrations of atrazine up to 200, I'd even

9 argue 50 and above, it's lower.

10 DR. HORTON: Okay.

11 DR. COOPER: But we haven't seen any

12 indication -- well, I have seen one, we do have

13 one set of data that says we can get an increase,

14 but it's in the afternoon, when we looked at very

15 low doses. So, I don't know whether it's -- 

16 DR. HORTON: Okay. The reason I'm

17 asking is, I'm wondering if it might fit a PCOS,

18 a polycystic ovarian syndrome model; and also,

19 has anyone looked at the body weights or body

20 compositions in these rats?

21 DR. COOPER: In the earlier -- 

22 DR. HORTON: In the females, yes.
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1 DR. COOPER: When you do the longer2 term studies at those high doses, they're down.

3 DR. HORTON: They're down? Okay.

4 DR. COOPER: Significantly, but when

5 you do the -- like, the first slide I showed -- I

6 mean, the early studies that were done were, I

7 think, hitting them with a hammer -- 

8 DR. HORTON: Yes.

9 DR. COOPER: -- and you do see marked

10 decreases in body weight, but when we look at the

11 shorter-term, lower dose things, we don't see a

12 whole lot of difference.

13 DR. HORTON: Okay.

14 DR. COOPER: I mean, we don't see a

15 difference. It's the same.

16 DR. HORTON: Okay.

17 DR. COOPER: That's not -- I should --

18 I have to qualify that, because sometimes, you

19 say you don't see a lot of difference and they're

20 not eating. But no, that's -- 

21 DR. HORTON: Okay, okay, but that's in

22 terms of body weight, but no one has actually
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1 looked at body composition?

2 DR. COOPER: Not to my knowledge.

3 DR. HORTON: Okay, no one has done a

4 glucose tolerance test?

5 DR. COOPER: We have, yes.

6 DR. HORTON: Yes, from what I -- 

7 DR. COOPER: I'm sorry, yes, we've

8 measured glucose, and we haven't found any change

9 with blood glucose over the four days that we did

10 the study.

11 DR. HORTON: Okay, thank you.

12 DR. COOPER: So, we didn't do a glucose

13 tolerance test, no.

14 DR. HORTON: Okay, thank you.

15 SESSION CHAIR PORTIER: Dr. LeBlanc?

16 DR. LeBLANC: There's a lot going on

17 here. A couple of questions, for clarification

18 first.

19 In these studies, have you ever looked

20 at the adrenal mass? Do the adrenals enlarge in

21 size?

22 DR. COOPER: Yes, I'm trying to think
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1 of the -- again, we got into looking at the

2 adrenals kind of late. So, I'm sort of

3 embarrassed to say, we don't have a real

4 characterization of changes in body weight, nor

5 histopath, and they may have it in some of the

6 longer term studies that were submitted for

7 registration. I haven't had a chance to look at

8 them.

9 But what we see is almost an immediate

10 enlargement in the adrenal gland, dose dependent,

11 and then it settled back down.

12 PARTICIPANT: Did you have one in the -

13 - 

14 DR. COOPER: And in the pubertal assay,

15 they were increased, the male pubertal. But,

16 yes.

17 DR. LeBLANC: The 2009 study by Laws,

18 these were done in animals that were not

19 gonadectomized, is that right?

20 DR. COOPER: Right.

21 DR. LeBLANC: Because you said, you

22 thought the testosterone came from the testes. 
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1 So, obviously, they had testes, and I guess I

2 agree with that presumption.

3 In terms of where the progesterone is

4 coming from, is that because most of the

5 progesterone in the blood comes from the adrenal? 

6 You said you thought the progesterone -- 

7 DR. COOPER: In females, on vaginal

8 proestrus, there is a number of studies. One of

9 my PhD mentors, was his claim to fame, with --

10 showed that the majority of progesterone comes

11 from the adrenal vein -- 

12 DR. LeBLANC: Okay.

13 DR. COOPER: -- on the day of

14 proestrus.

15 DR. LeBLANC: Okay.

16 DR. COOPER: I wanted to just throw

17 this up. This was a slide -- this is a

18 gonadectomized slide, where the animals were --

19 again, it was a study that Laws did earlier,

20 wherein, she looked at both androstenedione and

21 testosterone, here on the right, in response to

22 50 to 200 milligrams, and the estrogen production
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1 over here on the left, and what was -- and this

2 was an intact animal.

3 So, this is your testosterone here,

4 and this is androstenedione -- I'm sorry, this is

5 androstenedione in the intact animal, and in the

6 castrated animal, and this is testosterone in the

7 intact animal and there is nothing there, in the

8 castrated animal.

9 And we've actually looked at the

10 adrenals of these animals, to see if we can find

11 androstenedione using HPLC, and we see it, and

12 you know, you're not suppose to have CYP17 in the

13 adrenals, and there are papers that say under

14 certain circumstances and during development, you

15 can see CYP17, that there is a methylation

16 silencing that's taking place, and I just don't

17 understand it.

18 But the point is, is that those data,

19 to me, argue pretty strongly, A) that it's

20 something coming out of those adrenals, if

21 nothing else, it's androstenedione, and over

22 here, there is a production of estrogens that
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1 persisted and if you look at the Y-axis, they're

2 not that different, after castration in the male.

3 So, back to your progesterone

4 question, I'm sorry.

5 DR. LeBLANC: One last point, for

6 clarification.

7 The cartoon you had at the end, the

8 conceptual cartoon, I thought it was very

9 helpful, and in there, you had the inhibition of

10 steroidogenesis by clinical steroids, at the

11 bottom.

12 DR. COOPER: Yes, right there.

13 DR. LeBLANC: Right, so, over and above

14 all of this, are you suggesting that there is

15 something else going on, that's contributing to

16 the increase in testosterone, that -- we're not

17 seeing a great increase, but we are seeing

18 increases.

19 DR. COOPER: Right, okay, good

20 question. Number one, I think those studies,

21 looking at decreased steroidogenesis are really

22 the result of some pretty high doses, 50, 200
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1 milligrams per day. 

2 I know that there was one that went

3 five, ten, 50, 75 and 100 milligrams per day,

4 from -- in the perinatal, even. But most of them

5 are in the intact animals, peripubertal or going

6 on into adults.

7 So, they're high and I think what's

8 happening there, if you do a single dose with

9 this, you'll always see an increase in

10 testosterone. You'll see an increase in

11 testosterone, and if you take the Leydig cell

12 out, and you stimulate the Leydig cell, you'll

13 see an increase in testosterone, you'll see an

14 increase in progesterone, okay.

15 That's been done at APA, with Gary

16 Klinefelter and there is a publication coming out

17 soon, that that's the case. 

18 You put that cell back in the body and

19 can expose it to the glucocorticoids for an

20 extended period of time, increasing

21 glucocorticoid activity by a number of different

22 means, if you want to stress them, and you do
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1 that really mean stress, where you put them in

2 the restraint cage, and -- for an hour a day and

3 shine a light on them, and you know, you really

4 keep the cort up, that will overwhelm the

5 protective mechanism within the Leydig cell and

6 you do see this decrease.

7 And there is studies now, even showing

8 that that process, that glucocorticoid

9 activation, stimulation -- hyperstimulation, that

10 receptor is even bad for the developing animal.

11 So, it's a biphasic or bimodal effect. 

12 Initially, what you see in vitro and what you see

13 with a single dose is increased T, extended

14 dosing -- and I'm hypothesizing through increased

15 adrenal activity, you're seeing perhaps, a direct

16 effect on the gonads, and then of course, what

17 you're supposed to see is that when you decrease

18 T, the compensatory increase in LH, and the

19 studies that Susan and Walter Modic did, didn't

20 really show a whole lot of decreased baseline LH

21 in those males, and we can go back and look at

22 that.
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1 So, that's why I'm leaning a little

2 bit, towards it being a direct gonadal inhibition

3 there.

4 But again, it could be a central

5 mechanism, but I think -- that's central -- you

6 know, I -- there is a paper by Zerkin and Ewing,

7 years ago, that said, "How much LH do I need to

8 keep secreting testosterone," and so, they took

9 the pit out and they put silastic capsules in, or

10 somehow, they fed them LH at real low levels, and

11 it is -- you'd be surprised how low they went,

12 before they would see a decrease in T.

13 SESSION CHAIR PORTIER: Dr. Selvage?

14 DR. SELVAGE: Yes, I just had a

15 question regarding the CORT/ACTH measurements.

16 Do you have any time points that

17 aren't in that -- where you measured these, that

18 aren't in that frame, right after the atrazine

19 administration, in the chronic studies? 

20 So, for instance, are you disrupting

21 circadian rhythm or anything like that?

22 DR. COOPER: Yes, Melanie, in the
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1 female, what we did -- in other words, if you

2 perturb it in the morning, is this -- the

3 afternoon is going to be altered -- 

4 DR. SELVAGE: Yes, or the -- yes, or

5 was it -- before, you know, you would normally

6 give it in the morning, and what would be CORT7 level?

8 DR. COOPER: The data that we have in

9 the -- it's a four-day exposure. We looked at

10 the dose immediate responses, but then we also

11 looked at the afternoon increase in progesterone,

12 because if you -- we were thinking that maybe

13 progesterone later on in the day was being

14 impaired.

15 And there -- in CORT, and Susan --

16 well, number one, is that there -- I think it was

17 the high dose -- Melanie, was the high dose of --

18 which one knocked down P4 in the afternoon? 

19 Yes, the high dose DIA did decrease

20 progesterone in the afternoon, but for the rest

21 of the things that we treated with and doses that

22 we treated, there was nothing there, which was
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1 surprising to me.

2 DR. SELVAGE: How many hours was that?

3 DR. COOPER: That would be -- yes,

4 let's see, that would be treat 9:00 a.m. and

5 you're looking at an hour before. So, you're

6 looking from three hours, one hour and one hour

7 after lights out -- three hours before lights

8 out, 1600, 1800 and 2000 hours.

9 DR. SELVAGE: Okay.

10 SESSION CHAIR PORTIER: Dr. Delclos,

11 please, use your mic.

12 DR. SELVAGE: I'm sorry, but you don't

13 have it like, at say, eight? You're dosing them

14 at nine, right?

15 DR. COOPER: When we did the proestrus,

16 we did the -- the day of proestrus, we measured

17 every two hours, up to 2000, from nine to 2000,

18 and most of the dramatic changes we saw were the

19 early -- 

20 DR. SELVAGE: Right.

21 DR. COOPER: -- ones, because, you

22 know, it's coming up, and one of the things that
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1 Susan found in the male was that when you look in

2 the afternoon, if you try to increase cort in the

3 afternoon, that's one of the things she wanted to

4 do, you could get it to go any higher. 

5 There's sort of like, a ceiling effect

6 there. She couldn't get it to go up.

7 PARTICIPANT: It was still up then.

8 DR. COOPER: It was still up? Right,

9 yes.

10 SESSION CHAIR PORTIER: Dr. Delclos, I

11 think was next, and then, Dr. Akana.

12 DR. DELCLOS: I just wanted to make

13 sure I understood. Does this mechanism play

14 into the delay of puberty at all? Where you take

15 the DACT having effect on that, but not having

16 effect on the -- it was something that confused

17 me, as I read the document.

18 DR. COOPER: There's two questions

19 there, and the answer is, I don't know, to number

20 one.

21 I mean, boy, you read the pubertal --

22 and you guys are the experts, and you read the
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1 pubertal and adrenal literature, especially

2 earlier stuff, I was really -- it's really hard

3 for me to understand it, because you get this --

4 when you do things like adrenalectomy and all

5 this kind of stuff, you seem to see the -- you

6 seem to have an impact on the body weight of the

7 animal, that might confound this a little bit.

8 Conceptually, I could make that

9 argument, and there have been some kind of

10 sophisticated explanations, as to how, if you

11 dose with particular things that either inhibit

12 or activate the glucocorticoid receptor, you

13 could impair -- slow down puberty.

14 But the question about DACT, it's a

15 separate question, because I think DACT -- I'm

16 almost confident that it has to eventually impact

17 regulation of the LH surge, and when I say it has

18 to eventually do it, I mean, by dose, and by

19 duration.

20 If you look at the blood levels in the

21 rat, and we have limited data for this, but when

22 we look at it, DACT is present in such high
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1 concentrations, even -- no matter what you give

2 them, and then you give them DACT, this equimolar

3 dosing thing is -- it's nothing like what you

4 really see inside the animal, when you measure

5 it. You have very high concentrations of DACT.

6 And that's even if you -- you know, if

7 you dose them with atrazine, the amount of DACT

8 is way up there.

9 So, why in the pubertal assays, you

10 see that, I don't know whether there's another

11 mechanism kicking in or what, but it is -- it is

12 something over there, that you can't dismiss. It

13 doesn't always fit the picture. 

14 I guess, if you were really making the

15 argument that the adrenal was involved, you'd

16 want no effects, with DACT, but that's not what -

17 - the way the system was designed, and it bothers

18 -- or it's something that we can't explain at the

19 moment.

20 SESSION CHAIR PORTIER: Dr. Akana?

21 DR. AKANA: Could you repeat that

22 finding in the hypothalamus, in the Modic study?
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1 What I'm thinking about is the

2 possibilities of central action of atrazine, and

3 there are aromatases in the hypothalamus and

4 there are some nice papers showing very site5 specific brain localizations, like BNST, and a

6 lot of those sites are also very gonadal-steroid

7 sensitive.

8 So, it seems the framework could be

9 there for some central regulation.

10 DR. COOPER: If I understand your

11 question right, do you mean in the adult or the

12 developing animal, first?

13 DR. AKANA: Adult first.

14 DR. COOPER: Okay, Susan, you looked at

15 -- go ahead, do you want to -- 

16 SESSION CHAIR PORTIER: Please identify

17 yourself, if you come up.

18 DR. COOPER: This is Dr. Susan Laws,

19 and she's the -- 

20 DR. LAWS: Hi, I'm Susan Laws, from

21 EPA. The question you were asking, the Modic

22 study, we were looking at the hypothalamus for
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1 message, for aromatase CYP19, and those studies

2 indicated that after they were treated in vivo,

3 there were no differences in the message, and we

4 looked at -- after a single dose multiple time

5 points, we looked after three doses, daily doses,

6 and then at -- I think, that had a couple of time

7 points also, and we were not able to see any

8 differences in that.

9 So, it's -- it's challenging to

10 measure, so it's a no-effect study, is what we

11 have.

12 DR. COOPER: But the reason I asked

13 about the developing animal, of course, is then,

14 that's a whole new ball game or a whole different

15 ball game, because of A) the concentration. 

16 Susan tells me they're much greater in the

17 neonate, and so, if maybe there is one

18 opportunity where there may be effects that we

19 haven't looked at, that might be important.

20 DR. AKANA: Also wasn't there also some

21 discussion of a critical period, in development

22 for the aromatase?
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1 DR. COOPER: Yes, well, early on, I

2 mean, that was one of the driving forces behind

3 her actually measuring the younger animal,

4 because during development, the aromatase was

5 coming down and we figured if we -- what Stoker

6 found was a reflection of the earlier increased

7 importance of the animal.

8 But we didn't look at the peripubertal

9 or anything that would -- we haven't, yet, looked

10 at the peripubertal -- we haven't looked around

11 birth. That's what I'm trying to say, not

12 puberty, perinatal period.

13 SESSION CHAIR PORTIER: Dr. Williams?

14 DR. WILLIAMS: I just want to switch

15 gears a little bit, to get you to clarify the

16 comments you made several hours ago, regarding

17 the mammary gland tumors.

18 You said with aging, the cycles become

19 irregular, the LH surge doesn't happen and this

20 endocrine milieu in the rat promotes a

21 development of mammary tumors, and then in your

22 summary slide, you said that reproductive aging
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1 is driven by the brain in the rat and by the

2 ovary in the human, and therefore, the mammary

3 gland tumor development isn't relevant to humans.

4 I don't really see that connection,

5 though. It seems to me that you should be more

6 concerned about the reproductive endocrine

7 milieu, potentially leading to mammary gland

8 development in humans, whether or not

9 reproductive senescence is an issue as a separate

10 story. Can you clarify that for me?

11 DR. COOPER: Let me repeat the

12 question, because that was a long one.

13 DR. WILLIAMS: Okay.

14 DR. COOPER: I want to make sure I get

15 it right. You're asking me, you said that we

16 looked at the aging animal, but you're talking

17 about mammary gland development, or are you

18 talking about mammary gland tumor development?

19 DR. WILLIAMS: So, this is directly

20 from your own slides, the nine and ten.

21 DR. COOPER: Okay.

22 DR. WILLIAMS: So, basically, you said
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1 that you don't get the LH surge, so you don't

2 have regular cycling and you end up getting in

3 the -- in the rat, loss of CNS regulation, and

4 that this endocrine milieu causes development of

5 mammary gland tumors, and then in your summary

6 slide, you said, because reproductive aging is

7 different in humans, then the endocrine milieu

8 isn't really relevant to human mammary

9 development -- mammary -- 

10 DR. COOPER: If I said that, I

11 misspoke. The hormonal environment, I think, is

12 important, in both species, I mean, obviously.

13 I think that what happens with normal

14 aging, and the fact that atrazine appears to

15 accelerate that aging process in the rodent, is

16 different than what you would anticipate in the

17 humans, okay.

18 So, in the humans -- I mean, in the

19 rat, what we're doing is, we're driving a faster

20 pace, disruption of regular cycles and earlier

21 onset, and really, I think once that cyclicity is

22 disturbed, the pattern of constant estrus sets
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1 the clock for when you're eventually going to get

2 a tumor.

3 How long you expose estradiol, how

4 long you keep your other hormones out of balance,

5 the more likely you're going to see the tumor

6 over time.

7 When I said it wasn't relevant, from

8 the standpoint of these studies to humans is,

9 that humans don't go constant estrus when they

10 stop cycling. They have not -- they have

11 insufficient number of follicles to -- the reason

12 they stop ovulate -- I'm sorry, the reason they

13 stop cycling their menstrual cycle is because

14 they lose the follicles, critical mass there, and

15 there is a few still left in there, like, 200,000

16 or something. 

17 DR. WILLIAMS: Right, but as Dr. Horton

18 brought up earlier, in cases where women don't

19 really ovulate, for example, polycystic ovarian

20 syndrome, they actually do have elevated levels

21 of estradiol that are fairly, you know, prevalent

22 throughout the cycle, rather than the nice peak
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1 at pre-ovulatory and then lower during the rest

2 of the cycle.

3 And so, it seems like the hormonal

4 milieu may be fairly similar and -- 

5 DR. COOPER: Oh, yes, if you want to go

6 -- okay, now, I understand your question better.

7 Yes, especially in light of some of

8 the recent papers in the rodent modeling, trying

9 to develop a model for polycystic ovarian

10 disease, wherein they argue that the induction of

11 constant estrus in the rat is going to produce,

12 not only the endocrine environment, but also,

13 some of the histological changes down within the

14 ovary itself, that are reminiscent of, you know,

15 the persistent follicles that you see.

16 Earlier on, in that literature, people

17 -- and where I did my turnaround was the work

18 that Ojeda has done lately, you may be familiar

19 with -- or not lately, but when he started

20 publishing on it, I began to believe that

21 polycystic ovarian disease may be something that

22 might fit into this picture, with the rodent
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1 literature.

2 Now, in that case, I don't -- I would

3 agree, that that's an important consideration. 

4 How that plays into the whole atrazine thing, I'm

5 not sure of, because it's different.

6 I mean, those studies would probably -

7 - those studies with the persistent estrous

8 animal are done in a young adult female, and I'm

9 not familiar, if there are any where they started

10 to look at that kind of homology, if you will,

11 between what you see in the aging female rat and

12 what you see in someone with PCOS.

13 But, yes, now I understand your

14 question and I'm in agreement with you.

15 SESSION CHAIR PORTIER: Dr. O'Byrne.

16 DR. O'BYRNE: Point of clarification. 

17 You said that you've tried blocking the LH surge

18 with atrazine, in an acute fashion, and failed

19 miserably. With other compounds, it works.

20 DR. COOPER: Right.

21 DR. O'BYRNE: To block the surge.

22 DR. COOPER: Yes, we've done a number
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1 of studies using things like dithiocarbamates,

2 which -- or and other fungicides that works to

3 specifically disrupt neuroadrenergic

4 transmission, and usually, we give them,

5 somewhere during the critical period, usually

6 about 15 minutes prior, in our -- between two and

7 four o'clock in the afternoon, and very rapidly,

8 you see the decrease in neuroendocrine and then

9 the decrease in pulses.

10 DR. O'BYRNE: Okay, so, you know the

11 mechanism action is quite clear?

12 DR. COOPER: Yes.

13 DR. O'BYRNE: Just another point, if I

14 may. I'm sure we're desperate for some break and

15 some tea or coffee.

16 Your pulsatile data, I don't know

17 whether it was yours or somebody else's, but

18 averaging pulsatile data and then trying to

19 describe it as pulses, is -- it's very difficult

20 to appreciate.

21 DR. COOPER: Well, yes.

22 DR. O'BYRNE: But you said you had the
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1 individual data and you put it through the pulsar

2 program, and the 50 milligrams, which is a

3 whooping great dose, had no effect. Is that -- 

4 DR. COOPER: In the mean, right.

5 DR. O'BYRNE: No, no, no, in the

6 individuals, and I don't know how many animals

7 were -- 

8 DR. COOPER: Yes, this model -- 

9 DR. O'BYRNE: Do you have access to

10 that?

11 DR. COOPER: Do we have access to the

12 data?

13 DR. O'BYRNE: I have not seen those

14 individual profiles. I'm just curious, as to

15 whether there was a suppression of frequency,

16 which you can't read from this average data. 

17 DR. COOPER: Right, boy, that was 1997. 

18 When we did DMDC, we did the -- these are 28-day

19 females, you put the catheter in, beautiful

20 pulses, okay, and what you see, in the individual

21 animal -- and the question that you're asking is,

22 you inject them with the dithiocarbamate. It's
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1 pulse, pulse, boom, okay, like, some data I've

2 seen, other people have pub, and it's immediate,

3 you know.

4 You know, and then they'll hang down

5 there for three or four hours until it clears and

6 then, you can see the pulses resume.

7 For Dr. Tyrey's data, for the 50 -- I

8 know -- I can tell you, what it looked like for

9 the 200, okay, pulse, pulse, flat, all right, and

10 then D-flat, and then you'd see an occasional

11 burst-through with the different -- now, an

12 individual animal, you would see this gigantic

13 pulse, like the GnRH hormones have to dump, that

14 kind of thing.

15 But the 50, I think with the

16 individual animals, you'd see a broader -- the

17 broader pulses. So, it's a slowing frequency,

18 but the amplitude was not down all that much. 

19 They're still doing okay, and boy, that was an

20 old memory trace that, to pull back.

21 SESSION CHAIR PORTIER: I think at this

22 point, we are going to take a break. Dr. Young?
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1 (Off the record comments.)

2 DR. YOUNG: So, I've been kind of

3 looking at this, you have to understand, I'm a

4 statistician, so, that's going to be my kind of

5 question.

6 So, do you do analysis for each time

7 period or do you synthesize and to one large

8 analysis?

9 DR. COOPER: For which study?

10 DR. YOUNG: Well -- 

11 DR. COOPER: For the -- 

12 DR. YOUNG: -- pretty much, all of

13 these? So, for example -- 

14 DR. COOPER: When we do this -- 

15 DR. YOUNG: -- the ones on page 20 --

16 on slide 26, the ones on slide 23?

17 DR. COOPER: Twenty-six and 23, boy,

18 Stoker, I hope these are your data.

19 SESSION CHAIR PORTIER: So, you're

20 talking about coming up at the little stars on

21 the top?

22 DR. YOUNG: Yes, how do you get that
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1 star?

2 SESSION CHAIR PORTIER: How do you get

3 those stars?

4 DR. YOUNG: Yes, you're right.

5 (Off the record comments.)

6 DR. YOUNG: I saw, on one of your --

7 well, on -- I couldn't find the Tyrey paper, if

8 that's the way you -- 

9 DR. COOPER: That's an abstract.

10 DR. YOUNG: Okay, I saw the abstract,

11 but where I -- no, I couldn't -- no, I didn't see

12 that.

13 DR. COOPER: We have it in the 2007,

14 but I don't -- 

15 DR. YOUNG: Okay, I couldn't -- one, I

16 couldn't find the 1997 one.

17 DR. COOPER: Yes, please don't take me

18 to task on the pulsar, because -- 

19 DR. YOUNG: No, no, I'm just -- 

20 DR. COOPER: -- we can -- 

21 DR. YOUNG: I'm just trying to figure

22 this out.
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1 DR. COOPER: Right, but here is 25, is

2 that what you want?

3 DR. YOUNG: No, no.

4 DR. COOPER: Oh, the LH surge?

5 DR. YOUNG: Something like that.

6 DR. COOPER: Right, these are -- who

7 did this?

8 DR. YOUNG: So, did you do one at each

9 time point, or did you do one analysis for the

10 whole graph?

11 DR. COOPER: The whole graph.

12 DR. YOUNG: Because sometimes -- in the

13 captions, it talks about by time point. So, my

14 assumption was, analysis was by time point and --

15 but I'm not sure that's right.

16 DR. HOLLADAY: I think that is, for

17 this.

18 DR. YOUNG: This is the time point -- 

19 DR. COOPER: She did the analysis, let

20 her speak.

21 (Off the record comments.)

22 SESSION CHAIR PORTIER: Can I suggest
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1 that we hold this and that you guys talk about it

2 at the break, and then we'll come back with that

3 question? 

4 DR. YOUNG: Excellent suggestion. 

5 Thank you very much.

6 SESSION CHAIR PORTIER: I know it's a

7 large group of people, and a 15 minute break is

8 very difficult, but my watch says 3:15 p.m. So,

9 we'll be back at 3:30 p.m., on the dot. Thank

10 you.

11 (Whereupon, the above-entitled matter

12 went off the record at 3:15 p.m. and resumed at

13 3:33 p.m.)

14 SESSION CHAIR PORTIER: I was ready to

15 get started, but Dr. Cooper wasn't here, so, I

16 can't.

17 So, we're going to continue on and see

18 if first, EPA can answer Dr. Young's question

19 about analysis, and then, I think Dr. Williams

20 wanted to come back to her question, to see if we

21 can get that clarified.

22 DR. YOUNG: All right, I -- 
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1 SESSION CHAIR PORTIER: I remind the

2 Panel, this is our time to get clarification on

3 the presentations and the material on the white

4 paper.

5 So, it's not quite right on the

6 slides, but you've got something in the white

7 paper you can point to, we can go with that, as

8 well. So, Dr. Young?

9 DR. YOUNG: I think I got clarification

10 in the break. Some of the more recent papers do

11 look at the whole study, some of the older

12 papers, even though an effort has been made to

13 look for proper analysis, do do time-by-time

14 analysis, and some, we don't have the data to

15 even know one way or the other.

16 In addition, I think there was a

17 slight misspeaking, in that, one study in which

18 we talked about a rat, after one dose, in the

19 same rat, four doses later, those were actually

20 different rats. So -- 

21 DR. COOPER: They had to be different

22 rats. They were killing them.
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1 But the one other thing that's

2 important is that these data aren't transformed,

3 and usually, when they do hormone data, they do

4 the transformation and so, it's my estimation

5 that these are really conservative evaluations,

6 and I may be wrong in that approach, that if we

7 didn't do the transformations because of the

8 transformations, the amount of variance that you

9 see, may change. Susan has just re-did a data

10 set, doing that.

11 DR. LAWS: My data was -- 

12 SESSION CHAIR PORTIER: Identify

13 yourself.

14 DR. LAWS: Susan Laws, U.S. EPA. My

15 data that you see the -- the ACTH and the CORT16 data, those that had the different time points,

17 they were first analyzed with analysis of

18 variants in -- for time and time of dose

19 interactions.

20 But however, there is heterogeneity of

21 variance in those data. So, those data, we

22 actually used a non -- rather than transform
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1 them, do a live transformation, which is usually

2 done with hormone data, or can be done with

3 hormone data, we used a non-parametric test for

4 those and we did do those by time, each time it

5 was done, in between.

6 And so, it was the analysis of the

7 variants and then, there was a post hoc test for

8 those stars, that you see.

9 Recently, we've transformed some data

10 -- used a live transformation, and actually, it

11 looks like they -- we have lower doses that are 

12 significant, not in this data set, but another

13 data set.

14 So, I think the non-parametric test

15 that we used for that report was fairly

16 conservative, when it looked at differences

17 between groups.

18 SESSION CHAIR PORTIER: Dr. Williams? 

19 DR. WILLIAMS: Just to try to clarify,

20 the mammary gland tumor development in women

21 versus rats, and the mechanism of action you were

22 talking about, can you clarify, maybe not what's
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1 on your slide, but what is in the white paper, in

2 terms of causing -- causative concerns regarding

3 atrazine, LH surge lag, the endocrine milieu and

4 mammary gland tumor developments?

5 DR. COOPER: You mean, the --

6 essentially, the strain difference? You mean,

7 essentially, the strain difference, if you will,

8 in humans versus rats?

9 DR. WILLIAMS: Why is it that you don't

10 believe that the LH and endocrine milieu changes

11 wouldn't be relevant to human mammary development

12 tumor -- 

13 DR. COOPER: No, no, no, that's -- if

14 I'm giving you that impression -- 

15 DR. WILLIAMS: That's why I wanted to

16 clarify it.

17 DR. COOPER: That's not true, okay,

18 that's not what we're implying, or I'm implying,

19 is that the -- that environment that you see in

20 the rat, is what's conducive for the growth of

21 tumors, hyperplasia and then eventually, the

22 tumors.
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1 The human doesn't get to that

2 condition, is what we're saying that, during

3 aging in the human, what you see is a depletion

4 of the follicles, and therefore, that you don't

5 develop the high levels of estrogen when they go

6 through menopause. Menopause is a period of low

7 estradiol, or estrogen.

8 DR. WILLIAMS: So, then potentially,

9 the mechanism of action would be relevant to a

10 non-menopausal human, though?

11 DR. COOPER: If you can -- yes, that

12 was a question that came up during the break. I

13 would assume that if you could get a constant

14 estrous human, a polyfollicular human maybe, I'm

15 not familiar with one, a model like that, but if

16 it's the case, then I don't know why that

17 wouldn't be the same endocrine environment, yes.

18 So, yes, I apologize if I mislead you. 

19 I'm not -- it's -- that hormonal environment is

20 the consequence of differential patterns of

21 aging, rat versus human, and that's why the

22 argument that the relevance that we see for that
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1 particular outcome, in the rat, it doesn't appear

2 to apply to humans.

3 And so, there is a -- it's sort of

4 like, you know, I guess we make assumptions and

5 this was our -- that argument was what we tried

6 to make clear, the last meeting, and I -- rushing

7 through that, sometimes, you don't get the -- all

8 the little key events, like that. They don't

9 come out right.

10 But your question is on target from

11 the comment that, if you create this environment,

12 rat or human or even -- you know, no matter what

13 the strain -- I know there's a mouse strain. 

14 They say that atrazine doesn't induce mammary

15 gland tumors in mouse, but there is a mouse

16 strain that they used in aging, that was --

17 showed similar patterns of pituitary and mammary

18 gland development in the female, when she grows

19 older.

20 They showed it as a consequence of

21 altered ovarian cycles and perhaps, if that

22 strain is -- you should see the -- if that was
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1 what you see, then you brought about the same

2 premature reproductive aging as the experimental

3 -- the studies show in that mouse strain, that

4 you would see the same thing.

5 It's how you get there, or can you get

6 there, in a human.

7 SESSION CHAIR PORTIER: Dr. Fenner8 Crisp?

9 DR. FENNER-CRISP: Ralph, back in the

10 stone age, when we were working on the mammary

11 tumor MOA, this -- one could only say that

12 atrazine had some effect, not otherwise defined,

13 with respect to direct or indirect. The work

14 hadn't been done to sort anything out,

15 specifically, yet, adequately.

16 Now, with this new body of data,

17 describing the disturbances in the HPA axis, the

18 inferences, although you haven't stated it

19 explicitly yet, that -- that may have to proceed

20 the disturbance in the HPG axis for the mammary

21 tumors, which would be indirect.

22 What evidence exists for or against
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1 the -- a direct pathway being at play, and what

2 could you do or have you done, to separate the

3 two, to show whether or not there's still an

4 opportunity for direct effects?

5 DR. COOPER: For the tumors outcome? 

6 There is a study that the registrant did, I

7 think, that might speak to it, is that if the

8 adrenal gland was actually driving the

9 development of the tumors, independent of altered

10 gonadal function, then you would see it, if you

11 removed the gonads and dosed with atrazine for an

12 extended period of time, removed the ovaries, in

13 this case, and didn't they submit that study? 

14 (Off the record comments.)

15 DR. COOPER: That would -- 

16 DR. FENNER-CRISP: Maybe that would -- 

17 DR. COOPER: That's the statistician --

18 DR. FENNER-CRISP: Maybe then the

19 registrar could speak to my question, tomorrow.

20 DR. COOPER: I thought that that study

21 was done. I guess, I misspoke.

22 DR. FENNER-CRISP: Okay.
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1 SESSION CHAIR PORTIER: I think there

2 was a hand in the audience, indicating that

3 tomorrow, probably the registrant will speak to

4 that, if we can -- 

5 I think at this point, we've kind of

6 picked through this part and we're ready to move

7 on to the discussion of the immunotoxicity. Dr.

8 Luebke?

9 DR. LAWS: Go back to the -- whatever

10 it's called, the hard drive. Go back to the hard

11 drive. Thank you. 

12 DR. LUEBKE: Okay, so I'm going to talk

13 about some atrazine immunotox studies and

14 basically, just summarize some of the work that

15 has been done. I will not be going into the

16 level of detail that Ralph did.

17 And because this is the first time

18 through for immunotox, for the SAP Panel, I know

19 that we have a couple of experts here, but for

20 the rest of you, I thought it would be a good

21 idea, just to cover just a couple of very general

22 topics first.
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1 So, immunotox is essentially

2 unintended modulation of the immune system, and

3 this can take the form of suppression or

4 enhancement of certain functions that the cells

5 do, and that the body does, and this can result

6 in an increase in allergy, it can increase the

7 risk of hyper-sensitivity, or autoimmune disease,

8 and in very general terms, these mode of actions

9 includes things like an altered supply in the

10 cells, that would be coming in to perform these

11 different duties.

12 There could be altered maturation of

13 the cell types. There could be a difference in

14 how the cells function or in the case of

15 autoimmune disease, which we see up there, this

16 could be a failure just to control auto17 reactivity by some fairly sophisticated

18 processes.

19 And the proximal cause of

20 immunotoxicity can either be direct, so there are

21 effects right directly on the immune system cells

22 themselves or on their supporting tissues, or
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1 they could be indirect, where there are effects

2 that might perturb some other system and the

3 fall-out from that perturbation would actually

4 change how the immune cell functions.

5 So, host factors, as we have been

6 talking about for the last little while here, can

7 also have a dramatic effect.

8 So, up here at the top, you see that

9 during -- well, that doesn't work, okay. During

10 development and maturation of the immune system,

11 it seems to be one of the more critical times for

12 adverse effects on the immune system.

13 During this maintenance phase, when

14 everyone is young and healthy, we can still get

15 effects, and do, and we see those in adult

16 immunotoxicity studies.

17 Gender and genotype can also have a

18 big effect. Females tend to make a more robust

19 response than males do, immunologically, and

20 genotype controls a wide array of things.

21 So, the wide array of what constitutes

22 normal function in an individual, normal function
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1 across a broad scale of the population, and it

2 also, as we've heard for effects on endocrine

3 disruption, with Ralph, it can also control how

4 an animal responds to exposure to an

5 immunotoxicant.

6 So, mice exposed to very small amounts

7 of dioxin get immunosuppression and doses many,

8 many times, 30 times that high, don't have much

9 of an effect on rats.

10 So, why would we do immunotox hazard

11 IV studies? Sometimes, there is some clues from

12 general tox studies, and these can be things like

13 a change in organ weight, input organ weights

14 with the cellularity. These tend to be sort of

15 observational snapshots captured at one in time

16 and it tells you sort of like, what the immune

17 system was like, right then.

18 There may be a known or suspected mode

19 of action. So, if -- we know that the compound

20 alters protein-synthesis or cell division or

21 alters neuroendocrine effects, that may be a clue

22 that we need to look for immunotoxicity.
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1 In some cases, testing is actually

2 mandated for certain types of compounds, and they

3 may be planned, like the NTP would look for

4 effects, and these are generally functional

5 effects that people are going to be looking for.

6 So, in those assays, you'll have some

7 of those -- these observational snapshots, but

8 what you might not have are these functional

9 assays and what you will not have in the general

10 tox studies.

11 So, in these functional studies, we

12 ask the immune system to do something. So, it's

13 generally challenged with an antigen, and then we

14 measure the response to that.

15 So, the critical mode of action for

16 evaluation of the immunotoxicity of atrazine was

17 obviously, endocrine function. 

18 We know that there are a variety of

19 industrial compounds and pesticides and other

20 compounds that are endocrine-active compounds,

21 and they also have an effect on the immune

22 system.
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1 So, this first study that I'm going to

2 talk about was done in my laboratory, at EPA in

3 Research Triangle Park, and it was done by a

4 postdoctoral student, Andrew Rooney, when he came

5 through my lab.

6 He came out of Lou Gillette's lab at

7 University of Florida, where he had studied the

8 Lake Apopka alligators. So, he was very

9 interested in endocrine disfunction and he had

10 measured some endpoints in the immune system, as

11 well, and this seemed like a perfect project for

12 him.

13 So, he picked a dose of atrazine that

14 would be just above what Susan Laws had reported

15 for changes in the onset of puberty in female

16 pups, and for a reduction in the NOEL of

17 prolactin, in Tammy Stoker's studies.

18 Rather than including a dose response

19 here, we included a couple of pharmacological

20 agents, because we wanted to see if we could

21 produce the same effects by altering prolactin

22 production and we chose our dose there, to be the
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1 LOEL for prostitis, and we also included PTU,

2 propylthiouracil, to see if there was -- if we

3 could do this by altering thyroid hormone

4 production.

5 So, after the moms gave birth, we took

6 the pups away. We segregated them out by gender

7 and dose and then we re-distributed five males

8 and five females to all the -- all the dams. We

9 didn't make any attempt to return animals to

10 their biological mom or to not return them, and

11 we also got weights on the animals, at that day.

12 Then on day 14, we took one pup from

13 each gender and we got thyroid hormone -- we got

14 thyroid hormone levels on those animals and we

15 also took a spleen and a thymus weight at that

16 day, to see if anything had happened to those

17 immune systems organs.

18 Then, once the animals became

19 immunologically mature, we asked their immune

20 system to do something by immunizing them to have

21 them make antibodies or to make a cell mediated

22 immune response.
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1 We also looked at the ability of cells

2 to produce phagocytosis, which can be the first

3 step in resistance to certain sorts of

4 infections, and we also evaluated natural killer

5 cell activity, which is something done by

6 specialized lymphocytes that kills tumor cells.

7 And we did these -- the assays -- the

8 functional assays at a couple of time points, to

9 see if the effects were persistent, and if you

10 look at these data here, you can see that there

11 was a real increase in the percent mortality.

12 So, two-thirds of the atrazine litters

13 actually lost pups, and the numbers of litters

14 that actually lost pups was also increased for

15 bromocryptine. This didn't happen for PTU.

16 As Ralph mentioned earlier, we know

17 that changes in prolactin levels will alter

18 maternal behavior and we think, but don't know

19 for a fact, that the reason that we had this

20 increased mortality in the atrazine pups was for

21 the same reason we did in the bromocryptine pups,

22 because maternal behavior had been altered, and
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1 they just weren't as good a mom.

2 We looked at the pup weights, to see

3 how well they did during development, just as

4 sort of a general measurement of pup health, and

5 as you can see, we didn't really have any effects

6 at all of atrazine in these animals at PND2. 

7 We did pick up what was a

8 statistically significant effect in the males, on

9 PND7, but if you also look at the n value there,

10 you can see that we had a lot of pups who -- this

11 was a very large study and because of this, the

12 one gram difference between the controls and the

13 atrazine pups showed up as being statistically

14 significant.

15 So, the bromocryptine and PTU had some

16 effects as well, particularly on PND7.

17 Now, this one, I know is sort of busy. 

18 I'm going to try and show you here. These are

19 body weights, going across here at the top, and

20 you can see, there was no effect on PND14, in the

21 body weights of the offspring, in the atrazine

22 group, although the bromocryptine and the PTU
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1 animals were still suppressed.

2 We also looked at the spleen to body

3 weight ratio, sort of a somatic index, and spleen

4 weights were not affected, nor were thymus

5 weights affected in the atrazine-exposed animals.

6 They were, in the thymus -- I mean, in

7 the PTU and the bromocryptine groups as well, but

8 those were transient effects and PND62, they had

9 all recovered.

10 So, this was a functional assay, where

11 we immunized a large group of mice and then, we

12 bleed them and we measured antibody titers, and

13 what we found was there was actually a

14 suppression in the male mice, but not in the

15 female mice that were exposed to atrazine, and

16 these effects were not re-capitulated by

17 bromocryptine or PTU, and then a sub-group of

18 those animals was given another dose a week --

19 two weeks later, of the same antigen, and we

20 measured the IgG response and in this case, there

21 was on effect on males or females.

22 We did a cell mediated immune assay,
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1 where we had the animals respond to the swelling

2 response to an antigen and what we found again

3 here, was this sexually dimorphic effect, where

4 there was suppression in the males, but not in

5 the females.

6 This occurred at nine weeks, and I

7 should mention here, on the antibody response, we

8 looked again at six months and the effects that

9 we saw on the primary antibody response were no

10 longer apparent at six months, just at the -- at

11 eight weeks of age.

12 So, here, we see that there was

13 suppression of cell mediated immune responses at

14 nine and 12 weeks. This did not persist out to

15 six months.

16 So, in both of these cases, where IgM

17 was suppressed and cell mediated immune function

18 was suppressed, although it recovered, there was

19 a time period there where the suppression could

20 have rendered the animals more susceptible to

21 certain sorts of infections, and these include

22 viral infections and certain types of bacterial
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1 infections.

2 There were also a number of negative

3 effects that we had here. There was no effect on

4 maternal weight gain, so, these effects, we don't

5 think, were due to any sort of overt toxicity on

6 mom. 

7 There was on effect on phagocytic

8 activity of these phagocytes at all. These

9 phagocytes also do other things, like

10 participating in antibody responses. So, we

11 don't know whether they were responsible at all

12 for suppressed antibody responses, but their

13 phagocytic activity was not affected.

14 Natural killer cell activity was not

15 affected and at least, you think these things

16 might be refractory to any sort of developmental

17 effects. Diethylstilbestrol given to neonatal

18 female mice will suppress natural killer cell

19 activity almost for life, in these animals. So,

20 it is possible for an endocrine disrupting

21 compound to change that.

22 We didn't see any effect on the
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1 relative or absolute spleen and thymus weights,

2 which suggests that there wasn't any sort of

3 effect on the supply of cells that these animals

4 had to work with, but clearly, somehow, their

5 function had been altered, and we didn't seem to

6 reproduce effects whatsoever, by using these

7 pharmacological inhibitors.

8 So, this made us think that low levels

9 of prolactin and low levels of thyroid hormone

10 were not really to blame for the effects that we

11 saw in the immune response, and so, since Andy

12 had a background in endocrine disruption, he came

13 up with the idea, before he talked to Ralph

14 Cooper, that the GnRH may have something to do

15 with this.

16 We know from a variety of different

17 subjects, different studies, that this is

18 sexually dimorphic, GnRH expression and the

19 protein and the receptor expression are set early

20 in development. They're sexually dimorphic. 

21 Antagonists that are given to primates

22 actually do suppress cell mediated and humoral
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1 immunity in the males, but not in the females. 

2 The agonists, ironically, up-regulate effects on

3 cell populations, not on function, but on cell

4 populations in the female offspring, and we know

5 that once this receptor is bound by its agonist

6 on the lymphocytes, this leads to increased

7 antibody production and it leads to increased

8 cytokine production.

9 So, now, for the caveat, we did all --

10 we did those studies that I just described twice. 

11 Each time we did them, the data came out pretty

12 much the same. Then, we moved about half a mile

13 down the road, to a new facility, and because we

14 didn't have a dose response, we went back to

15 generated dose response, which we were unable to

16 do.

17 We did the study three or four times. 

18 The same people were involved, that did the

19 studies both times. We had used different lots

20 of atrazine in the first study, and it didn't

21 have any effect. So, I don't think that could

22 have any -- you know, out -- bearing on the
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1 outcome.

2 We did monitoring for parasites, the

3 normal sentinel animal stuff in both facilities. 

4 There was no difference in infections.

5 I have a whole lot of confidence in

6 both data sets, because of the things that I've

7 just told you about. What I don't know is what

8 this unknown environmental factor is, that in one

9 case, the animals were suppressed, but in another

10 case, at the same dose, they were not.

11 It could be something, just sort of an

12 additive thing, with cage movement or something

13 like that, some change in the way they were cared

14 for, but we have not been able to figure out what

15 that was.

16 So, there was another developmental

17 immunotox study done. This time, it was done in

18 mice and these mice were done for again, going

19 back to these host factors that we talked about

20 earlier, to see if there were differences in

21 genotype.

22 The exposure here was quite a bit
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1 different because they used a little implant that

2 constantly delivered a trickling dose of

3 atrazine, the same amount within a 24 hour

4 period, and so, when they started dosing, they

5 were at about our same level. They chose these

6 doses, based on the studies that we had done.

7 But this had gone down to about 23

8 milligrams per kilogram per day, at the time that

9 the animals were born, and then, they weaned the

10 animals a little bit later than we did, at 28

11 days and then they assayed them, once they were

12 mature.

13 They also found sexually dimorphic

14 effects here, but what they found was that

15 humoral immunity, the antibody response, was

16 actually increased in the mice, where we had seen

17 suppression, and it didn't matter how you -- how

18 they expressed the data, whether they

19 standardized it to the number of cells in the

20 spleen or the number of cells in the spleen that

21 were precursors to the antibody-forming cells.

22 They also found that there was an
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1 effect on cell mediated immunity. They used

2 different assays than what we did. The one on

3 the left actually has -- causes cells to

4 proliferate in response to foreign antigens. The

5 one on the right, specifically armed cytotoxic T6 cells kill target cells.

7 But just as was the case with the

8 humoral immunity, what they found was increased

9 reactivity in the mice.

10 And so, we talked about suppression in

11 our animals, leading to a greater risk of

12 infection. There are a lot of animal models out

13 there that are shown. Compounds that cause this

14 unwanted increase in immune reactivity can also

15 make auto-immune disease worse or can lead to

16 hyper-sensitivity and allergic effects in

17 susceptible individuals.

18 They found the same sort of negative

19 effects that we did. So, mom wasn't really

20 affected in her weight gain, pregnancy rate,

21 litter rate, things like that, were not really

22 affected. There was no effect on offspring
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1 weight gain, when they looked at it, at a single

2 time period, so, the pups weren't particularly

3 sick or anything like that, and because they

4 didn't find any effects on the spleen weight, or

5 they looked at the distribution of lymphocytes

6 from within the spleen, for various types of

7 cells. They didn't see any effects there, which

8 would suggest that the supply of cells was not

9 altered, but once again, the function of the

10 cells was clearly altered because of what the

11 outcome was.

12 So, what might have caused all of

13 this? Well, we heard a great deal, a few minutes

14 ago, about how much of a dose and for how long a

15 dose, and what effects that might have on the

16 outcome. 

17 Rowe et al. put their doses sub-Q, and

18 so, that means that not the same proportion of

19 parent and metabolite is going to be produced in

20 those animals.

21 But also, from the work that was done

22 by Ralph Cooper and Tammy Stoker, it looks like
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1 we might be looking at some sort of a qualitative

2 -- I mean, quantitative effect there, by the

3 amount of atrazine that was given, metabolite

4 that actually reached the brain, but not a

5 qualitative one.

6 So, that doesn't seem to explain the

7 difference. The functional assessment end points

8 were well recognized, and I think that they were

9 really measuring the same thing that we were.

10 So, it comes down to species,

11 differences in mouse strains, and we've already

12 talked about how we can have very different

13 effects, depending on what's the species of

14 exposure.

15 The mice that they used were sort of

16 prone to make antibody and allergic responses,

17 but that might explain some of the effects that

18 they saw, but not all of them, because both cell

19 mediated and humoral immunity were up-regulated

20 in those.

21 So, then the question is, are those

22 results really in conflict? What are these
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1 results telling us?

2 Well, we know that the effects on --

3 of gender were constant and the supply of cells

4 seems to be pretty constant. It's genotype

5 that's sort of, out of phase, and we can't really

6 explain this.

7 However, we've realized, in the

8 immunotox community, in the last maybe five to 10

9 years, that the thing that we really need to

10 think about is immunomodulation and not really

11 worry about whether we've suppressed the response

12 or whether we've enhanced the response or whether

13 it's allergy or what have you, we've caused

14 something to happen that we didn't intend to

15 happen, and so, immunomodulation is the thing

16 that we tend to focus on.

17 So, those were sort of full gestation

18 studies. There was one study that looked at just

19 the late part of development. This was a study

20 that was done in C57 black 6 mice, and you can

21 see the doses that were used there.

22 They exposed these mice, starting at
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1 four weeks of age, and these animals become

2 immunologically mature around seven or eight

3 weeks of age. So, what they did was expose the

4 animals, just for this last period of the immune

5 system development.

6 But rather than spend a lot of time on

7 the details of the study, we can summarize it by

8 saying that most of the effects that they saw,

9 particularly at the lower doses, say, 25 and

10 five, were sort of ephemeral and they were gone

11 by a day.

12 Even at the higher doses, most of the

13 effects had resolved by seven days, and all of

14 the data that they used -- unfortunately, all of

15 the data that they collected here were

16 observational endpoints, and that can give you

17 some really important information, if you know

18 that there is a defect, and it will help you

19 maybe choose what path to go down, to figure out

20 what the defect is.

21 But all we know right now is that

22 something happened in these animals and they
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1 recovered fairly quickly.

2 There have been a number of adult

3 exposure studies here, and probably the most

4 complete one that has been done to date was one

5 that was contracted by the National Toxicology

6 Program, and was carried out by a contractor up

7 at Medical College of Virginia, and they looked

8 at a whole bunch of these different functional

9 endpoints and observational endpoints, and they

10 found very few effects in these animals at the

11 lower dose group.

12 The one thing that is sort of

13 interesting is that second bullet point there,

14 where they found a 35 percent increase in

15 antibody production, at 25 milligrams per

16 kilogram, but it was perfectly flat across the

17 rest of the spectrum, and so, I'm not really sure

18 what that might mean.

19 They challenged the animals with tumor

20 cells. They found that at the top two doses that

21 -- the resistance to this tumor cell challenge

22 was decreased in these animals, but when you go
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1 back -- they also went back and looked at the

2 primary effector cells in these animals, and

3 those cells weren't really suppressed.

4 And so, I'm not exactly sure how to

5 interpret those data either, but they were --

6 they occurred at some pretty large doses.

7 And they also had a lot, as I

8 mentioned, these observational endpoints -- and

9 none of those things really pointed to any sort

10 of a clear picture of immunotoxicity.

11 They did look for antibody -- changes

12 in antibody production, using the same assay that

13 we did, and didn't find anything. They

14 challenged the animals with bacteria that would -

15 - that live inside cells and take a response of

16 their adaptive immune response T-cells to get

17 over it. They didn't really see anything there.

18 And so, we don't really have any clear

19 picture in the NTP study, even at doses up to 500

20 milligrams per kilogram.

21 There was another study that was done

22 in C57 black 6 mice and here, they based their
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1 doses on percentages of the LD50, and you can see

2 that the -- on the second line, the next to the

3 highest dose, that should be 433, not 4,300. I

4 think those animals would have been dead, without

5 any questions, if you could have gotten that much

6 into them.

7 So, there was really no effect on body

8 weights in these animals. They had sort of a

9 mixed bag, and I don't mean to be insulting, when

10 I say a mixed bag of changes, but that's

11 essentially what it was. There was no clear

12 arrow pointing and even suggesting even one

13 direction.

14 They didn't seem to have any effects

15 whatsoever on the supply of cells, because they

16 did the same sort of thing where they looked at

17 spleen cellularity and the distribution of these

18 cells, and there was no effect on the phagocytic

19 activity of the animals.

20 They also took spleen cells out of

21 these guys at different time points, and they

22 immunized these spleens in vitro and then they
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1 looked at the number of antibody producing cells

2 that resulted from that, and it was sort of

3 interesting there, at their lowest dose, at 25

4 milligrams per kilogram, they were initially

5 suppressed and then, as they were allowed to

6 recover out over time, over a period of about

7 three weeks, that lowest dose came back to about

8 control levels.

9 But at other doses, you didn't see

10 that picture at all. The very highest dose

11 jumped right back up to control levels at 14 days

12 and then sort of dove back down to being

13 suppressed and then went back up to being

14 enhanced by 21 days, and the doses that came in

15 between there were also somewhat mixed, like

16 that, and again, I'm not really sure what to make

17 of these studies, other than, most of the effects

18 that they saw tended to be at the higher doses,

19 with these effects on the antibody response, that

20 I just don't understand.

21 Then, there were a number of really

22 excellent studies that were done by Steve Pruett
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1 and his co-workers, and they chose large doses of

2 atrazine and large doses of ethanol, and large

3 doses of some other compounds that they knew

4 would induce a stress response, that they knew

5 would really increase corticosteroid production,

6 and their goal here was not really to do a hazard

7 ID study for whether or not atrazine is toxic to

8 the immune system or not, but rather, to see

9 whether they could use this rate of production of

10 corticosterone over time, as a predictor for how

11 they would affect a variety of endpoints,

12 including antibody production and things like

13 that.

14 I happen to see that Steve Pruett is

15 here at the meeting and I -- he may be talking

16 about some of this tomorrow. He may not be, I'm

17 not really sure. But these studies -- we know

18 that at these levels, that corticosterone levels

19 will definitely be up. 

20 The interesting thing about one of

21 Steve's studies was that he never did habituate

22 the cort response after 28 days, the restraint
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1 stress habituated alcohol habituated, but this

2 didn't. This was sort of in keeping with what

3 Ralph was talking about a few minutes ago, where

4 you continue to see, when you expose the system

5 to atrazine, that there's an increase in cort

6 production.

7 So, if I was to try and sum everything

8 up here in just one sentence, it would be that,

9 we have pretty clear evidence that it's the

10 developing immune system that seems to be the one

11 that's more sensitive than the adult immune

12 system, and it seems to be working through what

13 might be similar mechanisms.

14 We never got a chance to pursue the

15 GnRH thing, because we applied for funding, for

16 Andy to continue his postdoctoral fellowship and

17 that did not work out.

18 So, the other thing that I can say is

19 that we really don't have any evidence to suggest

20 that the developing immune system is any more

21 sensitive than the neuroendocrine system, at

22 least from the studies that we've done.
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1 Then, just to sum it up, there's one

2 more type of study that's been done, which is an

3 in vitro study, and this is where they put

4 different amounts of atrazine or the same amount

5 of atrazine on the spleen cells, over time. They

6 harvested those spleen cells and then they sent

7 them onto one of these natural killer cell

8 assays, and as you can see in the graph on the

9 left, that the more atrazine that was given, the

10 more suppression of the natural killer cell

11 activity went on in vitro.

12 In the graph on the right, the dark

13 black bars there -- I know that they're sort of

14 hard to see, and I apologize. I copied and

15 pasted out of a PDF, and it did not really work

16 out well.

17 But the dark black bar is the atrazine

18 on the right and as you can see there, the longer

19 you put those cells in culture with 10 micromolar

20 atrazine, the more suppression of the natural

21 killer cell activity there is.

22 But if you look at the graph at the
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1 bottom, these are the natural killer cell. This

2 is natural killer cell activity from the mice in

3 the NTP study, and what you can see there at the

4 bottom is -- if I can make this arrow appear,

5 right here is this one little blip, and this is

6 at 250 milligrams per kilogram per day, and it is

7 at the very lowest effector to target cell ratio.

8 So, in this assay, what you do is, you

9 mix more natural killer cells in there with the

10 numbers of target cells that you have in there,

11 and so, at the very lowest level of natural

12 killer cell activity, at this medium dose, they

13 found this one in vivo effect on natural killer

14 cell activity, which sort of makes me dismiss the

15 other ones as it was -- they were interesting

16 studies, there's no doubt about it.

17 Rowe found, in these studies, that he

18 did, that there was a specific defect in the

19 natural killer cells, that prevented them from

20 delivering a lethal hit to the target cells.

21 But these two studies don't tell us a

22 whole lot more about the effects, potential
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1 effects from natural -- of atrazine on natural

2 killer cells, because all of the animal studies

3 have tended to point to no effects on natural

4 killer cells, particularly at rational doses, and

5 that's all.

6 SESSION CHAIR PORTIER: Why don't we

7 open it up to any questions? Dr. Regal?

8 DR. REGAL: Yes, do you know in the

9 Rowe study, with the mice, was there any

10 mortality in the litters?

11 DR. LUEBKE: No, according to their

12 paper, they didn't see -- they didn't even see

13 any effects on pup numbers or weight gain or

14 anything, in those.

15 SESSION CHAIR PORTIER: Any other

16 questions? Yes, Dr. Holladay?

17 DR. HOLLADAY: Yes, Steve Holladay,

18 good overview. I think we've all been there

19 before, where something works well and then for

20 some reason, something changes and it doesn't

21 quite come back, but you know you did it well the

22 first time, and not much more Balb/c mouse work
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1 has been done. The B6C3F1's and the C57's are

2 more T-helper 1 strains on the Balb/c, T-helper

3 2.

4 You commented in rats that a much

5 higher dose of dioxin could be used before you

6 see the immune changes in mice, and it made me

7 think of Ralph Smialowicz in that. What do you

8 use, like one-tenth of a microgram per kilogram,

9 and suppress the DTH?

10 DR. LUEBKE: That was a developmental

11 study. Now, in that study, the developmental

12 exposure to rats caused life long suppression of

13 DTH in the offspring, and the male were a little

14 bit more sensitive than the female, and that was

15 in rats, and the same sort of thing happens in

16 mice.

17 I was talking about an adult study. 

18 So, the ID50 for suppression of the antibody

19 response in a C57 black 6 mouse is .7 micrograms

20 per kilogram of TCDD, and doses in rats with

21 STARS and F344's, up to 25 or 30 micrograms per

22 kilogram, don't do anything, and once you get
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1 above 30, you get some enhancement of the immune

2 response.

3 DR. HOLLADAY: I guess we've got

4 automatic shutoff switch here. 

5 Some of the differences, I think, are

6 undoubtedly strain related. The rat is not a

7 mouse. You have the Balb/c as a T-helper 2

8 skewed strain, or that's likely the case.

9 It makes me think too, that we're

10 seeing more and more with different compounds,

11 when we realize where we need to look. 

12 I can remember when we said DES

13 produced transient effects on the immune system

14 of mouse and then we realized, if we looked in

15 different places, that these were actually

16 permanent changes.

17 Then the same became true with dioxin. 

18 We described them as transient in the early 90's,

19 and then they became permanent shifts, and with

20 your different mouse models, are different models

21 of rodents. 

22 In one case, you're describing immune
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1 suppression and in the other case, immune

2 enhancement is being described, and I'm wondering

3 if we look in the right places, in the same or

4 different models, if we're going to see that

5 actually both occur and they co-exist, which is

6 kind of a strange phenomenon, but we're finding

7 out that in fact, it's true, when you treat an

8 animal with dioxin, they are both immune

9 suppressed and skewed toward immune enhancement. 

10 It just depends on which area you're looking,

11 what part of the immune system you're evaluating.

12 So, I don't know, I wonder if some of

13 this is going on with atrazine and that's part of

14 why we're seeing these differences and -- between

15 the models. What do you think?

16 DR. LUEBKE: Okay, so, that was a

17 question. So, yes, I think that it's strain

18 related and that was the first thing I thought,

19 when I saw Rowe's antibody data.

20 The problem is, it would be

21 interesting to go back and challenge these

22 animals with a dust mite allergen and see what
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1 happens, because that's the sort of model that

2 you're talking about there, and it's not just

3 endocrine disruptors that do that. We know that

4 heavy metals and a variety of things do that.

5 So, you're right, you have to use the

6 right assay, to see what's suppressed. 

7 Hexachlorobenzene is a perfect example, where you

8 have some effects going this way and that way and

9 the other way, and they're auto-immune and it's a

10 real mess.

11 So, we may not have done enough assays

12 on these animals, and you know, if -- in terms of

13 immunotox hazard ID, I think the best way to look

14 at this is that we had unintended modulation at

15 the same dose in two different strains of rodent,

16 that behave immunologically different, somewhat,

17 but that's still unintended, and I think that's

18 probably the crux of the matter here.

19 DR. HOLLADAY: Something else too, that

20 I was curious about. In your mice, the thymic

21 weight didn't go down, but T-cell function was

22 changed. Do you think it's corticosteroid
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1 independent, based on that, or is it too early to

2 say that?

3 DR. LUEBKE: Well, we didn't measure

4 cort levels in these animals. From all the work

5 that's been done by our colleagues over in the

6 reproductive tox group, I would have to say that

7 cort is involved here, some place. It just -- 

8 I mean, even if it's going to be

9 alteration of GnRH, you know, that seems to trace

10 back to an initial effect on -- you know, on the

11 HPA axis.

12 But I don't think that this is the

13 sort of sledge-hammer effects that you see, when

14 people start talking about, "Well, that's not

15 immunotoxicity. It's generalized toxicity,"

16 because you have huge levels of cort. 

17 I almost wish now, that we had gone

18 back and measured cort levels on these, because

19 it would give us some idea early on in those

20 pups' lives, what their cort levels were like,

21 how long it took for them to smooth out, how long

22 before they came back to normal and whether that
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1 -- you know, there are a number of studies that

2 have shown that if you do restraint stress on an

3 animal and then you come back and challenge that

4 animal later, if you -- I'm sorry, if you stress

5 mom, and you look at her offspring later, that

6 they make a much more pronounced stress response,

7 and that can have real consequences, just in

8 resistance to infectious disease, when you

9 challenge those animals with bacteria and

10 viruses.

11 But I wish that I could connect that,

12 I wish that I could tell you what prolactin

13 levels were like. I wish I could have, you know,

14 but I can't.

15 SESSION CHAIR PORTIER: Dr. LeBlanc?

16 DR. LeBLANC: What happened to thyroid

17 hormone levels in the Rooney study?

18 DR. LUEBKE: I can show you the -- no,

19 I can't. Yes, I have that on my laptop. They

20 were suppressed. They were non-detectable in the

21 day 14 PTU animals.

22 DR. LeBLANC: Okay.
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1 DR. LUEBKE: Surprisingly enough, there

2 were some papers that showed that if you

3 compromise thyroid function, in -- particularly

4 in adults, you also compromise immune function.

5 That certainly did not happen here,

6 and I was, frankly, surprised, when -- you know,

7 when we did the repeat study, we got exactly the

8 same thing, that there were -- you could tell

9 that those PTU treated animals just weren't quite

10 right, as they say, but their immune function was

11 fine.

12 SESSION CHAIR PORTIER: Yes, Dr. Akana?

13 DR. AKANA: Just a small comment on the

14 troublesome sets of data that didn't repeat.

15 We lost a whole year of research and

16 it was because our university decided to do

17 construction, unplanned, all around us, and it

18 had an amazing effect, but we did publish a paper

19 afterwards called "Beware Construction."

20 So, unplanned, unpredictable

21 vibration, which they like to do at the night, so

22 they don't bother the investigators or the
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1 patients, is just -- it was deathly for us, and

2 my other personal observation is, when we repeat

3 an experiment and we shift to the new barrier

4 facility, with the filtered air flow, that had a

5 decided effect on HPA.

6 So, small things, environmental, that

7 are not atrazine conducing.

8 SESSION CHAIR PORTIER: Okay, I don't

9 see any additional questions. We're going to

10 move on to Dr. Liccione and discussions of

11 neurological effects of atrazine.

12 DR. LICCIONE: Good afternoon,

13 everyone. In this presentation, I will be

14 discussing new studies that have been published

15 since 2003 on the broader effects of -- the

16 broader neurological effects of atrazine, and I

17 will be presenting our assessment of these

18 studies.

19 Okay, four new studies since 2003 have

20 been identified and were reviewed. The first two

21 pertain to monoamine systems in the brain and the

22 third one was reported on potential effects on
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1 the brain somatostatinergic system, and the last

2 one was on neurobehavioral development.

3 I will just go briefly through these

4 studies. The Rodriguez study examined, in part,

5 the broad effects of atrazine on various

6 monoamines that included dopamine, serotonin and

7 norepinephrine in the hypothalamus and various

8 extrahypothalamic areas of the brain.

9 However, the focus primarily in the

10 study was still on the nigrostriatal dopaminergic

11 system.

12 This was a six month dietary study to

13 several doses of atrazine. Monoamine levels were

14 measured only at the end of the study. Locomotor

15 activity following and acute D-amphetamine

16 administration was monitored at one time, and

17 then spontaneous locomotor activity was monitored

18 at several points in the study.

19 The number of dopaminergic and non20 dopaminergic neurons in the substantia nigra and

21 the ventral tegmental area were measured and

22 micro-dialysis was included to examine dopamine
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1 release from the striatum.

2 Coban and Filipov focused specifically

3 on the dopaminergic system, and in particular,

4 the nigrostriatal dopaminergic system and the

5 ventral tegmental area.

6 This was a 14 day oral gavage study,

7 and included various doses. Dopamine and its

8 metabolites, as well as the number of

9 dopaminergic neurons were measured in this study.

10 The third study, Giusi, reported

11 effects of atrazine on the mouse

12 somatostatinergic system in the hypothalamus in

13 various extrahypothalamic areas.

14 Dams were given atrazine in corn oil

15 solution and the rats were actually trained to

16 self-administer the solution from drinking it

17 from a syringe, and that was administered on

18 gestation day 14, through postnatal day 21.

19 The authors were trying to simulate

20 what they refer to as environmentally relevant

21 concentrations of atrazine as has -- that had

22 been detected in the drinking water.
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1 The dams were removed, the F1-

2 offspring were continued with treatment. Then

3 they were sacrificed at postnatal day 60 to 65,

4 and the measurements in this study included the

5 various somatostatinergic receptor sub-types. 

6 There are five receptor sub-types, and neuronal

7 degeneration.

8 Belloni, who was actually a co-author

9 to Giusi study, investigated the potential

10 neurobehavioral development in the mouse, and

11 dams were given atrazine as was done in the Giusi

12 study, on post-day -- on gestation day 14 to

13 postnatal day 21. 

14 Various neurobehavioral parameters

15 were measured. This included writing reflex,

16 cliff aversion, four-paw grasp, auditory startle. 

17 They also look at pup ultrasound vocalization. 

18 Auxiliary temperature and body weight were also

19 measured.

20 This slide summarizes our overall

21 assessment of the monoamine studies. The brain

22 monoaminergic studies indicated potential broad
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1 effects of atrazine on dopamine, norepinephrine

2 and serotonin, as well as a decrease in the

3 numbers of dopaminergic and non-dopaminergic

4 neurons in the substantia nigra and the ventral

5 tegmental area.

6 Only one study, that's the Rodriguez

7 study, actually provided some evidence of altered

8 behavioral responses. The overall findings from

9 these studies, however, are inconclusive because

10 of the number of limitations that I will discuss

11 briefly in the next slide.

12 Okay, limitations of the study include

13 the very small sample size that were used for the

14 stereology, the reverse transcriptase polymerase

15 chain reaction and the immunohistochemistry

16 experiments, to illustrate the impact of this.

17 In the Rodriguez studies, the results

18 of the stereology were based on a very small

19 sample size, and there was high individual

20 variability in the count data, when you looked

21 across all of the groups, and the decrease count

22 that was reported at the high dose, reflects a
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1 decrease in the counts in a few individuals when

2 you're considering the variability range.

3 They only presented median values. 

4 Other statistical data, such as the mean and

5 standard deviation, coefficient variation,

6 interquartile range were not available, that

7 would help interpret the statistical dispersion

8 that you can see in the data.

9 The high variability raises some

10 questions in the precision of the stereological

11 estimates. 

12 There was limited information on the

13 sampling procedure that they used and there was

14 no statistical data that would give you a clue on

15 the biological variation and the coefficient

16 variation, because these estimates, along with

17 the coefficient of error would give a better

18 assessment of the precision of the study, which

19 is very important in stereological examinations,

20 and insight that will give you an idea of the

21 biological variation between individuals and the

22 variance of the estimates at the level of the
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1 respective individual brain regions.

2 There was also a lack of a dose

3 response in these studies and there was also

4 overall, minimal alterations in the monoamine

5 levels.

6 The minimal changes in the dopamine

7 was also noted in the Rodriguez's micro-dialysis

8 experiment, which they commented on, when they

9 tried to interpret the lack of the change of

10 dopamine metabolites, DOPAC and HPA.

11 And the lack of dose response was also

12 evident in the count data for the dopaminergic

13 neurons, that was reported in the Coban and the

14 Filipov study.

15 There's also a lack of supporting

16 evidence. For example, in all of these studies,

17 there were either no photomicrographs on the

18 reverse transcriptase polymerase chain reaction

19 and immunochemistry results or only a few that

20 were of very poor quality.

21 Both studies also relied on positive

22 tyrosine hydroxylase immunoreactivity in those --
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1 as well as the stereology, to assess the actual

2 changes in the number of neurons, and Coban and

3 Filipov expressed this very well, the limitations

4 of this, where he acknowledges that it is unknown

5 if the decrease in the positive tyrosine

6 hydroxylase immunoreactivity is actually due to

7 neuron mortality or the loss of the positive

8 tyrosine hydroxylase phenotype.

9 Other quantitative approaches, for

10 example, morphological methods, would have been

11 useful to support their conclusions, given the

12 limitations, such as the small sample size, the

13 variability, the minimal changes in dopamine, the

14 lack of a dose response and limited or no

15 behavioral measures.

16 Now, to discuss a little bit about

17 behavior, I want to just elaborate, just a little

18 more.

19 In the Rodriguez study, it was not

20 possible to fully correlate the reported

21 increased locomotor activity with the levels of

22 dopamine levels, which were measured only at the
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1 end of the study.

2 A rationale for D-amphetamine

3 selection was not given and only one dose was

4 examined.

5 The persistent locomotor activity that

6 was reported as puzzling and is uncertain, as to

7 what -- how to interpret this.

8 There was no inclusion of any direct

9 dopamine receptor agonist and antagonist, as well

10 as any kind of receptor binding assays in the

11 study design.

12 All of these limitations are important

13 to consider because the authors concluded that

14 the altered behavioral response to D-amphetamine

15 may be due to an up-regulation of the striatal

16 dopamine receptors by atrazine, yet, they

17 provided no support for this critical hypothesis.

18 Their alternate hypothesis, that the

19 response may be due to dopamine release produced

20 by atrazine is actually not supported by their

21 own data, and that of Coban and Filipov, and in

22 Rodriguez's micro-dialysis study, it actually
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1 shows that atrazine actually attenuated the basal

2 and high potassium stimulated release of striatal

3 dopamine.

4 Coban and Filipov did not include any

5 behavioral measurements at all, to assess any of

6 the relevancy of the reported changes in the

7 dopamine and the metabolites in the dopaminergic

8 neuron counts. 

9 This is important because in the Coban

10 and Filipov study, the reported loss of dopamine

11 neurons did not correlate well with the dopamine

12 and metabolite changes at the various time points

13 that were measured. In addition, there was no

14 inclusion of dopamine receptor agonist and

15 antagonist, or any receptor binding assays that

16 would clarify the observations.

17 And another problem with the Coban and

18 Filipov study is although they studied the total

19 neuronal population that would include some of

20 the non-dopaminergic neurons, at various time

21 points, they did not actually present this data

22 with very good stereological estimates and that
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1 is another limitation of the study.

2 Okay, finally, another important point

3 that I want to address is that the authors, in

4 particular, Coban and Filipov, suggest a link

5 between atrazine exposure and human neurological

6 disorders, in particular, Parkinson's disease. 

7 But the data did not support this for several

8 reasons.

9 Although it is limited, the Rodriguez

10 study suggests potential non-specificity of

11 atrazine effects on monoamine levels in neuronal

12 populations other than dopimangeric neurons,

13 which contrasts with the clinical picture of

14 Parkinson's disease and what was known with

15 animal models of Parkinson's disease, which

16 reflected clearly a selective degeneration of

17 nigrostriatal dopaminergic pathway.

18 More over, the results of the

19 Rodriguez study suggest potential effects on

20 hypothalamic serotonin, as possibly more

21 sensitive than dopamine, and -- but no additional

22 investigation of this was actually performed.
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1 This is important because the authors,

2 in turn then, concluded that the effects on the

3 hypothalamic serotonin are consistent with

4 atrazine's neuroendocrine alterations, which we

5 know to date, are the most sensitive effects of

6 atrazine.

7 They did not explore this further, but

8 simply focused on the nigrostriatal dopaminergic

9 system.

10 In addition, the Coban and Filipov

11 study suggests that there is a maximal limit in

12 the loss of dopaminergic neurons, which again, in

13 contrast what is known with the clinical picture

14 of Parkinson's disease, which involves a

15 progressive loss of neurons, which can culminate

16 in greater than 50 percent of the neuronal loss.

17 There is also a lack of histological

18 behavioral correlates that you see with

19 Parkinson's disease. Neither in vivo study

20 demonstrated any significant increase in dopamine

21 turnover rates, which would be typical of the

22 clinical picture in Parkinson's disease and what
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1 you see in -- with animal models of Parkinson's

2 disease.

3 None of them included any clear

4 positive controls for Parkinson's disease, like

5 6-hydroxydopamine or MPTP, that would help to

6 support or -- their claims.

7 The limitations of the studies,

8 besides the limitations that I mentioned, another

9 limitation that would impact any conclusion on

10 Parkinson's disease relates to the lack of the

11 examination of neuronal loss in the striatum, per

12 se. The focus was only on the substantia nigra

13 pars compacta and the ventral tegmental.

14 Now, since Rodriguez' study indicates

15 non-selectivity of neuronal loss, this would be

16 important and had they looked at this, this might

17 clarify some of the potential effects that

18 they're seeing, and also, it would be a good

19 comparison with what is known with Parkinson's

20 disease.

21 Finally, the epidemiological evidence

22 itself, to date, does not support a link between
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1 atrazine exposure and Parkinson's disease or any

2 other neurological disorders.

3 Okay, moving onto the brain

4 somatostatinergic system, the Giusi study

5 reported altered expression of specific

6 somatostatin receptor sub-types in the

7 hypothalamus and various extra hypothalamic

8 regions of the brain in the males and female

9 mice.

10 However, the findings are inconclusive

11 because of serious limitations that limited its

12 use in risk assessment. 

13 Limitations of the study include the

14 small sample size that they used for the staining 

15 to assess neuronal degeneration, the reverse

16 transcriptase polymerase chain reaction and the

17 in situ hybridization experiments.

18 There was a lack of supporting

19 evidence. For example, somatostatin, per se, was

20 not measured, that would have supported the

21 neuronal degeneration and possibly provide some

22 insight into the up-regulation and the down-
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1 regulation that they were reporting in the

2 various receptor sub-types.

3 No in situ hybridization photo4 micrographs were provided for support. There was

5 no functional assessment of the reported changes,

6 for example, behavioral tests, growth hormone

7 measurements, which was one of the rationales for

8 looking at the study, or any other hormonal

9 measurements.

10 There was no -- the study design also

11 did not include any specific somatostatin

12 receptor antagonist, that would help to explain

13 all of this up-regulation and down-regulation

14 that is very confusing to understand.

15 There were some discrepancies between

16 statements made in the text, that were not

17 supported by the reference citations. There was

18 a lack of details on the age and body weights of

19 the mice used in the source and purity of

20 atrazine. 

21 The study also did not include any

22 measurements of systemic toxicity that might be
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1 confounding factors, and the photo-micrographs of

2 the amino cupric silver staining were of poor

3 quality. This is important because this is the

4 evidence that they used to support the neuronal

5 degeneration.

6 Finally, there was actually no

7 quantification of the neuronal degeneration,

8 especially in supporting an important conclusion

9 by the authors who state, in the dentagyros, the

10 neurons showed a rather significant overall

11 reduction in the total number of neuronal cells.

12 But yet, no quantitative data were

13 provided with appropriate statistical analysis to

14 support a very critical conclusion and no photo15 micrographs of the dentagyros were actually

16 provided.

17 And all of these limitations would

18 help to help in assessing the -- what is going

19 on, because it was very difficult to correlate

20 the neuronal degeneration with -- consistently

21 with the changes in neuronal expression of the

22 somatostatin receptors, as an example, in the
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1 high dose female, you will see some hippocampal

2 degeneration, but no change in the neuronal

3 expression.

4 Okay, now, for the neurobehavioral

5 development study, the Belloni study reported

6 alterations in writing and grasping reflex and

7 also, ultrasound vocalization in mouse pups. 

8 They also reported decreased auxiliary

9 temperature.

10 The findings, we think, are

11 inconclusive because of the serious limitations

12 of the study.

13 Limitations include inappropriate

14 statistical analysis. The authors relied

15 primarily on the pup as the statistical unit. 

16 The failure to count for the litter effects can

17 result in an increase in Type-1 errors and

18 overestimate any of the effects, thus, reducing

19 the validity of the findings.

20 In addition, there was no convincing

21 statistical evaluation of the potential

22 interactions, for example, sex, age and
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1 treatment, which the authors claim. 

2 There were two -- there were a number

3 of discrepancies in the reported number of pups

4 that were evaluated in the tables, which raises

5 questions about the accuracy of the results that

6 were reported.

7 There was no clear dose response

8 relationship for the reported effect on the

9 number of ultrasound vocalization and auxiliary

10 temperature. These effects were noted only in

11 the low dose mice, but not in the high dose mice,

12 and the authors did not provide any support for

13 their hypotheses that were put forth, to explain

14 the lack of the dose response.

15 They hypothesized effects on aromatase

16 modulation and hormone levels, but no

17 measurements -- such measurements were actually

18 made to support in -- at their conclusion.

19 In addition, Belloni acknowledged that

20 they cannot exclude the possibility that the

21 hormonal alterations in the dams may have

22 resulted in altered maternal care and
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1 consequently, in altered pup behavior, and as I

2 mentioned, those -- the study did not examine

3 hormonal levels, which would clarify this as a

4 possible confounding factor.

5 And another important point is that

6 the spectrographic analysis of the ultrasound

7 vocalization were very limited. It's not clear

8 to me, why considerably less number of pups that

9 were evaluated for the number of ultrasound

10 vocalization were subsequently examined for

11 spectrographic analysis, and this was an

12 important measurement to assess the various

13 specific parameters of the ultrasound

14 vocalization, especially since the authors

15 conclude that lower atrazine exposure was more

16 effective than the higher dose in modifying

17 behavioral response.

18 There was also a lack of objective and

19 validated behavioral methods. The authors relied

20 on methods published in 1965 and the final point

21 was that there was no neuropathology that would

22 help to clarify some of the results.
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1 In conclusion, the recent

2 neurotoxicity studies of atrazine on the brain

3 monoaminergic and somatostatinergic system and

4 neurobehavioral development, because of the many

5 numerous limitations, are -- did not provide any

6 definitive conclusions, and the effects on

7 neuroendocrine function, we think, are still the

8 most sensitive effects of atrazine.

9 SESSION CHAIR PORTIER: Okay, any

10 questions? Dr. Chambers?

11 DR. CHAMBERS: John, I was trying to

12 assess the dose levels of these things, and I was

13 confused when I read the Rodriguez paper.

14 Since that was a dietary study, how

15 did they go about assessing that those were the

16 dose levels? 

17 Not the rationale, it's just, I didn't

18 get a sense of how they assumed it was five

19 milligrams per kilogram per day, when it was a

20 dietary study. They didn't describe that very

21 well, did they?

22 DR. LICCIONE: No, they did not
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1 describe it. They reported the results at five

2 milligrams and 10 milligrams per day, but they

3 don't provide any information to verify how that

4 was derived.

5 A lot of these studies don't give any

6 information on quantification of the samples, any

7 analytical measurements, food consumption. I

8 think that would have helped to support their

9 conclusion. 

10 So, I agree with you, that that's

11 another limitation that one could actually add to

12 the study.

13 SESSION CHAIR PORTIER: Dr. LeBlanc?

14 DR. LeBLANC: Do you have any idea if

15 the Giusi and the Belloni studies represent the

16 same experiment, with different analyses

17 performed?

18 DR. LICCIONE: Well, the study design

19 is the same, but there are -- there were some

20 differences in a sense, that the Giusi study --

21 they removed the dams -- then the F1s were

22 treated for a longer time, but as far as I can
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1 tell, they were not part of the same experiment,

2 but one wonders, if they were two overlapping

3 studies, if that's what you're asking.

4 DR. LeBLANC: So, in the Belloni study,

5 the pups weren't treated?

6 DR. LICCIONE: Right, that's true. 

7 They were trying to look at lactational and it --

8 in gestational lactational exposure to the pups

9 only. In fact, they actually state that they

10 prevented the pups from drinking from the

11 syringe. 

12 So, there are differences in the

13 study.

14 SESSION CHAIR PORTIER: Yes, Dr. Reed?

15 DR. REED: I think what the Rodriguez

16 study -- I think -- I thought they restricted the

17 diet, so that they can do the calculation. They

18 didn't just let the animal eat as much as they

19 want. So, that was how they calculate the dose. 

20 I think there was -- 

21 DR. LICCIONE: It wasn't clear to me,

22 from -- 
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1 DR. REED: But I have a separate

2 question. I agree, then when I was looking at

3 these studies, they're not -- you know, they have

4 holes and gaps.

5 When I see your conclusion, saying

6 that the other, you know, endpoints were still

7 more sensitive, so, my question to you is, would

8 you be thinking of -- because some of the

9 deficiencies are reporting deficiencies and so

10 forth, that you might be able to go back to the

11 authors and say, "You know, if you have

12 something, some information, some protocol and

13 study design," you cannot.

14 DR. LICCIONE: Right.

15 DR. REED: The litter effects and how

16 they called the litters, and stuff like that.

17 DR. LICCIONE: That's an interesting

18 question, because give this some thought. If you

19 look at the Rodriguez study, which is a very

20 interesting -- is that the very first initial

21 results that they report are on brain

22 norepinephrine, dopamine and serotonin,
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1 indicating a non-specificity of effect.

2 Then they jump in to the nigrostriatal

3 dopaminegric pathway, without any good rationale. 

4 The only thing I can think of is maybe the lab is

5 comfortable with that, they're specialized in

6 that. Same thing with Filipov.

7 However, given that you're seeing

8 hypothalamic serotonin -- and Rodriguez actually

9 acknowledges that, this may be related to the

10 neuroendocrine effects, it seems like, to me, the

11 more proving experiment would have been to study

12 that, rather than focusing so much on dopamine

13 and Parkinson's -- and trying to -- you know,

14 with Filipov's study, I thought I was reading a

15 new model of Parkinson's disease.

16 So, I think the right experiment would

17 be to look at this, especially since the

18 serotonin was reported, it looks like it may be

19 more potential, but the results are limited,

20 because they only did a preliminary assessment of

21 these monoamines. 

22 It seems like to me, that the
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1 neuroendocrine in serotonin thing might be more

2 fished out, rather than relying on dopamine.

3 DR. REED: And that was actually one of

4 the questions that I was curious about, in that

5 given all the gaps and deficiencies these studies

6 have, my question was since -- you know, your

7 conclusion is that they're still not the most

8 sensitive endpoints, but apparently, you have

9 some idea of how the study could be conducted, as

10 you were just describing.

11 Would you be interested in designing

12 something, just to see, you know, what the

13 endpoint is going to fall out to be, because for

14 example, I think most of them were very high dose

15 studies -- 

16 DR. LICCIONE: Right.

17 DR. REED: -- but the Rodriguez study

18 was, you know, five -- 

19 DR. LICCIONE: Five milligrams, the

20 lowest dose.

21 DR. REED: And they were seeing some

22 effects. So, my question to you, so, it's
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1 getting close to the endpoint issue, in terms of

2 what is most sensitive. Are you thinking of

3 designing something that could get the answer

4 that you were looking for?

5 DR. LICCIONE: I haven't given -- 

6 DR. LOWIT: John, if we could answer

7 that. Liz, do you want to jump in? 

8 SESSION CHAIR PORTIER: That's Anna

9 Lowit.

10 DR. LOWIT: Yes, sorry, and I've been

11 moving around chairs. That's a good question. I

12 think the short answer would be, we're not sure

13 of the value of what those studies would be, and

14 if there is an argument that those studies would

15 be valuable, with respect to keeping in mind,

16 that at the end of the day, we're asking risk

17 assessment questions, and if you could design an

18 experiment that will lead you to something of a

19 lower endpoint, of a shorter duration, that's in

20 a separate direction from where the HPA,

21 particularly new data, is leading us, which we

22 think was going to really drive many of those
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1 regulatory decisions.

2 So, you're a regulator, you know how

3 it goes. If it's something that's going to --

4 that you believe would change the direction of

5 the assessment, I think those would be valuable. 

6 But that's the question, how valuable would those

7 experiments be?

8 SESSION CHAIR PORTIER: Dr. Horton?

9 DR. HORTON: I have more of a comment

10 than a question here, because I think, in

11 response to your question, in terms of the

12 development of the neuroendocrine system, with

13 respect to both the hypothalamic-pituitary14 gonadal axis and the hypothalamic-pituitary15 adrenal axis, both of those are in play, at this

16 point.

17 Anything that's going to influence the

18 development, and since things seem to be pointing

19 back to the developing axes, we do know that in

20 the development of those, both the BNST and the

21 brain regions that we're talking about right now

22 play important roles. 
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1 Also, the hippocampus plays important

2 role in the regulation of those areas, and that

3 if there's anything that's going to have a toxic

4 effect, or not even a toxic effect, but alter the

5 developmental pathways of those in a plastic way,

6 we need to be aware of it.

7 And so, if there's anything in this

8 data that suggests that that might be there, then

9 it's probably worth going back and evaluating

10 those under-properly controlled and properly

11 designed studies.

12 DR. LOWIT: Just one follow up and we

13 can probably close this.

14 To the extent that, you know, that

15 there is science to support those things, we

16 would encourage it to appear in your report, or

17 in your deliberations over the next few days.

18 I just want to be weary, that -- and

19 in the days of limited resources and moving

20 towards less animals and not more, that we design

21 those experiments in a way that we get the most

22 out of them.
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1 SESSION CHAIR PORTIER: I think we will

2 go on. I would like to say, I'd like to see one

3 of these studies done with adequate sample sizes,

4 though. 

5 We've seen a lot of neurotox studies

6 and they're always under-powered, for the kind of

7 results they're looking for, and it's very

8 frustrating, because I think we all kind of

9 agree, that this should be important, but why

10 aren't we putting the effort into those studies?

11 Dr. Mendez, you have a summary.

12 DR. LOWIT: And we're doing a computer

13 pass, as we speak. Well, maybe Liz can start

14 talking, since we're running really late.

15 SESSION CHAIR PORTIER: How many mics

16 can we drop? He's got it untangled. Now, watch

17 the water jug.

18 DR. MENDEZ: I sure require a lot of

19 assistance, don't I? Just give me one second. 

20 Okay, I don't think this is mine.

21 All right, I promise, I'm going to try

22 and move quickly, and pick up the pace here.
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1 So, what I wanted to sort of do is

2 bring us back, wrap things up, as to where we are

3 and where we hope to go, between now and

4 September.

5 The status of the reevaluation, we

6 have reviewed approximately 100 studies that have

7 a wide range of topics, from mode of action,

8 reproductive and developmental effects,

9 immunotox, neurotoxicity and carcinogenesis.

10 You'll notice that we did not talk

11 about the carcinogenesis when we were putting

12 this paper together. We were hoping that we

13 would be able to address cancer issues in

14 September.

15 As that is not the case, we've chosen

16 to defer that conversation so that we can look at

17 both the animal and the epi data together.

18 We still believe that the effects of

19 neuroendocrine function are the most sensitive

20 effects, based on the data that we have in front

21 of us today.

22 We continue to evaluate additional
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1 studies that have become available since

2 February, and studies that will become available,

3 hopefully, in the spring and summer.

4 Having said that, where are we right

5 now? Mode of action, our understanding of the

6 mode of action is expanded. 

7 In 2003, it all hinged about the

8 perturbation of the HPG axis and that is still

9 applicable. The activation of the HPA axis,

10 however, has come into play over the past seven

11 years, and we think that it may precede the

12 effects on HPG axis, and Dr. Fenner-Crisp

13 actually alluded to that a little earlier, in one

14 of her questions.

15 We see changes in ACTH, corticosterone

16 and progesterone, within minutes of exposure.

17 However, the toxicological significance of these

18 adrenal hormone changes per say is still unclear

19 to us. Were those 15 minute blips sufficient to

20 cause an adverse health outcome?

21 From the data that Dr. Cooper

22 discussed earlier today, we believe that there is
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1 a general stimulatory effect in steroidogenesis,

2 not necessarily a direct effect on aromatase.

3 We see the delays in puberty onset in

4 both genders. Prostatitis is related to decrease

5 in prolactin and atrazine exposed dams during

6 lactation, and we didn't talk a lot about that

7 today, but it's described in the paper in some

8 detail, and the mammary gland tumor development,

9 based on the findings in the -- and the

10 conclusions of the 2000 SAP and what we have in

11 front of us today, still do not appear to be

12 relevant to humans, in terms of the mode of

13 action that we're addressing today.

14 Oh, this is a little skewed, but this

15 is a schematic that appears in the paper, about

16 the mode of action. Can I have the pointer,

17 please?

18 And what -- I'm not going to go

19 through each one of these steps. I think that

20 what's important to keep in mind is that we had

21 some of these steps back in 2003. We had the

22 GnRH pulses going down. We had the decreases in
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1 LH and prolactin, and we had the gonadal changes

2 that led us to the altered reproductive function.

3 As important as the understanding of

4 the additional steps are, as they pertain to the

5 HPA axis, one of the things that I find very

6 important about this, one of the reasons why I

7 like this particular schematic is, to my mind's

8 eye, this almost looks like a house, and the idea

9 that in 2003, we had this mode of action data,

10 and the foundation of that house is still solid,

11 seven years later. It still stands, and that's

12 important, that's an important message to take

13 home, in my mind.

14 Immunotoxicity, I'm going to really

15 fly over this. Immunotoxicity exposure during

16 development may lead to altered immune function

17 of the offspring. However, that does not appear

18 to be more sensitive than the atrazine induced

19 effects on neuroendocrine function, and as Dr.

20 Luebke alluded to, during his talk, it may be

21 related to some of that GnRH changes, that we're

22 seeing.
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1 Immunotoxicity, we've just had a

2 discussion about that. Based on the data that we

3 have in front of us, it does not appear to be

4 more sensitive than the atrazine induced changes

5 in neuroendocrine function, and it does not

6 appear to be related to Parkinson's disease.

7 So, where does that leave us? Well,

8 that leaves us with the understanding that the

9 toxic effects are due to multi-level interactions

10 of a variety of systems, neuroendocrine,

11 reproductive, nervous, immune. 

12 At the activation of the HPA axis is

13 followed by the disruption to the HPG axis, which

14 then leads us to the most sensitive effects

15 attributed to atrazine exposure, but what is

16 still not clear is the extent of HPA activation,

17 both in terms of duration or dose level, that

18 meet -- that are needed to elicit the decrease in

19 GnRH, and subsequent LH surge attenuation.

20 All right, so, I just told you where

21 we are, as of today, and we sort of give you the

22 coming attractions.
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1 The next steps in preparation for

2 September, as we want to apply the mode of action

3 framework to analyze the data that we have in

4 front of us. We want to further characterize the

5 HPA/HPG axis interactions, describing the

6 temporal relationship between HPA axis activation

7 and adverse health outcome.

8 We want to better describe the dose

9 response relationship between atrazine exposure,

10 HPA axis activation and adverse health outcomes. 

11 We have some data that we hope will be coming in,

12 in the spring and the summer, that will help us

13 address these two issues.

14 Once we have that data, we intend to

15 conduct benchmark dose analysis, to better

16 characterize the dose response curve for the

17 effects on HPA and HPG. 

18 Dr. Cooper alluded that some studies

19 we had in NOAEL-5 and in LOAEL-50, we'd like to

20 be able to define that a little bit better.

21 We have additional review of data that

22 is coming in, in the spring and summer. Again,
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1 data available between February 2010 and July

2 2010, in the mammary gland development, which is

3 a separate issue from the tumorigenesis.

4 We have decided to postpone that

5 conversation because we are aware that there are

6 data that will be hopefully published very, very

7 shortly, that will really help us have a fuller

8 picture and a fuller understanding of that issue,

9 and we felt that it was best that rather than

10 roll it out piecemeal, to bring it all together.

11 We need to start thinking the duration

12 of exposure. How long must somebody be exposed,

13 before an adverse outcome occurs? 

14 Life stages, we all know that response

15 to chemical exposure may vary through life

16 stages. How do we do that, in terms of atrazine?

17 We've seen that we have a variety of

18 effects, whether we have animals expose pre19 natal, perinatal or postnatal. So, we need to

20 start thinking about that, as we think about the

21 risk assessment.

22 What is the life stage that we really
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1 need to be protecting and therefore, will protect

2 all other life stages?

3 We are going to review the available

4 non-cancer epi data. We're going to start

5 working on a weight of evidence analysis

6 integrating the experimental tox data and the epi

7 data. 

8 If warranted, we intend to propose new

9 points of departure. We will reevaluate the FQPA

10 safety factor and we will reconsider the drinking

11 water sampling strategy, in relationship to the

12 toxicological duration of concern, because we all

13 understand that the shorter duration of

14 toxicological concern may lead us to more

15 frequent sampling.

16 So, as I said, we're going to apply

17 the moral framework. Let me tell you where we

18 are, within that process.

19 Postulating the MOA, can the MOA be

20 established in animals? Well, we already had the

21 HPG axis that's been going through review, so, we

22 have the MOA in the animals. 
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1 We're going to describe the key

2 events. We've been starting to do that, as we

3 talked about the changes in ACTH, the changes in

4 cort, changes in progesterone. That's where we

5 are at this point.

6 We're going to start working on

7 establishing the dose response concordance and

8 establish the temporal concordance. 

9 Once we've narrowed that down a little

10 bit further, then we'll proceed with the

11 analysis, talking about the strength and

12 consistency of the finding, the biological

13 possibility, whether other MOA's can be ruled

14 out, and the statement of confidence analysis and

15 implications.

16 So, additional data that we expect in

17 the spring and summer, sort of wet your appetites

18 for what's coming.

19 We have studies coming on in effect of

20 four day atrazine exposure on ACTH, cort,

21 progesterone and LH. Effect of atrazine on

22 steroidogenesis in rat granulosa cells, and that
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1 study has actually been submitted for

2 publication.

3 Effect of atrazine exposure on GnRH

4 and kisspeptin neuron regulation. Effect of

5 gestational exposure to atrazine, an oral gavage

6 immunotoxin and hormone evaluation study for the

7 effect of atrazine in male rats, and male

8 prostate inflammation on low dose metabolite

9 exposure, and that manuscript is in preparation.

10 Other data that we expect is oral

11 study of effects of atrazine on estrous cyclicity

12 and the estrogen induced hormone surge in female

13 rats, comparison of effects of atrazine on

14 pulsatile LH release and the LH surge in non15 adrenal-ectomized compared to adrenal-ectomized

16 female Wistar rats, and I believe that somebody

17 in the Panel asked about that. We know that the

18 study is underway, we just don't have the data

19 yet.

20 Use of a PBPK model, to characterize

21 atrazine by transformation to inactive moieties,

22 in relationship to dynamic changes in hormone
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1 levels, and potential adverse outcomes, and a

2 dose response modeling and determination of

3 points of departure for risk assessment and the

4 validation methods for that.

5 So, what we hope to do with the dose

6 response concordance is establish the extent of

7 corticosterone changes needed to result in

8 adverse health outcome, incorporate this data in

9 the point of departure and determinations as

10 needed, and with regards to temporal concordance,

11 situation of changes in GnRH, ACTH,

12 corticosterone and progesterone needed for an

13 adverse health outcome, changes seen within

14 minutes, sustain changes need to elicit the

15 adverse outcome, one day, four days, one week.

16 We do know that atrazine and its

17 metabolites are quickly absorbed and distributed

18 in the body, so, we need to take that into

19 consideration, as we move forward in our

20 analysis.

21 And just a little bit about the

22 mammary glands development. These are some of
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1 the data that are currently available and it's

2 the adverse effects. You can see -- you can read

3 them as well as I can.

4 A number of studies are currently

5 available in the literature, about potential

6 adverse effects on mammary gland development and

7 a few more are coming. 

8 Atrazine dose dependent effects on

9 mammary gland development in Sprague Dawley's and

10 Long-Evans rats, the effects of atrazine induced

11 mammary gland effects in Sprague Dawley and Long12 Evans rats and carcinogen induced tumor incident,

13 and an oral development study of atrazine in the

14 rat, including cross-fostering and pair feeding.

15 The Agency already has that last

16 study, but because it speaks to the mammary gland

17 development, we have deferred the discussion to

18 it for a later date.

19 And then the 2011 SAP on

20 carcinogenesis, AHS epidemiology study on

21 atrazine in human cancer publication, we hope

22 that that will happen some time by the end of
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1 this year. We integrate experimental

2 carcinogenesis data and the epi data, AHS and

3 other cancer epidemiology studies, and we will be

4 seeing you then, in 2011.

5 So, if there are no questions -- 

6 SESSION CHAIR PORTIER: Any questions? 

7 Dr. Krishnan? 

8 DR. KRISHNAN: A minor one, related to

9 the -- your house pictorial, number five slide.

10 Actually, I was -- since it's more of

11 a statement of the mode of action, I was looking

12 for some level of statement about the dose

13 metrics involved or the consideration of

14 alternative dose metrics.

15 So, I know if it's a split-level or

16 cottage, I could see that, but I don't see the

17 final connects of this. So, if you just want to

18 clarify what level of thinking has gone into that

19 or is it only the pharmaco-dynamic, if you will,

20 without potential toxic being captured in here? 

21 What was intended?

22 DR. MENDEZ: At this point in time, my
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1 intent with the little house was to sort of

2 illustrate the key events.

3 We are thinking about the PK aspects

4 of it, but that's not at this point, in there,

5 just yet.

6 SESSION CHAIR PORTIER: Dr. Fenner7 Crisp?

8 DR. FENNER-CRISP: I guess my question

9 earlier, goes to whether or not your roof is

10 leaking. The point being whether or not the

11 whole left side of the roof exists. That was --

12 I interpreted that step one as being the old

13 direct effect.

14 DR. MENDEZ: So, your question was

15 about step seven?

16 DR. FENNER-CRISP: No, one, one.

17 DR. MENDEZ: Okay.

18 DR. FENNER-CRISP: The roof. Does the

19 whole roof exist? That was the essence of my

20 question earlier. Is there evidence to support a

21 direct effect of atrazine in this whole thing, or

22 is it all going to be shown to be indirect
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1 through initial disruption in HPA to get to the

2 disruption in the HPG?

3 DR. MENDEZ: Ralph, you want to attempt

4 it?

5 DR. COOPER: Yes, I think I understand

6 the question. I think that right now, the -- I

7 just told Dr. Levine, this looks more like -- it

8 needs an arm out there, to be a children's swing

9 set, and -- 

10 But one and seven, seven are the -- if

11 we put it this way, I think based again, on the

12 temporal aspects, at least for the CNS ACTH

13 response, I'd argue that one is centrally up

14 there. If it's not at the brain, it's so rapid,

15 it would have to be brain impaired. So, that one

16 still exists.

17 Whether GnRH is still the target, I

18 think it's -- those shingles are still there, but

19 seven, there's an increasing number of shingles

20 on that roof, that says that seven is growing

21 credence, if nothing else.

22 So, but so, that means then -- and you
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1 know, we always think linearly, or we always

2 think sequentially, and they say tox pathways

3 paint us in these boxes that are lines, and this

4 is more -- we understand, given the assumption,

5 anyway, right now, that we're dealing with a very

6 basic cellular mechanism, disruption of maybe

7 cyclic AMP signaling, and we're going to have a

8 lot of pits in the whole neuroendocrine axis.

9 So, I'm not going to place my bets on

10 whether that roof is going to hold up under a lot

11 of scrutiny, but seven seems to be winning out,

12 right at the moment.

13 SESSION CHAIR PORTIER: Okay, is most

14 of this team going to be available tomorrow

15 morning, because I doubt if we're going to get

16 through all of the EPA presentation today, at

17 this point, since we're running about 45 minutes

18 behind.

19 I'm just wondering if the Panel has

20 questions in the morning, and we have kind of an

21 open -- Anna, will any, or most of these people

22 be available?
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1 DR. AKANA: We're all here, all the

2 meeting.

3 SESSION CHAIR PORTIER: Okay, good.

4 DR. AKANA: Including our colleagues

5 from North Carolina.

6 SESSION CHAIR PORTIER: Okay, good. 

7 Okay, I think we need probably a few minutes, for

8 you to change over to the hydrology groups and

9 so, we can stand, but don't leave the room,

10 unless you really have to.

11 (Whereupon, the above-entitled matter

12 went off the record at 5:13 p.m. and resumed at

13 5:16 p.m.)

14 SESSION CHAIR PORTIER: Let's begin

15 again. Just for the Panel's -- just so you know

16 my thinking, I think we probably will try to get

17 through six o'clock, but depending on the -- I

18 guess, we'll ask the -- Mr. Thurman, when he

19 wants to make the break, but I'm certain that

20 we're going -- we probably won't get the summary

21 and conclusion until tomorrow morning, and maybe

22 -- you know, the water sampling summary, until
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1 tomorrow morning and maybe the artificial neural

2 network might be a good topic for tomorrow

3 morning.

4 Okay, Mr. Thurman is going to be

5 starting the discussion on evaluating the water

6 sampling strategies.

7 MR. THURMAN: Okay, I thought I'd start

8 out, because it seems odd to have water sampling

9 in the middle of a toxicity SAP. So, I'm going

10 to kind of remind you why we're here.

11 You know, in light of new science, we

12 may end up looking at a different endpoint than

13 we looked at for the 2003 -- based on 2003 RED,

14 and if that's the case, the question is going to

15 become, we had registrants do monitoring study in

16 community water systems in vulnerable areas with

17 a sampling frequency sufficient to characterize

18 in 90 day exposure period.

19 They sampled weekly during that --

20 during the use and run-off season and biweekly in

21 other parts of the year. If we end up with a

22 shorter duration, the questions that are going to
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1 be coming to us are, well, how well does that

2 existing monitoring design characterize the

3 shorter durations of exposure, if they don't, do

4 you need to sample more frequently, in order to

5 do that?

6 We want to be able to answer those

7 questions when they come, instead of having to

8 say, well, wait, we've got to go separately.

9 One thing I'm going to point out, this

10 is a question that doesn't just apply to

11 atrazine. It's the type of question we wrestle

12 with, with other pesticides as well.

13 Atrazine is a little unique, and we're

14 going to be focusing on atrazine because it's

15 probably got more monitoring data than you're

16 going to see in all of the other pesticides

17 combined, and that may be a hyperbole, but the

18 point is, atrazine may be one of the few

19 pesticides where we're able to do drinking water

20 exposure almost entirely on monitoring, rather

21 than supplementing monitoring and modeling

22 together.
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1 So, that does make it unique, but we

2 are interested in what may apply beyond this.

3 Very quickly, I'm going to provide you

4 with some considerations, you need to take into

5 account, both in designing a monitoring study and

6 evaluating existing monitoring studies. Then,

7 I'm going to provide an overview of some of the

8 approaches we've been looking at, for analyzing

9 monitoring data of varying sampling frequencies

10 and in terms of applying through various

11 durations of exposures.

12 Then, we will either get to one or

13 both of these example approaches that are in the

14 background paper we gave you, today, or split it

15 between today and tomorrow, and then I'll come

16 back and provide you with a summary.

17 The next few slides are going to

18 illustrate the -- how -- the complex spatial and

19 temporal patterns we find in pesticides in water. 

20 Some of the other -- these factors all -- from

21 the temporal and spatial patterns, to the

22 temporal autocorrelation, which means the
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1 pesticide concentrations you measure on one day

2 are related to exposures that you would find the

3 day before, and the day after.

4 We also tend to find, when we talk

5 about sensor data, we're talking about pesticide

6 concentrations that are below a level of

7 detection, and we often see infrequent sampling.

8 All of this provides us with

9 challenges, both in terms of looking at a

10 monitoring study design, as well as interpreting

11 that, and so, I want to make sure we have that

12 background, as we go forward.

13 You saw this map in Anna's

14 presentation. I'm not going to spend too, too

15 long on this, I hope. When you're looking at

16 spatial -- and we know atrazine has widespread

17 use, but at the same time, there's enough

18 information on atrazine that we know that we can

19 zoom into certain parts of the country, and

20 that's where we expect to find community water

21 systems with higher concentrations than in other

22 parts.
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1 When you're trying to address spatial

2 variability, there's a number of ways of doing

3 that. On one extreme, you could sample every

4 community water system in the country. That's

5 several thousand of them, and you're probably not

6 going to get that with any level of intensity.

7 On the other end of it, you may look

8 it -- and this is what we did for an ecological

9 monitoring study that we brought to the SAP in

10 the past. So, you've heard that, this one is

11 focusing on drinking water.

12 We started out by using a model

13 developed by U.S. geological survey, a watershed

14 regression on pesticide, which was developed

15 using atrazine monitoring data, to identify the

16 watersheds that would be most vulnerable to

17 atrazine exposure, based on that model, and

18 that's what you see in the dark blue.

19 What we did in that case is, we

20 basically had a study set up, that sampled

21 watersheds that represent those most vulnerable

22 areas and we looked at how far we could apply
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1 that.

2 The drinking water is a little

3 different than that, in that, what we did for

4 this is, as a result of the 2003 IRED, atrazine

5 is already being monitored quarterly at each of

6 the community water systems, as part of the Safe

7 Drinking Water Act.

8 We were looking at a 90 day exposure

9 period, so, we said, you know, quarterly sampling

10 probably isn't frequent enough to characterize a

11 90 day exposure period.

12 So, what we did is, we looked at

13 community water systems that had annual average

14 concentrations above a certain threshold of

15 concentration, and those were put into more

16 intensive sampling.

17 The interesting thing that I want to

18 show here is that almost -- the vast majority of

19 those community water systems fell into this area

20 as identified as the most vulnerable watersheds

21 using the WARP modeling.

22 So, that helps us know that -- we've
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1 already a good bit, and we're working with what

2 we've learned, but it tells us that we know we

3 can zoom in on certain areas. Even within those

4 areas, we're seeing that there are some water --

5 community water systems that tend to have higher

6 concentrations of atrazine more frequently than

7 others.

8 So, there is localized variability

9 that further drives that. Some of this, we're

10 learning and it is a result of ecological

11 monitoring and some of the feedback we've gotten

12 from the SAP on that, that we hope to pass on.

13 But because of the nature of the fact

14 that we're looking at individual community water

15 systems that get thrown into this because of the

16 monitoring data, spatial patterns aren't as much

17 of a challenge for us in this regard as the

18 temporal patterns, and because we were looking at

19 these individual community systems, each of which

20 serves its own population, and each person --

21 each population potentially drinks the same

22 concentration of atrazine, as their neighbors do.
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1 So, I'm going to go into the temporal

2 patterns. One of the things, when you're trying

3 to show temporal patterns and try to show daily

4 variations, you quickly find that there's not a

5 whole lot of monitoring data out there, that

6 samples daily or almost daily.

7 What I'm showing you here are some

8 monitoring that was done with the ecological -- 

9 atrazine ecological exposure monitoring program. 

10 They tend to be a little farther upstream then

11 what you would see for most of the community

12 water systems, although there are a few community

13 water systems that are in those same type of

14 stream networks.

15 These were flowing water systems and

16 what you would expect for flowing water body is,

17 you expect to see a short, higher pulse moving

18 through than you would for a reservoir, which

19 would tend to dampen it out and spread it out.

20 But what I wanted to do is illustrate,

21 this is -- when we're talking about seasonal

22 variations, this is -- typically, what you'll see
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1 is one or two short pulses, where you get

2 elevated concentrations that decline fairly

3 rapidly and a lot of times, either low in

4 negligible detections.

5 This is in one year. The previous

6 year at that site, the same site, we got a little

7 different pattern, and a different pattern can

8 result from different application periods,

9 different rain fall events, different ways it's

10 used.

11 There's a couple of things I wanted to

12 show you. When we're talking about the auto13 correlation, you can really see it here, where

14 you see how the concentrations are related to the

15 neighbors. You also tend to see a tail coming

16 out, where you could -- a rapid, initial peak and

17 then a tail, tailing out. This is common in a

18 lot of our -- particularly, flowing water, but it

19 is a common thing that we see, and just to throw

20 in another one, when Mary Frankenberry starts

21 talking about short exposures, longer exposure

22 chemographs, shapes of the chemographs, this is
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1 an illustration of one where you do -- what you

2 actually have is multiple peaks running together,

3 so that you get a longer duration of exposure.

4 This is interesting because it does

5 make a difference on how frequently you have to

6 sample. We're not always able to predict those

7 shapes of those chemographs A-priority, but to

8 the point that we can, it helps us interpreting

9 the results of the monitoring data.

10 It's not enough just to worry about

11 how much -- how -- variability you have in a

12 season, but you do have year-to-year variability.

13 The first slide I showed you happens

14 to be this year, and the second one was -- this

15 was the double-peaks. What you tend to see from

16 the year-to-year, and this is a six year period,

17 is not only do you see differences in the

18 magnitude of your exposures, but you also see

19 different shapes in the chemographs.

20 And just to drive home the spatial

21 variability again, this site is 50 miles south,

22 same years, and you can see the difference in
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1 your exposures from year to year, so that it does

2 thrown in the fact that it's -- that a lot of

3 these differences are also localized and it does

4 present some challenges to us.

5 So, now, all we have to do is figure

6 out how to take that into account, when you're

7 looking at designing a monitoring study.

8 When we're looking at monitoring study

9 proposal, a protocol that would be submitted to

10 us, we need -- the questions we have is, how is

11 it going to account for spatial and temporal

12 patterns in exposure, and a lot of that is by

13 targeting areas where the pesticide is used and

14 when it's used.

15 So, you have a limited number of

16 samples. Instead of spreading them out

17 throughout the year, you would concentrate them

18 in the times when you expect to find it. There

19 are a lot of variabilities, additional

20 variabilities, based on the nature of the

21 pesticide itself, how it's applied, the weather

22 patterns, it's mentioned some of the water body
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1 types.

2 It's also important, as you've -- as

3 we've heard referred to throughout the day, the

4 exposure duration of concern is also very

5 important, in terms of how frequently you have to

6 sample, and it makes sense that you're going to

7 have to have more intensive sampling, if you're

8 looking at shorter duration exposure, than a

9 longer term duration.

10 If we were to come out with an

11 exposure period that's 90 -- similar to what we

12 have now, 90 days or longer, we're probably okay

13 with it, but we are okay with the monitoring data

14 we have. But if it's a much shorter duration

15 exposure, that's where we have some questions.

16 On top of that, we're also looking at

17 the consequences of rather -- of failing to

18 detect high exposure, exposures above our level

19 of concern, when they do occur, or on the other

20 hand, estimating an exposure that's above the

21 level of concern when, in fact, it turns out not

22 to be.
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1 Because FTPA requires us to come to a

2 conclusion of reasonable certainty of no harm, we

3 tend to err on the side of false negatives, more

4 so than false positives, but at the same time, we

5 want to try to be as reasonable with our exposure

6 estimates as possible. We don't want to end up

7 with an outrageously high exposure estimate that

8 really doesn't do anybody any good in that

9 regard.

10 Finally, the reality is, we can't

11 overlook the cost. It's prohibitively expensive

12 to sample daily, at enough sites, in enough

13 years, to give a full characterization of any

14 potential exposure you're looking at.

15 So, we end up with less frequent

16 sampling and less -- and fewer monitoring sites. 

17 In a lot of cases, we rely on modeling to fill in

18 the holes, and sort of help us focus on more

19 vulnerable areas.

20 What we're coming to you today isn't

21 inventing a new wheel. It's building on things

22 that have already been done in the past. 
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1 Shortly after FTPA was passed and we

2 had to look -- and we started looking at drinking

3 water exposures routinely, International Life

4 Science Institute convened a pattern that -- a

5 panel that provided some recommendations on how

6 frequently you'd have to sample for -- for

7 instance, in estimating peak exposures.

8 We brought some information to an SAP

9 on what kind of monitoring study design you would

10 need to estimate chronic exposures. So, we've

11 built from that. 

12 Charlie Crawford provided some --

13 evaluated some varying sampling strategies and

14 you'll see in our paper, that we refer to a lot

15 of a Crawford's work and tried to take advantage

16 of what he found, to build on that.

17 And both of these particular authors

18 noted that the number and frequency of sampling

19 will depend on the time frame of concern. So,

20 that's, once again, bringing it back to that,

21 linking it together.

22 What I'm going to do is, spend a
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1 little bit of time now, talking about how we

2 analyze and interpret existing monitoring data,

3 because most of the time, we're not designing new

4 studies, but we're looking at existing monitoring

5 data that's already out there.

6 In the case of atrazine, we're looking

7 at several years of monitoring community water

8 systems, and once again, we're going to be asked

9 that question very soon, is that adequate for a

10 new exposure duration?

11 So, we want to be able to get at that.

12 I'm going to begin with some of the basic

13 approaches and then walk through to more complex

14 approaches, as we go along.

15 Let's go back to that chemograph we

16 had, that I showed you earlier, that has two

17 exposure peaks, one that occurs in late April and

18 another one, about a month later, and let's say,

19 for this particular thing, we know -- this is an

20 actual -- the true chemograph that you would see,

21 and let's say, we had monitoring that was done on

22 a weekly basis, beginning April 1st.
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1 So, those red dots you see are the

2 actual samples, and what you see is, well, we did

3 -- the timing of sampling happened to hit this

4 first peak pretty well.

5 For the second peak, we're on the

6 down-slope side of that, and what we ended up

7 with is roughly about half of what the actual

8 maximum concentration was, in that regard.

9 So, we already know that if we're

10 looking at an acute exposure, that we're going to

11 end up with an under-estimate.

12 We're still at the point is, if we're

13 looking at an average concentration over another

14 duration, exposure duration of concern, to get to

15 that, we've got to figure out, how best do you

16 fill in the holes in between? We've got these

17 seven day snapshots. How do we fill in the

18 holes?

19 Well, one way to fill them is to

20 assume the same concentration on subsequent days,

21 until you get your next monitoring, kind of a

22 stair step approach, and you end up with a blocky
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1 chemograph, which, if you blur it, a little bit,

2 it's not too bad, but it's still kind of blocky.

3 Another one that's done, probably more

4 commonly, is kind of doing a linear interpolation

5 between the sampling points, it's like connecting

6 the dots.

7 If you're looking at a short term

8 exposure of concern, and particularly, if you're

9 looking at duration of exposure that is less than

10 your sampling, then there's a good chance, in

11 most cases, you're going to miss your highest

12 exposures.

13 If you're looking at longer term

14 durations, that may not be as much a problem,

15 because of the -- it will average out over time. 

16 In fact, if you look at some of the things that

17 Mary will talk about later, that we do find that

18 for the longer your exposure duration of concern,

19 the less error we see in the estimates, but

20 shorter duration, the more error we see.

21 Now, even weekly sampling is still

22 kind of a Cadillac in a lot of monitoring
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1 studies. Typically, we will see studies that may

2 be sampled biweekly or monthly or quarterly. So,

3 we're going to go back to our original site and

4 instead of sampling monthly -- I mean, weekly,

5 we're going to sample every other week.

6 And so, you see, we still hit that

7 first peak, but suddenly, we're way down on the

8 tail of the second peak. So, any type of -- no

9 matter what interpolation you do, you see -- you

10 have missed where the highest exposure is.

11 What we'd like to do is, try to figure

12 out -- you know, at some point, the sampling is

13 going to be so infrequent, that your exposure

14 estimate is probably not going to reflect a whole

15 lot of what we see out there. 

16 Some of the questions we've been

17 wrestling with over the years is, how do you know

18 if you've missed this? Are the ways that can

19 help us know when we may have missed the exposure

20 point of long term concern?

21 We're still wrestling with that. Some

22 of the modeling methods that we mentioned at the
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1 end of our chapter are ways that we think might

2 help us start to get at that, but it's still a

3 challenge we have.

4 And so, the basic interpolation

5 approach, as I just showed you, like I said,

6 these are the ones that are commonly used. 

7 They're quick and they're simple and if you have

8 a long enough exposure duration, and in

9 particular, your sampling frequency is more

10 frequent than your exposure duration, that may be

11 fine, within incertain error bounds.

12 The disadvantages are, they assume no

13 concentration is greater than the maximum that

14 they measured. They're likely to under-estimate

15 your peak or your short term exposures, and how

16 well they characterize actual concentration

17 profile depends on the timing of sampling

18 frequency. The farther apart it is, the more

19 likely those methods are to fall apart.

20 So, what if we, instead of trying to

21 draw boxes or connecting dots, we want to try to

22 fit that monitoring data with more some type of a
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1 curvilinear pattern or something that may better

2 reflect what you're actually seeing there, or we

3 want to provide some type of confidence interval

4 around our exposure estimates.

5 You're going to see some of this

6 illustrated in Mike Messner's talk. He's going

7 to talk about one way, one approach, using

8 artificial neural networks, to try to fit that

9 pattern, the pattern of the monitoring data, and

10 some of the things that can be done, in terms of

11 providing some kind of confidence intervals and -

12 - and also, in terms of looking at how frequently

13 you did monitor, or where do you have to set your

14 threshold of exposure to kind of provide either

15 balance between the false positives and false

16 negatives?

17 Mary Frankenberry is going to present

18 an approach where we think we can start getting

19 us at providing some types of confidence

20 intervals.

21 The next couple of slides I'm going to

22 show you are ones that we did not provide an
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1 example for you yet, and I put it in there

2 because it is definitely something that we are

3 considering and we've done a little bit of

4 testing with.

5 If you've heard of kriging or nearest

6 neighbor approach, you've probably heard it used

7 in geo-spatial analysis. It's been a way to take

8 a look at monitoring points over an area, in

9 other words, monitoring points in space, and fill

10 in, in between those sample points.

11 It's a way, essentially, the way you

12 do it, is you have the points, you analyze them,

13 you look for any correlation between the sampling

14 points, which is what this variogram is one way

15 that it's done, and then, you fill in, by waiting

16 -- the waiting, based on the correlation between

17 the points with the nearest neighbor type

18 approach.

19 And so, most of the time, it's been

20 used for spatial analysis. We've looked at this

21 because I think, that same concept seems like it

22 would also work for temporal analysis, and I have
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1 seen -- I have been to some national meetings,

2 where I have seen this approach tried out.

3 We had a couple of people, Jim Hetrick

4 and Jim Wolf in our office, who looked at it and

5 did give it a try, and so, what I want to show

6 you is, very quickly, what they did is, some of

7 their preliminary analysis, they looked at

8 atrazine and they looked at a couple of other

9 pesticides. 

10 The basic approach is first doing a

11 visual inspection of the data, and you noted from

12 the atrazine chemographs I showed earlier, that

13 you could see the temporal correlation -- auto14 correlation in there. It was evident.

15 They did some variogram analysis and

16 it did -- to quantify the temporal dependence,

17 and what they found is that you did get

18 correlation between measurements that ranged from

19 10 to 60 days apart. 

20 The other thing they found is, it

21 wasn't constant from year to year. So, it's not

22 something you can apply to one year -- that you
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1 can analyze in one year, and apply year to year.

2 So, it isn't constant from year to

3 year, but it does find a way of pin-pointing that

4 auto-correlation and they've done some cross5 validation and what they have -- some of the

6 preliminary analysis is they can do a conditional

7 simulation with -- that can give you an imaging

8 of the time series over years. They can use --

9 come up with a probabilistic generation of

10 exposures, and do some stochastic simulations, so

11 that we can get some confidence bounds on that.

12 So, in addition to what you're going

13 to hear from Mary and Mike, this is another

14 approach that we're going to be taking a look at.

15 The statistical approaches that I've

16 mentioned, their disadvantages are complex. They

17 take a lot more effort. It's not a quick

18 analysis of your data.

19 But where we need to provide

20 probabilistic distributions or where we need

21 confidence bounds around existing monitoring

22 data, that may be -- we see that as an approach
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1 to take. 

2 One of the other advantages, they

3 don't necessarily assume that the greatest -- the

4 highest exposure has already been detected, and

5 that's one of the reasons for the confidence

6 intervals on that, and they provide us with some

7 non-subjective way of estimating missing values

8 and the ways to account for temporal correlation.

9 They're more complex. The other issue

10 is, they don't necessarily capture the underlying

11 explanatory variables, or explaining what caused

12 that spike to occur when it did, but they may

13 have a utility in certain instances, particularly

14 when we're looking at needing a confidence bound

15 on our exposure estimates.

16 I've mentioned a little bit about

17 modeling methods and we are getting -- you know,

18 getting into a lot more detailed, involved

19 procedures. WARP, I showed you how we've been

20 using WARP and a lot is, in terms of identifying 

21 -- raking watersheds, based on vulnerability and

22 then targeting areas of -- where more monitoring
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1 would be needed.

2 But WARP has provided an estimate of

3 selected percentiles, as well as an annual mean,

4 an annual maximum -- and it's provided some

5 moving average concentrations.

6 We look at it as a potential for use. 

7 A lot of it, as the authors and developers of

8 WARP have said, it helps us screen areas where we

9 need to have more targeted monitoring.

10 They have -- they do provide some

11 estimates of these various exposure percentiles,

12 with some confidence bounds on there, so, it's

13 something that we may be looking at, as we go

14 forward with this.

15 In a lot of cases, we've used

16 deterministic models to provide ground water -- I

17 mean, surface water exposure estimates. We've

18 used pesticide route zone model, which simulates

19 pesticide run-off from the field and we use exams

20 with exposure analysis modeling system, which

21 simulates the receiving body.

22 And we've used that to provide
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1 multiple years of daily concentrations, varying

2 with weather patterns, and so, again, it gives us

3 a way of assessing the effect of different

4 weather patterns, and we've used that in various

5 tiers of our drinking water exposures, exposure

6 estimates.

7 In the 2007 SAP, that we had on

8 atrazine's ecological exposure monitoring

9 programs, Syngenta investigated a potential for

10 using PRZM, to fill in concentrations between

11 measured data from the chemographs.

12 We've looked at that. It probably was

13 a little bit more intense involved and complex

14 than we were planning to go into, but it's

15 something we were considering and have taken a

16 look at.

17 I put this in, we really didn't

18 include this in the paper, but we have seen some

19 attempts to try to use stream-flow as a way to

20 adjust pesticide concentrations in between

21 monitoring events.

22 I've seen as many chemographs where it
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1 didn't work, as where it did. There are -- it's

2 not -- what we quickly learn is, it's not just

3 the flow, but it is also the flow in relating to

4 the timing of the planting, the timing of the

5 rain fall events, all those together.

6 Some folks at the USDA's ARS research

7 center and -- in Missouri, Columbia, Missouri,

8 have looking at an index of trying to couple flow

9 adjustments with the timing of planning of rain

10 fall events, and we're keeping an eye on that,

11 because that offers some promise, that we might

12 be able to use that.

13 At this point, I'm finishing my

14 presentation, and I'll open it for questions,

15 then, we will move on to the next one or two of

16 the next two examples. I'll let you folks figure

17 that.

18 SESSION CHAIR PORTIER: Likely, one. 

19 Questions? Yes, Dr. Krishnan?

20 DR. KRISHNAN: I have two clarifying

21 questions. First one is, in the graphs you

22 showed, it was atrazine, but was that like, a
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1 total, in terms of including also the other

2 duration products, or do such figures exist for

3 other duration products?

4 MR. THRUMAN: In that particular --

5 this particular illustrations, it was atrazine

6 only. 

7 One thing I just want to clarify,

8 we're not -- at this point, we're not really

9 doing -- presenting a drinking water exposure

10 assessment. We're using whatever available data

11 we have, to try to come up with approaches that

12 we'd use to analyze, that we would then apply to

13 the drinking water exposure assessment.

14 The monitoring data that we got from

15 Syngenta on community water systems is total

16 chlorotriazines. So, that would be what we would

17 be focusing on, in that regard.

18 DR. KRISHNAN: Okay, my second one, in

19 your initial slide, you refer to the 90 day

20 rolling average, probably you or someone else can

21 answer, as well, and you refer to the time frame

22 of concern being the major reason for the choice
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1 of 90 days.

2 I have seen some justification along

3 those lines, as well. I'm wondering if we could

4 get some further clarification on the choice of

5 the 90 days, as to what went into that thinking?

6 Is it based on the tox studies, during which -- 

7 DR. AKANA: I guess, I'll answer a

8 question, and I'm not asking, just to make sure

9 that we're on the same page.

10 The 90 day rolling average was what

11 was used in the 2003 risk assessment. So, one of

12 the major points on the table for

13 reconsideration, as part of this analysis, is in

14 a pretty straight forward question, is the 90 day

15 still the right time frame, and that, hopefully,

16 will get a lot of conversation over the next few

17 days.

18 So, it's absolutely on the table, to

19 move that 90 days shorter or longer, for that

20 matter, depending on, you know, where the data

21 move.

22 At that time, the 90 day rolling
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1 average was selected by a match to the toxicology

2 data, specifically, the LH data, specifically, a

3 six month rat study. I don't know the exact

4 author, if you really want to see it, but that's

5 my -- 

6 DR. KRISHNAN: No, I think we're on the

7 same page. At least, I understand, that's what I

8 wanted to make sure, because 90 days, typically,

9 in rodent studies, represents about a tenth of

10 the life time, which is not what corresponds to

11 what's typically the sub-chronic.

12 On the equivalent human, typically,

13 it's a tenth of a duration -- a life time is

14 considered to be about seven years. That's what

15 people normally use. That's why I tried to see,

16 but this clarification helps -- would help in

17 other discussions.

18 DR. AKANA: It was done as an equal

19 matching of the days, on an effect, the 90 days

20 or short than the six months. So, that was a

21 quite conservative choice on the Agency's part.

22 SESSION CHAIR PORTIER: Dr. Lee?
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1 DR. LEE: I have a question and a

2 comment. First, the question, do we know about

3 the measurement error uncertainty, in taking

4 these samples, from the water streams, and

5 they're sort of presented up here, as stated

6 points without any error.

7 Presumably, if you sent several people

8 to the same stream and had them all take a sample

9 and then go analyze them in separate labs, you'd

10 get different answers.

11 MR. THURMAN: First of all, we probably

12 can get a little bit of that information. They

13 have -- they did do some fill-blanks and such.

14 I think the question you ask is

15 complex in all kinds of different ways, because

16 it does -- what you saw were daily chemographs,

17 but they were basically sampling, for the most

18 part, taken in one day, one time -- one incident

19 a day, dipping graph sampling.

20 Now, a few of those actually were

21 auto-samplers that sift at intervals, and then

22 what you have for a daily is a 24-hour average
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1 over that.

2 You still have sampling taking one

3 point, across the stream. So, you will get some

4 variation in that. We don't really have that

5 characterized in this particular study.

6 DR. LEE: That could be a useful thing

7 to know a little bit more about, if you're trying

8 to make any sort of confidence interval. That's

9 going to be critical for your intervals.

10 MR. THURMAN: Yes, that's true. Now,

11 what I will say is that for the community water

12 systems, it comes from the -- they have --

13 they've sample both source water and the treated

14 water. We're focusing on the source water. It

15 comes from the intake.

16 So, what you see is what is integrated

17 at that intake, which takes some of that

18 variability out. You still have a temporal

19 variability that you're going to get in that.

20 In fact, sometimes, what we'll see is

21 monitoring data is, where they've paired the

22 source water with the treated water is, that
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1 sometimes, you'll see treated water with higher

2 concentrations than source water because it's

3 differences in time, and so, it's part of the

4 variability that's -- 

5 DR. LEE: That's natural variability.

6 MR. THURMAN: Yes.

7 DR. LEE: You can't get rid of it. The

8 question is just can we quantify it a little

9 better, and it's not that you need to sample it

10 everywhere, but if you had some sort of global

11 idea of what it might be like, that would be

12 really helpful.

13 MR. THURMAN: I know we have a couple

14 of USGS folks on the Panel, who hopefully, can

15 provide some words of wisdom to help us figure

16 that out.

17 That's one we've wrestled with,

18 because we do know that -- 

19 DR. LEE: I figured it's something you

20 must have looked at before, but I didn't see

21 anything about it in the white paper.

22 The other comment I want to make is,
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1 I think that the kriging Gaussian process type

2 approach has a lot of potential here. I'm glad

3 to see you folks are looking at it.

4 I did want to comment, that you talked

5 about some variogram analysis, and they've

6 noticed that it varies a lot from year to year. 

7 It's actually a very noisy process to try and

8 analyze a variogram, and I'd expect that even if

9 you sort of just took repeated samples, you'd get

10 very different variograms within the same year.

11 And so, there is a lot more possibly

12 going on there, and it may be that it actually

13 doesn't change that much year to year, and you're

14 just looking at variability, sampling

15 variability.

16 MR. THURMAN: Well, I will say that

17 their initial analysis was with a limited data

18 set. We were going -- we're going to be looking

19 at a lot -- hopefully, a lot more data -- sets of

20 data.

21 So, hopefully, some of that will start

22 shining in, but I appreciate that.
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1 SESSION CHAIR PORTIER: I had a

2 question, it was just a clarification. The

3 hydrographs we're seeing here are for the raw

4 water is raw water at the intake, or is this from

5 the ecological studies that we -- 

6 MR. THURMAN: The ones I showed you

7 were illustration of ecology studies, and the

8 reason I showed you that is because -- and you

9 see in the paper, we showed some of the

10 chemographs with the drinking water, but those

11 are weekly samples.

12 So, what I wanted to do, to try to --

13 particularly, when I started illustrating, you

14 know, let's take seven day samples, I realized,

15 that's not going to work for those -- you know,

16 for those chemographs we generated before.

17 So, that's why I went to the

18 ecological exposure monitoring, because it did

19 have daily variations.

20 SESSION CHAIR PORTIER: I was thinking

21 about intake water coming from -- well, we have a

22 dendritic system, right, and you're up here, at
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1 the ecological studies were high up here, level

2 one, level two streams, and rarely do community

3 water systems draw from that level. They're

4 drawing three, four and five, right?

5 MR. THURMAN: Yes, that's true,

6 although, as we've looked at this, I have found -

7 - I have come across looking at maps and

8 analyzing particularly, some of the monitoring

9 sites and where it goes, I've found community

10 water system intakes up in those same areas, and

11 some of -- 

12 So, it can happen. We know that those

13 are typically higher up in the watershed than

14 what you're going to see farther down. I

15 selected those because while they're farther up

16 stream, they do show the shape of the chemographs

17 that you're likely to see, even farther down

18 stream.

19 SESSION CHAIR PORTIER: That's the

20 confirmation. Dr. Young?

21 DR. YOUNG: I just have a basic

22 question. I don't -- I think I'm missing some big
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1 idea, because you talk about false positives and

2 false negatives. So, then that -- I'm not

3 clearly, exactly what you're trying to estimate,

4 because if you get a value, it could have

5 measurement error, but it may -- what if it's

6 right on, but you take another value and it's

7 right -- no measurement error, but you get

8 different values? 

9 Are you trying to estimate the mean

10 for the area, a quartile? You see, I don't see

11 what the foundation is for false positive and

12 false negative.

13 MR. THURMAN: I think that's one where

14 I think Mike Messner will be able to illustrate

15 it a little bit better in his presentation, than

16 what -- 

17 What we're looking at is, and just to

18 try to give you -- which I don't know if it will

19 help you or not, we get exposures -- monitoring

20 sample -- data samples, say, weekly, and we've

21 got to come up with an estimate of a duration --

22 of an exposure for a duration that's say, one
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1 month.

2 And so, if we take those weekly

3 samples, there's various approaches that you can

4 take. I mean, if you assume that the same

5 concentration for the next -- for a seven day

6 period until your next sampling and average --

7 and use that to average those together, to come

8 up with a one month sample, there are times when

9 you may have hit, where if the one sampling point

10 happened to hit your peak, and you carry that out

11 seven days, when in fact, it drops pretty

12 rapidly, you're going to end up with an over13 estimate of that monthly average.

14 There are other times when you may be

15 an under -- under-estimating, because you don't

16 hit that peak. So, that's what I'm -- 

17 DR. YOUNG: I think, let me see if I

18 have it. So, what you're trying to estimate is

19 the average for the temporal scale of interest?

20 MR. THURMAN: That's correct.

21 DR. YOUNG: Okay.

22 MR. THURMAN: That's correct.
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1 SESSION CHAIR PORTIER: Dr. Hayton,

2 from the Ohio State University joined us. He

3 wasn't here when we started, and he's got a

4 question, and -- 

5 DR. HAYTON: Well, a couple of

6 questions. One is, what -- you're talking --

7 these chemographs, what happens to that in the

8 pipe? I mean, when I open my faucet, am I -- you

9 know, if I took a sample out of my kitchen sink,

10 once a week, would it look like what you're

11 showing us, or does that get modulated in the

12 distribution?

13 MR. THURMAN: It gets modulated. There

14 are a number of factors that go into that. It

15 goes through a treatment system. Depending on

16 the type of treatment that the community water

17 system has, you may have some non or all of the

18 atrazine removed, depending on the treatment

19 system.

20 Because you're going into collecting

21 and holding tags of processing tags and moving

22 through, it does get -- tend to get modulated as
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1 you go through what's exposed. 

2 However, I will point out that EPA's

3 goal is to protect the source water. So, we're

4 focusing on how do we protect the source water?

5 We need to generate exposure estimates

6 that are going to reflect drinking water for

7 human health, at the same time. If you look at

8 the reasonable certainty of no harm, if we can

9 get the source water concentration lower than our

10 levels of concern, we can be certain that the

11 treated water is going to -- 

12 DR. HAYTON: So, there's a margin of

13 safety there, and then finally, what -- it wasn't

14 clear to me, exactly how do you use those

15 concentrations? I mean, obviously, protecting

16 public health, but how -- does a bell go off

17 somewhere, when the atrazine concentration spikes

18 and the whole water system shuts down, or what

19 happens?

20 MR. THURMAN: What we do is, we have a

21 dietary exposure assessment and Dr. Lowit will

22 probably be able to answer a little better than I
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1 do, but you basically, you take your drinking

2 water exposure estimate, with the average for

3 whatever duration of concern it is, couple that

4 with your dietary exposure and in cases where you

5 do have residential exposure, you couple those

6 together.

7 Atrazine, the dominant route of

8 exposure, and maybe the only real route of

9 exposure for atrazine is from the drinking water. 

10 So, we don't really have exposure in food that we

11 would expect, and while there may be some long

12 use in some areas, for the most part, we don't

13 have residential exposure, that we look.

14 So, essentially, we are looking, in

15 this case, at concentration in drinking water,

16 but for other pesticides, it's coupled with the

17 dietary exposure.

18 DR. HAYTON: But if you think it's too

19 high, do you -- you know, what's the next step?

20 SESSION CHAIR PORTIER: I think Dr.

21 Bradbury can answer that.

22 DR. BRADBURY: So, just let me touch on
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1 your question and reaffirm that the conditions of

2 the re-registration in 2003 are designed to

3 protect the source water.

4 So, the monitoring analysis that

5 you're going to hear about from the team,

6 combined with whatever you decided the

7 appropriate exposure window is, if we need to

8 change it, the whole construct of the regulatory

9 decision is that people are drinking the raw

10 water, not the finished water, and their goal is

11 to ensure protection of the source water, because

12 5th RED, we can protect the source water.

13 Safe Drinking Water Act, we use

14 technology, if necessary, to get the

15 concentration down to a safe level. Our approach

16 is, we should be protecting the source water

17 through a regulatory decisions.

18 Now, the conditions of re-registration

19 in 2003 have this monitoring program in place in

20 the community water systems, and if we get a

21 level above our level of concern, we're aware of

22 it quickly and I believe in our condition of re-
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1 registration, if in two -- let me back up.

2 The community water system is

3 monitored for five years. So, if it goes into

4 the program, it's monitored for five years. If

5 during the course of the five years, it never

6 exceeds the level of concern, then it can get out

7 of the monitoring program, but it could always

8 come back in again, if it's safe drinking water

9 sampling regime, which is once every quarter,

10 starts to approach the three part per billion MCL

11 and then it goes back into the sampling program.

12 So, it's an ongoing monitoring

13 program. But five years in a row, you don't

14 exceed a rolling 90 day average, then you -- it

15 comes out of the monitoring program.

16 If it hasn't exceeded in two years,

17 so, one year, it exceeds, it exceeds the next

18 year, then atrazine is off-labeled in that

19 drinking water schedule and it can't be used in

20 that watershed.

21 So, we do have a bell that goes off

22 and the bell that goes off is, you can't use
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1 atrazine in that drinking watershed, if you

2 exceed the level of concern.

3 Some of the dialog we'll have on the

4 science is, is that 90 day rolling average

5 changing, as we look at the toxicology? Do you

6 have a monitoring program in place, if exposure

7 window is variable? How should your frequency of

8 sampling vary?

9 SESSION CHAIR PORTIER: Well, a bell

10 has gone off. It's 6:02 p.m. by my ruling and we

11 have about an hour's worth of presentation by

12 EPA, that we're going to put off, I'm sorry,

13 Mary, until tomorrow morning.

14 Well, I'll looked at your slides, and

15 the statisticians over here could probably stand

16 it, I'm sure this whole Panel would -- would fall

17 off.

18 We're going to pick up in the morning. 

19 This will impact the public presenters, in the

20 sense that they're going to be moved back another

21 hour. If there are presenters for which this is

22 going to cause a problem, please, let myself or
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1 Joe Bailey know. We'll try to schedule you a

2 little earlier. I know some people don't stay

3 for all of this discussion.

4 We start again tomorrow morning at

5 8:30 a.m., on time, with EPA's continued

6 presentation on the water. 

7 (Whereupon, the above-entitled matter

8 concluded at approximately 6:05 p.m.) 

9

10

11

12

13

14

15

16

17

18

19

20

21

22
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87:3,10 88:17

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83:10

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209:15,15

adult 54:19 72:3,10

111:11,13 118:8

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160:11 164:17

adults 58:1 103:6

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69:8 70:18 136:12

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210:15 211:2,6

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23:21 55:1

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55:18 57:15 88:6

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106:20 108:2,3

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ages 65:13

age-dependent

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113:22 114:16

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180:14

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191:10 193:2

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ahead 5:13 13:14

111:15

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alcohol 160:1

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36:19

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allergic 150:16

152:16

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allowed 17:2 158:5

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alter 74:4 141:17

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73:19 177:4 182:4

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131:21 133:9

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146:5 151:9,10

175:7 179:14

184:5 188:22

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140:3

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alternative 212:14

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137:21

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21:14 31:6 59:1

63:17 65:6 67:11

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149:3 152:3 161:4

amounts 137:6

161:4

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amplitude 60:12

90:21 91:20

121:18

analogous 64:22

analyses 50:13

191:16

analysis 33:13 36:2

36:5,7 38:12 39:1

40:9,11 41:9,20

49:6,19,20 51:1,2

51:4,7 63:8 122:6

122:8 124:9,14,19

125:19 126:13,14

127:17 128:6

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210:20 237:7,20

237:22 238:7,15

239:6,18 241:20

245:13 250:5,17

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231:2 237:12

239:1 244:12

247:9 250:8

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101:5,11,21

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38:8 40:13 54:19

55:21 56:2 57:13

61:13 62:12 63:16

64:16 65:1,13,14

66:2,4 67:14

72:10 85:14 90:9

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109:7 110:4

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113:3,7 114:16

118:8 120:21

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169:4 181:15

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57:22 58:6,15,19

58:21 59:2,8 60:1

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61:15 62:5,15,19

63:2,22 64:6,20

65:21 66:19,20

68:13,20 69:7

70:6 71:3,20 72:3

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142:6 143:1,5,18

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146:3 148:9 149:9

149:10 150:11

151:20 154:1,4,22

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156:2,14 157:4,8

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167:12 168:4

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antagonist 179:9

180:15 185:12

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antibodies 140:21

antibody 143:12

144:7,9 145:10,12

147:7 149:15

152:16 155:15

156:11,12 158:1

158:19 159:12

164:18 166:19

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149:21

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antigen 138:13

143:19 144:2

antigens 150:4

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anyway 55:9 76:1,8

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apart 61:6 235:18

235:19 238:19

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apparent 59:4

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apparently 67:20

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applied 160:15

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207:16 218:10

219:2 221:22

238:22 239:1

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232:22 235:5

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238:2,10 239:14

239:22 250:2

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231:14 239:15

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argues 92:15,22

arguing 81:20 91:9

argument 78:13

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72:21 73:5,7 74:4

75:2,16 76:10,15

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111:21 114:15

120:21 192:3

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aspects 41:10 94:17

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180:15

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41:18 42:16,20

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176:18 184:12

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16:21 19:14,16

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21:9,19 22:4,10

22:16,18 23:8

24:2 26:10 27:2

27:10,16,22 29:9

29:20 31:5,13,17

32:16 33:15 34:5

36:14 39:17,19

42:12 44:16 45:22

46:1,6,11 49:18

50:16 53:14,20

54:6 56:20 57:11

58:5,10 63:12

64:7,12 65:14

66:17 67:2 68:19

69:7 70:6 72:5,15

74:4,16 75:14,19

76:22 77:7,13,14

78:14,22 79:10,16

80:4 81:8,17,21

82:7,13 84:1,3,8

85:2,16,17,20,22

86:6,17 87:19

88:8,20 89:5,14

89:22 91:19 92:10

94:17 95:5 96:8

105:18 110:7

111:2 115:14

118:4,18 129:3

131:14 132:12

133:11 134:13

138:16 139:13

141:12,20 142:6

142:13,21 143:15

147:20 149:3

152:3 159:2,7

160:5 161:4,5,9

161:17,20 163:1

166:13 171:7,11

171:16 172:5,13

173:11,14,21

174:11 175:1

179:16,20 180:1

181:5,11 182:6

184:1 185:20

189:15 190:2,8

202:5 203:18

204:4,15 205:9

206:16 208:20,21

209:3,5,7,11,13

209:21 210:16

211:8,10,13,21

213:21 218:11,13

218:14,18 220:16

220:18 221:15,17

222:4 223:6,22

224:9 231:6 238:8

238:12 243:22

244:5 255:18

256:17 257:7,9

259:18 260:1

atrazine's 33:12

182:4 242:8

atrazine-exposed

143:5

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63:22

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attempt 50:1 54:10

140:9 214:3

attempts 242:19

attenuated 87:10

180:1

attenuation 47:1

47:10 48:1,20

49:4 204:19

attractions 50:20

204:22

attributed 204:15

audible 43:15

audience 6:16

134:2

auditory 174:16

Australia 18:1

author 246:4

authors 173:19

179:13 181:3

182:1 186:9

187:14 188:1,12

189:14,19 193:11

230:17 241:7

auto 135:16 225:12

238:13

autocorrelation

219:22

autoimmune 135:7

135:15

automatic 165:4

auto-correlation

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auto-immune

150:15 167:9

auto-samplers

247:21

auxiliary 174:18

187:8 188:9

availability 70:20

73:20

available 5:21 6:1

15:8 23:14 25:14

25:20 32:18 34:5

34:7 36:6 176:6

201:1,2 206:1

207:3 211:1,5

215:14,22 244:10

average 41:17

120:16 222:13

232:13 233:15

241:5 244:20

245:10 246:1

247:22 254:6,7,13

254:19 257:2

259:14 260:4

averages 41:13

averaging 119:18

aversion 174:16

aware 34:3 198:6

206:5 258:21

axes 197:19

axis 9:9,17 34:12

46:18 47:9 53:21

54:7,8 61:5 70:2

81:19 84:2,17

88:1 91:8,9,11,17

92:1 94:9,11,18

94:19,22 95:7

132:17,20 168:11

197:14,15 201:8,9

201:12 203:5

204:12,13 205:5,6

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215:8

A-priority 226:7

a.m 107:4 261:5
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99:11 102:3

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121:20 125:2,9,20

132:9 134:9,10

147:14 148:19

156:1,1 158:7,11

158:12,13 163:21

166:21 168:10,18

168:22 169:3

193:10 197:19

198:9 200:2

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230:20 231:15

234:3 259:1,8,11

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background 8:5

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219:14 220:12

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Bailey 2:22 4:3,4

12:12 13:17,22

30:17 261:1

balance 9:18 116:4

236:15

Balb/c 163:22

164:2 165:7

ball 112:14,15

Ballroom 1:15

bar 161:17

barrier 171:3

Barry 2:3 10:4

bars 59:2 161:13

basal 63:17,18

180:1

base 18:2

based 15:7 25:10

26:12 32:17 43:6

46:15 48:14,17

49:1,4 57:10

149:6 156:22

168:1 175:18

200:20 202:9

204:2 214:11

217:13 221:17

227:20 237:16

240:21 245:6

baseline 61:20 96:6

104:20

basic 37:6 215:6

231:12 235:4

238:10 252:21

basically 41:14

47:9 114:22

134:14 221:20

247:17 257:1

basis 21:3 231:22

bath 61:18

bathes 56:13

bear 15:9 17:18

bearing 147:22

beautiful 120:19

began 117:20

beginning 18:12

24:4 35:13 36:2,2

38:22 231:22

behalf 34:19

behave 167:16

behavior 56:1 57:3

141:18,22 178:17

189:1

behavioral 175:8

178:15 179:14

180:5 182:18

185:6 189:17,19

belief 33:6

believe 34:8 39:4

41:15 48:19 49:14

117:20 129:10

197:4 200:18

201:22 209:16

258:22

bell 256:16 259:21

259:22 260:9

Belloni 174:8 187:5

188:19 191:15

192:4

benchmark 20:22

205:15

best 15:8 23:12

29:21 32:18

167:13 206:9

232:15

bet 92:11

bets 215:9

better 23:4 26:3

27:7 28:7 33:8,9

35:20 117:6

176:17 205:8,15

205:20 236:1

249:9 253:15

256:22

Beware 170:19

beyond 219:2

big 37:18 136:18

252:22

bigger 74:10

billion 259:10

bimodal 104:11

binding 179:10

180:15

biological 26:22

27:9 140:10

176:15,21 208:12

bio-statistician 7:7

biphasic 104:11

birth 113:11 140:5

bit 21:9 42:6 44:6,8

44:10 45:6 65:17

74:9 105:2 109:7

113:15 148:22

149:10 164:14

178:16 205:20

208:10 210:21

223:1 231:1 233:1

237:3 240:16

242:13 247:12

248:7 253:15

biweekly 217:20

234:2

black 16:1 153:20

156:22 161:13,17

164:19

blame 146:10

bleed 143:12

blend 40:9

blip 162:5

blips 201:19

block 58:5 78:21

90:21 118:21

blockade 57:21

blocked 64:6

blocking 118:17

blocks 76:5

blocky 232:22

233:2

blood 67:18 76:8

98:9 100:5 109:20

blue 42:8 221:18

blur 233:1

BNST 111:5 197:20

Board 2:1 8:13

Bob 32:10,11 51:1

body 33:7 48:18

73:8 96:19,19

97:10,22 98:1

99:4 103:18 109:6

132:16 135:5

142:19,21 143:2

157:7 174:18

185:18 210:18

224:16 227:22

241:21

boom 121:1

born 149:9

bother 170:22

bothers 110:17

bottom 102:11

162:1,4

bound 65:22 147:5

240:14

bounds 66:15

235:11 239:11,21

241:12

box 16:1

boxes 215:3 235:21

boy 108:21 120:17

121:19 122:17

Bradbury 12:21

13:2 38:14 257:21

257:22

brain 56:9,12 57:1

61:4 62:21 63:18

63:19 64:1 67:8

67:11 71:7 73:9

73:10,12 80:8

85:8 92:19 94:1

111:5 114:1 152:4

171:21 172:1,8

174:21 177:1

184:3,8 190:2

193:21 197:21

214:14,15

brain's 63:12

break 119:14

121:22 125:2,7

126:10 130:12

216:19

breaks 43:22

breast 73:17

brief 44:3 46:3

54:10

briefly 46:13 53:8

68:15 172:3

175:11

bring 15:9 17:5

200:2 206:10

bringing 29:20

230:20

brings 14:15,22

59:13

broad 8:5 26:5

27:19 28:3 30:1

137:1 172:5

174:22

broaden 74:9 95:3

broader 22:16

26:16 61:5 78:3

79:5 121:16,17

171:15,16

broadly 27:18

29:22

bromocryptine

141:15,21 142:15
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142:22 143:7,17

brought 17:17 23:7

116:18 132:1

221:9 230:8

Brower 67:10

Bucher 1:21 11:12

11:12

build 33:5 230:16

building 229:21

built 230:11

bullet 51:16 67:1

155:13

bullets 90:11

bunch 155:8

burst-through

121:11

business 71:9

busy 142:17

button 35:1

B6C3F1's 164:1

C

Cadillac 233:22

cage 104:2 148:12

calculate 192:19

calculation 192:17

California 8:16,20

9:16 11:8

call 19:9 75:15

called 134:10

170:19 193:16

Canada 18:1

cancer 7:6 24:22

25:7,10,21 26:1

38:15,18 39:7

45:21 46:1 200:13

211:21 212:3

cancer/non-cancer

38:11

capable 62:6 64:10

capsules 105:9

captions 124:13

capture 28:7

240:10

captured 137:15

212:20

carboxymethyl

82:19

carcinogen 211:12

carcinogenesis

200:9,11 211:20

212:2

carcinoma 74:19

care 188:22

cared 148:13

Carmen 2:16 10:9

Carolina 10:11

11:2 216:5

carried 155:6

carry 254:10

cartoon 55:11 56:7

102:7,8

case 19:14 20:11,15

46:12 78:1 86:2

86:18 87:16

103:17 118:2

130:16 133:13

135:14 143:20

148:9,10 150:7

165:8,22 166:1

200:15 217:14

221:19 231:6

257:15

cases 116:18 138:1

144:16 229:17

233:11 241:15

257:4

cast 50:1

castrated 101:6,8

castration 102:2

catecholamine

46:21

catheter 85:15

120:19

causal 34:10

causative 129:2

cause 65:11 66:1

85:11,22 135:19

150:13 201:20

260:22

caused 86:19

151:12 153:13

164:12 240:11

causes 66:17 115:4

150:3

causing 85:3 129:2

caveat 147:9

ceiling 108:5

cell 78:11 93:11

103:11,12,18

104:5 135:13

136:4 137:20

140:21 141:5

143:22 144:13,17

145:14,18 146:22

147:3,3 150:1

152:18 155:21

161:7,10,21 162:1

162:2,7,12,14

cells 75:12,19 76:13

79:1 83:21 92:12

93:6,8 135:4,10

135:14,21 141:1,6

146:3 149:19,20

149:21 150:3,6,6

151:7,8,10 153:3

155:20 156:2,3,15

157:15,18,20

158:1 161:5,6,19

162:9,10,19,20

163:2,4 186:11

208:22

cellular 79:6 215:6

cellularity 137:14

157:17

cellulose 82:19

cell-line 74:18,19

74:20 76:20

center 10:5 243:7

central 64:13 67:13

82:1 92:4 105:4,5

111:2,9

centrally 214:13

century 27:6

certain 77:13

101:14 135:4

138:2 141:3

144:21,22 216:19

220:19 222:14

223:3 240:13

256:10

certainly 30:16

170:5

certainty 229:2

256:8

chain 175:15

177:18 184:16

Chair 1:17,18,20

1:21 6:5,8 7:10,12

7:15,19 9:1,7

11:22 43:11,16

52:1 53:1,12 95:9

98:15 105:13

107:10 108:10

110:20 111:16

113:13 118:15

121:21 122:19

123:2 124:22

125:6,14 126:1

127:12 128:18

132:7 134:1 163:6

163:15 169:15

170:12 171:8

190:9 191:13

192:14 196:8

197:8 199:1,15

212:6 213:6

215:13 216:3,6,14

243:18 246:22

251:1,20 252:19

255:1 257:20

260:9

chairs 6:17 196:11

challenge 155:21

166:21 169:3,9

223:17 235:3

challenged 138:13

155:19 156:14

challenges 220:9

227:4

challenging 112:9

CHAMBER 11:16

Chambers 1:22

11:16 52:1,2,10

190:10,11

chance 99:7 160:14

233:10

change 18:18,19

43:5 75:19 80:11

85:6 88:1 96:2

98:8 127:9 136:4

137:13 145:21

148:13 177:9

187:2 197:4 216:8

250:13 258:8

changed 43:3,4,10

167:22

changes 46:21 55:6

61:4 64:1 69:15

70:20 76:17 77:17

78:1 79:14 80:5,8

84:5 89:22 91:7

91:12 94:17,22

95:5 99:4 107:18

117:13 129:10

139:15 141:17

156:11 157:10

163:20 164:6

165:16 177:6

178:2,13 180:6,12

185:5 186:21

201:15,18 203:1

203:21 204:4

208:3,3,4 209:22

210:7,11,13,14

changing 52:20

260:5

chapter 235:1

characterization

23:3 99:4 229:13

characterize 205:4

205:16 209:20

217:17 218:2

222:10 235:16

characterized

94:15 248:5

Charlie 230:12

Charlottesville

8:10

check-in 21:21

chemical 8:2 16:9

17:8 18:12,14

19:20 33:7 41:7

85:13 206:15

chemically 84:16
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chemicals 9:6

16:11 27:12,19

71:5 79:8

chemograph

231:15,20 233:1

chemographs

225:22,22 226:7

226:19 238:12

242:11,22 247:16

251:10,16 252:16

255:7

children's 214:8

chlorotriazines

74:15 244:16

choice 244:22

245:4 246:21

choose 41:14

154:19

chose 139:22 149:5

159:1

chosen 200:15

chronic 10:7

105:19 230:10

circadian 105:21

circumstances

101:14

citations 185:17

cited 32:1

claim 100:9 188:1

claims 183:6

clarification 98:17

102:6 118:16

126:2,9 245:4

246:16 251:2

clarified 125:21

clarify 52:2 113:15

114:10 128:19,22

129:16 180:16

183:17 189:3,22

212:18 244:7

clarifying 43:13

243:20

clear 68:11 82:7

83:7 87:22 92:2

94:13 119:11

131:6 156:10,18

157:11 160:9

183:3 188:7 189:7

192:21 204:16

256:14

clearly 26:6 27:1

54:7 146:4 151:10

181:16 253:3

clears 121:5

cliff 174:16

clinical 102:10

181:13 182:13,22

clock 116:1

close 31:16 50:4

196:1 198:13

closely 72:20

clue 137:21 176:14

clues 137:11

CNS 115:3 214:12

CNS-mediated

70:14

Coban 173:2

177:13 178:2

179:21 180:4,9,17

181:4 182:10

coefficient 176:5

176:15,17

coffee 119:15

cold 43:21

collaboration 18:7

collaborative 18:5

colleague 7:15

29:12

colleagues 13:22

15:12 17:22 18:6

25:17 28:12 29:6

29:13 32:12 44:12

51:8 76:11 168:5

216:4

collect 50:2

collected 42:1

154:15

collecting 255:20

College 9:12 11:17

155:7

Columbia 243:7

combined 218:17

258:6

come 6:1 20:14

22:5 30:17 41:3

51:18 76:3 111:17

125:2,20 131:9

163:21 169:3

201:10 218:7

219:15 228:10

229:1 239:9

244:11 252:7

253:21 254:7

259:8

comes 20:3 100:5

100:10 152:10

248:12,15 259:15

comfortable 194:5

coming 21:12

24:11 26:2 30:18

43:21 44:14 45:4

51:6,9 55:14

100:4 101:20

103:16 107:22

113:5 122:20

135:10 204:22

205:11,22 208:18

208:19 211:7

218:1 225:15

229:20 251:21

comment 5:9 26:5

30:19 131:11

170:13 197:9

247:2 249:22

250:4

commentaries 50:7

commented 164:4

177:8

commenters 12:11

12:17

comments 5:12,14

5:22 40:8 95:11

113:16 122:1

123:5 124:21

133:14

commitment 31:3

31:8 34:18

Committee 5:7

common 225:17,19

commonly 233:4

235:6

community 15:12

153:8 217:16

220:20 221:4

222:6,13,19 223:5

223:14,19 224:11

224:12 231:7

244:15 248:11

252:2,9 255:16

258:20 259:2

compacta 183:13

companies 17:4

comparable 83:19

89:22

compare 59:19

84:4

compared 75:5

89:5 209:15

Comparing 90:6

comparison 183:19

209:13

compensatory

104:18

complete 57:20

155:4

completed 19:5,14

21:7

completing 25:11

complex 15:13 16:5

219:18 231:13

239:16 240:9

242:13 247:15

component 30:22

38:18 39:12 41:19

45:13

components 15:22

85:7

composition 98:1

compositions 96:20

compound 20:7

57:12 60:5,11

82:1 84:12 137:19

145:21

compounds 75:22

118:19 138:2,19

138:20,20 150:13

159:3 165:10

compromise 170:3

170:4

computer 199:12

concentrate 53:10

227:17

concentrating 45:3

concentration

63:21 68:2 112:15

222:15 223:22

232:8,13,20

235:13,16 254:5

256:9,17 257:15

258:15

concentrations

20:20 58:10 71:19

75:4 82:22 96:8

110:1,5 173:21

220:1,6,21 222:14

223:6 225:2,14

241:5 242:1,10,20

249:2 256:15

concept 14:17

19:19 237:21

concepts 15:4 27:2

27:17

conceptual 92:22

102:8

Conceptually

109:8

concern 41:7

207:12,14 228:4

228:19,21 230:19

232:14 233:8,18

234:20 244:22

256:10 257:3

258:21 259:6

260:2

concerned 42:12

114:6

concerns 129:2

concert 17:22

conclude 189:15

concluded 68:4

179:13 182:2

261:8

conclusion 76:18

183:9 186:8,14

188:18 190:1
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216:21 229:2

conclusions 178:11

190:6 202:10

concordance 40:18

208:7,8 210:6,10

condition 21:12

130:2 258:22

conditional 239:6

conditions 258:1

258:18

conducing 171:7

conducive 129:20

conduct 49:9 83:5

205:15

conducted 44:5

49:17 50:6 69:2

195:9

conducting 33:3

confidence 37:14

41:21 148:5

208:14 236:3,11

236:19 239:11,21

240:5,14 241:12

248:8

confident 27:16

37:13 83:9 109:16

confidentially

34:10

confirmation

252:20

confirmatory

20:14

conflict 152:22

confound 109:7

confounding 186:1

189:4

confused 108:16

190:13

confusing 185:14

connect 169:11

connecting 233:5

235:21

connection 33:12

33:14 114:4

connects 16:20

212:17

consequence 47:5

130:20 131:20

consequences

169:7 228:17

consequently 189:1

conservative 127:5

128:16 246:21

consider 31:7

45:12 179:13

considerably 189:8

consideration

118:3 210:19

212:13

considerations

219:4

considered 53:9,19

70:21 246:14

considering 176:2

237:3 242:15

consistency 208:12

consistent 38:2

64:1,2 182:3

consistently 96:1

186:20

constant 47:22

48:2 66:20 115:22

116:9 117:11

130:13 153:3,4

238:21 239:2

constantly 149:2

constitutes 136:21

construct 258:8

construction

170:17,19

consultant 8:9

consumption 191:7

contain 75:2

contained 33:22

contaminants 8:2

context 16:7 21:19

24:10,21 27:4

28:5,9 44:9

continue 33:5

125:17 160:4,16

200:22

continued 20:8

33:19 60:9 174:2

261:5

continues 66:2

continuing 39:19

contracted 155:5

contractor 155:6

contrast 182:13

contrasts 181:13

contribute 91:13

94:22 95:7

contributed 70:17

contributes 67:4

contributing

102:15

control 8:13 59:1

60:19 61:15 62:15

62:19 63:13 67:3

83:1 135:16 137:3

158:8,11

controlled 198:10

controls 136:20

142:12 183:4

controversy 80:20

convened 1:15

230:4

conversation

200:16 206:5

245:16

converts 73:6

convinced 60:16

convincing 85:9

187:20

Cooper 32:10

50:21 51:22 53:13

53:15 95:20,22

96:4,11,21 97:1,4

97:9,14,17 98:2,5

98:7,12,22 99:14

99:20 100:7,13,16

102:12,19 105:22

106:8 107:3,15,21

108:8,18 111:10

111:14,18 112:12

113:1 114:11,14

114:21 115:10

117:5 118:20,22

119:12,21 120:4,8

120:11,17 122:9

122:11,14,17

123:9,13,17,20

124:1,4,6,11,19

125:15 126:21

129:5,13,17

130:11 133:5,15

133:17,20 146:14

151:22 201:21

205:18 214:5

coordinator 4:13

copied 161:14

corn 44:19 173:14

correct 254:20,22

correlate 178:20

180:11 186:19

correlates 182:18

correlation 225:13

237:13,16 238:13

238:14,18 240:8

corresponds

246:10

cort 87:11 104:4

106:6,15 108:2

127:15 159:22

160:5 168:4,7,16

168:18,20 208:4

208:20

corticosteroid

159:5 167:22

corticosteroidal

82:8

corticosterone

82:14,22 83:4,8

83:19 85:18 86:8

86:9,14,20 89:9

89:16 93:6 159:10

159:18 201:15

210:7,12

CORT/ACTH

105:15

cost 229:11

cottage 212:16

coughing 44:1

count 175:20,21

177:12 187:16

country 37:3 39:18

42:10 220:19

221:4

counts 176:1 180:8

Coupe 2:2 9:3,3

couple 12:1 14:20

16:17 46:10 81:15

98:17 112:6

134:19,21 139:19

141:8 225:11

236:21 238:3,8

243:8 249:13

255:5 257:3,5

coupled 257:16

course 21:8 23:18

26:15 28:17 29:3

32:8 54:20 55:7

59:14 70:18 83:15

104:16 112:13

259:5

cover 134:21

co-author 174:8

co-exist 166:5

co-workers 159:1

Crawford 230:12

Crawford's 230:15

create 131:11

credence 214:21

CRF 94:1,3,4

Crisp 8:9 132:8

213:7

critical 26:10 27:22

28:1 112:21

116:14 119:5

136:11 138:15

179:17 186:14

248:9

crops 42:11

cross 239:4

cross-fostering

211:14

Crowne 1:15

crux 167:18

Cruz 8:21

culminate 182:15

culture 161:19

cupric 186:2

curious 120:14

167:20 195:4
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current 5:20 18:20

19:12 20:7 21:22

22:3,12 26:12

33:2 40:6 44:10

49:6,19 95:3

currently 8:9 19:11

211:1,4

curve 205:16

curvilinear 236:1

cut 84:22

cycle 54:16 55:3,3

56:6,6 59:10 65:3

65:20 69:15,17

116:13,22 117:2

cycles 64:17 69:13

69:16 113:18

115:20 131:21

cyclic 78:15 215:7

cyclicity 115:21

209:11

cycling 67:17 115:2

116:10,13

CYPs 93:16

CYP17 101:12,15

CYP19 112:1

cytochrome 73:5

cytokine 147:8

cytotoxic 150:5

C-O-N-T-E-N-T-S

3:1

C57 153:20 156:22

164:19

C57's 164:1

D

D 2:7

DABT 1:21,22 2:4

2:13

DACT 76:4 83:18

84:3 85:20 88:11

88:13 89:7 108:15

109:14,15,22

110:2,5,7,16

daily 112:5 224:3,6

224:6 229:12

242:1 247:16,22

251:19

dam 69:10

dampen 224:19

dams 48:19 140:8

173:14 174:1,11

188:21 191:21

202:5

Dan 9:8 11:5

DANIEL 1:23 2:15

dark 55:19 59:10

161:12,17 221:18

darker 87:4

dark-blue 42:8

data 20:13,14

21:14 22:20,21

23:2,3,13,13 25:8

25:22 33:8 34:9

36:6 40:9,14

41:21,22,22 44:4

46:10 49:10,11

50:13 53:9 57:4

58:4 62:16 88:22

93:19,20 96:13

101:18 106:8

109:21 119:16,18

120:1,12,16 121:1

121:7 122:18

126:14 127:2,3,9

127:11,15,16,21

127:21 128:2,3,9

128:12,13 132:16

141:10 147:11

148:6 149:18

154:14,15 156:5

166:19 170:14

175:20 176:4,8,14

177:12 179:21

180:21 181:7

186:12 196:21

198:8 200:17,20

201:21 203:9

204:2 205:3,11,14

205:21 206:1,6

207:4,6,7 208:16

209:10,18 210:8

211:1 212:2,2

218:15 219:9

220:5 221:15

223:16 224:5

226:9 228:13

231:2,5 235:22

236:9 238:11

239:18,22 242:11

244:10,14 245:20

246:2,2 248:21

250:17,19,20

253:20

database 50:4

databases 49:21

date 155:4 182:5

183:22 211:18

Dawley 45:9 58:7

59:20 211:11

Dawleys 60:3

Dawley's 211:9

day 4:9 7:14 39:2

41:12,13,17 48:17

48:22 51:17 52:6

52:11,16,17 55:8

55:9,9,12 58:9,18

59:12 62:12 82:20

87:6,13 90:20

100:13 103:1,3

104:2 106:13

107:16 140:11,12

140:16 149:8

154:11 162:6

169:21 173:6,18

173:18 174:3,12

174:13 190:19

191:2 196:16

208:20 210:15

217:18 220:1,3,3

222:8,11 228:3

232:17 244:19

245:10,14,22

247:18,19 251:14

254:5 259:14

260:4

days 34:20 35:3

37:22 39:11 41:16

55:7 58:22 59:19

60:3,6,7,15 62:6

71:10,22 82:17

86:12,13,21 89:11

90:4,18 94:21

98:9 149:11

154:13 158:11,14

159:22 198:17,19

210:15 228:12

232:20 238:19

245:1,5,17,19

246:8,19,19

254:11

DEA 85:22 88:20

dead 157:4

deal 27:19 28:2

151:13

dealing 215:5

deathly 171:1

decent 75:4,5

decide 18:13 42:19

43:8

decided 81:19

170:16 171:5

206:4 258:6

deciding 42:22

decision 4:18 14:15

14:19 15:6,21

16:6,13,16 20:15

258:9

decisions 4:19

16:13,14,19,22

17:10 26:11 29:20

31:2 33:1 35:18

197:1 258:17

decline 89:12 225:2

decrease 57:14

58:22 66:18 69:17

70:14,16 78:16

88:6 90:21 91:20

92:17 93:3 104:6

104:17 105:12

106:19 119:8,9

175:2,21 176:1

178:5 202:4

204:18

decreased 48:18

64:2 102:21

104:20 155:22

187:8

decreases 59:17

97:10 202:22

defect 154:18,20

162:18

defer 44:11 200:16

deferred 211:17

deficiencies 193:9

193:9 195:5

define 205:20

defined 132:12

definitely 159:19

237:2

definitive 190:6

degeneration 174:7

181:16 184:15,21

186:5,7,20 187:2

delay 59:5 68:19

71:2 108:14

delayed 47:13

48:17 49:1 69:6

84:10

delays 202:3

Delclos 2:3 10:4,5

107:10 108:10,12

deliberations 13:11

14:6 15:18 34:20

198:17

delivered 149:2

delivering 162:20

demonstrated

182:20

demonstrating

82:6

dendritic 251:22

dentagyros 186:9

186:15

Department 9:1,20

11:1,7

departure 43:1

46:15 207:9 210:3

210:9

depend 230:19

dependence 238:16

dependent 57:14

61:3 99:10 211:8

depending 12:7

77:7 152:13

216:17 245:20
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depends 81:2

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depletion 67:21

130:3

derived 191:4

DES 165:12

describe 119:19

190:20 191:1

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described 147:10

165:18 166:2

202:7

describing 132:17

165:22 195:10

205:5

desethylatrazine

75:16

design 179:11

185:10 191:18

193:13 196:17

198:20 218:2

220:10 230:9

Designated 2:22

4:6 13:18

designed 110:17

198:11 258:2

designing 195:11

196:3 219:5 227:7

231:3

designs 25:1 28:21

desire 5:11

desperate 119:14

detail 50:9 134:16

202:8

detailed 30:6 35:4

36:4 240:18

details 53:22 154:7

185:18

detect 228:18

detected 173:22

240:4

detection 220:7

detections 225:4

determination

210:2

determinations

210:9

determine 33:18

49:13

determining 19:20

deterministic

241:16

develop 49:14

117:9 130:5

developed 17:21

32:5 221:13,14

developers 241:7

developing 10:2

70:8,9 72:9

104:10 111:12

112:13 160:10,20

197:19

development 10:14

29:7 32:9 44:13

48:5 52:21 73:21

101:14 112:21

113:4,21 114:3,8

114:17,18 115:4,9

128:20 129:11

131:18 133:9

136:10 142:3

146:20 153:19

154:5 172:2

174:10 187:5

190:4 197:12,18

197:20 202:8

203:16 206:2

210:22 211:6,9,13

211:17

developmental

10:21 45:18 52:13

52:19 69:11

145:16 148:16

164:10,11 198:5

200:8

developments

129:4

deviation 176:5

DFO 4:13

DIA 85:22 86:19

87:18,21 88:9,20

89:3,5 106:19

dialog 260:3

dialogue 36:4

diestrus 87:7,7

95:18

diet 192:17

dietary 17:15

172:12 190:14,20

256:21 257:4,17

Diethylstilbestrol

145:17

difference 40:22

62:4 63:9 97:12

97:15,19 129:6,7

135:13 142:12

148:4 152:7 226:5

226:22

differences 112:3,8

128:16 148:20

152:11 165:5

166:14 191:20

192:12 226:17

227:3 249:3

different 23:10

26:22 42:1 47:20

54:12 56:8 58:6

58:16 59:3 60:13

67:20 68:2,11,16

70:5 71:5 73:8,13

73:14,14,22 75:1

76:16 78:4,5

79:17 80:1 82:10

82:15 90:12 102:2

103:21 112:14

115:7,16 118:5

121:11 126:20,21

127:16 135:11

146:16,17 147:19

149:1 150:2

152:12 155:8

157:21 161:4

165:10,15,20,20

166:4 167:15,16

191:16 217:12

222:3 225:7,7,8,9

225:9 226:19

242:3 247:10,15

250:10 253:8

differential 130:20

differentiation

73:11

difficult 80:11

119:19 125:8

186:19

dimorphic 144:3

146:18,20 149:13

dioxin 137:7 164:5

165:17 166:8

dipping 247:19

direct 81:9 89:14

92:10 93:5,21,22

94:5 104:15 105:2

132:13 133:1,4

135:20 179:8

202:2 213:13,21

direction 157:13

196:20 197:4

directly 114:19

135:21

Director 7:5 11:13

12:21 30:9

disadvantages

235:12 239:16

disclosure 5:2

discrepancies

185:15 188:3

discuss 33:11

175:10 178:16

discussed 201:22

discussing 171:14

discussion 53:2

112:21 134:7

204:2 211:17

217:5 261:3

discussions 27:2

171:10 246:17

disease 117:10,21

135:7,15 150:15

169:8 181:6,14,15

182:14,19,22

183:2,4,10,20

184:1 194:15

204:6

disfunction 139:9

dismiss 110:12

162:14

disorders 181:6

184:2

dispersion 176:7

disrupt 71:3 73:19

119:3

disrupting 63:12

64:16 67:14 69:4

105:20 145:20

disruption 61:3

69:12 70:14 91:11

91:14,22 95:1,8

115:20 137:3

146:12 204:13

214:1,2 215:6

disruptive 63:7

disruptors 167:3

disrupts 67:2

distinct 55:6,18

distress 85:4

distributed 210:17

distribution 151:5

157:17 255:12

distributions

239:20

disturb 64:13

disturbance 132:20

disturbances 56:20

132:17

disturbed 115:22

dithiocarbamate

120:22

dithiocarbamates

119:1

diurnal 66:12

diverse 35:6

divided 53:16

division 29:4,5

30:10 31:19

137:20

DMDC 120:18

docket 1:10 5:15,17

5:18,21 6:2 12:16

12:19 50:18

doctors 31:22

document 78:7

108:17

doing 25:12 28:5
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244:9

dollar 92:11

dominant 257:7

DOPAC 177:10

dopamine 172:6,22

173:7 175:1 177:6

177:10 178:13,22

179:9,16,19 180:3

180:7,10,11,14

181:21 182:20

193:22 194:12

195:2

dopaminegric

194:3

dopaminergic

172:10,19,20

173:3,4,9 175:3

177:12 180:7

181:17 182:8,12

dopimangeric

181:12

dose 33:8 34:12

37:9 40:3,17

49:12 57:13,21

58:9,14,21 59:4

59:17 60:15,20,22

63:5,9 64:7,20

65:19 69:7 71:3

71:11 72:4,11

83:7,16,18 85:16

86:5,12,17,18

87:3,5,19,21 88:7

88:21 89:1,7

90:13 91:2 93:1

94:20 97:11 99:10

103:8 104:13

106:10,17,17,19

109:11,18 110:7

112:4 120:3

126:18 127:18

139:13,18,22

140:7 143:18

147:14,15 148:10

149:2 151:14,15

155:11 157:3

158:3,7,10 162:12

164:5 167:15

175:22 177:2,11

178:14 179:3

187:1 188:7,11,11

188:14 189:16

190:12,16 192:19

195:14,20 204:17

205:8,15,16 208:7

209:8 210:2,5

211:8 212:12,14

dosed 57:9 61:13

61:20 62:6 68:13

69:10 82:17,18,19

86:20 87:6,18

133:11

doses 57:11 58:16

59:3,8 60:13,17

65:15 70:7 79:17

80:4 82:11,15

87:5 89:8 90:14

96:15 97:2 102:22

106:21 112:5,5

126:19 128:11

137:7 149:6

151:17 153:21

154:9,12 155:20

156:6,19 157:1

158:9,14,18 159:1

159:2,3 163:4

164:20 172:13

173:7

dosimetry 21:10

24:3,5,10 33:12

dosing 59:12,16

60:3,9,22 83:2

87:9 104:14

107:13 110:3

149:4

dot 125:9

dots 232:1 233:6

235:21

double-peaks

226:15

doubt 162:16

215:15

dove 158:12

down-regulation

185:13

down-slope 232:6

Dr 6:3,6 7:8,17,21

8:3,8,15,19,22 9:3

9:7,8,11,15,19

10:4,9,15,18,22

11:5,12,16 13:2

30:5,8 31:12,14

31:14,15 34:14,21

35:1 38:14 39:13

40:3 43:12,17,19

46:2 49:7 50:21

51:1,2,9,12,14,17

51:22 52:1,2,8,10

52:12 53:1,2,7,13

53:15 62:8 71:16

79:13 81:16 85:19

86:16 88:22 95:11

95:12,20,21,22

96:3,4,10,11,16

96:21,22 97:1,3,4

97:8,9,13,14,16

97:17,21 98:2,3,5

98:6,7,11,12,14

98:15,16,22 99:14

99:17,20,21 100:7

100:12,13,15,16

102:5,12,13,19

105:13,14,22

106:4,8 107:2,3,9

107:10,12,15,20

107:21 108:8,10

108:11,12,18

110:20,21 111:10

111:13,14,18,18

111:20 112:12,20

113:1,13,14

114:11,13,14,19

114:21,22 115:10

116:17,17 117:5

118:15,16,20,21

118:22 119:10,12

119:13,21,22

120:4,5,8,9,11,13

120:17 121:7,22

122:2,9,10,11,12

122:14,15,17,22

123:4,6,9,10,13

123:15,17,19,20

123:21 124:1,3,4

124:5,6,8,11,12

124:16,18,19

125:4,15,18,19,22

126:8,9,21 127:11

127:14 128:18,19

129:5,9,13,15,17

130:8,11 132:7,9

133:5,15,16,17,18

133:20,22 134:7,9

134:12 163:7,8,11

163:16,17 164:10

165:3 166:16

167:19 168:3

169:15,16,18,22

170:1,12,13

171:10,12 190:10

190:11,22 191:13

191:14,18 192:4,6

192:14,15,21

193:1,14,15,17

195:3,16,17,19,21

196:5,6,10 197:8

197:9 198:12

199:11,12,18

201:12,21 203:19

205:18 212:7,8,22

213:6,8,14,16,17

213:18 214:3,5,7

216:1,4 243:19,20

244:18 245:7

246:6,18,22 247:1

248:6 249:5,7,19

252:20,21 254:17

254:21 255:1,5

256:12,21 257:18

257:20,22

drabs 81:14

draft 34:1 46:8

dramatic 58:22

84:7 107:18 136:7

draw 235:21 252:3

drawing 252:4

dribbles 81:14

drinking 1:7 6:13

8:1 17:16 20:17

20:19 21:14,20

24:7,9 25:1,3 28:5

28:8,13,15,19

29:14 32:6 33:15

35:7 36:18,19

37:2,12 38:9,13

39:2,3 41:4,6,19

42:13 43:8 49:16

51:19 173:16,22

192:10 207:10

218:19 221:11

222:2,7 230:2

242:5 244:9,13

251:10 256:6

257:1,9,15 258:9

258:13 259:8,19

260:1

drinks 223:21

drive 41:11 134:10

134:11 196:22

226:20

driven 39:5 67:7,20

114:1

drives 223:9

driving 68:18

113:2 115:19

133:8

drop 199:16

dropped 90:14

drops 254:11

DTH 164:9,13

due 92:9 93:5 145:5

178:6 179:15,19

204:9

Duke 62:9

Duluth 10:17

dump 121:13

duration 39:6,8

41:9,14 43:4

59:16 60:21

109:19 196:19
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233:18,20 235:8

235:10 244:2,3

246:13 253:21,22

257:3

durations 37:9

218:3 219:11

233:14

dust 166:22

duties 135:11

dynamic 21:3

209:22

D-amphetamine

172:15 179:2,14

D-flat 121:10

D.C 1:17

E

E 1:22 2:22

earlier 57:10 58:4

69:17 77:11 78:14

90:11 96:21

100:19 109:2

113:6 115:20

116:18 117:16

141:16 148:20

201:13,22 213:9

213:20 231:16

238:12 261:2

early 29:11 66:19

66:21 67:4 88:19

90:19 94:10 97:6

107:19 113:1

146:19 165:18

168:1,19

easier 70:1

eat 192:18

eating 97:20

Eco 11:6

ecological 17:8

20:5 44:22 45:4

221:8 223:10

224:8,9 242:8

251:5,18 252:1

ecology 251:7

editor 50:8

EFED 51:8

effect 9:13 54:6

59:16 60:2,12

63:7 69:5 71:8,12

76:4,10 78:9 79:5

81:9,22 82:7

87:22 88:13 89:14

90:18 92:4,10,13

93:5 94:13,15

104:11,16 108:5

108:15,16 120:3

132:12 136:7,18

137:9 138:21

142:8,20 143:21

144:3 145:3,7,22

146:3 147:21

150:1,22 152:2

157:7,18 162:13

168:10 170:18

171:5 188:8 194:1

198:4,4 202:1,2

208:19,21 209:3,4

209:7 213:13,21

242:3 246:19

effective 59:17

60:22 189:16

effector 156:2

162:7

effectors 92:16

effects 1:6 3:9,10

3:14 6:11 10:7

11:10 17:9 20:5

24:2,12,19,22

25:7 29:4,5 30:10

31:19 38:21 39:5

40:19,21 41:2

43:18 45:1,3,4

46:6,21 48:11,12

48:15 52:19 54:11

61:9 68:12 76:22

78:22 79:19 82:4

83:3 90:3,6,8

92:14 110:16

112:18 133:4

135:21 136:1,12

136:15 137:2,21

138:4,5 139:21

141:9 142:5,16

143:8,16 144:8

145:3,4,17 146:6

146:10 147:2

149:14 150:16,19

151:4,7,15 152:13

152:17 153:2

154:8,13 155:10

157:14 158:17,19

162:22 163:1,3,13

165:13 167:8

168:13 171:11,15

171:16,22 172:5

173:11 175:1

181:11,19 182:2,5

183:17 187:16,18

188:10,15 190:6,8

193:15 194:10

195:22 200:8,18

200:20 201:12

203:19 204:9,14

205:17 206:18

209:11,13 211:2,6

211:8,10,11

effort 13:8 36:14

126:12 199:10

239:17

efforts 13:12 16:20

23:16 30:21 31:14

34:18

eggs 66:6

eight 52:3 107:13

144:11 154:2

either 50:6 72:14

75:11 80:6,18

90:8,20 92:4

109:11 135:20

156:5 177:17

219:12 225:3

236:14

elaborate 178:17

elegant 81:15

elevated 47:5 48:3

96:3 116:20 225:2

elevation 86:13

elicit 204:18 210:14

Elizabeth 31:14

else's 119:17

elucidate 34:4

embarrassed 99:3

EMBASE 49:22

emerging 21:18

26:17

emphasis 11:19

16:10 36:1

employee 8:10

encourage 198:16

ended 19:2 232:6

endocrine 45:13

54:21 66:14 68:3

69:4 85:7 113:20

114:6 115:4,7

117:12 129:3,10

130:17 137:2

138:17 139:9

145:20 146:12

167:3

endocrine-active

10:8 138:20

endocrine-toxico...

11:4

endocrinologically

55:9

endocrinology

10:12

endpoint 195:13

196:1,19 217:12

endpoints 76:4

139:10 154:16

155:9,9 156:8

159:11 193:6

195:8

energy 9:18

enhanced 153:12

158:14

enhancement

135:4 165:1 166:2

166:9

enlarge 98:20

enlargement 99:10

ensuing 47:2

ensure 15:11 16:14

17:10,11 18:17

19:11 20:2,7,20

21:21 22:11 25:2

29:19 33:19

258:11

ensuring 15:5

16:12 20:17 26:11

28:14 36:19

entire 48:7

entirely 218:20

environment 16:15

17:12 20:10 52:20

67:5 115:11

117:12 129:19

130:17,19 131:11

environmental 1:1

8:16 10:10 11:1,7

29:5 31:19 71:5

148:8 171:6

environmentally

173:20

enzyme 72:15,16

74:7 75:9

enzymes 74:21

93:14

EPA 1:1 5:19 8:11

12:6,18 111:21

125:18 127:14

139:2 215:16

260:12

EPA's 256:2 261:5

EPA-HQ-OPP-2...

1:10

ephemeral 154:10

epi 45:21 200:17

207:4,6 212:2

epidemiological

27:14 183:21

epidemiology

22:20 23:2,8,11

23:13 24:21 25:8

25:22 40:15 41:3

46:9,11 50:11,13

211:20 212:3

equal 246:18

equimolar 86:4,18
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err 229:3

error 176:17

233:19,20 235:11

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errors 187:17

especially 31:3

109:1 117:7 186:8

189:14 194:17

essence 213:19

essentially 53:17

61:7 129:6,7

135:1 157:11

237:11 257:14

establish 34:10

208:8 210:6

established 207:20

establishing 208:7

estimate 229:7

230:10 234:14

241:2 253:3,9,21

254:13,18 257:2

estimates 176:11

176:16,22 180:22

229:6 233:19

236:4 240:15

241:11,17 242:6

256:5

estimating 228:20

230:7 240:7

estimation 127:4

estradiol 66:8,12

67:17 68:2,14

71:19,21 72:5

75:1 77:3,7 79:22

116:3,21 130:7

estrogen 47:3,5,6

48:3 55:13 56:22

60:4 67:11 72:21

73:20 76:17,19

81:4 100:22 130:5

130:7 209:12

estrogens 72:9,17

73:6 74:17 76:2

77:1 80:15 101:22

estrogen-primed

90:9

estrone 72:5 75:11

77:4,7 80:3

estrous 54:16 69:16

118:7 130:14

209:11

estrus 66:21 87:7

115:22 116:9

117:11

et 151:17

ethanol 159:2

ethics 5:1,4

European 17:22

evaluate 45:14

49:11 59:9 200:22

evaluated 45:16

141:4 188:4 189:9

230:13

evaluating 3:19

51:11,13 53:6

166:11 198:9

217:5 219:6

evaluation 26:10

40:18 44:9 45:4

45:20 46:6,7

138:16 187:21

209:6

evaluations 24:10

51:19 127:5

Evans 211:12

Evanston 9:22

evening 12:7 55:21

event 54:21,21

55:20 70:16

events 34:11,13

40:16 46:20 67:12

78:12 92:17 94:2

131:8 208:2 213:2

225:9 242:21

243:5,10

eventually 60:11

73:20 91:21

109:16,18 116:1

129:21

everybody 30:14

evidence 38:12

40:10 74:3 80:16

132:22 160:9,19

175:7 177:16

183:21 184:19

186:4 207:5

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Ewing 105:6

exact 59:20 246:3

exactly 36:15,21

78:11 92:3 156:4

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examination

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examinations

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examine 172:22

189:2

examined 172:4

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example 21:1 23:7

36:13 116:19

122:13 167:7

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examples 41:15

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exams 241:19

exceed 259:14

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exceeding 20:21

exceeds 259:6,17

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excellent 125:4

158:22

exception 70:18

exciting 35:5

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excluded 50:5 53:5

exclusively 41:5

exist 213:19 244:2

existed 71:1

existing 49:11

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expanded 201:6

expect 34:6 35:9

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explain 93:19

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52:22 58:11 72:7

75:22 90:5 93:1

106:9 137:4

148:22 152:14

155:3 164:12

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189:15 192:8

201:16 203:15

204:15 205:9

206:12,15 208:20

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222:8,11 224:9

225:21 226:3

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231:17 232:10,14

233:8,9,18 234:10

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federal 1:3 2:22 4:6

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187:1 209:12,16

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136:18 140:8

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Fenner 8:8 132:7

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8:8 30:12 132:9

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fertility 9:14

fetal 10:1

fetuses 48:18

fewer 229:16

field 241:19

fields 26:17

FIFRA 1:4,19 4:4

4:16 6:10 7:13

figure 59:11 60:1

88:11 91:16

123:21 148:14

154:19 227:5

232:15 234:11

243:16 249:15

figured 113:5

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figures 244:2

Filipov 173:2

177:14 178:3

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180:18 181:4

182:10 194:6

Filipov's 194:14

fill 229:17 232:16

232:17,19 237:9

237:15 242:10

fill-blanks 247:13

filtered 171:4

final 189:20 212:17

finally 64:5 93:20

181:2 183:21

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Finch 67:10

find 57:12 80:11

101:10 123:7,16

151:4 156:13

203:5 219:19

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227:18 233:17

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finding 110:22

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findings 45:18 54:2

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fine 170:11 235:11

finish 13:16

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first 13:3 22:14

23:16 31:12 38:1

45:7,10 58:8

59:14 61:8 87:13

88:5 89:17 90:11

97:5 98:18 111:12

111:13 125:18

127:17 134:17,22

139:1 141:2

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166:18 171:20

193:20 226:13

232:4 234:7

238:10 243:21

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fit 4:21 54:9 96:17

110:13 117:22

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five 5:14 55:7 70:4

82:11,17 89:1,2

103:3 140:7,8

153:8 154:10

174:6 190:18

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flattened 63:10

Florida 9:2 139:7

flow 171:4 243:3,3

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flowing 224:15,16

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229:18

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focusing 23:21

24:19 77:19

194:12 218:14

221:11 244:17

248:14 256:4

folks 243:6,16

249:14 250:3

follicle 56:15

follicles 66:7,7

67:16,21 116:11

116:14 117:15

130:4

follow 198:12

followed 204:13

following 13:10

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food 17:14 191:7

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formulation 36:1

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four-to-five-day

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frameworks 27:11

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frankly 170:6

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frequency 1:8 3:20

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frequent 39:9

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frequently 218:4

223:6 226:5 228:5

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friends 38:15

front 200:20

202:11 204:3

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frustrating 199:8

FSH 56:18

FTPA 229:1 230:1

full 21:19 153:17

229:13

fuller 206:7,8

fully 178:20

full-blown 42:19

function 46:22 66:1

67:3 95:2 133:10

135:14 136:22,22

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FUNGICIDE 1:3

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further 6:6 34:4

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gaps 193:4 195:5

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gavage 58:11 173:6

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genotype 136:17,20

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geological 9:4

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GERALD 1:22

Gerry 10:22

gestation 52:16,17

153:17 173:18

174:12

gestational 192:8

209:5

getting 15:11 22:21

23:9,17 35:15

58:19 85:3 115:2

196:1 236:18

240:17,18

gigantic 121:12

Gillette's 139:6

GILLIOM 2:4

Giusi 173:10 174:9

174:11 184:4

191:15,20

give 6:15 12:15

24:15 26:3 32:2

44:3 50:19 51:6

85:13 106:6 110:1

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154:16 168:19

176:14,17,20

191:5 193:18

199:19 204:21

229:13 238:5

239:7 253:18

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92:5,12 143:18

145:17 146:21

152:3 161:9

173:14 174:11

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215:4

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glad 250:2

gland 45:8,17 47:7

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go 15:1 16:12,15,18

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86:7 88:14 104:21

108:4,6 111:15

116:9 117:5 126:7

130:5 134:9,10

154:19 155:22

166:21 167:21

172:3 190:15

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20:19 21:2 25:3

28:4 30:17 32:2

35:3 36:13,21

37:4,5 39:4,10,14

40:1,20 42:17,19

43:17 44:6,7,11

53:18 69:22 70:2

72:20 73:20 79:2

85:4 89:21 90:7

98:16 102:15

103:5 106:3 116:1

116:5 117:11

121:22 122:4

125:17 134:12,15

138:5 139:1

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151:19 166:4,13

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grasping 187:6

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habituated 160:1,1

half 4:9 7:14 86:5

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Hamilton 1:15,15

hammer 97:7

hand 134:2 228:20

handle 26:3

hands 71:18

hang 121:4

hangs 96:6

happen 13:19

47:20 68:7 113:19

141:15 153:14,15

159:14 170:5

211:22 252:12

happened 68:9

140:16 154:22

169:16 232:3

254:10

happening 48:8,8

64:20 103:8

happens 55:12

65:15 66:10 83:6

115:13 164:15

167:1 226:13

255:7 256:19

hard 31:4 109:2

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harm 229:2 256:8

harmonization

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harvested 161:6

hat 79:3

Hayton 2:6 255:1,5

256:12 257:18

hazard 37:5,6

39:12 42:15 49:12

137:10 159:6

167:13

head 11:1

health 1:6 3:9 6:11

10:11 16:15 17:12

20:9,22 25:12

29:4 30:9 32:16

33:20 38:17 43:18

44:22 45:3 46:6

46:14 142:4

201:20 205:7,10

210:8,13 256:7,16

healthy 136:14

hear 33:21 39:13

40:7 41:5 42:3,16

50:21 239:13

258:5

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137:2 151:13

221:10 228:3

237:5,6

hearing 29:2,6,11

heavily 32:21

heavy 167:4

HED 31:16

Heeringa 1:17,20

7:8,10,11

help 54:1 154:18

176:7 183:5

185:12 186:18,18

189:22 205:12

206:7 229:18

234:19 235:2

246:16 249:15

253:19

helped 13:19 31:10

191:8

helpful 27:10 102:9

249:12

helps 222:22 226:8

241:8 246:16

Herbert 2:11 8:19

herbicide 70:13

heterogeneity

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Hetrick 238:3

Hexachlorobenz...

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Hi 111:20

high 16:8 31:8 64:7

70:7 72:10 79:17

80:4 93:1 97:2

102:22 103:7

106:17,17,19

109:22 110:5

130:5 137:8

175:19,22 176:9

180:2 187:1

188:11 195:14

228:18 229:7

252:1 257:19

higher 59:8 63:4,9

83:16 86:12 88:14

108:4 154:12

158:18 164:5

189:16 220:21

223:5 224:17

249:1 252:13

highest 15:8 89:1

157:3 158:10

233:11 234:10

240:4

Higley 77:6

hinged 201:7

hippocampal 187:1

hippocampus

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histological 117:13

182:17

histopath 99:5

historical 53:18

history 44:7 45:7

hit 25:18 162:20

232:3 234:6 254:9

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hitting 41:8 97:7

hoc 13:5 128:7

hold 125:1 215:10

holding 255:21

holes 193:4 229:18

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Holladay 10:18,18

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163:17 165:3

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HOLLADY 2:7

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homology 56:4

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hope 25:13 63:4

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Horton 2:8 9:19,19

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host 136:5 148:19

Hotel 1:16

hour 58:16,17 59:6

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107:6,6 149:3

260:21

hours 44:15 55:19

55:21 57:16,17

59:6 60:16 71:8

107:2,6,7,8,17

113:16 121:5

hour's 260:11

house 203:8,10

212:9 213:1

HPA 9:9 94:14

132:17 168:11

171:5 177:10

196:20 201:9

203:5 204:12,16

205:6,10,17 214:1

HPA/HPG 205:5

HPG 47:9 56:9

132:20 201:8,12

204:13 205:17

207:21 214:2

HPLC 101:11

huge 168:16

human 1:6 3:10

6:11 16:15 17:8

17:12 20:9,22

32:16 40:20 43:18

44:22 45:3,19

46:6,9,13 47:20

56:6 67:19 74:19

114:2 115:8

129:11 130:1,3,10

130:14,14,21

131:12 132:6

181:5 211:21

246:12 256:7

humans 41:1 47:17

48:6,9,13 68:8

114:3,8 115:7,17

115:18 116:8,9

129:8 131:2

202:12

humoral 146:22

149:15 150:8

152:19

hybridization

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hydrographs 251:3

hydrology 216:8

hydroxylase

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hyperactivity

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hyperbole 218:17

hyperplasia 129:21

hyperstimulation

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hyper-sensitivity

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hypothalamic

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67:3 181:20 182:3

184:7 194:8

hypothalamic-pit...

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hypothalamic-pit...

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hypothalamic-pit...

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hypothalamus

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111:3,22 172:7

173:12 184:7

hypotheses 188:13

hypothesis 66:16

69:18 179:17,18

hypothesized

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hypothesizing

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H295R 74:19 83:21

H295Rs 76:11

I

ID 49:12 159:7

167:13

Idaho 9:9

idea 74:15 80:16

134:21 146:13

168:19 176:20

191:14 195:9

203:8 249:11

253:1

ideas 27:17

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Identification 3:4

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maturation 135:12

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mature 140:19

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maturing 56:15

maximal 182:11

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MCL 259:10

mean 52:5 62:15

85:17 97:6,14

104:1 108:21

109:18 111:11

113:2 115:12,18

118:6 120:4 129:5

129:6 143:6 152:2

155:18 157:9

168:8 176:4 234:4

241:3,17 253:9

254:4 255:8

256:15

means 42:21 62:18

103:22 151:18

214:22 219:22

meant 63:11

measure 57:5

62:21 86:10 110:4

112:10 138:14

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measured 55:4

63:16 86:9 98:8

105:17 107:16

139:10 143:12,20

168:18 172:14,21

173:9 174:15,19

178:22 180:13

184:20 235:14

242:11

measurement

142:4 189:12

247:3 253:5,7

measurements

105:15 174:4

180:5 185:7,9,22

188:17,17 191:7

238:18

measures 95:17,17

178:15

measuring 77:8

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mechanism 104:5

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110:11 119:11

128:21 130:9

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mechanisms

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median 176:3

mediated 140:21

143:22 144:13,17

146:22 150:1

152:19

Medical 10:16

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Medicine 11:17

medium 61:18

162:12

Medline 49:22

meet 204:18
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32:7 35:10 37:20

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meetings 6:19 13:8

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meets 20:8 39:1

Melanie 84:13,21

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member 7:7 8:12

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members 1:19 2:1

3:5 5:1 13:4,4,6

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memory 121:20

Mendez 31:14

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Mendez's 43:12

menopause 130:6,6

menstrual 116:13

mention 34:14

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mentioned 21:6

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79:9 141:16 156:8

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mentors 100:9

merge 38:13

mess 167:10

message 75:19,21

79:15 80:8,18

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messages 35:19

Messner 31:21

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Messner's 236:6

met 5:5

metabolism 11:20

metabolite 84:1

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180:12 209:8

metabolites 3:12

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metals 167:4

metestrus 95:18

methodology 22:11

methods 50:9

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210:4 234:22

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methylation 101:15

metrics 212:13,14

mic 6:6 51:22

107:11

mice 81:16 137:6

143:11,14,15

145:18 148:18,18

149:16 150:9

152:15 153:20,22

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163:9 164:6,16

167:20 184:9

185:19 188:11,11

Michael 31:21 32:5

51:14

Michigan 7:12

microgram 164:8

micrograms

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micrographs 185:4

186:15

micromolar 161:19

micromolars 75:5

75:7

microsomes 80:6

micro-dialysis

172:22 177:7

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mics 199:15

middle 35:16 42:9

217:9

Midwest 37:3

Mike 236:6 239:13

253:14

mile 147:12

miles 226:21

milieu 8:14 66:14

68:3 113:20 114:7

115:4,7 117:4

129:3,10

milligram 65:18

milligrams 48:22

49:3 58:18 63:3

82:12 86:4,5

87:20,20 88:7,8

89:4,19 100:22

103:1,3 120:2

149:8 155:15

156:20 158:4

162:6 190:19

191:2,2 195:19

million 44:17

mind 36:9 71:2

196:15 202:20

203:13

mind's 203:7

mine 199:20

minimal 83:3 177:4

177:6 178:13

Minnesota 10:16

minor 212:8

minute 125:7

201:19

minutes 5:14 16:18

35:13 87:9 88:19

119:6 151:13

160:3 201:16

210:14 215:17

216:7

miserably 118:19

mislead 130:18

missed 73:1 234:10

234:18,19

missing 240:7

252:22

Mississippi 11:18

Missouri 243:7,7

misspeaking

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misspoke 115:11

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mite 166:22

mix 162:9

mixed 157:9,10

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mixture 7:1

mixtures 8:2

mL 65:8

MOA 3:12 53:14

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207:19,19,22

MOA's 208:13

mode 21:10 24:3

26:19 29:10 33:7

34:4 40:15 45:14

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53:6,19 54:9,22

56:9 68:5 70:15

70:21 73:1 78:10

94:8 95:4 135:8

137:18 138:15

200:7 201:5,6

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model 64:4 95:15

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130:15 167:1

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modeling 8:1 40:14

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models 150:12

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modest 75:20

Modic 79:12

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modification 24:18

modifying 189:16

modulated 255:11

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modulation 135:2

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moieties 209:21

molecular 11:2

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mom 140:10 142:1

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moms 140:5

MONDAY 1:12

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monitored 172:16

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226:9 227:7,8

228:13 229:16

230:9 231:2,4,7

231:21 232:21

233:22 235:22

236:9 237:8,9

239:21 240:22

241:9 242:8,21

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monoamine 171:21

172:13 174:21

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monoaminergic

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monoamines 172:6

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month 172:12

231:18 246:3

254:1,8

monthly 234:2,4

254:13

months 26:2 144:8

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Montreal 7:18

moral 207:17

morning 4:11 5:10

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87:8 96:1 106:2,6

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217:1,3 260:13,18

261:4

morphological

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mortality 141:11

141:20 163:10

178:7

mouse 131:13,15

131:15 132:3

152:11 163:22

164:19 165:7,14

165:20 173:11

174:10 187:7

move 7:8 27:4

28:14,18 29:9

30:2 34:7 43:2,17

53:13 134:6

171:10 199:22

210:19 243:15

245:19,21

moved 147:12

260:20

movement 148:12

moving 15:21

28:20 184:3

196:11 198:19

224:17 241:5

255:21

MPTP 183:5

multiple 31:5 41:13

52:13 112:4 226:2

242:1

multi-level 204:9

mysterious 16:1

M.D 2:16

N

n 142:9

nadir 82:20

nagging 71:1

name 4:4 9:11

names 32:3

nanograms 65:8

narrowed 208:9

NAS 35:19 36:15

natal 206:19

national 7:6 10:5

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27:4 38:15 155:5

238:1

natural 62:7 141:4

145:14,18 161:7

161:10,20 162:1,2

162:9,11,13,19

163:1,1,3 249:5

nature 18:5 52:19

223:13 227:20

NCI 25:17,19

nearest 237:5,17

neat 74:20

necessarily 74:8

77:22 78:2 79:7

202:2 240:3,10

necessary 33:19

74:22 258:14

need 16:6 17:5 22:2

31:7 35:14 36:18

37:15 43:3,5,9

49:14 65:5 105:7

137:22 153:9

165:11 198:6

206:11,19 207:1

210:14,18 216:7

218:4 219:4

227:10 230:10

239:19,20 241:9

249:9 256:5 258:7

needed 17:9 65:9

90:13,17 204:18

210:7,10,12 241:1

needing 240:14

needs 35:20 43:2,4

43:7 214:8

negative 145:2

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negatives 229:3

236:16 253:2

negligible 225:4

neighbor 237:6,17

neighbors 223:22

225:15

Neither 182:19

Nelson 31:20 32:4

42:3,6 51:9

neonatal 145:17

neonate 112:17

nerve 85:1

nervous 64:13

67:13 204:11

net 50:1

network 51:15

217:2

networks 224:14

236:8

neural 51:15 217:1

236:8

neuroadrenergic

119:3

neurobehavioral

172:2 174:10,14

187:4 190:4

Neurobiology 9:20

neuroendocrine

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137:21 160:21

182:4 190:7

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197:12 200:19

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neuroendocrinol...

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neurological 3:14

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184:2

neuron 178:7 180:8

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neuronal 174:6

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186:11,20,21

187:2

neurons 62:21

63:18,20 172:20

173:9 175:4

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neuropathology

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neuropeptide

56:11 64:10 94:3

neurotox 199:5

neurotoxicity 51:3

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neurotoxicology

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never 159:21

160:14 259:5

new 7:1,2 15:4

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21:18 22:1,4

31:17 33:4 34:3,9

38:14 40:9,9

42:14 43:6,7

49:10,10,13,15

112:14 132:16

147:13 171:3,14

171:19 194:15

196:21 207:8

217:11 229:21

231:3,10

newest 8:12

nice 42:7 69:14

79:18 111:4

116:22

night 170:21

nigra 172:20 175:4

183:12

nigrostriatal

172:10 173:4

181:17 182:8

194:2

nine 76:21 82:21

107:14,17 114:20

144:6,14

NOAEL 48:21 49:2

52:4 57:12

NOAEL-5 205:19

nocturnal 66:13

NOEL 89:19

139:16

noisy 250:7

non 24:21 50:6

53:3 127:22

172:19 209:14

255:17

non-cancer 3:15

24:2,19 38:21

39:5 48:12,15

207:4

non-detectable

169:20

non-dopaminergic

175:3 180:20

non-menopausal

130:10

non-parametric

128:3,14

non-selectivity

183:15

non-specificity

181:10 194:1

non-subjective

240:7

norepinephrine

172:7 175:1

193:22

normal 64:17

73:22 115:13

136:22,22 148:3

168:22

normally 61:22

65:2,13 106:5
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noted 177:7 188:10

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notice 200:10

noticed 250:6

no-effect 112:10

NTP 138:3 156:19

162:3

number 5:17 12:7

22:17 28:3 31:9

68:10 69:21 71:4

72:13 73:7 74:22

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90:18 100:8

102:20 103:21

106:16 108:19

116:11 118:22

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155:2 158:1,21

169:1 172:19

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178:2 186:11

188:2,3,9 189:8,9

211:4 212:9

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numbers 141:13

162:10 163:13

175:3

numerous 44:21

190:5

Nu-may 2:13 8:15

N.W 1:16

O

objective 33:3 49:9

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objectives 49:7

observation 85:12

171:2

observational

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observations

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observe 30:18

observed 54:11

obviously 27:22

92:3 100:1 115:12

138:17 256:15

OB/GYN 62:10

occasional 121:10

occasions 32:21

occur 62:14 69:6

69:13,19 81:22

166:5 228:19

240:12

occurred 59:5

144:6 156:6

occurring 57:15

61:4 64:1 68:13

occurs 55:17 65:17

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odd 81:12 217:8

offers 243:11

office 7:6 8:11

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30:13 31:21 32:8

44:12 51:9 238:4

Official 2:22 4:6

13:18

offspring 142:21

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164:13 169:5

174:2 203:17

off-labeled 259:18

Oh 117:5 124:4

202:14

Ohio 255:2

oil 173:14

Ojeda 117:18

okay 39:10 42:14

43:16 49:6 53:12

79:3 96:10,16

97:3,13,16,21,21

98:3,11,14 100:12

100:15 102:19

103:14 107:9

111:14 114:13,21

115:17 117:6

119:10 120:20

121:1,9,19 123:10

123:15 129:17

133:22 134:12

136:9 166:16

169:22 171:8,19

175:12 181:2

184:3 187:4 190:9

199:20 213:17

215:13 216:3,6,7

217:4,7 228:12,13

244:18 254:21

old 65:7 121:20

213:12

older 126:11

131:19

once 62:1 70:1

115:21 140:18

147:5 149:11

151:9 164:22

205:14 208:9

230:20 231:8

255:10 259:9

ones 41:16 107:21

122:15,16 162:15

235:6 236:22

251:6

one-tenth 164:8

one-time 8:10

ongoing 26:10

32:12 34:15

259:12

onset 47:13 49:1

65:16 115:21

139:15 202:3

open 15:20 16:2

59:2 163:7 215:21

243:14 255:8

opening 3:3,6

12:22

openness 15:15

OPP 29:18 31:12

opportunity 5:8

112:18 133:4

opposite 16:2

oral 173:6 209:5,10

211:13

orally 82:12

ORD 32:9,12

order 218:4

ordered 6:16

organ 137:13,13

organisms 11:11

organization 27:1

organs 140:17

origin 56:11

original 50:11

234:3

originally 25:6

38:10

ossification 48:17

outcome 52:21

131:1 133:5 148:1

151:11,16 201:20

205:7 206:13

210:8,13,15

outcomes 27:8 39:7

68:11 69:8 70:18

205:10 210:1

outpouring 55:16

outrageously 229:7

ovarian 56:6 64:17

69:12,15 96:18

116:19 117:9,21

131:21

ovariectomized

60:4 61:8 62:12

64:4,6 80:2 90:9

ovaries 67:21 73:16

133:12

ovary 55:14 56:22

61:9,11 67:16,17

90:2 114:2 117:14

overall 14:11 31:13

38:3 76:2 78:9

174:20 175:8

177:4 186:10

overestimate

187:18

overlapping 192:2

overlook 229:11

overt 145:5

overview 44:3

163:18 219:7

overwhelm 104:4

over-stimulation

93:12

ovulate 58:2 66:4

116:12,19

ovulating 91:4,5

ovulation 47:2

55:21 56:1 65:5

65:11 66:1,6

90:21

ovulators 56:4

O'Byrne 2:12 9:11

9:11 118:15,16,21

119:10,13,22

120:5,9,13

o'clock 82:21 119:7

216:17

P

pace 115:20 199:22

page 3:2 122:15

245:9 246:7

paint 215:3

pair 211:14

paired 248:21

panel 1:4,15 3:5

4:5,14,16,22 6:10

6:20,22 7:4,8 11:9

11:14,21 12:8,12

12:15 13:3,5,5

15:2 22:7,15,19

22:22 23:15,21

24:15 30:16,20

31:4 38:3 43:13

46:4,8 47:15,16

48:10 60:14 95:10

126:2 134:18

209:17 215:19

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260:16

panelists 7:1

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39:15 40:6 70:3

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papers 78:18

101:13 111:4

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parameters 174:14

189:13

parasites 148:2

parent 84:12

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parental 52:15

Park 139:3

Parkinson's 181:6

181:14,15 182:14

182:19,22 183:1,4

183:10,19 184:1

194:13,15 204:6

pars 183:13

part 5:6 14:11

15:10 21:13 23:8

42:9 44:5 46:11

50:12 54:3,10

56:17 63:17,18

68:17 72:22 94:8

134:6 153:19

166:11,13 172:4

192:1 222:6

245:13 246:21

247:18 249:3

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PARTICIPANT

99:12 108:7

participate 15:17

participating

145:10

participation 14:5

14:14,18 15:16

16:8

particular 20:16

57:7 83:22 109:11

131:1 173:3 181:4

181:6 203:7

230:17 231:19

235:9 244:4,5

248:5

particularly 30:20

31:2 41:1 42:10

42:15 142:16

151:2 154:9 163:4

170:3 196:21

225:18 233:8

240:13 251:13

252:8

partners 18:8

parts 53:17 56:8

217:21 220:19,22

pass 199:13 223:12

passed 230:1

pasted 161:15

path 154:19

pathway 34:11

41:6 77:12 79:6

93:18 133:1

181:17 194:3

pathways 26:20

27:7 69:9 78:5

198:5 215:2

patients 171:1

pattern 86:21

115:22 225:7,7

230:4 236:1,9,9

patterns 130:20

131:17 219:19,21

223:16,18 224:2,3

227:12,22 242:2,4

pause 20:6

PBPK 8:1 209:20

PCOS 96:17

118:12

PDF 161:15

peak 59:5,8 60:12

60:17 65:8,16

66:13 116:22

225:16 230:7

232:4,5 234:7,8

235:15 254:10,16

peaks 41:12 55:19

226:2 231:17

peer 13:6,13 14:9

14:11 15:10 23:16

24:14,16 26:9

44:7 45:7 50:15

PENELOPE 2:4

Penny 8:8 30:11

people 7:2 15:20

31:10 39:17,18

65:9 91:18 117:16

121:2 125:7 138:5

147:18 168:14

215:21 238:3

246:15 247:7

258:9 261:2

people's 32:3

peptide 61:21

percent 141:11

155:14 182:16

percentages 157:1

percentiles 241:3

241:11

perfect 139:11

167:7

perfectly 62:6 64:9

155:16

perform 135:10

performance 51:13

performed 181:22

191:17

perifusion 61:16

perinatal 40:19

103:4 113:12

206:19

period 60:10 61:19

70:7 103:20

112:21 113:12

119:5 122:7 130:6

133:12 144:19

149:4 151:2 154:4

158:6 217:18

222:9,11 226:16

228:11 254:6

periodic 21:3

periodically 18:16

periods 69:11

225:8

peripubertal 103:5

113:8,10

peripubertally

71:22

permanent 7:7,13

11:9,14,20 13:4

31:4 46:4 165:16

165:19

persist 87:16

144:14

persisted 86:11

102:1

persistent 47:3

66:20 117:15

118:7 141:9 179:5

person 223:20

personal 171:2

personally 96:5

perspective 30:1

perspectives 20:4

pertain 171:21

203:4

perturb 106:2

136:2

perturbation 46:17

47:10 136:3 201:8

perturbations

26:21 27:8

pesticide 8:6,11,13

8:17,17 11:18

12:22 15:7 16:13

17:1,11 19:20

20:5 21:2,5 28:11

29:4 30:10,13

70:13 220:1,5

221:14 227:13,21

241:18,19 242:20

pesticides 9:5

11:10 16:11 18:17

18:20 19:2,6,11

20:2 138:19

218:12,16,19

219:19 238:9

257:16

phagocytes 145:8,9

phagocytic 145:7

145:13 157:18

phagocytosis 141:2

pharmacokinetics

8:7

pharmacological

139:19 146:7

Pharmacology

10:16

pharmaco-dyna...

212:19

phase 59:10 136:13

153:5

PhD 100:9

phenomenon 166:6

phenotype 178:8

phosphodiesterase

78:16

photo 185:3 186:14

photomicrographs

177:17

photo-micrograp...

186:1

physiologist 9:17

Physiology 9:21

Ph.D 1:17,17,20,21

1:21,22,22,23 2:2

2:2,3,4,4,5,6,7,8,9

2:11,12,13,14,15

2:16,17

pick 142:7 199:22

260:18

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restraint 104:2

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result 48:19 102:22

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123:4 124:1,6,15

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131:9 135:21

137:17 150:5

154:21 158:11

161:12,18 162:5

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170:10 192:6

193:14 194:16

195:16 197:21

199:21 201:4

204:20 214:6

215:5,12 245:15

251:22 252:4

253:6,7

rising 55:12

risk 8:1,17,18 18:9

21:22 22:3,13

23:3,5 25:4 26:18

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28:22 29:16 32:16

32:20,22 35:21,21

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36:17 37:1 41:18

42:20 43:7 44:8

46:10,14,15 48:13

49:15 135:7

150:11 184:12

196:16 206:21

210:3 245:11

Riverside 11:8

road 39:1 41:8

147:13

ROBERT 2:4

robust 69:5 136:18

rodent 56:5 73:11

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117:8,22 167:15

246:9

RODENTICIDE

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Rodriguez 172:4

175:6,17 178:19

181:9,19 183:14

190:13 192:15

193:19 194:8

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Rodriguez's 177:7

179:22

role 73:11 198:2

roles 197:22

roll 206:10

rolling 41:17

244:20 245:10,22

259:14 260:4

roof 213:9,11,18,19

214:20 215:10

room 216:9

Rooney 139:4

169:17

root-cause 85:11

roughly 232:7

round 19:8

route 241:18 257:7

257:8

routinely 230:3

row 42:10 58:22

259:13

Rowe 151:17

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Rowe's 166:19

rubber 39:1 41:8

Ruby 2:13 8:15

ruled 208:13

ruling 61:10

260:10

running 199:14

215:17 226:2

run-off 217:20

241:19

rupture 56:16

rushing 131:6

S

sacrificed 174:3

safe 17:15 28:13

29:14 36:19 37:2

222:6 258:13,15

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safety 16:9,14 20:9

207:10 256:13

sample 175:13,19

178:12 184:14

199:3 218:4 221:3

226:6 228:6

229:12 230:6

234:5 237:10

247:8 248:13

249:9 253:20

254:8 255:9

sampled 217:19

221:20 234:2

samples 191:6

224:6 227:16

232:2 247:4 250:9

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25:2 51:11,13

176:13 207:11,15

216:22 217:6,8,17

219:9 220:7 222:9

222:16 228:7

229:16 230:13,18

232:3 233:5,10,21

234:4,12 235:9,17

237:13 247:17,19

248:2 250:14

254:6,9 259:9,11

260:8

San 9:16

sand 43:2

Sanderson 74:14

74:18 75:3,18

78:14 83:20

Santa 8:21

SAP 1:4,19 6:21

7:8,13 14:14

30:15,16 31:5

32:20 33:11 34:8

37:19 45:10,11,16

47:14 70:12

134:18 202:10

211:19 217:9

221:9 223:12

230:8 242:7

SAPs 44:21

save 95:13

saw 61:9 62:1

63:20 64:3 65:18

71:9 75:10 83:18

90:7,7 92:13

107:18 123:6,10

144:9 146:11

152:18 154:8

158:18 166:19

220:13 247:16

saying 70:6 75:5

130:2 154:8 193:5

says 79:20 96:13

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scale 137:1 254:19

scenarios 28:2

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schedule 12:13

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Schlenk 1:23 11:5

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School 10:17

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20:7 21:4,18,22

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23:20 26:12 28:21

29:15,21 30:2

31:8 32:18,19,22

33:4 34:2 35:6,18

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198:15 217:11

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Sciences 10:11 11:8

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scientific 1:4 4:5,16

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19:12 22:9 31:1

scope 36:6 49:19

74:9

screen 241:8

screening 69:4

scrutiny 215:11

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searched 49:22

season 217:20

226:12

seasonal 224:21

second 6:19 12:9

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sensation 47:2

sense 74:8 190:18

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sent 161:6 247:7

sentence 160:8

sentinel 148:3

separate 109:15

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September 24:16

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sequentially 215:2

series 6:19 46:19

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serotonin 172:6

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serum 55:14 66:8

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serum-estrone

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serves 223:20

serving 4:5 6:4

session 1:17,21 6:8

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163:15 169:15

170:12 171:8

190:9 191:13

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197:8 199:1,15

212:6 213:6

215:13 216:3,6,14

243:18 246:22

251:1,20 252:19

255:1 257:20

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127:10 128:12,13

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seven 21:8 22:5

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201:10 203:11

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214:19,20 215:11

232:17 246:14

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sex 187:22

sexual 73:11

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SF-1 77:20,20 78:1

shape 252:16

shapes 225:22

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shift 171:3

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shine 104:3

shingles 214:18,19

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222:18 224:3,3

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86:17 88:4,5 97:5

100:10 131:17,20

142:13 170:2

186:10 226:13

231:16 235:5

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243:22 251:6,8,9

showing 54:8 58:5

80:2 104:7 111:4

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shown 56:19 73:18

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slight 126:17

slow 109:13

slowing 121:17

small 65:5 137:6

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smear 55:5

Smialowicz 164:7

smooth 168:21

snapshot 39:16,20

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Society 7:6

sole 79:8

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solution 173:15,16

somatic 143:3

somatostatin 184:6

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somebody 32:1

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soon 103:17 231:9

sophisticated 35:5

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sorry 31:22 62:2

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sort 21:3 26:5 30:1

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247:5 248:8

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sorts 141:3 144:21

sought 57:11

sound 16:7 26:12

source 17:14 28:8

28:15 185:19

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249:2 256:3,4,9

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sources 20:19

21:21 25:3 28:16

81:5

south 226:21

space 237:9

spatial 219:18,21

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spatially 42:3

speak 12:11 124:20

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speakers 33:22

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speculate 65:12

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Sprague 45:9 58:7

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spring 25:14 201:3

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square 76:5

staff 4:5 6:21 13:18

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supplementing

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wet 208:17

we'll 25:20 26:2,8

26:14 28:16 35:17

41:15 42:15 43:6

43:8,16 45:2,2

76:3 125:2,9

208:10 216:18

248:20 260:3

261:1

we're 6:17 12:4,10

14:12 15:11 16:4

16:21 18:13 19:10

22:8,11 23:17

25:18 26:7 27:16

28:4 29:18,22

31:2 35:3,15,16

36:13,21 37:4,5

37:17 38:4 39:10

39:14 40:19 42:12

42:17,19 58:18

60:16 74:6 78:11

83:9 86:22 92:2

102:16 115:19,19

119:14 125:17

129:18 130:2

134:6 165:9 166:4

166:6,14 171:9

196:12,16 197:21

199:12,14 202:13

203:21 207:4,16

208:1,6 215:5,7

215:15,17 216:1

216:20 217:10

218:13,19 220:5

223:1,4,9,14

224:21 225:12

226:6 227:8

228:12,16 229:20

231:3,4,6,8 232:5

232:9,10,12,12

234:3,5,7,21

239:14 240:14

243:10 244:8,8,10

245:9 246:6

248:14 250:18

251:3 253:17

256:3 258:21

260:12,18

we've 5:15 6:21

10:20 31:4 50:15

54:4,11 56:18

59:7,20 71:4

81:10 84:21 95:5

95:22 96:5 98:7

101:9 118:22

128:9 134:5 137:2

152:11 153:7,11

153:12,13 160:22

163:18 165:3

199:5 200:15

204:1 206:17

208:2,9 218:8

219:8 222:22

223:2,11 228:3

230:10 232:15,16

234:16 237:3,20

240:19 241:15,17

241:22 242:4,12

249:17 252:6

253:20

whatsoever 146:6

157:15

wheel 229:21

white 126:3,6 129:1

249:21

whooping 120:3

wide 17:9 50:1

136:20,21 200:7

widely 44:16

widespread 220:16

WILLIAM 2:6

Williams 2:16 10:9

10:9 113:13,14

114:13,19,22

116:17 125:19

128:18,19 129:9

129:15 130:8

window 258:7

260:7

winning 215:11

wisdom 249:15

wish 168:17 169:11

169:12,13

wishes 12:11

Wistar 209:16

Wolf 238:4

women 116:18

128:20

wonder 166:12

wondering 53:5

96:17 166:2

215:19 245:3

wonders 192:2

words 106:1 237:9

249:15

work 13:20,22

22:18 24:11 28:4

31:10 36:9 39:17

39:19 50:11 57:10

59:7 65:9 67:9

68:10 117:17

132:13 134:14

136:9 146:4

151:21 160:17

161:15 163:22

168:4 230:15

237:22 243:1

251:15

worked 4:22 9:4

30:12 31:11,11

66:16 71:4

worker 17:13

workers 46:1

working 10:6 23:16

31:4 35:17 62:10

64:12 70:13 71:6

80:17 84:14 86:22

132:10 160:12

207:5 208:6 223:1

works 33:7 60:14

118:19 119:2

163:19

world 39:18

worry 153:11

226:10

worse 150:15

worship 84:5

worth 198:9 260:11

wouldn't 86:7

129:11 130:17

wrap 26:6 51:18

200:2

wrestle 218:11

wrestled 249:17

wrestling 234:17

234:21

writing 174:15

187:6

wrong 127:6

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year 6:20 21:17

28:17 31:3 44:18

45:5 82:6 170:15

212:1 217:21

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227:1,1,17 238:21

238:21,22 239:1,1

239:1,2,3 250:6,6

250:10,13,13

259:17,18
202-234-4433

Neal R. Gross & Co., Inc.

Page 299

years 8:12 15:3

21:8 22:6 44:21

54:5 105:7 153:9

201:11 203:11

226:22 229:13

231:7 234:17

239:8 242:1

246:14 259:3,4,5

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year-long 33:2

year-to-year

226:12,16

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young 2:17 8:22,22

58:1 118:8 121:22

122:2,10,12,15,22

123:4,6,10,15,19

123:21 124:3,5,8

124:12,18 125:4

125:22 126:8,9

136:14 252:20,21

254:17,21

younger 113:3

Young's 125:18

Y-axis 102:1

Z

Zerkin 105:6

zone 241:18

zoom 220:19 223:3

1

1 164:2

1st 231:22

1:00 1:15

1:09 4:2

10 48:21 86:3 87:20

88:8 89:3 153:8

161:19 191:2

238:19

100 31:16 103:3

200:6

1001 1:16

12 3:6 86:5 87:19

88:7 89:19 144:14

12.5 49:2

134 3:13

14 140:12 158:11

169:21 173:6,18

174:12

14th 1:16

15 87:8 88:19 119:6

125:7 201:19

15-minute 85:17

16 58:16

1600 107:8

171 3:14

18 58:16

1800 57:15 60:15

60:19 107:8

1950s 44:20

1965 189:20

1984 19:7

199 3:15

1997 120:17 123:16

2

2 164:3 165:7

2,500 65:8

20 122:15

200 50:5 58:17 63:3

63:4 65:10 82:12

90:13 91:2 96:8

100:22 102:22

121:9

200,000 116:15

2000 29:8 45:16

47:14 59:5 61:2

107:8,17,17

202:10

2000s 29:11

2003 19:15 21:7

22:1 32:16 41:17

44:8 45:20 46:13

46:15,19 48:13

50:3 53:20 70:11

171:15,19 201:7

202:21 203:9

217:13,13 222:4

245:11 258:2,19

2006 19:5

2006/2008 19:3

2007 19:8 81:10

123:13 242:7

2008 19:6

2009 35:18 46:3

99:17

2010 1:13 46:7

206:1,2

2011 25:19,20 26:1

38:19 211:19

212:4

21 52:17 60:15

71:22 86:13

158:14 173:18

174:13

21st 27:6

21-day 93:1

217 3:19

23 122:16,17 149:7

24 149:3

24-hour 247:22

25 124:1 154:9

155:15 158:3

164:21

250 162:6

26 1:13 122:16

261 3:22

28 62:12 149:10

159:22

28-day 120:18

3

3:15 125:8,12

3:30 125:9

3:33 125:13

30 3:7 137:8 164:21

165:1

300 50:4 58:19 91:2

34 3:8

35 155:14

4

4 3:3

4,300 157:3

43 3:10

433 157:3

45 215:17

5

5th 258:12

5:13 216:12

5:16 216:13

50 63:3,4,6 65:18

89:2,2 90:15 96:9

100:22 102:22

103:3 120:2 121:7

121:15 182:16

226:21

500 156:19

53 3:12

6

6 3:4 153:20 156:22

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183:5

6.25 49:2

6:02 260:10

6:05 261:8

60 174:3 238:19

65 174:3

7

7 164:19

70 44:17 48:22

75 86:18 103:3

8

8:30 261:5

9

9:00 107:4

90 41:16 217:18

222:8,11 228:11

228:12 244:19

245:1,5,10,14,19

245:22 246:8,19

259:14 260:4

90's 165:18