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# TOXICOLOGICAL REVIEW

OF

ACRYLONITRILE

(CAS No. 107-13-1)



# In Support of Summary Information on the Integrated Risk Information System (IRIS)

January, 2010

NOTICE

This document is an Interagency Science Consultation draft . This information is distributed solely for the purpose of pre-dissemination peer re view under applicable information quality guidelines. It has not been formally disseminated by EPA. It does not represent and should not be construed to represent any Agency determination or policy. It is being circulated for review of its technical accuracy and science policy implic ations.

U.S. Environmental Protection Agency

Washington, DC

### ii DRAFT - DO NOT CITE OR QUOTE DISCLAIMER

This document is a preliminary draft for review pu rposes only. This information is distributed solely for the purpose of pre-dissemina tion peer review under applicable information quality guidelines. It has not been formally disse minated by EPA. It does not represent and should not be construed to represent any Agency det ermination or policy. Mention of trade names or commercial products does not constitute en dorsement or recommendation for use.

### iii DRAFT - DO NOT CITE OR QUOTE CONTENTS —TOXICOLOGICAL REVIEW OF ACRYLONITRILE (CAS No. 107-13-1)

LIST OF TABLES.....................................

................................................... ........................... vii

LIST OF FIGURES ....................................

................................................... ......................... xvi

LIST OF ABBREVIATIONS AND ACRONYMS ................. ............................................ xviii

FOREWORD ...........................................

................................................... ........................... xxii

AUTHORS, CONTRIBUTORS, AND REVIEWERS ............... ......................................... xxiii

1. INTRODUCTION ...................................

................................................... ...........................1

2. CHEMICAL AND PHYSICAL INFORMATION .............. .................................................3

3. TOXICOKINETICS .................................

................................................... ..........................5 3.1. ABSORPTION ...................................

................................................... .............................5 3.1.1. Studies in Humans ..........................

................................................... ........................5 3.1.2. Studies in Animals .........................

................................................... .........................5 3.2. DISTRIBUTION .................................

................................................... ............................7 3.3. METABOLISM...................................

................................................... ..........................14 3.3.1. Oxidation of AN to CEO .....................

................................................... .................15 3.3.2. Interaction of AN with GSH .................

................................................... ................23 3.3.3. Covalent Binding of AN and Its Metabolites to Subcellular Macromolecules........28 3.4. ELIMINATION..................................

................................................... ...........................34 3.4.1. Studies in Humans ..........................

................................................... ......................34 3.4.2. Studies in Animals .........................

................................................... .......................34 3.4.2.1. Exhalation ...............................

................................................... ..................... 34 3.4.2.2. Fecal Excretion ..........................

................................................... .................. 35 3.4.2.3. Urinary Excretion........................

................................................... ................. 35 3.5. PHYSIOLOGICALLY BASED TOXICOKINETIC MODELS ... ..................................40

4. HAZARD IDENTIFICATION..........................

................................................... ...............53 4.1. STUDIES IN HUMANS—EPIDEMIOLOGY AND CASE REPOR TS.........................53 4.1.1. Oral Exposure ..............................

................................................... .........................53 4.1.2. Inhalation Exposure ........................

................................................... ......................53 4.1.2.1. Acute Exposure...........................

................................................... ................. 53 4.1.2.2. Chronic Exposure.........................

................................................... ................ 55 4.1.3. Dermal Exposure ............................

................................................... ....................115 4.1.3.1. Acute Exposure...........................

................................................... ............... 115 4.1.3.2. Chronic Exposure.........................

................................................... .............. 117 4.1.4. Ocular Exposure............................

................................................... ......................117 4.2. SUBCHRONIC AND CHRONIC STUDIES AND CANCER BIO ASSAYS IN ANIMALS—ORAL AND INHALATION........................ ..........................................120 4.2.1. Oral Exposure ..............................

................................................... .......................121 4.2.1.1. Subchronic Studies.......................

................................................... .............. 121 4.2.1.2. Chronic Studies..........................

................................................... ................ 127

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4.2.2. Inhalation Exposure ........................

................................................... ....................156 4.2.2.1. Subchronic Studies.......................

................................................... .............. 156 4.2.2.2. Chronic Studies..........................

................................................... ................ 157 4.3. REPRODUCTIVE/DEVELOPMENTAL STUDIES—ORAL AND I NHALATION..164 4.3.1. Studies in Humans ..........................

................................................... ....................164 4.3.2. Studies in Animals .........................

................................................... .....................167 4.3.2.1. Oral Studies.............................

................................................... ................... 167 4.3.2.2. Inhalation Exposure ......................

................................................... ............. 175 4.3.2.3. Intraperitoneal Administration...........

................................................... ........ 177 4.3.3. In Vitro Studies ...........................

................................................... ........................179 4.4. OTHER DURATION- OR ENDPOINT-SPECIFIC STUDIES . ...................................180 4.4.1. Acute Toxicity Data........................

................................................... ....................180 4.4.1.1. Effects of AN on the GI Tract............

................................................... ........ 184 4.4.1.2. Effects of AN on the Kidney..............

................................................... ........ 186 4.4.1.3. Effects of AN on the Adrenal Gland.......

................................................... ... 186 4.4.1.4. Neurotoxic Effects of AN .................

................................................... ......... 187 4.4.1.5. Effects on Hearing .......................

................................................... .............. 188 4.4.2. Immunotoxicity of AN.......................

................................................... .................191 4.5. MECHANISTIC DATA AND OTHER STUDIES IN SUPPORT OF THE MODE OF ACTION .............................................

................................................... .......................196 4.5.1. Mode-of-Action Studies.....................

................................................... .................196 4.5.1.1. Noncancer Endpoints ......................

................................................... ........... 196 4.5.1.2. Cancer Effects...........................

................................................... ................. 210 4.5.2. Genotoxicity Studies.......................

................................................... ....................223 4.5.2.1. Studies in Humans ........................

................................................... ............. 223 4.5.2.2. In Vivo Tests in Mammals.................

................................................... ........ 227 4.5.2.3. Short-term Tests: Bacteria, Fungi, Droso phila, Others................................ 230 4.5.2.4. Mammalian Cell Short-term Tests..........

................................................... ... 235 4.6. SYNTHESIS AND EVALUATION OF MAJOR NONCANCER E FFECTS AND MODE OF ACTION—ORAL AND INHALATION ................. .................................255 4.6.1. Oral .......................................

................................................... ..............................255 4.6.2. Inhalation .................................

................................................... ...........................259 4.6.3. Mode-of-Action Information .................

................................................... .............263 4.6.3.1. GI Effects ...............................

................................................... .................... 263 4.6.3.2. Neurotoxicity ............................

................................................... ................. 264 4.6.3.3. Reproductive/Developmental Effects .......

................................................... . 266 4.6.3.4. Hematological Effects....................

................................................... ............ 267 4.6.3.5. Immunotoxicity...........................

................................................... ............... 268 4.6.3.6. Covalent Binding to Sulfhydryl Groups ....

................................................... 268 4.7. EVALUATION OF CARCINOGENICITY—SYNTHESIS OF HU MAN, ANIMAL, AND OTHER SUPPORTING EVIDENCE, CONCLUSIONS ABOUT HU MAN CARCINOGENICITY, AND LIKELY MODE OF ACTION......... ............................269 4.7.1. Summary of Overall Weight of Evidence......

................................................... .....269 4.7.2. Synthesis of Human, Animal, and Other Suppo rting Evidence.............................269 4.7.3. Mode-of-Action Information .................

................................................... .............272 4.7.3.1. Hypothesized Mode of Action: Direct Muta genic Mode-of-Action............ 273 4.7.3.2. Experimental Support for the Hypothesized Mode of Action ...................... 273 4.7.3.3. Other Possible Modes of Action ...........

................................................... ..... 284 4.7.3.4. Possible Modes of Action for Forestomach Tumors .................................... 292

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4.7.3.5. Possible Modes of Action for Hepatomas... .................................................. 2 93 4.7.3.6. Possible Modes of Action for Tumors of In testines, Tongue, Zymbal Gland, and Harderian Gland................................

................................................... .. 294 4.7.3.7. Possible Modes of Action for Lung Cancer. ................................................. 29 4 4.8. SUSCEPTIBLE POPULATIONS AND LIFE STAGES...... .........................................294 4.8.1. Possible Childhood Susceptibility ..........

................................................... ............294 4.8.2. Possible Geriatric Susceptibility..........

................................................... ...............297 4.8.3. Possible Gender Differences................

................................................... ...............298 4.8.4. Genetic Polymorphisms ......................

................................................... ................301 4.8.4.1. CYP450...................................

................................................... ................... 301 4.8.4.2. Glutathione S-transferases ...............

................................................... .......... 302 4.8.4.3. EH .......................................

................................................... ....................... 302

5. DOSE-RESPONSE ASSESSMENTS......................

................................................... ......304 5.1. ORAL REFERENCE DOSE (RfD) ....................

................................................... ........304 5.1.1. Choice of Principal Study and Critical Effe ct................................................. .......304 5.1.2. Methods of Analysis—Including Use of PBTK M odeling....................................308 5.1.2.1. PBTK Modeling............................

................................................... ............. 308 5.1.2.2. BMD Modeling.............................

................................................... ............. 309 5.1.3. RfD Derivation—Including Application of Unc ertainty Factors (UFs) ................314 5.1.4. Oral Data Array for Noncancer Endpoints ....

................................................... .....315 5.1.5. Previous RfD Assessment....................

................................................... ...............318 5.2. INHALATION RfC...............................

................................................... ......................318 5.2.1. Choice of Principal Study and Critical Effe ct................................................. .......318 5.2.2. Methods of Analysis ........................

................................................... ...................321 5.2.3. RfC Derivation—Including Application of UFs

................................................... .322 5.2.4. Inhalation Data Array for Noncancer Endpoin ts ................................................. ..323 5.2.5. Previous Inhalation Assessment.............

................................................... .............325 5.3. UNCERTAINTIES IN THE ORAL RfD AND INHALATION RfC............................325 5.4. CANCER ASSESSMENT ............................

................................................... ..............327 5.4.1. Choice of Study/Data—with Rationale and Jus tification ......................................327 5.4.2. Dose-Response Data .........................

................................................... ..................328 5.4.2.1. Human Occupational Data..................

................................................... ....... 328 5.4.2.2. Rat Oral Data ............................

................................................... ................. 329 5.4.2.3. Rat Inhalation Data ......................

................................................... .............. 333 5.4.3. Dose-Response Modeling .....................

................................................... ..............334 5.4.3.1. Human Occupational Data..................

................................................... ....... 334 5.4.3.2. Rat Oral Data ............................

................................................... ................. 335 5.4.3.3. Rat Inhalation Data ......................

................................................... .............. 342 5.4.4. Cancer Risk Values.........................

................................................... ....................345 5.4.4.1. Oral CSFs................................

................................................... ................... 345 5.4.4.2. Inhalation Unit Risk.....................

................................................... .............. 347 5.4.4.3. Quantitative Analysis of Early Life Expos ure Scenarios.............................. 349 5.4.5. Uncertainties in Cancer Risk Values .........

................................................... ..........359 5.4.5.1. Oral Cancer Assessment ...................

................................................... ......... 359 5.4.5.2. Inhalation Cancer Assessment .............

................................................... ...... 365

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6. MAJOR CONCLUSIONS IN THE CHARACTERIZATION OF HA ZARD AND DOSE RESPONSE...........................................

................................................... ........................369 6.1. HUMAN HAZARD POTENTIAL .......................

................................................... ......369 6.2. DOSE-RESPONSE ................................

................................................... .....................371 6.2.1. Oral RfD...................................

................................................... ...........................371 6.2.2. Inhalation RfC.............................

................................................... ........................372 6.2.3. Oral CSF ...................................

................................................... ..........................374 6.2.4. Cancer Inhalation Unit Risk................

................................................... ................375

7. REFERENCES .....................................

................................................... ..........................376

APPENDIX A. SUMMARY OF EXTERNAL PEER REVIEW AND PU BLIC COMMENTS AND DISPOSITION...........................

................................................... . A-1

APPENDIX B. BENCHMARK DOSE CALCULATIONS ........... ......................................B-1 APPENDIX B-1. NONCANCER ORAL DOSE-RESPONSE ASSESSM ENT (RfD): BENCHMARK DOSE MODELING RESULTS EMPLOYING THE INCID ENCE OF FORESTOMACH LESIONS (HYPERPLASIA AND HYPERKERATOSIS ) IN MALE AND FEMALE SPRAGUE-DAWLEY RATS, F344 RATS, AND B6C3F 1 

### MICE CHRONICALLY EXPOSED ORALLY TO AN FOR 2 YEARS.. ..................B-1 APPENDIX B-2. NONCANCER INHALATION DOSE-RESPONSE A SSESSMENT (RfC): BMD MODELING RESULTS EMPLOYING THE INCIDENC E DATA FOR NONNEOPLASTIC NASAL LESIONS IN RATS EXPOSED TO AN B Y INHALATION FOR 2 YEARS (TABLES B-6 THROUGH B-9) .... ......................B-116 APPENDIX B-3. CANCER ORAL DOSE-RESPONSE ASSESSMENT : BMD DOSE MODELING RESULTS FOR TUMOR INCIDENCE DATA FROM RATS CHRONICALLY EXPOSED TO AN IN DRINKING WATER........ .....................B-123 APPENDIX B-4. CANCER INHALATION DOSE-RESPONSE ASSE SSMENT: BMD MODELING RESULTS FOR TUMOR INCIDENCE DATA FROM RATS CHRONICALLY EXPOSED TO AN VIA INHALATION........... .........................B-246 APPENDIX B-5. ANALYSIS TO ASSESS COMBINING TUMOR I NCIDENCE DATA FROM TWO CANCER BIOASSAYS EMPLOYING SPRAGUE-DAWLEY RATS ...............................................

................................................... ......................B-283 APPENDIX B-6. ESTIMATION OF COMPOSITE CANCER RISK FROM EXPOSURE TO AN BY COMBINING RISK ESTIMATES ACROSS MULTIPLE T UMOR SITES..............................................

................................................... .......................B-289 APPENDIX B-7. STATISTICAL ANALYSIS OF BLAIR ET AL. (1998) ....................B-293

APPENDIX C. PBPK MODEL DESCRIPTIONS AND SOURCE COD E .........................C-1

APPENDIX D. UNCERTAINTIES ASSOCIATED WITH CHEMICAL -SPECIFIC PARAMETERS EMPLOYED IN THE PBPK MODEL FOR AN DOSIME TRY IN HUMANS ..........................................

................................................... ..................... D-1

### vii DRAFT - DO NOT CITE OR QUOTE LIST OF TABLES

3-1. Recovery of radioactivity from male Sprague-D awley rats exposed to 5 or 100 ppm [1- 14 

### C]-AN for 6 hours via inhalation...................

................................................... .............. 6

3-2. Recovery of radioactivity after a single gava ge dose of 0.1 or 10 mg/kg [1- 14 

### C]-AN to male Sprague-Dawley rats ...........................

................................................... ....................... 6

3-3. Percentage recovery of radioactivity in tissu es of male Wistar rats following a single oral dose of radiolabeled AN .......................

................................................... ....................... 9

3-4. Apparent kinetic parameters of CEO formation from AN in B6C3F1 mice, F344 rats, and humans .........................................

................................................... .............................. 20

3-5. Apparent kinetic parameters for glutathione c onjugation of AN and CEO at pH 6.5.......... 26

3-6. Glutathione conjugation of AN and CEO with or without microsomal or cytosolic GST from rat, mouse, and human liver preparations ......

................................................... .......... 26

3-7. Urinary excretion of thioethers derived from AN ................................................. ............... 38

4-1. Clinical signs in 144 subjects accidentally e xposed to AN....................................... ........... 54

4-2. Distribution of select incidence and mortalit ies among wage workers and all workers at an AN plant .....................................

................................................... .............................. 56

4-3. Distribution of select incidence and mortalit ies among wage workers and all workers at an AN plant .....................................

................................................... .............................. 59

4-4. Distribution of select incidence and mortalit ies among wage and salary workers at an AN plant........................................

................................................... ............................... 61

4-5. Distribution of select mortalities among expo sed workers in two AN plants...................... 6 3

4-6. Distribution of select mortalities among expo sed workers ........................................ .......... 64

4-7. Crude and adjusted hazard ratio estimates for 100 ppm-year increase in cumulative
exposure ...........................................

................................................... ................................. 65

4-8. Hazard ratio estimated for select cancer mort ality by lagged cumulative exposure for 100 ppm-year increase in cumulative exposure.......

................................................... ......... 66

4-9. Distribution of select mortalities among AN-e xposed and unexposed workers .................. 73

4-10. Lung cancer mortality of AN-exposed workers stratified by cumulative dose and latency........................................

................................................... ............................... 74

4-11. Distribution of select mortalities among AN- exposed and unexposed workers ................ 80

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4-12. Distribution of select mortalities among AN- exposed and unexposed workers ................ 83

4-13. Distribution of mortality among AN-exposed w orkers............................................. ......... 87

4-14. Summary of relative regression analyses for cancer of the bronchus, trachea, and lung ...........................................

................................................... ................................ 88

4-15. Distribution of observed lung cancer deaths among AN-exposed workers, using regional rates for comparison......................

................................................... .................... 89

4-16. ORs of lung cancer for AN exposure ..........

................................................... .................... 93

4-17. Derived all-cancer SMRs for major cohort stu dies on AN exposure................................ . 96

4-18. Derived lung cancer SMRs for major cohort st udies on AN exposure .............................. 9 8

4-19. Industrial AN exposure, levels of AN and thi ocyanate in urine, and prevalence of physical signs of adverse effects in workers expose d to AN at six acrylic fiber factories in Japan .................................

................................................... .......................... 102

4-20. Comparison of reproductive outcomes in wives of exposed and control males at a chemical fiber plant ...............................

................................................... ........................ 108

4-21. Comparison of reproductive outcomes between exposed and control females at a chemical fiber plant ...............................

................................................... ........................ 108

4-22. Epidemiology studies of noncancer outcomes a mong cohorts of workers exposed to AN ..............................................

................................................... ............................... 117

4-23. Effect on SCV in male Sprague-Dawley rats ex posed to AN via gavage for 12 weeks ...........................................

................................................... ............................. 124

4-24. Incidence of nonneoplastic lesions in Spragu e-Dawley rats exposed to AN in drinking water for 2 years .........................

................................................... .................... 129

4-25. Selected tumor incidences in response to AN administered to Sprague-Dawley rats in drinking water for up to 2 years ................

................................................... ................ 130

4-26. Histopathologic location of astrocytomas in the CNS of male Sprague-Dawley rats administered AN in drinking water for 2 years......

................................................... ....... 132

4-27. Incidence of nonneoplastic lesions in Spragu e-Dawley rats exposed to AN in drinking water for 2 years .........................

................................................... .................... 134

4-28. Selected tumor incidences in Sprague-Dawley rats exposed to AN in drinking water for up to 2 years..................................

................................................... ........................... 136

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4-29. Incidence of nonneoplastic lesions in Spragu e-Dawley rats exposed to AN by gavage for 20 months......................................

................................................... ........................... 138

4-30. Cumulative incidence of tumors in response t o AN administered to Sprague-Dawley rats by gavage for up to 2 years...................

................................................... .................. 139

4-31. Incidences of nontumorous lesions in F344 ra ts exposed to AN in drinking water for 2 years............................................

................................................... ................................ 143

4-32. Selected tumor incidences in F344 rats expos ed to AN in drinking water for 2 years .... 144

4-33. Incidence and severity of nonneoplastic lesi ons in B6C3F 1 

### mice exposed by gavage to AN for 2 years ..................................

................................................... ......................... 146

4-34. Incidences of selected neoplastic lesions in B6C3F 1 

### mice exposed by gavage to AN for 2 years........................................

................................................... .............................. 147

4-35. Incidence of tumors in female Sprague-Dawley rats exposed to AN in drinking water for up to 46 weeks ...........................

................................................... .................... 151

4-36. Summary of chronic oral toxicity studies of AN: noncancer effects in rats and mice ...........................................

................................................... ............................. 151

4-37. Summary of chronic oral toxicity studies of AN: cancer effects in rats and mice .......... 153

4-38. Effect on SCV in male Sprague-Dawley rats ex posed to AN via inhalation for 24 weeks ...........................................

................................................... ............................. 156

4-39. Incidence of histopathological lesions of th e nasal turbinates in Sprague-Dawley rats exposed to AN via inhalation for 2 years ......

................................................... ......... 158

4-40. Incidence of dose-related noncancerous histo pathological lesions in Sprague-Dawley rats exposed to AN via inhalation for 2 years ......

................................................... ......... 159

4-41. Cumulative incidence of tumors in Sprague-Da wley rats exposed to AN via inhalation for up to 2 years.......................

................................................... ..................... 160

4-42. Comparison of carcinogenic effects of chroni c exposure to AN at 60 ppm starting either in utero or in adulthood, in Sprague-Dawley rats ............................................... ... 162

4-43. Incidence of fetal abnormalities among litte rs of Sprague-Dawley rats following maternal exposure to AN on GDs 6–15 ................

................................................... ........ 168

4-44. Morphological alterations in GD 12 fetuses o f Sprague-Dawley rats exposed to 100 mg/kg AN on GD 10 ..............................

................................................... ................ 169

4-45. Group-specific reproductive indices in three generations of Sprague-Dawley rats receiving AN in drinking water.....................

................................................... ................ 172

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4-46. Group-specific pup weights in three generati ons of Sprague-Dawley rats receiving AN in drinking water...............................

................................................... ...................... 173

4-47. Incidence of fetal malformations among litte rs of Sprague-Dawley rats exposed to AN by inhalation ...................................

................................................... ........................ 175

4-48. Effects of AN on organ weight, clinical chem istry, and biochemical parameters when administered to male Wistar rats via inhalatio n .................................................. ... 182

4-49. Time course of the effect of AN administrati on on [ 3 

### H]-thymidine uptake into mouse splenocytes under the influence of different mitogens in vitro............................. 193

4-50. Summary of immunotoxicity studies of AN.....

................................................... ............. 194

4-51. Effect of AN on RBC metabolic intermediates following a single oral dose................... 196

4-52. Detection of N 7 

### -(2-oxoethyl)guanine after i.p. administration of 5 0 mg/kg AN or CEO to male F344 rats ..............................

................................................... .................... 212

4-53. Summary of studies on the mutagenicity/genot oxicity of AN ...................................... ... 239

4-54. Formation of 8-oxodG in DNA from tissues of male Sprague-Dawley and F344 rats exposed to AN in drinking water for 21 days ........

................................................... ....... 251

4-55. Summary of studies on the indirect mutagenic ity or genotoxicity of AN........................ 25 3

4-56. Noncancer effects in animals repeatedly expo sed to AN by the oral route...................... 23 5

4-57. Noncancer effects in human workers and anima ls repeatedly exposed to AN by inhalation ......................................

................................................... ............................ 259

4-58. 8-OxodG in brain DNA and brain tumor inciden ce in male F344 rats exposed to AN in drinking water...............................

................................................... ...................... 287

4-59. 8-OxodG in brain DNA and brain tumor inciden ce in male Sprague-Dawley rats exposed to AN in drinking water ....................

................................................... .............. 288

5-1. Incidences of forestomach lesions (hyperplasi a or hyperkeratosis) in Sprague-Dawley and F344 rats exposed to AN in drinking water for 2 yea rs................................................. .... 305

5-2. Incidences of forestomach lesions (hyperplasi a or hyperkeratosis) in male and female B6C3F 1 

### mice administered AN via gavage for 2 years....... ................... 306

5-3. Candidate RfDs based on BMD modeling of the i ncidence of nonneoplastic forestomach lesions (hyperplasia or hyperkeratosis) in male and female Sprague-Dawley rats exposed to AN in drinking water for 2 years .................................. 310

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5-4. Candidate RfDs based on BMD modeling of the i ncidence of nonneoplastic forestomach lesions (hyperplasia or hyperkeratosis) in male and female F344 rats exposed to AN in drinking water for 2 years........

................................................... .......... 311

5-5. Candidate RfDs based on BMD modeling of the i ncidence of nonneoplastic forestomach lesions (hyperplasia or hyperkeratosis) in male and female B6C3F 1 

### mice exposed to AN via gavage for 2 years......... ................................................ 312

5-6. Results of dose-response analyses of incidenc e data for selected nasal lesions in male and female Sprague-Dawley rats exposed by inha lation to AN for 2 years ............. 321

5-7. Incidence of CNS tumors in Sprague-Dawley and F344 rats exposed to AN in drinking water for 2 years.........................

................................................... ...................... 329

5-8. Incidence of mammary gland tumors in F344 and Sprague-Dawley rats exposed to AN in drinking water for 2 years ...................

................................................... ................. 330

5-9. Tumor incidences Sprague-Dawley and F344 in r ats exposed to AN in drinking water for 2 years ........................................

................................................... ............................... 331

5-10. Incidences of intestinal, CNS, Zymbal gland, tongue, and mammary gland tumors in Sprague-Dawley rats exposed to AN via inhalation for 2 years .................................. 333

5-11. Four different dose metrics, two external an d two internal, based on doses employed in studies of Sprague-Dawley and F344 rats exposed to AN in drinking water for 2 years .........................

................................................... .................... 335

5-12. BMD modeling results using tumor incidence d ata from male and female Sprague-Dawley and F344 rat studies in which animal s were exposed to AN in drinking water for 2 years .........................

................................................... .................... 336

5-13. Site-specific oral CSFs for AN based on BMD modeling of tumor incidence data in rats and predicted CEO levels in blood (AUC/24 hour s) of rats and humans assuming episodic exposure to AN ...................

................................................... ............ 338

5-14. Site-specific oral CSFs for AN based on BMD modeling of tumor incidence data in rats and predicted AN levels in blood (AUC/24 ho urs) of rats and humans assuming episodic exposure to AN ...................

................................................... ............ 339

5-15. Site-specific oral CSFs for AN based on BMD modeling of tumor incidence data in rats and BW scaling to the 3⁄4 power to conve rt from rat to human administered doses .................................

................................................... ....................... 340

5-16. Two different dose metrics, one external and one internal, based on administered air concentrations of AN employed in a 2-year bioas say in Sprague-Dawley rats.......... 341

5-17. BMD modeling results using tumor incidence d ata from male and female Sprague-Dawley rats exposed to AN via inhalation fo r 2 years and CEO concentration in blood predicted from an EPA-modifi ed PBTK model .......................... 342

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5-18. Site-specific IURs for AN based on BMD model ing of tumor incidence data in Sprague-Dawley rats and PBTK modeling of CEO levels in blood (AUC/24 hours) of rats and humans.................................

................................................... ........................ 343

5-19. Site-specific IURs for AN based on BMD model ing of tumor incidence data in Sprague-Dawley rats exposed to AN via inhalation ...

................................................... .. 343

5-20. Estimated human equivalent oral CSFs for com posite risk based on tumor incidence in AN-exposed rats and predicted CEO-AUC levels in blood......................... 345

5-21. Estimated human equivalent composite IURs ba sed on tumor incidence in AN-exposed rats and predicted CEO-AUC levels in blo od............................................. 347

5-22. Tumor incidences in Sprague-Dawley rats foll owing inhalation exposure to 60 ppm AN for 104 weeks, starting either in utero ( GD 12) or as adults at 13 wks of age......................................

................................................... ........................... 350

5-23. Tumor incidences in female Sprague-Dawley ra ts exposed to AN in drinking water for approximately 46 weeks, starting either in uter o or at 5 weeks of age....................... 353

5-24. Overall extra risks of multiple tumor incide nce, for chronic exposure beginning either in early-life or in adulthood; based on Spra gue-Dawley rats exposed to AN........ 355

5-25. Application of ADAFs for estimating human ca ncer risk from 70-year oral or inhalation exposures to AN from ages 0 to 70 .......

................................................... ....... 357

5-26. Summary of uncertainty in the AN oral cancer risk assessment ................................... ... 359

5-27. Summary of uncertainty in the AN inhalation cancer risk assessment ............................ 3 64

B-1. Incidences of forestomach lesions (hyperplasi a or hyperkeratosis) in Sprague-Dawley and F344 rats exposed to AN in drinking water for 2 yea rs................................................. .... B-1

B-2. Incidences of forestomach lesions (hyperplasi a or hyperkeratosis) in male and female B6C3F 1 

### mice administered AN via gavage for 2 years ....... .............................................. B-3

B-3. Summary of the BMD modeling results based on the incidence of forestomach lesions (hyperplasia or hyperkeratosis) in male and female Sprague-Dawley rats exposed to AN in drinking water for 2 years .................................. B-4

B-4. Summary of the BMD modeling results based on the incidence of forestomach lesions (hyperplasia or hyperkeratosis) in male and female F344 rats exposed to AN in drinking water for 2 years........

................................................... ........ B-52

B-5. Summary of the BMD modeling results based on the incidence of forestomach lesions (hyperplasia or hyperkeratosis) in male and female B6C3F 1 

### mice exposed to AN via gavage for 2 years .................................

................................................... ........................ B-83

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B-6. Incidence data for selected nasal lesions in Sprague-Dawley rats exposed by inhalation to AN for 2 years.......................

................................................... ................. B-116

B-7. A summary of BMDS (version 1.3.2) modeling re sults based on incidence of hyperplasia of mucus-secreting cells in male Spragu e-Dawley rats exposed to AN via inhalation for 2 years......................

................................................... ................ B-117

B-8. A summary of BMDS (version 1.3.2) modeling re sults based on incidence of flattening of respiratory epithelium in female Spra gue-Dawley rats exposed to AN via inhalation for 2 years......................

................................................... ................ B-120

B-9. Incidence of forestomach (nonglandular) tumor s in Sprague-Dawley rats exposed to AN in drinking water for 2 years ...................

................................................... ............. B-124

B-10. Summary of BMD modeling results based on inc idence of forestomach (nonglandular) tumors in Sprague-Dawley rats expose d to AN in drinking water for 2 years........................................

................................................... .......................... B-124

B-11. Incidence of CNS tumors in Sprague-Dawley ra ts exposed to AN in drinking water for 2 years........................................

................................................... .......................... B-139

B-12. Summary of BMD modeling results based on inc idence of CNS tumors in Sprague-Dawley rats exposed to AN in drinking water for 2 years............................. B-139

B-13. Incidence of Zymbal gland tumors in Sprague- Dawley rats exposed to AN in drinking water for 2 years ......................

................................................... ............... B-154

B-14. Summary of BMD modeling results based on inc idence of Zymbal gland tumors in Sprague-Dawley rats exposed to AN in drin king water for 2 years ............ B-154

B-15. Incidence of tongue tumors in Sprague-Dawley rats exposed to AN in drinking water for 2 years ..................................

................................................... ...................... B-169

B-16. Summary of BMD modeling results based on inc idence of tongue tumors in Sprague-Dawley rats exposed to AN in drinking water for 2 years............................. B-169

B-17. Incidence of mammary gland tumors in Sprague -Dawley rats exposed to AN in drinking water for 2 years .........................

................................................... ................ B-184

B-18. Summary of BMD modeling results based on inc idence of mammary gland tumors in Sprague-Dawley rats exposed to AN in drin king water for 2 years ............ B-184

B-19. Incidence of forestomach (nonglandular) tumo rs in F344 rats exposed to AN in drinking water for 2 years .........................

................................................... ................ B-192

B-20. Summary of BMD modeling results based on inc idence of forestomach (nonglandular) tumors in F344 rats exposed to AN in drinking water for 2 years ...... B-193

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B-21. Incidence of CNS tumors in F344 rats exposed to AN in drinking water for 2 years............................................

................................................... ............................ B-208

B-22. Summary of BMD modeling results based on inc idence of CNS tumors in F344 rats exposed to AN in drinking water for 2 yea rs ............................................... B- 208

B-23. Incidence of Zymbal gland tumors in F344 rat s exposed to AN in drinking water for 2 years........................................

................................................... .......................... B-223

B-24. Summary of BMD modeling results based on inc idence of Zymbal gland tumors in F344 rats exposed to AN in drinking water for 2 yea rs ............................................... B- 223

B-25. Incidence of mammary gland tumors in F344 ra ts exposed to AN in drinking water for 2 years........................................

................................................... .......................... B-238

B-26. Summary of BMD modeling results based on inc idence of mammary gland tumors in F344 rats exposed to AN in drinking water for 2 years ........................................... B-2 38

B-27. Incidence of intestinal tumors in Sprague-Da wley rats exposed to AN in air for 2 years............................................

................................................... ............................ B-247

B-28. Summary of BMD modeling results based on inc idence of intestinal tumors in Sprague-Dawley rats exposed to AN in air for 2 year s................................................ B- 247

B-29. Incidence of CNS tumors in Sprague-Dawley ra ts exposed to AN in air for 2 years............................................

................................................... ............................ B-253

B-30. Summary of BMD modeling results based on inc idence of CNS tumors in Sprague-Dawley rats exposed to AN in air for 2 year s................................................ B- 253

B-31. Incidence of Zymbal gland tumors in Sprague- Dawley rats exposed to AN in air for 2 years........................................

................................................... .......................... B-262

B-32. Summary of BMD modeling results based on inc idence of Zymbal gland tumors in Sprague-Dawley rats exposed to AN in air for 2 y ears............................................ B-2 62

B-33. Incidence of tongue tumors in Sprague-Dawley rats exposed to AN in air for 2 years............................................

................................................... ............................ B-272

B-34. Summary of BMD modeling results based on inc idence of tongue tumors in SpragueDawley rats exposed to AN in air for 2 years .......

................................................... .... B-272

B-35. Incidence of mammary gland tumors in Sprague -Dawley rats exposed to AN in air for 2 years........................................

................................................... .......................... B-278

B-36. Summary of BMD modeling results based on inc idence of mammary gland tumors in Sprague-Dawley rats exposed to AN in air for 2 y ears............................................ B-2 78

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B-37. Summary of PODs for composite cancer risk as sociated with episodic oral exposure to AN, using CEO-AUC levels in blood as do se metric and multiple tumor incidence data in rats.......................

................................................... ................ B-291

B-38. Summary of PODs for composite cancer risk as sociated with inhalation exposure to AN, based on multiple tumor incidence data in ra ts and CEO-AUC levels in blood...........................................

................................................... ........................... B-291

B-39. Estimated human oral CSFs for AN based on mu ltiple tumor incidence data in rats and CEO-AUC levels in blood ...................

................................................... ........ B-292

B-40. Estimated human IURs for AN based on multipl e tumor incidence data in rats and CEO-AUC levels in blood............................

................................................... ............. B-292

C-1. Rat and human PBPK model parameter values ....

................................................... .......... C-2

D-1. Tissue:blood PCs .............................

................................................... ............................... D-2

D-2. Impact of method of estimation of PCs on the peak AN and CEO model predictions ..... D-3

D-3. PBPK mass balance predictions for an 8-hour h uman exposure to 2 ppm AN................. D-6

D-4. Sensitivity of AN and CEO metrics for continu ous inhalation exposure.......................... D- 9

D-5. Sensitivity of AN and CEO metrics for continu ous oral exposure.................................. D-10

D-6. Estimated CVs for AN and CEO metrics .........

................................................... ............ D-12

D-7. Parameter contributions to overall CVs for in halation exposure.................................. ... D-13

D-8. Parameter contributions to overall CVs for or al exposure ........................................ ...... D-14

### xvi DRAFT - DO NOT CITE OR QUOTE LIST OF FIGURES

2-1. Chemical structure of AN.....................

................................................... ............................... 3

3-1. Scheme for the metabolic transformation of AN

................................................... ............... 14

3-2. Structure of the PBTK model for AN and CEO...

................................................... ............. 41

3-3. Intravenous exposure, dosimetry, and model fi ts................................................. ................ 46

3-4a. Inhalation exposure, CEO concentrations .....

................................................... .................. 47

3-4b. Inhalation exposure, AN concentrations ......

................................................... ................... 48

3-5a. Oral exposure, CEO concentrations...........

................................................... ...................... 49

3-5b. Oral exposure, AN concentrations............

................................................... ....................... 50

3-5c. Oral exposure, urinary excretion, and Hb bin ding............................................... ............... 51

5-1. Comparison of LOAELs for noncancer effects ac ross target organs following oral exposure to AN in animals..........................

................................................... ..................... 316

5-2. Comparison of LOAELs for noncancer effects in human workers following inhalation exposure to AN .....................................

................................................... ........................... 323

5-3. Comparison of tumor responses to inhalation e xposure of acrylonitrile, by age at start of exposure (offspring at GD 12, adults at 13 weeks ), sex, and length of exposure, for Sprague-Dawley rats (Maltoni et al., 1988).........

................................................... ............ 351

5-4. Comparison of composite oral CSFs derived fro m tumor incidence data in four different sex/strain/species of rats exposed chroni cally to AN. For each sex/strain/species combination, two different dose metrics were employed: (1) CEO concentration in blood, and (2) human equiv alent administered dose................. 360

5-5. Comparison of Composite IURs derived from: ( 1) tumor incidence data in male and female Sprague-Dawley rats exposed chronically to A N, and (2) neurological effects in humans exposed to AN occupationally. In derivin g the animal-based IURs, two different dose metrics were employed: (1) predicte d CEO concentration in blood, and (2) human equivalent administered AN concentration in air............................................. . 365

C-1. Human inhalation exposure level vs. internal AN concentration ................................... ... C-5

C-2. Human inhalation exposure level vs. internal CEO concentrations ................................. . C-6

C-3. Human oral exposure level vs. internal AN con centration for continuous exposure ........ C-8

C-4. Human oral exposure level vs. internal CEO co ncentration for continuous exposure ...... C-8

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C-5. Human oral exposure level vs. internal AN con centration for episodic exposure............. C-9

C-6. Human oral exposure level vs. internal CEO co ncentration for episodic exposure .......... C-9

### xviii DRAFT - DO NOT CITE OR QUOTE LIST OF ABBREVIATIONS AND ACRONYMS

ABS AN butadiene styrene ABT 1-aminobenzotriazole ADAF age-dependent adjustment factor ADUR AN-derived undialyzable radioactivity AIC Akaike’s Information Criterion ALT alanine aminotransferase AMAP amplitude of the motor action potential AN acrylonitrile ASAP amplitude of the sensory action potential AST aspartate aminotransferase ATP adenosine triphosphate ATPase adenosine triphosphatase ATSDR Agency for Toxic Substances and Disease Registry AUC area under the curve BAL broncho alveolar lavage BMC benchmark concentration BMCL 95% lower bound of the BMC BMD benchmark dose BMDL 95% lower confidence limit of benchmark dose BMDS benchmark dose software BMR benchmark response BrdU bromodeoxyuridine BSO buthionine sulfoximine BUN blood urea nitrogen BW body weight CA chromosomal aberration CAIII carbonic anhydrase III CAP compound action potential CASRN Chemical Abstracts Service Registry Number CEMA 2-cyanoethyl mercapturic acid CEO 2-cyanoethylene oxide CEVal N-(2-cyanoethyl)valine CF correction factor CHL Chinese hamster lung CHO Chinese hamster ovary CI confidence interval CNS central nervous system con-A concanavalin-A CSF cancer slope factor CV coefficient of variation CYP450 cytochrome P450 DEM diethylmaleate DEX dexamethasone dGMP deoxyguanosine-5 ′ -monophosphate DMSO dimethyl sulfoxide DNA deoxyribonucleic acid

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DPOAE distortion product otoacoustic emission DTH delayed-type hypersensitivity EC exposure concentration ECG electrocardiogram EH epoxide hydrolase ERK extracellular signal-regulated kinase EROD ethoxyresorufin-O-deethylase FISH fluorescence in situ hybridization FSH follicle stimulating hormone GAPDH glyceraldehyde-3-phosphate dehydrogenase GD gestation day GEI gastric erosion severity index GI gastrointestinal GJIC gap junction intercellular communications GSH reduced glutathione GSSG glutathione disulfide GST glutathione-S-transferase GSTM GST of the μ subclass γ -GTP γ -glutamyl transpeptidase Hb hemoglobin HbCO carboxyhemoglobin HbO oxyhemoglobin HEC human equivalent concentration HED human equivalent dose HMPA hexamethylphosphoramide HPLC high performance liquid chromatography hprt hypoxanthine guanine phosphoribosyl transferase IC 50 

### median inhibitory concentration Ig immunoglobulin i.p. intraperitoneal IPCS International Programme on Chemical Safety IRIS Integrated Risk Information System IUR inhalation unit risk i.v. intravenous KCN potassium cyanide LC 50 

### median lethal concentration LD 50 

### median lethal dose LDH lactate dehydrogenase LEC 95% lower bound of exposure concentration LH luteinizing hormone LOAEL lowest-observed-adverse-effect level LPS lipopolysaccharide MCMC Markov chain Monte Carlo MCV motor conduction velocity MDA malondialdehyde mEH microsomal epoxide hydrolase MEK mitogen-activated/ERK-activating kinase MEL melatonin MetHb methemoglobin

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MN micronucleus, micronuclei MNU methylnitrosourea MP microsomal protein 4MP 4-methylpyrazole NAC N-acetylcysteine NADP(H) nicotinamide adenine dinucleotide phosphate (redu ced) NAS National Academy of Sciences NCI National Cancer Institute NCTB Neurobehavioral Core Test Battery NHA normal human astrocyte NIHL noise-induced hearing loss NIOSH National Institute for Occupational Safety and Heal th NMR nuclear magnetic resonance NOAEL no-observed-adverse-effect level NRC National Research Council NTP National Toxicology Program OBN octave band of noise OHC outer hair cell OR odds ratio OTC L-2-oxothiazolidine-4-carboxylic acid 8-oxodG 8-oxodeoxyguanosine, also referred to as 8-oxo-7,8 -dihydro2 ′ deoxyguanosine and 8-hydroxy-2 ′ -deoxyguanosine PB phenobarbital PBN phenyl-N-tertiary-butylnitrone PBPK physiologically based pharmacokinetic PBTK physiologically based toxicokinetic PC partition coefficient PCR polymerase chain reaction PH phorone PHA phytohemagglutinin PK protein kinase PMA phorbol 12-myristate 13-acetate PND postnatal day POD point of departure PRL prolactine RBC red blood cell RfC reference concentration RfD reference dose RLC rat liver cell RNA ribonucleic acid ROS reactive oxygen species RR relative risk SAED serially additive expected dose

s.c. subcutaneous SCE sister chromatid exchange SCV sensory conduction velocity SD standard deviation SDH sorbitol dehydrogenase SEER Surveillance, Epidemiology and End Results

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SG USEPA Supplemental Guidance for Assessing Susceptibility from EarlyLife Exposure to Carcinogens SGPT serum glutamate pyruvate transaminase SHE Syrian hamster embryo SIR standardized incidence ratio SMR standardized mortality ratio SOD superoxide dismutase SRBC sheep red blood cell STS sodium thiosulfate TAU taurine TBARS thiobarbituric acid-reactive substances TCPO 1,1,1-trichloropropane-2,3-oxide 6-TG 6-thioguanine TNF- α tumor necrosis factor TPO 3,3,3-trichloropropylene oxide TRX trolox TWA time-weighted average UCL upper confidence limit UDS unscheduled DNA synthesis UF uncertainty factor U.S. EPA U.S. Environmental Protection Agency v/v volume/volume WBC white blood cell WHO World Health Organization WT wild-type

### xxii DRAFT - DO NOT CITE OR QUOTE FOREWORD

The purpose of this Toxicological Review is to prov ide scientific support and rationale for the hazard and dose-response assessment in IRIS pertaining to chronic exposure to acrylonitrile. It is not intended to be a comprehe nsive treatise on the chemical or toxicological nature of acrylonitrile. The intent of Section 6, Major Conclusions in the Characterization of Hazard and Dose Response, is to present the major conclusions reached in the derivation of the reference dose, reference concentration and cancer assessment, wher e applicable, and to characterize the overall confidence in the quantitative and qualitative aspe cts of hazard and dose response by addressing the quality of data and related uncertainties. The discussion is intended to convey the limitations of the assessment and to aid and guide the risk ass essor in the ensuing steps of the risk
assessment process. For other general information about this assessment or other questions relating to IRIS, the reader is referred to EPA’s IRIS Hotline at (20 2) 566-1676 (phone), (202) 566-1749 (fax), or hotline.iris@epa.gov (email address).

### xxiii DRAFT - DO NOT CITE OR QUOTE AUTHORS, CONTRIBUTORS, AND REVIEWERS

CHEMICAL MANAGER

Diana Wong, Ph.D., DABT National Center for Environmental Assessment Office of Research and Development U.S. Environmental Protection Agency Washington, DC

AUTHORS

Diana Wong, Ph.D., DABT Ted Berner, MS John Fox Rosemarie Hakim, Ph.D. Karen Hogan, MS Amanda Persad, Ph.D. Leonid Kopylev, Ph.D. Paul Schlosser, Ph.D. National Center for Environmental Assessment Office of Research and Development U.S. Environmental Protection Agency Washington, DC

Roglio Tornero-Valez, Ph.D. Office of Research and Development U.S. Environmental Protection Agency Washington, DC

CONTRACTOR SUPPORT

Lutz W.D. Weber, Ph.D., DABT (First Draft) George Holdsworth, Ph.D. (First Draft) Janusz Z. Byczkowski, Ph.D., D.Sc., DABT (First Dr aft) Donna Cragle, Ph.D. (First Draft) Virginia H. Sublet, Ph.D. (First Draft) Oak Ridge Institute for Science and Education Oak Ridge Associated Universities Oak Ridge, TN

Margaret Fransen, Ph.D. (Second Draft) Michael Lumpkin, Ph.D. (Second Draft) Jennifer Rhoades, B.S. (Second Draft) Peter McClure, Ph.D., DABT (Second Draft) Environmental Science Center SRC, Inc. North Syracuse, NY

### xxiv DRAFT - DO NOT CITE OR QUOTE

INTERNAL EPA REVIEWERS

James Allen, Ph.D. NHEERL Office of Research and Development U.S. Environmental Protection Agency Research Triangle Park, NC

Dave Bayliss, Ph.D. National Center for Environmental Assessment Office of Research and Development U.S. Environmental Protection Agency Washington, DC

Jerry Blancato, Ph.D. NERL U.S. Environmental Protection Agency Research Triangle Park, NC

Anthony DeAngelo, Ph.D. NHEERL Office of Research and Development U.S. Environmental Protection Agency Research Triangle Park, NC

Rob Dewoskin, Ph.D. National Center for Environmental Assessment Office of Research and Development U.S. Environmental Protection Agency Research Triangle Park, NC

Lynn Flowers, Ph.D., DABT National Center for Environmental Assessment Office of Research and Development U.S. Environmental Protection Agency Washington, DC

Kate Guyton, Ph.D., DABT National Center for Environmental Assessment Office of Research and Development U.S. Environmental Protection Agency Washington, DC

Karl Jensen, Ph.D. NHEERL Office of Research and Development

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U.S. Environmental Protection Agency Research Triangle Park, NC

Jennifer Jinot National Center for Environmental Assessment Office of Research and Development U.S. Environmental Protection Agency Washington, DC

Channa Keshava, Ph.D. National Center for Environmental Assessment Office of Research and Development U.S. Environmental Protection Agency Washington, DC

John Lipscomb, Ph.D. National Center for Environmental Assessment Office of Research and Development U.S. Environmental Protection Agency Cincinnati, OH

Robert MacPhail, Ph.D. NHEERL Office of Research and Development U.S. Environmental Protection Agency Research Triangle Park, NC

Jeff Ross, Ph.D. NHEERL Office of Research and Development U.S. Environmental Protection Agency Research Triangle Park, NC

Cheryl Scott National Center for Environmental Assessment Office of Research and Development U.S. Environmental Protection Agency Washington, DC

Lawrence Valcovic, Ph.D. National Center for Environmental Assessment Office of Research and Development U.S. Environmental Protection Agency Washington, DC

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John Whalan National Center for Environmental Assessment Office of Research and Development U.S. Environmental Protection Agency Washington, DC

### DRAFT - DO NOT CITE OR QUOTE 1 1. INTRODUCTION

This document presents background information and j ustification for the Integrated Risk Information System (IRIS) Summary of the hazard and dose-response assessment of acrylonitrile (AN). IRIS Summaries may include oral reference do se (RfD) and inhalation reference concentration (RfC) values for chronic and other ex posure durations, and a carcinogenicity

assessment. The RfD and RfC, if derived, provide quantitative i nformation for use in risk assessments for health effects known or assumed to be produced through a nonlinear (presumed threshold) mode of action (MOA). The RfD (expressed in units of mg/kg-day) is defined as an estimate (with uncertainty spanning perhaps an order of magn itude) of a daily exposure to the human population (including sensitive subgroups) that is likely to be without an appreciable risk of deleterious effects during a lifetime. The inhalat ion RfC (expressed in units of mg/m 3 

### ) is analogous to the oral RfD, but provides a continuou s inhalation exposure estimate. The
inhalation RfC considers toxic effects for both the respiratory system (portal of entry) and for effects peripheral to the respiratory system (extra respiratory or systemic effects). Reference values are generally derived for chronic exposures (up to a lifetime), but may also be derived for acute ( ≤ 24 hours), short-term (>24 hours up to 30 days), an d subchronic (>30 days up to 10% of lifetime) exposure durations, all of which are deri ved based on an assumption of continuous exposure throughout the duration specified. Unless specified otherwise, the RfD and RfC are derived for chronic exposure duration. The carcinogenicity assessment provides information on the carcinogenic hazard potential of the substance in question and quantita tive estimates of risk from oral and inhalation exposure may be derived. The information includes a weight-of-evidence judgment of the likelihood that the agent is a human carcinogen and the conditions under which the carcinogenic effects may be expressed. Quantitative risk estima tes may be derived from the application of a low-dose extrapolation procedure. If derived, the oral slope factor is a plausible upper bound on the estimate of risk per mg/kg-day of oral exposure . Similarly, an inhalation unit risk is a plausible upper bound on the estimate of risk per μ g/m 3 

### air breathed. Development of the hazard identification and dose-r esponse assessments for AN has followed the general guidelines for risk assessment as set forth by the National Research Council (NRC, 1983). U.S. Environmental Protection Agency (U.S. EPA) Guidelines and Risk Assessment Forum Technical Panel Reports that may h ave been used in the development of this assessment include the following: Guidelines for the Health Risk Assessment of Chemic al
Mixtures (U.S. EPA, 1986a), Guidelines for Mutagenicity Risk Assessment (U.S. EPA, 1986b), Recommendations for and Documentation of Biological Values for Use in Risk Assessment (U.S. EPA, 1988), Guidelines for Developmental Toxicity Risk Assessme nt (U.S. EPA, 1991), Interim

### DRAFT - DO NOT CITE OR QUOTE 2 Policy for Particle Size and Limit Concentration Is sues in Inhalation Toxicity (U.S. EPA, 1994a), Methods for Derivation of Inhalation Reference Conc entrations and Application of Inhalation Dosimetry (U.S. EPA, 1994b), Use of the Benchmark Dose Approach in Health Risk
Assessment

(U.S. EPA, 1995), Guidelines for Reproductive Toxicity Risk Assessmen t (U.S. EPA, 1996), Guidelines for Neurotoxicity Risk Assessment (U.S. EPA, 1998a), Science Policy Council
Handbook : Risk Characterization (U.S. EPA, 2000a), Benchmark Dose Technical Guidance
Document

(U.S. EPA, 2000b), Supplementary Guidance for Conducting Health Risk A ssessment of Chemical Mixtures (U.S. EPA, 2000c), A Review of the Reference Dose and Reference
Concentration Processes (U.S. EPA, 2002), Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005a) , Supplemental Guidance for Assessing Susceptibilit y from Early-Life Exposure to Carcinogens (U.S. EPA, 2005b), Science Policy Council Handbook: Peer Review (U.S. EPA, 2006a), and A Framework for Assessing Health Risks of Environme ntal Exposures to Children (U.S. EPA, 2006b). The literature search strategy employed for this co mpound was based on the Chemical Abstracts Service Registry Number (CASRN) and at le ast one common name. Any pertinent scientific information submitted by the public to t he IRIS Submission Desk was also considered in the development of this document. The relevant literature was reviewed through June 2009.

### DRAFT - DO NOT CITE OR QUOTE 3 2. CHEMICAL AND PHYSICAL INFORMATION

AN (CASRN 107-13-1) is a three-carbon alkene carry ing a nitrile substituent group as part of the terminal carbon atom (carbon 1) (Figure 2-1). Synonyms for the compound include vinyl cyanide, propenenitrile, and cyanoethylene, a nd there are a variety of trade names. AN is a colorless, flammable, and volatile liquid with a we akly pungent onion- or garlic-like odor. Some physical and chemical properties are shown below (N LM, 2003; IPCS, 2002; ATSDR, 1990).

Figure 2-1. Chemical structure of AN.

Formula: C 3 

### H 3 

### N Molecular weight: 53.06 Melting point: –83°C Boiling point: 77.4°C Density: 0.806 g/mL (at 20°C) Log K OW 

### : –0.92 Log K OC 

### : –0.07 Vapor pressure: 100 mm Hg at 22.8°C Henry’s law constant: 8.8 × 10 -5 

### atm-m 3 

### /mol Conversion factors: 1 ppm = 2.17 mg/m 3 

### 1 mg/m 3 

### = 0.46 ppm

AN is a commercially important chemical with a wid e range of uses in the chemical industry. It is used in the production of acrylic and modacrylic fibers, plastics (AN butadiene styrene [ABS] and AN-styrene resins), and nitrile r ubbers and as an intermediate in the production of other important chemicals, such as ad iponitrile and acrylamide. AN is used in the plastics industry in the formation of surface coati ngs and adhesives. It is a chemical intermediate in the synthesis of antioxidants, pharmaceuticals, and dyes and, in general, for processes requiring the introduction of a cyanoethyl group in to a molecule (NLM, 2003). AN is also used in clinical practice in the form of dialysis tubing (Mulvihill et al., 1992). AN was used occasionally as a fumigant insecticide for stored g rain. A measure of the commercial importance of AN may be judged by the amount produced in a giv en year. The Agency for Toxic Substances and Disease Registry (ATSDR, [1990]) rep orts that 1,112,754 metric tons of AN were produced in the United States in 1987. Produc tion had increased to 1,455,735 metric tons 

# C C C N H

H H

### DRAFT - DO NOT CITE OR QUOTE 4 by 1995 (ACS, 2003). Exposure of the general publi c to AN can potentially occur through migration of residual monomer in polymeric products via contact with food or water. Exposure to airborne AN is possible among members of the gen eral population living in the vicinity of emission sources such as acrylic fiber or chemical manufacturing plants or waste sites (ATSDR, 1990). In addition, smokers are expected to be exp osed to AN, which has been detected in cigarette smoke at levels of 3.2–15 mg per cigarett e (IARC, 1999).

### DRAFT - DO NOT CITE OR QUOTE 5 3. TOXICOKINETICS

Although only limited information on the toxicokin etics of AN in exposed humans is available, a substantial body of evidence has accum ulated on the absorption, distribution, metabolism, and excretion of AN in experimental ani mals. The overall conclusion that can be drawn is that AN is rapidly and nearly completely a bsorbed, widely distributed among the tissues, and biochemically transformed into several discrete metabolic products that are excreted in the urine and, to a much lesser extent, in feces and expired air. Characterization of the excretory products of AN, with support from in vitr o and in vivo kinetic data on its biotransformation, has contributed to a picture of how AN is rearranged into a series of metabolic products. Two primary processes appear t o be involved: (1) interaction with reduced glutathione (GSH) and (2) cytochrome P450 (CYP450) 2E1-mediated formation of 2-cyanoethylene oxide (CEO). Each product of these processes can undergo further metabolic transformations. For example, CEO can be hydrolyze d to cyanide with further transformation to thiocyanate. Alternatively, CEO can itself interac t with GSH, resulting in the formation of a number of metabolites, several of which have been i dentified in the urine of experimental
animals. Important data elements that have contributed to t he EPA's current understanding of the
toxicokinetics of AN are summarized in the followin g sections.

3.1. ABSORPTION
3.1.1. Studies in Humans There are few data on the absorption of AN in huma ns. However, Jakubowski et al. (1987) provided some information on the topic by ad ministering AN via inhalation to six male
volunteers for 8 hours at concentrations of either 5 or 10 mg/m 3 

### from a chamber. Lung ventilation and retention of AN in the lungs of the se individuals were measured by determining the concentrations of AN in the inhaled and expired air. A respiratory retention of 52% was estimated, based on 90 minutes to 8 hours of observ ation.

3.1.2. Studies in Animals Most of the available information on the absorption of AN has come from studies in experimental animals. Young et al. (1977) carried out a series of experiments in which [1- 14 

### C]-AN was administered to male Sprague-Dawley rats via the oral, inhalation, or intravenous (i.v.) route. Semiquantitative evidenc e of extensive absorption of AN has come from an inhalation experiment of Young et al. (1977 ) in which four rats/group were exposed nose only to 5 or 100 ppm AN vapor for 6 hours. Fo llowing the exposure, the animals were kept in metabolism cages and excreta were collected for 220 hours. Total recovered doses estimated

### DRAFT - DO NOT CITE OR QUOTE 6 from total recovered radioactivity for the low and high exposure levels were 0.7 and 10.2 mg/kg [1- 14 

### C]-AN, respectively. Substantial amounts of the re covered dose were found in urine, feces, and tissues, which indicated that AN has the capaci ty to be absorbed via the inhalation route (Table 3-1).

Table 3-1. Recovery of radioactivity from male Spr ague-Dawley rats exposed to 5 or 100 ppm [1- 14 

### C]-AN for 6 hours via inhalation

5 ppm 100 ppm Site of recovery Percentage of recovered dose (mean ± standard devia tion [SD])
Urine 68.50 ± 9.38 82.17 ± 4.21
Feces 3.94 ± 0.97 3.15 ± 0.82

14 CO 2 6.07 ± 1.58 2.60 ± 0.83 Body 18.53 ± 4.68 11.24 ± 2.85 Cage wash 2.95 ± 3.95 0.85 ± 0.58

Total dose (mg/kg) 0.7 10.2

Source: Young et al. (1977).



### In the gavage experiments of Young et al. (1977), animals were kept in metabolic cages after a single dose of either 0.1 or 10 mg/kg [1- 14 

### C]-AN (vehicle not stated), and the fate of the
radiolabel was monitored for 72 hours. As shown in Table 3-2, only about 5% of the
administered radiolabel was recovered in the feces after 72 hours. By contrast, most of the administered radiolabel was recovered in the urine, carcass, and skin, with smaller fractions of the administered radiolabel expired as 14 

### CO 2 

### . These data suggest that at least 95% of
administered AN was absorbed.

Table 3-2. Recovery of radioactivity after a singl e gavage dose of 0.1 or 10 mg/kg [1- 14 

### C]-AN to male Sprague-Dawley rats

0.1 mg/kg 10 mg/kg Recovery site Percent of dose
Urine 34.22 ± 6.26 66.68 ± 10.6
Feces 5.36 ± 1.43 5.22 ± 1.17 Expired CO 2 4.56 ± 1.82 3.93 ± 1.79
Carcass 24.24 ± 5.02 16.04 ± 1.87
Skin 12.78 ± 1.17 10.57 ± 4.55

Total recovery 81.2 102.4

Source: Young et al. (1977).



### Ahmed et al. (1983) administered a single oral dos e of 46.5 mg/kg AN to male SpragueDawley rats in distilled water, using 50 μ Ci/kg of either [2,3- 14 

### C]- or [1- 14 

### C]-AN as a tracer.

### DRAFT - DO NOT CITE OR QUOTE 7 Only 8–10% of administered radioactivity from the [ 2,3- 14 

### C]-AN dose had been excreted in feces 72 hours after dosing, compared with 2% from orally administered [1- 14 

### C]-AN during the same period. Thus, AN was readily absorbed at the gastrointestinal (GI) tract. The time course of radioactivity released from feces showed a major spike of [2,3- 14 

### C]-AN-derived radiolabel after 72 hours. The delayed release suggests that at least a portion of this released radioactivity may have resulted from biliary elimination of absor bed AN. The major peak of released radiolabel from [1- 14 

### C]-AN was at 24 hours postexposure, possibly indica tive of a different metabolic fate for the nitrile portion of the molec ule. Kedderis et al. (1993a) administered [2,3- 14 

### C]-AN orally to male F344 rats (0.09– 28.8 mg/kg) and male B6C3F 1 

### mice (0.09–10 mg/kg). Three to five percent of th e administered
dose was recovered in the feces of rats after 72 ho urs. Between 2 and 8% of the dose was
recovered in the feces of male B6C3F 1 

### mice. These data indicated the near-complete abso rption of the compound when administered via the oral rout e.

3.2. DISTRIBUTION The toxicokinetic experiments of Young et al. (197 7) provided data on the deposition of radiolabel when male Sprague-Dawley rats were expos ed to [1- 14 

### C]-AN via inhalation, gavage, or i.v. injection. As shown in Table 3-1, an avera ge of 11.24% of total recovered dose (10.2 mg/kg [1- 14 

### C]-AN) was obtained in the tissues when a group of four rats were exposed to 100 ppm of [1- 14 

### C]-AN for 6 hours via inhalation, and excreta were collected for 220 hours. Another group exposed to 5 ppm [1- 14 

### C]-AN had an average of 18.53% of the recovered radiolabel (0.7 mg/kg [1- 14 

### C]-AN) deposited in the tissues. When the fate of radiolabel administered by gavage was monitored, combining the recoveries of the administered radioactivity in carcass and skin gave a value of 3 7% for tissue deposition at the lower AN concentration (0.1 mg/kg) vs. 27% at the higher con centration (10 mg/kg) (Table 3-2), indicating possible metabolic saturation at the higher dose. The percentage of expired CO 2 

### was lower for the high-dose group than the low-dose group (3.93 v s. 4.56%), providing support for possible
metabolic saturation. Young et al. (1977) examined the distribution of th e radiolabel among the major organs and tissues after oral and i.v. administration of [ 1- 14 

### C]-AN. Radioactivity was detected at a range of tissues, including lungs, liver, kidneys, stomach, intestines, skeletal muscle, heart, spleen, brain, thymus, testes, skin, carcass, and b lood cells. Of these, the stomach, red blood cells (RBCs), and skin appeared to be the most impo rtant deposition sites for radiolabeled AN or its metabolites, regardless of the route of adminis tration, dose level, or time. Radioactivity found in the stomach was highest after either oral or i.v . route and was not due to unabsorbed AN since
similar results were obtained with either i.v. or o ral dosing. In a follow-up time course experiment, Young et al. (1977) administered 10 mg/kg [1- 14 

### C]-AN intravenously via the tail vein to three male Sprague-Dawley rats and examined the

### DRAFT - DO NOT CITE OR QUOTE 8 distribution of radioactivity to the stomach and ad renal glands. The level of radioactivity in the
stomach and its contents increased from 5 minutes t o 24 hours postinjection. On the other hand, radioactivity was high in the adrenal gland at 5 mi nutes but decreased 13-fold in 24 hours. Radioactivity was observed in the bile of a single bile-duct-cannulated rat, indicating biliary excretion. Maximal radioactivity in bile was obser ved after 15 minutes but declined at later time points. When both sexes of adult Sprague-Dawley rats (incl uding some pregnant animals) and two cynomolgus monkeys were exposed orally (26 mg/k g) or intravenously (13 mg/kg) to single doses of [1- 14 

### C]-AN, whole-body autoradiography from 20 minutes a fter injection primarily showed radioactivity in the bile, intestinal conten ts, and urine (Sandberg and Slanina, 1980). Other organs showing accumulation of isotope in the autoradiogram were blood, liver, kidney, lung, and adrenal cortex, in which the activity dec lined slowly during 24 hours. There also was uptake of the label in the stomach mucosa and hair follicles. Distribution of radioactivity in fetal tissue following i.v. and oral administration to pr egnant rats was uniform and showed a low uptake compared to maternal tissue. An exception w as found in the eye lens, in which the radioactivity exceeded that of the maternal blood ( Sandberg and Slanina, 1980). Jacob and Ahmed (2003a) used whole-body autoradiog raphy to examine the distribution of 11.5 mg/kg [2- 14 

### C]-AN administered orally or intravenously to male F344 rats 5 minutes and 8, 24, and 48 hours postexposure. Levels of radioa ctivity per gram of tissue were highest 5 minutes after oral dosing for stomach lumen and m ucosa, small intestine lumen and mucosa, liver, nasal mucosa, spleen, and kidney; other tiss ues (including the lung, brain, spinal cord, thyroid, and testis) had peak levels at 8 hours. C ovalently bound radioactivity was detected 48 hours later in stomach mucosa, blood, and hair f ollicles. Five minutes following i.v. administration, the highest levels of radioactivity per gram of tissue were detected in the lung, liver, spleen, small intestine lumen, kidney, epidi dymis, and adrenal gland. At 24 hours, tissues that showed peak levels included bone marrow, brain , lacrimal gland, and testis. Tissues with the highest level at 24 hours included the lung, li ver, and bone marrow. The levels of covalent bound radioactivity (nCi/g) were higher 48 hours af ter i.v. exposure compared with oral exposure, with bound radioactivity retained in live r, spleen, bone marrow, lung, kidney, and adipose tissue ranging from 2.5 to 23 times higher following i.v. exposure. The only organs that retained higher levels of covalently bound radioact ivity 48 hours following oral exposure were the stomach mucosa (3×) and heart blood (5.7×). Th e total radioactive dose retained in animals after i.v. and oral exposures were 70 and 38%, resp ectively. Jacob and Ahmed (2003a)
concluded that the metabolism and distribution of A N is greatly influenced by the portals of entry, with a higher amount of AN metabolized and e xcreted following oral exposure compared with exposure by i.v. injection. Rapid delivery of AN after i.v. treatment resulted in fast conjugation and/or covalent interaction of the pare nt compound with biological molecules, resulting in minimal metabolism and excretion in ur ine or feces.

### DRAFT - DO NOT CITE OR QUOTE 9 Sapota (1982) administered 40 mg/kg AN in saline, containing either 40 μ Ci/kg [1,2- 14 

### C]-AN or [1- 14 

### C]-AN to male Wistar rats, either via gavage or int raperitoneally. Tissue distribution of radioactivity as measured by liquid scintillation counting after intraperitoneal (i.p.) and oral administration showed that the high est specific radioactivity in tissue (nCi/g) was found in RBCs, liver, and kidneys. Tissue-wide rec overy of the radiolabel from either [1,2- 14 

### C]-AN or [1- 14 

### C]-AN at 2, 8, and 24 hours after a single oral dos e is shown in Table 3-3. Statistically significant differences were observed in the distribution of radioactivity from the two forms of labeled AN in RBCs, plasma, liver, and kidney at 8 and 24 hours after administration. More rapid loss of tissue radioact ivity in the liver, kidneys, and brain was also observed after oral administration of [1- 14 

### C]-AN than [1,2- 14 

### C]-AN. These results suggested different pathways for disposition and biotransform ation of the cyano and vinyl moieties of the
AN molecule.

Table 3-3. Percentage recovery of radioactivity in tissues of male Wistar rats following a single oral dose of radiolabeled A N

Recovered radioactivity (percent of dose in tissue) Distribution from [1- 14 C]-AN Distribution from [1,2- 14 C]-AN Target organ/ tissue 2 h 8 h 24 h 2 h 8 h 24 h
RBCs 5.36 4.82 a 5.45 5.31 7.27 a 6.72
Plasma 2.63 4.00 a 0.50 a 1.93 1.92 a 1.70 a
Liver 6.13 1.21 a 1.00 a 7.00 5.98 a 2.67 a Kidney 1.17 0.27 a 0.15 a 0.82 0.77 a 0.30 a Spleen 0.22 0.10 0.08 0.14 0.17 0.10 Lung 0.36 0.25 0.25 0.30 0.27 0.11
Brain 0.25 0.12 a 0.09 0.24 0.25 a 0.12
Total 16.1 10.8 7.5 15.7 16.6 11.7

a p < 0.05; significant difference between [ 14 CN]-AN and [1,2- 14 C]-AN at the same time point.

Source: Sapota (1982).



### In an in vivo study on the interaction of orally ad ministered 46.5 mg/kg [1- 14 

### C]-AN or 5 mg/kg K 14 

### CN with rat blood, Farooqui and Ahmed (1982) report ed that up to 94% of 14 

### C from AN in RBCs was covalently bound to cytoplasmic and membrane proteins. On the other hand, 90% of the radioactivity from K 14 

### CN in erythrocytes was bound to the heme fraction o f hemoglobin (Hb), indicating that CN
– 

### liberated from potassium cyanide (KCN) interacted with heme. In addition, distribution of 14 

### C from erythrocytes of rats treated with [1- 14 

### C]-AN showed that more than 40% of total radioactivity was local ized in membrane residue, 20–35% in the globin fraction, and 11–25% in the heme fraction. In contrast, 70% of 14 

### C from K 14 

### CN in red cells was localized in the heme fraction, 14–25% in globin, and 5–10% in cell membrane. The study authors concluded that KCN interacted with ra t blood mainly through liberation of CN
–


### ,

### DRAFT - DO NOT CITE OR QUOTE 10 which was bound to heme. Since AN was found to be mainly covalently bound to cell membranes, AN might cause damage to RBCs by mechani sms other than the release of CN
–



### . In male Wistar rats that received 40 mg/kg AN (abo ut half the median lethal dose [LD 50 

### ]) by gavage in water, peak blood levels of AN (2 μ g/mL) were detected 1.5 hours after dosing (Shibata et al., 2004). By 2.5 hours after dosing, blood levels of AN had dropped to less than
0.2 μ g/mL. Ten hours after dosing, AN was still detecta ble in blood at 50 ng/mL. Ahmed et al. (1983, 1982) studied the distribution of AN administered to male SpragueDawley rats by gavage with a dose equivalent to one -half the LD 50 

### (46.5 mg/kg). In the first experiment (Ahmed et al., 1982), the dose additiona lly contained 50 μ Ci/kg [1- 14 

### C]-AN. In the second experiment (Ahmed et al., 1983), both [2,3- 14 

### C]-AN (both carbons in the vinyl moiety were radiolabeled) and [1- 14 

### C]-AN were studied in rats administered an oral dos e of 46.5 mg/kg. Radioactivity from both forms of labeled AN or its metabolites initially was sequestered mainly in the stomach and stomach content, followed by the rest of the GI tract, including small and large intestines. The GI tract contained the h ighest levels of radioactivity up to 72 hours before beginning to decline, suggesting that AN or its metabolites were re-secreted in the stomach (Ahmed et al., 1983). In addition, radioac tivity became widely distributed in all tissues within 1–6 hours after dosing, with liver, kidney, and blood showing higher radioactivity than muscle, fat, and bone (Ahmed et al., 1983, 1982). Heart, spleen, brain, and thymus showed maximum concentrations between 3 and 6 hours. By 2 4 hours after administration, the levels of radioactivity found in liver, kidney, and lung bega n to decline, resulting in 10- to several 100-fold reductions from peak concentrations over t he course of the 10-day experiment. However, in several tissues, the decline of radioac tivity was much lower: at 10 days postdosing, radiolabel concentrations had declined only 2.4-fol d in skin, 2.9-fold in blood, 3.8-fold in spleen, and 4.9-fold in eyes, as compared with peak levels. Two differently labeled AN preparations were admini stered to rats to elucidate potential
differences in distribution and metabolism between the cyano and vinyl groups. One important finding of these studies was that radioactivity in blood was predominantly in the RBCs, especially for radioactivity from [2,3- 14 

### C]-AN. Radioactivity from [1- 14 

### C]-AN in plasma was higher than that from [2,3- 14 

### C]-AN. For radioactivity from [1- 14 

### C]-AN in RBCs, 40% was localized in membrane residue, 20–35% in the globin fraction, and 11–25% in the heme fraction. In contrast, 50% of radioactivity from [2,3- 14 

### C]-AN was in the membrane fraction, 45% in the globin fraction, and only a trace amount in the hem e fraction. In addition, compared to [1- 14 

### C]-AN administered to animals, the percentage of co valent binding of [2,3- 14 

### C]-AN to proteins was significantly higher even 72 hours after dosing. Subcellular distribution of radioactivity from [2,3

- 14 

### C]-AN was also different from that derived from [1- 14 

### C]-AN. For [2,3- 14 

### C]-AN, the cytosol fraction attained the lowest cov alent protein binding in tissues. The percentage of covalently b ound radioactivity in tissues relative to the
total increased four- to fivefold over that of the 1-hour level. At 72 hours after administration,

### DRAFT - DO NOT CITE OR QUOTE 11 the highest bound radioactivity was in the mitochon drial fractions of kidney, spleen, lung, and heart. However, in liver, the microsomal fraction contained the highest radioactivity (Ahmed et al., 1983). For [1- 14 

### C]-AN, covalent binding to macromolecules in tissue s remained unchanged over time. Cytosol contained the highest levels of tota l radioactivity in the six tissues (liver, kidney, spleen, brain, lung, and heart) selected for the st udy of subcellular distribution. Twenty to 40% of total radioactivity was bound to nuclear, mitoch ondrial, or microsomal fractions. Only 6–14% of total radioactivity was bound to cytosol over 6 hours (Ahmed et al., 1982). Farooqui and Ahmed (1983a) demonstrated the irrever sible binding of radiolabel from [2,3- 14 

### C]-AN to proteins and nucleic acids in vivo. AN wa s administered by gavage as a bolus dose of 46.5 mg/kg (one-half LD 50 

### ) in distilled water to male Sprague-Dawley rats (3 –4/group). Proteins were extracted by chloroform-isoamyl alcoh ol-phenol, and ribonucleic acid (RNA) and deoxyribonucleic acid (DNA) were isolated by hydrox yapatite chromatography. Protein binding at 1 hour after dosing was highest in spleen and st omach, followed by liver, brain, and kidney. Protein binding in spleen and stomach declined afte r 1 hour, whereas binding in liver, kidney, and brain increased. At 6 hours after dosing, prot ein binding fell to lower values in spleen and stomach but increased in other tissues. Binding pl ateaued in all tissues between 6 and 48 hours, with levels in spleen > liver > stomach > kidney > brain. Binding to RNA was highest in liver, stomach, and brain, with liver attaining a maximum by 6 hours and stomach and brain by 24 hours. The subsequent decline until 48 hours wa s also slow. DNA binding did not reach a maximum until 24 hours after dosing, with levels in brain > stomach > liver. Again, the decline of DNA-bound radioactivity during the following 24 hours was slow. Binding of AN to DNA in brain, stomach, and liver was 56, 45, and 5 μ mol AN per mol DNA, respectively, at 24 hours. The study authors also calculated a covalent bindin g index for DNA, defined as the ratio of ( μ mol AN bound per mol DNA) to (mmol AN applied per k g body weight [BW]). The values for brain, stomach, and liver were 65, 52, and 6, r espectively. Silver et al. (1987) examined the distribution of 100 mg [1- 14 

### C]-AN in female SpragueDawley rats after i.v. injection to investigate why this procedure induced acute hemorrhagic necrosis of the adrenal gland 2 hours after adminis tration and why this damage was more prominent with i.v. injection than with oral admini stration. Total radioactivity was found to be highest in the blood, liver, kidney, duodenum, and adrenals 15–90 minutes following i.v. injection of the radiolabeled compound. (This resu lt was largely in agreement with the wholebody autoradiographic findings of Sandberg and Slan ina [1980] in rats and monkeys.) Total radiolabel in blood increased over this time period , whereas the total radiolabel in other organs
remained constant or decreased with time. The leve l of covalently bound radiolabel in the adrenals was lower than that observed in blood, liv er, kidney, forestomach, and glandular
stomach.

### DRAFT - DO NOT CITE OR QUOTE 12 Silver et al. (1987) also administered the same dos e of [1- 14 

### C]-AN in water by gavage to female Sprague-Dawley rats (four/group) and investi gated the distribution of radiolabel up to 24 hours after dosing. Total radioactivity was hig hest during the first 8 hours after dosing in the blood, GI tract, liver, and kidney. At 24 hours af ter dosing, the highest total radioactivity was found in the blood, forestomach, and glandular stom ach. The highest level of covalently bound radioactivity was found in these same tissues durin g the first 8 hours after dosing and remained highest in the blood and forestomach at 24 hours af ter dosing. The study authors concluded that their observations would not support a role of cova lent binding in the hemorrhagic effect of AN on the adrenals. Rather, the initial high concentr ations of radiolabel from AN might play a role in the action of AN on the adrenal gland. However, it should be noted that in both studies, the cyano carbon, not the vinyl carbons, was labeled. The rapidity with which AN was biotransformed and distributed to the brain as its epoxide metabolite, CEO, was reported in two studie s (Kedderis et al., 1993b; Roberts et al., 1991). Roberts et al. (1991) administered 4 mg/kg AN to male F344 rats and B6C3F 1 

### mice (three/group) and measured CEO levels in blood at 0 .5, 1, 4, or 24 hours after dosing. Higher
levels of CEO were found in rat blood than in mouse blood. In addition, CEO was cleared from mouse blood in 4 hours, but was cleared in rat bloo d in 24 hours. The dose dependence of CEO
concentrations in blood was also evaluated. Blood CEO was measured 0.5 hours after oral dosing in F344 rats given either 0, 1, 4, 10, or 30 mg/kg AN and in B6C3F 1 

### mice given either 0, 1, 4, 8, or 10 mg/kg AN. Blood CEO concentrations increased with dose in rats and mice but at higher concentrations in rats at the same doses. In the first experiment by Kedderis et al. (1993b), three male F344 rats and three male
B6C3F 1 

### mice were administered 10 mg/kg AN in water by gav age. The rats were sacrificed 10 minutes after dosing, while the mice were sacrif iced 5 minutes after dosing. CEO
concentrations from blood and brains of rats and mi ce were measured. Higher CEO
concentrations were found in the blood and brains o f rats than in mice (13% higher in blood and 23% higher in brain). In addition, CEO concentrati on in rat blood 10 minutes after oral administration was about twice the concentration pr eviously reported by Roberts et al. (1991) at 30 minutes after oral dosing of 4 mg/kg AN to three male F344 rats. On the other hand, CEO
concentration in mice 5 minutes after oral administ ration was about 10 times higher than that reported at 30 minutes after oral dosing of 4 mg/kg AN to three male B6C3F 1 

### mice (Roberts et al., 1991). These results suggested that CEO was r apidly cleared in both rats and mice and that the clearance of CEO in mice was more rapid than in rats. Kedderis et al. (1993b) also administered 3 mg/kg [ 2,3- 14 

### C]-CEO orally to F344 rats and
B6C3F 1 

### mice to determine the tissue distribution of radio activity from labeled CEO after 2 and 24 hours. Radioactivity from labeled CEO was widel y distributed in major organs of rats and mice 2 hours after administration, with the highest level of radioactivity found in the stomach and intestines of rats and mice. However, radioact ivity detected in the stomach and intestines of

### DRAFT - DO NOT CITE OR QUOTE 13 mice was only about 15 and 40%, respectively, of th at detected in rats, suggesting that mice absorbed CEO more rapidly than rats (Kedderis et al ., 1993b). By 24 hours, radioactivity decreased by 71–90% in all tissues, including the b rain, liver, and lung. Stomach and intestines continued to retain the highest level of radioactiv ity, probably due to covalent binding of CEO to macromolecules in these organs. Burka et al. (1994) monitored the tissue distribut ion of radiolabel derived from [2- 14 

### C]-AN after oral dosing at 0.87 mmol/kg (46 mg/kg) to untreated, phenobarbital (PB)-pretreated, or SKF 525A pretreated male F344 r ats (three/group). PB induces a number of CYP450 isozymes, including CYP2B1 and CYP2B2, where as SKF 525A is a general inhibitor of CYP450. After 24 hours, about 10% of the admini stered dose in untreated rats was present in the blood with a further 4% sequestered in the tiss ues. In PB-pretreated rats, a 40% increase in AN-derived radioactivity was found in both the live r and glandular stomach when compared with rats treated with AN alone, with no changes in other tissues. However, AN-derived radioactivity in most tissues of SKF 525A pretreate d rats were up to 278% higher, suggesting the involvement of CYP450 metabolism in the disposition of AN and/or its metabolites. (AN reacts more rapidly with tissue nucleophiles than CEO; hen ce, decreasing its oxidative metabolism to CEO would increase tissue binding of radiolabel.) Because PB pretreatment had little effect on tissue distribution, the isoforms of CYP450 induced by PB are probably not the ones involved in
the metabolism of AN. It is known that AN is metab olized by CYP2E1, not CYP2B1 or CYP2B2, to CEO (see Section 3.3). PB might increas e AN-derived radioactivity in the liver and stomach by inducing other enzymes, such as nicotina mide adenine dinucleotide phosphate (NADPH)-cytochrome CYP450 reductase. Ahmed et al. (1996a) monitored the tissue distribu tion of AN-derived radioactivity in F344 rats (four/group) up to 48 hours following i.v . injection of 11.5 mg/kg of [2- 14 

### C]-AN (50 μ Ci/kg). The study authors used whole-body autoradi ography to chart a time course of tissue deposition and obtained the highest levels of activ ity in lung (998 nCi/mg), intestinal contents (752 nCi/mg), liver (713 nCi/mg), and spleen (539 n Ci/mg) 5 minutes after dosing. Other tissues with high radiolabel at this time point were the ki dney (283 nCi/mg), epididymis (266 nCi/mg), adrenal gland (241 nCi/mg), intestinal mucosa (245 nCi/mg), heart-blood (166 nCi/mg), bonemarrow (178 nCi/mg), thyroid (121 nCi/mg), adipose tissue (169 nCi/mg), and lacrimal gland (122 nCi/mg), while the brain, spinal cord, and tes tis had the lowest levels of radioactivity. At 8 hours after dosing, the contents of the large int estine, especially the cecum, had the highest level of radioactivity (852 nCi/mg). Radioactivity in brain (92 nCi/mg), lacrimal gland (294 nCi/mg), and thyroid (211 nCi/mg) peaked at 24 hours after dosing, while radioactivity level in bone marrow (698 nCi/mg) peaked at 48 hour s. Covalent bound radioactivity, as determined after acid-extraction techniques on free ze-dried sections, was observed in the spleen, liver, bone marrow, and lung.

### DRAFT - DO NOT CITE OR QUOTE 14 3.3. METABOLISM A proposed scheme for the metabolic pathways of AN in mammals is shown in Figure 3-1. The scheme has been developed as a res ult of studies on the identification of urinary metabolites following acute exposure (Fennell and S umner, 1994; Kedderis et al., 1993a; Fennell et al., 1991; Turner et al., 1989; Müller et al., 1 987; Tardiff et al., 1987; Gut et al., 1985; Kopecky et al., 1980; Langvardt et al., 1980), meas urements of the in vivo modulation of AN-induced toxicological and biochemical changes by enzyme inhibitors or inducers (Wang et al., 2002; Sumner et al., 1999; Burka et al., 1994; Kedderis et al., 1993c; Pilon et al., 1988a, b; Ghanayem and Ahmed, 1986; Ahmed and Abreu, 1981; Ab reu and Ahmed, 1980), determination 1996a), and analysis of metabolites formed in vitro by subcellular fractions of liver, lung, and kidney in response to AN administration (Mostafa et al., 1999; Kedderis et al., 1995; Kedderis and Batra, 1993; of the subcellular distribution of metabolic products of AN (Nerland et al., 2001; Ahmed et al., Roberts et al., 1991, 1989; Hog y, 1986; Geiger et al., 1983; Ahmed and Abreu, 1981; Guengerich et al., 1981; Abreu and Ahm ed, 1980).

CH 2 CH O

CN 

### N C H 2 

### C CH

CYP2E1 Acrylonitrile 

### RSCH 2 

### CH 2 

### CN

GS CH 2 

### CH 2 

### CN

S CH 2 

### CH 2 

### CN HOOC CH 2 

### S CH 2 

### CH 2 

### CN

N-acetyl-S-(2-cyanoethyl)cysteine 

### OH

CHO + CN - 

### SCN Thiocyanate rhodanese



### GS CHCN CH 2 

### OH

S CHCN

CH 2 

### OH

N-acetyl-S-(1-cyano-2-hydroxyethyl)cysteine GSH



### GS CH 2 

### CHCN

OH

Cyanohydrin 

### CN - 

### SCN Thiocyanate rhodanese



### GS CH 2 

### CHO S-2-oxoethylglutathione

GSH



### Cys S CH 2 

### COOH

S CH 2 

### COOH S-(carboxymethyl)cysteine

N-acetyl-S-(carboxymethyl)cysteine 

### S CH 2 

### CH 2 

### OH N-acetyl-S-(2-hydroxyethyl)cysteine



### HOOC CH 2 

### S

O

CH 2 

### COOH Thionyldiacetic acid 

### CH 2 

### O H

NC

Cyanoacetaldehyde spontaneous rearrangement



### CH 2 

### O OH

NC

Cyanoacetic acid 

### CH 2 

### NC H H

OH Cyanoethanol 

### CH 2 GSH

Cyanide Cyanide



### Ac-N-Cys Ac-N-Cys

Ac-N-Cys Glycol aldehyde epoxide hydrolase glutathione

S-transferase



### Ac-N-Cys 2-Cyanoethylene oxide S-(2-cyanoethyl)thioacetic acid

S-(2-cyanoethyl)glutathione



### Source: National Toxicology Program (NTP) (2001).

Figure 3-1. Scheme for the metabolic transformatio n of AN.

### DRAFT - DO NOT CITE OR QUOTE 15 Primary components of the scheme are formation of CEO by the action of mixed function oxidases (predominantly CYP4502E1), detoxification of AN by interaction with GSH, and covalent binding of AN reactive metabolite to other biological macromolecules. In rats, CYP2E1 is present in the liver and widespr ead among other tissues. This isoform can be induced in the tongue, esophagus, forestomac h squamous epithelia (Shimizu et al., 1990), and intestinal mucosa (Subramanian and Ahmed, 1995) . It is present, albeit at levels 10– 20 times lower than in liver, in such tissues as ki dney and lung. It is also present in the brain (Geng and Strobel, 1993; Sohda et al., 1993). The formation of CEO has important implications for the toxicity of AN, because the intermediate ha s been proposed as the principal carcinogenic metabolite of AN. However, CEO can undergo a numbe r of further transformations. These
include the interaction with GSH to form a series o f cysteine or N-acetyl cysteine derivatives and the production of cyanide via the action of epoxide hydrolase (EH). Subsequent detoxification of cyanide to thiocyanate is thought to occur under the action of rhodanese (Kopecky et al., 1980).

3.3.1. Oxidation of AN to CEO
Evidence for the oxidation of AN to CEO and its su bsequent transformations came from a number of studies. Abreu and Ahmed (1980) studie d the in vitro conversion of AN to cyanide in subcellular fractions of liver from Sprague-Dawl ey rats (also reported in Ahmed and Abreu [1981]). The metabolic activity was localized in t he microsomal fraction and required NADPH, MgCl 2 

### , and oxygen for maximal activity. Determination o f the kinetic parameters (K m 

### and V max 

### ) of the transformation of AN to cyanide pointed to a higher affinity and faster rate of product formation in microsomes from rats pretreated with C YP450-inducing agents, such as Aroclor 1254 and PB. (Six AN concentrations rangin g from 10 to 300 mM were used for each preparation.) The K m 

### values calculated for the PB and Aroclor 1254 preparations were 54.8 and 40.9 mM, respectively, and were lower than the cont rol (190 mM). Pretreatment of rats or addition to incubation mixtures with agents that in hibit CYP450 activity, such as SKF 525A or cobalt chloride, reduced the amount of cyanide form ed by rat liver microsomes. Abreu and Ahmed (1980) studied the effect on cyani de formation when 1,1,1-trichloropropane-2,3-oxide (TCPO), a specific inhibitor of E H, was added to the microsomal incubation mixtures. Production of cyanide was dose-dependent ly reduced to 19% of control levels at
TCPO concentration of 1 × 10 -2 

### M. Abreu and Ahmed (1980) also tested the effect of sulfhydryl compounds on microsomal metabolism of AN, as measur ed by the rate of cyanide formation. Only cysteamine decreased cyanide formation; other sulfhydryl compounds, including GSH and cysteine, enhanced the rate of cyanide formation fr om AN. Abreu and Ahmed (1980) suggested that probably more than one step was involved in the enzymatic conversion of AN to cyanide. The study a uthors proposed the initial product of AN oxidation to be CEO, which could then undergo a num ber of alternative transformations, one of

### DRAFT - DO NOT CITE OR QUOTE 16 which would be non-enzymatic conversion to cyanide. That another transformation might involve EH was indicated by the decrease in cyanide formation following administration of the inhibitor TCPO. Because cyanide production was enh anced in the presence of sulfhydryl compounds, such as GSH, chemical interaction of CEO with GSH could lead to formation of cyanohydrin. Rearrangement of this cyanohydrin to an aldehyde could result in the release of cyanide. Cysteamine might diminish cyanide formati on due to its inhibition of CYP450- dependent metabolism (Buckpitt et al., 1979). Geiger et al. (1983) studied the conversion of AN t o its metabolic products in isolated rat hepatocytes and demonstrated the formation of CEO a nd its hydrolysis to cyanide, which itself was transformed and detected as thiocyanate.
In vitro incubation of AN with liver microsomes iso lated from male F344 rats pretreated with inhibitors or inducers of specific members of the CYP450 family of mixed function oxidases indicated that CYP2E1 is the major catalys t in the oxidation of AN to CEO (Kedderis et al., 1993c). The rate (V max 

### ) at which rat liver microsomes oxidized AN to CEO was increased
more than fivefold from V max 

### of 366 pmol CEO/minute-mg for untreated rats follo wing acetone pretreatment, although K m 

### was increased from 11 to 19 μ M. Because acetone is a potent inducer of CYP2E1, the data suggest that this isoform is a primary catalyst of AN epoxidation in rats.
Treatment with β -naphthoflavone to induce CYP1A1 and CYP1A2 or with dexamethasone (DEX) to induce the CYP3A enzymes increased V max 

### only less than twofold, but K m 

### was increased by 3.5 and 5.2-fold, respectively, for AN epoxidation in these two pretreatment systems. Treatment with PB to induce CYP2B1 and CY P2B2 slightly decreased the V max 

### but
increased the K m 

### in microsomes from rats. These studies demonstrat ed that other forms of CYP450 (CYP2B1, CYP2B2, and the 3A enzymes) can oxi dize AN but with specific activities
much lower than CYP2E1. The effect of a number of CYP450 inhibitors on epo xidation of 1.2 mM AN by rat hepatic microsomes was investigated (Kedderis et al ., 1993c). Neither SKF 525A nor metyrapone were effective inhibitors, retaining 87% of control activity. After treatment of rats with DEX or PB, SKF 525A became a more effective in hibitor, retaining 45 and 47% of control activity. Metyrapone also became a more effective inhibitor of epoxidation of AN after DEX treatment. The CYP450 ligand, 1-phenylimidazole, w as a potent inhibitor of AN epoxidation (4% of control activity). Chlorzoxazone (27%), eth anol (42%), and diethyldithiocarbamate (17%) also inhibited this pathway. The changes in the degree of inhibition of epoxidation of AN following DEX and PB treatments could be interprete d as multiple CYP450 enzymes from rat hepatic microsomes were capable of oxidizing AN. Antibodies to CYP2E1 (sheep or goat anti-rabbit CYP 2E1) inhibited more than 85% of AN epoxidation in liver microsomes from untreated o r acetone-treated rats but only 40 and 60% inhibition following DEX and PB treatment, respecti vely (Kedderis et al., 1993c), suggesting that CYP450 enzymes other than CYP2E1 might partici pate in the epoxidation. However, it

### DRAFT - DO NOT CITE OR QUOTE 17 should be noted that the AN concentration in these in vitro studies was high (1 mM). Forms of CYP450 enzymes other than CYP2E1 might have been re cruited to AN metabolism. Kedderis et al. (1993c) also investigated the kinet ics of the epoxidation of 1.2 mM AN by using human hepatic microsomes. K m 

### and V max 

### values for oxidation of AN by liver microsomes from six uninduced individuals ranged from 12 to 18 μ M and from 129 to 315 pmol/minute-mg, respectively. Antibodies to CYP2E1 produced 58–70% inhibition of AN epoxidation catalyzed by the six human liver microsomal preparations. Th is suggests that, while CYP2E1 was the major catalyst of AN epoxidation in humans, other i soforms of CYP450 may also be involved. Sumner et al. (1999) investigated the role of CYP45 0 in the metabolism of AN in mice. Three male wild-type (WT) mice and three to four ma le CYP450 2E1-null mice were treated orally with either 2.5 mg or 10 mg/kg of [1,2,3- 13 

### C] AN. Urinary metabolites in samples collected over 24-h were characterized using 13 

### C nuclear magnetic resonance (NMR). In WT mice, urinary metabolites of CEO predominated, with metabolites derived from GSH conjugation at the 3-carbon of CEO accounting for 6 7–71%. Metabolites from GSH conjugation
at the 2-carbon accounted for about 13%. Metabolit es from direct GSH conjugation with the parent compound, AN, accounted for 15–21%. In the urine of CYP2E1-null mice, however, only metabolites from direct GSH conjugation were d etected. Sumner et al. (1999) interpreted their data as indicating that CYP2E1 may be the onl y CYP450 involved in the metabolism of AN
in mice. Subramanian and Ahmed (1995), attempting to charac terize the specific intestinal toxicity of AN, incubated microsomes isolated from male Sprague-Dawley rat intestinal mucosa in vitro with AN in the presence of NADPH. AN meta bolism to cyanide was enhanced by the addition of sulfhydryl compounds such as GSH, cyste ine, and D-penicillamine. AN metabolism to cyanide was also enhanced following the inductio n of microsomal proteins (MPs) by treating rats with PB (inducer of CYP2B1), β -naphthoflavone (inducer of CYP1A1), and 4-methylpyrazole (inducer of CYP2E1). AN metabolis m to cyanide was inhibited to 8 and 20% of control, respectively, when dimethyl sulfoxide ( DMSO) or ethanol (competitive inhibitors of CYP2E1) was added to the incubation mixtures. Subramanian and Ahmed (1995) showed that the intest inal CYP450 isoform had a high affinity for AN, with a K m 

### of 1.1 μ M and a V max 

### of 1,250 pmol/mg protein/minute. Addition of DMSO in varying concentrations (final 30 mM) increa sed the K m 

### of the reaction to 10 μ M, but
V max 

### remained unchanged. Since DMSO is a specific subst rate and competitive inhibitor for CYP2E1, these studies indicated that CYP2E1 was the main CYP450 isoform that bio-activates AN in the intestine. In addition, anti-P450 3a imm unoglobulin (Ig)G (which cross-reacts with rat CYP2E1) caused a concentration-dependent inhibition of the metabolism of AN to cyanide in the ethanol-induced intestinal microsomes (Subramanian and Ahmed, 1995). These results showed that CYP2E1 was the main intestinal mucosa enzyme m etabolizing AN to cyanide.

### DRAFT - DO NOT CITE OR QUOTE 18 Similarly, Abdel-Aziz et al. (1997) demonstrated t he metabolism of AN to cyanide when
AN was incubated in vitro with NADPH and a microsom al fraction prepared from SpragueDawley rat testis. The V max 

### of this reaction was 65 pmol CN
– 

### /mg protein/minute, and the K m 

### was 88.6 μ M AN. Addition of SKF 525A or benzimidazole (compe titive inhibitors of CYP450)
to the incubation mixture inhibited the formation o f cyanide, whereas microsomes obtained from PB-treated rats increased activation of AN to cyani de. Thus, AN was metabolized in rat testis
via CYP450 mixed function oxidase. Addition of GSH , L-cysteine, D-penicillamine, or 2-mercaptoethanol also enhanced the release of cyan ide from AN. The capability of rat kidney to metabolize AN to cy anide was demonstrated by Mostafa et al. (1999) in an in vitro study that investigate d the mechanism by which AN caused renal toxicity. In renal subcellular fractions from Spra gue-Dawley rats, the metabolism of AN to cyanide was highest in the microsomal fraction. An NADPH-generating system in the presence of magnesium ions was required for maximal activity . The V max 

### of this reaction was 118 pmol
CN – 

### /mg protein/minute, and the K m 

### was 160 μM AN. Metabolism of AN to cyanide was increased when microsomes were obtained from PB-, e thanol-, 4-methylpyrazole-, and 3-methylcholanthrene-treated rats. On the other ha nd, addition of SKF 525A or benzimidazole
to the incubation mixture inhibited AN metabolism. These data suggested that AN was metabolized in the kidney via a CYP450-dependent mi xed function oxidase system. Addition of GSH, L-cysteine, cysteamine, D-penicillamine, or 2- mercaptoethanol to the incubation mixture
enhanced AN metabolism. Ahmed and Patel (1981) carried out a series of sing le-dose gavage experiments on male Sprague-Dawley rats and male Swiss mice at fraction s of the LD 50 

### values of AN and KCN. (The
LD 50 

### of AN is 93 mg/kg in rats and 27 mg/kg in mice; the LD 50 

### of KCN is 10 mg/kg in rats and 8.5 mg/kg in mice.) Cyanide was measured and detec ted in blood, liver, kidney, and brain of
both rats and mice 1 hour after administration in a dose-dependent manner. However, cyanide
concentrations from metabolism of one LD 50 

### AN in blood and tissues of rats were significantly lower than those produced from one LD 50 

### of KCN. On the other hand, comparable concentrations of cyanide in blood and tissues were observed after one LD 50 

### AN or KCN was
administered to mice. Blood and liver contained hi gher amounts of cyanide per unit volume than kidney and brain (the other two organs evaluated). Observed signs of toxicity were also different in r ats and mice administered an LD 50 

### of AN. Rats developed severe cholinomimetic signs inc luding salivation, lacrimation, diarrhea, wheezing on expiration, and peripheral vasodilatati on within 10 minutes after administration of 93 mg/kg AN. These signs were not observed in rats treated with KCN. Severe central nervous system (CNS) effects such as depression, convulsion s, and asphyxia were observed in rats 10– 20 minutes after treatment with 10 mg/kg KCN (LD 50 

### ). These CNS signs of cyanide toxicity
were observed in AN-treated rats 2–3 hours after do sing. No physiological adverse effects were observed in rats receiving 0.25 LD 50 

### AN. Mild salivation, diarrhea, and vasodilation w ere

### DRAFT - DO NOT CITE OR QUOTE 19 observed after one-half LD 50 

### AN in rats. However, in mice treated with equitox ic dose (LD 50 

### 27 mg/kg) AN, CNS signs identical to those observed after KCN was administered were observed. These results demonstrated species diffe rences in the toxicity and metabolism of AN. Moreover, Ahmed and Patel (1981) showed that pretre atment of rats with Aroclor 1254 and PB increased AN metabolism to cyanide in rats, and pretreatment of rats with CoCl 2 

### or SKF 525A decreased blood cyanide concentrations. These results showed that the AN transformations demonstrated by Abreu and Ahmed (19 80) in vitro also could take place in vivo. In addition, increased metabolism of AN to cyanide would increase CNS effects. However, acute AN toxicity was also manifested as cholinomim etic signs, which were not from cyanide. Shibata et al. (2004) employed headspace gas chrom atography to simultaneously measure blood levels of AN and its metabolite, hydrogen cya nide, following oral administration to rats. Plasma and urinary thiocyanate concentrations were also measured by the colorimetric method. Male Wistar rats that received 40 mg/kg AN (about h alf the LD 50 

### ) by gavage in water showed toxic signs such as tachycardia 1 hour later. Peak blood levels of AN (2 μ g/mL) and cyanide (0.7 μ g/mL) were detected 1.5 hours after dosing. By 2.5 hours after dosing, blood levels of AN had dropped to less than 0.2 μ g/mL and blood levels of cyanide decreased to 0.1 μ g/mL; at that time, thiocyanate was detected in plasma (20 μ g/mL). Plasma thiocyanate concentrations rose over time, peaking at 5 hours (31.3 μ g/mL). At the same time, excretion of thiocyanate in urine began to increase significantly. Ten hours after d osing, AN was still detectable in plasma at 50 ng/mL, but cyanide had decreased to a background level of about 5 ng/mL. The cumulative urinary elimination of thiocyanate gradually increa sed, and at 10 hours, about 1.2 mg thiocyanate
was excreted into the urine. This amount was calcu lated to be 7% of the total administered AN. Urinary AN level was not measured. The capacity for formation of CEO from AN has been demonstrated in F344 rat liver microsomes, lung microsomes, and isolated lung cell s. The rate of CEO formation in rat lung was cell specific, with the Clara cell-enriched fra ction having a rate of CEO formation 7 times greater than other cell fractions (Roberts et al., 1989). The overall rate of CEO formation was about 15 times greater in the livers than the lungs (Roberts et al., 1989). Roberts et al. (1991) provided data on the kinetics of CEO formation in liver and lung microsomes isolated from male F344 rats, B6C3F 1 

### mice, and humans (Table 3-4). While CEO was produced in vitro by lung and liver microsomes in both rats and mice, the metabolite was produced at a greater rate in liver compared with l ung and in mice vs. rats. These data potentially implicated the liver as the primary sit e of CEO formation after oral challenge with AN but suggested differences in the kinetics of CEO formation between species. The rate of
CEO formation in microsomes isolated from human liv ers was comparable to that of F344 rats,
but about 4 times lower than that of B6C3F 1 

### mice. The average rate of CEO formation in liver microsome samples from six human donors was 501 ± 1 12 pmol/minute-mg protein. (The almost eightfold variation in enzymatic activity am ong these human samples appeared to

### DRAFT - DO NOT CITE OR QUOTE 20 correlate with the amount of CYP450 in each prepara tion.) However, after oral administration of AN, the concentration of CEO in mouse blood was abo ut one-third that in rat blood at all doses and time points tested. Thus, blood CEO concentrat ion did not correlate with rate of microsomal CEO formation, suggesting that species differences in detoxification of CEO might play a role in determining CEO concentrations in blood. The singl e human lung microsome sample tested in the study formed 0.55 pmol CEO/minute-mg protein, w hich was much lower than that for rat liver or lung microsomes.

Table 3-4. Apparent kinetic parameters of CEO form ation from AN in B6C3F1 mice, F344 rats, and humans

Tissue Species V max (pmol/min-mg protein) K m (μM) a Mouse 2,801 a 67
Rat 667 a 52 Liver

Human 501 b Not available

Mouse 570 a 1,229
Rat 45 a 1,854 Lung

Human 0.55 c Not available

a Values are the mean of eight replicates.
b Value is the mean of six human donors.

c Value is from one human donor.

Source: Roberts et al. (1991).



### Guengerich et al. (1981) used a reconstituted enzy me system containing purified rat liver CYP450 and NADPH-P450 reductase and a NADPH-generat ing system to oxidize AN in vitro to a metabolite that they identified colorimetrical ly as CEO. The extent of CEO accumulation was decreased by the addition of purified rat liver EH to the incubation medium. When 0.5 mM
CEO was incubated with 30 μ g/mL purified EH, the rate that CEO was hydrolyzed was 5.5 nmol/minute. The rate of disappearance of CEO (due to nonenzymatic hydrolysis) was 1.7 nmol/minute in the absence of EH or in the pres ence of inactivated EH. HCN was released at a rate of 1.5 nmol/minute during the hydrolysis of CEO by EH. (The rate of HCN release was 0.2 nmol/minute in the absence of EH.) The study a uthors suggested that the reason the HCN release was not stoichiometric with epoxide disappe arance might be due to a finite level of cyanohydrin existing in solution. A K m 

### of 0.8 mM and a V max 

### of 300 nmol/minute-mg based on disappearance of CEO was estimated for the hydrolys is of CEO by purified rat liver microsomal EH. The half-life of CEO in 0.1 M potassium phosph ate was estimated to be about 2 hours at 37°C (Guengerich et al., 1981). Kopecky et al. (1980) also investigated the role of EH and the generation of hydrogen cyanide from AN metabolism. AN was incubated in vi tro with liver microsomes isolated from female Wistar rats, with and without cofactors (NAD P, Mg 2+ 

### , etc.) for 60 minutes. After the

### DRAFT - DO NOT CITE OR QUOTE 21 incubation, the mixtures were adjusted to either pH 1.8 (acidic processing) or 6.3 (alkaline processing). Cyanide released, in the presence of cofactors, was found to be fourfold higher under alkaline processing condition than acidic pro cessing condition. The role of EH in AN metabolism in rats was supported by the increase in cyanide released after alkaline processing, indicating the existence of a cyanohydrin intermedi ate (glycolaldehyde cyanohydrin) in the biotransformation of AN. (Cyanohydrins generally d ecompose spontaneously to hydrogen cyanide and a carbonyl compound at pH higher than 7 .) Moreover, when 3,3,3-trichloropropylene oxide (TPO), a potent inhibitor of EH, wa s added to the incubation mixture, the conversion of AN to cyanide was decreased by 70%. This result also provided evidence for the participation of the cyanohydrin in AN metabolism b ecause the hydration of CEO to glycolaldehyde cyanohydrin was significantly inhibi ted by TPO. Kedderis and Batra (1993) compared the rates of CEO hydrolysis, enhanced by liver cytosol and microsomes from rats, mice, and humans, to the background rate of non-enzymatic hydrolysis displayed by the chemical. [2,3- 14 

### C]-CEO was incubated at pH 7.3 and 37°C for 5 minutes with liver cytosol or microsomes. [2,3- 14 

### C]-CEO and its hydrolysis products were separated by high performance liquid chromatography (HPLC). The identity of the hydrolysis products could not be determined and did not corres pond to aldehydes. Human hepatic microsomes enhanced the formation of hydrolysis pro ducts of CEO, whereas both human hepatic cytosol and liver cytosol and microsomes from F344 rats and B6C3F 1 

### mice had no effect on hydrolysis product formation from CEO. The study a uthors concluded that rodent hepatic microsomal and cytosolic EHs were not active toward CEO, contrary to conclusions developed by Guengerich et al. (1981) on rat purified microso mal EH and the conclusions by Kopecky et al. (1980). One possible explanation that EH activity was not o bserved by Kedderis and Batra (1993) in microsomes from rats and mice was that th eir enzymatic reactions had not been optimized. No cofactors were used in the incubatio n mixture, and the incubation duration was only for 5 minutes. Both Kopecky et al. (1980) and Guengerich et al. (1981) used an NADPHgenerating system in their incubation mixture. Kedderis and Batra (1993) also showed that the heat -labile human EH activity was inhibited by the specific inhibitor, 1,1,1-trichlor opropene oxide (median inhibitory concentration [IC 50 

### ] of 23 μ M), indicating that EH was the catalyst in the hydr olysis of CEO. The half-life of CEO in sodium phosphate buffer (pH 7.3), as estimat ed from hydrolysis by human liver microsomes, was 99 minutes. Estimated K m 

### using liver microsomes from six individuals ranged
from 0.6 to 3.2 mM. V max 

### ranged from 8.3 to 18.8 nmol hydrolysis products/m inute-mg protein. The affinity of the human liver microsomal EH for C EO was relatively low, suggesting that the contribution of the hydrolysis pathway to the clear ance of CEO would be small at low substrate concentrations. Increase in microsomal hydrolysis was observed after treatment of mice and rats

### DRAFT - DO NOT CITE OR QUOTE 22 with PB or acetone, suggesting that CEO hydrolysis is inducible. However, treatment of rats and mice with AN did not induce hepatic EH activity tow ards CEO (Kedderis and Batra, 1993). Studies that demonstrated that EH is present in rat s and humans are also available. Immunoblot analysis of MPs was used by de Waziers e t al. (1990) to measure EH in different organs and tissues of rats and humans. They report ed that EH occurred in rat liver microsomes
at 165 μ g/mg protein and in human liver microsomes at 170 μ g/mg protein. Therefore, the
concentrations of EH in MP are similar in rats and humans. Guengerich et al. (1979) also reported that multiple forms of EH exist in rats an d humans. EH activity was demonstrated in mice in a recent st udy, contrary to the conclusion by Kedderis and Batra (1993). El Hadri et al. (2005) demonstrated that microsomal EH was present in WT mice, which metabolized AN administered by ga vage to cyanide in a dose- and timedependent manner. Blood cyanide levels in microsom al EH-null mice treated with a gavage dose of 0.047–0.38 mmol/kg AN were lower than level s in similarly treated WT mice. Blood cyanide level was also largely abolished in CYP2E1- null mice and in WT mice pretreated with a nonselective CYP inhibitor, 1-aminobenzotriazole (A BT), confirming that CYP2E1 was the key enzyme for the epoxidation of AN and the subsequent formation of cyanide. AN-treated CYP2E1- and mEH-null mice showed less severe sympto ms of cyanide poisoning (labored breathing, lethargy, and trembling) than similarly treated WT mice (El Hadri et al., 2005). Significantly higher levels of AN-derived blood cya nide levels were observed in male mice than in female mice, suggesting gender-related differenc es in toxicity. Western blot analysis also demonstrated that expression of soluble EH was grea ter in male than female mice. Detection and identification of urinary metabolite s of AN from male F344 rats or B6C3F 1 

### mice exposed orally to [1,2,3- 13 

### C]-AN (10 or 30 mg/kg for rats, 10 mg/kg for mice), using

13 

### C NMR spectroscopy, also offered more information o f its possible metabolic interactions (Fennel and Sumner, 1994; Fennel et al., 1991). As detailed in Section 3.4, some of the hypothetical metabolites of AN shown in Figure 3-1 were detected in the urine of animals exposed to AN. A major urinary metabolite in rats was N-acetyl-S-(2-cyanoethyl)cysteine, from conjugation of AN with GSH. Other metabolites, for med following oxidation of AN to CEO and subsequent conjugation to GSH, were identified as N -acetyl-S-(2-hydroxyethyl)cysteine, thiodiglycolic acid, S-carboxylmethylcysteine, and thionyldiacetic acid, all derived from addition of GSH to the 3-position of CEO. Thiocyanate was d etected in urine as a metabolite of released cyanide. Moreover, N-acetyl-S-(1-cyano-2-hydroxyet hyl)cysteine was formed after addition of GSH to the 2-position of CEO (Fennel and Sumner, 19 94). These metabolites were also found in
mouse urine. Species differences in the extent of AN metabolism via oxidation to CEO, and subsequent conjugation of CEO with GSH, may exist. Fennell et al. (1991) and Fennell and Sumner (1994) noted differences in the relative abu ndance of these urinary metabolites in mice compared with rats. After oral administration of 1 0 mg/kg AN to mice, 80% of the urinary

### DRAFT - DO NOT CITE OR QUOTE 23 metabolites were derived from CEO, most notably thi odiglycolic acid and S-(carboxymethyl)- cysteine. By contrast, these metabolites made up o nly 60% of metabolites in the urine from rats administered orally with 10 or 30 mg/kg AN. This d ifference indicated that more CEO was produced in the mouse than in rats. In addition, t he ratio of metabolites derived from glutathione conjugation of CEO at the 2- and 3-positions determ ined the amount of cyanide released, since cyanide is released from CEO metabolites conjugated at the 3-position. This ratio was 0.43 in rats and 0.21 in mice, indicating that a greater pe rcentage of the CEO produced in mice was metabolized to release cyanide. Thus, mice were li kely to be exposed to a higher cyanide level produced from CEO, possibly accounting for the grea ter acute toxicity of AN in the mouse (Fennel and Sumner, 1994). Wang et al. (2002) confirmed the central role of CY P2E1 in the metabolism of AN to cyanide via CEO. Male WT and CYP2E1-null mice were dosed by gavage with 0, 2.5, 10, 20, or 40 mg/kg AN, and cyanide was measured in blood and tissues. Expression of CYP2E1 and EH was monitored concurrently using Western blot techn iques. Cyanide concentrations in blood and tissues of AN-treated WT mice increased dose depend ently but remained at background levels in
CYP2E1-null mice or control WT mice. Results from Western blots showed CYP2E1 to be well expressed in the liver, kidney, and lung of WT mice and not detected in tissues of CYP2E1-null mice. EH was equally expressed in both WT and CYP2 E1 mice, supporting the hypothesis that CYP2E1-mediated oxidation of AN is an early step in the metabolism of AN to cyanide. The role of cyanide in the acute toxicity of AN was con firmed by the lack of acute symptoms of AN toxicity in CYP2E1-null compared with WT mice. Pre treatment of WT mice with a universal CYP450 inhibitor, ABT, likewise blocked cyanide for mation and abolished the symptoms of acute toxicity. Wang et al. (2002) concluded that the metabolism of AN to CEO was exclusively catalyzed by CYP2E1.

3.3.2. Interaction of AN with GSH A succession of research findings showed that AN c onjugates with GSH, both nonenzymatically or by being catalyzed by glutathione transferase. Young et al. (1977) suggested that since the toxicity of AN was due to the parent compound (AN) or its oxidative metabolites, the cyanoethylation of sulfhydryl-containing compou nds, such as GSH or cysteine, by AN represented a detoxification mechanism. This metab olic pathway was shown indeed to play a role in the detoxification of AN (Ghanayem and Ahme d, 1986; Ghanayem et al., 1985; Appel et al., 1981). The toxicity of AN would be expected t o increase in severity as the GSH level becomes depleted (Benz et al., 1997a). Kopecky et al. (1980) administered 0.75 mmol/kg AN or 0.5 mmol/kg [1- 14 

### C]-AN to female Wistar rats by different routes (oral, i.p., subcutaneous [s.c.], and i.v.) and measured radioactivity and thiocyanate excreted in the urine . “Non-thiocyanate” metabolites excreted in
urine constituted about two-thirds of the administe red dose. Paper chromatography of the

### DRAFT - DO NOT CITE OR QUOTE 24 metabolites in urine identified AN mercapturic acid as the key metabolite. Kopecky et al. (1980) proposed that there were at least two pathways for AN metabolism. The minor route was oxidative metabolism to cyanide, which was further metabolized to thiocyanate and other “nonthiocyanate” metabolites. The major route was conj ugation with glutathione, catalyzed by glutathione S-alkenetransferases, to N-acetyl-S-(2- cyanoethyl)cysteine. Further support for this proposition came from Geig er et al. (1983), who studied AN metabolism in isolated F344 rat hepatocytes. GSH l evels and AN-protein binding were measured after incubating rat hepatocytes with [1- 14 

### C]- or [2,3- 14 

### C]-AN. GSH-adduct levels were determined by chromatographic procedures of al iquots of the trichloroacetic acid supernatant. Exposure to AN at 5 or 10 mM resulted in decrease of GSH levels to 15–20% of controls within 10 minutes. The primary radiolabel ed product was S-(2-cyanoethyl)glutathione, and not S-(2-oxoethyl)GSH (the compound formed by r eaction of CEO with GSH in the presence of purified GSH transferase).
Indirect evidence for the involvement of GSH in the metabolism of AN was provided by Langvardt et al. (1980, 1979), who used gas chromat ography-mass spectrometry and gas chromatography-infrared spectroscopy to identify ur inary components in male Sprague-Dawley rats 16 hours after exposure to [1- 14 

### C]- or [2,3- 14 

### C]-labeled AN by gavage. They identified two major components: the first was N-acetyl-S-(2-cyan oethyl)cysteine, which they assumed to be a product of AN conjugation with GSH, and the other w as thiocyanate. A third metabolite, N-acetyl-S-(2-cyanoethyl)cysteine, was tentatively identified and was proposed by Langvardt et al. (1980) to have resulted from the action of GSH on the epoxide intermediate. The authors speculated that the detoxification of AN likely inv olved conjugation with GSH, and the toxicity of AN was likely affected by the status of GSH pool s in target tissues, since a rapid and dosedependent decrease in GSH stores in the liver, lung s, kidney, and adrenals was observed by Szabo et al. (1977) after i.v. injection of 1–15 mg /100 g AN to Sprague-Dawley rats. A sharp
decrease in cerebral GSH concentrations occurred be tween 5 and 15 mg/100 g AN and correlated with the occurrence of mortality. On the other han d, oral dosing of 0.002–0.05% AN to rats for 21 days resulted in up to 25% increase in hepatic G SH and might represent a rebound phenomenon (Szabo et al., 1977). Benz et al. (1997a) studied the time and dose depe ndence of the depletion of tissue GSH and tissue cyanide and the covalent binding to tiss ue after s.c. injection of 0, 20, 50 (LD 10 

### ), 80 (LD 50 

### ), or 115 mg/kg (LD 90 

### ) AN to male Sprague-Dawley rats. GSH levels in live r were the most sensitive marker of AN exposure and were deple ted by 50% at 20 mg/kg, a dose without overt toxicity. At 50 mg/kg, the threshold dose fo r overt toxicity, GSH was depleted by ≥ 85% and followed by a rapid recovery of 60% at 4 hours. Liver GSH was depleted almost completely within 30 minutes when rats were injected with 80 m g/kg AN. The depletion was sustained through 120 minutes and followed by 40% recovery th rough the end of study period of 4 hours.
Blood and brain GSH were more resistant to the GSH depleting effects of AN and were depleted

### DRAFT - DO NOT CITE OR QUOTE 25 less extensively in a dose-dependent manner as the doses were in the toxic range. (The highest dose of 115 mg/kg depleted only 40% brain GSH at 2 hours.) In addition, brain GSH levels showed little capacity for recovery during the stud y period, unlike liver and kidney. Glandular and forestomach GSH were also dose-dependently depl eted by AN treatment and were unable to recover within the study period. GSH depletion was accompanied by a dose-dependent i ncrease of cyanide in the blood and brain during the first 60 minutes. At the lowe st dose of 20 mg/kg, blood and brain cyanide declined after 60 minutes. At the higher doses, bl ood and brain cyanide continued to increase to 120 minutes and then declined. Covalent binding of AN to tissue protein increased in all tissues rapidly during the first 30 minutes at all doses. At 20 mg/kg, covalent binding reached a plateau at 30 minutes. At the three higher doses, covalent binding continued to increase after 30 minutes and reached a plateau level by 2–4 hours. Benz et al. (1997a) concluded that when liver GSH was depleted, detoxification of AN was terminated. Acute AN toxicity became apparent, and a sustained increase in covalent binding to tissue pr otein was observed. Further experiments by Ahmed and coworkers (Ahmed et al., 1983, 1982; Ghanayem and Ahmed, 1982) confirmed the involvement of hepatic G SH in AN metabolism. For example, when bile was collected from male Sprague-Dawley ra ts given a single oral dose of 46.5 mg/kg AN containing 12 μ Ci/kg [1- 14 

### C]-AN, four metabolites were isolated and character ized in biliary
extracts at 6 hours after treatment. The two main metabolites were S-cyanoethyl glutathione and N-acetyl-S-(2-cyanoethyl)cysteine (Ghanayem and Ahm ed, 1982). Both were glutathione conjugates of AN. Pretreatment of rats with diethy l malate (a glutathione-depleting agent) significantly decreased or abolished all of the met abolites in the bile. The study authors proposed GSH conjugation as a major pathway of AN m etabolism, probably catalyzed by glutathione transferases. The product, S-cyanoethy l glutathione, is further metabolized to N-acetyl-S-(2-cyanoethyl)cysteine. Nearly 27% of t he administered dose was excreted in the bile after 6 hours (Ahmed et al., 1982). Kedderis et al. (1995) compared the kinetics of AN and CEO interaction with GSH in vitro by measuring the formation of conjugates when [2,3- 14 

### C]-labeled AN or CEO were incubated for a very short time (20 seconds for mic e, 30 seconds for rats) with [glycine2- 3 

### H]-GSH in the presence of microsomal and cytosolic subcellular fractions of human, rat, or mouse liver. Because of the rapid non-enzymatic re action of AN and CEO with GSH at pH 7.3, the steady-state kinetics of GSH conjugation were d etermined at pH 6.5. HPLC-mass spectrometry was used to separate and identify the conjugates, which included S-(2-cyanoethyl)- glutathione from AN; and S-(1-cyano-2-hydroxyethyl) glutathione and S-(2-cyano-2-hydroxyethyl)-glutathione from CEO. The apparent kinetic parameters for the conjugation reactions (V max app 

### and K m app 

### ) were estimated by fitting the Michaelis-Menten eq uation to the data, giving
estimates of V max app 

### for the conjugation reactions catalyzed by mouse c ytosolic enzymes that were four to six times greater than those for rat c ytosolic enzymes at pH 6.5 (Table 3-5). These

### DRAFT - DO NOT CITE OR QUOTE 26 data suggest that mouse liver cytosolic glutathione -S-transferase (GST) has a greater capacity for conjugating AN and CEO than do rat liver enzymes. Initial velocity studies were also carried out with microsomes and cytosol from human liver, provi ding data to suggest that GSH conjugation of AN with human liver cytosol was broadly similar to that of rodent liver cytosol (Table 3-6).

Table 3-5. Apparent kinetic parameters for glutath ione conjugation of AN and CEO at pH 6.5

Fixed substrate Species V max app ( μ mol/min-mg) a K m app (GSH) (mM) a

Rat 3.32 ± 0.29 17.47 ± 3.60 AN Mouse 21.68 ± 1.75 23.39 ± 3.99
Rat 2.00 ± 0.20 9.36 ± 2.27 CEO Mouse 8.34 ± 0.75 15.12 ± 2.84

a Values are the means ± SDs of three determinations.

Source: Kedderis et al. (1995).



### Table 3-6. Glutathione conjugation of AN and CEO w ith or without microsomal or cytosolic GST from rat, mouse, and hu man liver preparations

Nanomoles of product Species a Substrate Non-enzymatic Microsomal Cytosolic
Rat 32.6 ± 1.9 b 36.1 ± 3.0 b

Mouse 31.3 ± 1.2 b 36.6 ± 1.4 b

Human AN 25.5 ± 2.0
19.5–24.5 c 25.2–34.4 c

Rat 16.6 ± 1.1 25.2 ± 1.1 b

Mouse 18.9 ± 1.0 b 25.9 ± 3.7 b

Human CEO 15.5 ± 1.3
11.2–14.3 c 12.6–14.5 c

a Rodent values are means ± SDs of three determinatio ns. b Statistically significantly greater than the non-en zymatic reaction ( p < 0.05) as calculated by the authors.

c Range of values for subcellular fractions prepared from six human subjects.

Source: Kedderis et al. (1995).



### In the same report, Kedderis et al. (1995) describ ed the determination of the initial velocities of non-enzymatic vs. enzymatic GSH conju gation of AN and CEO at pH 7.3 in the absence or presence of GST (Table 3-6). Both subst rates reacted rapidly with GSH in a nonenzymatic reaction, and addition of hepatic microso mes or cytosol from rats and mice statistically significantly enhanced the rate of pr oduct formation from AN ( p < 0.05). Initial velocities indicated that AN conjugated more effect ively with GSH than did CEO. Hepatic cytosol enhanced the rate of product formation from CEO to a greater extent (up to 52% higher) than did microsomes, suggesting that rodent cytosol ic GST is more active toward CEO than

### DRAFT - DO NOT CITE OR QUOTE 27 microsomal GST. Under physiological conditions (pH 7.3), addition of liver cytosol from four out of six individuals similarly enhanced GSH conju gation with AN but not CEO. Human liver microsomes did not enhance the velocity of CEO or A N conjugation with GSH, suggesting that human microsomal GST forms do not catalyze this rea ction (Table 3-6). Similarly, Guengerich et al. (1981) studied the reaction of AN and CEO with glutathione in vitro. The pseudo first-order rate constant for disappearance of GSH at pH 7.7 (37°C) was 0.28/minute, when 0.5 mM was mixed with 0.1 M AN. The rate constant for the disappearance of GSH in the presence of 0.1 mM CEO was 0.11/minut e. Guengerich et al. (1981) also incubated [1- 14 

### C]-AN or -CEO with GSH at pH 6.5 in the presence of cytosolic fraction from rat liver, huma n liver, or rat brain to determine GST activity. Rat liver cytosol showed GSH S-transferase activity towards AN, with a K m 

### of 33 mM and a
V max 

### of 57 nmol/minute-mg protein. Human liver and rat brain cytosolic fraction had no activity towards AN. Rat liver also showed activity towards CEO, with activity in rat brain more than an order of magnitude lower. The importance of sulfhydryl compounds in the deto xification of AN was shown in a number of studies, particularly by the demonstratio n that treatment with exogenous sulfhydryl compounds could protect the organism from the harmf ul effects of AN. Appel et al. (1981) reported that sulfhydryl compounds such as cysteine were effective antidotes for both orally and intraperitoneally administered lethal doses of AN i n rats. N-acetyl-cysteine was ineffective when given intraperitoneally and less effective tha n cysteine when administered orally. The GSH-depleting effect of a single s.c. dose of AN ad ministered to male Sprague-Dawley rats and the subsequent GI bleeding and gastric mucosal necr osis could be blocked by pretreatment with sulfhydryl-containing agents such as L-cysteine or cysteamine (Ghanayem and Ahmed, 1986; Ghanayem et al., 1985). Benz et al. (1990) studied the effectiveness of D- or L-cysteine and N-acetyl-D-cysteine or N-acetyl-L-cysteine in the detoxification of acu tely administered AN by determining the s.c.
LD 50 

### of AN in male Sprague-Dawley rats either administe red AN alone or in combination with
individual antidotes. The LD 50 

### of AN alone was determined to be 74.7 mg/kg. The LD 50 

### of AN when combined with other antidotes ranged from 93.3 mg/kg (with N-acetyl-D-cysteine) to 151.4 mg/kg (with L-cysteine). The antidote protec tive index ranged from 1.25 for N-acetyl-Dcysteine to 2.03 for L-cysteine. Thus, N-acetyl-D- cysteine was less effective than other antidotes in reducing acute lethality. Measurement of urinar y N-acetyl-S-cyanoethyl cysteine, which was derived from conjugation with GSH pathway, followin g s.c. injection of 50 mg/kg AN alone or AN plus an antidote, indicated that none of the ant idotes significantly increased the excretion of
this metabolite. Blood cyanide levels were also measured in rats at 0.5, 1, 2, 4, and 6 hours following s.c. injection of 50 mg/kg AN or AN plus an antidote. B enz et al. (1990) showed that all of the antidotes, except N-acetyl-D-cysteine, lowered bloo d cyanide levels. Since N-acetyl-D-cysteine

### DRAFT - DO NOT CITE OR QUOTE 28 was the least effective antidote, the antidotal eff ectiveness of these cysteine enantiomers was related to their cyanide detoxification mechanism. Discussing these findings, Borak (1992) pointed out that, because both D- and L-cysteine pr ovided equivalent protection against AN poisoning but only L-cysteine could be incorporated into GSH, the antidotal effects of these compounds may be unrelated to GSH repletion. In fa ct, since the potency of each antidote was proportional to their ability to lower cyanide leve ls, Borak (1992) suggested that their effects may be due to the ability of cysteine derivatives t o serve as sulfur donors for the detoxification of cyanide via rhodanese-mediated transformation of cy anide to thiocyanate. The protection provided by these antidotes for cyanide poisoning f rom AN exposure, however, does not necessarily extend to other forms of AN-induced tox icity.

3.3.3. Covalent Binding of AN and Its Metabolites to Subcellular Macromolecules When isolated hepatocytes from male F344 rats were incubated with 1 mM [2,3- 14 

### C]-AN for 2 hours (Hogy, 1986; Geiger et al., 1983), a ra diolabeled protein adduct was formed that
could be characterized after the removal of residua l AN and other low molecular weight products by dialysis. Analysis of the hydrolyzed non-dialyz able fraction indicated that about 75% of the radioactivity was contained in a single major peak that was chromatographically identified as S-(2-carboxyethyl)cysteine, the hydrolysis product of S-(2-cyanoethyl)cysteine, indicating direct cyanoethylation of cysteinyl residues by AN. When isolated hepatocytes were incubated with 2 mM [2,3- 14 

### C]-AN for 60 minutes, Geiger et al. (1983) estimate d the level of irreversible binding to protein to be 8.1 nmol/mg protein, a lev el of alkylation corresponding to modification of 1 in every 900 amino acid residues or roughly 1 of every 20 cysteine groups. In contrast to AN-protein binding, detection of binding of [2,3- 14 

### C]-AN-derived radiolabel to DNA and RNA in hepatocytes was limited by the low level of radi oactivity that could be incorporated into [ 14 

### C]-AN because of polymerization and microsynthesis problems and by the high level of protein binding. Therefore, hepatocytes were incub ated with 2 mM [2,3- 14 

### C]-AN for 60 minutes in the presence of extracellular calf thymus DNA (0 .5 mg/mL) (Hogy, 1986; Geiger et al., 1983).
RNA and both intracellular and extracellular DNA we re isolated. The isolated RNA contained 53 pmol AN metabolites per mg RNA of which 9 pmol/m g RNA could be attributed to the contaminating protein. The isolated extracellular DNA contained 47 pmol AN adducts per mg DNA, of which 30 pmol/mg DNA could be attributed to protein. A portion of incubated extracellular DNA was further purified; alkylation of extracellular DNA was not observed at a
detection limit at 3.5 × 10 5 

### bases (Geiger et al., 1983). Hogy and Guengerich (1986) treated an F344 rat int raperitoneally with 0.6 mg/kg [2,3- 14 

### C]-CEO to assess macromolecular binding in liver an d brain 1 hour after treatment. DNA and RNA in liver and brain were isolated, and the a mounts were estimated. Bound radioactivity was estimated by liquid scintillation counting. Co valent binding of CEO-derived radioactivity was detected in both liver and brain protein at rat es of 1.1 and 1.0 alkylations per 10 6 

### amino

### DRAFT - DO NOT CITE OR QUOTE 29 acids, respectively. However, no covalent binding to DNA or RNA could be detected at the level of 0.3 alkylations per 10 6 

### bases in liver and brain. In another experiment by Hogy and Guengerich (1986) , liver and brain DNA were
isolated from three rats 2 hours after treatment wi th 50 mg/kg AN i.p. or 6 mg/kg CEO i.p. Using thin layer chromatography with fluorescent pl ates, the study authors were able to detect
N 7 

### -(2-oxoethyl)guanine at 0.014 and 0.032 alkylations per 10 6 

### DNA bases in liver for rats treated with CEO and AN, respectively. This DNA adduct was apparently derived from CEO, consistent with its recovery after AN and CEO treat ment. The apparent lineage of this DNA adduct was different from the protein adduct, S-(2- cyanoethyl)cysteine, described previously,
which was derived from AN.
N 7 

### -(2-oxoethyl)guanine was only at the level of detec tion in rat brain DNA. In addition, 1,N 6 

### -ethenoadenosine or 1,N 6 

### -ethenodeoxyadenosine were not detected in liver DN A, using HPLC with fluorescence detector in the analyses of these two adducts. Binding of AN and/or
CEO to DNA is also discussed in Section 4.5.1.2.1. As discussed in Section 3.3.2, when 0, 20, 50, 80, or 115 mg/kg [2,3- 14 

### C]-AN was injected subcutaneously into male Sprague-Dawley ra ts, GSH became almost completely depleted (>95%) in liver at 80 mg/kg within 30 minu tes, while blood and brain GSH were more resistant to the depleting effect of AN. Brain and blood GSH were not affected at 20 mg/kg. The amount of cyanide in blood and brain increased dose dependently in the first hour after dosing (Benz et al., 1997a). Covalent binding to t issue proteins increased in a dose-dependent fashion during the first 30 minutes at all doses, w ith binding to blood proteins being 3–4 times greater than in any other tissue. Benz et al. (199 7a) suggested that GSH depletion in liver was related to AN toxicity and covalent binding. The effect of GSH depletion on the irreversible bi nding of AN to tissue macromolecules has been studied in male F344 rats exposed to 4 mg/ kg [2,3- 14 

### C]-AN either by inhalation (Pilon et al., 1988a) or gavage (Pilon et al., 1988b). Bi nding of radiolabel to tissue macromolecules was evaluated in control rats or rats depleted of G SH by an i.p. injection of phorone (PH)/ buthionine sulfoximine (BSO) about 30 minutes prior to AN exposure. GSH contents in control rats were as follows: liver (17.3 μ mol/g), kidney (4.5 μ mol/g), lung (3.1 μ mol/g), stomach (5.3 μ mol/g), brain (3.9 μ mol/g), and blood (4.2 μ mol/g). A significant depletion of GSH was produced in liver (43%), kidney (42%), and lung (22 %) after PH/BSO treatment. No significant depletion of GSH was observed in blood, brain, or s tomach 30 minutes after a combined
PH/BSO treatment. In the inhalation studies (Pilon et al., 1988a), th ree rats were exposed to initial AN concentrations of 0, 25, 50, 100, 500, or 750 ppm i n a closed-circuit inhalation chamber for 240 minutes. AN was not replenished during the exp osure, and the decrease in chamber AN concentration was monitored by taking samples every 10 minutes during the exposure. Uptake of AN vapor by control rats showed two distinct pha ses: an initial, rapid phase that lasted about

### DRAFT - DO NOT CITE OR QUOTE 30 60 minutes, followed by a slower phase. An uptake rate of 4.82 mg/kg-hour was estimated for a concentration of 100 ppm using the uptake curve for the rapid phase. In GSH-depleted rats, the mortality rate was higher. The rate of AN uptake w as increased in the rapid phase but decreased at 500 and 750 ppm. In the slow phase, uptake was similar to that in control rats for concentrations below 200 ppm, but was elevated at 5 00 and 750 ppm. Radioactivity irreversibly associated with tissue m acromolecules was measured in control rats 1, 2, 4, 6, 12, or 24 hours after the AN dose. In GSH-depleted rats, radioactivity was measured 1, 6, or 24 hours postexposure. In most t issues, the concentration of AN-derived undialyzable radioactivity (ADUR) reached a maximum in ≤ 1 hour in both control and GSH-depleted rats. (In the brain, ADUR levels reac hed a maximum in 2 hours.) The time course of ADUR levels showed a plateau from 1 to 6 hours in studied organs of control rats, followed by a decrease thereafter during the next 6 hours. This was then followed by an increase between 12 and 24 hours in the lung and kidney (but not in the brain, stomach, and liver). The time course of ADUR levels in blood showed high lev el 1 hour after AN administration, decreased from 6 to 12 hours, and increased from 12 to 24 hours, resulting in a maximum level at
24 hours. Total radioactivity recovered from brain, stomach, liver, kidney, and blood decreased by 54% in GSH-depleted rats compared with controls at both 1 and 24 hours. In GSH-depleted rats, ADUR levels remained constant in all organs evaluat ed throughout the 24-hour postexposure period and were lower than those in controls. The kidney was the most affected organ, with an average 52% decrease in ADUR levels, followed by th e liver (44%). ADUR levels in the brain, stomach, and lung of GSH-depleted rats were 31% low er when compared with controls. Blood ADUR levels were decreased by 50% in GSH-depleted r ats. Irreversible binding of ADUR with total nucleic aci ds (RNA + DNA) of brain, stomach, and liver was also evaluated in control and GSH-dep leted rats 1 hour after an inhalation dose of 4 mg/kg (40 μ Ci) AN vapor. In control rats, ADUR in total nucle ic acids was found to be highest in the brain (63 pmol AN equivalents/mg), f ollowed by that in the stomach (20 pmol AN equivalents/mg) and the liver (12 pmol AN equivalen ts/mg). In GSH-depleted rats, ADUR in
nucleic acids in the brain was about 50% lower than that in controls, but no change was detected
in stomach or liver. ADUR in DNA could not be dete cted in any tissue of control or GSH-depleted rats. The study authors suggested tha t ADUR in DNA was not detected because the analytical method used was not sensitive enough to detect radiolabel bound to DNA. Nevertheless, a preferential binding of ADUR with b rain RNA was observed in both control and GSH-depleted rats, with ADUR in brain RNA about 50% lower in GSH-depleted rats. It is unlikely that the observed decrease in radiol abel binding in GSH-depleted rats
treated with PH/BSO was due to treatment effect on CYP2E1. BSO is a selective inhibitor of GST; PH depletes GSH in liver, kidney, and lung but not in the blood or brain by conjugation

### DRAFT - DO NOT CITE OR QUOTE 31 with GSH. PH was reported not to affect the hepati c microsomal mixed-function oxidase system (Younes et al., 1986). In the oral studies on male F344 rats, total radioa ctivity recovered in the tissues examined was similar in control and GSH-depleted rats at bot h 1 and 24 hours. However, significantly higher recovered radioactivity was found in stomach , lung, and blood of GSH-depleted rats than of control rats 1 hour after dosing, while the radi oactivity in kidney was lower in GSH-depleted rats (Pilon et al., 1988b).
The concentration of ADUR in brain reached a maximu m in ≤ 1 hour for both control and GSH-depleted rats and remained constant for 24 hour s. In GSH-depleted rats, 60–80% increase in ADUR was measured in brain at 1, 6, and 24 hours after dosing. The highest ADUR level was
found in stomach and increased with time in control rats. ADUR levels in liver and kidney of control rats was characterized by an increase over the first 6 hours and a decrease between 5 and 24 hours. GSH-depletion resulted in an increase in ADUR levels in liver, lung, kidney, stomach, blood, and brain between 6 and 24 hours after the d ose. GSH depletion also caused a significant increase in ADUR levels in total nucleic acid (DNA + RNA) in both brain and stomach (one and a ha lf- and threefold, respectively) 6 hours after the dose. No change was found in liver. ADU R associated with DNA was detected in stomach tissue of control rats only. Pilon et al. (1988b) suggested that ADUR levels reflected the relative concentration of covalently bound radi oactivity in control and GSH-depleted rats and that the reaction of AN with protein and other macr omolecules was responsible for the rapid
increase in ADUR at ≤ 1 hour. The slower increase in ADUR in metabolical ly competent organs (liver, kidney, and lung) of control rats and all o rgans of GSH-depleted rats might represent the binding of CEO to macromolecules. Urinary excretio n of thiocyanate, a final metabolite from the epoxide pathway of AN metabolism, was increased twofold in GSH-depleted rats. Since urinary thiocyanate is indicative of CEO formation, Pilon et al. (1988a) interpreted their results as indicating that more CEO was formed after GSH-de pletion. Farooqui and Ahmed (1983a) also reported covalent b inding of [2,3- 14 

### C]-AN to protein, DNA, and RNA of tissues of male Sprague-Dawley rats treated with a single oral dose of 46.5 mg/kg. DNA from tissue homogenate was isolate d by extraction with chloroform/isoamyl alcohol/phenol and application of the aqueous extra ct to hydroxyapatite chromatography. DNA alkylation was higher in brain and stomach than tha t in the liver, with highest levels of covalent binding in the brain. The covalent binding indices for the liver, stomach, and brain at 24 hours after dosing were 5.9, 51.9, and 65.3, respectively

. Ahmed et al. (1992a) demonstrated the covalent bind ing of radiolabel from [2,3- 14 

### C]-AN to testicular DNA after a single gavage of radiolab eled AN (46.5 mg/kg) to male SpragueDawley rats. In a time course study, bound activit y was shown to be greatest after 30 minutes (8.93 ± 0.80 μ mol AN bound per mol nucleotide). Using an identic al experimental protocol, Ahmed et al. (1992b) demonstrated the capacity of A N to bind covalently to DNA in the lung.

### DRAFT - DO NOT CITE OR QUOTE 32 Binding was associated with a 28–41% decrease in re plicative DNA synthesis at time points up to 24 hours after dosing. Jacob and Ahmed (2003a) used whole-body autoradiog raphy to examine the distribution of [2- 14 

### C]-AN administered orally or intravenously to male F344 rats. Two days after oral dosing, covalently bound radioactivity was retained at higher levels in the gastric mucosa, blood, and hair follicles. After i.v. injection, covalent ly bound radioactivity was retained in liver, spleen, bone marrow, adipose tissue, and lung. The amount of radioactivity associated with covalent binding was lower for oral dosing than for i.v. injection, which was consistent with the higher recovery of radioactivity excreted following oral dosing compared with injection (see Section 3.4.2). Covalent binding of [2,3- 14 

### C]-AN to tissue protein and globin was also studied in male Sprague-Dawley rats after a single s.c. injection o f 1.2–115 mg/kg (Benz et al., 1997b). Covalent binding to tissue protein reached completi on in 1–4 hours and was linear in the low dose range (1.2–50 mg/kg), with the relative order (in descending order) as follows: blood > kidney = liver > forestomach = brain > glandular st omach > muscle. Covalent binding to globin followed a similar dose-response curve. Benz et al . (1997b) also measured an N-(2-cyanoethyl)- valine (CEVal) adduct of globin at this dose range. This adduct was formed by reaction of AN
with the NH 2 

### -terminal residue of globin (Osterman-Golkar et al. , 1994) and represented only 0.2% of total AN binding to globin. However, regre ssion of tissue protein binding vs. globin total covalent binding or globin CEVal adduct indic ated that both globin biomarkers could be used as surrogates for the amount of AN bound to ti ssue protein. Using a similar dosing regimen, Nerland et al. (20 01) employed sodium dodecyl sulfatepolyacrylamide gel electrophoresis to separate labe led proteins isolated from subcellular fractions of liver from treated rats. Binding of A N was found to be associated preferentially with
GST of the μ subclass (GSTM). Within this subclass, GSTM1 was labeled about seven times more strongly than GSTM2, while, from the α -subclass, only GSTA3 was labeled (at about 1/35 the strength of GSTM1). No label was associat ed with GSTA1 or GSTA2. The site of binding was identified as exclusively cysteine 86. Since this particular cysteine residue in rGSTM1 appeared to have been targeted specifically, the study authors hypothesized that high reactivity at cysteine 86 was due to its potential interaction with histidine residue at position 84, which would lower the pk a 

### of cysteine 86, increasing reactivity towards sulf hydryl reagents. These data would suggest that tissue proteins conta ining cysteine residues with an abnormally low pk a 

### value would be likely targets for AN. In an in vi vo experimental approach, Nerland et al. (2003) demonstrated that subcutaneously adminis tered AN preferentially bound to the cysteine 186 residue of carbonic anhydrase III (CAI II) in rat liver. A considerable body of evidence demonstrated the a bility of AN to bind to intercellular proteins, in particular to Hb. Osterman-Golkar et al. (1994) reported a method for quantifying an N-terminal cyanoethyl-valine adduct, CEVal, the pro duct of reaction between AN and the

### DRAFT - DO NOT CITE OR QUOTE 33 N-terminal valine of Hb. The method was based on t he N-alkyl Edman procedure involving the derivatization of globin with pentafluorophenyl iso thiocyanate and gas chromatography-mass spectrometry analysis. Osterman-Golkar et al. (199 4) showed that the method was applicable to experimental animals exposed to AN in drinking wate r and to humans exposed to AN in tobacco smoke. Hb from smokers (10–20 cigarettes/day) with a daily intake of 0.5–5 μ g AN per kg BW contained about 90 pmol CEVal/g, whereas adduct lev els in the Hb of nonsmokers were below the detection limit of about 20 pmol/g Hb. This ut ility was confirmed by Tavares et al. (1996) for occupationally exposed workers and for smokers. A subsequent study by Bergmark (1997) showed that t he Hb of smokers contained adducts of ethylene oxide and acrylamide as well as AN. In nonsmokers, the CEVal Hb adduct of AN was below the detection limit of <2 pmol/g of globin. In the 10 smokers studied, the levels of this adduct ranged from 25 to 178 pmol/g (mean 106 pmol/g) and correlated with the number of cigarettes smoked per day (correlation co efficient = 0.94). Fennell et al. (2000) determined CEVal from blood s amples of 16 nonsmokers and 32 smokers and reported that CEVal Hb adducts incre ased with increased cigarette smoking. The estimated CEVal level from smoking was 170 fmol per mg Hb per pack-day. Two participants in a smoking cessation program showed a gradual reduction of CEVal levels (Perez et al., 1999). Thus, the use of the Hb adduct CEVa l may have utility as a biomarker to assess low-level exposure to AN (in the region of 50 ppb), even in a complex mixture of toxicants, although smoking would be a confounding variable. Fennell et al. (2000) also reported that the null genotypes for GSTM1 or GSTT1 had little effect on CEVal levels when compared to active
genotypes. Borba et al. (1996) measured CEVal as a marker of AN exposure in occupationally exposed workers in an acrylic fiber factory. The v alues for CEVal among the subjects were 8.5– 70.5 pmol/g globin in controls, 635.2–4,603.5 pmol/ g globin for continuous polymerization workers, and 93.9–4,746 pmol/g globin for maintenan ce workers. These findings pointed to the ready formation of AN adducts with Hb in an occupat ional setting. CEVal Hb adduct was also used as a follow-up dose monitor after accidental exposure of four cleaning workers to AN in an AN-containing tan k wagon (Bader and Wrbitzky, 2006). On day 25 after exposure, CEVal adduct levels in Hb ra nged from 640 (blood sample partly hemolyzed) to 2,020 pmol/g globin for the three smo kers and was 566 pmol/g globin for the nonsmoker, indicating residual AN adducts from the accidental exposure. On day 175, CEVal adduct levels were 81–276 pmol/g globin for the smo kers and 2 pmol/g globin for the nonsmoker and represented background CEVal of the study parti cipants according to their smoking status. For both the smokers and nonsmoker, the adduct conc entrations in blood declined linearly with time. Linear regression analysis of the data estim ated a total elimination interval of 148 days, longer than the standard lifespan of 126 days of er ythrocytes. Linear regression analysis also
allowed estimation of the initial adduct levels of the workers on the day of the accident and

### DRAFT - DO NOT CITE OR QUOTE 34 estimation of the exposed AN concentrations based o n the correlation from the former German exposure equivalent that 3 ppm AN yields 17,200 pmo l/g globin.

3.4. ELIMINATION
3.4.1. Studies in Humans In an inhalation study of six male volunteers expo sed to 7.8–10 mg/m 3 

### AN for 8 hours (Jakubowski et al., 1987), 44–58% (mean = 52%) of t he inhaled AN was absorbed, of which
about 22% of absorbed AN was metabolized and excret ed in the urine over 31 hours from the start of exposure as N-acetyl-S-(2-cyanoethyl)-L-cy steine (2-cyanoethyl mercapturic acid [CEMA]). Elimination followed first-order kinetics , with a half-life of about 8 hours. The authors concluded that individual urinary CEMA leve ls were not a useful measure for exposure
to AN.

3.4.2. Studies in Animals Three pathways are involved in the elimination of AN from an organism: exhalation, urinary excretion, or fecal excretion.

3.4.2.1. Exhalation In a study by Young et al. (1977), male Sprague-Daw ley rats were exposed to [1- 14 

### C]-AN via inhalation (5 or 100 ppm) or a single oral dose (0.1 or 10 mg/kg). Exhalation of AN as CO 2 

### within 6 hours after dosing decreased with increasi ng dose, from 6.1 to 2.6% of the dose following inhalation exposure and from 4.6 to 3.9% after gavage (see Tables 3-1 and 3-2). When Ahmed et al. (1983) administered a single oral dose of 46.5 mg/kg AN to male Sprague-Dawley rats in distilled water, using 50 μ Ci/kg of either [2,3- 14 

### C]- or [1- 14 

### C]-AN as tracer, the recovery of total dose in expired 14 

### CO 2 

### varied from 2% for [2,3- 14 

### C]-AN to 12% for [1- 14 

### C]-AN 24 hours after dosing. Burka et al. (1994) a dministered 0.87 mmol/kg (46.2 mg/kg) [2- 14 

### C]-AN by gavage to male F344 rats. About 2% of the dose was expired as volatile organic components, predominantly unchanged AN, while 11% w as liberated as 14 

### CO 2 

### 24 hours after dosing. Jacob and Ahmed (2003a) compared excretion of 11.5 mg/kg [2- 14 

### C]-AN administered orally or intravenously to male F344 rats. In the 48 hours after oral dosing, 61% of the radioactive dose was excreted, with 4% in exhaled C O 2 

### , 4% in urine, and 53% in feces. Following i.v. administration, 30% of the dose was eliminated over 48 hours, with 2% in expired air, 8% in urine, and 21% in feces. In the 8 hours after oral dosing, 3% of the radioactive dose
was in exhaled CO 2 

### , 2% in urine, and 48% in feces. Following i.v. ad ministration, 2% of the
dose was in exhaled CO 2 

### , 3% in urine, and 0.2% in feces. Jacob and Ahmed (2003a) concluded that these results indicated a significant differen ce in biological fate of AN following i.v. or oral

treatment.

### DRAFT - DO NOT CITE OR QUOTE 35 3.4.2.2. Fecal Excretion Young et al. (1977) also investigated the fecal ex cretion of AN in male Sprague-Dawley rats. This route of excretion showed little depend ence on the route of administration, amounting to 3–4% of the dose following inhalation exposure a nd about 5% following gavage within 6 hours of dosing. Young et al. (1977) also invest igated the possibility of biliary excretion with subsequent reabsorption from the intestines in one male rat. A cannula was inserted between the common bile duct and the duodenum for sampling of b ile, and [ 14 

### C]-AN was given intravenously. Based on the concentrations of radi oactivity in bile, urine, RBCs, and plasma as a function of time, the rate of elimination from the bile was found to be faster than from other fluids during the first 6 hours after dosage. The initial half-life for excretion of radioactivity vi a bile was estimated to be about 15 minutes. One uni dentified metabolite was excreted in the bile and underwent enterohepatic circulation to the GI t ract, contributing partially to 5% of the dose
excreted in feces. Kedderis et al. (1993a) estimated that 3–5% of AN d oses were excreted in feces of F344 rats (0.09–28.8 mg/kg orally), while 2–8% of the do se were recovered from the feces of B6C3F 1 

### mice (0.09–10 mg/kg orally). In either species, th e differences in fecal excretion were not related to the administered dose. Farooqui and Ahm ed (1982) administered a single oral dose of 46.5 mg/kg [1- 14 

### C]-AN to male Sprague-Dawley rats, the highest perc entage of 14 

### C excreted in feces (2%) occurred between 12 and 24 hours after d osing. At the end of 10 days, 2.5% of the dose was excreted in feces. In another study, male Sprague-Dawley rats were given a single gavage dose of 46.5 mg/kg [1- 14 

### C]-AN; four radioactive peaks were identified in bi liary extracts at 6 hours after treatment. The two major metaboli tes in bile were GSH conjugates of AN: S-cyanoethyl glutathione and N-acetyl-S-(2-cyanoeth yl)cysteine (Ghanayem and Ahmed, 1982). Nearly 27% of the dose appeared in the bile after 6 hours (Ghanayem and Ahmed, 1982; Ahmed et al., 1982). The GI tract contained the highest level of radioactivity up to 72 hours, suggesting
resecretion of AN metabolites to the stomach or bin ding of metabolites to the stomach mucosa (Ahmed et al., 1982).

3.4.2.3. Urinary Excretion
A substantial number of studies demonstrated the r apid urinary elimination of AN or its metabolites when AN was administered to experimenta l animals via the oral or inhalation routes (Burka et al., 1994; Fennell and Sumner, 1994; Kedd eris et al., 1993a; Ahmed et al., 1983, 1982; Young et al., 1977). For example, when Young et al . (1977) exposed male Sprague-Dawley rats to radiolabeled AN via inhalation (5 or 100 ppm) or a single oral dose (0.1 or 10 mg/kg), most of the radiolabel was recovered in the urine, with muc h lower proportions of the initial dose in feces or expired air (see Table 3-1 and 3-2). Urinary ex cretion increased with dose, from 69 to 82% of

### DRAFT - DO NOT CITE OR QUOTE 36 the dose following inhalation exposure and from 34 to 67% after gavage (Tables 3-1 and 3-2). Excreted dose in urine was mostly unidentified meta bolites. In another study, Sapota (1982) administered 40 mg /kg AN, containing either 40 μ Ci/kg [1,2- 14 

### C]- or [1- 14 

### C]-AN, in saline to male Wistar rats, either via ga vage or intraperitoneally. In parallel to the depletion of radiolabel in tissues at 24 hours postexposure, 82–93% of the dose was eliminated from the body in the urine, with 3–7 % exhaled unchanged in the breath in 24 hours, independent of the route of administratio n and the position of the radiolabel. However, when Farooqui and Ahmed (1982) administered an oral dose of 46.5 mg/kg [1- 14 

### C]-AN to male Sprague-Dawley rats, 40% of the radioactivity was e xcreted in urine over 24 hours after dosing. At the end of 10 days, 61% of the total dose was ex creted in urine. Similarly, when Ahmed et al. (1983) gave a single oral dose of 46.5 mg/kg AN to male Sprague-Dawley rats in distilled water, using 50 μ Ci/kg of either [2,3- 14 

### C]- or [1- 14 

### C]-AN as tracer, 40% of the radioactivity from [1- 14 

### C]-AN but 60% of [2,3- 14 

### C]-AN-derived radiolabel were detected in the urine in the initial 24 hours. Neither of the two studies provided deta ils that might explain the discrepancy. However, the observed discrepancy might indicate th e impact of different strains used in the
studies. The single gavage dose experiment of Burka et al. (1994), in which male F344 rats were placed in metabolic cages after receiving 0.87 mmol /kg (46.2 mg/kg) [2- 14 

### C]-AN, resulted in 67% of the load being voided to the urine after 24 hours. This proportion of the recovered load
was similar to the 55–56% value obtained when male F344 rats or B6C3F 1 

### mice were orally exposed to [1,2,3- 13 

### C]-AN (Fennell and Sumner, 1994). However, Ahmed e t al. (1996a) recovered only about 4% of the counts in 48-hour ur ine samples when F344 rats were injected intravenously with 11.5 mg/kg [2- 14 

### C]-AN. About 27% of the load was eliminated via al l routes combined. In this study, much higher levels of tis sue binding were observed than in other
studies. Identification of the urinary metabolites derived from AN metabolism was attempted in several studies. Langvardt et al. (1980) administe red [2,3- 14 

### C]- and [1- 14 

### C]-AN orally to male Sprague-Dawley rats, thereby specifically tracing t he fate of the vinyl and cyano groups of AN. Two main urinary metabolites, thiocyanate and N-ace tyl-S-(2-cyanoethyl)cysteine, were identified. Thiocyanate, formed from the epoxide m etabolite CEO, was the predominant urinary metabolite following oral dosing with 30 mg/kg of [ 1- 14 

### C]-AN and accounting for 54% of the injected radioactivity within 16 hours after dosing . On the other hand, thiocyanate only accounted for 1% of the urinary radioactivity after dosing with [2,3- 14 

### C]-AN. The second metabolite, N-acetyl-S-(2-cyanoethyl)cysteine, a me rcapturic acid derived from direct conjugation between AN and GSH, constituted 18% of the radiolabel derived from [1- 14 

### C]-AN and 28% from [2,3- 14 

### C]-AN. Another metabolite, tentatively identified as N-acetyl-3-carboxy5-cyanotetrahydro-1,4-2H-thiazine, constituted 19% of the label from [1- 14 

### C]-AN and 35% from [2,3- 14 

### C]-AN. Evidently, this metabolite was formed from conjugation of CEO with GSH.

### DRAFT - DO NOT CITE OR QUOTE 37 Langvardt et al. (1980) found another four minor me tabolites that were not identified structurally. Tardiff et al. (1987) monitored the urinary metabo lites of AN-treated male SpragueDawley rats 24 hours after i.v. or i.p. single dose s (0.6, 3, or 15 mg/kg) or inhalation exposure to 4, 20, and 100 ppm for 6 hours. Three major metabo lites were measured: thiocyanate, N-acetylS-(2-hydroxyethyl)cysteine, and N-acetyl-S-(2-cyano ethyl)cysteine, that were also detected by Langvardt et al. (1980). These three excreted meta bolites represented 50–54% of the administered dose in urine within 24 hours, indepen dent of the dose. Tardiff et al. (1987) found that following i.p. or i.v. administration of AN, N -acetyl-S-(2-hydroxyethyl)cysteine and thiocyanate each represented between 5 and 10% of t he urinary metabolites; the major metabolite was N-acetyl-S-(2-cyanoethyl)cysteine, r epresenting 74–78% of the urinary metabolite when AN was administered intraperitoneal ly or intravenously. However, following inhalation exposure of AN, only 8% of the dose was excreted as N-acetyl-S-(2-cyanoethyl)- cysteine, and the major urinary metabolite was thio cyanate at 20 and 100 ppm. Moreover, N-acetyl-S-(2-hydroxyethyl)cysteine was excreted in larger amounts than N-acetyl-S-(2-cyanoethyl)cysteine. These results also showed that the percentage of dose excreted as urinary thiocyanate increased with dose when AN was adminis tered by inhalation. The study authors
concluded that the route of administration of AN ha d an important influence on the pattern of
metabolic excretion. Shibata et al. (2004) investigated the urinary exc retion of thiocyanate in male Wistar rats that received 40 mg/kg AN (about half the LD 50 

### ) by gavage in water. Urinary excretion of thiocyanate became measurable at the time of peak p lasma thiocyanate levels, 5 hours after dosing. Excretion of urinary thiocyanate gradually increased so that at 10 hours after dosing, about 1.2 mg thiocyanate (7% of administered dose) had been excreted into urine. Gut et al. (1981) administered [1- 14 

### C]-AN to male Wistar rats (dose not given) by the oral, i.v., i.p., and s.c. routes. Total excretion of radioactivity after 48 hours was reported to be close to 100% following oral administration but 75– 84% following the other routes of administration. The patterns of urinary radioactiv ity elimination were also different: after parenteral administrations, elimination of radioact ivity was highest within the first 4 hours after dosing, with much smaller amounts for the remaining 44 hours. After oral dosing, between
6 and 8% of the dose was eliminated in urine for th e time periods 4, 8, and 12 hours after dosing with much lower amounts thereafter. However, the m ajor difference was found to be urinary thiocyanate elimination: 23% during the 48 hours a fter oral dosing and 4% following i.p., 4.6% following s.c., and 1.2% following i.v. administrat ion. In another study (Gut et al., 1985), male Wistar ra ts were exposed via inhalation to 57, 125, or 271 mg/m 3 

### AN for 12 hours. A constant ratio between thiocya nate and the sum of thioether compounds (AN mercapturic acids) in urine was found throughout the three doses. Average total amounts of thioethers excreted in uri ne during 12 hours of exposure were 24, 63,

### DRAFT - DO NOT CITE OR QUOTE 38 or 83 μ mol/kg for 57, 125, or 271 mg/m 3 

### AN, respectively. Average total amounts of thiocyanate excreted were 14, 24, and 49 μ mol/kg for 57, 125, and 271 mg/m 3 

### AN, respectively. The ratio of thioethers to thiocyanate was about 2: 4 during the 12 hours of exposure and was similar to that from oral exposure to AN. Thus, th ioethers, not thiocyanate, were the major urinary metabolites following inhalation and oral e xposure. These results were different from those reported by Langvardt et al. (1980) and Tardi ff et al. (1987). Müller et al. (1987) quantified four urinary metab olites and unchanged AN following inhalation exposure of male Wistar rats to 1–100 pp m of AN for 8 hours (thiocyanate was not measured). At 24 hours postexposure, N-acetyl-S-(2 -cyanoethyl)cysteine was the primary urinary metabolite, followed by N-acetyl-S-(2-hydro xyethyl)cysteine, thiodiglycolic acid (also known as thiodiacetic acid), S-carboxyethyl-L-cyste ine, and unchanged AN. The excretion pattern of AN and its metabolites was dependent on the inhalation exposure concentrations. The study authors proposed cyanoethyl mercapturic acid was the most sensitive indicator metabolite of AN exposure at levels of 5 ppm. Fennell et al. (1991) also measured GSH-derived met abolites, but not thiocyanate, in the urine of male F344 rats (10 or 30 mg/kg) and male B 6C3F 1 

### mice (10 mg/kg), following oral administration of [1,2,3- 13 

### C]-AN. The results of this study are shown in Tabl e 3-7. N-acetylS-(2-cyanoethyl)cysteine was formed by conjugation of AN with GSH, whereas the other
metabolites were from reaction of CEO with GSH. Th e results support the finding that rats and mice differ in the way they metabolize AN, and mice evidently metabolize more AN through the
CYP2E1-mediated formation of CEO.

Table 3-7. Urinary excretion of thioethers derived from AN

Rat (30 mg/kg) Mouse (10 mg/kg) Metabolite (see Figure 3-2) Percent of total metabolites N-acetyl-S-(2-cyanoethyl)cysteine 42.8 ± 4.8 20.5 ± 2.0 N-acetyl-S-(2-hydroxyethyl)cysteine 26.7 ± 1.8 22.3 ± 1.2 N-acetyl-S-(1-cyano-2-hydroxyethyl)cysteine 17.4 ± 2.2 13.9 ± 3.2 N-acetyl-S-(carboxymethyl)cysteine and thiodiacetic acid 7.4 ± 2.9 43.2 ± 3.5 Thionyldiacetic acid 5.7 ± 0.21 Not detected

Source: Fennell et al. (1991).



### Kedderis et al. (1993a) studied the dose dependence of the urinary excretion of AN
metabolites in male F344 rats and male B6C3F 1 

### mice. In rats during the 72 hours following oral doses of 0.09–28.8 mg/kg [2,3- 14 

### C]-AN, 73–99% of the dose was excreted in urine, wh ile 3–5% was found in feces. In mice receiving 0.09–10 mg/k g [2,3- 14 

### C]-AN, 83–94% of the dose was
excreted in urine and 2–8% in feces. Excretion of radioactivity by both routes was not dose dependent in either species.

### DRAFT - DO NOT CITE OR QUOTE 39 The position of the radiolabel did not allow detect ion of thiocyanate. Radiochromatograms of urine from rats or mice identified five ma jor peaks, two of which contained more than one compound. Following administration of [2,3- 14 

### C]-CEO, two of the five peaks were not found, indicating that those peaks were derived fro m direct conjugation of AN without metabolic activation to CEO. The sum of the percent of total radioactivity from CEO conjugate-derived peaks was higher than that from the AN conjugate-de rived peaks in both rats and mice. None of the metabolites appeared to be glucuronides. Kedde ris et al. (1993a) detected four of the five metabolites shown in Table 3-7, but could not ident ify thionyldiacetic acid. In addition, S-(2-cyanoethyl)-thioacetic acid was detected in mo use urine only, likely a degradation product of N-acetyl-S-(2-cyanoethyl)cysteine.
The excretion of metabolites derived from CEO was a pproximately linear with the AN dose in both rats and mice. However, the urinary e xcretion of N-acetyl-S-(2-cyanoethyl)cysteine increased nonlinearly with increasing dose of AN, a n effect that was much more pronounced in rats than in mice. This probably indicated the pre sence of a competing pathway, namely, epoxidation of AN, with the conjugation of AN with GSH. The fraction of the total dose
recovered as metabolite from CEO was 0.5 in rats an d 0.67 in mice. The study authors estimated that the ratio of AN epoxidation to GSH conjugation ranged from 4.8 to 1.3 as the AN dose
increased in rats and from 5.7 to 2.7 as the dose i ncreased in mice. Kedderis et al. (1993a) also pointed specifically to the species differences det ected in this study—a roughly 10-fold higher excretion of thiodiglycolic acid (thiodiacetic acid ) in mice as compared with rats and measurable excretion of S-(2-cyanoethyl)thioacetic acid in mic e. This urinary metabolite could not be
detected in rats at all. Sumner et al. (1999) treated three male WT and fou r male CYP2E1-null mice (C57BL/GN × Sv129) orally to 0, 2.5, or 10 mg/kg [1 ,2,3- 13 

### C]-AN and used NMR spectroscopy to characterize AN metabolites in urine samples col lected over 24 hours. WT mice excreted metabolites derived from CEO (80–85% of total excre ted) and from direct GSH conjugation with AN (15–21% of total excreted), with the largest per centage of metabolites from conjugation of
GSH with the 3-carbon of CEO. CYP2E1-null mice dis played only metabolites derived from direct GSH conjugation with AN in their urine follo wing administration of 2.5 or 10 mg/kg [1,2,3- 13 

### C]-AN. This confirmed the role of CYP2E1in the oxi dation of AN to CEO and its subsequent transformation to a range of other produ cts. Since CYP2E1-null mice did not excrete metabolites that would be produced by oxidation by other CYP450s, CYP2E1 may be the only CYP450 enzyme involved in the metabolism of AN. In addition, CYP2E1-null mice excreted about the same percentage of administered dose as t he WT mice, indicating CYP2E1-null mice compensated for the CYP2E1 deficiency by producing more metabolites from direct conjugation
of AN with GSH. Taken together, the animal data indicate that AN c an be exhaled as parent compound at a low percentage of the administered dose, probably i ncreasing at high doses (e.g., 10 mg/kg).

### DRAFT - DO NOT CITE OR QUOTE 40 Fecal excretion amounts to about 5% of a given dose . The biliary pathway leading to fecal
excretion has not been well characterized. To a sm all extent, similar to fecal excretion, AN is metabolized completely and exhaled as CO 2 

### . Both pathways appear to be quite independent of the administered dose. Urinary excretion of AN met abolites has been well characterized but is not without contradictory findings. There appears to be little doubt that mice metabolize more AN via the CYP2E1-mediated oxidative pathway than d o rats. To what extent this pathway is likely to be overcome by large doses, or what contr ibution the GSH conjugation makes with varying doses of AN and different species exposed, is not known.

3.5. PHYSIOLOGICALLY BASED TOXICOKINETIC MODELS A physiologically based toxicokinetic (PBTK) model for AN was previously developed in rats (Kedderis et al., 1996; Gargas et al., 1995 ) and extended to describe the dosimetry of both AN and CEO in humans (Sweeney et al., 2003). The P BTK model structure consists of two parallel modules, one for AN and one for CEO, inter linked by the rate of oxidative metabolism of AN to CEO in the liver, essentially as described by Gargas et al. (1995). Each module consists of seven dynamic tissue compartments repre senting the lung, slowly perfused tissues, fat, well-perfused tissues, brain, stomach, and liv er (Figure 3-2). All perfusion-limited tissue compartments are linked through blood flow, followi ng an anatomically accurate, typical, physiologically based description (Andersen, 1991).

### DRAFT - DO NOT CITE OR QUOTE 41 Source: Sweeney et al. (2003).

Figure 3-2. Structure of the PBTK model for AN and CEO.

Because AN and CEO are retained by the tissue in ea ch compartment according to their tissue/blood partition coefficients (PCs) (which we re measured in vitro), the concentrations of both chemicals in venous blood (leaving the tissue) are lower than those in arterial blood during the equilibration phase (except CEO in the liver). Therefore, the rate of change in the amounts of both chemicals in each tissue compartment is giv en by the difference between concentration in blood entering and exiting the tissue multiplied by the blood flow. Simple differential equations for each compartment, corrected for the non-enzymat ic conjugation with GSH, are integrated over time, giving the amounts of AN and CEO present in the tissue (Kedderis et al., 1996) (see equation below). Therefore, knowing (from the lite rature) the actual volume of each tissue,
concentrations of AN and CEO in each tissue can be calculated over time.

### DRAFT - DO NOT CITE OR QUOTE 42 dA i



### /dT = Q i 

### (CA–CV i 

### )–(K SO 

### × 

### CV i 

### × 

### GSH) × 

### V i


### where
Q i 

### = blood flow rate to the target tissue (i) CA = concentration of AN in arterial blood CV i 

### = concentration of AN in venous blood K SO 

### = rate constant for the conjugation of AN with g lutathione (GSH) V i 

### = volume of the target tissue (i)

For the lung compartment, with two mass inputs (mix ed venous blood and inhaled air) and two outputs (arterial blood and exhaled air), t he amount of either chemical in alveolar air is in equilibrium with the amount in lung blood at the steady state. Thus, concentrations of AN and CEO in arterial blood can be calculated from simple mass balance equations. Such calculations
take into account the alveolar ventilation rate and the rate of blood flow through the lung, a parameter made equal to cardiac output (both known from the literature) and corrected for binding to Hb and blood sulfhydryls. For the liver compartment, with mass input from bl ood and two outputs (venous blood and metabolism, excluding biliary excretion that wa s not considered), the chemical mass transfer is given by the difference between concentrations i n portal and venous blood multiplied by hepatic blood flow and corrected for: (1) metaboli sm of AN to yield CEO (calculated from the Michaelis-Menten equation, subtracted from the mass of AN, and added to the mass of CEO), (2) enzymatic hydrolysis of CEO (also described by the Michaelis-Menten equation), and (3) the first-order conjugation with GSH. A simplified sch eme of the mass flow in the PBTK model for AN and CEO is shown in Figure 3-2 (Sweeney et al., 2003). The model was initially calibrated in rats for thr ee routes of AN administration—oral, i.v. (bolus), and inhalation (Kedderis et al., 1996)—by manually adjusting the metabolic parameters
V max 

### and K m 

### for AN oxidation, first-order constants for AN- an d CEO-GSH conjugation, and first-order constant for absorption of AN from the GI tract, guided by the approximate statistical likelihood calculation of SimuSolv. Absorption thr ough the skin, which has been estimated at about 1% of that through the lung (Rogaczewska, 197 5), was not considered in this model. Chemical-specific modeling parameters were either: (1) measured in vitro in rats (PC [Teo et al., 1994]; macromolecular interaction constants [Gargas et al., 1995]), (2) fitted to the experimental data by the model (metabolism parameters: V max 

### and K m 

### ), or (3) estimated from the literature (CEO elimination constants).
The model assumed that rats do not have EH activit y, based on data from Kedderis and Batra (1993). As discussed previously in Section 3 .3.1, this assumption is probably incorrect, based on data from de Waziers et al. (1990), Guenge rich et al. (1981), and Kopecky et al. (1980). This PBTK model did not scale allometrically EH act ivity to humans, whose liver microsomes display EH activity toward CEO (Kedderis and Batra, 1993). Instead, Kedderis (1997) estimated

### DRAFT - DO NOT CITE OR QUOTE 43 this activity in humans in vivo based on the ratio of EH to CYP450 activity in subcellular hepatic fractions multiplied by the CYP450 activity in vivo . In addition, the human blood-to-air PC for AN was determined experimentally (Kedderis and Held , 1998). Because no in vivo pharmacokinetic data were available to validate the human model, human in vitro data were scaled to experimental data obtained from rats by u sing a “parallelogram approach.” The model by Kedderis et al. (1996) overestimates the oral exposure of venous blood CEO concentration by 3- to 10-fold. This is a syst ematic bias, which suggests that the model parameters need to be reevaluated or that the model is not capturing an important kinetic process for CEO clearance. In particular, for all tissues except the liver, the measured rise in CEO
concentration for the first 10–15 minutes after ora l and i.v. exposures is much slower than predicted by the model, and the model continues to overpredict the oral data for all measured time points, with the overprediction in the brain b eing the worst. Kedderis et al. (1996) suggested that the overestimation of CEO concentrat ion in blood at early time points is “most likely due to a large intrahepatic first-pass effec t.” This hypothesis has not been further evaluated, but, even if correct, the model structur e has not been revised to simulate this phenomenon. The model continues to overestimate CE O levels in blood (albeit to a lesser degree) at later time points when the hypothesized first-pass effect would be less of a contributing factor. It should also be noted that Kedderis et al. (1996 ) did not compare their model predictions to data on the urinary elimination of A N-GSH and CEO-GSH conjugates and on total activity bound to Hb, as was done in a previous ver sion of the model (Gargas et al., 1995). While fits to those data may have informed the para meters reported by Kedderis et al. (1996), this is clearly not the case in this instance. Als o, the blood and tissue time-course data shown by Kedderis et al. (1996) do not include all of the po ints shown in the previous publication. Since Kedderis and colleagues (1996) did not inclu de EH activity in their rat model (but other evidence strongly indicates significant CEO h ydrolysis be EH), did not perform a more global, numerical optimization of their parameters, may not have included the urinary and Hb data, and the subsequent model fits consistently ov erpredicted CEO pharmacokinetics in blood and brain to a large extent, the model parameteriza tion was revised to hopefully improve the model characterization of the rat pharmacokinetic d ata and provide a more sound footing for human-rat dosimetry comparisons and hence risk extr apolation, at least making the results numerically reproducible. Guengerich et al. (1981) measured CEO hydrolysis with purified rat
EH and obtained a V max 

### of 0.3 μ mol/minute-mg protein and a K m 

### of 800 μ M. Since the highest
blood levels observed for CEO were ~2 μ M (0.1 μ g/mL), to a good approximation hydrolysis can then be described using a first-order rate cons tant of 0.3/800 = 3.75 × 10 -4 

### L/minute-mg EH protein. The EH content of rat liver was measured by de Waziers et al. (1990), who found 0.165 mg EH/mg MP and a value of 40 mg MP/g liver f rom Ploemen et al. (1997) can be applied.

### DRAFT - DO NOT CITE OR QUOTE 44 Finally, the liver fraction for the rat as used in the model 40 g/kg BW was applied, assuming a standard 0.25 kg rat. The rate constant for a standard rat would then be k EH 

### = (3.75 × 10 -4 

### L/minute-mg EH) × (0.165 mg EH/mg MP) × (40 mg MP/g liver) × (40 g liver/kg BW) × (0.25 kg BW) × (60 minutes/hour) = 1.49 L/hour. Because k EH 

### is effectively the ratio,
V max 

### /K m 

### , for EH, and a V max 

### is expected to scale with BW across species while K m 

### is not expected to scale with BW, k EH 

### is expected to scale in the same way as a V max 

### . In particular,
since k EH 

### is a total activity (rather than an activity per u nit volume of liver), it is expected to
scale as BW 0.7 

### . Therefore, as for V max 

### values in general, one derives a scaled constant, k EHC 

### = k EH 

### /(0.25 kg) 0.7 

### = 3.92 L/h-kg 0.7 

### . Based on similar in vitro (Krause et al., 1997) and in vivo (Kemper et al., 2001) EH activity data for butadien e mono-epoxide, it is suspected that the in vivo enzymatic hydrolysis of CEO is also similar to in vitro values, further supporting this direct extrapolation. Because of the close dose spacing used in the prot ein kinase (PK) studies and the limited data on metabolite disposition, we found that not a ll of the remaining parameters were readily identifiable from the in vivo PK data. Therefore, a value of K m 

### for AN oxidation to CEO from in vitro experiments with rat liver microsomes from Ro berts et al. (1991) will be used:
52 μ M × 0.05306 mg AN/ μ mol = 2.76 mg/L. While the model predictions of AN and CEO blood lev els after oral exposures tended to either match or exceed the measured levels, the mod el predictions of the Hb-binding data were below the measured levels, indicating that the corr esponding binding constants that had been
determined in vitro were too low. Since the data a re only for total binding to Hb (AN plus CEO), the ratio of the AN:CEO binding constants fro m in vitro was held constant, but the absolute value of the constants was allowed to vary

. Given the values for K m 

### and the k EHC 

### obtained above, the parameters varied during model fitting were V max 

### (AN oxidation), k FC 

### (GST activity towards AN), k FC2 

### (GST activity towards CEO), k A 

### (oral absorption), and k H 

### (AN-Hb binding constant, with the CEO-Hb binding constant, k H2 

### , varied in direct proportion, so that k H 

### /k H2 

### remained equal to the ratio of the values measured in vitro). An approximate log likelihood function as described by Cole et al. (2001) was used as a measure of goodness of fit. During i nitial optimizations, it was assumed that the heteroscedasticity values for AN and CEO were disti nct but that the same value held for each compound among all three tissues sampled (brain, li ver, and blood). However, examination of the standard deviations (SDs) noted in the data of Kedderis et al. (1996) and Gargas et al. (1995) indicated that measurement error was approximately proportional to the signal strength, so the
heteroscedasticities were set to two. Initial attempts to fit the model to the entire da ta set by varying other model parameters were not satisfactory. While the results are not s hown here in detail, a possible reason that the model could not entirely fit the data is that it as sumes constant GSH levels in each tissue, while previous studies (e.g., Benz et al., 1997a) have sh own significant GSH depletion at dose levels in

### DRAFT - DO NOT CITE OR QUOTE 45 the range of those used in the PK studies. Since G SH depletion will be least significant at the lowest doses used, and the most interest is in the low-dose range for extrapolation, it was decided to reestimate the model parameters by using only th e lowest concentration pharmacokinetic data: the oral doses at or below 3 mg/kg, i.v. dose of 3. 4 mg/kg, and inhalation concentration of 186 ppm. Also, of the data used to estimate parame ters, it was determined that the last AN blood measurement from both the 3 mg/kg oral data and the 3.4 mg/kg i.v. data appeared to be outliers since they were well above the otherwise log-linear clearance curve defined by the preceding data, so they too were not used in the estimation. (Model simulations of all exposure concentrations and doses will be shown as compared with the data, but only the data for the exposure values stated two sentences above were use d for fitting.) The following figures show the model fits obtained with the parameters of Kedderis et al. (1996) as compared with the EPA's revised parameter s. (All parameter values are listed in Table C-1 of Appendix C.) The term “fits” is used here t o describe the closeness of model simulations to the data, recognizing that only a subset of the data, as described in the preceding paragraph and indicated in the figure legends, was actually u sed in parameter estimation.) The most remarkable aspect of the revised fits is how close they are to identical to the original model fits. Results are nearly identical for most of the i.v., inhalation, and oral (Figures 3-3 to 3-5a) bloodand tissue-time-course data. The revised fits to t he CEO blood- and tissue-time-course data after oral dosing are slightly worse than in the original model (Figure 3-6b), but then the fits to the urine and especially the Hb-binding data (Figure 3- 6c) are considerably better than those obtained with the parameters of Kedderis et al. (19 96). Since only a few of the fits were degraded slightly, while others were improved, the revised model parameters are considered to represent the overall data set at least as well as the original. The fact that the revised parameters are specifically defined by the low-dose data, whic h are closest to the range where the model will be applied and are obtained using an objective crit eria and numerically reproducible methods (the approximate likelihood function with numerical optimization), gives further support for their

use.

### DRAFT - DO NOT CITE OR QUOTE 46 Note: Only 3.4 mg/kg data were used to estimate re vised parameters, with circled point excluded.

Figure 3-3. Intravenous exposure, dosimetry, and m odel fits. 

## CEO in blood

### DRAFT - DO NOT CITE OR QUOTE 47 Note: Only 186 ppm data were used to estimate revi sed parameters.

Figure 3-4a. Inhalation exposure, CEO concentratio ns. 

## CEO in brain

### DRAFT - DO NOT CITE OR QUOTE 48 Note: Only 186 ppm data were used to estimate revi sed parameters.

Figure 3-4b. Inhalation exposure, AN concentration s. 

## AN in blood

### DRAFT - DO NOT CITE OR QUOTE 49 Note: Only 3 mg/kg data were used to estimate revi sed parameters.

Figure 3-5a. Oral exposure, CEO concentrations. 

## CEO in blood CEO in blood

### DRAFT - DO NOT CITE OR QUOTE 50 Note: Only 3 mg/kg data were used to estimate revi sed parameters.

Figure 3-5b. Oral exposure, AN concentrations.

### DRAFT - DO NOT CITE OR QUOTE 51 Note: points are data; lines are model fits or sim ulations. Only data for doses ≤ 2 mg/kg were used to estimate revised parameters.

Figure 3-5c. Oral exposure, urinary excretion, and Hb binding.

Since the human metabolic parameters were extrapola ted from in vitro measurements by using the relationship between in vitro measured an d in vivo estimated values from the rat (Sweeney et al., 2003), it is appropriate to update the human metabolic parameters and model in parallel with the EPA's update of those in the rat. For EH, Sweeney et al. (2003) used the in vivo:in vitro relationship for the CYP450

- mediated metabolism, since there had been no parall el relationship for hydrolysis. As we are now choosin g to extrapolate the rat EH from in vitro to in 

## CEO

- GSH in urine

### DRAFT - DO NOT CITE OR QUOTE 52 vivo based only on enzyme content, microsomal conte nt, liver fraction, and BW, a parallel approach for the human would be to do the same, rat her than using a correction factor based on a different class of enzymes. In the case of humans, Kedderis and Batra (1993) measured EH activity in vitro by using hepatic microsomes, so w e do not need to use the amount of enzyme per mg MP in the calculation. Kedderis and Batra ( 1993) determined a V max 

### and K m 

### EHmediated hydrolysis of CEO using liver samples from six individual humans. The lowest
estimated K m 

### in the group was 600 μ M, so again, we choose to describe the metabolism a s first order, using the ratio of V max 

### /K m 

### . The ratio of V max 

### /K m 

### was first calculated for each individual
since V max 

### and K m 

### tend to be statistically correlated due to the way they are estimated, and an average value for the ratio was then determined to be 7.02 × 10 -6 

### L/minute-mg MP. We can then apply the value of 56.9 mg MP per g liver from Lips comb et al. (2003), the liver fraction of 25.7 g/kg BW, and the standard value of 70 kg for a human. The rate constant for a standard
human is then k EH 

### = (7.02 × 10 -6 

### L/minute-mg MP) × (56.9 mg MP/g liver) × (25.7 g liver per kg BW) × (70 kg BW) × (60 minutes/hour) = 43.1 L/hour, assuming it also scales as BW 0.7 

### , k EHC 

### = k EH 

### /(0.70 kg) 0.7 

### = 2.20 L/hour-kg 0.7 

### . Recall that the value for rats was estimated to be 3.92 L/hour-kg 0.7



### . The original PBTK model for humans was assessed for its sensitivity to changes in key input parameters, and the expected variability in C EO concentrations in humans under different AN exposure scenarios was estimated (Sweeney et al. , 2003). In addition to updating the CEO hydrolysis rate constant for the human model (and u sing a first-order equation for that reaction) as previously discussed, the ratio of V max 

### for the oxidation step as estimated in vivo vs. me asured
in vitro for the rat was used to estimate the human in vivo V maxC 

### , and the enzymatic GSH conjugation rate constants for AN (k FC 

### ) was likewise estimated from the rat estimated in vivo vs. measured in vitro ratio (k FC2 

### was unchanged during the reestimation). Since the rat values for
V maxC 

### and k FC 

### were revised, and these values were each one leg of the metabolic extrapolation “parallelogram,” the human in vivo values should be accordingly varied. The result is that the ratio of revised/original human values for each of these constants is simply equal to the respective revised/original in vivo values for the rat constants; the revised human values are
V maxC 

### = 22.1 mg/hour-kg 0.7 

### and k FC 

### = 77 kg 0.3 

### /hour. Finally, since the original model extrapolation assumed that the oral absorption cons tant, k A 

### , and the Hb-binding constants, k H 

### and
k H2 

### , were the same in humans as in rats, these assumpt ions were retained, updating the human parameters appropriately. Appendix C provides model source codes written in acsXtreme (AEgis Technologies, Huntsville, AL) and Matlab (The Mathworks, Inc., Na tick, MA) that were used to model AN/CEO pharmacokinetics with the PBTK models of Ked deris et al. (1996, as revised) and Sweeney et al. (2003) in this evaluation.

### DRAFT - DO NOT CITE OR QUOTE 53 4. HAZARD IDENTIFICATION

4.1. STUDIES IN HUMANS—EPIDEMIOLOGY AND CASE REPOR TS 4.1.1. Oral Exposure No studies were identified that addressed the expo sure of human beings to AN via the
oral route.

4.1.2. Inhalation Exposure
4.1.2.1. Acute Exposure In a study on six male volunteers, a single 8-hour inhalation exposure of 5–10 mg/m 3 

### AN produced no subjective symptoms, such as headache, nausea, or general weakness (Jakubowski et al., 1987). A report by Chen et al. (1999) collated 144 acute AN poisoning cases that had occurred
between 1977 and 1994 in China. Each case involved a brief workplace accidental exposure to a high concentration of AN. There were few reliable data on the levels of exposure in these cases, although transient concentrations of AN were though t to range from 40 to 560 mg/m 3 

### (18– 258 ppm) for 60 cases and may have been over 1,000 mg/m 3 

### for the remaining 84 cases. All but 9 of the 144 subjects were males, ranging in age fr om 18 to 53 years old. Forty-two of the cases
were considered to have resulted in severe acute AN poisoning, while the rest fell into the mild
acute category. Table 4-1 summarizes the incidence of symptoms and signs of toxicity that were evident in the 144 cases. Other changes in monitored bioch emical or physiological parameters included transient increases in peripheral white blood cell (WBC) count to greater than 10 × 10 9 

### /L in 66 cases and a number of apparent fluctuations in c linical chemistry parameters. Out of 120 subjects whose liver function was monitored, se ven subjects showed abnormal increases in alanine aminotransferase (ALT) (slight), aspartate aminotransferase (AST), and cholylglycine (i.e., glycocholic acid). Up to 23 times the norma l serum concentration of the latter compound was detected. The seven subjects with abnormal liv er functions were poisoned at low concentrations in air (40–79 mg/m 3 

### [18–36 ppm]) but for a comparatively long duration of acute exposure (36 hours). Blood levels of GSH were depr essed up to 50% in the severe cases, and urine thiocyanate was increased up to fourfold.

### DRAFT - DO NOT CITE OR QUOTE 54 Table 4-1. Clinical signs in 144 subjects accident ally exposed to AN

Symptoms Cases (%) Symptoms Cases (%) Dizziness 144 (100) Congestion of pharynx 105 (73) Headache 144 (100) Hoarseness 13 (9) Feebleness 144 (100) Pallor 108 (75) Sore throat 87 (60) Profuse diaphoresis 95 (66) Chest tightness 144 (100) Rough breathing sound 18 (13) Cough 16 (11) Rapid heart rate 36 (25) Dyspnea 118 (82) ECG abnormalities a 15 (10) Nausea 133 (92) High blood pressure 20 (13) Vomiting 95 (66) Low blood pressure 5 (4) Abdominal pain 97 (68) Liver tenderness 9 (7) Numbness of the limbs 50 (40) Hepatomegaly and sple nomegaly 7 (5) Fainting 104 (72) Coma 7 (5) Convulsion 46 (32) Hyperactive knee jerk 137 (95)

a All 15 instances of electrocardiogram (ECG) abnorma lities occurred in cases of severe poisoning.

Source: Chen et al. (1999).



### These changes disappeared after poisoned subjects w ere removed from the accident site and underwent treatment that included amyl nitrite via inhalation and an i.v. injection of 3% sodium nitrite followed by 50% sodium thiosulfate ( STS). Other treatments included infusion with glucose, adenosine triphosphate (ATP), coenzym e A, and DEX along with oxygen inhalation to prevent the development of cerebral e dema and to protect brain and liver cells. In a study that was possibly reflective of combine d inhalation and dermal exposure to AN, Wilson et al. (1948) reported that workers expo sed to AN vapors at 16–100 ppm (35– 217 mg/m 3 

### ) for periods of 20–45 minutes while involved in cl eaning operations in polymerizer facilities complained of dull headache, fullness in the chest, irritation of all mucous membranes (eyes, nose, and throat), and a feeling of apprehen sion and nervous irritability. Some workers also complained of intolerable itching of the skin but had no clinically demonstrable dermatitis. Workers who had direct skin contact with AN display ed a sequence of symptoms, including skin irritation and erythema, followed by bleb formation and then desquamation with slow healing (Wilson et al., 1948). An earlier report by Wilson (1944) reported the onset of nausea, vomiting, weakness, headache, fatigue, diarrhea, and an “oppr essive feeling” in the upper respiratory passages following exposure to “mild concentrations ” of the compound. Several cases of reversible mild jaundice and one case of slow-to-re verse severe jaundice were identified and
associated with occasional liver tenderness and low -grade anemia, but it was unclear whether they were related to inhalation or dermal contact e xposures to only AN or to a combination of AN with other industrial rubber manufacturing chemi cals such as butadiene and styrene.

### DRAFT - DO NOT CITE OR QUOTE 55 4.1.2.2. Chronic Exposure
4.1.2.2.1. Cancer epidemiology
Cohort studies A retrospective cohort study involving workers at a DuPont textile fibers plant in Camden, South Carolina, was the first epidemiologic study addressing the potential carcinogenicity of AN (O’Berg, 1980). Shortly ther eafter, reports from other cohorts of AN-exposed workers, based in Germany, the Netherlan ds, the United Kingdom, and the United States, were published. Other smaller-scaled occup ational cohorts have also been utilized to better assess the association between AN exposure a nd adverse human health effects. Early studies did not utilize quantitative measures of exposure nor were they able to control for smoking (an important consideration whe n lung cancer is an outcome of interest). These factors were being taken into account by the late 1980s. The following section provides a summary of some of the major cohort studies conduct ed both within and outside the United
States.

The DuPont studies
Researchers from DuPont conducted a series of studi es among male workers potentially exposed to AN (Symons et al., 2008; Wood et al., 19 98; Chen et al., 1987; O’Berg et al., 1985; O’Berg, 1980). The original study was conducted in South Carolina, with a follow-up study a few years later. A second DuPont plant, located in Virginia, was the site for another cohort study. Finally, Wood et al. (1998) combined the co horts from South Carolina and Virginia to further investigate the relationship between AN exp osure and cancer. Most recently, Symons et al. (2008) updated this combined cohort, adding 11 years of follow-up for a total follow-up period of over 50 years. The first epidemiologic study addressing the potent ial carcinogenicity of AN (O’Berg, 1980) examined cancer incidence and mortality in a cohort of 1,345 male workers from a DuPont textile plant who were potentially first exposed to AN between 1950 and 1966. The cohort was chosen from a larger group of more than 10,000 work ers, based on examination of work history (wage roll employees and some salaried employees), recollection of plant supervisors (wage roll maintenance employees and salaried employees), and survey of salaried employees (salary roll employees). No individual or area exposure monitor ing data were available during the period of study. Several surrogate measures of potential exp osure were utilized in the analyses, including job title, initial period of first exposure, length of exposure, and payroll (assuming that wage roll employees have higher potential exposure than super vision or salary roll employees). Workers were followed through the end of 1976, thus allowing a latency period of at least 10 years for all surviving members of the cohort. Cancer incidence was ascertained for all cohort members who were diagnosed during their empl oyment, and cause of death was
determined for all cohort members who died either w hile employed or after termination.

### DRAFT - DO NOT CITE OR QUOTE 56 Comparison rates for cancer incidence and mortality were derived from similarly collected data in a company-wide cancer incidence and mortality re gistry system. Additional mortality information was supplied by the Social Security Adm inistration, and death certificates were obtained for all known deaths. Other standard comp arison rates were also utilized and presented; however, the company-wide data represented the most comparable control group. After observing only one incident case of cancer in the 217 employees with <6 months of exposure, examination of the incidence data was con centrated on the 1,128 employees who had more than 6 months of exposure. Among this group, cancer incidence was stratified by interval of diagnosis: 1956–1964, 1965–1969, and 1970–1976. The cancer incidence was statistically significantly elevated only in the last interval wi th 19 cases observed compared to 10.1 expected (standardized incidence ratio [SIR] = observed ÷ ex pected = 1.88, 95% confidence interval [CI] = 1.17–2.88, p < 0.01), based on company-wide rates. Seventeen o f the 19 cases were among wage roll employees, the remaining two were salary roll employees. The difference between the observed and expected number of cases among the wag e employees was statistically significant (SIR = 2.05, 95% CI = 1.23–3.21, p < 0.01) (Table 4-2).

Table 4-2. Distribution of select incidence and mo rtalities among wage workers and all workers at an AN plant

Wage workers All workers
Cause of disease/death Observed

cases SIR a

(CI) Observed

deaths SMR a

(CI) Observed

cases SIR a

(CI) Observed deaths SMR a

(CI) Less than 6 months of exposure
All cancers 1 0.77 (0.04–3.19) 3 1.30

(0.33–3.55) 1 0.67

(0.03–3.29) 3 1.25

(0.32–3.40) Respiratory cancer 0 0.00 1 1.11 (0.06–5.48) 0 0.00 1 1.11 (0.06–5.48) Greater than 6 months of exposure
All cancers (1956–1976) 20 1.30 (0.82–1.97) 15 1.16

(0.68–1.87) 24 1.26

(0.82–1.85) 17 1.13

(0.68–1.78)
All cancers (1970–1976) 17 2.05 b (1.23–3.21) 11 1.41

(0.74–2.45) 19 1.88 b

(1.17–2.88) 13 1.44

(0.80–2.41) Respiratory cancer (1956–1976) 8 2.35 b (1.09–4.47) 6 1.30

(0.53–2.71) 8 1.95

(0.91–3.71) 7 1.35

(0.59–2.66) Respiratory cancer (1970–1976) 6 2.86 b (1.16–5.94) 5 1.61

(0.59–3.57) 6 2.40 b

(0.97–4.99) 6 1.71

(0.69–3.57)

a SIR and SMR standardized against company-wide rates

. b Statistically significant ( p < 0.05).

SMR = standardized mortality ratio

Source: Amended from O’Berg et al. (1980).

### DRAFT - DO NOT CITE OR QUOTE 57 Eight incident respiratory cancer cases were observ ed in the cohort of 1,345 workers. All eight of the respiratory cancers occurred in the gr oup of employees who had >6 months of exposure, and all were among wage roll employees. Six of the eight respiratory cancers occurred in the 1970–1976 time interval compared to 2.1 expe cted based on company-wide rates (SIR = 2.86, 95% CI = 1.16–5.94, p < 0.05) (Table 4-2). The numbers were too small t o perform any other cancer-specific analyses. In order to consider the effects of latency and lev el of exposure, further analyses were performed looking at the group of workers who had f irst been exposed between 1950 and 1952, when AN was first used at the plant and when exposu res were known to have been highest. Statistically significant differences between the n umber of observed and expected cases were found among the wage roll employees in the diagnosi s interval from 1970 to 1976, with 17 cancers observed and 5.6 expected (SIR = 3.04, 9 5% CI = 1.83–4.78), with six of these cancer cases being respiratory cancers with an expected va lue of 1.5 (SIR = 4.0, 95% CI = 1.62–8.32). This group is presumed to have the longest latency and highest exposures to AN. Other factors related to significant differences in cancer incidence between observed and expected cases among the wage roll employees during the time period 1970–1976 were: (1) being a mechanic (10 observed vs. 3.7 expected) , (2) duration of exposure of more than 10 years (9 observed vs. 2.8 expected), and (3) exp osure above “low level” (13 cancers observed vs. 5.5 expected), low level not defined. Similar relationships were found among respiratory cancers except for duration of exposure of more tha n 10 years. Incidence data among wage roll employees were exami ned by duration of exposure, excluding exposures of <6 months. The duration cat egories were <5, 5–9, and ≥ 10 years. The SIRs for all cancers in these three duration of exp osure categories were 0.7 (95% CI = 0.23– 1.79), 1.2 (95% CI = 0.49–2.50), and 2.3 (95% CI = 1.18–4.14), respectively.
A total of 89 deaths was observed in the entire coh ort of 1,345 workers by the end of 1976. The mortality analyses using company-wide ra tes for comparison did not show any large deviations between observed and expected numbers fo r all cancers or for respiratory cancers alone. Observed and expected numbers of cancer dea ths between 1970 and 1976 for the wage roll employees with ≥ 6 months of exposure were not markedly different, w ith 11 cancers observed vs. 7.8 expected (standardized mortality r atio [SMR] = 1.41, 95% CI = 0.74–2.45) and 5 respiratory cancers observed vs. 3.1 expected (SM R = 1.61, 95% CI = 0.59–3.57) (Table 4-2). The excess mortality observed is of interest, since statistical significance may have been hindered by the small sample size. The use of company-wide rates as a comparison may b e problematic because the company-wide rates are based on other plants where exposure to carcinogenic agents may be possible. Additionally, company-wide rates include both exposed and unexposed workers, thus weakening the ability to observe increased risk amo ng the exposed workers. The use of this population-based referent may hide true association s between AN and cancer. Additionally, the

### DRAFT - DO NOT CITE OR QUOTE 58 number of incident cancer cases and cancer-specific mortalities was too small for further analysis. However, the fact that the cancer/respir atory cancer comparisons appeared to be stronger for workers with longer latency, longer ex posure, jobs with higher exposure, and work during the early years of observation when exposure s were highest added to the weight of the
evidence. Another potential limitation of this study was unde r-ascertainment of incident lung cancer cases. Two confirmed lung cancer cases that should have been included in the cohort were omitted because of clerical error. A validity chec k of a subsample of 465 employees revealed five more omissions, suggesting that a problem exis ted with ascertainment of lung cancer cases. The omission of these cases may have resulted in th e underestimation of the risk estimate for the incidence of lung cancer. Also, subjective exposur e assessment could have resulted in misclassification of exposure. If the exposure mis classification was random, it would bias the
risk ratio toward the null value. If it was nonran dom because those assessing AN exposure believed it could cause illness, the effect on the risk estimate is unpredictable. However, other metrics used in this study, including duration of e xposure, time of diagnosis, and job category, had internal validity and supported the finding of an association between AN exposure and
cancer. Another limitation is the indication that workers may have been exposed to other chemicals in addition to AN. Lastly, there was no adjustment for smoking. The EPA AN health assessment (U.S. EPA, 1983) adjusted the results of this analysis based on smoking rates in the plant and among U.S. blue-collar workers, estimatin g that the expected number of cancer cases would be 15% higher and would reduce, but not elimi nate, the association between AN and cancer in this study. Finally, the small sample si ze and limited follow-up restricted the ability to
detect most cancers. A second DuPont study extended the follow-up of the above cohort through 1983 for cancer incidence and 1981 for cancer mortality, add ing 7 and 5 years of follow-up, respectively (O’Berg et al., 1985). The exposure assessment was not updated, and case ascertainment and calculation of expected incidence and mortality wer e unchanged from the above study. To evaluate dose-response relationships and latency, c umulative exposure was categorized into three groups (<2, 2–12, and ≥ 13 years), and latency was dichotomized into “less than 20 years” or “20 or more years.” Men with <6 months of exposure were included in the analyses. As with the earlier study, DuPont cancer registry data were used as a comparison for the cancer incidence rates observed in the exposed cohort. DuPont and U .S. death rates were used as a comparison for the mortality data in the exposed cohort. There were 43 incident cancer cases, including 10 l ung cancer cases and 6 prostate cancer cases (Table 4-3). The authors did not comment on the problems with ascertainment of incident lung cancer cases described in the O’Berg (1980) st udy. Two additional cases of lung cancer were identified. No significant differences betwee n observed all-cancer incidence or even lung cancer incidence and expected values were found amo ng workers (Table 4-3). There was a

### DRAFT - DO NOT CITE OR QUOTE 59 statistically significant association between AN ex posure and prostate cancer incidence (SIR = 6 observed ÷ 1.8 expected = 3.3, 95% CI = 1.35–6.93 ). All prostate cancer cases were observed among wage workers who had at least 20 years of lat ency. No other significant relationship between latency and cumulative exposure was detecte d.

Table 4-3. Distribution of select incidence and mo rtalities among wage workers and all workers at an AN plant

Wage workers All workers Cause of disease/death Observed

cases SIR a,b

(CI) Observed

deaths SMR a

(CI) Observed

cases SIR a,b

(CI) Observed

deaths SMR a

(CI)
All causes – – 139 1.18 (1.00–1.39) – – 155 1.15 (0.98–1.34)
All cancers 37 1.25 (0.89–1.70) 31 1.15 (0.79–1.61) 43 1.17 (0.86–1.56) 36 1.14 0.81–1.56) Lung cancer 10 1.67 (0.85–2.97) 12 1.17 (0.63–2.00) 10 1.39 (1.41–4.95) 14 1.21 (0.69–1.98)
Prostate 6 4.00 c (1.62–8.32) 1 1.11 (0.05–5.48) 6 3.33 c (1.35–6.93) 1 1.00 (0.05–4.93)

a SIR and SMR standardized against company-wide rates

. b Calculated based on observed and expected values pr ovided.

c Statistically significant ( p < 0.05).

Source: Amended from O’Berg et al. (1985).



### A total of 155 deaths was reported, 36 of which wer e attributed to cancer. No significant differences between observed and expected deaths we re reported among either wage workers or salary workers (Table 4-3). Twelve lung cancer dea ths were observed vs. 10.2 expected (SMR = 1.17, 95% CI = 0.63–2.00), and 1 prostate cancer de ath was observed vs. 0.9 expected (SMR = 1.11, 95% CI = 0.05–5.48). The mortality compariso ns were less elevated than the morbidity comparisons, indicating that a longer follow-up per iod may be needed. The observation that prostate cancer was elevated in the incidence data but not in the mortality data could reflect the fact that prostate cancer has a relatively high 5-y ear survival rate. In summary, O’Berg et al. (1985) added approximatel y 7 years of follow-up to the previous DuPont cohort but did not aid in refining knowledge about the potential for a relationship between AN exposure and lung-cancer in cidence. The population was exposed to chemicals other than AN, and these additional expos ures were not accounted for in the analyses. The small number of lung cancer and prostate cancer cases made the interpretation of the stratified analyses difficult, and the observed num bers of cases were not different from expected numbers of cases in either the highest cumulative e xposure group or the longest latency group. This study shares the same limitations as the O’Ber g (1980) study. Smoking status, which was not available in O’Berg et al. (1985), may have act ed as a confounder. As the numbers of

### DRAFT - DO NOT CITE OR QUOTE 60 incident cases and cancer-specific deaths are small , and concomitant exposure to other chemicals is a potential limitation, this study does not prov ide a substantial basis for the evaluation of the relationship between AN exposure and cancer inciden ce. Chen et al. (1987) assembled a cohort of 1,083 most ly white male workers from a DuPont plant in Waynesboro, Virginia, that produced the acrylic fiber Orlon ® 

### . The manufacturing process was similar to that at the Ca mden plant except there was greater distance between the process areas at the Waynesboro facilit y (Wood et al., 1998). Workers employed at the plant between 1944 and 1970 who had a potential for AN exposure were included. The cohort consisted of 805 wage roll employees and 278 salary roll employees. Potential exposure was based on the review of work histories. No quan titative information was available for exposure levels to AN; however, each job was classi fied as having either low, moderate, or high levels of AN exposure. Because data prior to 1957 were not available, the investigators analyzed only deaths between 1957 and 1981. As with previous DuPont cohort studies, morbidity i n the exposed cohort was compared with company-wide cancer incidence rates, while mor tality was compared with company-wide
rates and national rates. A total of 92 deaths was observed, with 21 attributed to cancer. For both wage workers and salary workers, the number of observed deaths was significantly lower than expected (Table 4-4). No excess of observed c ancer deaths was observed in either worker category. Among the wage workers, the five observe d lung cancer deaths were not statistically different than expected based on U.S. rates (SMR = observed ÷ expected = 0.59, 95% CI = 0.22– 1.32). The significant deficit in observed deaths likely indicates, at least in part, the presence of a healthy worker effect, incomplete cohort identifi cation, and possibly incomplete ascertainment of mortality data. It should be noted that death i nformation was gathered for active and pensioned employees, and names of terminated employ ees were submitted to the Social Security
Administration for identification of vital status. Vital status for 20 people (1.8%) was unknown. No lung cancer deaths were observed among the salar y workers. As for other cause-specific deaths, no significant trends were detected among e ither wage or salary workers by time period or duration of exposure. Analyses by the level of AN exposure and cumulative exposure did not show significant differences between observed death s and expected values.

### DRAFT - DO NOT CITE OR QUOTE 61 Table 4-4. Distribution of select incidence and mo rtalities among wage and salary workers at an AN plant

Wage workers Salary workers Total Cause of disease/death Observed

deaths SMR US a

(CI) SMR DuPont a

(CI) Observed

deaths SMR US a

(CI) SMR DuPont a,b

(CI) Observed

cases SIR DuPont a,b

(CI)
All causes 68 0.57 b (0.44–0.78) 0.77 b

(0.61–0.98) 24 0.41 b (0.27–0.60) 0.66 b

(0.43–0.97) – –

All cancers 18 0.75 (0.44–1.16) 0.88

(0.54–1.37) 3 0.24 b (0.06–0.66) 0.31 b

(0.08–0.85) 37 1.01

Lung cancer 5 0.59 (0.22–1.32) 0.66

(0.24–1.46) 0 Not determined Not

determined 5 0.72

(0.26–1.61)
Prostate

cancer 1 1.11 (0.06–5.48) 1.11

(0.06–5.48) 1 2.0 (0.03–2.47) 2.0

(0.03–2.47) 5 2.63 (0.96–5.83)

a Calculated based on observed and expected values pr ovided.
b Statistically significant ( p < 0.05).

SMR DuPont

= SMR based on DuPont Registry; SMR U.S. = SMR based on U.S. statistics

Source: Amended from Chen et al. (1987).



### Analyses of cancer incidence or morbidity reported 37 incident cancers in the cohort (Table 4-4). Twenty-seven were among the wage roll employees (vs. 26.0 expected) and 10 were among the salary roll employees (vs. 10.5 e xpected). No increase was noted in lung cancer incidence, with 5 cases observed in the tota l group vs. 6.9 expected (SIR = observed ÷ expected = 0.72, 95% CI = 0.26–1.61). The incidenc e of prostate cancer was increased, with 5 observed cases compared to 1.9 expected based on the company-wide database (SIR = 2.63, 95% CI = 0.96–5.83). In summary, no statistically significant observed e xcess in overall cancer incidence or mortality was found among AN workers, but the prese nce of a healthy worker effect is likely. An increase in prostate cancer incidence was noted. As there is a general high rate of survival for prostate cancer cases, cancer incidence rather than mortality should be considered in the evaluation of AN exposure and disease. Some of the study’s disadvantages that limit the interpretation of the results include the small sam ple size and number of cancer cases, subjective exposure assessment, lack of smoking information, a nd lack of stratification by latency and dose in the data analysis. There was the possibility of under-ascertainment of cases, particularly prostate cancer cases, by relying on the DuPont Can cer Registry as the source of information on cancer incidence. The results of this study suppor t the findings of an excess in prostate cancer by O’Berg et al. (1985), but the aforementioned study limitations may have hindered the observation of an association between lung cancer a nd AN. Wood et al. (1998) combined the Virginia and South Carolina cohorts described above (Chen et al., 1987; O’Berg et al., 1985) and analyz ed 2,428 male workers with an added decade of follow-up. The exposure assessment was updated, taking into account plant histories,

### DRAFT - DO NOT CITE OR QUOTE 62 descriptions of manufacturing processes, and change s that would affect exposures, a matrix of job titles, and work area names, documentation of p ersonal protective equipment use, personal and area air sampling data from 1975, and descripti ons of working conditions by long-term employees. Environmental air samples confirmed cha nges in plant processes, engineering, and ventilation. Exposure levels for the period before 1975 were estimated from information provided by a panel of “knowledgeable employees.” Wood et al. (1998) estimated peak AN exposure in parts per million for a 40-hour workwee k for each job title/work area combination and averaged this over a year. Peak exposure level categories, reported as the interval averages, were low (0.11 ppm), moderate (1.1 ppm), high (11 p pm), and very high (30 ppm). Other exposure variables analyzed included latency (<20 a nd ≥ 20 years of observation), duration of exposure (<5, 5–9, and ≥ 10 years), and cumulative exposure (<10, ≥ 10–<50, ≥ 50–<100, and

≥ 100 ppm-years). There was no information on exposu re to other chemicals or on smoking status of the subjects. The cohort included all employees who worked in exp osed areas in either plant until the plants were closed. The DuPont Cancer Registry was used to identify incident cases of cancer among employees during employment. Thus, incident cancer cases occurring after tenure at
DuPont would not have been identified. Vital statu s of past employees was determined through a review of the National Death Index (1979–1991) an d the Social Security Administration (all years). Vital status of living employees was confi rmed through pension records, motor vehicle records, and credit bureau reports. Expected numbe rs of deaths were derived from the DuPont mortality files and the U.S. population. The perio d of follow-up was extended through 1991 in the South Carolina plant and 1990 in the Virginia p lant. At the end of the follow-up period, approximately 18% of the cohort was deceased (n = 4 54). The entire cohort had a total of 72,083 person-years of follow-up for the mortality analyses and 29,461 person-years for the morbidity analyses. More than half of the study po pulation was born before 1930, and 82% were first exposed before 1971, thus allowing adequate f ollow-up to examine latency and adequate attained age to examine most cancer outcomes. A to tal of 37% of the population had a cumulative exposure level estimated at 50 or more p pm-years. The SMR analysis revealed that the 454 deaths obser ved in the cohort were significantly below the expected number of deaths based on U.S. r ates (SMR = 0.69, 95% CI = 0.62–0.75). There were 126 deaths from cancer, which include 46 lung cancer deaths, 27 digestive cancer deaths, and 11 prostate cancer deaths (Table 4-5). The SMR for all cancers was also significantly lower than expected (SMR = 0.78, 95% CI = 0.64–0.93), indicating a possible healthy worker effect. Incomplete ascertainment of the endpoint of death may have also played a role in the low SMR value, as only 18% of the cohor t was deceased at the time of the follow-up. Among the site-specific cancer mortalities, an exce ss number of prostate cancer deaths was reported (SMR = 1.29, 95% CI = 0.64–2.30). A compa rison of the cohort death rates with those derived from the DuPont mortality registry showed S MRs that were slightly different than those

### DRAFT - DO NOT CITE OR QUOTE 63 derived from the U.S. data but did not provide any definitive differences. For all comparisons, there was no evidence of a relationship with any me asure of exposure. For respiratory cancer, a nonsignificant excess of observed deaths was noted for the highest exposure level within the stratified analysis (SMR = 1.23 based on 23 observe d deaths, 95% CI = 0.80–1.85). Cancer incidence in the cohort was compared with co mpany-wide incidence rates derived from the DuPont Cancer Registry. There were no sig nificant elevations reported in any cancerspecific category (Table 4-5), although an excess i n prostate cancer cases was reported. There were sufficient deaths in several categories to all ow examination of the patterns of incidence by the four measures of exposure utilized in the morta lity analyses. Specifically, all cancers, digestive organ cancers, respiratory system cancer, and prostate cancer were examined in the exposure analyses. There was no evidence of a rela tionship with any measure of exposure for all cancers, respiratory cancer, or digestive organ can cers.

Table 4-5. Distribution of select mortalities amon g exposed workers in two AN plants

South Carolina cohort Virginia cohort Combined cohort Cause of disease/death Observed

deaths SMR a

(CI) Observed

deaths SMR a

(CI) Observed

deaths SMR a

(CI) Observed

cases SIR a

(CI)
All causes 271 0.76 b (0.67–0.85) 185 0.60 (0.51–0.69) 454 0.69 b (0.62–0.75) – –

All cancers 77 0.88 (0.69–1.10) 50 0.66 (0.49–0.87) 126 0.78b (0.64–0.93) 101 0.97 (0.79–1.18) Lung cancer 35 1.06 (0.74–1.47) 11 0.40 b (0.20–0.71) 46 0.76 (0.56–1.02) 17 0.81 (0.48–1.28) Digestive

cancer 12 0.57 b (0.29–0.99) 15 0.81 (0.45–1.33) 27 0.69 (0.45–1.00) 22 0.89

(0.56–1.34)
Prostate

cancer 5 1.23 (0.40–2.86) 6 1.32 (0.48–2.88) 11 1.29 (0.64–2.30) 12 1.58

(0.82–2.76)

a SIR and SMR standardized against company-wide rates

. b Statistically significant ( p < 0.05).

Source: Amended from Wood et al. (1998).



### In summary, this study provided better exposure ass essment than previous studies of this group of workers. Additional follow-up and the com bination of two small cohorts enhanced the information available for inclusion; however, the a pparent healthy worker effect may have masked a relationship between AN exposure and death from or incidence of lung cancer or other

cancers. Symons et al. (2008) provided an update based on th e combined Virginia and South Carolina cohorts from Wood et al. (1998), adding 11 years of follow-up. The exposure
assessment was the same as described in Wood et al. (1998) with exposure being based on a job-

### DRAFT - DO NOT CITE OR QUOTE 64 exposure matrix, documentation of personal protecti ve equipment use, personal and area air sampling data, and descriptions of working conditio ns by long-term employees. Vital statistics were obtained through the DuPont Epidemiology Regis try and verified by the National Death Index. New in this update was the assignment of me an intensity values based on estimated intensity categories ranging from <0.2 to >20 ppm. These intensity categories were coupled with duration of employment to determine cumulative expo sure. For SMR calculations, the expected number of deaths were derived both the U.S. populat ion and regional DuPont employees. To reduce potential bias associated with the healthy w orker effect, the Occupational Mortality Analysis Program (OC-MAP) was utilized for SMR calc ulations. For the estimation of relative mortality risk via a hazard ratio, a log linear mod el for AN exposure was assumed for all-cause and cause-specific outcomes. Of the 2,559 workers from Wood et al. (1998), 11 wo rkers were found to be exposed to
AN for <6 months and thus were excluded from the co hort in Symons et al. (2008). A total of 839 deaths (32%) were observed in this updated coho rt of 2,548 male workers. Of these, 240 deaths were due to cancer, with 88 deaths being specific to lung cancer (Table 4-6). One quarter of the updated cohort were found to be in t he mean intensity exposure group of <2.0 ppm, while, two-thirds were in the 2.0–19.9 pp m mean intensity exposure category. The number of deaths, especially cause-specific deaths, in these exposure groups was not reported.

Table 4-6. Distribution of select mortalities amon g exposed workers

Cause of death South Carolina cohort Virginia cohort Combined cohort

Observed deaths SMR a

(95% CI) Observed

deaths SMR a

(95% CI) Observed

deaths SMR a

(95% CI) SMR b

(95% CI)
All causes 481 0.98 (0.89–1.07) 358 0.85 c (0.76–0.95) 839 0.92 c (0.86–0.98) 0.69 c

(0.64–0.74)
All cancers 144 1.00 (0.84–1.18) 96 0.81 c (0.67–0.99) 240 0.92 (0.81–1.04) 0.73 c

(0.64–0.82) Lung cancer 61 1.14 (0.88–1.49) 27 0.64 c (0.42–0.93) 88 0.92 (0.75–1.14) 0.74 c

(0.60–0.91)
Prostate cancer 12 0.93 (0.48–1.63) 13 1.12 (0.60–1.92) 25 1.02 (0.66–1.51) 0.91

(0.59–1.35)

a Based on company regional rates.
b Based on U.S. population rates.

c Statistically significant ( p < 0.05).

Source: Amended from Symons et al. (2008).



### Symons et al. (2008) also reported hazard ratio est imates for 100-ppm years increase in cumulative exposure (Table 4-7). In addition to th e variable ‘exposure term’ used in the crude model, the adjusted model utilized in generating ha zard ratio estimates included ‘birth period’ (6-decade ordinal variable) and ‘employment in Sout h Carolina start-up group’ (binary

### DRAFT - DO NOT CITE OR QUOTE 65 indicator). The authors noted a slight significant increase in all-cause mortality associated with increasing cumulative exposure to AN in the crude m odel but did not find any other statistically significant findings. Colorectal and brain cancers had elevated hazard ratios but were not statistically significant in either the crude or ad justed models.

Table 4-7. Crude and adjusted hazard ratio estimat es for 100 ppm-year increase in cumulative exposure

Crude Adjusted a Cause of death Hazard ratio 95% CI Hazard ratio 95% CI
All causes 1.12 b 1.04–1.21 1.05 0.97–1.14
All cancers 1.07 0.92–1.24 1.00 0.86–1.17 Lung cancer 1.04 0.81–1.33 0.95 0.73–1.23
Prostate cancer 0.81 0.48–1.35 0.78 0.46–1.32
Colorectal cancer 1.13 0.74–1.71 1.16 0.75–1.81
Brain and CNS 1.37 0.59–3.16 1.03 0.38–2.78

a Model includes exposure term, birth period, and emp loyment in South Carolina start-up group.
b Statistically significant ( p < 0.05).

Source: Amended from Symons et al. (2008).



### Hazard ratios estimates were also derived based on lagged cumulative exposure. Increasing exposure lags resulted in decreasing haz ard ratios for all cancers, lung cancer, and colorectal cancer. However, an increase in hazard ratio estimates over lagged cumulative exposure was observed for brain and CNS cancer and lymphatic and hematopoietic cancer. It
should be noted that the number of events for these cancers were small (Table 4-8).

### DRAFT - DO NOT CITE OR QUOTE 66 Table 4-8. Hazard ratio estimated for select cance r mortality by lagged cumulative exposure for 100 ppm-year increase in cu mulative exposure

5-Yr lag (n = 2,224) 10-Yr lag (n = 2,066) 15-Yr lag (n = 1,907)

Cause of death Events Hazard ratio (95% CI) Events Hazard ratio (95% CI) Events Hazard ratio (95% CI)
All cancers 210 1.03 (0.87–1.23) 199 0.98 (0.80–1.20) 179 0.94 (0.74–1.19) Lung 75 0.95 (0.70–1.28) 72 0.84 (0.59–1.19) 63 0.80 (0.53–1.22)
Prostate 22 0.86 (0.48–1.53) 19 0.98 (0.50–1.92) 15 0.95 (0.41–2.22)
Colorectal 26 1.06 (0.64–1.76) 24 0.90 (0.49–1.66) 23 0.81 (0.40–1.66)
Brain and CNS 4 1.38 (0.43–4.47) 4 1.55 (0.44–5.47) 4 1.96 (0.49–7.84) Lymphatic and hematopoietic 16 1.09 (0.59–2.01) 14 1.29 (0.66–2.54) 13 1.27 (0.57–2.86)

Source: Amended from Symons et al. (2008).



### In summary, Symons et al. (2008) followed workers f or over 50 years and, among the 33% mortality in the cohort, reported that no stati stically significant observed excess in overall mortality was found among AN workers. Unlike the p revious studies based on the DuPont cohort, Symons et al. (2008) did not provide cancer incidence data or address previous issues with this cohort such as smoking status and concomi ttent exposure to other chemicals. This update did attempt to reduce potential bias from th e healthy worker effect with specialized statistical program. Differences between U.S. popu lation-based SMRs and regional workerbased SMR indicated that there may still be a stron g healthy worker effect. Although Symons et al. (2008) categorized workers in different mean in tensity exposure and cumulative exposure groups, the authors did not report the observed num ber of cause-specific deaths in these categories or provide cause-specific SMR estimates. In deriving hazard ratio estimates, Symons et al. (2008) adjusted for workers ‘employment in S outh Carolina start-up group.’ Based on O’Berg (1980), it appears that workers in the South Carolina start-up group may have had higher levels of exposure to AN. Additionally, the metric derived by quantitation of AN exposure and SMR derivation of this subgroup would have been hel pful for better assessing the relationship between AN exposure and lung cancer.

Overall summary The DuPont cohort studies were the first to hypoth esize an association between AN exposure and cancer, specifically lung and prostate cancer. It should be noted that the DuPont
cohort studies are limited to male workers and lack appropriate unexposed worker comparison

### DRAFT - DO NOT CITE OR QUOTE 67 groups to better assess the risk of developing caus e-specific diseases, namely cancer. Even in the most recent cohort study by Symons et al. (2008 ), smoking and concomitant exposures were not adequately addressed in any of the DuPont cohor t studies. Interestingly, the prostate cancer findings in the Wood et al. (1998) study revealed a closer association to duration of employment rather than exposure. This observation is echoed w ith brain and CNS cancer and lymphatic and hematopoietic cancer in Symons et al. (2008). Excluding Symons et al. (2008), the DuPont cohort s tudies are the only studies that evaluate the association between AN exposure and ca ncer incidence rather than relying on a surrogate marker such as cause-specific death. For cancer incidence, the cohort studies appeared to only focus on data from the DuPont cancer regist ry rather than including data from state or national tumor registries that have known quality a ssurance and quality control procedures for diagnoses. Symons et al. (2008) assessed risk based on mortal ity. As with the other DuPont studies, the reliance on mortality statistics from the U.S. population as a comparison group is less desirable given the potential for bias from the hea lthy worker effect. Symons et al. (2008) attempted to address this issue by employing DuPont regional workers as a comparison group instead of using company-wide statistics as in othe r DuPont studies. Information regarding other chemical exposures among regional workers would aid in reducing the uncertainty of exposure to other potential carcinogens in this comparison g roup. As with its predecessor, Wood et al. (1998), the mo st recent DuPont cohort study Symons et al. (2008) may also suffer from exposure misclas sification, as no exposure monitoring existed prior to 1975. This lack of information on exposur e potential and level may also subject the studies to recall bias. However, given the shortco mings of each of the individual DuPont studies, there is still suggestive evidence that there may b e an association between AN exposure and the
incidence of cancer.

American Cyanamid Company Collins et al. (1989) conducted a retrospective coh ort study of 2,671 men who worked at two American Cyanamid Company plants in Louisiana a nd Florida from start-up (1951 for the Louisiana plant, 1957 for the Florida plant) throug h December 1973. One facility manufactured AN and other materials, and the other facility util ized large quantities of AN in the manufacturing of acrylic fiber. All 2,671 study su bjects were followed through the end of 1983 for mortality, thus allowing at least 10 years of follow-up for the cohort. According to Collins et al. (1989) for exposure estimation, indu strial hygiene monitoring, which began in 1977, was considered representative of previous exp osure levels, with adjustments made for changes in practices and engineering controls. Any actual measurements that were available were also used to tailor job-specific exposure. Th e investigators created four exposure categories: 0–<0.01, 0.01–0.7, 0.7–7.0, and >7 ppm /year. Exposed workers were defined as

### DRAFT - DO NOT CITE OR QUOTE 68 having a cumulative exposure of >0.01 ppm/year. Sm oking information was only available for 58% of the workers. Each person in the cohort was coded as smoker (smoked for ≥ 3 months), nonsmoker (smoked for <3 months), or unknown (infor mation not available). The authors used an internally standardized method of adjustment for age (<45, 45–54, 55–64, 75+ years), race (white, nonwhite), smoking status (smoker, nonsmoke r, unknown), latency (<10, 10–19, 20+ years), and time period (<1965, ≥ 1965). In the calculation of the SMR, the expected number of cause-specific deaths was derived from U.S. gene ral population data on men. More than 50% of the exposed workers in this study were followed for at least 20 years. By the end of the study, a total of 237 deaths (92 from the unexposed group and 145 from the exposed group) were observed, and death certificate s were located for 224 of these workers. From both groups combined, there were 65 cancers, i ncluding 23 respiratory cancers, of which 22 were lung cancers. For lung cancer, there was n o significant elevation in the SMR for either the exposed or unexposed group (SMR in unexposed gr oup = 1.08, 95% CI = 0.69–1.61; SMR in exposed group = 1.01, 95% CI = 0.74–1.35). A simil ar pattern was observed among the lung cancer deaths, with no significant elevations repor ted (SMR in unexposed group = 1.01, 95% CI = 0.44–2.01 [7 cancer deaths]; SMR in exposed group = 1.00, 95% CI = 0.58–1.61 [15 cancer deaths]). The SMRs for the AN exposure categories for lung cancer were 1.09 (95% CI = 0.51– 2.08), 0.63 (95% CI = 0.10–2.06), 0.64 (95% CI = 0. 20–1.53), and 1.41 (95% CI = 0.68–2.58) for categories 0–<0.01, 0.01–0.7, 0.7–7.0, and >7 p pm/year, respectively

. Using an internally standardized method that adjusted for smoking, race , latency, age, and time period, the SMRs were 1.11 (95% CI = 0.52–2.11), 0.72 (95% CI = 0.12 –2.36), 0.71 (95% CI = 0.23–1.72), and 1.22 (95% CI = 0.59–2.23), respectively, for the ab ove exposure categories. None of these risk estimates or subsequent trend tests was statistical ly significant. No additional information was provided with regard to the nature of the trend tes t. The inclusion of an analysis for the unexposed grou p compared to the U.S. population was helpful and allowed an evaluation of whether el evations in cancer rates in the exposed group were also observed in the unexposed group and thus were not likely to be related to exposure. It should be noted that indirect standardization (the use of age-specific mortality rates from the standard U.S. population to derive regional expecte d deaths) was used, thus hindering the ability to compare SMRs across groups. This study attempte d to quantify exposure levels and control for smoking history. The study did allow for appro ximately 50% of the exposed cohort to have at least 20 years of follow-up, thus strengthening the possibility that a health effect might be detected. However, since the endpoint marker used was death, as recorded on the death certificates, and with less than 10% of the study c ohort deceased by the end of the study, the study may have been premature in attempting to link AN exposure to cancer deaths. This study may have had insufficient power as portrayed by the observation of only 15 lung cancer deaths in the exposed group. It should also be noted that th is study, as with many other cohorts assembled to assess the relationship between AN and cancer, c onsists of only men.

### DRAFT - DO NOT CITE OR QUOTE 69 Because the results presented were adjusted by late ncy, duration of exposure, and time since exposure, relative risks (RRs) in these strat a could not be readily compared with the results of the studies of Symons et al. (2008), Benn and Os borne (1998), Blair et al. (1998), Swaen et al. (1998), Wood et al. (1998), O’Berg et al. (1985), a nd O’Berg (1980). Unlike other studies that assumed early exposure levels were higher, Collins et al. (1989) assumed that AN exposure levels in 1977 were representative of the time fram e prior to that date. This assumption may have led to exposure misclassification, resulting i n a flattening of the dose-response gradient. Other limitations included low statistical power to evaluate lung or rarer cancers, particularly in subgroup analyses, incomplete smoking information, and use of SMRs rather than comparable unexposed controls. In summary, this study may hav e been premature in assessing the relationship between AN exposure to cancer deaths.

Synthetic chemical plant in the U.S. Waxweiler et al. (1981) examined the mortality rate s in a cohort of 4,806 chemical plant workers who were exposed to many potential carcinog ens, including AN. The cohort was identified as all workers at the synthetic chemical s plant who were first employed between 1942 and 1973. These workers were followed through the end of 1973. Since the majority of the cohort (63%) were actually hired before 1954, t his allowed for at least 20 years of latency and follow-up for the majority of the workers. How ever, it should be noted that some workers had less than 1 year of follow-up, latency, or expo sure. The cohort was described as young, with only 30% of live workers being over 55 years of age

. Mortality rates in the plant cohort were compared t o those derived from the U.S. white male population. Under the assumption that all wor kers were considered at risk from the first day of employment, no difference was noted between the observed deaths and the expected deaths (556 observed deaths vs. 550.2 expected deat hs, SMR = 1.01, 95% CI = 0.93–1.10). The number of observed cancer deaths was higher than ex pected (109 observed vs. 92.5 expected, SMR = 1.18, 95% CI = 0.97–1.42). Upon stratificati on of cancer deaths, higher numbers of respiratory system and CNS cancers were observed am ong the workers (respiratory cancer SMR = 1.49, 95% CI = 1.09–1.99; CNS cancer SMR = 2.09, 95% CI = 1.02–3.84). A secondary analysis was performed among workers wh o had at least 10 years of exposure. Waxweiler et al. (1981) noted similar fi ndings, though actual values were not reported. The authors did note that there were 39 observed deaths from cancers of the respiratory system compared to 25 expected (SMR = 1 .56, 95% CI = 1.12–2.11). A similar elevation had been observed by the authors in a pre vious publication (Waxweiler et al., 1976) that focused on the workers with high vinyl chlorid e monomer exposure; thus, the authors concluded that the excess lung cancer risk may not solely be due to exposure to a single
chemical.

### DRAFT - DO NOT CITE OR QUOTE 70 Serially additive expected dose (SAED) modeling was performed to determine whether exposure to chemicals, including AN, was associated with excess lung cancer risk. Job histories were used to assess the potential for exposure to 1 9 chemicals routinely used at the plant. Each job was assigned a qualitative exposure rating (fro m 0 for no exposure to 5 for intimate contact on the skin or high inhalation potential) for each year of the study. Thirty-five of the 80 (56%) job categories ranked had no exposure to AN, with a nother 30% reporting minimal to low levels of exposure. An exposure score was derived for eac h chemical for all workers by summing each exposure rating for each year. The exposure score for each cohort member dying from respiratory system cancers was compared to the scor e for a group of workers with a similar birth year and year of first hire (the “subcohort” from w hich the case arose). Scores in the nonrespiratory death subcohorts (expected scores) w ere subtracted from the observed scores in the respiratory cancer deaths to obtain an observed -minus-expected cumulative dose difference per lung-cancer case. For AN, this calculation res ulted in a negative unit, reflecting that expected cumulative dose greatly exceeded the obser ved cumulative dose. No significant differences with regard to AN exposure were observe d in this analysis. While this study showed significant increased risks of death from lung and CNS cancer in a cohort of workers exposed to multiple carcinogens , limitations with the study design hindered the ability to assess the relationship between the observed deaths and exposure to AN. The population of workers was potentially exposed to mu ltiple carcinogens, so any effect of exposure to AN may have been impossible to measure.

Rubber manufacturing plant Delzell and Monson (1982) analyzed the mortality am ong workers from a rubber manufacturing plant in order to determine if potent ial exposure to AN might be associated with excess deaths. The study included 327 white males who had been employed at the plant for at least 2 years between January 1940 and July 1971. These employees were selected from over 15,000 workers because they worked in departments w here AN exposure was most likely. Mortality information was gathered on both active a nd pensioned workers through July 1978, allowing at least 7 years of follow-up for most wor kers in the cohort. Workers without a record of death were assumed to be alive. Mortality rates were compared with the white male subset of the U.S. general population rates, stratifying by c ause of death, age, and calendar time. By mid-1978, a total of 74 deaths (~ 22%) were obser ved, 22 of which were from various types of cancers. The differences between the obse rved and expected deaths for all-cause and for cancer mortality were not statistically significant , with SMRs of 0.8 (95% CI = 0.7–1.0) and 1.2 (95% CI = 0.8–1.9), respectively. Nine lung ca ncer deaths were observed as compared to the 5.9 expected (SMR = 1.5, 95% CI = 0.7–2.9). The ab ility to detect statistical significance may have been hindered by the small number of deaths. The numbers of deaths from bladder, lymphatic, and hematopoietic cancers exceeded the e xpected values, but the number of deaths

### DRAFT - DO NOT CITE OR QUOTE 71 were small. Lung cancer deaths were examined by du ration of employment and latency. No trends were noted, and there were no deaths in the group employed for ≥ 15 years. However, 7 lung cancer deaths were observed as compared to t he 4.1 expected in the group with 15 or more years of latency since first exposure. This study was based on a small number of study par ticipants, with less than a quarter reaching the study endpoint of death. The study pr ovides no quantitative assessment as to the level of AN exposure. Mixed exposure is also an is sue, since it is noted that butadiene, styrene, and vinyl pyridine were utilized at the plant durin g the exposure time frame. However, there is no information in the study as to whether the study participants were potentially exposed to these other agents. Finally, though lung cancer was spec ifically analyzed, no mention of data collection or adjustment for smoking history was re ported. These shortcomings limit the weight that this study carries with regard to assessing th e relationship between AN exposure and cancer mortality.

The Netherlands cohort Three successive papers (Swaen et al., 2004, 1998, 1992) reported mortality analyses of a Dutch cohort consisting of 2,842 male workers emplo yed ≥ 6 months from 1956 to 1979 in eight companies that produced AN, latex polymer, acrylic fiber, AN polymers, resins, or acrylamide. This cohort was compared to 3,961 workers at a neig hboring plant during the same time frame who were not exposed to any known carcinogens in th e normal work setting. Use of this reference population aided in minimizing the impact of a potential healthy worker effect. In the original study (Swaen et al., 1992), exposur e assessment for most companies was conducted using a job matrix model and air AN sampl es collected in 1978–1979. The exposure assessment took into account changes in the product ion process, industrial hygiene control measures, and work procedures over time. Potential for exposure misclassification was enhanced by the extrapolation of exposure monitorin g data from one plant to the other seven plants, for which there were no exposure monitoring data. For all of the companies involved, most jobs were classified in the following ranges: 0–0.5, 0.5–1, 1–2, and 2–5 ppm. However, for some jobs, only two categories could be disting uished: 0–2 and 2–5 ppm. For all exposed workers in the study, a cumulative measure of expos ure was derived by multiplying the average concentration for a particular exposure class by th e number of years in that class. Although workers were characterized by duration of exposure and duration of follow-up, these variables were not used in the evaluation of the relationship between AN and cancer deaths. Both the exposed and the unexposed groups were comp ared with national Dutch death rates to generate SMRs. No direct comparison of ra tes in the exposed and unexposed groups was
followed for ≥ 20 years after entry into the cohort. Almost 24% o f the exposed cohort was categorized in the highest category of cumulative e xposure of ≥ 10 ppm-years, a cutoff higher
than the ≥ 8 ppm used in the Blair et al. (1998) study.

### DRAFT - DO NOT CITE OR QUOTE 72 Mortality information was collected for both groups through the end of 1987, allowing at least 8 years of follow-up for all surviving study members. A total of 134 deaths was observed in the exposed group (SMR = 0.78, 95% CI = 0.65–0.9 2) and 572 deaths in the unexposed group (SMR = 0.77, 95% CI = 0.71–0.84), undertaken, with the authors citing differences in age and calendar time between the groups as the rationale. Nearly half of the exposed group worked with AN for at least 5 years, and 26% of the unexposed g roup was both observations significantly lower than expected. As both exposed and unexposed workers were compared to a national rate, the lower observed deaths may be attributable to th e healthy worker effect. Among the workers exposed to AN, no significant differences were note d between the number of observed and expected cancer deaths (i.e., 42 observed deaths vs . 50.8 expected, SMR = 0.83, 95% CI = 0.60– 1.10). Analyses of site-specific cancer deaths in this group did not reveal any significant
differences between the observed cancer deaths and the expected values. However, among the unexposed workers, the number of observed deaths fr om cancer of the trachea and lung was significantly lower than expected (i.e

. , 67 observed deaths vs. 93.3 expected deaths, SMR = 0.72, 95% CI = 0.56–0.90), likely indicating, at least in part, the presence of a healthy worker effect. Among exposed workers in the highest exposure categ ory, the number of observed lung cancer deaths exceeded the number expected (SMR = 1.11, 95 % CI = 0.48–2.19). Compelling evidence of the healthy worker effect is provided by the fac t that the observed number of deaths among the unexposed group, regardless of disease category , is significantly lower than the expected estimates derived from the national population stat istics. In an updated analysis by Swaen et al. (1998), an a dditional 8 years of follow-up yielded 156 more deaths in the exposed cohort and 411 more deaths in the unexposed group, bringing the total number of observed deaths to 290 and 983, res pectively. The exposure assessment was not updated because more recent exposures were consider ed to be negligible. For both groups, the total number of cancers observed was lower than exp ected. The exposed group had 97 deaths from neoplasms observed vs. 110.8 expected (SMR = 0 .88, 95% CI = 0.71–1.06) and the unexposed group had 332 deaths observed vs. 400.4 e xpected (SMR = 0.83, 95% CI = 0.74– 0.92). With the increased follow-up time, slight, but mainly statistically nonsignificant, increases in cancer of the brain, large intestine, prostate, and all leukemias for the exposed group were observed that were not previously evident. Wh ile these increases were based on small numbers, it is noteworthy that intestinal tract and brain are cancer target organs in rat studies. The association between AN exposure and mortality, all-cancer mortality, and lung cancer mortality was examined by the following expo sure variables: latency, peak exposure, cumulative exposure, respirator use, and exposure t o other carcinogens. Overall, among workers exposed to AN, the number of observed deaths did no t differ greatly from expected. Swaen et al. (2004) revisited this cohort of AN wor kers and added 5 years of follow-up to the analysis, for a minimum of 22 years of follow-u p. This updated study added 142 new deaths for the exposed cohort and 360 deaths to the unexpo sed cohort, bringing the total number of

### DRAFT - DO NOT CITE OR QUOTE 73 observed deaths for 432 and 1,343, respectively. T he number of deaths was 2.5-fold higher than in the original cohort study and accounted for over a quarter of the original study population. The exposure assessment was not updated from the fi rst study. SMR analyses were conducted for both the exposed an d unexposed cohorts, using the Dutch general population rates as a comparison. Th e observed number of cancer deaths in the exposed group was not significantly different from the expected value (Table 4-9). The study found that number of respiratory cancer deaths in t his group was higher than expected, 67 observed vs. 62.5 expected (SMR = 1.07, 95% CI = 0.83–1.36). Analyses by peak exposure, respirator use, and possible exposure to cocarcinog ens were also performed, yielding no indication for elevated site-specific cancer risks in any of the subgroups. Additional analyses were performed by examining the SMRs for lung cance r by various measures of dose and latency (Table 4-10). An increasing SMR was noted with increasing levels of exposure (i.e

. , 0.92, 1.06, and 1.15 for low, medium, and high expo sure, respectively).

Table 4-9. Distribution of select mortalities amon g AN-exposed and unexposed workers

Exposed workers Unexposed workers Cause of death Observed Expected SMR 95% CI Observed Expected SMR 95% CI All causes 432 467.8 0.92 0.84–1.01 1,343 1,545.2 0 .87 0.82–0.92 a
All cancers 146 164.5 0.89 0.75–1.04 447 519.8 0.86 0.78–0.94 a Lung and trachea cancer 67 62.5 1.07 0.83–1.36 160 203.8 0.78 0.67–0.92 a

a Statistically significant (

p < 0.05).

Source: Amended from Swaen et al. (2004).

### DRAFT - DO NOT CITE OR QUOTE 74 Table 4-10. Lung cancer mortality of AN-exposed wo rkers stratified by cumulative dose and latency

All cancer mortality Lung cancer mortality Dose Observed Expected SMR 95% CI Observed Expected SMR 95% CI Low (<1 ppm/yr) <10 Yrs latency 0 1.9 – – – 0.7 – – 10–20 Yrs latency 7 7.5 0.93 0.37–1.91 3 2.9 1.03 0.21–2.97
≥ 20 Yrs latency 10 11.3 0.88 0.42–1.62 4 4.0 1.00 0.27–2.53

Total 17 20.7 0.82 0.48–1.31 7 7.6 0.92 0.37–1.89 Moderate (1–10 ppm/yr) <10 Yrs latency 8 8.4 0.95 0.41–1.87 1 3.2 0.31 0.40– 1.58 10–20 Yrs latency 31 32.1 0.96 0.66–1.37 16 12.4 1.29 0.74–2.09
≥ 20 Yrs latency 39 49.4 0.79 0.56–1.08 19 18.2 1.04 0.63–1.63

Total 78 89.9 0.87 0.69–1.08 36 33.8 1.06 0.75–1.47 High (>10 ppm/yr) <10 Yrs latency 8 6.0 1.33 0.57–2.62 3 2.5 1.20 0.24–3.44 10–20 Yrs latency 25 21.1 1.18 0.77–1.75 12 8.4 1.43 0.74–2.49
≥ 20 Yrs latency 18 26.3 0.68 0.40–1.08 9 10.0 0.90 0.41–1.70

Total 51 53.4 0.95 0.71–1.26 24 20.9 1.15 a 0.75–1.68 a

a Calculated based on reported data.

Source: Amended from Swaen et al. (2004).



### In summary, as with previous analyses of this cohor t, the interpretation of the results from this study is limited by the following: poten tial misclassification of AN exposure because of the use of current measures to derive past expos ures and the use of subjective information about exposure, use of a population-based control g roup, pooling of data from factories with different kinds of AN production and exposures with out adjusting for this, and lack of information on smoking. Epidemiology studies based on this Dutch cohort pro vided better exposure assessment than studies using the SAED method or similar extra polation tools. Here, exposure categories represented estimates based, in part, on actual mea surements rather than ordinal ranking. The number of lung cancer deaths observed among the AN- exposed workers was higher than expected. However, the following biases regarding the Dutch cohort studies are possible: potential misclassification of AN exposure because of the use of current measures to estimate past exposures and the use of subjective informatio n about exposure, use of a population-based control group, pooling of data from factories with different kinds of AN production and exposures without appropriate adjustment, and bias based on the lack of smoking information available. The low SMRs observed indicate the pres ence of a potential healthy worker effect, making it more difficult to detect an association w ith AN.

### DRAFT - DO NOT CITE OR QUOTE 75 The Dutch studies cohort utilized an unexposed work er cohort for a “comparison” group. The use of this unexposed group was not fully explo red by developing rates by age and calendar time in the unexposed group to be used as a basis f or developing expected rates in the exposed group. Instead, the unexposed group was compared t o national rates and then used as a “standard” to see if the patterns of SMRs generated in the exposed cohort looked similar to those generated in the unexposed cohort. Therefore, the true comparison group used in these studies was the national population. It should be noted th at the lung cancer SMR among workers exposed to AN was found to be higher than that amon g unexposed workers. Direct comparison between the exposed and unexposed workers in terms of an RR was not derived, as the demographics between the exposed and unexposed work ers may have differed. Though no explicit details were provided, it is noted that th e number of person-years and crude mortality rate are higher in the unexposed workers (recruited from a different plant) than in the exposed workers. Thus, the expected number of deaths for e ach group, on which the SMRs are based, would be dependent on different distributions or st andards, a situation in which comparing the SMRs between the exposed and unexposed groups would not be recommended. Additional support is provided with the increasing SMR with le vel of exposure; a progressive increase of 0.92 in the low exposure group to 1.15 in the high exposure group was reported. Finally, the statistical measure used in all the Du tch cohort studies was the SMR. This statistic allows for the comparison of cause-specif ic deaths and not the incidence of disease. Using deaths as a surrogate for disease may underes timate the true relationship between AN exposure and cancer, especially when the majority o f the cohort population is not deceased. As with other studies that evaluate AN exposure using SMRs, these Dutch studies were focused on determining if AN exposure may lead to an excess of cause-specific deaths; however, these studies lack the appropriate design to address the issue of AN exposure and the incidence of disease, namely site-specific cancers.

BASF plants in Germany A mortality study was conducted among workers from 12 BASF plants in Germany (Thiess et al., 1980). Though none of these plants manufactured AN, this substance, along with styrene and butadiene, was used in many of their pr ocesses. The number of employees in each plant varied, ranging from 30 to 334 employees. Th e first uses of AN at these plants did not occur simultaneously but rather over a course of 14 years, from 1954 to 1968. A total of 1,469 active and former employees who had worked fo r >6 months processing AN were identified for mortality follow-up. The cohort was followed through May 15, 1978, and death
certificates were obtained and coded for cause of d eath. There were 1,081 German workers in the cohort, and the vital status was traced for 98% of these workers. Tracing was less successful for the 388 foreign workers in the cohort, with onl y 56% follow-up.

### DRAFT - DO NOT CITE OR QUOTE 76 No measurements of levels of AN exposure were avail able for use in this study. It was noted that prior to 1976, AN was handled manually, and as a result, there may have been increased exposure during that time (Thiess et al., 1980). In later years, closed systems were utilized, leading to reduced exposures. Although m easurements were not available, this study assumed that workers were occasionally exposed to l evels of ≥ 20 ppm for short periods, based on the manual handling of AN at specific work sites prior to 1976. Several other known carcinogens were used at some of the facilities and could have presented a confounding effect in terms of cancer outcomes. One plant (Plant 5) was subsequently excluded from the analysis because of the potential for concurrent exposure to β -naphthylamine. The comparison rates used for the majority of the a nalyses were derived from mortality rates for the Federal Republic of Germany. The 1,4 69 workers accounted for a total of 15,350 person-years of follow-up. A total of 89 de aths were observed, a value lower than the 99 predicted deaths based on rates for the Federal Republic of Germany (SMR = 0.90, 95% CI = 0.72–1.10). A total of 27 cancer deaths was observ ed for the entire cohort, compared to the 20.5 expected deaths (SMR = 1.32, 95% CI = 0.89–1.8 9). In the analysis that excludes Plant 5, the number o f observed deaths dropped to 74, with the expected deaths at 78.8 (SMR = 0.94, 95% CI = 0 .74–1.17). Among these deaths, 20 were attributed to cancer, with a calculated expected va lue of 16.1 deaths (SMR = 1.24, 95% CI = 0.78–1.88). In both analyses, the number of cancer deaths exceeded expected estimates, but the small sample size might have hindered the observati on of statistically significant findings. When cause-specific cancer deaths were examined, a signi ficant difference was noted between the observed and expected bronchial carcinoma (lung can cer) deaths, regardless of the inclusion of Plant 5 in the analysis (i.e., 11 observed deaths v s. 5.7 expected in the full cohort and 9 observed vs. 4.4 expected in the cohort without Plant 5). Neoplasms of the lymphatic and hematopoietic organs were also observed to be elevated, but not significantly (i.e., 4 observed vs. 1.7 exp ected in the full cohort and 4 observed vs. 1.4 expected in the cohort without Plant 5). Becau se of the small number of deaths in this category, further stratification or examination was precluded. It should be noted that two of the four deaths in this category were from Hodgkin’s di sease, which is significantly different from the 0.3 deaths expected. Analyses were conducted, excluding Plant 5, for the group of workers who were followed for at least 5 years before death or loss to follow -up. This comprised 944 workers, with only seven bronchial carcinomas reported. These carcino ma deaths were stratified by duration of exposure into three categories: 0–4, 5–9, and ≥ 10 years. There were no bronchial carcinomas in the 0–4 year exposure category, four in the 5–9-yea r exposure category and three in the highest exposure category. For the latter two categories, the observed number of deaths was higher than expected (SMR 4–9 years 

### = 3.86, 95% CI = 1.23–9.31; SMR ≥ 10 years 

### = 2.23, 95% CI = 0.57–6.07).

### DRAFT - DO NOT CITE OR QUOTE 77 The study of BASF workers showed a significant exce ss in lung-cancer deaths in workers potentially exposed to AN. The follow-up time was not specifically quantified; however, examination of the exposure (1954–1968) and follow- up (5/15/1978) dates indicates that most
workers in the cohort were followed for at least 9 years. The study is limited by the fact that only 6% of the study cohort was recorded as decease d; this observation is important since death
certificates were used to determine if an associati on between AN exposure and certain cancers existed. An additional limitation of this study is the fact that the cohort was assembled from 12 different plants and some of the plants were ack nowledged to have concurrent exposures to known carcinogens such as β -naphthylamine, vinyl chloride, or solvents. The s tudy did not indicate when these overlaps in exposures could hav e occurred and how many workers at the plant could have been possibly exposed, and no info rmation on the level of exposure was provided. This limitation coupled with a lack of a bility to characterize the workers by job or exposure level makes this study less informative in trying to assess the relationship between cancer mortality and AN exposure.

Six factories in the United Kingdom There have been two successive studies evaluating t he mortality rates in a cohort of male workers potentially exposed to AN at six United Kin gdom polymerization and spinning factories (Benn and Osborne, 1998; Werner and Carter, 1981). For both studies, workers were included if they were employed for at least 1 year between 1950 and 1968. Werner and Carter (1981) examined the mortality rates in a cohort of 1,111 m en drawn from six factories in England, Wales, Scotland, and Northern Ireland. This cohort was followed through the end of 1978, allowing for a minimum 10-year follow-up for all su rviving workers. The workers included in the study were deemed to have the potential for the highest level of AN exposure, since they were involved in either the AN polymerization proce ss or spinning of acrylic fiber. However, no exposure monitoring data were available for the per iod of the study. Additionally, there was potential for concomitant exposure to styrene and b utadiene in the work environment. Each worker in the cohort was classified according to the length of time spent in a highexposure job. This categorization resulted in 934 workers with ≥ 1 years and 177 workers with <1 year of potential for high exposure to AN. The remainder of the analyses focused on the
934 workers with ≥ 1 year in a job with potential for high exposure. Examination of the personyears distribution by age group in these 934 worker s revealed that <2% of the person-years was observed in persons over age 65, while 65% of the p erson-years was observed in the 15–44-year age range. Thus, the follow-up time for this cohor t may be inadequate to detect excess cancer
deaths. Among the 934 workers, 68 deaths were observed comp ared to the 72.4 expected based on mortality rates for the total male population of England and Wales (SMR = 0.93, 95% CI = 0.73–1.18). Of these observed deaths, 21 were attr ibuted to cancer, with 9 specifically attributed

### DRAFT - DO NOT CITE OR QUOTE 78 to cancer of the trachea, bronchus, and lung. The SMRs for all malignant neoplasms and cancer of the trachea, bronchus, and lung are 1.10 (95% CI = 0.72–1.70) and 1.20 (95% CI = 0.58– 2.17), respectively. Incidentally, the number of o bserved stomach cancer deaths was significantly higher than expected (5 observed vs. 1.9 expected, SMR = 2.63, 95% CI = 0.96– 5.83).
The distribution of cancer deaths was also examined by age at death (age groups: 15–44, 45–54, 55–64, and ≥ 65 years). No significant differences between the number of observed and expected all-cause deaths were found in any of the age groups. Of the 14 deaths observed in the 15–44-year age group, 3 deaths were attributed to c ancer of the trachea, bronchus, and lung, a significant increase over the 0.7 expected value (S MR = 4.28, 95% CI = 1.09–11.66). No significant differences between observed and expect ed cancer-specific deaths were noticed in any of the other age groups.
All-cause deaths were also stratified based on the year of first exposure to determine if cancer risks were higher for those who were exposed in the early years of the factories’ operations (usually a surrogate for longer and ofte n higher exposure and longer latency) compared with more recent hires. Three time period s were examined: 1950–1958, 1959–1963, and 1964–1968, with the observed number of deaths b eing 35, 21, and 12, respectively. No significant differences between the number of obser ved and expected deaths were found. Observed and expected deaths from all cancer types, including cancer of the trachea, bronchus, and lung, were similar in all three time periods, w ith only a slight increase in the most recent time period (i.e., 1964–1968) (all-cancer SMR = 1.3 6, 95% CI = 0.55–2.83; cancer of the trachea, bronchus, and lung SMR = 1.87, 95% CI = 0. 48–5.10). In order to further examine latency, an analysis of cancer deaths by length of time since first exposure was performed. No increases in canc ers of the stomach or cancers of the trachea, bronchus, and lung were noted with increasing time since first exposure. Similarly, the observed
increases in cancers of the stomach and of the trac hea, bronchus, and lung could not be related to duration of exposure, year of first exposure, or la tency. It should be noted that the study power to examine these parameters was quite limited. Fur thermore, 25% of the cohort (foreign workers, who may have had the highest exposure) wer e lost to follow-up, potentially introducing a bias resulting from an under-ascertainment of dea ths. Another shortcoming of this study was that the comparison group selected to derive the ex pected values may not have been representative of the other regions and the compari sons may have been biased downwards by the healthy worker effect. This study was also limited by the short length of follow-up and small
number of deaths observed. Aside from the shortcom ings of this study, if an effect of AN were to be observed, one would expect cancer rates to be elevated in the group with the earliest years of first exposure, which represents the workers wit h the highest potential for greater exposure, longest follow-up, and longest latency. The fact t hat increases were observed in the most recent group (i.e., those first exposed between 1964 and 1 968) weakens the argument that there was an

### DRAFT - DO NOT CITE OR QUOTE 79 exposure effect demonstrated in this study, because the latter group probably had lower exposure levels and fewer than 15 years latency and follow-u p. In the update of the above study, Benn and Osborne (1998) expanded the sample to include workers employed in the same six AN polymer ization and acrylic fiber spinning factories from 1969 to 1978 and extended follow-up through 1991, allowing for at least 13 years of follow-up. Added to the study were craftsmen wi th possible AN exposure, control laboratory workers, other possibly exposed workers, and unexpo sed workers. The sample size was 2,763 men employed for ≥ 1 year. The exposure assessment in this study was based on a threshold limit enacted by the British government i n 1981, a few measurements from the late 1970s, and an exposure estimated for the period 195 8–1977 by a chemist at one of the factories. The available exposure measurements were found to b e lower than the calculated 8-hour timeweighted average (TWA) (0.4–2.7 vs. 20 ppm, respect ively). Job titles were collapsed into three AN exposure categories: polymer workers and spinne rs—“high”; craftsmen, control laboratory workers, and others with possible AN exposure—“othe r or medium”; and all others into the “little or no” AN exposure group. No details were provided on how these categories were based on the previously described exposure estimates. Un like the earlier study by Werner and Carter (1981), death rates for England and Wales were used to calculate expected deaths for the factories that were located in England and Wales. Scottish rates were used for the factories located in Scotland and Northern Ireland (rates for Northern Ireland were not available). The 13 years of follow-up resulted in a total 409 o bserved deaths, a value significantly lower than the expected (SMR = 0.84, 95% CI = 0.76– 0.93). This result demonstrates a likely healthy worker effect. Stratifying by cause of dea th, no significant differences were noted between observed and expected deaths (Table 4-11), except in the case of all-circulatory diseases, in which the number of observed deaths wa s significantly lower than expected (SMR = 0.86, 95% CI = 0.75–0.99). Upon stratification by the level of AN exposure, no significant excess in cause-specific mortality was observed (Ta ble 4-11); however, an excess of lung, trachea, and bronchial cancers in the highest expos ure group was found. In addition, linear regression analysis found a significant increasing trend between level of AN exposure and stomach cancer mortality. The distribution of caus e-specific deaths was also examined by age of death, with age categorized in the same manner as b y Werner and Carter (1981). No significant
difference was found between the observed number of deaths in each age category and the expected value. This observation was also noted wh en all-cancer mortality was stratified by age group. Interestingly, among the youngest cohort of AN-exposed workers, the number of observed deaths from respiratory cancers was signif icantly higher than expected (5 observed vs. 0.8 expected, SMR = 6.10, 95% CI = 2.23–13.51).

### DRAFT - DO NOT CITE OR QUOTE 80 Table 4-11. Distribution of select mortalities amo ng AN-exposed and unexposed workers

Exposure level
Cause of death High Possible Little or none Total
O a E a SMR O a E a SMR O a E a SMR O a E a SMR
All causes 170 181.2 0.94 (0.80–1.09) 97 124.7 0.78 b (0.63– 0.94) 142 179.6 0.79 b

(0.67– 0.93) 409 485.5 0.84 b

(0.76–0.93)

All cancers 58 50.1 1.16 (0.89–1.49) 22 35.9 0.61 b (0.39– 0.91) 41 51.1 0.80

(0.58– 1.08) 121 137.1 0.88

(0.74–1.05)

Lung, tracheal, bronchial

cancer 27 19.1 1.41 (0.95–2.03) 7 13.3 0.52 (0.23– 1.04) 19 19.1 0.99

(0.62– 1.52) 53 51.5 1.03

(0.78–1.34)

Stomach

cancer c 7 4.2 1.66 (0.73–3.30) 3 2.9 1.03 (0.26– 2.81) 1 4.3 0.23

(0.01– 1.15) 11 11.4 0.96

(0.51–1.68)

Circulatory disease 81 86.9 0.93 (0.74–1.15) 49 59.1 0.83 (0.62– 1.09) 70 86.2 0.81

(0.64– 1.02) 200 232.2 0.86 b

(0.75–0.99)

a O = observed deaths; E = expected deaths.
b Statistically significant ( p < 0.05).

c Statistically significant trend ( p < 0.05).

Source: Amended from Benn and Osborne (1998).



### Data were also analyzed by stratifying by year of f irst exposure, time since first exposure, and length of exposure. The latter variables were divided into the following groups: <5, 5–10, 10–15, and >15 years. When cause-specific deaths, including all cancers and respiratory cancers, were examined within these categories, no significant differences were noted between observed and expected values. However, a significa nt increasing trend was noted for all deaths and circulatory diseases based on time since first exposure but not with length of exposure. The analysis that focused on cause-specific mortality a nd the year of first exposure differed from the previous study by Werner and Carter (1981) in that workers were divided into the following three groups: pre-1960, 1960–1968, and post-1968. No differences in all-cause or cancer deaths were noted between the observed and expected values , but a significant increase in respiratory cancer deaths was noted in the subgroup of workers that were exposed post-1968 (7 observed deaths vs. 2.6 expected deaths, SMR = 2.70, 95% CI = 1.18–5.32). This study increased the number of observed deaths sixfold as compared with the number of deaths reported in the previous study by Werner and Carter (1981). The number of cancer deaths, including deaths from lung cancer, also ros e proportionally. However, the number of observed deaths only represented less than 15% of t he studied cohort and thus may have contributed to not finding an overall statistically significant association between lung cancer and

### DRAFT - DO NOT CITE OR QUOTE 81 exposure to AN. As seen in the initial study, canc ers of the trachea, bronchus, and lung (respiratory cancers) were elevated in the youngest age group. While significant, this statistic was based on five subjects in the younger age group . Also noted was the fact that there was a significant elevation of deaths from cancers of the trachea, bronchus, and lung in the workers who were first exposed in 1969 and later, rather th an those first exposed prior to that year. Smoking history, an important confounder when asses sing cause-specific lung cancer, was not addressed. The analyses on the high-exposure group included fewer than 800 workers from the total cohort; therefore, power to detect trends and excess deaths was limited in this part of the publication. Although not statistically significan t, an increased SMR for lung, tracheal, and bronchial cancers was observed in the high exposure group (SMR = 1.41, 95% CI = 0.95–2.03, n = 27). The finding of an increase in stomach can cer in the high exposure group is interesting,
but the small total number of stomach cancer deaths (n = 11) makes rigorous analysis difficult. This study had no quantitative AN levels, use of a population reference group could have masked associations, and statistical power needed t o detect rare cancers such as stomach cancer
was low. There was no evidence of a dose-related t rend between increasing AN exposure and respiratory cancer, which is not surprising given s tudy deficiencies and the lack of quantitative exposure data.

Acrylic fiber factory in Italy A retrospective cohort study was conducted with 671 male workers who had at least 12 months of exposure to AN (or mixed exposure to A N and dimethylacetamide) at an acrylic fiber factory in Venezia, Italy (Mastrangelo et al. , 1993). Mortality patterns were examined to
determine whether excess cancer cases were related to these exposures. Occupational exposure to AN occurred between 1959 and the end of 1988, wi th mortality tracked until the end of 1990, thus allowing at least 2 years of follow-up for eve ry person in the cohort. Workers with past exposure to vinyl chloride or benzidine were exclud ed from the study cohort. Study participants were categorized based on their level of AN exposur e as follows: (1) high exposure to AN only, (2) low exposure to AN plus exposure to dimethylace tamide, and (3) episodic exposure to AN plus exposure to dimethylacetamide. SMRs were calc ulated based on the observed deaths and the expected number of deaths in the general popula tion. The expected death rate took into account age, gender, year, cause, and person-time. No significant difference in all-cause mortality wa s observed during 1959–1990, with only 32 deaths (4.7% of total cohort) being reporte d. A total of 12 deaths from cancer was
observed in the total cohort. This observation was slightly, but not significantly, higher than the 8.73 expected cancer deaths. None of these cancer deaths was observed among the 100 workers who were only exposed to high levels of AN. Of the 12 cancer cases, there were 2 lung cancer cases and 4 intestinal cancer cases. The lung canc er cases were observed among the 272 workers who had discontinuous but episodic exposure to AN a nd dimethylacetamide, and the number was

### DRAFT - DO NOT CITE OR QUOTE 82 not significantly different than the expected numbe r of lung cancer cases. The intestinal and colon cancer cases were equally distributed between the groups that had concomitant exposure to dimethylacetamide and were significantly higher tha n expected in both groups. When analyses were stratified by duration of exposu re and time since first exposure, no relationship was found with regard to all-cause mor tality or all cancers. Among individuals exposed for 1–4 years, significant differences were noted between the number of observed testicular, rectal, intestinal, and colon cancer de aths and the expected values. However, the number of cancer-specific deaths was small, with on ly one or two deaths being attributed to the above cancer types. In addition to questions about the comparison group , the ability of this study to greatly inform an assessment of the relationship between AN and cancer is quite limited due to its small sample size. The follow-up time is also short, as reflected by the fact that less than 5% of the cohort was deceased by the end of the follow-up per iod. These factors combined may contribute to the study’s lack of sufficient power to determin e if AN exposure is associated with cancer.

National Cancer Institute (NCI) cohort study Many studies have investigated the relationship be tween AN exposure and cause-specific death using a cohort assembled by the NCI (Starr et al., 2004; Marsh et al., 2001, 1999; Blair et al., 1998). The studies were found to differ by th e types of analyses used, comparison groups, cohort subsets, or years of follow-up. Blair et al. (1998) assembled a cohort of 25,460 wo rkers (18,079 white males, 4,293 white females, 2,191 nonwhite males, and 897 nonwhite females) who were employed in AN production or use beginning in the 1950s through 1983. The cohort included workers who were employed prior to 1984 and after the start-up of AN operations (between 1952 and 1965) at one of eight plants located in Alabama, Florida, Lo uisiana, Ohio, Texas, and Virginia. This method allowed for the examination of both AN-expos ed workers and unexposed workers. Workers were followed through the end of 1989, allo wing ≥ 6 years of follow-up. Exposure was assessed for each plant by developing a quantitative estimate for each job, department, and time period. Sources used to devel op the estimates were walk-through surveys, personal and area monitoring data, and interviews w ith longtime workers. The exposure assessment for this study was more detailed (Stewar t et al., 1998) than for any previously published study. More than 10,000 estimates were d eveloped for 3,662 job, department, and plant combinations for a 30-year period of time. I ndividual worker exposure estimates were developed, including estimates for workers whose ex posures were difficult to estimate because of their movement through all areas of a plant (i.e ., maintenance workers). The estimation methods were compared with actual data for validati on. SMR analyses were performed to compare observed mor tality in both the exposed and unexposed groups to expected numbers of deaths base d on U.S. race- and gender-specific death

### DRAFT - DO NOT CITE OR QUOTE 83 rates. Subsequent analyses used the unexposed work er rates to develop internal comparison rate ratios adjusted for birth year, plant, calendar tim e, race, gender, wage, and salary status. These comparisons alleviate the healthy worker effect tha t is expected when using external general population rates. Smoking history was obtained on a sample of workers by using a case-cohort design to allow statistical adjustment for risk est imates calculated for known smoking-related cancers, such as lung cancer. A 10% sample of livi ng workers was chosen at random to be interviewed regarding their smoking history. A 10% sample of persons deceased prior to 1983 was chosen, and next-of-kin interviews were at tempted. Also, all brain and lung cancer deaths that were not chosen in the 10% sample of de ceased persons were also selected for nextof-kin interview. At the end of the study, the total person-years for the exposed workers was 348,642, while the person-years for the unexposed w orkers tallied 196,727. More than 66% of the members of the cohort had at least 20 years of follow-up. A total of 1,217 exposed workers and 702 unexposed workers were known to be deceased . For all-cause mortality, significant lower numbers of observed deaths than expected were reported for both AN-exposed and unexposed groups (Table 4-12). This pattern is als o noted for all-cancer mortality among exposed workers; however, no statistically signific ant difference between observed and expected deaths was found among the unexposed workers. A si milar observation was made for lung and tracheal cancer death, with SMR values for AN-expos ed and unexposed workers being 0.9 (95% CI = 0.8–1.1) and 0.8 (95% CI = 0.6–1.1), respectiv ely (Table 4-12). Interestingly, among the exposed workers, the numbers of observed deaths fro m pancreatic cancer, lymphosarcoma, and reticulosarcoma, as well as noncancer deaths like d iabetes, cerebrovascular disease, and liver cirrhosis, were significantly lower than expected v alues. Upon comparison of the exposed workers to the unexposed workers, a small excess in lung and tracheal cancer deaths was observed (see RR in Table 4-12).

Table 4-12. Distribution of select mortalities amo ng AN-exposed and unexposed workers

Exposed workers Unexposed workers Cause of death Observed SMR 95% CI Observed SMR 95% CI RR (95% CI)
All causes 1,217 0.7 0.6–0.7 a 702 0.7 0.7–0.8 a 0.9 (0.8–1.0)
All cancers 326 0.8 0.7–0.9 a 216 0.9 0.8–1.0 0.8 (0.7–1.0) Lung and tracheal cancer 134 0.9 0.8–1.1 59 0.8 0.6–1.1 1.2 (0.9–1.6)
Pancreatic cancer 10 0.5 0.3–0.9 a 13 1.2 0.7–2.1 0.4 (0.2–1.0)
Cerebrovascular disease 37 0.5 0.4–0.7 a 23 0.5 0.4–0.8 a 0.9 (0.5–1.6)

a Statistically significant (

p < 0.05).

Source: Amended from Blair et al. (1998).

### DRAFT - DO NOT CITE OR QUOTE 84 Data were stratified by time since first exposure ( <10, ≥ 10–20, and ≥ 20 years) to examine any evidence of latency effects. Using the unexpos ed group for comparison, no significant increases in cancer deaths were observed among AN e xposed workers in any of the latency intervals examined. The RRs for lung cancer mortal ity were increased for the longer latency periods; however, these RRs and the overall trend w ere not statistically significant. The RRs were 0.4, 1.6, and 1.3 in the <10-years exposure gr oup, the ≥ 10–20-years group, and the
≥ 20 years group, respectively. Cumulative exposure was examined by stratifying the data into five exposure groups: <0.13, ≥ 0.13–0.57, ≥ 0.57–1.5, ≥ 1.5–8.0, and ≥ 8.0 ppm-years. There was no evidence of a doseresponse effect across the quintiles of exposure wh en death rates for all cancers combined were examined. Similarly, lung cancer death rates did n ot increase across the exposure categories with rate ratios of 1.1, 1.3, 1.2, 1.0, and 1.5, re spectively. A sufficient number of lung cancer deaths were available to analyze the relationship b etween latency and cumulative exposure. Among the lung cancer deaths that occurred within 1 0 years since first exposure to AN, there was no significant increase in deaths with increasi ng exposure. This observation is also noted for lung cancer deaths occurring 11–19 years after firs t exposure to AN. For the workers with
≥ 20 years since first exposure, a statistically sign ificant rate ratio of 2.1 (95% CI = 1.2–3.8) was reported in the highest cumulative exposure quintil e; however, there was not a significant exposure-response trend ( p = 0.11). The risk of lung cancer mortality was also analyzed by other exposure variables, including duration, intensity, frequency of peak ex posures, and cumulative exposures, considering different lag periods and adjustment fa ctors. Most exposure variables showed a nonsignificant increase in lung cancer deaths among workers with the highest level of AN exposure, but none yielded a strong exposure-respon se gradient or statistically significant exposure-response trend. No exposure-response patt erns were observed for duration of exposure at any intensity level. Additional analyses focused on the workers with 20 or more years since first exposure in order to examine the factors that might contribute to increased risk of lung cancer at the highest cumulative exposure level in this group. The incre ased risk was not observed when analyses were restricted to workers first employed between 1 960 and 1969. This could be because workers who were first employed between 1960 and 19 69 would have at least 10 fewer years of follow-up than those hired before 1960 and would te nd to be younger. Also, having a later hire date would allow workers in this group less time to work and accumulate exposure, so they would be less likely to be included in the highest quintiles of exposure. This is confirmed by the fact that 42 lung cancer cases were observed in the two highest quintiles for those first hired before 1960, and 9 were observed in the two highest quintiles for those first hired between 1960 and 1969. The increase in risk in the highest exposure quintile was evident in both wage and salary employees and for both fiber and nonfibe r plants for this group that was followed for

### DRAFT - DO NOT CITE OR QUOTE 85 20 or more years after first exposure. None of the trend tests for cumulative exposure in workers with 20 or more years since first exposure was sign ificant. Smoking history was sought on a 10% sample of study subjects. A total of 2,655 workers was identified for interview, and 1,890 (71%) of th is group were interviewed. For lung cancer deaths, 64 next-of-kin interviews were conducted. Additional analyses were performed by controlling for smoking status. These analyses did not change previous results, although they did result in a slight reduction in the risk ratios in the highest quintile of exposure. Blair et al. (19 98) stated that they assumed that if smoking data were available for the full cohort, then the smoking adjustment would yield the same proportion of effec ts in the full cohort as in the subcohort. In summary, the sample size and follow-up time in t his study were likely large enough to detect any substantial elevation of cause-specific cancer deaths. For lung and tracheal cancer deaths, an elevated RR of 1.2 (95% CI = 0.9–1.6) wa s observed in AN-exposed workers compared to the unexposed worker population. With lung cancer deaths as the surrogate for the development of lung cancer and less than 10% of the worker population being deceased at the time of the study evaluation, lung cancer risk may have been underestimated. The study authors state that increased risk with latency or cumulativ e exposure in separate analyses was not
demonstrated. This observation could be attributab le to the reduced level of power in the subgroup analyses. However, a statistically signif icant RR of 2.1 (95% CI = 1.2–3.81) was observed in the highest cumulative exposure quintil e among workers with ≥ 20 years since first exposure. Overall, this study provides suggestive evidence with regard to AN exposure and lung

cancer. Marsh et al. (1999) added 7 years of follow-up and focused on analyzing a subset of the original cohort of Blair et al. (1998). The subcoh ort was comprised of 992 white male workers
who had worked for ≥ 3 months between 1960 and 1996 at a chemical plant in Ohio. Analyses included the calculation of SMRs and RRs for catego ries of exposure and latency for lung cancer and the calculation of SMRs (based on regional mort ality rates) and RRs for stomach, prostate, large intestine, and lymphohematopoietic cancers by cumulative exposure level. Exposure assessment in this cohort mirrored that of the original cohort study by Blair et al. (1998) with the following modifications. A pan el of industrial hygienists used all of the exposure data collected to assign calendar time-spe cific categories to each job title. The following categories were designated: <0.2, ≥ 0.2–2.0, 2.1–20.0, and >20.0 ppm. Job titles were also assessed for the potential for exposure to nit rogen products in a qualitative manner (potential, no potential). Marsh et al. (1999) men tioned that other known potential occupational hazards at the plant included asbestos, 1,3-butadie ne, and depleted uranium; exposure to these chemicals was not assessed. However, in the exposu re assessment by Stewart et al. (1998) on this cohort, these chemicals were not singled out a s impactful potential occupational hazards. For AN exposure, the quantitative evaluations for e ach job title were used to compute three timedependent measures of exposure for each worker who held any job where AN exposure was

### DRAFT - DO NOT CITE OR QUOTE 86 possible. These measures included duration of expo sure, cumulative exposure, and average intensity of exposure. Cumulative exposure was rec orded in ppm-years, with workers being assigned to one of the following categories: >0–0. 139, 0.14–0.579, 0.58–1.509, 1.51– 7.999 ppm-years, and ≥ 8.000 ppm-years. Unlike the study by Blair et al. (1998), which measured person-year accumulation from the first da y of employment at the plant to the end of
1989 or date of death or last date known to be aliv e, Marsh et al. (1999) extended their 1960– 1988 job exposure matrix to include new job categor ies and monitoring data through 1996. Thus, the exposure assessment by Marsh et al. (1999 ) covers all jobs held from the beginning of the plant operation (1960) through the end of 1996.
The total cohort of 992 workers included 474 worker s who never worked in a job where AN exposure was possible and 518 workers who were p otentially exposed to AN in at least one of their jobs. A total of 110 deaths was observed in the cohort through the end of 1996. Smoking history was collected for 90.3% of the tota l cohort and 93.2% of the AN-exposed group. The prevalence of smokers was similar betwe en the two groups with 58% of the unexposed workers being smokers and 62.5% of the ex posed workers being smokers. However, the prevalence of smoking in the exposed group was associated with the level of cumulative AN exposure and increased with increasing levels of ex posure. Of the 110 deaths observed, 43 deaths were attribut ed to cancer. The observed number of cancer deaths did not differ from expected values b ased on the U.S. mortality rates or the regional death rates, with SMRs of 0.98 (95% CI = 0 .71–1.32) and 0.97 (95% CI = 0.70–1.31), respectively. Fifteen of the observed cancer death s were attributed to respiratory cancers, which showed a similar pattern of nonsignificant SMRs <1 (Table 4-13). With the exception of bladder tumors, none of the other site-specific cancers eva luated showed a significant difference between observed and expected values using either the U.S. mortality rates or the regional mortality rates. The number of bladder cancer deaths among workers w as significantly higher than expected (SMR = 4.5, 95% CI = 1.23–11.53); however, all the deaths occurred among workers not exposed to AN.

### DRAFT - DO NOT CITE OR QUOTE 87 Table 4-13. Distribution of mortality among AN-exp osed workers

Exposed workers Unexposed workers Overall cohort

Cause of death Ob SMR (95% CI) Ob SMR

(95% CI) Ob SMR US

(95% CI) SMR regional

(95% CI) RR

(95% CI)
All causes 41 0.58 a 0.42–0.79 69 0.78 b

0.60–0.98 110 0.64 a

0.53–0.77 0.69 a

0.57–0.83 0.74

0.5–1.1
All cancers 17 0.88 0.52–1.42 26 1.04

0.68–1.53 43 0.98

0.71–1.32 0.97

0.70–1.31 0.87

0.4–1.7 Respiratory

cancer 9 1.28 0.58–2.42 6 0.64

0.24–1.40 15 0.88

0.49–1.43 0.92

0.51–1.51 1.98

0.6–6.9
Bladder and other urinary

cancer 0 – 0.00–8.23 4 7.01 a

1.91–17.96 4 4.50 a

1.23–11.53 3.93 a

1.07–10.06 Not

determined

a Statistically significant (

p < 0.05).

Ob = observed deaths

Source: Amended from Marsh et al. (1999).



### For respiratory cancers, there were nine observed d eaths in the exposed group and six in the unexposed group, leading to a risk ratio of 1.9 8 (95% CI = 0.6–6.9) (Table 4-13). This indicates that there was nearly 2 times the rate of lung cancer deaths in the exposed group as in the unexposed group. Respiratory cancer deaths wer e further examined using RR regression models that were able to adjust for age and calenda r time as well as one other potential confounding factor, such as year of hire or smoking . Two variables were marginally associated with lung cancer risk in the total cohort (exposed and unexposed workers): duration of employment and time since first exposure. Smoking was not related to lung cancer risk; therefore, it is probable that there was misclassif ication of this risk variable, and use of smoking information in models of time-related exposure vari ables to control for a smoking effect was not possible. Regression analyses performed using cate gories of duration of exposure, cumulative exposure, and average exposure compared to no expos ure were not more informative than previous analyses that compared exposed to unexpose d rates. For each analysis, the exposed worker RR was approximately 2 times that for unexpo sed workers across all categories of exposure (Table 4-14). The risk ratios, derived in the regression analysis, increased with exposure level and time since first exposure, thoug h the small numbers of observed deaths may have hindered the observation of a statistically si gnificant increasing trend.

### DRAFT - DO NOT CITE OR QUOTE 88 Table 4-14. Summary of relative regression analyse s for cancer of the bronchus, trachea, and lung

Exposure measure Category Observed deaths RR 95% CI Unexposed 6 1.00
>0–4.9 3 1.71 0.25–8.94
5.0–13.9 3 2.28 0.35–11.38 Duration (yrs)

14.0+ 3 2.15 0.34–10.70 Unexposed 6 1.00
>0–7.9 2 1.96 0.81–12.04 Cumulative exposure (ppm-yrs)

8.0+ 7 2.07 0.58–7.58 Unexposed 6 1.00
>0–7.9 2 1.97 0.18–12.10
8.0–109.9 4 2.15 0.43–9.33 Cumulative exposure (ppm-yrs)

110.0+ 3 1.97 0.31–9.42 Unexposed 6 1.00
>0–4.9 3 1.97 0.31–9.54
5.0–11.9 3 1.70 0.26–8.26 Average exposure (ppm)

12.0+ 3 2.64 0.42–12.67

Source: Amended from Marsh et al. (1999).



### The risk ratio for all-cancer mortality and AN expo sure derived by Marsh et al. (1999) was similar to the risk ratio derived in the larger -scale study by Blair et al. (1998). Despite the
limitations of the small number of observed deaths and the focus on only white males, this study does indicate that there may be an association betw een AN exposure and increased risk in respiratory cancer deaths. Marsh et al. (2001) performed a sensitivity analysi s on data from the original cohort of Blair et al. (1998), examining dependency of lung c ancer RR estimates on selection of referent populations. Exposure categorization from the Blai r et al. (1998) study was retained for this analysis, but the comparison groups differed. Mort ality analyses were performed using U.S. mortality rates and local county rates. SMRs were calculated for both AN-exposed and unexposed workers. Upon comparison with U.S. and regional mortality ra tes, both exposed and unexposed workers were found to have significantly lower rate s of all-cause mortality. Using the U.S. morality rates, the SMRs for the unexposed group an d the exposed group were 0.75 (based on 702 deaths, 95% CI = 0.7–0.8) and 0.66 (based on 1, 217 deaths, 95% CI = 0.6–0.7), respectively. The SMRs for all-cause mortality utilizing regional rates were nearly identical to those using U.S. rates. Additionally, the number of lung cance r deaths observed among workers, both exposed and unexposed, was significantly lower than regional estimates, with SMRs for each group of workers being 0.74 (95% CI = 0.6–0.9) and 0.68 (95% CI = 0.5–0.9), respectively, compared with U.S. population rates. These finding s indicate a potential healthy worker effect.

### DRAFT - DO NOT CITE OR QUOTE 89 Observed lung-cancer deaths were stratified by the cumulative exposure to AN and time since first exposure to derive RRs and regional-mortality -rate-based SMRs (Table 4-12). Workers with the highest cumulative exposures and at least 20 years of exposure were twice as likely to have lung cancer as unexposed workers (RR = 2.1, 95 % C.I = 1.2–3.8). The numbers of observed and expected deaths in this highest exposu re, longest duration category were about the same using external comparisons (SMR = 1.07, 95% CI = 0.7–1.6). This illustrates how the use of an external comparison population can mask an ap parent association; the discrepancy is most likely attributable, at least in part, to the healt hy worker effect. There was no evidence of a linear exposure-response relationship for lung canc er, based on the categories used to assess time since first exposure. SMRs in each category did ap pear to increase with increasing cumulative exposure category (Table 4-15).

Table 4-15. Distribution of observed lung cancer d eaths among AN-exposed workers, using regional rates for comparison

Time since first exposure Less than 10 yrs 10–19 Yrs At least 20 yrs Cumulative
exposure (ppm-yrs) Ob RR (CI) SMR (CI) Ob RR (CI) SMR (CI) Ob RR (CI) SMR (CI)
>0–0.13 7 0.4

(0.2–1.2) 0.72

(0.3–1.5) 9 0.5

(0.5–3.2) 0.71

(0.3–1.4) 11 1.1

(0.6–2.2) 0.56

(0.3–1.0)
0.13–0.57 3 0.4

(0.1–1.4) 0.63

(0.1–1.8) 12 2.6 a

(1.2–5.7) 1.18

(0.6–2.1) 11 1.0

(0.6–2.2) 0.57

(0.3–1.0)
0.57–1.50 2 0.4

(0.1–1.6) 0.70

(0.1–2.5) 10 2.0

(0.9–4.8) 1.01

(0.5–1.8) 16 1.2

(0.5–2.1) 0.71

(0.4–1.2)
1.50–8.00 2 0.4

(0.1–2.0) 0.87

(0.1–3.1) 7 1.2

(0.5–3.1) 0.66

(0.3–1.4) 18 1.2

(0.6–2.2) 0.61

(0.4–1.0)
≥ 8.00 1 0.4

(0.1–3.1) 0.81

(0.02–4.5) 4 0.9

(0.3–1.2) 0.54

(0.2–1.4) 21 2.1 a

(1.2–3.8) 1.07

(0.7–1.6)

a Statistically significant (

p < 0.05).

Ob = observed deaths

Source: Amended from Marsh et al. (2001).



### To look for plant-specific risks, the lung-cancer d eaths in each of the eight study plants were analyzed separately by cumulative level of exp osure. Only one plant showed an increased risk of lung-cancer deaths among the exposed worker s, with the highest level of exposure (i.e.,
≥ 8 ppm-years) having an SMR of 2.68 (based on 10 dea ths, 95% CI = 1.3–4.9). There was no comparison of process differences in the plants, th us raising uncertainty as to whether workers at this plant were exposed to other potential carcinog ens or if these findings were due to chance. In addition, the small number of observed lung-cancer deaths in the plant-specific exposure categories lowers the level of power this study had to discern trends in SMRs that might provide more information on the association between AN expo sure and cancer.

### DRAFT - DO NOT CITE OR QUOTE 90 In summary, Marsh et al. (2001) focused on external comparison groups rather than the available unexposed worker cohort. The use of an e xternal comparison group, rather than a cohort more comparable to the exposed population (i .e., internal comparison group), may subject the relationship between exposure and lung cancer t o biases such as the healthy worker effect. Internal comparison groups are generally preferred since they tend to be less influenced by the healthy worker effect, other sources of selection b ias, and confounding (Checkoway et al., 1989). Marsh et al. (2001) mentioned potential occupationa l hazards such as asbestos, 1,3-butadiene, and depleted uranium not being assessed. Stewart e t al. (1998) conducted an exposure assessment for the cohort of workers exposed to AN. Exposure to 340 substances other than AN was assessed qualitatively. 1,3-Butadiene and deple ted uranium were not among the chemicals with exposures of >20,000 person-years. Additional ly, Blair et al. (1998) did not observe any deaths from asbestosis or mesotheliomas, which woul d have been indicative of asbestos

exposure

. 

### The reanalysis by Marsh et al. (2001), particularl y the RR results, does support the association, found by Blair et al. (1998), between AN exposure and increased lung cancer mortality risk among workers with the highest expos ure level, but the healthy worker effect, small sample sizes within subcategories, use of ext ernal controls, and short follow-up may limit the detection of stronger support for such an assoc iation. Data from this cohort were reanalyzed employing sem iparametric Cox regression models with time-dependent covariates to estimate addition al risk of death from lung cancer for several different AN occupational exposure scenarios (Starr et al., 2004). The “cumulative exposure estimate” was a time-dependent covariate, and “plan t worked” was a time-independent covariate. The analysis focused on the largest race-sex group (18,079 white males) from the original Blair et al. (1998) study. The Cox models allowed for th e calculation of the cumulative risk of dying from a disease by a certain age. The outcome measu rement used was the risk of dying from lung cancer by age 70 years. Baseline rates were develo ped for the unexposed worker population and for three different AN exposure scenarios: (1) ear ly intense exposure, (2) long moderate exposure, and (3) late intense exposure. All scena rios provided 50 ppm-years of cumulative exposure by age 55 years. The increased number of lung cancers per 1,000 workers that would develop by age 70 was calculated as 0.77–1.56, 0.74 –1.50, and 0.68–1.56, respectively (the ranges reflect the use of different plant-specific baseline rates). The upper bound of additional risk was in the range of 7.5–15.1 per 1,000 workers with the upper bound on the exposure parameter being 0.0048 per ppm-working year. It is important to note that this study analysis did not control for smoking. Also, based on the extent of exposure misclassification, any exposureresponse association may have been underestimated. In summary, the study by Blair et al. (1998) report ed an elevated risk of lung cancer deaths among AN-exposed workers as compared to the unexposed workers, particularly among workers in the highest cumulative exposure quintile with ≥ 20 years since first exposure (RR = 2.1, 95% C.I. = 1.2–3.8). However, the short follo w-up may have contributed to the study’s

### DRAFT - DO NOT CITE OR QUOTE 91 inability, overall, to demonstrate an increased ris k associated with latency or cumulative exposure. Similar to Blair et al. (1998), Marsh et al. (1999) found an increased risk of lung cancer deaths among AN-exposed workers as compared to the unexposed workers, though the point estimate of 1.98 was not statistically signif icant. However, Marsh et al. (1999) only focused on a small subset of the NCI cohort. Thoug h the small sample size and the study inclusion of only white males reduces the statistic al power and generalizability of the study, the observation of the excess lung cancer risk in Marsh et al. (1999) does provide some weight with regard to hazard inferences. Marsh et al. (2001) utilized primarily an external comparison group and, while they provide better stability of comparison rates than i nternal controls as used by Blair et al. (1998), a limitation of external controls as the referent pop ulation is the risk of having potential associations masked by a healthy worker effect or o ther factors that may be more similar within an occupational cohort than between the cohort and the general population. The results from Marsh et al. (2001) indicate the presence of such a n effect dampening the observation of an
association between AN and cancer. Though the studies by Marsh et al. (2001) and Blair et al. (1998) have a relatively large cohort size, the number of observed deaths is small . These studies, though they rely on cancerspecific mortality ratios rather than cancer incide nce as in the Wood et al. (1998) study, have several advantages to the Wood et al. (1998) study. The low SMR for overall mortality reported by Wood et al. (1998) suggests the potential presen ce of a number of biases, including the healthy worker effect, incomplete cohort identifica tion, and incomplete ascertainment of the outcome measure. Furthermore, Blair et al. (1998) provide a better job exposure matrix than Wood et al. (1998). Although cancer incidence is t ypically preferred, mortality rates do serve as a good surrogate for incidence for some cancers lik e lung cancer. On the other hand, these mortality studies may miss associations with treata ble cancers such as prostate cancer. The small percentage of deaths in the NCI cohort su ggest a young mean age, which can impact statistical power. Thus, the observation of a statistically significant elevation in SMR among those with the longest latency and high cumul ative exposure is noteworthy. Additional follow-up of this cohort may be useful to further a ssess the association between AN exposure and cancer suggested by the excess in lung cancer d eaths that has been observed among workers exposed to high levels of AN.

Case-control studies A large case-control study conducted in seven Europ ean countries investigated the association between occupational exposure to vinyl chloride, AN, and styrene and the risk of lung cancer (Scélo et al., 2004). The study includ ed new cases of lung cancer occurring between
1998 and 2002 in 15 centers in six Central and East ern European countries and in Liverpool in the United Kingdom. Controls, consisting of subjec ts hospitalized in general public hospitals in

### DRAFT - DO NOT CITE OR QUOTE 92 the same areas as cases, were frequency matched to cases based on age and gender. Controls had to have been hospitalized within 3 months of diagno sis of the case and could not have cancer or any tobacco-related diseases. A total of 3,403 cas es and 3,670 controls met the study inclusion criteria; after exclusions and refusals to particip ate, the final study group included 2,861 cases and 3,118 controls. In order to ascertain exposure and lifestyle inform ation, such as tobacco consumption, each study participant was interviewed using a stan dard questionnaire. Exposure assessment was obtained from the work history portion of the quest ionnaire, where information was collected for each job held at ≥ 1 year. Experts evaluated the frequency and intens ity of exposure to AN, among other agents, for each job held by each study subject. The following exposure models were constructed for analysis: (1) duration of exp osure, (2) weighted duration of exposure (which considered both duration and frequency), and (3) cumulative exposure in ppm-years. Models included age, gender, center, tobacco consum ption, and other occupational factors. A total of 10,555 jobs were held by the 2,861 study participants with lung cancer, and a total of 11,174 jobs were held by the 3,118 control s. AN exposure was associated with 48 jobs held by the cases and 26 jobs held by the controls. Thirty-nine of the 2,861 cases and 20 of the 3,118 controls were characterized as being exposed to AN, resulting in a significant odds ratio (OR) of 2.20 (95% CI = 1.11–4.36) (i.e., cases were 2 times more likely to be exposed to AN than controls). However, it was found that more th an half of the study participants that were exposed to AN were also exposed to styrene. Furthe r analysis was conducted on individuals not exposed to styrene (17 cases and 10 controls). Thi s resulted in a similar OR estimate but with a wider CI due to the smaller sample size (OR = 2.08, 95% CI = 0.82–5.27). Increasing linear trends for lung cancer were noted for both weighted duration of exposure ( p = 0.05) and cumulative exposure (

p = 0.06) (Table 4-16). Additional analyses employe d a 20-year lag for exposures, which did not change the results appreci ably. The authors reported an increased risk of exposure among lung cancer cases diagnosed befor e the age of 60 (43% of the cases), where the OR for ever being exposed was 2.79 (95% CI = 1. 01–7.70), while the OR for ever being exposed among those over 60 years was 1.02 (95% CI = 0.35–2.92). An age-exposure interaction test yielded nonsignificant results.

### DRAFT - DO NOT CITE OR QUOTE 93 Table 4-16. ORs of lung cancer for AN exposure

Exposure measure Cases Controls OR 95% CI Weighted duration of exposure (yrs) Not exposed 2,822 3,098 1.00
0.01–1.00 13 9 2.03 0.72–5.73
1.01–2.25 9 5 2.73 0.73–10.20
>2.25 17 6 2.91 0.87–9.79 Linear trend: p = 0.05 Cumulative exposure (ppm-yrs) Not exposed 2,822 3,098 1.00
0.01–0.46 13 9 2.03 0.72–5.73
0.47–1.61 10 4 2.76 0.68–11.22
>1.61 16 7 2.87 0.85–9.66 Linear trend: p = 0.06

Source: Amended from Scélo et al. (2004).



### Because of the personal interviews conducted with e ach case and control, this study was able to provide an in-depth assessment of potential confounding factors, such as smoking history and lifestyle factors. The exposure assessment, th ough different than for the recent generation of cohort studies where actual plant measurements were possible, utilized reasonable and standardized methods to assign various levels of AN exposure to different jobs. As a multiindustry study, the possibility of exposure misclas sification in this study was probably greater than in single-industry studies, though exposure mi sclassification is probably nondifferential with respect to disease and therefore would serve t o lessen the outcome measures (ORs) calculated. The key observation in this study is t he fact that, even after adjustment for confounding factors such as smoking history, an ass ociation between AN exposure and lung
cancer incidence was observed. This observation ad ds to the weight of evidence in support of an
association between AN and cancer.

Cross-sectional studies A detailed cross-sectional study was conducted amon g workers at a Hungarian AN factory in June 2000 (Czeizel et al., 2004). Of th e 888 employees, 72 employees did not work during the study time frame and 33 refused to parti cipate. The remaining 783 employees were interviewed, with information gathered on demograph ics, lifestyle and habits, occupational exposures, and history of general and occupational diseases, among other factors. Medical
records aided in the validation of the workers’ res ponses. Workers were categorized into three groups based on level of contact with AN (i.e., direct exposure, indirect or sporadic exposure, and no exposure). Since the interviews were done w ith living current workers, cancer

### DRAFT - DO NOT CITE OR QUOTE 94 information for any worker who had left the plant o r died before the study was conducted was
anecdotal. It is known that 12 former workers from the factory had died from cancer between 1990 and 1999, and none of these deaths was due to lung cancer. Of the 783 workers interviewed, 12 workers were found in the interview sample that had cancer. Of these, only one lung-cancer case was identified. This worker, cate gorized as having direct exposure to AN, started working at the plant in 1973 and was diagno sed 15 years later. Five of the 12 cancer cases were among the group (n = 452) thought to hav e the highest level of exposure to AN, while 4 cancer cases were noted among workers with no exp osure to AN. No significant association between AN exposure and the development of cancer w as observed. The study mentioned three of its shortcomings: persons with serious disorder s who died or had premature pensions were not included, updated information on occupational e xposures was unavailable, and there was difficulty in identifying appropriate controls. It should be noted that workers were not exposed exclusively to AN but to a mixture of other chemica ls as well. The small number of cancer incidences and the identified shortcomings hinder t he reliability of this study in evaluating the association between AN exposure and the development of cancer.

Other supporting studies In 2006, the Ohio Department of Health assessed the burden of cancer among residents of Addyston, Hamilton County, Ohio, who lived near a t hermoplastics manufacturing plant that emitted AN and 1,3-butadiene into the environment ( Ohio Department of Health, 2006). The study population consisted of invasive cancer cases identified through the Ohio Cancer Incidence Surveillance System between 1996 and 2003. The inc idence of site-specific cancer was compared to the expected number of cases, the latte r being derived from national background cancer incidence rates from NCI’s Surveillance, Epi demiology and End Results (SEER) program in 1998–2002 and region-specific cancer incidence r ates from 1993 to 2003. A total of 55 invasive cancer cases were identified among the 1,010 residents in the area, with an SIR = 1.8 (95% C.I. = 1.3–2.3) based on the 1998–2002 SEER ag e-specific incidence rates. Cancer of the lung and bronchus was the most common cancer identi fied (13 cases, 23.6%), followed by colorectal cancer (10 cases, 18.2%). The number of observed cancer cases in both instances was higher than expected (lung and bronchus SIR = 3.2, 95% C.I. = 1.7–5.4; colon and rectum SIR = 3.0, 95% C.I. = 1.5–5.6). SIRs based on the region -specific cancer incidence yielded similar results. Although cancer incidence in this cohort was higher than expected, the association between AN exposure and the incidence of lung cance r may be confounded by other risk factors, such as smoking, that were acknowledged but not con trolled in the analyses.

### DRAFT - DO NOT CITE OR QUOTE 95 Overall summary of epidemiology data The early DuPont studies found potential increases in incidence and/or death from lung cancer and prostate cancer among persons possibly e xposed to AN. These studies were the impetus for generating several additional studies s panning more than 20 years after the first publication. Exposure assessment was not fully exp lored until recently, though older studies did examine qualitative distributions of exposure. The cohorts ranged from a few hundred workers to over 25,000 workers. The follow-up period for m any of the studies was short, not allowing half of the population to reach a terminal endpoint so that a health outcome such as cancer could be observed. However, over time, the cohort studie s increased in power by increasing the number of workers, length of follow-up, and sophist ication of the exposure assessment. A composite of the major cohort studies reviewed, a long with all-cancer SMRs, is provided in Table 4-17. Table 4-18 summarizes SMRs for lung cancer, a cancer type that has been assessed in most of the epidemiology studies r eviewed. In both tables, the SMRs are based on the cohort population most likely to be exposed to AN, as the actual cohort sample size in many cases included an unexposed worker group. As in most studies, the number of deaths on which the SMRs are based is a fraction ( ≤ 33%) of the actual cohort studied; thus, the actual cohort size may not reflect the relative number of deaths in the SMR calculation. These SMRs were evaluated by the size of the exposed cohort, n umber of observed deaths, percentage of observed deaths within each study, and year of publ ication to determine if any of these factors
was associated with increased SMR values. For both all-cancer mortality and lung-cancer mortality, no discernable association was observed between increased SMRs and the size of the exposed cohort, number of observed deaths, percenta ge of observed deaths within each study, or year of publication (data not shown).96 DRAFT - DO NOT CITE OR QUOTETable 4-17. Derived all-cancer SMRs for major cohort studies on AN exposureReference Study population Comparison groupPotentially exposedcohortObserveddeathsAll-cancerSMRaDuPontO’Berg (1980) Male workers exposed to AN between 1950 and 1966 at aDuPont Plant in South Carolina and followed through1976.DuPont Registry 1,128b17 1.13(0.68–1.78)O’Berg et al. (1985) As above but updated extendedto 1983 DuPont Registry 1,345 36 1.14(0.81–1.56)Chen et al. (1987) Male workers exposed to AN between 1944 and 1970 atDuPont Plant in Virginia and followed through 1983.White male subset ofU.S. population1,08318c0.75(0.44–1.16)Chen et al. (1987) As above.DuPont Registry 1,083 18c0.88(0.54–1.37)Wood et al. (1998) Combined O’Berg et al. (1985) and Chen et al. (1987) U.S. general population 2,559126 0.78d(0.64–0.93)Wood et al. (1998) As above.DuPont Registry 2,559 126 0.86(0.72–1.02)Symons et al. (2008) Update from Wood et al. (1998) with 11 yrs of follow-up Regional Dupont workers2,548 839 0.92(0.81–1.04)Symons et al. (2008) As above.U.S. general population 2,548 839 0.73d(0.64–0.82)NCIBlair et al. (1998) Workers employed in eight AN-producing facilities from1950s to 1983, followed through 1989.U.S. general population 25,460 326 0.80d(0.70 -0.90)Blair et al. (1998) As above.Unexposed workers 25,460 326 RR = 0.80(0.7–1.0)Marsh et al. (1999) Subset of Blair et al. (1998).County mortality rates 518 17 0.88(0.52–1.42)Marsh et al. (1999) As above.Unexposed workers 518 17 RR = 0.87(0.4–1.7)Marsh et al. (2001) Same as Blair et al. (1998) Regional mortality rates 25,460 –American Cyanamid CompanyCollins et al. (1989) Male workers at two plants employed between 1951 to 1973,followed through1983.White male subset ofU.S. population1,774 43 1.01(0.74–1.35)Synthetic chemical plantWaxweiler et al. (1981) Chemical plant workers employed between 1942 and 1973,followed through 1973.White male subset ofU.S. population4,806 101 1.18(0.97–1.43)97 DRAFT - DO NOT CITE OR QUOTETable 4-17. Derived all-cancer SMRs for major cohort studies on AN exposureReference Study population Comparison groupPotentially exposedcohortObserveddeathsAll-cancerSMRaTable 4-17. Derived all-cancer SMRs for major cohort studies on AN exposureReference Study population Comparison groupPotentiallyexposed cohortObserveddeathsAll-cancerSMRaRubber industryDelzell and Monson (1982)White male rubber chemical plant workers employed for atleast 2 yrs between 1940 and mid-1971, followed throughmid-1978.White male subset ofU.S. population327 22 1.20(0.77–1.79)Netherlands cohortSwaen et al. (1992) Male workers exposed to AN in eight factories for≥6 mosbefore mid-1979, followed through 1987.Dutch general population2,842 42 0.83(0.61–1.11)Swaen et al. (1998) As above, but followed through1995. Dutch general population2,842 97 0.88(0.72–1.07)Swaen et al. (2004) As above, but followed through2000. Dutch general population2,842 146 0.89(0.75–1.04)BASF (Germany)Thiess et al. (1980) Male workers from 12 plants followed through mid-1978. German mortality rates 1,469 27 1.32(0.89–1.89)Six factories (U.K.)Werner and Carter (1981) Male workers employed forat least 1 yr in one of sixfactories from 1950 to 1968, followed through 1978.Male mortality rates inEngland and Wales934 21 1.10(0.70–1.65)Benn and Osborne (1998) As above but employed from1969 to 1978, followed through1991.Mortality rates fromdifferent Europeancountries2,963 121 0.88(0.73–1.05)Acrylic fiber factory (Italy)Mastrangelo et al. (1993)General population 671 12 1.37(0.74–2.33)aSMRmay be calculatedfrom article based on available data.bOnly workers employed for≥6 mos.cBased only on wage workers.dStatistically significant (p< 0.05).98 DRAFT - DO NOT CITE OR QUOTETable 4-18. Derived lung cancer SMRs for major cohort studies on AN exposureReference Study population Comparison groupPotentially exposedcohortObserved lungcancer deathsLung cancerSMRaDuPontO’Berg (1980) Male workers exposed to AN between 1950 and1966 at a DuPont Plant in South Carolina andfollowed through 1976.DuPont Registry 1,128b7 1.35(0.59–2.66)O’Berg et al. (1985) As above, but updated and extended to 1983. DuPont Registry 1,345 14 1.21(0.69–1.98)Chen et al. (1987) Male workers exposed to AN between 1944 and1970 at DuPont Plant in Virginia and followedthrough 1983.White male subset ofU.S. population1,0835c0.59(0.22–1.32)Chen et al. (1987) As above.DuPont Registry 1,083 5c0.66(0.24–1.46)Wood et al. (1998) Combined O’Berg et al. (1985) and Chen et al.(1987).U.S. general population 2,559 47 0.74d(0.55–0.98)Wood et al. (1998) As above.DuPont Registry 2,559 47 0.89(0.66–1.17)Symons et al. (2008) Update from Wood et al. (1998) with 11 yrs offollow-upRegional Dupont workers2,548 88 0.92(0.75–1.14)Symons et al. (2008) As above.U.S. general population 2,548 88 0.74d(0.60–0.91)NCIBlair et al. (1998) Workers employed in eight AN-producing facilitiesfrom 1950s to1983, followed through 1989.U.S. general population 25,460 134 0.90(0.8–1.1)Blair et al. (1998) As above.Unexposed workers 25,460 134 RR = 1.2(0.9–1.6)Marsh et al. (1999) Subset of Blair et al. (1998).County mortality rates 518 9 1.32(0.64–2.42)Marsh et al. (1999) As above.Unexposed workers 518 9 RR = 1.98(0.96–3.63)Marsh et al. (2001) Same as Blair et al. (1998). Regional mortality rates 25,460 134 0.74d(0.62–0.87)American Cyanamid CompanyCollins et al. (1989) Male workers at two plants employed between1951 and 1973, followed through 1983.White male subset ofU.S. population1,774 15 1.00(0.58–1.61)99 DRAFT - DO NOT CITE OR QUOTETable 4-18. Derived lung cancer SMRs for major cohort studies on AN exposureReference Study population Comparison groupPotentially exposedcohortObserved lungcancer deathsLung cancerSMRaTable 4-18. Derived lung cancer SMRs for major cohort studies on AN exposureReferenceStudy populationComparison groupPotentiallyexposed cohortObserved lungcancer deathsLung cancerSMRaSynthetic chemical plantWaxweiler et al. (1981) Chemical plant workers employed between 1942 and1973, followed through 1973.White male subset ofU.S. population4,806 42 1.49d(1.09–1.99)Rubber industryDelzell and Monson(1982)White male rubber chemical plant workers employedfor at least 2 yrs between 1940 and mid-1971,followed through mid-1978.White male subset ofU.S. population327 9 1.52(0.74–2.79)Netherlands cohortSwaen et al. (1992) Male workers exposed to AN in eight factories for≥6 mos before mid-1979, followed through 1987.Dutch general population2,842 16 0.82(0.48–1.30)Swaen et al. (1998) As above, but followed through1995. Dutch general population2,842 47 1.10(0.82–1.45)Swaen et al. (2004) As above, but followed through2000. Dutch general population2,842 67 1.07(0.84–1.35)BASF (Germany)Thiess et al. (1980) Male workers from 12 plants followed through mid1978.German mortality rates 1,469 11 1.85(0.97–3.22)Six factories (U.K.)Werner and Carter (1981) Male workers employed for≥1 yr in one of sixfactories from 1950 to 1968, followed through 1978.Male mortality rates inEngland and Wales934 9 1.20(0.58–2.20)Benn and Osborne (1998) As above but employed from1969 to 1978, followedthrough 1991.Mortality rates fromdifferent Europeancountries2,963 53 1.03(0.78–1.34)Acrylic fiber factory (Italy)Mastrangelo et al. (1993)General population 671 2 0.77(0.13–2.54)aSMRmay be calculatedfrom article based on available data.bOnly workers employed for≥6 mos.100 DRAFT - DO NOT CITE OR QUOTETable 4-18. Derived lung cancer SMRs for major cohort studies on AN exposureReference Study population Comparison groupPotentially exposedcohortObserved lungcancer deathsLung cancerSMRacBased only on wage workers.dStatistically significant (p< 0.05).

### DRAFT - DO NOT CITE OR QUOTE 101 To date, the largest cohort assessed in determining the relationship between AN and
cancer is the NCI cohort. The NCI/National Institu te for Occupational Safety and Health (NIOSH) cohort study of Blair et al. (1998) provide s the strongest evidence for carcinogenicity, although this evidence is not conclusive. This stu dy of 25,460 subjects in eight plants was designed to evaluate a relationship between AN expo sure and site-specific cancer, including lung cancer, an a priori hypothesis. Both AN-exposed an d unexposed subjects showed a favorable all-cause mortality rate compared to the all-cause mortality rate of the U.S. population. Although only 5% of the cohort had died, this study has a large number of observed deaths that could be analyzed. The study addressed known probl ems occurring with earlier studies by quantifying exposures, estimating the effect of smo king, and using an internal control group of unexposed workers. The study by Blair et al. (1998) is of particular i nterest because a possible association between AN exposure and death from lung cancer was observed among workers in the highest level of AN exposure. Specifically, workers with a t least 20 years since first exposure and exposed to a high level of AN were 2 times more lik ely to die of lung cancer than unexposed workers. However, though significance was found am ong workers exposed to high levels of AN, as with other studies, the exposure-response an alysis in the Blair et al. (1998) study did not provide strong or consistent evidence for a causal association. The observations of Swaen et al. (2004) of AN-expos ed workers in the Netherlands and of Benn and Osborne (1998) of AN-exposed workers in the United Kingdom support the findings of Blair et al. (1998) and provide some ev idence for carcinogenicity, although lung cancer SMRs in these studies were not statistically significant. Other supporting evidence comes from the observation that SMRs for lung cancer amon g subjects with the highest exposure (as compared to national mortality rates) were not only >1, but also larger than the SMRs for low- or no-exposed groups. Furthermore, the statistically significant increased OR for AN exposure in the lung-cancer case control study of Scélo et al. (2004) provides weight for this association. This study adjusted for effects related to individu al smoking history and to a number of potential coexposures found in a subject’s occupational setti ng. The finding of lung-cancer risk increasing with increasing exposure duration or with increasin g cumulative exposure provides further
evidence of an association with AN. Within the body of epidemiologic literature examini ng a potential relationship between exposure to AN and cancer in occupational cohorts, the following shortcomings are noted: low power from small numbers of exposed subjects, lack of quantitative exposure information on individual study subjects leading to a greater pote ntial for exposure misclassification bias, assessment of an insensitive outcome, and insuffici ent follow-up period for cancer latency. In addition, many of the studies used external compari son groups, and their results were subject to a downward bias from the healthy worker effect.

### DRAFT - DO NOT CITE OR QUOTE 102 An alleged shortcoming of the Blair et al. (1998) study has been the observation that the AN-exposed workers experienced a lower rate of lung -cancer deaths than in the general population; however, this is likely a manifestation of the healthy worker effect. The use of internal controls by Blair et al. (1998) was to dra w inferences about AN risks. With cancer mortality being used as a surrogate for developing cancer associated with AN exposure and with a low percentage of the cohort having died, there m ay be an underestimate of the risk associated with AN exposure. In addition, Selikoff and Seidma n (1992) showed based on histopathological analysis of a comparably large industrial cohort (1 7,800 asbestos workers) that as much as 13.7% of lung cancer cases are misdiagnosed on death cert ificates, both as neoplasms and nonmalignant diseases, with about 3% as asbestos only diseases ( mesothelioma and asbestosis). Therefore, Blair cohort may have as much as 10% of internal co ntrols that are actually lung cancers. That would cause a strong bias against finding a statist ically significant relationship. Finally, mortality data may be inadequate for assessing trea table cancers that could result from AN exposure. The earlier studies based on the DuPont cohort utilized cancer incidence as well as cancer mortality data. In these studies, although a better outcome measurement (i.e., cancer incidence) is used, observed rates are compared thr ough an SIR with company-wide or national population statistics rates, rather than rates from an internal control group. Thus, a strong healthy worker effect may hinder the observation of a cancer effect of AN exposure. Even in the most recent DuPont cohort study (Symons et al. 2008 ) where an attempt was made to reduce the bias due to healthy worker effect, there may be bia s from the health worker effect. It should be noted that unlike the other DuPont cohort studies, Symons et al. (2008), with over 50 years of follow-up, did not report cancer incidence. Though the outcome measure of mortality in the Blair et al. (1998) study is not as sensitive, this study has a relatively large number of lungcancer deaths and does compare cause-specific death s between exposed and unexposed workers as well as the general population. The resulting r isk ratio may not achieve statistical significance (as mentioned above, several factors may have cause d bias to the null), but the point estimate does indicate a potential excess in lung-cancer dea ths among workers exposed to AN. Furthermore, the observed RR in the group of worker s with the highest cumulative exposure and the longest time since first exposure was statistic ally significantly increased.

4.1.2.2.2. Epidemiological studies of AN in humans (noncancer effects). Sakurai et al. (1978) performed a cross-sectional health examination of 1 02 male workers exposed to AN in six acrylic fiber manufacturing factories in Japan in 1 976. Also examined were 62 nonexposed matched control workers from polyester fiber manufa cturing plants, power supply plants, or finishing branches of the acrylic fiber plants. Th e workers were selected by a random sampling process. By experimental design, all exposed subje cts were shift workers who had been exposed to AN in the workplace for at least 5 years but had no history of exposure to other chemicals. All subjects underwent medical examinations, and bl ood and urine samples were collected for

### DRAFT - DO NOT CITE OR QUOTE 103 chemical analysis. Clinical chemistry analyses inc luded urinary protein and other parameters, including Hb, total cholesterol, AST, ALT, alkaline phosphatase, cholinesterase, γ -glutamyl transpeptidase ( γ -GTP), and lactate dehydrogenase (LDH). Parameters that measured liver injury were a focus of the clinical examinations be cause a previous epidemiological study of 576 Japanese acrylic fiber manufacturing workers ex posed to <5 or <20 ppm AN between 1960 and 1970 had reported an increase in subjective sym ptoms and mild injury to the liver in exposed workers (Sakurai and Kusumoto, 1972). AN and thioc yanate concentrations in urine were also measured to evaluate individual exposure levels. Levels of AN in the air (Sakurai et al., 1978) wer e measured as 8-hour TWA from “spot” samples (from stationary air samplers) and from exp osed subjects wearing personal samplers. As shown in Table 4-19, the factories and exposed w orkers were classified into three groups (A, B, and C), according to their level of AN exposure. SDs for the means and ranges of the exposure concentrations were not reported. Mean ex posure durations for workers in the three groups of factories were 10.3 years (SD = 4.5) for group A, 10.8 years (SD = 4.4) for group B, and 12.6 years (SD = 2.1) for group C.

Table 4-19. Industrial AN exposure, levels of AN a nd thiocyanate in urine, and prevalence of physical signs of adverse effects in workers exposed to AN at six acrylic fiber factories in Japan

Mean 8-hr TWA AN concentration (ppm) Percentage of exposed vs. control workers with physical signs of adverse effects Factory
group (n = number of factories) Spot

samples Personal

samples AN in urine

(μg/L) Thiocyanate

in urine (μg/L) Reddening of

pharynx or conjunctiva Palpable

liver Rashes or

pigmentation of skin A (n = 2) 2.1

(n = 116) 0.1

(n = 11) 3.9

(n = 35) 4.50

(n = 19) 19.4 (n = 31)

vs. 18.2 (n = 22) 16.1 (n = 31)

vs. 9.1 (n = 22) 9.7 (n = 31)

vs. 9.1 (n = 22) B (n = 3) 7.4

(n = 394) 0.5

(n = 37) 19.7

(n = 51) 5.78

(n = 58) 11.3 (n = 53)

vs. 10.0 (n = 30) 15.1 (n = 53)

vs. 10.0 (n = 30) 3.8 (n = 53)

vs. 0 (n = 30) C (n = 1) 14.1

(n = 98) 4.2

(n = 14) 359.6

(n = 22) 11.41

(n = 14) 50.0 (n = 18)

vs. 30.0 (n = 10) 38.9 (n = 18)

vs. 30.0 (n = 10) 11.0 (n = 18)

vs. 0 (n = 10)
Control – – 0 (n = 22) 4.00

(n = 52) – – –

Source: Sakurai et al. (1978).



### Although there were some differences in mean age b etween the groups (38.1 years for group C, 33.9 years for group B, and 30.5 years for group A), the age distributions of exposed and control subjects were broadly similar (Sakurai et al., 1978). No statistically significant differences in mean clinical chemistry parameters w ere found between exposed workers and controls. Medical histories of exposed workers and controls suggested a transient AN-related

### DRAFT - DO NOT CITE OR QUOTE 104 increase in such symptoms as irritation of the conj unctiva and upper respiratory tract, runny nose, and skin irritation (for example, at the scro tum). Physical examination of subjects suggested a slight increase in the incidence of pal pable liver, reddening of the conjunctiva and pharynx, and occurrence of skin rashes (see Table 4 -19). However, the incidences of these findings among the groups did not rise to the level of statistical significance. Likewise, there were no AN-related changes in blood pressure or neu rological findings. EPA determined 4.2 ppm (average 8-hour TWA from th e high exposure group) as an equivocal lowest-observed-adverse-effect level (LOA EL) for physical signs of eye or throat irritation, liver enlargement, or skin irritation i n male workers with average durations of 10– 12 years of occupational exposure to airborne AN. Limitations to this LOAEL are that workplace air concentrations across the 10–12 years of exposure were not available, workers
who underwent medical examinations were not necessa rily the same as those whose air and urine were sampled, and no survey of self-reported sympto ms was conducted. A later study of Japanese acrylic fiber workers by some of the same investigators (Muto et al., 1992) included a survey of self-reported sy mptoms. A strength of the LOAEL is the concurrence between the urinary biomarkers of expos ure and the measured air concentrations (see Table 4-19). Muto et al. (1992) performed another cross-section al health examination of male workers in seven Japanese acrylic fiber manufacturing plant s in 1988. The seven factories included the
six factories studied in the 1976 cross-sectional h ealth examination of Japanese acrylic fiber workers (Sakurai et al., 1978). Exposed workers se lected for the study were 157 male shift workers with at least 5 years of experience on prod uction lines. The mean years of exposure for these workers was 17 ± 6.6 years. A nonexposed con trol group consisted of 537 male shift workers in polyester fiber plants, power supply pla nts, or finishing branches in the acrylic fiber plants. Controls were similar to exposed workers i n average age (42.2 years, controls; 41.9 years, exposed), percentage who drank alcohol (76.5%, controls; 77.1%, exposed), and percentage who smoked (58.1%, controls; 58.6%, expo sed). Subjects underwent a medical examination that documented past illnesses, work hi story, exposure to AN, smoking and drinking habits, subjective symptoms, physical cond ition, urinalysis, hematology, liver function blood variables (total bilirubin, AST, ALT, and γ -GTP), and chest X-rays. Prevalences of
workers with abnormal values for the medical examin ation parameters were analyzed statistically (protein, sugar, or urobilinogen in u rine; blood specific gravity >1.055, Hb <14 g/dL, hematocrit >40%, and RBC count <10 3 

### /mm 3 

### ; and bilirubin >1.0 mg/dL, AST >40 enzyme activity units, ALT >35 units, and γ -GTP >80 units). Exposure of workers (reported as 8-hour TWA concentrations) was assessed by data from workp lace area air samples and from personal air samples collected over a 2-day period for 142 o f the 157 exposed workers. Overall, the mean AN exposure concentrations for the exposed workers were 0.53 ± 0.52 ppm (range, 0.01– 2.80 ppm) based on stationary air samples and 0.62 ± 0.90 ppm (range, 0.01–5.70 ppm) based on

### DRAFT - DO NOT CITE OR QUOTE 105 personal air samples. The mean AN exposure measure ments were lower than the exposure measurements made in 1976 (see Table 4-19), suggest ing that workplace air concentrations in the plants had declined over the 12-year period bet ween the studies. Prevalences of subjective symptoms that were stati stical significantly different between the exposed and control groups included “heaviness in stomach” and decreased libido, with the symptom described as heaviness in stomach as most s ignificant (Muto et al., 1992). Reported prevalences for heaviness of stomach were 29.3% in the exposed group vs. 18.7% in the control group. No significant differences were found in pr evalences for other GI effects such as anorexia, nausea, vomiting, heartburn, or stomachac he. When workers were grouped into those from factories with mean TWA AN concentrations below 0.3 ppm (four factories; mean stationary and personal air concentrations of 0.27 and 0.19 ppm, respectively; Group A) or above 0.3 ppm (three factories; mean stationary and personal air concentrations of 0.84 and 1.13 pp m, respectively; Group B), statistically significant increased prevalences for the following symptoms (compared with controls) were found for the workers in the factories with higher exposure levels (Group B): decreased libido (54.9 vs. 40.2% for controls), poor memory (76.1 vs . 64.0% for controls), irritability (35.2 vs. 24.1% for controls), reddening of conjunctiva (21.1 vs. 11.7% for controls), and eye pain or lacrimation (32.4 vs. 19.2% for controls). There w ere no statistically significant differences between the exposed and control groups in the preva lences of clinically observed physical signs (skin rashes or reddening of conjunctiva) or abnorm al findings in urinalytic, hematological, liver function, or blood pressure variables. Prevalences of chest X-ray abnormalities were likewise not different between exposed and control groups. The mean 8-hour TWA personal air concentration of workers in the Group B factories, 1.13 ppm, was judged by EPA to be a LOAEL for small but statistically significant increased prevalences of several subjectively reported sympto ms (e.g., poor memory and irritability) in the absence of statistically significant increases in t he prevalences of physical signs or abnormal values for a number of urinalytic, hematological, l iver function, or blood pressure variables (Muto et al., 1992). The average 8-hour TWA person al air concentration in the Group A factories, 0.19 ppm, was judged to be a no-observed -adverse-effect level (NOAEL). Like the
NOAEL identified in the earlier cross-sectional hea lth examination of Japanese acrylic fiber workers (Sakurai et al., 1978), a limitation to the Muto et al. (1992) NOAEL is that the exposure
assessments were cross-sectional in nature. Histor ical measurements of air concentrations were
not available. Kaneko and Omae (1992) performed a cross-sectional health questionnaire study of exposed and nonexposed workers from seven acrylic f iber manufacturing plants in Japan. The questionnaire for surveying subjective symptoms was administered to 1,220 exposed male workers and 757 nonexposed male workers who were ei ther from the same factory or a close-by factory of the same company. The selected study po pulation included 504 exposed individuals

### DRAFT - DO NOT CITE OR QUOTE 106 and 249 unexposed controls. Subjects who were excl uded from the study were workers with administrative or nonshift jobs, a history of expos ure to other chemicals, ages not able to be matched, or incomplete information on the questionn aire. Workplace air concentrations of AN were measured on 2 consecutive days in each factory by using a portable gas chromatograph. Factories were grouped into three exposure groups w ith the following mean workplace air concentrations: Group L = 1.8 ppm, Group M = 7.4 p pm, and Group H = 14.1 ppm. Further information on the exposure measurements was not re ported (e.g., SD of means, ranges of values, or whether or not the reported concentratio ns represented 8-hour TWA concentrations). Mean durations of exposure in the three groups were 5.6, 7.0, and 8.6 years for the L, M, and H groups, respectively. All subjects filled in a d etailed questionnaire (232 questions in all) that was intended to detect neurological condition and s ubjective symptoms. The neurological statuses, as assessed with two dif ferent analytical methods (Fukamachi’s criteria and Cornell Medical Index pro files), of the AN-exposed workers were slightly higher than those of control workers, alth ough the differences were not statistically significant. Subjective symptoms with significantl y higher prevalences in the L, M, and H groups, compared with the nonexposed groups, incl uded headaches, tongue trouble, choking, lump in throat, fatigue, general malaise, heavy arm s, and heavy sweating. The numbers of subjective symptoms that were significantly more pr evalent in exposed workers were as follows: 8 in group L, 19 in group M, and 14 in group H. On ly the prevalence of one subjective symptom, “often feel a choking lump in the throat,” had a tendency to increase with increasing length of exposure to AN in all factories and in gr oup L. EPA identified 1.8 ppm as an equivocal LOAEL (Group L mean air concentration) for statisti cally significantly increased prevalences of subjective symptoms. In a translated study from China, Chen et al. (200 0) examined the health effects of occupational exposure to AN in 224 workers at an ac rylic fiber plant. The exposed group consisted of 180 males and 44 females, with an aver age age of 38.6 years (range 19–57 years) and an average of 13 years of service. The average AN concentration in the work areas at the plant was reported to be 1.04 mg/m 3 

### (0.48 ppm). All subjects were given a physical examination. The results of these investigations a nd of subjects’ hematological and clinical chemistry parameters were compared with those of un exposed controls. Reported symptoms that had significantly higher incidence in exposed subje cts than in unexposed controls included headache and dizziness (41 vs. 21%), poor memory (3 0 vs. 13%), feelings of choking in the chest (13 vs. 8%), and loss of appetite (13 vs. 7%) . However, of the other parameters evaluated in this study, all hematological data and all but o ne of the clinical chemistry parameters gave closely similar values to those of controls. The e xception was the serum activity of γ -GTP that was significantly higher ( p < 0.05) in exposed subjects than in controls (44.32 ± 32.21 vs. 40.22 ± 31.06 IU/L). The study authors identified 0.48 ppm as a LOAEL for statistically significantly increased prevalences of subjective s ymptoms (including headache, dizziness, poor

### DRAFT - DO NOT CITE OR QUOTE 107 memory, and loss of appetite) in workers employed i n an acrylic fiber manufacturing plant for an average of 13 years, without significant changes in most hematological and clinical chemistry variables except for γ -GTP activity. Lu et al. (2005a) employed the World Health Organi zation (WHO)-recommended Neurobehavioral Core Test Battery (NCTB), which inc ludes seven components, to evaluate neurobehavioral effects of workers exposed to AN in a Chinese plant. The subjects included 81 workers (68 males and 13 females) in the AN-mono mer department, 94 workers (67 males and 27 females) in the acrylic fibers department, a nd 174 workers (130 males and 44 females) in the administrative or embroidery departments with n o AN exposure. The monomer and fiber workers represented 96% of the eligible exposed wor kers in the two departments. Periodic short-term area sampling between 1997 and 1999 indi cated that the geometric means of AN exposure were 0.11 ppm (range 0.00–1.70 ppm for 390 samples) in the monomer department and 0.91 ppm (range 0.00–8.34 ppm for 570 samples) in t he fiber department; no personal sampling data were collected. As categorized by duration of employment, 23% of monomer workers were exposed for 1–10 years, 42% for 11–20 years, and 35 % for more than 20 years; and 47% of fiber workers were exposed for 1–10 years, 23% for 11–20 years, and 30% for more than 20 years. Mean durations of employment were not reported for the exposed groups. Monomer workers were also potentially exposed to cyanide and fiber workers to methyl methacrylate and heat, but levels of exposure to these possible confounders we re not monitored. The exposed workers were frequency matched on age (within 5 years) and years of education (within 1 year) with the unexposed workers. Exposed workers (mean age 40.8 years; range 25–53) were slightly older than unexposed workers (mean age 36.4 years; range 21–53); the percentage of females and years of education were roughly similar across grou ps. All subjects were interviewed for demographic data, general health status, and lifest yle. All tests were conducted by three specially trained physicians using a Chinese operat ional guide of the NCTB. Results of the analysis revealed that exposure to AN had adverse effects for some components of the NCTB, indicating neuropsychologic al impairment; scores from the following tests were statistically significantly different ( p < 0.05) from controls in analyses of covariance that took into account age, sex, and education leve l. In the Profile of Mood States test, all scores for negative moods (anger, confusion, depression, f atigue, and tension) were significantly higher in the exposed groups than in the unexposed group a nd higher for monomer workers (41–68% higher than controls) than for fiber workers (20–44 % higher than controls). Simple Reaction Time, a test of attention and visual response speed , was longer in the two exposed groups than in the unexposed group: 16% longer for monomer worker s and 10% longer for fiber workers. Exposed workers performed more poorly (by 21% for m onomer workers and 24% for fiber workers) in the backward sequence of the Digit Span test, a measure of auditory memory, but fiber workers had better performance in the forward sequence than unexposed workers. Both groups of exposed workers also had a 4% poorer perf ormance in the Benton Visual Retention

### DRAFT - DO NOT CITE OR QUOTE 108 test, a measure of visual perception and memory; sc ores in the Pursuit Aiming II test, which assesses fine motor skills and perceptual speed, we re 14% lower for monomer workers and 10% lower for fiber workers compared with controls. Ex posure to AN had no significant effect on scores for manual dexterity in the Santa Ana test o r for perceptual speed in the Digital Symbol test. In examining effects by duration of AN expos ure, there was no statistical relationship for mood scores and duration of exposure. However, the re was an insignificant decrease in Simple Reaction performance with duration of exposure for both monomer and fiber workers. Inverse relationships were found between performance and du ration in both the Digital Symbol test and total scores of the Digit Span test in the two expo sed groups. Decreased performance with duration of exposure was also found in the Pursuit Aiming II test for exposed monomer workers. Lu et al. (2005a) mentioned several limitations of this study. One was that the cited exposure data represented estimates of previous exp osure levels and no contemporaneous personal monitoring data were available. Furthermo re, as the NCTB was developed for populations in Europe and North America, it is not known to what extent cultural differences may have affected results of the Profile of Mood St ates test, shown to be sensitive to cultural differences. In addition, the study authors could not rule out the possibility that examiner drift may have affected the results. Selection bias amon g volunteers in different groups was mentioned as a possible confounding effect, but was discounted on the basis that the participation among exposed workers was so high. M oreover, largest measures of neurobehavioral effect occurred on the acrylic fibe r workers, who had lower average exposure
level. EPA determined the results from this study were co nsistent with the designation of the average exposure levels for the monomer workers, 0. 11 ppm, and the fiber workers, 0.91 ppm, as
LOAELs for small deficits in neurobehavioral tests of mood, attention and response speed, auditory memory, and motor steadiness but not in te sts of manual dexterity or perceptual motor speed. The toxicity of AN in an occupational setting has been the subject of a number of other reports from China, which were collectively submitt ed to the U.S. EPA as a Toxic Substances Control Act Test Submissions report (Acrylonitrile Group, 2000). While these studies are discussed below for hazard identification purposes, some reports lack sufficient detail to support reported findings of AN-related toxicity. For exam ple, Wang et al. (2000) reported on the disease incidence of 1,121 AN-exposed workers compa red with 489 unexposed controls in a university in the same area. Subjects in the expos ed group were stated to have a higher incidence of disease of the digestive system (16.95 vs. 8.28% ) and the liver (8.12 vs. 1.84%) than in the control group. The highest prevalence rate of 12.5 % for liver disease was found in workers exposed to AN over 20 years. The prevalence rate o f chronic disease also increased with duration of exposure. However, the report containe d no diagnostic information on these
conditions and no information on the levels of AN t o which the subjects had been exposed.

### DRAFT - DO NOT CITE OR QUOTE 109 Dong and Pan (1995) surveyed reproductive outcomes in 150 male and 105 female workers at a chemical fiber plant in China. The co ncentration of AN in the air in work areas of the plant ranged from 0.53 to 15.5 mg/m 3 

### (0.24–7.1 ppm; midpoint = 3.7 ppm). Controls in t he study were 110 male and 121 female workers who had not been exposed to AN. The report compared the reproductive outcomes for the wives of male workers to the wives of male controls (Table 4-20) and for all female workers at the plan t vs. female controls (Table 4-21). As shown in Table 4-20, the rates of premature delivery, spo ntaneous abortion, threatened abortion, stillborn fetuses, and sterility in the wives of ma le exposed workers all were higher than those in wives of male controls, with some differences achie ving statistical significance.

Table 4-20. Comparison of reproductive outcomes in wives of exposed and control males at a chemical fiber plant

Parameter Exposed group a (n = 150) Controls a (n = 110) Average age 20.97 ± 6.85 b 30.04 ± 3.37 Average working yrs 3.19 ± 5.35 8.53 ± 3.89 Pregnancies 168 113 Sterility (%) 9 (5.00) c 2 (1.82)
Life births 159 b 113
Normal births 141 104 Premature deliveries (%) 18 (10.71 d ) c 4 (3.54) Late deliveries (%) 6 (3.57) 4 (3.54) Spontaneous abortion (%) 8 (4.76) c 1 (0.88) Threatened abortion (%) 5 (2.98) c 1 (0.88) Stillborn fetuses (%) 4 (2.38) 0 (0) Low birth weight 5 (3.14) 4 (3.84)

a Numbers in parentheses are in %.
b Given as 7.74 in the report.

c Significantly different from controls ( p < 0.05 by Fisher’s exact test), as calculated by U .S. EPA.
d Significantly different from controls ( p < 0.001 by Student’s t-test), as calculated by U.S . EPA.

Source: Dong and Pan (1995).



### Table 4-21. Comparison of reproductive outcomes be tween exposed and control females at a chemical fiber plant

Outcome Exposed group a (n = 105) Control group a (n = 151) Average age 29.36 ± 5.12 b 20.68 ± 4.05 Average number of working yrs 10.19 ± 8.22 10.12 ± 4.34 Number of pregnancies 112 124
Number of alive newborns 105 125
Normal births 101 113 Immature deliveries (%) 8 (7.14) 5 (4.03) Late deliveries (%) 8 (7.14) 6 (4.84)

### DRAFT - DO NOT CITE OR QUOTE 110 Table 4-21. Comparison of reproductive outcomes be tween exposed and control females at a chemical fiber plant

Outcome Exposed group a (n = 105) Control group a (n = 151) Spontaneous abortions (%) 1 (0.89) 0 (0) Threatened abortions (%) 3 (2.68) 5 (4.03) Stillborn fetuses (%) 5 (4.46) c 0 (0) Mortality of newborns (%) 3 (2.86) 0 (0) Sterility (%) 3 (2.86) 1 (0.83)

a Numbers in parentheses are in %.
b Significantly different from controls ( p < 0.001 by Student’s t-test).

c Significantly different from controls ( p < 0.05), as calculated by the study authors.

Source: Dong and Pan (1995).



### Effects on the reproductive outcome in exposed fem ale workers at the plant were not as striking as in males, when compared with controls ( Table 4-21) (Dong and Pan, 1995). However, the rate of stillborn fetuses in the expos ed group was far higher than that of the control group (5/112 vs. 0/124, p < 0.05). It is unclear how much these differences may be related to the fact that in the first comparison (Table 4-20), the exposed males were significantly younger than the controls (

p < 0.001 by Student’s t-test, as calculated by the r eviewers), whereas in the second case (Table 4-21), the exposed childbearing females were significantly older than the controls ( p < 0.001). The results from this study identify the midpoint of the range of average workplace air concentrations of AN, 3.7 ppm, as a LOAEL for i ncreased prevalences of adverse reproductive outcomes in male and female workers em ployed for averages of about 3 and 10 years, respectively. The adverse outcomes showi ng statistically significantly increased prevalences compared with controls were premature d eliveries (18/150 vs. 4/110 in controls), threatened abortion (5/150 vs. 1/110 in controls), and sterility (9/150 vs. 2/110 in controls) for the male exposed workers and their wives and increa sed prevalence of stillborn fetuses in female exposed workers (4/105 vs. 0/151 in controls). In a follow-up to the study by Dong and Pan (1995) , Dong et al. (2000b) expanded the cohort to include the years 1994 and 1995, resultin g in 548 exposed male workers (496 controls) and 391 exposed female workers (427 controls). Ave rage employment durations for the exposed males and females were 11.0 ± 4.5 and 10.4 ± 3.8 ye ars, respectively. The average ages of the male and female workers were 33.8 and 32.4 years, r espectively. The age, length of service, and lifestyle of the controls were similar to the expos ed workers. The reported range of AN concentrations in the work place air, 0.11–15.5 mg/m 3 

### (0.05– 7.14 ppm, midpoint = 3.6 ppm), was not markedly dif ferent from that reported in the initial study. In the follow-up study, however, Dong et al . (2000b) also evaluated birth defects. The general trend of results was a slightly higher perc entage of abnormal findings in the exposed cohort, as compared with the initial study, and an incidence of 15.7% birth defects, as compared

### DRAFT - DO NOT CITE OR QUOTE 111 with 6.1% in controls. This difference was not sta tistically significant. There were, however, some statistically significant findings in the repr oductive outcome of exposed females. In the initial study, Dong and Pan (1995) had reported a s ignificant increase in stillbirths (4.5% in exposed vs. 0% in controls). In the expanded cohor t, this value was lower, 2.7 vs. 0.68%, but still statistically significant at the p < 0.05 level. There was also a significantly ( p < 0.05) increased incidence of birth defects (21.3 vs. 4.8% ), decreased incidence of low birth weights (3.5 vs. 4.8%), and highly significant ( p < 0.01) increase in premature deliveries (8.2 vs. 3 .9%). The results from the follow-up study identify the m idpoint of the range of workplace air concentrations, 3.6 ppm, as a LOAEL for statistical ly significantly increased prevalences of adverse reproductive outcomes (increased stillbirth s, birth defects, and premature deliveries) in female exposed workers employed for an average of 1 1 years. Dong et al. (2000a) also carried out an industrial hygiene survey of 68 male and 25 female workers at a Chinese chemical plant, as c ompared with 58 male and 38 female workers who had not been exposed to AN. The averag e age of exposed subjects was 27.9 years, and their years of employment at the plant ranged f rom 1 to 15 years. The average age of controls was 32.3 years. All subjects in the study answered lifestyle questions, including medical and occupational history, smoking and drink ing history, and subjective symptoms. They also were given a physical examination, including c linical examinations, chest X-rays, liver and gallbladder ultrasound, electrocardiogram (ECG), cl inical chemistry, and blood and urine tests. Air samples were collected from two workplace areas over a 3-year period and analyzed for AN, HCN, and acetonitrile concentrations. Annual avera ge AN concentration was not provided in the report, but measured AN concentrations were over 2 mg/m 3 

### at all times, with the highest concentration reaching 22.79 mg/m 3



### . Exposed workers reported the occurrence of headach e, dizziness, sleeping disorders, and a feeling of choking in the chest at a significantl y higher prevalence than nonexposed workers. Without presenting details, Dong et al. (2000a) ref erred to ultrasound tests of six individuals in the exposed group, which appeared to show diffuse c hanges in the liver. In this group, there was also a higher incidence of trembling of eyes, face, and fingers than in controls. However, all of the blood pressure, hematological, and clinical che mistry parameters under evaluation (including liver function tests) for exposed subjects were wit hin the normal range and closely similar to those of controls. Although the results indicated that increased prevalences of symptoms were reported by exposed workers compared with nonexpose d workers, the reported exposure information was inadequate to designate a LOAEL for this study. Li (2000) surveyed reproductive outcomes in 379 fe male workers in a Chinese AN manufacturing company and in 511 unexposed control workers from a bed sheet factory and a biological research institute in 1991. The average age and duration of employment of the (20.8 vs. 7.14%), premature deliveries (11.62 vs. 4.72%), and congenital defects (25.4 vs. 4.2 exposed workers were 33.95 years (22.75–54.83 years) and 14 .10 years (3.25–34.45 years), respectively.

### DRAFT - DO NOT CITE OR QUOTE 112 Average age and employment duration of the control workers were reported to be similar to the exposed group. Monthly workplace air concentration data for 1989 and 1990 were provided by the factory. The average AN air concentration was reported as 16.35 mg/m 3 

### (7.5 ppm, range = 0–152.88 mg/m 3 

### [0–70 ppm]). Statistically significant increased prevalences of the following reproductive outcomes were found, compared with con trols: sterility (2.64 vs. 0.78%), pregnancy complications %). Li (2000) also divided the exposed group into female workers with and without exposed male partners. Prevalence rate s for several adverse reproductive outcomes (pregnancy complications, premature delivery, late delivery, stillbirths, and congenital deficits) were statistically significantly elevated in female s with exposed partners, compared with those with nonexposed partners. This study identifies th e average workplace AN air concentration, 7.5 ppm, as a LOAEL for increased prevalences of advers e reproductive outcomes in female AN manufacturing workers employed for an average of 14 years. Xiao (2000a) reported on the fasting serum activit ies of serum glutamate pyruvate transaminase (SGPT, also known as ALT) in 372 worke rs exposed to AN for 1–31 years in a chemical factory in China and compared the levels w ith those in 186 unexposed workers.
Individuals with SGPT level ≥ 19 μ mol/L-minute were considered positive. The percent age of individuals with SGPT activity exceeding the benchm ark level was compared between the groups. Significantly higher percentage of positiv e individuals were found in the exposed group compared with controls (41.13 vs. 4.8%), with expos ed males being more severely affected than exposed females (50.23 vs. 27.82%). No data were p rovided on the level of AN exposure. Xiao (2000b) also reported on the levels of whole blood cholinesterase in 237 workers exposed to AN in a chemical factory in comparison w ith those in 184 unexposed workers. AN measurements were provided for three separate works hops, although it is not evident from the report whether the measurements were taken as spot samples or from personal samplers. A
colorimetric method was used to measure cholinester ase activity. The average AN concentrations in air for the three workshops were 7, 3.3, and 3 ppm, respectively. The authors reported that the levels of whole blood cholinester ase in AN-exposed workers from the three workshops were more than 50% lower than in controls . Health examination results showed there was also an apparent increase in the incidence of s ymptoms related to lowered cholinesterase activity in exposed subjects compared with controls . These symptoms included neurological disorder, excessive sweating, trembling, and discom fort in the chest. In an article published in a Chinese journal, Ding et al. (2003) evaluated mitochondrial DNA damage in a group of 47 Chinese workers randoml y selected from 1,020 active workers in the chemistry department of a petrochemical company . These workers were exposed to AN at a geometric mean concentration of 0.25 mg/m 3 

### (0.11 ppm) (median 0.36 mg/m 3 

### [0.17 ppm], range 0–3.70 mg/m 3 

### ) for an average of 17.3 ± 3.8 years. An unexposed control group of 47 persons
was selected from the teachers and staff of a colle ge, with an average length of employment of 18.7 ± 4.1 years. DNA was extracted from periphera l blood samples from each subject and

### DRAFT - DO NOT CITE OR QUOTE 113 evaluated using the polymerase chain reaction (PCR) with specific primer pairs to detect
deletions in mitochondrial DNA. Deletions in mitoc hondrial DNA were detected in 8/47 exposed workers compared with 0/47 nonexposed workers. A deletion rate of 0.00225 ± 0.00171 was calculated based on optical densities f rom gel scans of the deletion fragment compared with a fragment synthesized by using prime r pairs to a conserved region of mitochondrial DNA; this deletion rate was statistic ally significantly different ( p < 0.05) from the rate of 0 for the controls. For studying the effec ts of aging, a group of 12 healthy nonexposed retirees from governmental organizations (average a ge 79.15 ± 3.80 years) and a group of 12 healthy nonexposed high school students (average age 14.23 ± 1.52 years) were also examined. Deletion fragments were detected in 3/12 elderly subjects and 0/12 young subjects. The deletion rate for the elderly was calculated as 0.00193 ± 0.00086, which was not significantly different from that calculated for AN -exposed workers. The study authors suggested that exposure to AN might have an effect on the molecular process(es) of aging. Limitations of this study included the lack of repo rting for the criteria of selection for the controls and the gender composition of each group. The results identified the mean workplace AN air concentration, 0.11 ppm, as a LOAEL for incr eased prevalence of workers with deletions in peripheral blood mitochondrial DNA compared with controls. Ivanescu et al. (1990) used a radioimmunoassay to measure serum levels of testosterone in three groups of male workers exposed to AN in a chemical factory. Blood samples were taken from 39 subjects in May 1975, from 109 subjects in March 1976, and from 149 subjects in May 1977. Subjects were between 19 and 40 years old an d had been employed at the facility from 6 months to 10 years. Controls in the study consis ted of 145 unexposed men. The three groups of exposed subjects had average serum testosterone concentrations ranging from 3.5 to 4.1 ng/mL. This compared with average values rangi ng from 5.4 to 7.3 ng/mL in different subsets of the 145 control subjects. Although the time of blood sampling during the day was variable in this study and the circadian rhythm of testosterone was unknown, testosterone concentrations in sera of exposed groups were much lower than in control groups of the same month. However, no data were presented in the repo rt on the level of exposure to AN or other
chemicals. An epidemiological report by Czeizel et al. (2000, 1999) examined the incidence of congenital abnormalities and indicators of germinal mutations in the vicinity of an AN-using factory in Hungary. The study used the incidence o f congenital abnormalities from the Hungarian Congenital Abnormality Registry in 46,326 infants born between 1980 and 1996 in 30 settlements within a 25-km radius of an AN-using factory. A number of time-space-specific clusters of abnormalities were identified among the subjects, including pectus excavatum in the Tata community between 1990 and 1992 (OR = 78.5, 95 % CI = 8.4–729.6), undescended testis in Nyergesujfalu between 1980 and 1983 (OR = 8.6, C I = 1.4–54.3) and at Esztergom between

### DRAFT - DO NOT CITE OR QUOTE 114 1981 and 1982 (OR = 4.2, CI = 1.3–13.5), and clubfo ot in Tata between 1980 and 1981 (OR = 5.5, CI = 1.5–20.3). The relationship between the findings of clusters of abnormalities and AN exposure was uncertain because there were no exposure data in th e report. Consequently, it was not known by how much the mothers of affected infants were expos ed to the compound, if at all. Furthermore, when the incidence of congenital abnormalities was considered for infants born throughout the entire duration of the study, there were no increas ed incidences of congenital abnormalities compared with infants born throughout Hungary. The study authors stated that there was a technolo gical change at the AN factory in 1984 that resulted in greater environmental protection, implying that releases of AN to the environment were lower than before the change. Thi s suggests that the cluster of pectus
excavatum obtained at Tata between 1990 and 1992 wa s unlikely to have been due to AN exposure. However, the high incidence of undescend ed testis in Nyergesujfalu between 1980 and 1983 may have been an environmental phenomenon, because the region-wide incidence of this congenital abnormality appeared to decrease wi th increasing distance from the factory. In general, however, it is difficult to draw conclusio ns about a link between maternal exposure to AN and the incidence of congenital abnormalities fr om the data in this study because of a lack of exposure data. Wu et al. (1995) (in the English translation of th e abstract of an article in Chinese) reported findings on 477 female workers exposed to AN and 527 controls studied using the retrospective cohort method. Statistically signifi cant increases in the incidence of pernicious vomiting, anemia, preterm delivery, and birth defec ts were found in exposed women. However, the authors also emphasized several confounding fac tors in their study, such as illness, medicine taking, and X-ray exposure during pregnancy. Other reports of chronic occupational exposure to AN described additional health effects. Babanov et al. (1959) (as cited in IPCS, 1983) repo rted nonspecific changes in skin and pale
mucous membranes in addition to vocal cord inflamma tion in workers exposed to 0.6–6.0 mg/m 3 

### (0.3–3 ppm) AN in air for approximately 3 years. Depression, lowered arterial pressure, diffuse der mographia, and increased sweating in AN production workers was described by Ageeva (1970 ) (as cited in IPCS, 1983). Stamova et al. (1976) (as cited in IPCS, 1983) reported that w orkers in a polyacrylic fiber plant showed increased incidence of skin diseases when exposed t o air concentrations of 10–25 mg/m 3 

### (5– 12 ppm) AN. An increase in other “neurasthenic” co mplaints and diseases was also reported. However, the presence of other industrial chemicals and uncertainty in the length of exposure were potential confounding factors in these respons es. Borba et al. (1996) measured CEVal-Hb adducts as a marker of AN exposure in three groups of occupationally exposed workers in an acry lic fiber factory in Portugal. The groups comprised 20 administrative workers who were not ex posed to AN in the same plant,

### DRAFT - DO NOT CITE OR QUOTE 115 14 individuals employed in the continuous polymeriz ation department, and 10 equipment
maintenance workers. Considered a measure of the b iologically effective dose, CEVal values were 8.5–70.5 pmol/g Hb in controls, 635.2–4,603.5 pmol/g Hb for continuous polymerization workers, and 93.9–4,746 pmol/g Hb for maintenance w orkers. These findings pointed to the ready formation of AN adducts with Hb in exposed wo rkers. Unfortunately, the report lacked
critical information about the levels and duration of exposure to AN undergone by the workers of the different groups and whether such exposure and the adduct formation that resulted were associated with symptoms of ill health. Borba et al. (1996) also monitored several interna l exposure markers for the three groups of workers. The induction of CYP450 species was de termined by the excretion of D-glucaric acid (an end product of the glucuronic pathway) in the urine, and formation of malondialdehyde (MDA) (a final product of lipid peroxidation) in RB Cs was determined as a surrogate measure of oxidative stress. The study authors found no indic ation of AN-induced CYP450 induction, but a significant increase was seen for the oxidative str ess marker in the group of maintenance workers. Smoking had no influence on these metrics . Borba et al. (1996) also investigated markers for genotoxicity (viz., gene reversion acti vity of urine extracts, chromosomal aberrations (CAs), and sister chromatid exchanges [SCEs]). The se are discussed in the genotoxicity section (Section 4.5.2).

4.1.3. Dermal Exposure
4.1.3.1. Acute Exposure A case report by Vogel and Kirkendall (1984) descr ibed a 24-year-old ship’s officer who was accidentally sprayed with AN when a valve burst while he was unloading the chemical. Because the man’s face, eyes, and body were covered with AN, it is likely that he was exposed
via the oral and inhalation routes as well as to th e skin and eyes. Immediate responses to exposure included dizziness, flushing, and nausea w ith vomiting. During hospitalization, acute toxicological impacts included a rapid pulse rate ( 100 beats/minute) and a respiratory rate of 16/minute. The subject displayed erythema and mild conjunctivitis, tachycardia, and striking hematological changes (WBC count of 26,400 cells/cm 3 

### , of which 76% was polymorphonuclear leukocytes, 10% lymphocytes, and 7% each basophiles and monocytes). Methemoglobin (MetHb) concentration was 10.3% on admission. The patient received nitrite/thiosulfate treatment, underwent dialysis, and, overall, showed steady recovery over his 5-day hospitalization.
There are a number of additional case studies of t he toxic effects of AN resulting from acute exposure after accidental spillage in the wor kplace. These support the designation of AN as a skin irritant. In several cases, erythemas we re shown to result from direct dermal contact with solutions of AN (Davis et al., 1973 [as cited in IPCS, 1983]; Zeller et al., 1969; Wilson et al., 1948; Dudley and Neal, 1942). The lesions wer e followed by delayed blistering and burns,

### DRAFT - DO NOT CITE OR QUOTE 116 typically 1 or 2 days following exposure (Davis et al., 1973 [as cited in IPCS, 1983]; Zeller et al., 1969; Babanov et al., 1959; Dudley and Neal, 1942). In some cases, clinically diagnosed dermatitis was associated with irritation (Bakker e t al., 1991; Davis et al., 1973 [as cited in IPCS, 1983]). For example, Davis et al. (1973) (as cited in IPCS, 1983) reported a wide range of dermal effects from AN contact, including skin derm atitis, local irritation, erythema, swelling, blistering, and burns. However, dermatitis has not always resulted from AN-induced skin irritation (Zeller et al., 1969; Babanov et al., 19 59; Wilson et al., 1948; Dudley and Neal, 1942). When Dudley and Neal (1942) investigated the effec ts of AN exposures to laboratory animals, an accident in their laboratory resulted i n a case of occupational exposure. Symptoms similar to those described later by Wilson et al. ( 1948) were reported for a male laboratory worker who spilled small quantities of liquid AN on his hands. Diffuse erythema on hands and wrists was evident after 24 hours, with subsequent blistering on the fingertips on day 3. Both hands became slightly swollen, erythematous, itchin g, and painful. By day 10 after exposure, the skin of the fingers had cracked and peeled and the skin was dry and scaly with large areas of
tender new skin. Zeller et al. (1969) identified 137 cases of accid ental exposure to nitriles when reviewing industrial hygiene data from Germany on accidental exposures to chemical agents in an occupational setting over a 15-year period. Of the 137 cases, 66 cases related to AN exposure, of
which 50 cases resulted from direct skin contact an d the remaining 16 to inhalation or exposure to AN vapors. All 66 cases were judged to be minor and did not require hospitalization. However, up to 3 weeks of recuperation was required as a result of direct skin contact with the compound. Typically, the first symptoms appeared b etween 5 minutes to 24 hours after initial dermal contact with AN. For the most part, the wor kers complained of burning sensations of the skin, followed by reddening of the exposed area and the formation of blisters at any point during the first 24 hours. In one case, AN was thought to have diffused through the leather of a shoe on which it was spilled, resulting in a delay before b listers appeared and delayed healing. There was no indication of resorptive damages from the de rmal exposure in any of the 50 cases. In another study (Babanov et al., 1959), blisterin g was also observed on workers’ legs within 6–8 hours of contact with spilled AN, while a diluted (5%), heated (50°C) solution of AN
caused serious skin burns. A fatal case of dermal contact exposure with AN wa s described by Lorz (1950), when application of a delousing agent containing AN resu lted in the death of a 10-year-old girl. Following dermal application of the delousing agent to the scalp, the girl’s head was wrapped in a cloth and she went to bed. Symptoms of nausea, h eadaches, and dizziness were followed by repeated vomiting and coma. Cramps and increasing cyanosis were followed by death 4 hours after application. A similar case of fatal poisoni ng was reported by Grunske (1949) in which a 3-year-old girl died after reentry into a home that had been treated with an AN-containing

### DRAFT - DO NOT CITE OR QUOTE 117 fumigant. In both of these cases, exposure was lik ely to have occurred via inhalation as well as
the dermal route.

4.1.3.2. Chronic Exposure
In addition to the known skin irritation effects o f acute exposures to high-concentration liquids and vapors, various chronic dermal exposure effects were reported. There was limited
evidence that skin sensitization resulted in dermal allergies to AN. Therefore, an intrinsic capacity of AN to act as a skin sensitizing agent w as suggested. The abstract of a Japanese language report by Hash imoto and Kobayasi (1961) discussed the case of a chemical laboratory worker who develo ped skin lesions through contact with AN. Although much of the detail remained uncertain, inc luding period and duration of exposure and the influence of other chemicals on the subject’s c ondition, the lesions apparently spread across the subject’s body from the contact site, consisten t with a direct contact allergic reaction. Bakker et al. (1991) reported that 10 employees at an acrylic fiber factory complained of skin irritation. While five of the subjects develo ped irritant dermatitis, the other five subjects gave positive patch tests with AN, suggesting an al lergic reaction. This finding also supported the designation of AN as a sensitizing agent. Prolonged dermal contact for 6 weeks to methyl met hacrylate, a copolymer of AN, resulted in an allergic skin sensitization reaction in the case of a 27-year-old man who had his finger splinted for a torn ligament (Balda, 1975). The unpolymerized AN of the Plexidur copolymer resulted in strong skin irritation respon se, with erythema and formation of scaly skin and scattered blisters. Patch testing confirmed th at the allergic sensitization was to AN and not to a copolymer or the polymerization catalyst, benz oyl peroxide. A contributing factor may have been the man’s prior hyperhydrosis episode of the h ands that led to blister formation. Very few studies hinted at a possible desensitizat ion or adaptive effect for prolonged chronic exposures. Based on investigations carried out over a period from 1965 to 1971, Zotova (1975) reported complaints of poor health, which in cluded skin irritation, in workers at an AN manufacturing facility. Gincheva et al. (1977) (as cited in IPCS, 1983) did not find changes in the health status of a group of 23 men exposed to 4 .2–7.2 mg/m 3 

### (2–3.3 ppm) of AN for exposure durations of 3–5 years. Details of the st udy were not provided.

4.1.4. Ocular Exposure Secondary routes of exposure to AN include ocular exposure to either AN liquid or vapor. For example, in the Wilson et al. (1948) st udy, subjects exposed to AN at concentrations varying from 16 to 100 ppm (35–217 mg/m 3 

### ) for 20–45 minutes demonstrated irritation of all mucous membranes, including the eyes, nose, and thr oat. In other studies, blepharoconjunctivitis was reported in workers exposed to the compound (De livanova et al., 1978). Of 302 workers

### DRAFT - DO NOT CITE OR QUOTE 118 examined over 2 years (138 in 1976 and 164 in 1978) , 42 had severe cases of blepharoconjunctivitis related to AN exposure. In the case report by Vogel and Kirkendall (1984), the mucous membranes of the eyes of the 24-year-old man had been sprayed with AN. Amon g other symptoms, mild conjunctivitis but no apparent corneal clouding was observed. Eye irr itations and nasal discharge also were reported in workers exposed to relatively high leve ls of AN at an acrylic fiber plant (Sakurai, 2000; Sakurai et al., 1978). A synopsis of noncancer outcomes of exposure to AN is provided in Table 4-22.

Table 4-22. Epidemiology studies of noncancer outc omes among cohorts of workers exposed to AN

Reference Study population Exposure assessment Toxic effects/outcome Muto et al. (1992) 157 Male workers

employed in seven Japanese acrylic fiber plants with average of 17 yrs employment; 537 unexposed controls Mean 8-hr TWAs: Group A factories = 0.19 ppm; Group B factories = 1.13 ppm Increased prevalences of subjective symptoms in Group B factories, such as heaviness of the stomach, decreased libido, poor memory, irritability, conjunctival reddening, and eye irritation; not in Group A; no significantly increased prevalences of physical signs or abnormal values in urinalytic, hematological, liver function, or blood pressure variables in Group A or B compared with control
Sakurai et al. (1978) 102 Male workers in six

Japanese acrylic fiber plants with averages of 10–12 yrs of employment; 62 matched controls Mean 8-hr TWAs: Group A factories = 0.1 ppm; Group B factories = 0.5 ppm; Group C factories = 4.2 ppm Statistically insignificant increase in the incidence of palpable liver, reddening of the conjunctiva and pharynx, and skin rashes compared with controls; survey of subjective symptoms not performed

Kaneko and Omae (1992) 502 Male workers in

seven Japanese acrylic fiber plants with averages of 5.6, 7.0, and 8.6 yrs of employment at low-, medium-, and high-level workplace exposure; 249 unexposed matched controls Group L factories = 1.8 ppm; Group M factories = 7.4 ppm; Group H factories = 14.1 ppm: air concentrations reported as “means” without other information Statistically significant increased prevalences of subjective symptoms, such as headaches, tongue trouble, choking lump in chest, fatigue, general malaise, heavy arms, and heavy sweating in workers in Groups L, M, and H factories, compared with controls

Chen et al. (2000) 224 Workers (180 males

and 44 females) in an acrylic fiber plant with average of 13 yrs of employment; 224 unexposed controls 0.48 ppm Statistically significant increased prevalences of subjective symptoms, such as headache, dizziness, poor memory, choking feeling in the chest, and loss of appetite, compared with controls; increase in serum γ -GTP but not in other clinical chemistry or hematological variables

### DRAFT - DO NOT CITE OR QUOTE 119 Table 4-22. Epidemiology studies of noncancer outc omes among cohorts of workers exposed to AN

Reference Study population Exposure assessment Toxic effects/outcome Lu et al. (2005a) Chinese acrylic fiber

workers: 81 monomer workers (68 male and 13 female); 94 fiber workers (67 male and 27 female); 174 unexposed workers Mean 8-hr TWAs: Monomer work areas = 0.11 ppm (0–1.7 ppm); fiber manufacture work areas = 0.91 ppm (0– 8.34 ppm) Small but statistically significant deficits in tests of neurobehavior in monomer and fiber workers compared with controls; significant deficits in tests of mood (increased scores for anger, confusion, depression, fatigue, and tension), attention and response speed, auditory memory, and motor steadiness; not in tests of manual dexterity or perceptual motor speed Dong and Pan (1995) 255 Workers in a Chinese

chemical fiber plant (150 males and 105 females) with averages of 3.2 and 10.2 yrs of employment; 231 unexposed controls Workplace air concentrations = 0.24– 7.1 ppm; midpoint = 3.7 ppm Statistically significant increased prevalences of adverse reproductive outcomes (premature delivery [10.7 vs. 3.5%, wives of exposed males], stillbirths [4.5 vs. 0%, exposed females], and sterility [5.0 vs. 1.8%, exposed males]) compared with controls Dong et al. (2000b) 548 Male and 391 female

workers in a Chinese chemical fiber plant with averages of 11.0 and 10.4 yrs of employment; 496 male and 427 female unexposed controls Workplace air concentrations = 0.05– 7.14 ppm; midpoint = 3.6 ppm Statistically significantly increased prevalences of adverse reproductive outcomes (increased stillbirths [2.7 vs. 0%], birth defects [21.3 vs. 4.8%], and premature deliveries [8.2 vs. 3.9%]) in female workers compared with controls

Dong et al. (2000a) 93 Workers at a Chinese

chemical fiber plant; 96 unexposed controls Unclear presentation of exposure data Increased prevalences of subjective symptoms (headache, dizziness, sleeping disorders, and a feeling of choking in the chest) compared with controls Li (2000) 379 Female AN

manufacturing workers employed an average of 14 yrs; 511 unexposed controls Average workplace air concentration = 7.5 ppm; range = 0– 70 ppm Statistically significant increased prevalences of adverse reproductive outcomes (sterility [2.6 vs. 0.8%], pregnancy complications [20.8 vs. 7.1%], premature deliveries [11.6 vs. 4.7%], and congenital defects [25.4 vs. 4.2%]) in female exposed workers compared with controls Xiao (2000a) 372 Workers exposed to

AN in a chemical factory; 186 unexposed controls No data Increase in the serum ALT activity

Xiao (2000b) 237 Workers exposed to

AN in a chemical factory; 184 unexposed controls Workshop A = 7 ppm; workshop B = 3.3 ppm; workshop C = 3 ppm Reduction in whole blood cholinesterase activity; subjective symptoms such as neurological disorder, sweating, trembling, and discomfort in the chest
Ivanescu et al. (1990) 39 Subjects (May 1975),

109 subjects (March 1976), 149 subjects (May 1977) No data Reduced serum testosterone

Czeizel et al. (2000, 1999) Case control study of

babies born with congenital abnormalities in the vicinity of an AN-using factory No data Incidence of undescended testis possibly related to proximity to the AN-using facility

### DRAFT - DO NOT CITE OR QUOTE 120 Table 4-22. Epidemiology studies of noncancer outc omes among cohorts of workers exposed to AN

Reference Study population Exposure assessment Toxic effects/outcome Wu et al. (1995) 477 Female AN workers;

527 workers No data Increased vomiting, anemia, preterm delivery, and birth defects in pregnant females
Babanov et al. (1959) Unstated number of

exposed subjects 0.3–3.0 ppm Changes to skin and mucous membranes, vocal cord inflammation Ageeva (1970) (as cited in IPCS, 1983) Unstated number of

exposed workers No data Diffuse dermographia and increased sweating

Stamova et al. (1976) (as cited in IPCS, 1983) Unstated number of

exposed AN workers 5–12 ppm Skin reactions

Delivanova et al. (1978) 302 Exposed workers No data Blepharoconjunctivitis



### 4.2. SUBCHRONIC AND CHRONIC STUDIES AND CANCER BIO ASSAYS IN
ANIMALS—ORAL AND INHALATION AN has been demonstrated to be a multiple-site carc inogen in rat and mouse bioassays. Chronic oral exposure to AN-induced tumors in the b rain or spinal cord, Zymbal gland in the ear canal, the forestomach, and, to a lesser degree and less consistently, in the female mammary gland and the tongue in several oral bioassays with F344 rats (Johannsen and Levinskas, 2002b; Bigner et al., 1986; Biodynamics, 1980b) and Spragu e-Dawley rats (Johannsen and Levinskas, 2002a; Quast, 2002; Biodynamics, 1980a, b; Quast et al., 1980a). In addition, oral exposure for up to 46 weeks led to increases in brain astrocytom as and Zymbal gland in female SpragueDawley rats (Friedman and Beliles, 2002; Litton Bio netics, 1992). Lifetime inhalation cancer bioassays with Sprague-Dawley rats found exp osure-related increased incidences of brain tumors, Zymbal gland tumors, intestinal tumors, mal ignant mammary gland tumors, and tongue tumors (Dow Chemical Co., 1992a; Maltoni et al., 19 88, 1977; Quast et al., 1980b). In mice, a single gavage lifetime bioassay identified the fore stomach and the Harderian gland as sites of tumor development, but elevated incidences of brain , Zymbal gland, or mammary gland tumors were not found (NTP, 2001). Thus, consistent targe t organs for the carcinogenicity of AN include the forestomach, CNS, and Zymbal gland in r ats and the forestomach and ocular Harderian gland in mice. Exposure-related increase d incidences of tongue and mammary gland tumors have been observed, but the responses have n ot been observed as consistently across studies as the responses in the forestomach, CNS, a nd Zymbal gland in rats. Evidence from two studies of exposure to AN starti ng in early-life suggests increased susceptibility to the carcinogenicity of AN compare d with chronic exposure during adulthood only. The evidence for carcinogenicity in these st udies, a three-generation reproductive/ developmental study of AN in drinking water (Friedm an and Beliles, 2002) and an inhalation

### DRAFT - DO NOT CITE OR QUOTE 121 bioassay (Maltoni et al., 1988), is presented in Se ctions 4.2.1.2.8. and 4.2.2.2, respectively. The evidence for early-life susceptibility is discussed in Section 4.8.1. Oral toxicity studies in rats and mice identified the forestomach as the most sensitive target organ for the noncancer toxicity of oral exp osure to AN. Hyperplasia of the forestomach epithelium occurred at lower oral doses than doses producing other noncancer effects. Increases in other nonneoplastic lesions were observed in the kidney, Harderian gland, and ovary.
Available data include results from several oral to xicity and cancer bioassays of chronically exposed rats (see the first paragraph for reference s) and one oral toxicity and cancer bioassay in mice (NTP, 2001). Results from a single chronic inhalation toxicity study in rats (Quast et al., 1980b) identified the nasal epithelium as a sensitive nonc ancer toxicity target of AN. Hyperplasia of mucus-secreting cells and flattening of the respira tory epithelium developed with chronic exposure to concentrations as low as 20 ppm. A lim ited number of other subchronic studies in rats identified impaired sensory nerve conduction ( Gagnaire et al., 1998) and mild developmental effects in the presence of maternal toxicity (Saill enfait et al., 1993; Murray et al., 1978) (see Section 4.3) as other noncancer effects associated with repeated inhalation exposure to AN.

4.2.1. Oral Exposure
4.2.1.1. Subchronic Studies Single studies in dogs and mice are the only well-d ocumented standard bioassays for the subchronic toxicity of AN in experimental animals b y the oral route (NTP, 2001; Quast et al., 1975). A full report of a study in rats is not ava ilable (Humiston et al., 1975 [as cited in Quast, 2002]). Additional subchronic studies have evaluat ed only functional effects of AN exposure in specific organs, such as the adrenals (Szabo et al. , 1984) and the brain (Gagnaire et al., 1998). These endpoint-specific studies are discussed in Se ction 4.4.1. Humiston et al. (1975) (as cited in Quast, 2002) e xposed groups of Sprague-Dawley rats (10/sex/group) to AN in drinking water at concentra tions of 0, 35, 85, 210, or 500 ppm for 90 days. Reported intakes of AN for males/females, respectively, were 0/0, 4/5, 8/10, 17/22, or 38/42 mg/kg-day. Water consumption was decreased i n a dose-related manner in both sexes, with females more affected than males. However, th e lowest dose affecting males was not identified in the summary; in females exposed at 35 ppm, 9 of 26 measured intervals showed statistically significant decreases compared with c ontrols. In the 210 and 500 ppm groups, there were significant decreases in water consumption, fo od consumption, and BW, but no information was provided as to the magnitude of these changes. Exposure to AN had no effect on hematology, clinical chemistry, or histopathologic findings; urinalysis results were also unaffected by treatment, except for an increase in specific gravity that was correlated with increasing dose. Apparently, a number of treatment -related effects was observed in the 85 ppm group, but neither their identity nor the magnitude of change were specified. The summary

### DRAFT - DO NOT CITE OR QUOTE 122 provided by Quast (2002) did not provide sufficient detail to accurately identify NOAEL or LOAEL values from the study by Humiston et al. (197 5) (as cited in Quast, 2002). Szabo et al. (1984) evaluated the effect of subchr onic oral exposure to AN on the structure and function of the adrenal gland and int estinal tract in rats. Female Sprague-Dawley rats (three to four per group) were exposed for 7, 21, or 60 days to AN in drinking water at concentrations of 0, 1, 20, 100, and 500 ppm, repre senting approximate daily doses of 0, 0.2, 4, 20, and 100 mg/kg. Other groups of rats received e quivalent doses of AN by gavage for the
same duration. Water and food intakes were monitor ed continuously and BWs were recorded every fourth day. At the end of the studies, blood samples were taken to measure plasma corticosterone and aldosterone, and a complete necr opsy was carried out on all survivors. The adrenals, thyroid, liver, and one kidney were weigh ed. Samples of liver, kidney, lung, brain, and the entire adrenal and thyroid glands were measured for levels of nonprotein sulfhydryls in tissue homogenates. Adrenals, “other” endocrine organs, s tomach, duodenum, liver, kidney, lung, and heart were evaluated for histopathology. BWs were reduced by about 25% in rats exposed to 50 0 ppm in drinking water up to 60 days, but no reduction in BW was observed in rat s receiving the equivalent dose of 100 mg/kg-day by gavage (Szabo et al.,1984). Water intake was reduced in rats exposed to 500 ppm in drinking water but increased at the equi valent gavage dose. Adrenal weights were slightly lower than in controls in the 7- and 21-da y exposure groups, but significant increases in relative adrenal weights were observed after 60 day s of exposure to 500 ppm in drinking water or

to ≥ 0.2 mg/kg-day by gavage. The kidneys were enlarged in rats exposed to 100 or 500 ppm AN in drinking water for 60 days or 500 ppm for 21 day s. Histopathological lesions included adrenocortical h yperplasia in all rats exposed by
gavage at ≥ 0.2 mg/kg-day for 60 days. Enlarged kidneys and hy perplasia of the gastric mucosa at the junction of the glandular stomach and forest omach was observed in rats exposed to 100 or 500 ppm in drinking water for 21 or 60 days. No in cidence data were provided for these lesions. Plasma corticosterone levels were significantly dec reased by both 500 ppm AN in drinking water or by gavage in the 21-day study. Even the lowest concentration of 1 ppm AN by gavage
resulted in a 50% reduction in corticosterone. Pla sma aldosterone concentration was reduced, starting from 20 ppm AN. In the 60-day study, sign ificant suppression of plasma corticosterone was observed after exposure to 100 or 500 ppm AN in drinking water and in all exposure levels given by gavage. Levels of nonprotein sulfhydryls (glutathione) were increased by 20–50% in the 7- and 21-day studies but were significantly reduced by 20 –30% in the adrenals after 60 days of gavage exposure to 4–60 mg/kg-day. Increases in nonprotei n sulfhydryl concentrations in duodenal mucosa were observed in the 100 or 500 ppm AN expos ure groups in the 7- and 21-day studies and in all doses after 60 days, but not in the cont rol group of rats that received water by gavage. For the drinking water study, a NOAEL of 20 ppm (4 mg/kg-day) and a LOAEL of 100 ppm

### DRAFT - DO NOT CITE OR QUOTE 123 (20 mg/kg-day) were identified for enlarged kidneys and increases in regional hyperplasia of the gastric mucosa in female rats exposed for 60 days. For the gavage study, no NOAEL was identified, but a LOAEL of 0.2 mg/kg-day was identi fied for adrenocortical hyperplasia in rats exposed for 60 days. In a separate experiment, Szabo et al. (1984) evalu ated age-dependency in the sensitivity of Sprague-Dawley rats to the action of AN on the a drenals. Groups of weanling rats (40 g) and adult rats (190 g) were treated with 0, 0.002% (20 ppm), 0.01% (100 ppm), or 0.05% (500 ppm) of AN in drinking water for 21 days, or were given by the corresponding amount of AN by daily gavage for 21 days. The animals were sacrificed, a nd plasma and adrenals were collected as in the previous experiments. Young, immature rats tre ated with AN were found to have lower (up to 66%) levels of plasma corticosterone and aldoste rone than adult rats. These differences were statistically significant with 0.01% AN given by ga vage or 0.05% AN in drinking water. Quast et al. (1975) exposed beagles (four/sex/grou p) to 0, 100, 200, and 300 ppm AN (purity >99%) in drinking water for 6 months; the r eported calculated doses were approximately 0, 10, 16, and 17 mg/kg-day in males, respectively, and 0, 8, 17, and 18 mg/kg-day in females, respectively. Dogs were evaluated daily for clinic al signs and weighed weekly; food and water consumption were calculated from the consumption by groups of dogs penned together. Routine hematology examinations were conducted on all sampl es taken from all dogs 20 days before exposure and on days 83, 130, and 179. Blood and u rine samples for standard biochemical analyses were collected from all dogs 8 days before exposure, on days 84, 135, and 176, and at termination (day 182 for males and day 183 for fema les). Serum samples were collected from all dogs on day 155 to determine total protein concentr ations and evaluate the percentages of specific Igs by electrophoresis. Ophthalmic examin ations were conducted pretest and at 85, 112, and 175 days. All dogs were subjected to gross nec ropsy at which time organ weights were recorded for brain, heart, liver, kidneys, and test es; a full set of tissues from all dogs was examined for histopathology. Samples of liver and kidney were analyzed for nonprotein free sulfhydryl content. The following treatment-related effects were obser ved in dogs exposed to AN in drinking water for 6 months (Quast et al., 1975). No mortal ity was observed in the control or 100 ppm groups, but dogs exposed at 200 ppm (2/4 males and 3/4 females) and 300 ppm (3/4 males and 2/4 females) either died prematurely or were euthan ized in a moribund condition. Signs of toxicity manifested in these dogs included reduced consumption of food and water, decreased BW, roughened hair coat, and a nonproductive cough. These dogs subsequently exhibited lethargy, weakness, emaciation, respiratory distres s, and terminal depression. Decreased water consumption was observed throughout the study in ma les at 300 ppm and sporadically in females

at ≥ 200 ppm. Food consumption was reduced in males at 300 ppm and females at ≥ 100 ppm. A supplemental study was conducted on eight female do gs treated with 100 ppm AN for 5 weeks, and no reduction in food or water consumption was o bserved.

### DRAFT - DO NOT CITE OR QUOTE 124 Substantial reductions in BW were observed among d ogs that died (200 and 300 ppm); group mean weights among surviving male and female dogs were not statistically significantly
different from controls. RBC and Hb counts were re duced by 19–21% in males exposed to 200 ppm for 83 days but not at later time points; f emales exposed at 300 ppm exhibited 22–26% decreases in RBC counts after 83 and 130 days of ex posure. No treatment-related changes in hematology parameters were evident after 179 days o f exposure. Exposure to AN had no effect on urinalysis, clinical chemistry, ophthalmoscopic examinations, nonprotein free sulfhydryl content in liver or kidney, or the electrophoretic behavior of serum proteins. Statistically significant alterations in organ weight, such as in creases in relative kidney weights in males treated at 100 and 200 ppm, were not biologically s ignificant (less than 10% change). Histopathologic changes were observed in the esopha gus (focal erosions and/or ulcerations in the middle one-third, dilations, and thinning of the wa lls) and tongue (increased thickness of epithelium lining of the dorsal surface) of male an d female dogs treated at 200 and 300 ppm. Lesions of the lung were attributed to parasitic ne matode infection that was present in all dogs. In this study, a NOAEL of 100 ppm (8–10 mg/kg-day) and a LOAEL of 200 ppm (16–17 mg/kgday) were identified for early mortality and histop athological lesions of the esophagus and tongue in male and female dogs. In a comparative study of the neurotoxicity of nitr iles, Gagnaire et al. (1998) administered AN (>99% purity) at doses of 0, 12.5, 25, or 50 mg/kg-day to male SpragueDawley rats (12/group plus 10 controls) by gavage i n olive oil, 5 days/week for 12 weeks. BWs were measured weekly. After 3, 6, 9, and 12 weeks of treatment and after an 8-week recovery period (week 20), rats were evaluated for electroph ysiological parameters, with testing occurring 16 hours after dosing (or 48 hours for testing afte r weekends). Electrical stimulation of the tail nerve was used to assess four neurological properti es, the motor conduction velocity (MCV), sensory conduction velocity (SCV), and amplitudes o f the sensory and motor action potentials (ASAPs and AMAPs). One high-dose rat died during the first week of tre atment, but no other mortality was observed. High-dose rats showed reduced BW gain th at became significant after the fourth week of treatment, leading to a terminal BW 17% lower th an in controls. BWs of mid-dose rats became significantly lower than controls after the fifth week, resulting in a terminal weight approximately 7% lower than controls (as estimated by visual inspection of the data graph); this weight change was not considered biologically signi ficant. Five of 11 high-dose rats exhibited significant weakness of the hind limbs that somewha t improved during the recovery period. Rats exposed to AN showed acute signs of behavioral abno rmalities, including salivation, locomotor hyperactivity, and fur wetting within 1 hour of dos ing. Gagnaire et al. (1998) attributed these findings to cholinomimetic effects possibly caused by AN-induced changes in muscarinic acetylcholine receptors or by alterations in hepati c metabolism. Exposure to AN had no effect on MCV or AMAP except for a 40% increase in AMAP ob served in high-dose rats at the 9-week

### DRAFT - DO NOT CITE OR QUOTE 125 time point. The most consistent effect of AN was a significant reduction in SCV compared with that in controls (Table 4-23), ranging from 7.5 to 15% between weeks 6 and 12 ( p < 0.05 to

p < 0.001); this effect abated following the cessatio n of exposure, but a 10.6% reduction compared with controls (

p < 0.001) was observed after 8 weeks of recovery (w eek 20). A 25% reduction in ASAP was also observed in high-dose ra ts at week 20, but no effect on this parameter was observed during the treatment period. A NOAEL of 25 mg/kg-day and a LOAEL of 50 mg/kg-day were identified in the study by Gag naire et al. (1998), based on reduced BW and neurotoxic effects (weakness of the hind limbs and reduced SCV) in male rats exposed to AN by gavage.

Table 4-23. Effect on SCV in male Sprague-Dawley r ats exposed to AN via gavage for 12 weeks

SCV (m/s) a Exposure (weeks) Recovery Group (mg/kg) 0 3 6 9 12 20
0 34.2 ± 0.7 43.2 ± 0.6 45.2 ± 1.3 48.4 ± 1.1 46.6 ± 0.8 53.8 ± 1.5
12.5 34.9 ± 0.5 42.6 ± 0.9 45.7 ± 0.7 47.8 ± 0.7 46 .7 ± 0.9 51.8 ± 0.9
25 34.6 ± 0.8 40.0 ± 1.0 45.5 ± 0.6 46.0 ± 0.9 44.4 ± 0.9 51.3 ± 0.7
50 35.8 ± 1.1 42.2 ± 1.1 41.8 ± 1.3 b 44.0 ± 1.2 c 39.8 ± 0.6 c 48.1 ± 0.7 c

a Values are means ± SDs, n = 12 for treated rats and n = 10 for controls.
b Statistically significant compared with controls ( p < 0.05), as calculated by the authors.

c Statistically significant compared with controls ( p < 0.001), as calculated by the authors.

Source: Gagnaire et al. (1998).



### In a comparative study on the effects of nine comp ounds related to acrylamide (Barnes, 1970), AN was administered by gavage over a period of 7 weeks to six young adult albino rats of the Porton strain as 15 daily doses of 30 mg/kg, followed by 7 doses of 50 mg/kg, and finally 13 doses of 75 mg/kg. The time-adjusted average do se administered over the course of the study was 36 mg/kg-day. Rats were weighed weekly, and th eir gait and stance when walking on a sloping nonslippery surface including an ascent up a sloping wooden board were evaluated. Treated rats were also held by the tail in front of a sloping bar, and tested for the ability to grasp the bar with the front paws, and then grasp it with the hind feet, a reflex typically lost early in rats with peripheral neuropathies. No data were pr ovided for this experiment, but the study author reported that there was no evidence of adver se effects. In a recent study that explored the neurobehaviora l effects of AN in rats (Rongzhu et al., 2007), male Sprague-Dawley rats (10/group) were exp osed to 0, 50, or 200 ppm AN in drinking water. The study authors estimated AN doses to be 0, 4.03, and 13.46 mg/kg-day. Three neurobehavioral tests, including the open field tes t, rotarod test, and spatial water maze, were conducted to evaluate locomotor activities, motor c oordination, and learning and memory,

### DRAFT - DO NOT CITE OR QUOTE 126 respectively, prior to initiation of exposure and a t 4, 8, and 12 weeks of exposure. Thiocyanate
levels in urine were measured in a minimum of five rats from each group at week 12 and were reported to be 2.79, 6.10, and 25.03 mg/g creatinin e, respectively. Beginning from the sixth week of AN administration , three rats in the 50 ppm AN group and five rats in the 200 ppm AN group showed behavi oral changes. The coat appearance in all treated rats was soiled, and the main changes were head twitching, trembling, circling, backwards pedaling, and decreased home-cage activit ies. The two treatment groups also showed less BW gain than the control group. In the open f ield test, there were no significant differences in start-up latency among the exposed and unexposed groups. The 200 ppm group consistently had higher locomotor activity than the control grou p, from pretreatment to 12 weeks of exposure. There were also no changes in the number of rearing and grooming episodes. Therefore, there were no uniform changes in exploration and locomoti on. In the rotarod test, the maximal and the total and falling latency in the 50 and 200 ppm gro ups were significantly decreased in a doseand time-dependent manner. In the spatial water ma ze test, rats in the 200 ppm group had significantly increased training time and training duration, compared with the control and 50 ppm groups. However, these two parameters in th e exposed groups returned to close to control level at the end of the experiment. Rongzh u et al. (2007) suggested that this reversible phenomena may be caused by tolerance. The study au thors concluded that oral exposure to AN
induced neurobehavioral alterations. The neurochem ical mechanisms need to be further investigated. The LOAEL for neurobehavioral altera tions is 4 mg/kg-day. In a range-finding study for a 2-year bioassay (se e Section 4.2.1.2), the National Toxicology Program (NTP) (2001) treated B6C3F 1 

### mice (10/sex/group) with 0, 5, 10, 20, 40, or 60 mg/kg-day AN (purity >99%) by gavage in water, 5 days/week for 14 weeks; adjusted for intermittent exposure (5 days/7 days), the intakes were 0, 3.6, 7.1, 14.3, 28.6, and 42.9 mg/kgday. Clinical findings were recorded on day 8 and once weekly thereafter. BWs were recorded before treatment, weekly, and at study termination. Necropsies were performed on all animals, at which time organ weights were recorded for heart , right kidney, liver, lung, spleen, right testis, and thymus. Hematology analysis was conducted on a ll mice surviving at the end of the study. Complete histopathologic analyses were conducted on all control mice and those treated with 40 and 60 mg/kg-day; males receiving 20 mg/kg-day w ere also examined. At the end of the study, 10 males/group in the groups receiving 0, 5, 10, and 20 mg/kg-day were selected for reproductive evaluations; the left cauda, left epid idymis, and left testis were weighed and sperm samples were evaluated for sperm counts and motilit y. Also, 10 females/group in the groups receiving 0, 10, 20, and 40 mg/kg-day were evaluate d for vaginal cytology (estrous cycle and stage length) in the last 12 days of the study befo re termination. The following effects were observed in mice expose d by gavage to AN. Aside from one control male at week 9, there were no deaths at exp osures up to and including 20 mg/kg-day. Mortality at the two highest doses comprised 9/10 m ales and 3/10 females at 40 mg/kg-day and

### DRAFT - DO NOT CITE OR QUOTE 127 all mice treated at 60 mg/kg-day. All deaths occur red on the first day, except for one male in the 40 mg/kg-day group. Slight (2–8%) decreases in BW in treated mice compared with controls were not biologically significant. Survivors (seve n females and one male) receiving 40 mg/kgday exhibited lethargy and abnormal breathing immed iately after dosing “for several days” but then appeared to develop tolerance to AN. Sporadic, statistically significant alterations in hematological parameters included reductions in platelet counts by 20% in males at 20 mg/kg-day, in leukocyte and lymphocyte counts (~30% in males at 20 mg/kg-day and ~37% in fem ales at 40 mg/kg-day), and in Hb and RBC counts by 10% in females at 40 mg/kg-day; other statistically significant changes of doubtful biological significance in females include d reductions in RBC counts by 4% in groups treated with 5–20 mg/kg-day and in hematocrit by 6% in the 40 mg/kg-day group. Some of these hematological effects may have been secondary to st omach ulceration observed in some mice. Absolute and relative heart weights were increased by 20 and 30%, respectively, in males at 20 mg/kg-day. The absolute weights of the left cauda epididymides were increased by 15% in groups exposed at 10 and 20 mg/kg-day. However, no histopathological findings were reported in these organs. The only treatment-related lesion s were in the forestomach of females at 40 mg/kg-day: 4/7 with chronic active inflammation (associated with hyperplasia) and 5/7 with focal epithelial hyperplasia. Two females in this group exhibited focal ulceration of the forestomach associated with the hyperplasia. No ot her treatment-related histopathology was observed. Exposure to AN produced no effects on sp erm motility in males at ≤ 20 mg/kg-day. There were no differences in vaginal cytology param eters in females at ≤ 40 mg/kg-day. A NOAEL of 20 mg/kg-day and a LOAEL of 40 mg/kg-day w ere identified in the NTP (2001) bioassay, based on hyperplastic lesions in the fore stomach of female mice.

4.2.1.2. Chronic Studies The chronic toxicity and/or carcinogenicity of AN have been evaluated in drinking water or gavage studies in rats and a gavage study in mic e (Johannsen and Levinskas, 2002a, b; Quast, 2002; Biodynamics, 1980a, b; Quast et al., 1980a). Studies by Gallagher et al. (1988), Maltoni et al. (1988, 1977), and Bigner et al. (1986) were can cer bioassays that did not investigate nonneoplastic lesions caused by oral exposure to AN . In addition, a three-generation reproductive toxicity assay involving up to 46 week s of exposure to AN (Friedman and Beliles, 2002; Litton Bionetics, 1992) provided evidence of AN carcinogenicity. These studies are
discussed below.

4.2.1.2.1. Quast (2002) and Quast et al. (1980a). Quast (2002) and Quast et al. (1980a) conducted a 2-year toxicity and carcinogenicity stu dy in Sprague-Dawley rats (48/sex/group) exposed to AN (purity >99%) in drinking water at co ncentrations of 35, 100, or 300 ppm; groups of 80/sex receiving untreated drinking water served as controls. Additional interim-sacrifice

### DRAFT - DO NOT CITE OR QUOTE 128 groups of 10/sex/dose were exposed for 1 year and a nalyzed under the same protocol as the main study. The reported intakes of AN were 0, 3.4, 8.5 , and 21.3 mg/kg-day for male rats and 0, 4.4, 10.8, and 25.0 mg/kg-day for female rats. Rats wer e observed daily for clinical signs of toxicity and were weighed and examined monthly for palpable masses. Food and water consumptions were determined for 30 rats/sex/group weekly for th e first 3 months of the study and for 1 week during each of the following months: 4, 5, 6, 7, 9 , 11, 12, 15, 18, 21, and 24. Hematology examinations and urinalysis were conducted on 10 ra ts/sex in the control and the highest dose group on days 45, 87, 180, and 355. Additional hem atology examinations were conducted on 10 rats/sex from all groups on days 544 (males) and 545 (females) and at study termination on day 724 (males and females); an additional urinalys is was conducted on 10 rats/sex from all groups on day 181 to evaluate a dose response for i ncreased urine specific gravity observed previously at the highest dose group. Clinical che mistry examinations were conducted on 10 rats/sex from the control and highest dose group s on days 46 and 356, on 10 rats/sex from all groups on days 88, 180, and 550, and on all survivo rs on day 746. All rats, whether dying prematurely, sacrificed in a moribund condition, or sacrificed on schedule, were subjected to a gross necropsy, which included an ophthalmologic ex amination. Necropsies of rats on scheduled sacrifice included organ weight determinations for brain, heart, liver, kidneys, and testes. Complete histopathologic examinations were conducte d for rats in the control and 300 ppm groups in the 1-year interim and 2-year studies, an d, based on those results, a set of 22 tissues was examined microscopically in nearly all rats exp osed at 35 and 100 ppm; tumors and other lesions identified at gross necropsy were also exam ined microscopically.

Noncancer results Exposure to AN in drinking water reduced survival, BW, and consumption of food and water by Sprague-Dawley rats in a dose-related mann er (Quast, 2002; Quast et al., 1980a). In male rats exposed at 300 ppm, survival was signific antly reduced compared with controls ( p < 0.05), beginning at 16 months, and none survived after 22 months; survival in other treated male groups was not significantly different from co ntrols. In female rats, exposure at 300, 100, and 35 ppm resulted in significantly reduced surviv al beginning at 10, 12, and 18 months, respectively, with no high-dose females surviving p ast month 22; at 24 months, survival was 25, 8.3, 2.1, and 0% for the control and low- to high-d ose groups, respectively. The magnitude, time of onset, and duration of significantly lower BWs i n exposed rats compared with controls were dose related. Only the 17–22 and 17–18% decreases observed in males and females, respectively, at 300 ppm were biologically signific ant. Reductions only reached ~8–9% in the 100 ppm groups and ~6–9% in the 35 ppm groups. The study authors mentioned that BW comparisons nea r the end of the study tended to be confounded by geriatric changes, few surviving rats , and excessive tumor growth in exposed rats. Food intake (g/rat/day) was significantly lower in 100 and 300 ppm groups compared with

### DRAFT - DO NOT CITE OR QUOTE 129 controls beginning during the first week of the stu dy and only in females at 35 ppm. Significantly lower feed intake values for males an d females, respectively, compared with
controls were measured on 12/24 and 16/24 occasions at 300 ppm, 8/24 and 11/24 times at 100 ppm, and 9/24 times in females only at 35 ppm. The largest difference in high-dose rats was
a 25% reduction of feed intake in males after 6 mon ths and a 27% reduction in females after 9 months. Feed intakes during the last weeks of th e study were not significantly different among the different groups. Water intake was reduced during the first 10 days b y 36% in males and 38% in females exposed to 300 ppm AN and remained significantly lo wer for all 26 measurements throughout the study. Significantly lower water consumption w as also measured 24/26 times for males and 23/26 times for females at 100 ppm and 13/26 times for males and 21/26 times for females at 35 ppm. Male and female rats in the 100 and 300 pp m dose groups showed a lack of normal grooming later in the study. In addition, signs of nervous system dysfunction (erratic movements, trembling, circling, and limb weakness) were observed in the higher dose groups rats in the absence of end-stage kidney disease or pituitary tumors. These signs of nervous system dysfunction when they occurred in controls w ere correlated with end-stage kidney disease or pituitary tumors and occurred more frequ ently in males than in females. The study authors were unable to detect microscopic tumors or lesions that would correlate with the observed clinical signs. AN had no primary effect on hematological paramete rs, except for lowered RBC counts
associated with blood loss from ulcerated tumors or nutritional anemia during the later stages of the study. The only effect of AN on urinalysis was a slight, but statistically significant increase (1.3–3.0%) in urine specific gravity noted for 300 ppm group males at five time points (45– 355 days) and females at all six time points (45–54 5 days). Significant increase in urine specific gravity was also observed in 100 ppm male and femal e rats on day 181 and day 544 (females only). The lack of significant effect in treated m ales on days 544 and 724 was attributed by Quast (2002) to higher incidence of advanced chroni c renal disease in controls that resulted in an inability to concentrate urine normally. All 300 p pm male and female rats were dead by day 724. No toxicological significant alterations were observed in clinical chemistry parameters or in absolute or relative organ weights in the few treated rats surviving at termination. Lesions of the forestomach were the most prominent nonneoplastic histopathologic effects observed in Sprague-Dawley rats (Quast, 200 2; Quast et al., 1980a). In the 1-year interim sacrifice, the only treatment-related noncancer les ion was squamous cell hyperplasia of the forestomach, which was observed in 10/10 males and 9/10 females in the 300 ppm group and 4/10 males and 7/10 females in the 100 ppm group. At 2 years, the incidence of forestomach lesions (hyperplasia and/or hyperkeratosis of the s quamous epithelium) was dose related and significantly elevated in males at ≥ 100 ppm and in females at ≥ 35 ppm; incidences were 15/80, 15/47, 44/48, and 45/48 for males and 20/80, 23/48, 41/48, and 47/48 for females in the 0, 35,

### DRAFT - DO NOT CITE OR QUOTE 130 100, and 300 ppm dose groups, respectively. Minima l progressive chronic nephropathy was also
elevated in females treated at ≥ 100 ppm; incidences were 37/80, 24/48, 37/48, and 3 8/48 for control to high-dose groups. In males, minimal pro gressive nephropathy was elevated only in the 300 ppm group. However, significant increase i n severe progressive nephropathy was observed in males in the 35 and 100 ppm groups; inc idences were 11/80, 13/47, 13/48, and 10/48 for control to high-dose groups. Gliosis of the br ain, with or without perivascular cuffing, was significantly increased in the low- and middle-dose females (8/48 and 13/48, respectively, vs. 2/80 in controls), although the incidence (5/48) di d not reach statistical significance in the highdose females. In males, it was present in one rat exposed at 100 ppm and three rats exposed at 200 ppm. A NOAEL was not identified in this drinki ng water study. A LOAEL of 4.4 mg/kgday was identified for increases in forestomach les ions, decreased survival, and gliosis in brain in female rats exposed to 35 ppm AN in drinking water. Table 4-24 summarizes incidence of nonneoplastic lesions in Sprague-Dawley rats expose d to AN in drinking water for 2 years.

Table 4-24. Incidence of nonneoplastic lesions in Sprague-Dawley rats exposed to AN in drinking water for 2 years

AN in drinking water (ppm) 0 35 100 300 Male rats Dose (mg/kg-d) 0 3.4 8.5 21.3 Forestomach hyperplasia and/or hyperkeratosis 15/80 (19%) 15/47 (32%) 44/48 (92%) a 45/48 (94%) a Kidneys—chronic progressive nephropathy Severity: minimal 10/80 (12%) 4/47 (9%) 7/48 (15%) 16/48 (33%) a moderate 10/80 (12%) 5/47 (11%) 10/48 (21%) 16/48 (33%) a severe 11/80 (14%) 13/47 (28%) a 13/48 (27%) a 10/48 (21%) Female rats Dose (mg/kg-d) 0 4.4 10.8 25.0 Forestomach hyperplasia and/or hyperkeratosis 20/80 (25%) 23/48 (48%) a 41/48 (85%) a 47/48 (98%) a Kidneys—chronic progressive nephropathy Severity: minimal 37/80 (46%) 24/48 (50%) 37/48 (77 %) a 38/48 (79%) a moderate 17/80 (21%) 13/48 (27%) 8/48 (17) 5/48 ( 10%) severe 13/80 (16%) 9/48 (19%) 1/48 (2%) 4/48 (8%) Brain—gliosis and perivascular cuffing 2/80 (3%) 8/ 48 (17%) a 13/48 (27%) a 5/48 (10%)

a Statistically significant at p < 0.05.

Source: Quast (2002).

### DRAFT - DO NOT CITE OR QUOTE 131 Cancer results The drinking water study by Quast (2002) and Quast et al. (1980a) provided evidence of the carcinogenicity of AN in male and female Spragu e-Dawley rats. Tumor findings in the 1-year sacrifices included forestomach papillomas i n males: 1/10 at 100 ppm and 7/10 at 300 ppm. In females, the occurrence was 5/10 at 30 0 ppm. Also observed after 1 year of exposure were microscopic tumors of the CNS (brain) in 2/10 males and 4/10 females at 100 ppm and 1/10 males and 2/10 females at 300 ppm. Carcinoma of Zymbal gland and benign and malignant tumors of the mammary gland, also obs erved after 1 year of exposure, were considered by the study authors to be related to tr eatment. Histopathologic examinations after 2 years of expos ure revealed statistically significant and dose-dependent increase in incidences of severa l types of tumors (Table 4-25). Squamous cell papillomas or carcinomas of the forestomach we re significantly elevated in males and females exposed at ≥ 100 ppm. Carcinomas of Zymbal gland were significa ntly increased in males at 300 ppm and in females at ≥ 35 ppm.

Table 4-25. Selected tumor incidences in response to AN administered to Sprague-Dawley rats in drinking water for up to 2 y ears

Incidence of tumor formation
Male rats Female rats Exposure concentration (ppm)
0 35 100 300 0 35 100 300 Dose (mg/kg-d) Tissue type 0 3.4 8.5 21.3 0 4.4 10.8 25.0 Astrocytomas only 1/80 8/47 a 19/48 23/48 a 1/80 17/48 a 22/48 a 24/48 a Combined astrocytomas/glial cell proliferation 1/80 12/47 a 22/48 a 30/48 a 1/80 20/48 a 25/48 a 31/48 a Tongue (papilloma or carcinoma) 1/80 2/47 4/48 5/48 a 0/80 1/48 2/48 12/48 a
Forestomach (papilloma or carcinoma) 0/80 2/47 23/48 a 39/48 a 1/80 1/48 12/48 a 30/48 a Zymbal gland (carcinoma or adenoma) 3/80 4/47 3/48 16/48 a 1/80 5/48 a 9/48 a 18/48 a Small intestine (mucous cystadenocarcinoma) ND b ND ND ND 0/80 1/48 4/48 a 4/48 a Mammary gland (malignant) ND ND ND ND 1/80 1/48 3/4 8 10/48 a Mammary gland (malignant or benign) ND ND ND ND 58/80 42/48 a 42/48 a 35/48

a Significantly different from controls ( p < 0.05), as calculated by the study authors.
b ND = not determined.

Sources: Quast (2002); Quast et al. (1980a).

### DRAFT - DO NOT CITE OR QUOTE 132 An increase in papillomas or carcinomas of the tong ue in males at 300 ppm was also considered to be related to exposure. Increases we re also observed in the incidences of malignant tumors of the mammary gland. The inciden ce of malignant or benign mammary tumors was significantly increased in the low- and high-dose females but decreased in the highdose group. Quast (2002) noted that the lower mamm ary tumor incidence in the 300 ppm group was likely due to the marked early mortality in thi s group, despite the earlier occurrence of these tumors. The incidence of mammary tumors increased considerably in controls during the latter portion of the study, when few high-dose females su rvived. Two diagnostic categories—focal or multifocal glial cell proliferation (suggestive of early tumors), and focal or multifocal glial cell t umor (astrocytomas)—were used by Quast (2002) for tumors present in the brain or spinal co rd. These diagnoses were mutually exclusive and primarily based on the size of the lesion, with glial cell proliferation a smaller-sized lesion than astrocytoma. For enumerating the astrocytomas of the CNS, the incidence of glial proliferation was combined with the incidence of as trocytomas and was elevated in both males and females in all exposed groups (Table 4-25). Distribution of astrocytomas in the various region s of nervous tissue in male and female Sprague-Dawley rats is shown in Table 4-26. No tum ors were found from 0 to 12 months in any
location in either male or female rats. As noted b y Quast (2002), the sections of cerebral cortex
contained most of the tumors because of the cortex’ s larger size. However, astrocytomas were also found in the cerebellum, brain stem, and spina l cord in male and female rats. Smaller-sized lesions (glial cell proliferation) had a distributi on similar to astrocytomas.

### DRAFT - DO NOT CITE OR QUOTE 133 Table 4-26. Histopathologic location of astrocytom as in the CNS of male Sprague-Dawley rats administered AN in drinking wat er for 2 years

Location of astrocytomas a
Male rats Female rats

Age at sacrifice Cerebral

cortex Cerebellum Brain stem Spinal

cord Cerebral

cortex Cerebellum Brain stem Spinal

cord 0 ppm
13–18 mos 0/23 0/23 0/23 0/22 0/11 0/11 0/10 0/11
19–24 mos 1/43 0/43 0/43 0/43 0/48 0/48 0/47 0/46
Terminal kill 0/7 0/7 0/7 0/7 1/20 0/20 0/20 0/20 35 ppm
13–18 mos 2/14 0/14 1/14 0/14 1/13 0/13 1/13 0/13
19–24 mos 5/26 1/26 1/25 0/26 5/30 2/29 6/30 0/30
Terminal kill 1/5 0/5 1/5 0/5 3/4 0/4 2/4 0/4 100 ppm
13–18 mos 3/16 1/16 2/16 1/16 5/19 2/20 1/19 1/19
19–24 mos 13/26 0/26 6/26 1/26 12/24 1/24 9/24 1/24
Terminal kill 2/5 0/5 0/5 0/5 0/1 0/1 1/1 0/1 300 ppm
13–18 mos 10/26 0/26 2/26 1/26 11/23 2/23 4/23 3/22
19–24 mos 11/18 2/18 4/18 2/18 8/11 2/11 3/11 2/11
Terminal kill 0/0 0/0 0/0 0/0 0/0 0/0 0/0 0/0

a No astrocytomas were found in any locations from 0 to 12 mos.

Sources: Quast (2002); Quast et al. (1980a).



### 4.2.1.2.2. Johannsen and Levinskas (2002a) and Biodynamics (19 80a): drinking water study. Johannsen and Levinskas (2002a) and Biodynamics (19 80a) carried out another 2-year drinking water study of AN in Sprague-Dawley rats. Groups o f 100 rats/sex/group were exposed to 0, 1, or 100 ppm AN (100% purity) in drinking water; as c alculated by the study authors, average daily doses were 0, 0.09, and 8.0 mg/kg-day , respe ctively, for males and 0, 0.15, and 10.7 mg/kg-day, respectively, for females. Ten rat s/sex/group were selected from these groups for interim evaluations at 6, 12, and 18 months and at study term, leaving a maximum of 70/sex/group for lifetime exposure. Although the s tudy was designed to last 24 months, because of high mortality among high-dose rats, surviving m ales were necropsied after 22 months and
females at 19 months to ensure that a sufficient nu mber of animals would be available for clinical and pathological analyses. Rats were obse rved daily for morbidity and mortality and examined and palpated weekly to detect growths. Al l rats received ophthalmoscopic examinations in the period before treatment started and again at the time of necropsy. BWs were recorded weekly for the first 14 weeks, bi weekly between weeks 16 and 26, and monthly thereafter. Food intake and water cons umption were recorded over 3-day periods

### DRAFT - DO NOT CITE OR QUOTE 134 for about 25 rats/sex/group at the same intervals a t which BWs were recorded. Ten rats/sex from each group were selected for hematological, clinica l chemical, and urinalysis examinations at 6, 12, and 18 months and at study termination (22 mont hs for males and 19 months for females). All rats, whether dying prematurely, sacrificed in a moribund condition, or sacrificed on schedule, were subjected to a gross necropsy that i ncluded preservation of 40 tissues and organs, gross lesions, and tissue masses for possible histo pathological examination. At interim and terminal necropsies, weights were recorded for sele cted organs (brain, pituitary, adrenal, gonads, heart, kidney, and liver) in 10 rats/sex/group. In terim gross necropsies were performed after 6, 12, and 18 months on 10 rats/sex/group and on the r emaining rats at termination. For the scheduled interim and terminal sacrifices, complete histopathologic examinations were conducted on 10 rats/sex from the control and 100 p pm groups; on all other rats, a limited set of tissues was examined microscopically that included potential target organs (brain, ear canal, spinal cord, and stomach) and any tissue masses obs erved at necropsy.

Noncancer results
Treatment-related noncancer effects were observed i n Sprague-Dawley rats exposed to AN for 19–22 months (Johannsen and Levinskas, 2002a ; Biodynamics, 1980a). Statistically significant increases in early deaths were observed in high-dose male and female rats after 10 months and became particularly severe during the last 5 months of the study. Reduction in survival compared with controls was not significant in high-dose males at termination (22 months) but was significant in high-dose female rats terminated at 19 months. Food and water consumption in high-dose rats was lower than in controls throughout the study. Reduction in mean BW compared with controls was observed in h igh-dose males and females throughout the study (a significant 10% reduction in males and an insignificant 8% reduction in females at term). Slight reductions in hematocrit, RBC count, and Hb values compared with controls were observed during the study in high-dose groups but w ere generally not statistically significant; 3– 6% reductions in Hb values in high-dose males were statistically significant at the 6- and 18-month interim time points. Exposure to AN had n o effect on clinical chemistry or urinalysis parameters or ophthalmoscopic examinations; there w ere no treatment-related clinical signs except for some neurological symptoms at the time o f terminal necropsy in a few rats with astrocytomas of the brain or spinal cord. The only significant treatment-related effects on organ weights were lower absolute pituitary weights in hi gh-dose males at 12 months and in females at termination. Significant increase in mean relative kidney and liver weights observed in highdose males and females were considered by the study authors to reflect the reduced BWs rather than target organ effects, since this effect did no t occur at other study intervals. Statistically significant increases in nonneoplasti c lesions related to exposure to AN included renal transitional cell hyperplasia in hig h-dose females at termination (Table 4-27). Significant increase in squamous metaplasia of the uterus was observed in high-dose females at

### DRAFT - DO NOT CITE OR QUOTE 135 12 months compared with controls (5/10 vs. 0/10), a nd in low-dose females at 18 months (3/3 vs. 2/10). This effect was not significant in high-dos e females at 18 months (4/10), and was not
observed at terminal sacrifice.

Table 4-27. Incidence of nonneoplastic lesions in Sprague-Dawley rats exposed to AN in drinking water for 2 years

AN in drinking water (ppm) 0 a 1 100
Male rats Dose (mg/kg-d) 0 0.09 8.0 Kidney transitional cell hyperplasia 1/15 2/18 0/12 Forestomach squamous cell hyperplasia
Incidence at termination b 14/19 24/26 14/15 Severity: mild 5 4 1
moderate 7 14 c 8 c

severe 2 6 c 5 c Forestomach squamous cell hyperplasia Incidence in early deaths or unscheduled sacrifices 36/46 31/37 37/42 Severity: mild 9 10 4
moderate 17 15 18 c

severe 10 6 15 c
Female rats Dose (mg/kg-d) 0 0.15 10.7 Kidney transitional cell hyperplasia 2/27 1/18 8/14 d Forestomach squamous cell hyperplasia
Incidence at termination b 39/48 40/57 17/17 Severity: mild 12 8 4
moderate 18 25 9

severe 9 7 4 Incidence in early deaths or unscheduled sacrifices 14/20 6/12 33/43 Severity: mild 4 1 1
moderate 7 2 21 d

severe 3 3 11 d

a Drinking water control.
b Males exposed for 22 mos, females for 19 mos.

c Significantly different from controls as calculated by authors ( p ≤ 0.05).
d Significantly different from controls as calculated by authors ( p ≤ 0.01).

Sources: Johannsen and Levinskas (2002a); Biodynam ics (1980a).



### In addition, the incidence of squamous cell hyperpl asia was increased in high-dose males and females at terminal sacrifice and in spontaneou s deaths in high-dose groups (Table 4-27). The severity of squamous cell hyperplasia of the fo restomach was significantly greater (characterized as moderate or severe) than in contr ols in male rats at termination after exposure to 1 or 100 ppm AN; a significant increase in sever ity in high-dose males was also observed at 12 months (not shown) but not at 18 months. Increa sed incidences in forestomach hyperplasia

### DRAFT - DO NOT CITE OR QUOTE 136 characterized as moderate or severe were also obser ved in high-dose rats of both sexes that died prematurely or were sacrificed in a moribund condit ion. A NOAEL for nonneoplastic effects was not identified in this study. A LOAEL of 1 ppm (0.09 mg/kg-day) was identified for increased severity of squamous cell hyperplasia of the forestomach in male Sprague-Dawley rats exposed to AN in drinking water for 2 years (22 mon ths).

Cancer results Significant increases in the cumulative incidences of neoplasms of the CNS, ear canal (Zymbal gland), and forestomach were observed in Sp rague-Dawley rats exposed to 100 ppm AN in drinking water for 2 years (Johannsen and Lev inskas, 2002a; Biodynamics, 1980a). Statistically significant, dose-dependent increases were observed for astrocytomas of the brain in both sexes and astrocytomas of the spinal cord in f emales. The astrocytomas varied from
discrete solid masses to localized areas of diffuse infiltrations of neoplastic cells. In addition, adenomas of Zymbal gland (ear canal) in both sexes, carcinomas of Zymbal gland in both sexes, and squamous cell papillomas of the forestomach in females were increased. Intestinal adenocarcinomas were also found in high-dose male a nd female rats (see Table 4-28).

### DRAFT - DO NOT CITE OR QUOTE 137 Table 4-28. Selected tumor incidences in Sprague-D awley rats exposed to AN in drinking water for up to 2 years

Tumor incidence a
Male rats Female rats Exposure concentration (ppm)
0 1 100 0 1 100 Dose (mg/kg-d) Tissue type

0 0.09 7.98 0 0.15 10.7
CNS Brain (astrocytomas) 2/78 3/75 23/77 b 0/79 1/80 32/77 b Spinal cord (astrocytomas) ND c ND ND 0/76 0/79 7/78 b

Total 2/78 3/75 23/77 b 0/79 1/80 39/78 b Zymbal gland
Carcinomas 1/80 0/71 14/83 b 0/79 0/75 7/78 b

Adenomas 0/80 0/71 5/83 1/79 0/75 5/78
Total 1/80 0/71 19/83 b 1/79 0/75 12/78 b

Forestomach
Carcinomas 0/78 1/78 3/77 0/80 0/79 0/79 Papillomas 3/78 2/78 8/77 1/80 4/79 7/79 b

Total 3/78 3/78 11/77 b 1/80 4/79 7/79 b

Intestine
Adenocarcinomas 0/40 0/34 2/41 0/78 0/79 2/70

a Denominators are calculated from the total number o f animals examined (as reported in Table 4 of Johan nsen and Levinskas, 2002a) minus the animals scheduled for s acrifice at 6 and 12 mos. Thus, incidences are for animals scheduled for the 18-mo, spontaneous deaths and ter minal sacrifices (22 mos for males and 19 mos for f emales). For Zymbal gland tumors in the 100 ppm male, one carcin oma and adenoma occurred in the 12-mo sacrifice; th erefore, adjustment to the denominator was only made for the 6-mo sacrifice.
b Significantly different from controls ( p < 0.05), Fisher’s exact test.

c ND = no data collected.

Sources: Johannsen and Levinskas (2002a); Biodynam ics (1980a).



### Johannsen and Levinskas (2002a) reported that most of the tumors occurred in rats after 12 months of exposure. CNS astrocytomas were not d etected at the 6- or 12-month interim sacrifices (at which about 10 rats of each gender w ere sacrificed from each group). However, brain astrocytomas and Zymbal gland carcinomas were detected in high-dose females as early as after 6 months of exposure. One each of Zymbal gla nd carcinoma, adenoma, and squamous cell
carcinoma of the forestomach was detected at the 12 -month interim sacrifice in high-dose males. This finding was consistent with findings in the ot her drinking water bioassay with SpragueDawley rats, indicating that some male and female r ats exposed to 300 ppm AN developed tumors after only 7–12 months of exposure (Quast, 2 002). Mammary gland carcinomas were
detected in female rats scheduled for the terminal sacrifice but not in male or female rats scheduled for sacrifice at 6, 12, or 18 months. In cidences of female rats (scheduled for the

### DRAFT - DO NOT CITE OR QUOTE 138 terminal sacrifice) with mammary gland carcinomas, however, did not show exposure-related increases: 13/80, 4/79, and 14/79 for the control, 1 ppm, and 100 ppm female groups, respectively.

4.2.1.2.3

. Johannsen and Levinskas (2002a) and Biodynamics (19 80b): gavage study. In parallel to the chronic drinking water study in Spr ague-Dawley rats, Johannsen and Levinskas (2002a) and Biodynamics (1980b) conducted a lifetim e study in which groups of SpragueDawley rats (100 rats/sex/group) received 0, 0.1, o r 10 mg/kg-day AN by gavage in water for 7 days/week. The doses were selected to match the daily intake levels in the drinking water study. The schedule and protocols used in the gava ge study for observations of clinical signs, measurements of food and water consumption and BW, clinical biochemistry analyses, and gross necropsy and histopathologic analyses were identica l to those in the drinking water study. Ingestion of 10 mg/kg-day AN resulted in increased mortality after 12 months and was significantly higher in males at termination and in females beginning at month 14 compared with controls. The study was terminated after 20 months of exposure because of high treatmentrelated deaths, with a decreased survival of about 30 and 50% in males and females compared with their respective controls. BWs showed a signi ficant reduction of about 6% in high-dose males compared with controls, beginning on week 12 and reaching 13% by termination; there were no BW effects in exposed females. Exposure to AN had no effect on food consumption in either sex or on water consumption in males; high-dose females had slightl y increased water consumption during the first 12 months only. Small reductions in hematocr it, Hb, and RBC counts were observed in high-dose males at 12 and 18 months and reached sta tistical significance at terminal sacrifice (hematocrit, 15%; Hb, 19%; and RBC counts, 18%). S ignificant increases in absolute mean liver weights were observed in the high-dose males and fe males and low-dose males at the 18-month interval. Relative liver weights for high-dose mal es and females were significantly increased in most intervals and might be reflective of lower BWs . Absolute and relative kidney weights of high-dose males were increased significantly at 18 months and increased insignificantly in both males and females at study term. The adrenal gland of high-dose males was the organ that showed the most significant weight increase of 43% at termination.

Noncancer results Nonneoplastic histopathological effects were observ ed in male and female SpragueDawley rats exposed to 10 mg/kg-day AN by gavage fo r 20 months (Table 4-29). A significant increase in epidermal inclusion cysts was observed in male and female rats, most notably in animals dying spontaneously. Significant increases in renal transitional cell hyperplasia were observed in high-dose females at 12-month sacrifice and in high-dose males after 18 months. In addition, there was a significant increase in the s everity of squamous cell hyperplasia of the

### DRAFT - DO NOT CITE OR QUOTE 139 forestomach in high-dose males and females. This e ffect was most noticeable among rats dying early or at scheduled sacrifices after at least 12 months. High-dose rats showed a significant elevation in the incidence of moderate or severe hy perplasia. In this gavage study, a NOAEL of 0.1 mg/kg-day and a LOAEL of 10 mg/kg-day were iden tified for increased severity of forestomach lesions (squamous cell hyperplasia) in male and female rats.

Table 4-29. Incidence of nonneoplastic lesions in Sprague-Dawley rats exposed to AN by gavage for 20 months

Dose (mg/kg-d) 0 a 0.1 10
Male rats Skin: Epidermal inclusion cysts (in spontaneous de aths) 2/59 4/68 8/56 b Kidney: Transitional cell hyperplasia (18 mos) 3/1 1 0/8 10/10 c Heart: Cardiomyopathy (18 mos) 3/11 No data 8/10 b Forestomach: Squamous cell hyperplasia
Incidence at terminal sacrifice 10/10 No data 8/10 Severity: mild 2 0
moderate 5 2

severe 3 6 Incidence in early deaths or unscheduled sacrifices 46/58 46/67 49/56 Severity: mild 18 11 2
moderate 19 26 13 c

severe 9 10 34 c
Female rats Skin: Epidermal inclusion cysts (in spontaneous dea ths) 0/10 No data 4/10 b Kidney: Transitional cell hyperplasia (12 mos) 0/10 0/1 4/10 b Heart: Cardiomyopathy (18 mos) 4/10 No data 3/10 Forestomach squamous cell hyperplasia
Incidence at terminal sacrifice 8/10 No d ata 9/10 Severity: mild 1 1
moderate 5 3

severe 2 5 Incidence in early deaths or unscheduled sacrifices 47/57 63/69 53/59 Severity: mild 12 12 0
moderate 23 38 14 c

severe 12 13 39 c

a Water vehicle control.
b Significantly different from controls as calculated by the study authors ( p < 0.05).

c Significantly different from controls as calculated by the study authors ( p ≤ 0.01).

Sources: Johannsen and Levinskas (2002a); Biodynam ics (1980a).

### DRAFT - DO NOT CITE OR QUOTE 140 Cancer results The carcinogenic effects of AN on Sprague-Dawley ra ts exposed via gavage were similar to those in the drinking water studies (Johannsen a nd Levinskas, 2002a; Biodynamics, 1980b). Significant increase in tumor incidences were obser ved in male and female rats dosed with 10 mg/kg-day and included carcinomas of Zymbal glan d, astrocytomas of the brain, and tumors of the squamous epithelium of the forestomach (papi llomas and carcinomas in males and papillomas in females) (Table 4-30). Adenocarcinom as of the intestine were also observed in high-dose male rats that died or were killed after at least 12 months of exposure. Increases in carcinomas of the mammary gland were observed in hi gh-dose females that died prematurely.

Table 4-30. Cumulative incidence of tumors in resp onse to AN administered to Sprague-Dawley rats by gavage for up to 2 years

Tumor incidence a Male rats (mg/kg-d) Female rats (mg/kg-d) Tissue type 0 0.1 10 0 0.1 10 Brain astrocytomas 2/80 0/79 16/77 b 1/80 2/78 17/80 b Spinal cord astrocytomas 0/74 0/73 1/77 0/80 0/75 1 /79 Zymbal gland papillomas 0/76 0/73 3/76 0/65 0/74 0/ 74 Zymbal gland carcinomas 1/76 0/73 10/76 b 0/65 0/74 9/74 b Zymbal gland adenomas 0/76 1/73 5/76 b 1/65 0/74 5/74
Forestomach carcinomas 0/79 0/77 18/79 b 0/79 0/79 1/79 Forestomach papillomas 2/79 6/77 19/79 b 2/79 4/79 14/79 b

Intestine adenocarcinomas 0/80 0/80 6/80 b 0/40 0/40 1/41 Mammary gland carcinomas 0/80 0/78 0/80 5/80 6/80 2 1/80 b

a Denominators are calculated from the total number o f animals examined (as reported in Table 4 of Johan nsen and Levinskas, 2002a) minus the animals scheduled for s acrifice at 6 and 12 mos; thus, incidences are for animals scheduled for the 18-mo, spontaneous death, and ter minal sacrifices (20 mos).
b Significantly different from controls ( p < 0.05), as calculated by the study authors.

Sources: Johannsen and Levinskas (2002a); Biodynam ics (1980a).



### 4.2.1.2.4. Johannsen and Levinskas (2002b); Biodynamics (1980c ). A 2-year drinking water assay was conducted in F344 rats (Johannsen and Lev inskas, 2002b; Biodynamics, 1980c). Groups of rats (100/sex/group) were given AN (100% purity) in drinking water at concentrations of 0, 1, 3, 10, 30, or 100 ppm; two groups of 100/s ex served as untreated controls. The study authors reported the equivalent average daily doses of AN as 0, 0.1, 0.3, 0.8, 2.5, and 8.4 mg/kgday for males and 0, 0.1, 0.4, 1.3, 3.7, and 10.9 m g/kg-day for females. Rats were observed twice daily for overt signs of toxicity and examine d and palpated weekly to detect growths. Ophthalmoscopic examinations were carried out befor e testing and again at the time of necropsy. BWs were recorded weekly for the first 14 weeks, bi weekly between weeks 16 and 26, and monthly thereafter. Food intake and water consumpt ion were recorded over a 3-day period at the

### DRAFT - DO NOT CITE OR QUOTE 141 same intervals that BWs were recorded for about 25 rats/sex/group for all groups. At intervals of 6, 12, and 18 months and at study termination (26 m onths for males and 23 months for females), 10 rats/sex/group from each exposed and control gro up were sacrificed for clinical pathology and microscopic evaluation. At 6, 12, and 18 months and at termination, 10 rats /sex from the 100 ppm group and 5 rats/sex from each of the control groups were sel ected for hematology, clinical chemistry, and urinalysis examinations. Lower dose group rats wer e evaluated as needed to determine possible dose-response relationships. All rats, whether dyi ng prematurely, sacrificed in a moribund condition, or sacrificed on schedule, were subjecte d to a gross necropsy that included preservation of 40 tissues and organs, all gross le sions, and tissue masses for possible histopathologic examination. At interim and termin al sacrifice, weights were recorded for selected organs (brain, pituitary, adrenal, gonads, heart, kidney, and liver) for 10 rats/sex from treated groups and 5 rats/sex from each control gro up. For the interim sacrifices, complete histopathologic examinations were conducted on 10 r ats/sex from the 100 ppm group and 5 rats/sex from the two control groups. Potential target organs (e.g., brain, ear canal, spinal cord, and stomach), gross lesions, and tissue masses were examined microscopically in all study animals. All surviving females were terminated aft er 23 months and all males after 26 months. Terminal necropsies included complete microscopic e xaminations for 10 rats/sex exposed to 100 ppm AN and 5/sex/group for the two control grou ps. Potential target organs and suspicious
lesions were examined in all animals in other dose groups.

Noncancer results
Treatment-related noncancer effects were observed i n F344 rats exposed to AN in drinking water for 2 years (Johannsen and Levinskas , 2002b; Biodynamics, 1980c). Statistically significantly early deaths ( p < 0.05), compared with controls, were observed in male and female rats exposed to 100 ppm, beginning after 14 months of exposure. A statistically significant
decrease in survival was also observed in female ra ts exposed to 30 ppm but not to 10 ppm, beginning after 18 months of exposure. Exposure to AN did not result in any overt neurological impairments or ophthalmoscopic findings. Statistically significant decrease in BWs (~12% lowe r than controls, p < 0.01) were observed in male and female rats exposed to 100 ppm AN. A statistically significant decrease in BWs of less than 5% was found in male rats exposed to 30 ppm AN and was not biologically significant. Total food consumption (g/week) was r educed compared with controls in rats exposed at 100 ppm (more prominently in female rats after week 13), but consumption on a BW basis (g/kg) for both 100 ppm male and female rats was not significantly different from that for controls. Total water consumption (mL/week) was si gnificantly lower in the 100 ppm male and female rats compared with controls. No differences in food and water consumption from controls were found for groups exposed to ≤ 30 ppm AN. Hematological analyses revealed slight

### DRAFT - DO NOT CITE OR QUOTE 142 reductions in Hb, hematocrit, and RBC counts in the 100 ppm group, beginning at 12 months, with Hb significantly lower in female rats at 12 an d 18 months (13% at 18 months). Hematocrit in 100 ppm female rats was 4% lower at 12 months. However, no statistically significant
differences from controls were noted at termination

. Serum alkaline phosphatase levels were significantl y elevated by 80 and 65% ( p < 0.05), respectively, in 100 ppm females at 18 and 23 month s. Results of clinical chemistry for the 30 and 10 ppm groups were not reported. However, t he study authors noted that female rats in these dose groups also showed significant elevation of this enzyme. A significant 33% increase in SGPT was also observed in 100 ppm female rats at 18 months but not at other intervals. The only treatment-related urinalysis finding was a sli ght increase in urine specific gravity in 100 ppm males at 18 and 26 months. No significant dose-related changes were observed for absolute organ weights; elevations in relative orga n weights (kidney, brain, liver, adrenal, testis, heart, and pituitary in females) sporadically obser ved at 100 ppm at intervals throughout the study were attributed by the study authors to lower BWs rather than target-organ toxicity. Unlike Sprague-Dawley rats exposed to AN in drinkin g water (see above, Quast [2002]),
F344 rats did not show forestomach lesions at the 6 - or 12-month sacrifices. In rats exposed for periods >1 year, treatment-related nonneoplastic ef fects were observed in the forestomach (Table 4-30) and skin. The incidence of squamous c ell hyperplasia or hyperkeratosis of the
forestomach was elevated in male and female rats ex posed to 3, 10, and 30 ppm but not to 100 ppm. Johannsen and Levinskas (2002b) suggested that, because the lesions were observed more frequently in late surviving animals, the redu ced survival in 100 ppm group may have been the reason that no significant increase was observe d for that dose group. Because these
forestomach lesions were not observed in rats exami ned during the 6- or 12-month sacrifices, no
such incidence data are listed in Table 4-31. An i ncrease in epidermal inclusion cysts of the skin, observed in 4/50 male rats treated at 100 ppm but in no other group, was also considered by the study authors to be treatment related. A NOAEL of 1 ppm (0.1 mg/kg-day) and a LOAEL of 3 ppm (0.3 and 0.4 mg/kg-day for males and females, respectively) were identified for increases in squamous cell lesions (hyperplasia and/or hyperk eratosis) of the forestomach in male and female F344 rats exposed to AN in drinking water fo r 2 years.

### DRAFT - DO NOT CITE OR QUOTE 143 Table 4-31. Incidences of nontumorous lesions in F 344 rats exposed to AN in drinking water for 2 years

AN in drinking water (ppm) 0 a 1 3 10 30 100 Male rats Dose (mg/kg-d) 0 0.1 0.3 0.8 2.5 8.4 Forestomach squamous cell hyperplasia or hyperkeratosis b 11/159 3/80 18/75 c 13/80 d 17/80 c 9/77

Foci of cellular alteration in liver 7/94 5/31 11/5 1 8/45 14/50 c 6/68 Epidermal inclusion cysts 0/61 0/12 0/12 0/11 0/17 4/50 d Chronic nephropathy, bilateral 118/149 57/58 d 62/64 c 52/54 d 57/60 d 42/62 Atrophy of seminiferous tubules, bilateral 150/172 72/75 d 68/84 64/74 78/78 c 64/87 Female rats Dose (mg/kg-d) 0 0.1 0.4 1.3 3.7 10.9 Forestomach squamous cell hyperplasia or hyperkeratosis b 4/156 2/80 16/80 c 23/74 c 13/80 c 5/74

Foci of cellular alteration in liver 1/84 2/20 4/39 d 3/49 0/40 1/70 Chronic nephropathy, bilateral 52/68 10/19 21/26 20 /29 23/26 18/50

a Drinking water control.
b Males exposed for 18–26 mos, females for 18–23+ mos ; excludes rats sacrificed at 6 or 12 mos. These i ncidences were further adjusted to exclude (from the denomina tors) rats that died between 0 and 12 mos in the st udy. Rats dying during this time period were determined from page 6 of Appendix H and Table 1 in Biodynamics (19 80c) and Table 8 in Johannsen and Levinskas (2002b). Un scheduled deaths between 0 and 12 mos in the study occurred in two female controls, two males at 3 ppm, three f emales at 10 ppm, and three males and three females at 100 ppm.

c Significantly different from vehicle control as cal culated by study authors ( p ≤ 0.01).
d Significantly different from vehicle control as cal culated by study authors ( p ≤ 0.05).

Sources: Johannsen and Levinskas (2002a); Biodynam ics (1980a).



### Other microscopic findings included increase in chr onic nephropathy and atrophy of seminiferous tubules, which were significant at 1 p pm. However, the study authors did not consider these effects to be related to treatment, but rather to be due to the sample selection procedure that only tissues showing questionable or suspicious lesions were selected for microscopic examination for the intermediate dose g roups (1–30 ppm), resulting in the selection of tissues from more aged animals.

Cancer results Increases in tumor incidences (Table 4-32) were obs erved in multiple organs, following chronic exposure of F344 rats to AN in drinking wat er (Johannsen and Levinskas, 2002b; Biodynamics, 1980c). No tumors were detected in ra ts sacrificed after only 6 months of exposure. One female rat exposed to 100 ppm for 12 months had an adenocarcinoma of the mammary gland that the study authors considered to be possibly related to treatment. Treatmentrelated tumors, appearing at the 18-month interim s acrifice, included brain astrocytomas (one/sex/group) in male and female rats exposed to 30 and 100 ppm, squamous cell papillomas of the ear canal (Zymbal gland) in 2/9 males at 100 ppm and 1/9 females at 30 ppm, and squamous cell carcinomas of the latter organ in one female at 100 ppm. AN-related neoplastic

### DRAFT - DO NOT CITE OR QUOTE 144 lesions were observed at terminal sacrifice in the brain, spinal cord, forestomach, ear canal (Zymbal gland), and mammary gland (females only). Significant dose-related elevations in astrocytomas were observed in the brains of male an d female rats exposed to 30 and 100 ppm and in the spinal cord of male rats exposed to 100 ppm (see Table 4-32). Dose-related increases in squamous cell adenomas/carcinomas of the ear can al (Zymbal gland) were observed in males exposed to 30 and 100 ppm and in females at 10–100 ppm. Increased incidences of squamous cell papillomas or carcinomas of the forestomach, o bserved in males exposed to 3 and 10 ppm and in both sexes exposed to 30 ppm, were considere d by the study authors to be likely treatment related despite the lack of a dose response. Fibro adenomas of the mammary gland were slightly increased in females treated with 10 and 30 ppm. O ther lesions considered by the study authors to be possibly treatment related included a single case of squamous cell carcinoma of the salivary gland in one male at 100 ppm and squamous cell papi llomas of the tongue in female rats (one/group) exposed to 10 and 30 ppm.

### DRAFT - DO NOT CITE OR QUOTE 145 Table 4-32. Selected tumor incidences in F344 rats exposed to AN in drinking water for 2 years

AN in drinking water (ppm) 0 a 1 3 10 30 100
Male rats b Dose (mg/kg-d) 0 0.1 0.3 0.8 2.5 8.4 Brain astrocytoma Total c Adjusted d 2/200 c 2/160 d 2/100

2/80 1/100

1/78 2/100

2/80 10/99 e

10/79 e 21/99 e

21/76 e Spinal cord astrocytoma 1/196 1/156 0/99

0/79 0/92

0/70 0/98

0/78 0/99

0/79 4/93 f

4/70 f Ear canal (Zymbal gland) squamous cell papilloma/adenoma and carcinoma 2/189 1/147 1/97

1/76 0/93

0/73 2/88

0/67 7/94 e

2/71 e 16/93 e

14/68 e Forestomach squamous cell papilloma/carcinoma 0/199 0/159 1/100

1/80 4/97 f

4/78 f 4/100 f

3/80 f 4/100 f

4/80 f 1/101

1/77 Mammary gland fibroadenoma 2/48 1/4 2/7 2/12 0/7 2/45

Mammary gland carcinoma 1/48 0/4 0/7 0/12 0/7 0/45

Female rats b Dose (mg/kg-d) 0 0.1 0.4 1.3 3.7 10.9 Brain astrocytoma 1/199 1/157 1/100

1/80 2/101

2/80 4/95

4/75 6/100 e

6/80 e 23/98 e

23/76 e Spinal cord astrocytoma 0/197 0/155 0/97

0/78 0/99

0/79 1/92

1/72 0/96

0/77 1/91

1/69 Ear canal (Zymbal gland) squamous cell papilloma/adenoma and carcinoma 0/193 0/157 0/94

0/73 2/92

0/73 4/90 e

0/70 e 5/94 e

2/73 e 10/86 e

8/62 e Forestomach squamous cell papilloma/carcinoma 1/199 1/157 1/100

1/80 2/100

2/79 2/97

2/77 4/100 f

4/80 f 2/97

2/75 Mammary gland fibroadenoma 12/65 12/156 5/14

5/80 6/14

6/80 9/16 e

8/79 10/22 f

9/80 9/49

9/73 Mammary gland carcinoma 1/65 3/156 2/14

4/80 0/14

0/80 0/16

1/78 3/22

3/80 2/49

6/73

a Drinking water control.
b Males exposed for 26 mos, females for 23+ mos.

c Total cumulative number of rats with lesion.
d The denominators for incidences excluded rats from the 6- and 12-mo sacrifices and rats that died befo re the appearance of the first tumor for each of three tum or sites: CNS, Zymbal gland, and forestomach. The termination history reports in Appendix C and the individual an imal histopathology reports in Appendix H of the Bi odynamics (1980b) report were examined to determine time of d eath and tumor occurrence for each of the F344 rats . Times of first detection of tumors were 419 d for forestomac h tumors, 495 d for CNS tumors, and 475 d for Zymba l gland tumors. Due to the limited number of mammary gland s examined in most groups, the adjusted denominator s represented the number of animals that were exposed for more than 12 mos for each group; mammary gland tumor incidences are for animals scheduled for the 18-mo and terminal sacrifices.

e Significantly different from vehicle control as cal culated by study authors (cumulative only) ( p ≤ 0.01).
f Significantly different from vehicle control as cal culated by study authors (cumulative only) ( p ≤ 0.05).

Sources: Johannsen and Levinskas (2002a); Biodynam ics (1980a).



### 4.2.1.2.5. NTP (2001). NTP (2001) evaluated the toxicity and carcinogenici ty of AN (>99% purity) given by gavage in water to B6C3F 1 

### mice (50/sex/dose) at doses of 0, 2.5, 10, and 20 mg/kg-day, 5 days/week for 2 years. Adjusted fo r discontinuous exposure (5 days/7 days), the intakes were 0, 1.8, 7.1, and 14.3 mg/kg-day. The doses were chosen based on results of the

### DRAFT - DO NOT CITE OR QUOTE 146 14-week assay described in Section 4.2.1.1. Mice w ere observed twice daily for clinical signs that were recorded on day 29, every 4 weeks, and at study termination. BWs were recorded before the start of the exposure period, then every 4 weeks, and at study termination. Five male
and five female mice were evaluated at 2 weeks and 3, 12, and 18 months for urinalysis parameters. All mice were subjected to gross necro psies and complete histopathologic
examinations.

Noncancer results Survival was significantly reduced in male and fema le mice treated with 20 mg/kg-day; 38/50, 42/50, 39/50, and 14/50 males and 39/50, 32/ 50, 39/50, and 23/50 females survived to 104–105 weeks with increasing dose. Despite a tend ency for BWs in high-dose mice to be slightly lower compared with controls after 30 week s of treatment, AN had no significant effect on terminal BWs; no treatment-related clinical sign s were observed. Exposure to AN significantly increased the incidenc es of nonneoplastic lesions in male and female mice compared with control mice (Table 4 -33). Statistically significant increases in the incidences of mild focal or multifocal epitheli al hyperplasia of the forestomach were observed in males treated with 10 or 20 mg/kg-day a nd in focal or multifocal epithelial hyperplasia of the forestomach in females treated w ith 20 mg/kg-day. The hyperplastic lesions were often accompanied by focal hyperkeratosis and occasionally associated with chronic inflammation. The incidence of hyperkeratosis (dif fuse or focal) of the forestomach was statistically significantly elevated in males treat ed at 20 mg/kg-day. AN-treated males showed a higher incidence of hyperplasia of the Harderian gl and, but only the increase observed at 10 mg/kg-day was statistically significantly differ ent from the control. No significant increase was found in treated females (Table 4-33). Statist ically significant elevations were observed in the incidences for ovarian cysts in females treated with 2.5–20 mg/kg-day and for ovarian atrophy in females treated with 10–20 mg/kg-day; fo r both ovarian lesions, the highest incidences were observed at 10 mg/kg-day. A NOAEL was not identified for noncancer effects in this gavage study. A LOAEL of 1.8 mg/kg-day (ad justed for continuous exposure) was identified for increased incidence of ovarian cysts in female mice. A NOAEL of 1.8 mg/kg-day and a LOAEL of 7.1 mg/kg-day were identified for in creased incidences of forestomach hyperplasia in male mice.

### DRAFT - DO NOT CITE OR QUOTE 147 Table 4-33. Incidence and severity of nonneoplasti c lesions in B6C3F 1 

### mice exposed by gavage to AN for 2 years

Adjusted dose (mg/kg-d) a 0 b 1.8 7.1 14.3
Males
Number of male mice examined 50 50 50 50 Forestomach hyperkeratosis, diffuse/focal 2 c (2.5) d 3 (2.0) 7 (1.7) 12 f (1.8) Forestomach epithelial hyperplasia, focal 2 (3.0) 4 (2.3) 8 e (2.0) 9 f (1.9) Harderian gland hyperplasia 1 (2.0) 4 (2.3) 7 e (3.4) 4 (2.3)
Females
Number of female mice examined 50 50 50 50 Forestomach hyperkeratosis, diffuse/focal 2 (1.5) 1 (2.0) 2 (2.0) 4 (2.0) Forestomach epithelial hyperplasia, focal, or multi focal 2 (1.5) 2 (3.0) 5 (1.8) 7 e (1.6) Harderian gland hyperplasia 5 (3.0) 4 (3.3) 6 (2.2) 8 (3.5) Ovarian atrophy 6 (3.0) 8 (3.9) 45 f (4.0) 40 f

(4.0) Ovarian cyst 12 (2.3) 20 e (2.3) 27 f (2.1) 19 e (2.1)

a Doses administered 5 d/wk.
b Vehicle control.

c Number of mice with lesion.
d Average severity grade of lesions in affected mice: 1 = minimal, 2 = mild, 3 = moderate, 4 = marked.

e Significantly different from vehicle control as cal culated by authors ( p ≤ 0.05).
f Significantly different from vehicle control as cal culated by authors ( p ≤ 0.01).

Source: NTP (2001).



### Cancer results In mice exposed to AN, treatment-related carcinogen ic effects (Table 4-34) were observed in the forestomach, Harderian gland, and, less consistently, lung and ovary of treated female mice (NTP, 2001). Histopathologic examinati on revealed significantly increased incidences of forestomach squamous cell papillomas and in overall incidence of papillomas or
carcinomas in male and female mice treated with 10 or 20 mg/kg-day. Forestomach squamous cell carcinomas alone were significantly increased in males at ≥ 10 mg/kg-day and in females at 20 mg/kg-day. Incidences of Harderian gland adenom a and adenomas or carcinomaswere significantly elevated in males at ≥ 2.5 mg/kg-day and in females at ≥ 10 mg/kg-day. The overall
incidence of alveolar/bronchiolar adenomas or carci nomas was significantly elevated in females treated at 10 mg/kg-day but not at the highest dose . Increase in benign or malignant granulosa cell tumor of the ovary was observed in females tre ated with 10 mg/kg-day AN. However, the increase was not statistically significant. Signif icant positive trends (

p ≤ 0.001) were observed in
both male and female mice for the incidences of for estomach squamous cell papilloma or carcinoma and Harderian gland adenoma or carcinoma; there was also a significant positive trend ( p = 0.029) for alveolar/bronchiolar adenoma or carcin oma in treated females. An inverse relationship between tumor latency and dose was obs erved for forestomach squamous cell papillomas or carcinomas in females and for Harderi an gland adenomas or carcinomas in males.

### DRAFT - DO NOT CITE OR QUOTE 148 Table 4-34. Incidences of selected neoplastic lesi ons in B6C3F 1 

### mice exposed by gavage to AN for 2 years

Adjusted Dose (mg/kg-d) a Control b 1.8 7.1 14.3
Males c
Number of mice examined 50 50 50 50
Forestomach Squamous cell papilloma (includes multiple) 3 4 19 d 25 d Squamous cell carcinoma 0 0 8 d 9 d Squamous cell papilloma or carcinoma 3 4 26 e 32 e Harderian gland Adenoma (includes bilateral) 5 16 d 24 d 27 d

Carcinoma 1 1 4 3
Adenoma or carcinoma 6 16 f 27 e 30 e
Females c
Number of mice examined 50 50 50 50
Forestomach Squamous cell papilloma (includes multiple) 3 6 24 d 19 d Squamous cell carcinoma 0 1 1 11 d Squamous cell papilloma or carcinoma 3 7 25 e 29 e Harderian gland Adenoma (includes bilateral) 10 10 25 d 23 d

Carcinoma 1 0 3 2
Adenoma or carcinoma 11 10 26 e 25 e Lung
Alveolar/bronchiolar adenoma or carcinoma 6 6 14 g 9 Ovary Benign or malignant granulosa cell tumor 0 0 4 1

a Doses administered 5 d/wk.
b Vehicle control.

c Number of mice with tumor.
d Significantly different from vehicle control as cal culated by authors ( p ≤ 0.01).

e Significantly different from vehicle control as cal culated by authors ( p ≤ 0.001).
f Significantly different from vehicle control as cal culated by authors ( p = 0.014).

g Significantly different from vehicle control as cal culated by authors ( p = 0.039).

Source: NTP (2001).



### 4.2.1.2.6. Gallagher et al. (1988). In a cancer bioassay, groups of 20 male Sprague-Daw leyderived CD rats were exposed to 0, 20, 100, or 500 ppm AN in drinking water for 2 years (Gallagher et al.,1988). As calculated from the re ported AN concentration and average daily drinking water consumption data, the intakes of AN were 0, 1.5, 7.1, and 28 mg/kg-day. Rats were weighed weekly, and feed intake and water cons umption were measured for 1 week each month. All rats, whether dying prematurely or sacr ificed at termination, were subjected to a

### DRAFT - DO NOT CITE OR QUOTE 149 complete gross necropsy. Tissues exhibiting gross lesions and a selection of organs (liver, stomach, adrenal, kidney, heart, brain, pituitary, and lung) were examined for histopathology. Significantly reduced survival compared with contro ls was observed in the high-dose group after 1 year of exposure but not in the other treatment groups. The last high-dose rat died shortly before the scheduled termination. BWs were significantly reduced in high-dose rats after 8 months and in mid-dose rats after 16 months; comp ared with terminal BWs of the control group, reductions of >50% at 500 ppm and >20% at 10 0 ppm were estimated from the data graph. Exposure to AN had no effect on food consum ption, but water consumption was reduced in a dose-related fashion (by 7.5, 11.3, and 30% in the low- to high-dose groups). A NOAEL of 1.5 mg/kg-day and a LOAEL of 7.1 mg/kg-day were ide ntified for reduced BW in rats exposed to AN for 2 years. This study was limited as to it s usefulness for noncancer risk assessment because few tissues were evaluated for histopatholo gy and noncancer histopathology was not reported. Gallagher et al. (1988) reported dose-related incre ases for the incidences of tumors of the forestomach and ear canal (Zymbal gland). Four of 20 high-dose rats (20%) had papillomas of the squamous epithelium of the forestomach, a tumor type not observed in the other groups. Squamous carcinomas of Zymbal gland were observed i n 1/20 (5%) mid-dose rats and 9/20 (45%) high-dose rats but not in low-dose rats or controls. This study provided evidence of the carcinogenicity of AN to the forestomach and Zy mbal gland in male rats. Limitations of the study in evaluation of AN carcinogenicity included small group sizes, lack of testing in females, and only limited tissues were evaluated in gross an d histopathological examination.

4.2.1.2.7. Bigner et al. (1986). In an interim (18-month) report of a 2-year drinkin g water study (Bigner et al., 1986), F344 rats were exposed to AN at targeted concentrations of 0 ppm (51 males and 49 females), 100 ppm (50 rats/sex), a nd 500 ppm (two subgroups, with a total of 197 males and 203 females). One group of the 500 p pm rats, 147 males and 153 females, was allocated for studies of morphology, tumor biology, and karyotyping, leaving the remaining rats for studies of comparative survival and tumor incid ences. By using reference average BWs for F344 rats in a chronic-duration study and an allome tric equation deriving drinking water consumption from BW (U.S. EPA, 1988), the average d aily doses of AN were calculated as 0, 12.9, and 64.5 mg/kg-day for males and 0, 14.8, and 74.2 mg/kg-day for females. Rats were observed twice daily for neurological signs and dea th and were weighed weekly. Complete gross necropsies were conducted on all rats. Brain s were evaluated for tumors using light and electron microscopy. The only endpoints related to noncancer effects reported for this study were mortality, BW, and clinical signs. Incomplete quantitative data were provided for mortality, which was reported to show dose-response effect in both sexes, occurring earlier in 100 and 500 ppm females than in males. A total of 215 high-dose rats died between month 6 and 18, whereas only “a few” male and female controls w ere reported to have died by month 18. No

### DRAFT - DO NOT CITE OR QUOTE 150 quantitative results were provided for the magnitud e or statistical significance of BW reductions that affected high-dose male rats by the third week and high-dose females “slightly” later. BW reductions in the mid-dose group occurred in males after 2 months and females sometime during the second year. The incidences of neurological cl inical signs (paralysis, head tilt, circling, and seizures) were dose related, affecting a total of 4 5/400 rats treated at 500 ppm, 4/100 rats at 100 ppm, and 0/100 controls exposed for 12–18 month s. The reported data were insufficient to accurately identify a NOAEL or LOAEL for noncancer effects in this study. A final report of this study was not located. In 215 rats in the 500 ppm group that died between months 6 and 18, the types of tumors frequently found included s.c. papillomas, papillom as of the forestomach, and tumors in Zymbal gland, but no incidence data were provided for thes e lesions (Bigner et al., 1986). A statistically significant increase in tumors of the brain bearing similarity to astrocytomas was observed in rats exposed to 500 ppm AN, with 49 primary brain tumors observed among the 215 rats dying between months 6 and 18; incidences in other treatm ent groups were not reported. The tumors were observed mostly in the cerebral cortex (about 75%) and also in the brain stem and
cerebellum. When the brain tumors were classified according to size, 10/49 of these tumors were larger than 5 mm, 28/49 were between 1 and 5 m m in diameter, and 11/49 were detected only microscopically. Although this study provided support for the carcinogenic effect of AN at multiple sites in rats, the lack of numerical resul ts rendered it inadequate for the purpose of quantifying cancer risk.

4.2.1.2.8. Maltoni et al. (1988, 1977). Maltoni et al. (1988, 1977) reported a cancer bioas say (designated BT203) in which groups of Sprague-Dawle y rats (40/sex) received 5 mg/kg AN by gavage in olive oil, 3 days/week for 52 weeks; a co ntrol group of 75/sex received olive oil alone on the same schedule. After the exposure period, r ats were maintained without further treatment for the rest of their natural lives (the study endi ng on week 131). Rats were examined 3 times daily for their general health status and were subj ected to a clinical examination for gross changes every 2 weeks. Rats were weighed every 2 w eeks during the first year and monthly thereafter. All rats were examined by gross necrop sy. All tissues with gross lesions and a limited set of 12 tissues/organs from each rat were examined microscopically. No statistically significant increases in tumors were observed in tr eated rats in this study. However, slight decrease in tumor latency or increase incidence wer e observed for some types of tumors identified in other studies on AN. For example, a carcinoma of Zymbal gland was noted in 1/40 exposed males (latency 84 weeks) and 1/75 cont rol females (latency 90 weeks). Papillomas
and acanthomas of the forestomach were observed in 1/40 exposed males (latency 92 weeks), 4/40 exposed females (average latency 97.5 weeks), and 1/ 75 control females (latency 54 weeks). Maltoni et al. (1977) recognized the in crease in forestomach tumors as treatment related. Gliomas (a category that includes astrocy tomas) appeared in 1/40 treated females

### DRAFT - DO NOT CITE OR QUOTE 151 (latency of 33 weeks), 2/75 control females (averag e latency 104 weeks), and 1/74 control males (latency 98 weeks). The major limitation of this s tudy as a cancer bioassay was the relatively short exposure period and the small number of anima ls in each group. The dose was also low for a single exposure group study.

4.2.1.2.9. Friedman and Beliles (2002); Litton Bionetics (1992 ). In a three-generation reproductive toxicity study in Sprague-Dawley rats, Friedman and Beliles (2002) and Litton Bionetics (1992) provided further evidence of the p ossible carcinogenicity of AN (methods and reproductive/developmental findings of this study a re presented in Section 4.3.2). In this study, 15 males and 30 females per dose level (F0 parents) were exposed to 0, 100, and 500 ppm AN in drinking water for 100 days prior to mating for 6 d ays. As calculated by the study authors, the concentrations were equivalent to doses of 0, 11, a nd 37 mg/kg-day for males and 0, 20, and 40 mg/kg-day for females. A subset of F0, F1, and F2 females underwent two cycles each of breeding, then were held for a further 20 weeks aft er weaning of the second litter prior to
termination. Considering each generation separately, F1b female breeders in the 500 ppm group showed statistically significant increased incidenc es of brain and Zymbal gland tumors, while
increased incidences of tumors in F0 or F2b female breeders in the 100 or 500 ppm groups compared with controls were consistent with the F1b responses, but not statistically significant (Table 4-35). These were relatively small groups, however, with low power to detect responses as high as 10% statistically significant. Across a ll of the generations, there was a statistically significant increasing trend in both tumor types, s upporting the conclusion that exposure to AN for up to 51 weeks at 100 or 500 ppm in drinking wa ter was associated with increased tumor incidence in female Sprague-Dawley rats.

### DRAFT - DO NOT CITE OR QUOTE 152 Table 4-35. Incidence of tumors in female Sprague- Dawley rats exposed to AN in drinking water for up to 46 weeks

Tumor incidence in rats Brain astrocytomas Zymbal gland

Exposure concentration (ppm)
0 100 500 0 100 500 Dose (mg/kg-d) Generation 0 20 40 0 20 40
F0 0/19 1/20 2/24 0/19 0/20 2/24
F1b 0/20 1/19 4/17 a 0/20 2/19 3/17 a
F2b 0/20 1/20 1/20 0/20 0/20 3/20
Total 0/59 b 3/59 7/61 a 0/59 b 2/59 8/61 a

a Significantly different from controls ( p < 0.05), as calculated by the authors.
b Statistically significant by Cochran-Armitage trend test, p < 0.01.

Sources: Friedman and Beliles (2002); Litton Bione tics (1992).



### Table 4-36 summarizes the noncancerous effects obs erved in chronic oral studies of AN
in rats and mice. Table 4-37 summarizes the cancer ous effects observed in chronic oral studies
of AN in rats and mice.

Table 4-36. Summary of chronic oral toxicity studi es of AN: noncancer effects in rats and mice

Strain number/sex Exposure

route/ duration a Doses Effects NOAEL/ LOAEL a References Comments
Rats
F344 100/sex/group

Unexposed controls = 200/sex Drinking

water/ 2 yrs M: 0, 0.1, 0.3,

0.8, 2.5, 8.4 mg/kg-d; F: 0, 0.1, 0.4, 1.3, 3.7, 10.9 mg/kg-d Squamous cell

hyperplasia/ hyperkeratosis of the forestomach; decreasedsurvival in highdose groups, increase in epidermal inclusion cysts of the skin NOAEL =

0.1 mg/kg-d; LOAEL = 0.3 mg/kg-d (M) 0.4 mg/kg-d (F) Johannsen and

Levinskas (2002b); Biodynamics (1980c) 10 rats/sex/group

were taken from exposed and control groups for interim sacrifice at 6, 12, and 18 mos

### DRAFT - DO NOT CITE OR QUOTE 153 Table 4-36. Summary of chronic oral toxicity studi es of AN: noncancer effects in rats and mice

Strain number/sex Exposure

route/ duration a Doses Effects NOAEL/ LOAEL a References CommentsSpragueDawley 100/sex/group Drinking

water: 22 months (M); 19 months (F) M: 0, 0.09,

8.0 mg/kg-d; F: 0, 0.15, 10.7 mg/kg-d Squamous cell

hyperplasia of the forestomach, decreasedsurvival in highdose groups, reduction in absolute/relative pituitary weight (F) LOAEL =

0.09 mg/kg-d (M) Johannsen and

Levinskas (2002a); Biodynamics (1980a) 10 rats/sex/group

were taken from exposed and control groups for interim sacrifice at 6, 12, and 18 mos

SpragueDawley 100/sex/group Gavage/

20 months 0, 0.1,

10 mg/kg-d Squamous cell

hyperplasia of the forestomach, small reductions in hematocrit, Hb, and RBCcount in highdose males, increase in absolute/relative liver weight in high-dose groups NOAEL =

0.1 mg/kg-d; LOAEL = 10 mg/kg-d Johannsen and

Levinskas (2002a); Biodynamics (1980b) 10 rats/sex/group

were taken from exposed and control groups for interim sacrifice at 6, 12, and 18 mos

SpragueDawley 48/sex/group; Controls: 80/sex Drinking

water/ 2 yrs M: 0, 3.4, 8.5,

21.3 mg/kg-d; F: 0, 4.4, 10.8, 25.0 mg/kg-d Hyperplasia/

hyperkeratosis of the forestomach, reduced survival and BW, minimal progressive nephropathy, gliosis of the brain LOAEL =

4.4 mg/kg-d (F) Quast (2002);

Quast et al. (1980a)

F34450/sex lowdose; 197 males and 203 females high-dose. Controls: 51-males and 49-females: Drinking

water/ lifetime M: 0, 12.9,

64.5 mg/kg-d; F: 0, 14.8, 74.2 mg/kg-d Neurological

signs No data Bigner et al. (1986) Doses calculated

using default assumptions (U.S. EPA, 1988); noncancer effects not evaluated in the study

### DRAFT - DO NOT CITE OR QUOTE 154 Table 4-36. Summary of chronic oral toxicity studi es of AN: noncancer effects in rats and mice

Strain number/sex Exposure

route/ duration a Doses Effects NOAEL/ LOAEL a References Comments
Mice
B6C3F 1 50/sex/group Gavage/

2 yrs 0, 2.5, 10,

20 mg/kg-d, 5 d/wk; continuous
exposureadjusted doses: 0, 1.8, 7.14, 14.3 mg/kg-d Reduced survival

in high dose
group; hyperkeratosis/ hyperplasia of the forestomach; ovarian cysts and atrophy (F) LOAEL:

1.8 mg/kg-d (F); NOAEL = 1.8 mg/kg-d; (M) LOAEL = 7.1 mg/kg-d (M) NTP (2001)

a M = male; F = female.



### Table 4-37. Summary of chronic oral toxicity studi es of AN: cancer effects in rats and mice

Strain number/sex Exposure

route/ Duration Doses a Effects a References Comments
Rats
F344 100/sex/group

Unexposed controls = 200/sex Drinking

water/ 2 yrs Males: 0, 0.1,

0.3, 0.8, 2.5,and 8.4 mg/kgd; females: 0, 0.1, 0.4, 1.3, 3.7, and 10.9 mg/kg-d Males: increase in brain

astrocytomas and Zymbal gland tumors, increase in forestomach tumors; females: increase in brain astrocytomas, Zymbal gland tumors, and forestomach
tumors Johannsen and Levinskas (2002b); Biodynamics (1980c) 10 rats/sex/group

were taken from exposed and control groups for interim sacrifice at 6, 12, and 18 months

SpragueDawley 100/sex/group Drinking

water/ 22 months (M); 19 months (F) Males: 0, 0.09,

and 8.0 mg/kgd; females: 0, 0.15, and 10.7 mg/kg-d Significant increases in

incidences of tumors of the CNS, Zymbal gland, and forestomach Johannsen and Levinskas (2002a); Biodynamics (1980a) 10 rats/sex/group

were taken from exposed and control groups for interim sacrifice at 6, 12, and 18 monthsSpragueDawley 100/sex/group Gavage/

20 months 0, 0.1, and

10 mg/kg-d Increase in brain

astrocytomas, and tumors of Zymbal gland, forestomach, and intestine. Carcinomas of the mammary gland in females Johannsen and Levinskas (2002a); Biodynamics (1980b) 10 rats/sex/group

were taken from exposed and control groups for interim sacrifice at 6, 12, and 18 monthsSpragueDawley 48/sex/group; Controls: 80/sex Drinking

water/ 2 yrs Males: 0, 3.4,

8.5, and 21.3 mg/kg-d; females: 0, 4.4, 10.8, and 25.0 mg/kg-d Increases in CNS tumors,

squamous cell papillomas or carcinomas of the forestomach, carcinomas of Zymbal gland, as well as benign and malignant tumors of the mammary gland Quast (2002); Quast et al. (1980a)

### DRAFT - DO NOT CITE OR QUOTE 155 Table 4-37. Summary of chronic oral toxicity studi es of AN: cancer effects in rats and mice

Strain number/sex Exposure

route/ Duration Doses a Effects a References Comments
F34450/sex lowdose; 197 males and 203 females high-dose. Controls: 51 males and 49 females Drinking

water/ lifetime M: 0, 12.9, and

64.5 mg/kg-d; females: 0, 14.8, and 74.2 mg/kg-d Tumors found included brain

astrocytomas, Zymbal gland tumors, an d papillomas of the forestomach Bigner et al. (1986) Doses calculated

using default assumptions (U.S. EPA, 1988); no tumor incidence data were provided

SpragueDawley 40/sex Control: 75/sex Gavage/

3 ds/week for 52 weeks; rats maintained without
treatment until natural death (study ended week 131) 0, 5 mg/kg in

olive oil Treatment-related increase in

forestomach tumors Maltoni et al. (1977) Study limitations:

single dose, short exposure period, and small number of animals in each
group

SpragueDawley 20 M/group Drinking

water/2 yrs 0, 1.5, 7.1, and

28 mg/kg-d Increase in tumors of the

forestomach and Zymbal gland Gallagher et al. (1988) Study limitations:

small group size, lack of testing in females, and only limited tissues were examined for histopathology.SpragueDawley 15 M/group, 30 F/group Drinking

water/ 46 weeks(threegeneration reproduction/ developmental study) 0, 11,

37 mg/kg-d (M); 0, 20, and 40 mg/kg-d (F) Increase in incidences of

brain and Zymbal gland
tumors Friedman and Beliles (2002); Litton Bionetics (1992) Study suggested

increased susceptibility to the carcinogenicity of AN from early-life exposure (see Section 4.8.1).

Mice
B6C3F 1 50/sex/group Gavage/

2 yrs 0, 2.5, 10, and

20 mg/kg-d, 5 d/wk, continuous
exposureadjusted doses: 0, 1.8, 7.14, and 14.3 mg/kg-d Increase in tumors of the

forestomach and of Harderian gland in males and females NTP (2001) Overall incidence of alveolar/bronchiolar adenomas or carcinomas was significantly elevated in females at 10 mg/kg-d, but not at 20 mg/kg-d.

a M = male; F = female.

### DRAFT - DO NOT CITE OR QUOTE 156 4.2.2. Inhalation Exposure
4.2.2.1. SubchronicSubchronic Studies The only subsubchronic study of inhalation effects of AN in animals was a comparative study of the neurotoxicity of nitriles (Gagnaire et al., 1998). Groups of 12 male Sprague-Dawley rats were exposed (whole body) to AN vapor at conce ntrations of 25, 50, or 100 ppm, 6 hours/day, 5 days/week for 24 weeks. A control g roup of 10 male rats was exposed to filtered air. BWs were measured weekly. Following 4, 8, 12 , 16, 20, and 24 weeks of exposure and an 8-week recovery period (week 32), rats were evaluat ed for the same electrophysiological parameters that were tested in parallel experiments on orally exposed rats (see Section 4.2.1.1). As in the companion study, electrophysiological tes ting was performed at least 16 hours after daily exposure (waiting period was 48 hours for wee kends). Electrical stimulation of the tail nerve was used to assess MCVs, SCVs, ASAPs, and AMA Ps. No mortality was observed during the treatment period, but, during the first and sec ond week of the recovery period, 2/12 rats in the 100 ppm group died and one rat each in the 100 and 25 ppm groups was euthanized in week 31 because of tumors in the neck. BW gain in the 100 ppm group was significantly lower than in controls in weeks 4, 8, 16, and 21–24, such that th e BW was 11% lower at the end of week 24. Rats exposed to AN did not develop weakness of the hind limbs or disturbances in gait. After 1 or 2 weeks of exposure, rats exposed at ≥ 50 ppm exhibited clinical signs of gross toxicity (wet fur and excessive salivation but not hyperacti vity). Excessive salivation was attributed by the study authors to a cholinomimetic effect of AN. Exposure to AN had no effect on neurophysiological parameters during the first 8 we eks and no effect on the AMAP at any time during the study. Statistically significant concen tration-dependent SCV reductions of ~9% compared with controls were observed in the 100 ppm group from weeks 12–24 (Table 4-38). In week 12, an ~7% reduction was observed in the 50 ppm group, and in week 24 the SCV was reduced by 5% in the 25 ppm group (not biologically significant) and by >8% in the 50 and 100 ppm groups. The ASAP was significantly reduced by 14.5–20% in the 50 ppm group and by 29–30% in the 100 ppm group from weeks 16–24. Afte r recovery in week 32, a 21% reduction in ASAP persisted in the 100 ppm group. Sporadic r eductions in MCV were observed in 100 ppm rats beginning in week 16 (11% reduction) b ut were not concentration dependent in week 24 or after recovery in week 32. A LOAEL of 2 5 ppm was identified for reductions in SCV in rats exposed to AN by inhalation for 24 week s. A NOAEL was not identified.

### DRAFT - DO NOT CITE OR QUOTE 157 Table 4-38. Effect on SCV in male Sprague-Dawley r ats exposed to AN via inhalation for 24 weeks

SCV (m/s) a Exposure (weeks) Recovery Exposure (ppm) 0 12 16 20 24 32
0 35.0 ± 0.5 49.7 ± 0.8 49.9 ± 1.0 50.3 ± 0.5 53.3 ± 1.0 53.4 ± 0.6
25 35.2 ± 0.4 48.2 ± 0.7 47.8 ± 1.0 50.2 ± 0.7 50.5 ± 0.8 b 51.8 ± 0.8
50 35.3 ± 0.6 46.3 ± 0.8 c 48.0 ± 1.1 50.5 ± 0.6 49.1 ± 0.5 d 51.3 ± 1.0
100 35.8 ± 0.5 45.3 ± 1.0 c 46.2 ± 0.7 b 48.1 ± 0.7 b 48.4 ± 1.0 d 50.4 ± 0.8

a Values are means ± SDs (n = 12 for treated, n = 10 for controls).
b Statistically significant compared with controls ( p < 0.05) as calculated by the study authors.

c Statistically significant compared with controls ( p < 0.01) as calculated by the study authors.
d Statistically significant compared with controls ( p < 0.001) as calculated by the study authors.

Source: Gagnaire et al. (1998).



### 4.2.2.2. Chronic Studies Two chronic inhalation bioassays in rodents were a vailable: Dow Chemical (1992a)/ Quast et al. (1980b) and Maltoni et al. (1988, 1977 ).

4.2.2.2.1. Dow Chemical (1992a) and Quast et al. (1980b). Dow Chemical (1992a) and Quast et al. (1980b) evaluated the effects of AN in Sprag ue-Dawley rats (100/sex/group) exposed by inhalation at concentrations of 0, 20, or 80 ppm (0 , 43.4, or 173.6 mg/m 3 

### ) 6 hours/day, 5 days/week for 2 years. Additional groups of 7 an d 13 rats/sex/group were exposed and sacrificed at 6 and 12 months, respectively. BWs w ere determined 10 times during the first 3 months and monthly thereafter. Rats were observe d daily for clinical signs and mortality, and beginning after 6 months, were examined for palpabl e masses and dental condition. Moribund animals or those with ulcerating tumors were sacrif iced and subjected to gross necropsy. Hematology and urinalysis examinations were conduct ed on 10 rats/sex/group on days 174/175, 365/366, 616/617, and 727/727 for males/females, re spectively. The hematology determinations of male rats was also conducted on day 183 to verif y observations made on day 174. Clinical chemistry analyses were conducted on 10 rats/sex/gr oup on days 176, 372, and 735. Water consumption was determined for representative male and female rats in each group for the first 8 months. At terminal sacrifice, all rats received an ophthalmologic examination and necropsy during which organ weights were recorded for brain, heart, liver, kidneys, and testes. Complete histologic examinations were carried out on all rat s in the control and 80 ppm groups at terminal sacrifice. More than 80% of rats in the 20 ppm gro up were examined for gross lesions, and 23 selected organs and all tissues with grossly rec ognized tumors were collected for histopathology examination. Because there were sig ns of upper respiratory tract irritation in the nasal turbinate, about 10 rats/sex/group from the t erminal sacrifice were evaluated by light

### DRAFT - DO NOT CITE OR QUOTE 158 microscopy. In addition, because of brain lesions observed during drinking water studies, nine sections from various regions of the CNS of all rat s were examined microscopically.

Noncancer results Inhalation exposure to AN resulted in significant c oncentration-related noncancer effects compared with controls (Quast et al., 1980b). Stat istically significant ( p < 0.05) decreases in survival with respect to controls were observed in males after 6 months of exposure at 80 ppm and in females after 10 months of exposure at 80 pp m or 22 months at 20 ppm. The numbers of rats surviving at termination (out of 100/sex) were 18, 14, and 4 males and 22, 9, and 1 females in the control, 20 ppm, and 80 ppm groups, respecti vely. BWs were decreased by about 10–15% in male and female rats after 9 months of exposure to 80 ppm AN. A significant decrease of less than 10% was also observed in 20 ppm female rats. By the end of the study, BWs in 20 and 80 ppm females were not significantly different from t hose in controls. Hb and RBC counts were significantly lower (by ~9%) in rats exposed to 80 ppm for 4– 8 months but not later. However, the study authors considered these changes to be a secondary effect of reduced growth, tumor formation, and hemo rrhage, resulting from exposure and not due to bone marrow toxicity. Statistically significant increases in water consumption were observed in both exposed groups of male and female rats duri ng the first 6 months of the study and were consistent with slightly decreased urine specific g ravity measured in 80 ppm groups during that period. No significant effects on urinalysis param eters were observed after 6 months. Exposure to AN had no consistent significant effect on clini cal chemistry parameters or results of ophthalmoscopic examinations. A significant elevat ion (about 26%) in blood urea nitrogen (BUN) was observed in the 20 and 80 ppm female rats on day 176. SGPT was also elevated by 57% in the 80 ppm females at that time. However, n o significant findings of these parameters were found upon subsequent evaluation at a later ti me interval. Hence, Quast et al. (1980b) considered these changes as secondary responses and not indications of direct renal or hepatotoxicity from AN exposure. Significant incre ases in relative weights of brain, heart, and testes of male rats exposed at 80 ppm were consider ed by the study authors to be a consequence
of the reduction in BW. Gross pathological examinations found statistically significantly findings in the nasal turbinates, lungs, teeth (malocclusion), and liver of the 80 ppm rats. Gross observation of male rats indicated significant increase in minimal chro nic nephropathy in the 80 ppm group (40/100 vs. 24/100). Significant increase in pneum onia, atelectasis, or edema was found in the 20 and 80 ppm males (14/100, 27/100, and 30/100 for 0, 20, and 80 ppm groups, respectively). Gross observations of nontumorous changes included enlarged liver in female rats, with incidence of 2/100, 9/100, and 7/100 in 0, 20, and 80 ppm groups, respectively. (The increased incidence in the 20 ppm group was statistically sig nificant.)

### DRAFT - DO NOT CITE OR QUOTE 159 Statistically significant increases in the incidenc e of histopathologic lesions of the nasal turbinates were observed in all rats exposed at 80 ppm and most rats in the 20 ppm group. These effects were considered by the study authors to be the result of irritant effects of AN (Table 4-39). These lesions appeared in rats sacri ficed after at least 13 months (usually 19 months) of exposure. These inflammatory and deg enerative changes included hyperplasia, flattening, focal erosion, and squamous metaplasia of the respiratory epithelium and hyperplasia of mucus secreting cells. Flattening of the respir atory epithelium in females and hyperplasia of mucus-secreting cells in males were both significan tly increased at the 20 ppm exposure level.

Table 4-39. Incidence of histopathological lesions of the nasal turbinates in Sprague-Dawley rats exposed to AN via inhalation fo r 2 years

Concentration (ppm)
0 20 80 Response Incidence
Males Suppurative rhinitis 0/11 1/12 5/10 a Hyperplasia of respiratory epithelium 0/11 4/12 10/ 10 a Focal erosion of mucous lining 0/11 0/12 4/10 a Squamous metaplasia of the respiratory epithelium 0 /11 1/12 7/10 a Hyperplasia of mucus-secreting cells 0/11 7/12 a 8/10 a
Focal inflammation 0/11 1/12 1/10 Flattening of the respiratory epithelium 0/11 2/12 3/10
Females Suppurative rhinitis 1/11 0/10 2/10 Hyperplasia of respiratory epithelium 0/11 2/10 5/1 0 a Focal erosion of mucous lining 0/11 1/10 1/10 Squamous metaplasia of the respiratory epithelium 0 /11 2/10 5/10 a Hyperplasia of mucus-secreting cells 0/11 2/10 8/10 a
Focal inflammation 2/11 6/10 7/10 a Flattening of the respiratory epithelium 1/11 7/10 a 8/10 a

a Statistically significant (

p < 0.05), as calculated by the study authors.

Source: Quast et al. (1980b).



### Increase in acute suppurative pneumonia was observe d in the lungs of the 80 ppm male rats during the 7–12-month time interval. A nonsig nificant increase was also observed in the 20 ppm group. Other histopathological observations included an i ncrease in the incidence of gliosis and perivascular cuffing in the brain of high-dose rats (either sex) and, in males only, minimal chronic focal progressive nephrosis and formation o f keratinized cysts in the thyroid gland (Table 4-40). Incidences of focal necrosis of the liver were increased in 20 and 80 ppm female

### DRAFT - DO NOT CITE OR QUOTE 160 rats. The incidence of AN-related hyperplasia and hyperkeratosis of the nonglandular portion of the stomach did not achieve statistical significanc e in either sex but was statistically significant ( p < 0.05) by Fisher’s exact test when the data were c ombined. There were concentration-related
increases in the incidences of several lesions that were secondary to other effects of AN exposure (numerical data not provided here). These included hepatocellular atrophy without fatty changes and atrophy of mediastinal fat in 80 ppm male rats, attributed by the study authors to the
decreased feed intake of the rats at the end of the study, and extramedullary hematopoiesis of the spleen in females, a consequence of the reductions in RBC and Hb counts. An increase in lymphoid hyperplasia in males at 80 ppm was interpr eted by the study authors to be secondary to tumors of the ear canal and inflammatory changes in the nasal turbinates. A NOAEL was not identified in this study. A LOAEL of 20 ppm was id entified for increased lesions of the nasal turbinates (hyperplasia of mucus-secreting cells in males and flattening of the respiratory epithelium in females) and focal necrosis in liver of female rats exposed to AN vapor for 2 years.

Table 4-40. Incidence of dose-related noncancerous histopathological lesions in Sprague-Dawley rats exposed to AN via inhalation for 2 years

Concentration (ppm)
0 20 80 Response Incidence
Males Focal nephrosis (progressive) 22/100 24/100 48/100 a Minimal chronic nephropathy 24/100 21/100 40/100 a Thyroid cyst 4/95 9/97 13/96 a Gliosis and perivascular cuffing (brain) 1/100 2/99 7/99 a Acute suppurative pneumonia 0/100 4/100 10/100 a Pulmonary changes 15/100 26/100 a 20/100 Hyperplasia of the nonglandular epithelium (stomach ) 8/98 7/100 16/99
Females Gliosis and perivascular cuffing (brain) 0/100 2/10 0 8/100 a
Focal necrosis in liver 3/100 16/100 a 10/100 a Vasculization of spinal myelin (minimal) 42/100 67/ 100 a 47/100 Hyperplasia of the nonglandular epithelium (stomach ) 2/99 3/99 7/97

a Statistical significance (

p < 0.05), as calculated by the study authors.

Source: Quast et al. (1980b).



### Cancer results In rats chronically exposed to AN vapor, there were significant increases in tumors at multiple sites, several of which also had been affe cted in oral exposure bioassays (Quast et al., 1980b). In males and females exposed to 80 ppm AN, there were increased incidences of

### DRAFT - DO NOT CITE OR QUOTE 161 astrocytomas of the brain as well as glial cell pro liferation that was considered an earlier stage in the progression to astrocytomas. The incidence dat a in Table 4-41 combine the incidences of astrocytomas and glial cell proliferation. The inc idence of CNS tumors was also significantly increased in females exposed to 20 ppm AN and insig inificantly increased in males exposed to 20 ppm AN. Carcinomas of Zymbal gland were signifi cantly elevated in the 80 ppm rats of both sexes. Other tumor increases observed in the 80 pp m groups were squamous cell papillomas or carcinomas in the tongue and carcinomas of the inte stinal tract of males and adenocarcinomas of the mammary gland in females. An increase was obse rved in forestomach tumors in 80 ppm male rats and nasal turbinate tumors in 80 ppm fema le rats. Both types of tumors were considered by the study authors to be treatment rel ated, although the increase was not statistically significant. Table 4-41 presents inc idences of AN-induced target organ-specific tumor formation. All tumors were found in exposed rats that died or were sacrificed after 12 months of exposure, with the exception of one ma le rat with a CNS tumor and three female rats with mammary gland adenocarcinomas that died b etween 7 and 12 months.

Table 4-41. Cumulative incidence of tumors in Spra gue-Dawley rats exposed to AN via inhalation for up to 2 years

Males (ppm) Females (ppm) Tissue 0 20 80 0 20 80
All brain/CNS a 0/96 4/93 22/82 b 0/93 8/99 b 20/89 b Zymbal gland 2/96 4/93 11/82 b 0/93 1/98 11/89 b

Intestinal tract 4/96 3/93 17/82 b Not increased Mammary gland (adenocarcinomas) 0/100 0/100 1/100 9 /93 8/98 20/99 b Mammary gland (total, benign and malignant) 4/100 5 /100 7/100 88/100 95/100 85/100 Forestomach (squamous cell papilloma) 1/98 1/100 4/ 99 0/99 0/99 1/97 Tongue 1/95 0/14 7/82 b 0/96 0/9 1/91 Nasal turbinate (carcinoma in respiratory epithelial region) Not increased 0/11 0/98 2/10

a Incidence data include all brain/CNS tumors (astroc ytomas and glial cell proliferation). Male tumor i ncidence data are from Tables 22, 25, and 26 of the Quast et al. (1980b) report; female tumor incidence data are fro m Tables 31, 34, and 35 in the same report. For all incidence d ata, the denominators excluded rats dying earlier t han 12 mos in the study. These data were ascertained from Tables 22, 25, 31, 34, and 35 in the original study repor t by Quast et al. (1980b).
b Significantly different from controls ( p < 0.05) as calculated by the study authors.

Sources: Dow Chemical (1992a); Quast et al. (1980b ).



### An apparent decrease in the incidence of tumors of the pituitary, adrenals, thyroid, and pancreas of male and female treated rats, and teste s of males, was observed when compared with
controls.

### DRAFT - DO NOT CITE OR QUOTE 162 4.2.2.2.2. Maltoni et al. (1988, 1977). The following studies by Maltoni et al. (1988, 1977 ) were cancer bioassays that did not investigate nonn eoplastic effects in rats exposed to AN vapor. These study authors reported a number of experiment s in which Sprague-Dawley rats were exposed to AN by inhalation. In the first (designa ted BT201 by the authors), 30 rats/sex/group were exposed to 0, 5, 10, 20, and 40 ppm 4 hours/da y, 5 days/week for 52 weeks; the animals then were allowed to complete their natural life sp ans, with the final deaths occurring in week 136 (Maltoni et al., 1977). Rats were examined 3 t imes weekly for general health status and subjected to a clinical examination for gross chang es every 2 weeks. Rats were weighed every 2 weeks during the exposure period and monthly ther eafter. All rats were subjected to gross necropsy. Histopathologic examinations were conduc ted on all gross lesions and a selection of about 12 organs and tissues, including the Zymbal g lands, interscapular brown fat, salivary glands, tongue, lungs, liver, kidneys, spleen, stom ach, intestine, bladder, and brain. Exposure to AN had no significant effect on surviv al or BWs in male or female rats. A moderate increase in gliomas, forestomach tumors, Z ymbal gland carcinomas, and mammary tumors was found in the treated group. However, in creases in the incidences of these tumors in exposed rats were not statistically significant and could be due to the small number of animals in each dose group. For example, gliomas were found i n 20 and 40 ppm males at 1/30 and 2/30, respectively, and not in controls and other exposur e groups. The average latency of the gliomas was shorter at the higher concentration (63.5 vs. 8 4 weeks). Forestomach papillomas and acanthomas were found in males at 0/30, 1/30, 2/30, and 3/30 for 0, 5, 10, and 40 ppm, respectively. In females, forestomach tumor incide nces were 0/30, 1/30, 2/30, and 1/30 for the 0, 5, 10, and 20 ppm groups. The average latency o f forestomach tumors ranged from 103 to 124 weeks. Zymbal gland carcinomas were also found at 1/30 in the 10 ppm group for male and female and 1/30 for the female 20 ppm group. No Zy mbal gland carcinomas were found in the control and other dose groups. Moreover, a possible treatment-related effect of AN in the mammary gland of females was observed, as indicated by the following inciden ces of benign or malignant tumors in relation to exposure level: 5/30 (controls), 10/30 (5 ppm), 7/30 (10 ppm), 10/30 (20 ppm), and 7/30 (40 ppm) (Maltoni et al., 1977). Slight discr epancies in the incidence of tumors of the mammary gland were reported for controls and highes t-exposed females in a subsequent report of this study (Maltoni et al., 1988). In the later study, the incidence of tumors in control females was listed as 20%, an incidence of 6/30, whereas th at of highest-concentration females was listed as 26.7%, an incidence of 8/30. In the later repor t, taking both sexes together, the incidences of encephalic gliomas were 3/60 and 2/60 in the 40 and 20 ppm groups, respectively, and none in the control and lower-dose groups. Although this c ancer study was consistent with other studies
in the identification of tumor sites associated wit h exposure to AN, it was limited in that the exposure concentrations were too low, the number of animals per group was too small, and the exposure duration was too short to result in statis tically significant increases in specific tumor

### DRAFT - DO NOT CITE OR QUOTE 163 types. However, this study demonstrated that rats with less-than-lifetime exposure and allowed to recover to their natural life span developed the same tumor types as rats with lifetime exposure
to AN. The later report by Maltoni et al. (1988) describe d two additional lifetime exposure experiments in which Sprague-Dawley rats were expos ed to AN by inhalation beginning during the gestation period. In the first experiment (des ignated BT4003), 54 adult pregnant females, beginning on gestation day 12, were exposed to 60 p pm AN for 4 hours/day, 5 days/week for 7 weeks and then 7 hours/day, 5 days/week for 97 we eks. A group of 60 unexposed adult females served as controls. Gestation was permitte d to proceed normally and the offspring were exposed on the same schedule as the dams. The expo sed offspring included 67 males and 54 females, whereas the controls were 158 males and 149 females. Overall, there was a statistically significant tre atment-related increase in the percentage of dams with malignant tumors at all sites (37 vs. 15%). Increased incidences in exposed dams compared with controls were observed for several si tes, but none of these was statistically significant: Zymbal gland carcinomas (5.5 vs. 1.7% ), mammary gland carcinomas (5.5 vs. 3.3%), benign or malignant mammary gland tumors (69 vs. 40%), extrahepatic angiosarcomas (1.8 vs. 0%), and encephalic gliomas (5.5 vs. 0%). No hepatomas were observed in exposed or unexposed dams. These site-specific results are su mmarized in Table 4-42.

Table 4-42. Comparison of carcinogenic effects of chronic exposure to AN at 60 ppm starting either in utero or in adulthood, in Sprague-Dawley rats

Percent with tumor

Stage during
exposure Exposure

protocol Sex a Number

of rats at start b Brain

tumors (encephalic gliomas) Zymbal

gland carcinomas Hepatomas Malignant
mammary tumors Extrahepaticangiosarcomas Chronic c F 54 5.5 5.5 0.0 5.5 1.8 Adult only Unexposed

controls F 60 0.0 1.7 0.0 3.3 0.0

Chronic M

F 67 54 16.4

18.5 14.9 c

1.8 7.5

1.8 0.0

16.7 d 4.4

5.5 e

Subchronic d M

F 60 60 5.0

3.3 6.7

1.7 1.7

0.0 0.0

6.7 5.0

1.7 Starting at GD 12 Unexposed

controls M

F 158 149 1.3

1.3 1.3

0.0 0.6

0.0 1.9

5.4 0.6

0.0

a F = female; M = male.
b Animals were allowed to live until spontaneous deat h.

c Chronic: 4 hrs/d, 5 d/wk for 7 wks (starting durin g gestation), followed by 7 hrs/d for 97 wks.
d Statistically significantly higher than correspondn g control incidence, p < 0.05.

e Subchronic: 4 hrs/d, 5 d/wk for 7 wks (starting du ring gestation), followed by 7 hrs/d for 8 wks.

Source: Maltoni et al. (1988).

### DRAFT - DO NOT CITE OR QUOTE 164 In contrast, chronically exposed male and female o ffspring showed statistically significant increases in the incidences of specific types of tumors: malignant tumors of the mammary gland in females (16.7 vs. 5.4%; p < 0.05), extrahepatic angiosarcomas in females (5.5 vs. 0%; p < 0.05), hepatomas in males (7.5 vs. 0.6%; p < 0.05), Zymbal gland carcinomas in males (14.9 vs. 1.3%; p < 0.01), and encephalic gliomas (16.4% in males and 18.5% in females vs. 1.3% for controls of both sexes; p < 0.01) (see Table 4-42). Higher responses in the exposed offspring at these sites relative to the dams sugge sts some early-life susceptibility to AN carcinogenity. These results are discussed further in Section 4.8.1. The second exposure experiment (BT4006) involving g estational exposure of SpragueDawley rats started with the same exposure conditio ns as for experiment BT4003, except that exposure of the offspring (127 males and 114 female s) ended after 15 weeks (Maltoni et al., 1988). Exposure in this group of offspring was for 4 hours/day, 5 days/week for 7 weeks starting on GD 12, followed by 7 hours/day, 5 days/week for 8 weeks. All animals were kept under observation until spontaneous death, at which time they were examined for the presence of tumors. The control group of offspring was the one used in experiment BT4003 (158 males and 149 females). There was a statistically significan t increase in the total incidence of malignant tumors in exposed offspring compared with controls for both males (31.7 vs. 17.1%, p < 0.05) and females (35.0 vs. 17.4%, p < 0.01). Increases in the following tumors were ob served when compared with controls: Zymbal gland tumors in mal es and females (4.2 vs. 0.7%); extrahepatic angiosarcomas in males (5.0 vs. 0.6%); encephalic g liomas in males and females (4.2 vs. 1.3%); and hepatomas in males (1.7 vs. 0.6%) (see Table 4- 42). However, these increases were not statistically significant.

4.3. REPRODUCTIVE/DEVELOPMENTAL STUDIES—ORAL AND I NHALATION
In contrast to the extensive information on cancer and noncancer effects of AN in experimental animals and exposed human populations, there are comparatively few data that address the reproductive and developmental toxicity and teratogenic action of AN.

4.3.1. Studies in Humans There have been some preliminary translated report s of surveys of the reproductive history of women occupationally exposed to AN in ch emical factories in China. While these studies pointed to a possible link between occupati onal exposure to AN and adverse effects on pregnancy, in some cases, there was insufficient in formation in the reports to assess the validity of these claims. However, there are studies with u sable data. As described in Section 4.1.2.2, Dong and Pan (1995) provided data on exposure and r eproductive outcomes in 150 male and 106 female workers employed at a chemical fiber pla nt. These subjects, routinely exposed to AN concentrations ranging from 0.53 to 15.5 mg/m 3 

### (0.24–7.1 ppm), were compared with
110 male and 121 female workers who had not been ex posed to AN. The results of the study

### DRAFT - DO NOT CITE OR QUOTE 165 were divided into two sections, one dealing with a comparison of the reproductive outcome for female employees, exposed vs. unexposed, and the se cond comparing the reproductive outcome of the wives of exposed male employees to that of t he wives of unexposed male controls. In the former case, there were few differences in reproduc tive performance between exposed females and controls (see Table 4-21 for details), although the incidence of stillborn fetuses in the exposed group was significantly greater than in con trols (5/112 vs. 0/124). However, it should be noted that there was a statistically significant age difference between the groups (29.36 ± 5.12 in exposed females vs. 20.68 ± 4.05 i n female controls). The wives of exposed male workers at the plant had poorer reproductive o utcomes than the wives of male controls, even though they were significantly younger than th eir counterparts. For example, there were differences in the incidence of live births as a pr oportion of the total number of pregnancies (159/168 vs. 113/113), spontaneous abortions (8/168 vs. 1/113), threatened abortions (5/168 vs. 1/113), stillborn fetuses (4/168 vs. 0/113), and st erility (9/150 vs. 2/110). These data suggested a potential AN-related impact on the sperms and repro ductive performance of exposed males. An elevated incidence of complications in pregnanc y was reported also by Li (2000) in 379 female workers exposed to an average AN concent ration of 7.5 ppm for ≥ 1 year. When compared with 511 unexposed controls, exposed subje cts had a higher rate of overall complications (20.8 vs. 7.14%) and premature delive ries (11.62 vs. 4.72%). Exposed subjects were subdivided to create a category where both par tners had been exposed to AN. Overall rates of complications, premature delivery, overdue deliv ery, and deficiency were greater than in cases where only the female partner was exposed. In another Chinese study, Wu et al. (1995) reporte d statistically significant increases in the incidence of pernicious vomiting, anemia, prete rm delivery, and birth defects in 477 females exposed to AN in the workplace compared with 527 co ntrols. The epidemiological report and follow-up by Czeize l et al. (2000, 1999) examined the environmental distribution of congenital abnormalit ies in 30 settlements within a 25 km radius of an AN factory, drawing on data from the Hungarian C ongenital Abnormality Registry covering 46,326 infants born between 1980 and 1996. A numbe r of time-space-specific clusters of abnormalities were identified among the subjects, t he most striking of which was the incidence of pectus excavatum in the community of Tata betwee n 1990 and 1992. This effect was
associated with an OR of 78.5 and a 95% CI of 8.4–7 29.6. Other clusters of congenital abnormalities in the vicinity of the factory were u ndescended testis in the community of Nyergesujfalu between 1980 and 1983 (OR = 8.6, CI = 1.4–54.3) and at Esztergom between 1981 and 1982 (OR = 4.2, CI = 1.3–13.5) and clubfoo t in the Tata community between 1980 and 1981 (OR = 5.5, CI = 1.5–20.3). As set forth in Section 4.1.2.2, the relationship between the findings of clusters of
abnormalities and AN is uncertain because there are no exposure data in the report (Czeizel et al., 2000, 1999). Consequently, it is not known by how much the mothers of affected infants

### DRAFT - DO NOT CITE OR QUOTE 166 were exposed to the compound if at all. Furthermor e, when the incidence of these and other
abnormalities was considered for infants born throu ghout the duration of the study, there were no overall increased incidences of congenital abnormal ities within the study area compared with infants born throughout Hungary. The study authors stated that there was a technolo gical change at the AN factory in 1984 that resulted in greater environmental protection, implying that releases of the compound to the
environment were less after 1984 than before the ch ange. This suggested that the cluster of pectus excavatum obtained at Tata between 1990 and 1992 was unlikely to have been due to AN exposure. However, the high incidence of undescend ed testis in Nyergesujfalu between 1980 and 1983 may have been an environmental phenomenon, because the region-wide incidence of this congenital abnormality appeared to decrease wi th increasing distance from the factory. In general, however, it was difficult to draw conclusi ons about a link between maternal exposure to AN and the incidence of congenital abnormalities fr om the data in this study because of a lack of exposure data. Ivanescu et al. (1990) reported lower serum testos terone level in male workers exposed to AN in a chemical factory (see Section 4.1.2.2.2). Xu et al. (2003) performed conventional sperm anal ysis according to WHO guidelines and investigated DNA strand breakage and sex chromo some aneuploidy in spermatozoa of 30 AN-exposed workers compared with 30 unexposed co ntrols. The mean concentration of AN at exposure sites was reported to be 0.8 ± 0.25 mg/ m 3 

### (0.37 ppm). Sperm density was significantly lower in the exposed group (75 × 10 6 

### /mL) than in the control group (140 × 10 6 

### /mL). Sperm number per ejaculum was 205 × 10 6 

### in the exposed group, significantly lower than the
280 × 10 6 

### spermatozoa in the control. However, there were n o significant differences between the groups in semen volume, sperm motility, viabili ty, or morphology. Xu et al. (2003) used single cell gel electrophoresis (comet assay) to mo nitor the incidence of DNA strand breakage of sperm cells. The rate of comet sperm nuclei was 28 .7% in the exposed group, significantly higher than in the control group (15.0%). Mean com et tail length was 9.8 μ m in exposed
workers but 4.3 μ m in control workers. The frequency of sex chromos ome aneuploidy in sperm cells was analyzed using fluorescence in situ hybri dization (FISH). Sex chromosome disomy was found to be 0.69% in the exposed group, signifi cantly higher than 0.35% in controls. XY-bearing sperm was the most common sex chromosome disomy, with an average rate of 0.37% in exposed vs. 0.20% in controls. XX- and YY -bearing sperm accounted for an additional 0.09 and 0.23% of sperm in exposed vs. 0.05 and 0.1 0% in controls, respectively. Xu et al. (2003) concluded that AN exposure affected semen qu ality among occupationally exposed persons by the induction of DNA strand breakage and sex chromosome nondisjunction.

### DRAFT - DO NOT CITE OR QUOTE 167 4.3.2. Studies in Animals
4.3.2.1. Oral Studies Assessments of reproductive/developmental effects of AN in orally exposed animals are derived from standard toxicity assays in rats and m ice, standard developmental toxicity assays in female rats, and a three-generation reproductive to xicity assay in male and female rats.

4.3.2.1.1. Standard toxicity assays: reproductive organ patho logy. As described in Section 4.2.1, standard 2-year oral toxicity assays in rats revealed no evidence for increased reproductive histopathology in males or females exp osed to AN at doses as high as 8–25 mg/kgday (Johannsen and Levinskas, 2002a, b; Quast, 2002 ; Biodynamics 1980a, b, c; Quast et al., 1980a). In addition, there was no evidence for adv erse effects of AN on functional reproductive parameters (sperm morphology, estrous cycle) or the histology of reproductive organs in male
B6C3F 1 

### mice treated with AN by gavage 5 days/week at 20 m g/kg-day or in females at 40 mg/kg-day for 14 weeks (NTP, 2001). In this sub chronic study, the weights of the left cauda epididymides were significantly elevated compared w ith controls in male mice exposed to 10 and 20 mg/kg-day, but this effect was not consid ered biologically significant in the absence of histopathology. In the companion 2-year gavage ass ay (NTP, 2001), no reproductive histopathology was observed in male mice treated 5 days/week with AN at doses as high as 20 mg/kg-day, but effects were observed in females (Table 4-33). The incidence of ovarian cysts was significantly elevated at 2.5, 10, and 20 mg/kg -day, and the incidence of atrophy of the ovary increased at 10 and 20 mg/kg-day. Atrophy wa s severe and was characterized by lack of histologically evident follicle and corpus luteum d evelopment with a predominance in interstitial tissue. The lowest dose of 2.5 mg/kg-day in this s tudy was identified as the LOAEL for ovarian cysts and atrophy.

4.3.2.1.2. Developmental toxicity assays

. 

### Dow Chemical (1992b) and Murray et al. (1978) eval uated developmental effects in pregnant female Sprague-Da wley rats (29–39/group) that received 10, 25, or 65 mg/kg AN by gavage in water on GDs 6–15; an additional group of 43 controls received water alone. Dams were observed daily for clinical signs and weighed on GDs 6, 10, 16, and 21. Food and water consumption were monito red at 3-day intervals on GDs 6–21, at which point all animals were sacrificed and materna l liver weights were recorded. Among the reproductive parameters evaluated were the numbers and positions of live, dead, and resorbed fetuses and the number of implantation sites. Deve lopmental toxicity was evaluated by the weight, sex ratio, and crown-rump length of the fet uses. One-third of the fetuses in each litter
were evaluated for visceral malformations and soft tissue abnormalities; the rest were examined
for skeletal alterations. Maternal toxicity of AN was most evident in the hi gh-dose group. Systemic effects observed only at this dose included a single matern al death on GD 6, an increase in clinical signs

### DRAFT - DO NOT CITE OR QUOTE 168 (hyperexcitability and excessive salivation) during the dosing period, BW gain reduced 46% compared with controls by GD 15 (22% by GD 21), wat er consumption significantly increased by an unspecified amount on GDs 6–20, and a statist ically significant 11% increase in absolute (but not relative) liver weight compared with contr ols. Food consumption was significantly reduced by an unspecified amount compared with cont rols in high- and mid-dose dams on GDs 6–8. At necropsy, most (number not specified) dams dosed with 65 mg/kg-day and 3/33 dams dosed with 25 mg/kg-day displayed a thick ening of the nonglandular portion of the stomach. Pregnancy rate was significantly decrease d among dams given 65 mg/kg-day AN, with only 20 of 29 dams producing litters. Uterine stai ning revealed implantation sites in four additional dams. A NOAEL for maternal toxicity was identified as 10 mg/kg-day AN, and 25 mg/kg-day was the LOAEL for hyperplasia of fores tomach. Exposure to AN had no statistically significant ef fect on the average numbers of implantations/dam, live fetuses/litter, or resorpti ons/litter; the average sex ratio of litters was no t reported. At 65 mg/kg-day, there were statisticall y significant reductions in fetal BW (by 7.4%) and crown-rump length (by 1.8%) compared with contr ols. The high-dose group also showed a significant increase in external malformations (sho rt tail in 6/17 litters and short trunk in 3/17 litters); there was also a significant increas e in skeletal malformations (missing vertebrae) (Table 4-43). The defect ranged in severity from t he absence of a single lumbar vertebra to the
absence of all sacral and lumbar vertebrae and most thoracic vertebrae. Although the incidence of malformations at 25 mg/kg-day was not statistica lly significant (Table 4-43), a minimal LOAEL of 25 mg/kg-day was identified for fetal malf ormation in Sprague-Dawley rats. The NOAEL for fetal toxicity was 10 mg/kg-day.

### DRAFT - DO NOT CITE OR QUOTE 169 Table 4-43. Incidence of fetal abnormalities among litters of SpragueDawley rats following maternal exposure to AN on GD s 6–15

AN (mg/kg-d) Type of malformation 0 10 25 65 Number of fetuses affected/number of litters examin ed
External and skeletal malformations 443/38 388/35 3 12/29 212/17
Visceral malformations 154/38 135/35 111/29 71/17

Number of fetuses (litters) affected
External malformations Short tail 1 (1) 0 (0) 2 (2) 8 (6) a Short trunk 0 (0) 0 (0) 0 (0) 3 (3) a Imperforate anus 0 (0) 0 (0) 0 (0) 2 (2)
Visceral abnormalities Right side aortic arch 0 (0) 0 (0) 1 (1) 1 (1) Missing kidney, unilateral 1 (1) 0 (0) 0 (0) 1 (1) Anteriorly displaced ovaries 0 (0) 0 (0) 1 (1) 1 (1 )
Skeletal malformations Missing vertebrae 1 (1) 0 (0) 2 (2) 8 (6) a Missing two vertebrae and two ribs 7 (1) 0 (0) 7 (2 ) 0 (0) Hemivertebrae 0 (0) 0 (0) 0 (0) 0 (0)

Total malformed 8 (2) 0 (0) 10 (4) 8 (6) a

a Significantly different from controls ( p < 0.05), as determined by the study authors.

Source: Murray et al. (1978).



### Behavioral teratogenicity of AN was examined in th e progeny of pregnant Wistar rats (15/group) that received 0 or 5 mg/kg-day AN by gav age on GDs 5–21 (Mehrotra et al., 1988). Dams were weighed at intervals, and food and water intakes and the length of gestation were recorded. At parturition (postnatal day [PND] 0), litters were culled to four males and four females. On PND 1, pups were sexed and examined fo r gross external anomalies; litters with fewer than two/sex were rejected. Eight pups from four litters were examined for behavioral abnormalities, including tests for spontaneous loco motion and passive avoidance. Excised brains of 21-day-old pups were assayed for biogenic amines (noradrenaline, dopamine, and 5-hydroxytryptamine) and for the activities of Na + 

### ,K + 

### -adenosine triphosphatase (ATPase), monoamine oxidase, and acetylcholinesterase. Exposure to AN at 5 mg/kg-day had no significant e ffect on BW or food and water intakes in dams or on reproductive parameters such as gestational length, number of viable offspring, or pup sex ratio. No AN-induced effects were observed on postnatal morphological development, pup BWs, developmental indices (eye op ening or incisor eruption), or tests of neurological impairment (righting reflex, cliff avo idance, and grip strength). The levels of biogenic amines were significantly altered in speci fic brain regions as a result of exposure.

### DRAFT - DO NOT CITE OR QUOTE 170 Levels of 5-hydroxytryptamine were increased by 32% in the pons medulla and decreased by 44% in the corpus striatum and 30% in the hippocamp us. Levels of noradrenaline were decreased by 40% in the pons medulla and increased by 81% in the hippocampus. Gestational exposure to AN resulted in a statistically signific ant 49% reduction in brain levels of monoamine oxidase in 21-day-old pups; levels of acetylcholine sterase and Na + 

### ,K + 

### -ATPase were not significantly affected. The biological significanc e of the enzyme and neurotransmitter changes was unclear, given that no treatment-related behavi oral effects were observed. However, Mehrotra et al. (1988) noted that alterations in th e levels of biogenic amines may become more prominant after prolonged exposure or exposure to h igher doses of AN. In a study comparing developmental toxicities of a liphatic nitriles in vitro and in vivo, Saillenfait and Sabaté (2000) administered a single dose of 0 or 100 mg/kg AN by gavage in olive oil to groups of four pregnant Sprague-Dawley rats on GD 10. Dams were sacrificed on GD 12, and the numbers of uterine implantation site s and fetuses with heartbeats were recorded.
Viable fetuses were examined for defects of the all antois, trunk, and misdirected caudal extremity (left-sided), which the investigators had found to be typical in embryos exposed to sodium cyanide. Maternal effects of all of the nit riles (including AN) included increases in clinical signs (piloerection, prostration, and/or t remors) and unspecified maternal BW loss between GDs 10 and 12. AN exposure had no effect o n the numbers of implants/litter or live embryos/litter, but significantly increased the inc idence of overall poor and abnormal development and the incidence of misdirected allant ois or allantois, trunk, and caudal extremity misdirected (Table 4-44). The study authors sugges ted that maternal production of the metabolite cyanide may have contributed to the deve lopmental toxicity of AN since the characteristic defects that occurred in embryos exp osed to cyanide were found in AN-exposed embryos. The single applied dose of 100 mg/kg is a LOAEL for maternal and fetal effects.

Table 4-44. Morphological alterations in GD 12 fet uses of Sprague-Dawley rats exposed to 100 mg/kg AN on GD 10

Group (number of litters examined)

Response Control (n = 4) 100 mg/kg (n = 4) Implants/litter 13.25 ± 1.71 13.75 ± 0.96 Live embryos/litter 13.0 ± 1.83 12.5 ± 1.0 Total embryos examined 52 50 Allantois, trunk, and/or caudal extremity misdirect ed Embryos affected/embryos examined 0/52 13/46 a
Litters affected/litters examined 0/4 3/4

a Significantly different from controls ( p < 0.01) as calculated by the reviewers (Fisher’s ex act test).

Source: Saillenfait and Sabaté (2000).

### DRAFT - DO NOT CITE OR QUOTE 171 4.3.2.1.3. Reproductive toxicity assay. Friedman and Beliles (2002) and Litton Bionetics (1 992) conducted a three-generation reproductive study in Sprague-Dawley rats (groups of 15 males and 30 females) exposed to 100 or 500 ppm AN in drinkin g water for 100 days before mating. Groups of 10 male and 20 female controls received u ntreated drinking water. As calculated by the study authors, the concentrations were equivale nt to average doses of 0, 11, and 37 mg/kgday for males and 0, 20, and 40 mg/kg-day for femal es. The calculated average doses, averaged across sexes, were 0, 16, and 39 mg/kg-day. Rats w ere observed daily, especially for signs of neurotoxicity (e.g., abnormal gait). Water consump tion in the F0 generation was measured twice a week, food intake was measured weekly, and BWs we re recorded every 2 weeks. After 100 days of exposure, rats were paired for mating f or 6 days; females not bred after 6 days were mated to another proven breeding male from the same exposure group. The offspring (F1a) of the first mating were examined on PNDs 0, 4, and 21 . Litters were culled to 10 pups on PND 4 to achieve an equal sex ratio. Litter BWs were rec orded on PND 4 and individual pup weights
were recorded on PND 21. Two weeks after removal o f the F1a offspring, F0 females were remated to produce the F1b litter, and those not us ed in breeding F1a were also mated to produce F1b pups to ensure a sufficient number of offspring for the F2 generation, although these animals should have been discarded according to the origina l study design. The original study design stipulated discarding F1a pups (those not scheduled for breeding) at weaning, but, because of high mortality in the 500 ppm group, they were reta ined to ensure sufficient time-mated females to use as foster mothers (one-half of each high-dos e litter was fostered onto untreated females). All F0 males used for breeding were discarded after the second mating, and those not used in breeding were discarded when the F1a litter were we aned. At weaning (21 days), one male and one female from the unfostered F1b litter (or from the F1a litter, if needed) were selected as potenti al breeders for the F2 generation. All F1 offspring exposed to AN were checked daily for m ortality, and necropsies were performed on
all animals either found dead or killed in a moribu nd condition. The F0 dams and females not producing a litter were exposed for an additional 2 0 weeks after weaning the F1b pups. After that period, they were sacrificed and the sciatic n erve, gastrocnemius muscle, brain, and gross lesions were examined for histopathology. F1a and F1b rats were sacrificed in week 95 of the study and necropsied for the examination of papillo mas in the stomach and intestines. The protocol for the subsequent generations (F1b parent s and F2a and F2b offspring; F2b parents and F3a and F3b offspring) was as described for the fir st generation. F2 females, after an additional 20 weeks of exposure following the weaning of the F 3b litters, were necropsied, and sciatic nerve, gastrocnemius muscle, brain, stomach, and gr oss lesions were evaluated for histopathology. F3b rats (10/sex) in the control a nd 500 ppm groups were randomly selected for histologic examination. The following discussion of results does not inclu de cancer data from this study, which were presented separately in Section 4.2.1.2. In F 0 parents, BWs were lower than controls after

### DRAFT - DO NOT CITE OR QUOTE 172 4 weeks of exposure to 500 ppm, the reduction reach ing 22% in males and 17% in females by week 10. This BW reduction was accompanied reducti on in food intake by ~18% in 500 ppm males and 8% in 500 ppm females for the first 10 we eks. Water consumption was reduced in males and females by about 50% at the high dose and 20–25% at the low dose for the first 10 weeks. Reduced water consumption and possibly B Ws may have been a result of reduced palatability of treated water. Exposure to AN had no effect on the incidence of neurological or other clinical signs, male or female fertility indi ces, or the duration of mating or gestation of F0 parents. Compared with controls, no significant changes in f ertility index or gestational index were observed in any of the exposed generations (Ta ble 4-45) (Friedman and Beliles, 2002; Litton Bionetics, 1992). However, poor fertility a mong controls for the F1b (50–60%) and
F2b (60–70%) parents might have limited the capability of this study to detect differences in fertility between control and treated rats (Table 4 -45). The durations of mating and gestation were also unaffected, except the mating duration of F2b rats for F3a generation. Significant decreased viability and lactation indices were obse rved in the 500 ppm F0 parents for the F1a generation, due to the deaths of pups between 1 –4 and 5–21 days, respectively. Significant decreases in viability index were also observed in 100 and 500 ppm F0 parents for the F1b generation and in 500 ppm F2b parents for the F 3a generation (Table 4-45). In addition, decreases of about 10–40% in pup weights were obser ved in the F1a, F1b, F2a, F2b, F3a, and F3b generations in the 500 ppm groups (Table 4-46). Overall, the results identified a drinking water concentration of 100 ppm (16 mg/kg-day) as a minimal reproductive toxicity LOAEL for decrease in lactation index in F2a generations. Al though no effects on fertility were observed in this three-generation study, poor fertility among c ontrols in F1b and F2b parents might have limited the sensitivity of this assessment. The st udy also identified a LOAEL of 100 ppm for reduced viability in F0 parents.

### DRAFT - DO NOT CITE OR QUOTE 173 Table 4-45. Group-specific reproductive indices in three generations of Sprague-Dawley rats receiving AN in drinking water

Male a,b Female c,d Generation/group Fertility index Gestation index e Viability index f Lactation index g F0 parents for F1a
Control 10/10 18/20 18/18 185/186 138/150 100 ppm 8/10 16/20 16/16 197/201 139/150 500 ppm 10/10 16/20 16/16 166/177 h 95/143 h F0 parents for F1b
Control 10/10 16/20 16/16 186/186 137/150 100 ppm 10/10 17/20 17/17 182/202 h 132/139 500 ppm 13/15 22/28 22/22 99/109 h 87/99 F1b parents for F2a
Control 5/10 10/20 10/10 107/109 91/91 100 ppm 7/10 11/20 11/11 116/124 95/104 h 500 ppm 8/10 14/20 14/14 133/140 107/114 h F1b parents for F2b
Control 6/10 10/20 10/10 101/101 82/82 100 ppm 5/10 8/20 8/8 93/97 70/73 500 ppm 8/10 14/20 14/14 138/138 123/123 F2b parents for F3a
Control 6/10 14/20 14/14 161/161 128/131 100 ppm 9/10 13/20 13/13 157/158 124/124 500 ppm 10/10 15/20 15/15 157/166 h 134/135 F2b parents for F3b
Control 9/10 14/20 14/14 170/176 106/108 100 ppm 10/10 15/20 15/15 198/198 117/119 500 ppm 10/10 17/20 17/17 170/178 115/125

a Doses in males: 0, 11, or 37 mg/kg-d for 0, 100, o r 500 ppm as calculated by the study authors.
b Fertility index in males = number of males producin g a litter/number mated.

c Doses in females: 0, 20, or 40 mg/kg-d for 0, 100, or 500 ppm, as calculated by the study authors.
d Fertility index in females = number of pregnant fem ales/number mated.

e Gestation index = number of litters born/number of pregnant females.
f Viability index = number of pups that survived to P ND 4/number of pups born alive.

g Lactation index = number of pups surviving to weani ng/number of pups alive on PND 4.
h Significantly lower than controls ( p < 0.05), as calculated by the study authors.

Sources: Friedman and Beliles (2002); Litton Bione tics (1992).

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Table 4-46. Group-specific pup weights in three ge nerations of SpragueDawley rats receiving AN in drinking water

Weight (g) Generation-concentration D 4 D 21 (males)
F1a-control 11 42 F1a-100 ppm 10 40 F1a-500 ppm 9 a 28 a
F1b-control 10 39 F1b-100 ppm 9 36 F1b-500 ppm 10 34 a
F2a-control 11 39 F2a-100 ppm 10 39 F2a-500 ppm 9 a 30
F2b-control 11 53 F2b-100 ppm 10 46 F2b-500 ppm 9 30 a
F3a-control 10 43 F3a-100 ppm 9 43 F3a-500 ppm 8 a 30 a
F3b-control 10 50 F3b-100 ppm 10 47 F3b-500 ppm 8 a 32 a

a Significantly different from controls ( p < 0.05), as calculated by the study authors.

Sources: Friedman and Beliles (2002); Litton Bione tics (1992).

4.3.2.1.4. Male exposure reproductive toxicity studies

. 

### Tandon et al. (1988) evaluated reproductive toxicity in male CD-1 mice that received 0, 1, or 1 0 mg/kg-day AN by gavage in saline for 60 days. The testes of six mice/group were examined h istopathologically, and homogenates of pooled testes (four testes) in each group were assa yed for the activities of sorbitol dehydrogenase (SDH), acid phosphatase, LDH, glucose-6-phosphatase dehydrogenase, and β -glucuronidase. Exposure to AN decreased the epididymal sperm count by 21 and 45% at the low- and high-dose group, respectively. However, the decrea se was statistically significant ( p < 0.05) only with the 10 mg/kg-day group. Histopathologica l examination of the testes did not reveal changes in the low-dose group. In high-dose mice, degenerative changes were seen in 40% of seminiferous tubules. In addition, the testes of m ice dosed with 10 mg/kg-day showed a 12% increase in the activity of LDH, a 22% decrease in the activity of SDH, a 37% increase in the activity of β -glucuronidase, and a 16% decrease in the activity of acid phosphatase compared with controls. AN exposure had no effect on the ac tivity of testicular glucose-6-phosphatase dehydrogenase. The study authors suggested that th e changes in the activities of LDH and SDH were related to the AN-induced degeneration of germ inal epithelium. In this study, a NOAEL of

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1 mg/kg-day and a LOAEL of 10 mg/kg-day were identi fied for the toxicological effects of AN
on the testes of male CD-1 mice. In a range-finding acute toxicity study for a domi nant lethal assay, groups of 10 male F344 rats received 45, 60, 68, 75, or 90 mg/kg-day AN by gavage in 0.9% saline daily for 5 days (Working et al., 1987). Rats were observed for a t otal of 42 days from the first administration. No deaths were observed in groups receiving 45 or 6 0 mg/kg-day. In the higher dose groups, the study was terminated early on account of mortality: 40% at 68 mg/kg-day (terminated on day 6), 30% at 75 mg/kg-day (terminated on day 4), and 30% at 90 mg/kg-day (terminated on day 2). As a result of this range-finding study, 60 mg/kg-d ay was selected as the maximum tolerated dose for the dominant lethal assay. In this assay, groups of 50 male F344 rats received AN by gavage at 0 or 60 mg/kg-day in 0.9% saline for 5 da ys. BWs of males were recorded three times during the week of treatment and then weekly during the mating period of 10 weeks; males were caged with a different female each week for 6 days. A transient reduction in mean BW (~4%) compared with controls was observed in rats on trea tment days 3 and 5 and on the fourth posttreatment day; BW gain in treated rats was equivale nt to controls beginning the second week of observation. AN exposure in males had no effect on the incidence of pre- or postimplantation losses, indicating a negative result in the dominan t lethal assay. AN also had no effect on the fertility of exposed males in any postexposure week

.

4.3.2.2. Inhalation Exposure Information about reproductive/developmental toxic ity in animals exposed to AN by inhalation comes from a standard chronic toxicity a ssay in rats, developmental toxicity assays in rats, and a dominant lethal assay in male mice.

4.3.2.2.1. Standard toxicity assays

. As described in Section 4.2.2.2, no reproductive histopathology was observed in male or female Sprag ue-Dawley rats that were exposed to AN at concentrations as high as 80 ppm 6 hours/day, 5 day s/week for up to 2 years (Dow Chemical Co., 1992a; Quast et al., 1980b).

4.3.2.2.2. Developmental toxicity assays. 

### Haskell Laboratory (1992a) and Murray et al. (1978) evaluated developmental toxicity in groups of 30 pr egnant Sprague-Dawley rats exposed (whole body) to 0, 40, or 80 ppm AN vapor for 6 hours/day on GDs 6–15. The parameters examined were the same as those for the oral exposure study by these authors described in Section 4.3.2.1. Inhalation exposure to 40 or 80 ppm AN did not resu lt in deaths, changes in appearance, gastric thickening, or increase in terminal liver weight in dams. Maternal BW gain was significantly reduced during GDs 6–15 by 47% in the 40 ppm group and by 58% in the 80 ppm group (a reduction of about 20% in both groups for GDs 6– 21). Both exposure groups exhibited significant (unspecified) decreases in food consump tion on GDs 6–9 (but not later intervals) and

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increases in water consumption on GDs 9–20. In thi s study, a NOAEL for maternal effects was not identified, but a LOAEL of 40 ppm was identifie d for reduced BW gain in dams. Gestational exposure to AN had no significant effec t on any of the reproductive parameters (pregnancy rates, numbers of implantatio ns, live fetuses, or resorptions) and no effect on fetal BW or crown-rump length measurements. Fur thermore, no single major malformation occurred at significantly higher incidence in AN-ex posed rats vs. controls. However, as shown in Table 4-47, there was an increase in the inciden ce of total major malformations when they were considered collectively ( p < 0.06) for the high-dose group (present in 6/35 l itters). Malformations observed in litters of 80 ppm group i ncluded short tail, missing vertebrae, short trunk, omphalocele, and hemivertebra. In this stud y, a NOAEL of 40 ppm and a LOAEL of 80 ppm were identified for increases in total malfo rmations in rats.

Table 4-47. Incidence of fetal malformations among litters of SpragueDawley rats exposed to AN by inhalation

AN concentration (ppm) Type of malformation 0 40 80 Number of fetuses/number of litters examined
External and skeletal malformations 421/33 441/36 4 06/35
Visceral malformations 140/33 148/36 136/35 Number of fetuses (litters) affected
External malformations
Short tail 0 (0) 0 (0) 2 (2)
Short trunk 0 (0) 0 (0) 1 (1) Imperforate anus 0 (0) 0 (0) 0 (0) Omphalocele 0 (0) 1 (1) 1 (1)
Visceral abnormalities Right-sided aortic arch 0 (0) 0 (0) 0 (0) Missing kidney, unilateral 0 (0) 0 (0) 0 (0) Anteriorly displaced ovaries 0 (0) 0 (0) 1 (1)
Skeletal malformations Missing vertebrae 0 (0) 0 (0) 2 (2) Missing two vertebrae and two ribs 8 (1) 2 (1) 7 (2 ) Hemivertebrae 0 (0) 0 (0) 1 (1)
Total malformed 8 (1) 3 (2) 11 (6) a 

### subchronic

a Significantly different from control, as calculated by the study authors ( p = 0.06).

Source: Murray et al. (1978).



### Saillenfait et al. (1993) included AN in a survey o f the relative developmental toxicities of inhaled aliphatic mononitriles in rats. Pregnan t Sprague-Dawley rats (20–21/group) were exposed (whole body) for 6 hours/day to 0, 12, 25, 50, and 100 ppm AN vapor on GDs 6–20.

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Dams were observed daily throughout pregnancy and B Ws were recorded on GDs 0, 6, and 21. All subjects were sacrificed on GD 21, and the uter i were weighed and opened to assess the numbers of implantations, resorption sites, and liv e and dead fetuses. The fetuses were examined for external abnormalities and then split into two equal groups for examination of
skeletal or visceral anomalies. AN exposure did not cause premature deaths in the dams, but exposure to ≥ 25 ppm caused concentration-related, statistically signifi cant reductions (by 16–45%) in overall BW gain and concentration-related losses in absolute BW (ex clusive of gravid uterus weight) in dams. In this study, 12 ppm is a NOAEL and 25 ppm is a LOAEL for reduced BW in dams. AN exposure had no effect on reproductive parameter s (pregnancy rate, average number of implantations, numbers of live fetuses, incidenc es of nonsurviving implants, or resorptions per litter). Concentration-dependent, statistically si gnificant reductions in average fetal weight (by 5–15% compared with controls) were observed at ≥ 25 ppm. There were no significant increases in the incidences of external, visceral, or skeleta l anomalies in the exposed groups and one control fetus. In this study, a NOAEL of 12 ppm an d a LOAEL of 25 ppm were identified for significantly reduced fetal BW. In a dominant lethal assay for AN, Zhurkov et al. (1983) continuously exposed male ICR mice (20/group, whole body) to AN at concentrations of 0, 20, or 100 mg/m 3 

### (0, 9.1, or 46 ppm) for 5 days. After exposure, each male was mated to two unexposed females for 8 weeks. Females were sacrificed between GDs 13 and 15, and a number of reproductive and developmental parameters were monitored, including the percentage of pregnant females, number of corpora lutea, implantations, and live an d dead fetuses per female as well as total and pre- and postimplantation mortality. Exposure to A N did not result in any dominant lethal effect on male germ cells nor did it cause adverse pre- or postimplantation outcomes. The highest exposure level in this study, 46 ppm, was a NOAEL f or reproductive toxicity. This study was limited by sparse descriptions of methods and a lac k of quantitative reporting of results.

4.3.2.3. Intraperitoneal Administration In a translated study in Chinese, the effect of AN on spermatogenesis was examined in groups of male Kunming mice (10 3–4-week-old pubert al and five 6–8-week-old adult mice per group) treated by i.p. injection (Liu et al., 2004) . The animals received AN (>99% purity) at doses of 1.25, 2.5, or 5.0 mg/kg-day (1/24, 1/12, o r 1/6 of the LD 50 

### ) for 5 days. Negative controls received physiological saline (10 mL/kg) d aily for 5 days, whereas positive controls received a single injection of 40 mg/kg CP (not ide ntified but presumably cyclophosphamide). On day 35, mice were sacrificed, the left testicle was selected from five mice per group, and testicular cell suspensions were evaluated using fl ow cytometry. The following dose-related effects observed in the 2.5 and 5.0 mg/kg-day groups were statistically significantly different from the nega tive control group ( p < 0.05); the same effects

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were observed in positive controls (Liu et al., 200 4). AN decreased the percentage of haploid testicular cells (indicative of completed spermatog enic meiosis) by 14.3 and 15% in mid- and high-dose adult mice, but a slight reduction was no t statistically significant in pubertal mice. The percentage of apoptotic testicular cells was si gnificantly increased by 58.7 and 74.8% in mid- and high-dose pubertal mice and by 81.5 and 10 8% in mid- and high-dose adult mice. The percentages of spermatogenic epithelial cells in G 0 

### /G 1 

### phase were significantly reduced by 18 and 20% in mid- and high-dose pubertal mice and by 35.5 and 40.5% in mid- and high-dose adult mice. The percentage of spermatogenic epithe lial cells in G 2 

### /M phase was significantly elevated in adult mice by 31.4 and 32.8% at the mid - and high doses, respectively. AN exposure had no effect on the percentage of spermatogenic ep ithelial cells in S phase. The NOAEL and LOAEL for suppression of spermatogenesis were 1.25 and 2.5 mg/kg-day, respectively. The teratogenic effects of AN were investigated in groups of pregnant golden hamsters that were exposed via an i.p. injection on GD 8 (Wi llhite et al., 1981). The actual numbers of dams per group were not reported, but data were pre sented for 3–6 litters in the exposed groups and 12 litters for the controls injected with sodiu m chloride. Dose levels were 0, 0.09, 0.19, 0.47, 1.23, and 1.51 mmol/kg (equivalent to 0, 5, 1 0, 25, 65, and 80 mg/kg). No adverse clinical symptoms were observed in the dams exposed to up to 1.23 mmol/kg (65 mg/kg) AN by GD 14,
when the dams were sacrificed. No malformations we re observed in the offspring. In contrast, dams exposed to 1.51 mmol/kg (80 mg/kg) showed inte nse dyspnea, gasping, incoordination, hypothermia, salivation, and convulsions for 1–5 ho urs after injection. Additionally, several
fetal abnormalities and malformations were observed at this exposure level, including encephaloceles and fused or bifurcated ribs. Coadm inistration of 8.06 mmol/kg STS and 1.51 mmol/kg AN induced neither maternal toxicity n or fetal malformations. Coadministration of 8.06 mmol/kg STS and a higher dose of AN (1.88 m mol/kg, 100 mg/kg) prevented toxic symptoms in dams but not the teratological effects in fetuses. The study authors concluded that the teratogenic action of AN was related to the met abolic release of cyanide. The effect of AN on rat liver cytochrome P-450 and serum hormone levels were studied in male Sprague-Dawley rats (4/group) injected with 33 mg/kg AN (i.p.) for 3 consecutive days (Nilsen et al., 1980). Control animals were treate d with 0.9% sodium chloride. Blood were collected immediately after the animals were sacrif iced and serum luteinizing hormone (LH), follicle stimulating hormone (FSH), and prolactine (PRL) were measured by radioimmunoassay. Serum corticosterone levels and liver microsomal cy tochrome P-450 were also determined. A significant increase (3%) in BW was reported in the AN treated group when compared with controls (Nilsen et al., 1980), but relative l iver weight was not increased. A significant
decrease in liver microsomal content of CYP450 was observed. Serum corticosterone measured 24 hours after the last AN injection was decreased by 70%, while FSH levels were increased by 118%. Serum PRL levels were decreased by 63% when compared with the controls, while

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serum LH levels were unchanged. Nilsen et al. (198 0) suggested that the increase in FSH might be secondary to impaired spermatogenesis in the tes tes of treated rats.

4.3.3. In Vitro Studies The embryotoxicity of AN was evaluated in cultures of whole rat embryos by Saillenfait and coworkers in a series of studies (Saillenfait e t al., 2004, 1992; Saillenfait and Sabaté, 2000). As described initially in Saillenfait et al. (1992) , the experimental system involved incubating day 10 embryos from pregnant Sprague-Dawley rats fo r 26 hours in whole organ culture in a medium containing AN at concentrations of 76–760 μ mol/L. The growth-related parameters evaluated were functional yolk-sac circulation, yol k-sac diameter, crown-rump length, head length, number of somites, number of malformed embr yos, incidences of abnormal brain, malformed caudal extremities, delayed yolk-sac circ ulation, and defective flexion. The effects of metabolic activation on the embryotoxicity of AN we re evaluated by the inclusion of S9 and cofactors (NADPH, glucose-6-phosphate) for CYP450-d ependent biotransformation in the incubation system. Exposure to AN induced concentration-related effec ts on growth and development. Functional yolk-sac circulation (circulating erythr ocytes) was reduced at ≥ 304 μ M and was completely absent at 760 μ M. Crown-rump length was reduced at 304 μ M and could not be measured at higher concentrations. A concentration -dependent increase in the incidence of malformations was observed following in vitro expos ure of day 10 fetuses to AN at 152 μ M and
above. AN at 152 and 304 μ M induced malformations in 53 and 100% of the expos ed embryos, respectively. Malformations primarily consisted of a shortened caudal extremity (significant at
152 μ M) and a reduction of the brain (achieving signific ance at 304 μ M). Other general malformations were delayed development of the yolk- sac circulation and defective flexion. Furthermore, growth retardation and severity of mal formations induced by 304 μ M AN were enhanced by the presence of S9 and cofactors, sugge sting a role for oxidative biotransformation in AN embryotoxicity. Addition of 0.1–2.2 mM GSH i n the incubation medium reduced the embryotoxic effects of AN in this system. Similarly, a later experiment by this research gro up (Saillenfait and Sabaté, 2000) demonstrated that day 10 rat embryos exposed to AN for 46 hours in vitro showed concentrationrelated effects on growth, development, and morphol ogy. Reduced growth (reduced yolk sac diameter and crown-rump length) occurred at 100 μ M. The head length and somite number were
reduced at 125 μ M. Abnormal development (reduced prosencephalon an d mesencephalon) and maxillary process defects occurred at ≥ 125 μ M AN. Defects of the rhombencephalon and the auditory system were observed less frequently. The se effects were characteristic of those developed by embryos exposed to sodium cyanide in c ulture. Addition of microsomes and NADPH to the culture medium containing 150 or 175 μ M AN enhanced the observed growth

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retarding and dysmorphogenic effects, especially in increasing the incidence of rhombencephalon and auditory system defects. Saillenfait et al. (2004) evaluated the effects of eight aliphatic nitriles on the viability and differentiation of cultured limb bud cells from Spr ague-Dawley rat embryos on GD 13. Limb bud micromass cultures were exposed for 5 days to A N at concentrations between 0.01 and 0.45 mM (0.5 and 23.9 μ g/mL), with or without microsomal activation, after which they were evaluated for cytotoxicity (neutral red uptake assa y) and differentiation of chondrocytes (number and total surface of foci with Alcian blue staining were used as indicator of cell differentiation). The concentrations that inhibited cell viability an d cell differentiation by 50% of concurrent
untreated controls were determined.
The IC 50 

### values were 0.24 mM (13 μ g/mL) for cytotoxicity (viability) and 0.33–0.38 mM (18–20 μ g/mL) for differentiation (total surface of foci an d number of foci), respectively. The
ratios of IC 50 

### for cytotoxicity and differentiation were 0.6 for number of foci and 0.7 for total
surface of foci. Microsomal activation had no effe ct on the results with AN. In parallel experiments, the IC 50 

### for cytotoxicity in cultured 3T3 cells (differenti ated mouse fibroblast cell line) exposed to AN was 0.065 mM. The relative pot ency of the tested nitriles in this limb bud cell culture system matched previously published re sults for cultured whole embryos, but not necessarily for in vivo teratogenicity (false negat ive results were obtained for two of the eight nitriles). Saillenfait et al. (2004) characterized the response of AN in the micromass culture assay as equivocal, since it depended on the criter ia used to define a positive result. According to one criterion, AN might be considered to have te ratogenic potency because its IC 50 

### was less
than 50 μ g/mL. However, under the “twofold rule” that defin es a positive result by a value >2 for the ratio (IC 50 

### for cytotoxicity)/(IC 50 

### for differentiation), AN would be classified as having poor potential developmental hazard. As sug gested by comparison of the IC 50 

### for cytotoxicity, embryonic rat limb bud cells were not more vulnerable to AN than differentiated 3T3 mouse fibroblasts. These suggestive results ar e consistent with the observations in vivo (see Section 4.3.2) that fetal toxicity from AN occurs o nly at exposure levels that cause maternal toxicity.

4.4. OTHER DURATION- OR ENDPOINT-SPECIFIC STUDIES 4.4.1. Acute Toxicity Data Closely similar values have been reported for the oral LD 50 

### in rats: 78 mg/kg (Benesh and Cherna, 1959), 93 mg/kg (Smyth and Carpenter, 1 948), 90 mg/kg (Sprague-Dawley rats) (Younger Labs, 1992), and 81 mg/kg (male CF Nelson rats) (Vernon et al., 1990). Lower value has been published for the oral LD 50 

### in mice: 25 mg/kg (H-strain, sex not stated) (Ben esh and Cherna, 1959) and 36 and 48 mg/kg in male and femal e mice, respectively (strain not stated) (Tullar, 1947, as cited in IPCS, 1983). These find ings indicate that mice are more susceptible to the acute toxicity of AN than are rats. Published LD 50 

### values for guinea pigs (56 mg/kg)

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(Jedlicka et al., 1958) and rabbits (93 mg/kg) (Pau let and Desnos, 1961) are in the same narrow range as those for rats and mice. For the inhalati on route, median lethal concentration (LC 50 

### ) values in rats of 217 ppm (470 mg/m 3 

### ) (Knobloch et al., 1971) and 333 ppm (777 mg/m 3 

### ) (Haskell Laboratory, 1992b) have been reported. Ho wever, exposing Sprague-Dawley rats to 1,008 ppm AN for 1 hour failed to produce mortality (Younger Labs, 1992). A 4-hour
LC 50 

### value of 946 ppm (2,053 mg/m 3 

### ) was reported for Sprague-Dawley rats following no seonly exposure (WIL Research Laboratories, 2005); no mortality was observed in male or female rats at exposures as high as 775 ppm (1,682 mg/m 3 

### ) in this study. However, ataxia, labored respiration, and hypoactivity were observed at this exposure concentration and higher.
LC 50 

### values (duration not reported) of 138 ppm (300 mg/ m 3 

### ) in mice and 456 ppm (990 mg/m 3 

### ) in guinea pigs have been reported (Knobloch et al., 1971). As set forth in the English abstract of an article in Polish, Knobloch et al. (1971) investigated the acute and subacute toxicity of AN in BN mice, Wistar rats, and guinea pigs (strain not given). For rats, s.c. and i.p. LD 50 

### values of 80 and 100 mg/kg, respectively, were reported. For mice, the LD 50 

### was 34 mg/kg. An earlier subacute study examined the effect of o ral AN administration on the liver of sodium PB-pretreated (400 μ mol/kg) or Aroclor 1254-pretreated (300 μ mol/kg) male and female Sprague-Dawley rats that received 100 or 500 ppm AN in drinking water for 21 days (Silver et al., 1982). Other pretreated animals were given 0, 50, 75, 100, or 150 mg/kg AN by gavage for up to 3 days. Some liver-related biochemical chang es were noted as a result of AN exposure, including a dose-dependent reduction in hepatic non protein sulfhydryl concentrations (maximal reduction of 81% at the highest dose of 150 mg/kg). Serum SDH activity was increased by fourfold 24 hours after administration of 150 mg/kg AN. On the other hand, SGPT activity was not significantly altered. Pretreatment with PB or Aroclor 1254 resulted in only a slight
enhancement of AN-induced elevation of serum SDH or SGPT activities. In the experiment in which female rats were pretreated with either vehic le, PB or Aroclor 1254, and treated with 100 ppm or 500 ppm AN for 21 days, there was a 60% increase in serum SDH activity in animals receiving 500 ppm AN in drinking water. In the 3-day studies, there was some evidence of fo cal superficial necrosis of the liver in rats receiving high gavage doses (100 or 150 mg/kg) . This effect was associated with the presence of hemorrhagic gastritis and distention of the forestomach. However, while the biochemical and pathology changes implied a limited perturbation of the liver by AN, light microscopy showed only minor changes in the histopa thology of the organ and no ultrastructural changes to the liver were evident when evaluated by electron microscopy. Silver et al. (1982) concluded that liver did not appear to be a target organ in the acute or subacute toxicity of AN. Dudley and Neal (1942) exposed several species of laboratory animals—rat, guinea pig, rabbit, cat, dog, rhesus monkey—to AN vapor for 0.5 –8 hours at concentrations ranging from 0.063 to 5.3 mg/L (30–2,445 ppm). In rats (Osborne Mendel, sex not stated), 1,260 ppm was

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found to be an effective lethal concentration when administered for 4 hours. During or after an 8-hour exposure, 320 ppm AN was fatal. A 4-hour ex posure to 260 ppm AN was fatal in rabbits (strain and sex not stated), while 1,160 ppm appear ed to be a fatal concentration in guinea pigs. Other lethal concentrations were 600 ppm for 1.5 ho urs in cats and 110–165 ppm for 3 hours in dogs (breed not given, male and female), while Rhes us monkeys (males and females) tolerated 90 ppm AN with only minor, transitory adverse effec ts (skin redness, sleepiness). In all species except guinea pig, AN caused an initial respiratory stimulation, followed by rapid, shallow breathing, nasal exudate, and watering eyes. In ra ts, the most striking symptom was reddening of the skin in the less prominently haired regions (nose, ear, feet). Reddening of the skin was also observed in the other species, again with the exception of guinea pigs. The study authors concluded that, in five of the six species investig ated, AN-induced symptoms resembled cyanide poisoning. By contrast, AN acted as a severe pulmo nary irritant in guinea pigs. Consistent with these findings, sodium nitrite (a cyanide antidote) protected five of the species studied, but not guinea pigs, from AN toxicity. The study authors p ostulated that guinea pigs may metabolize AN differently than rats, rabbits, cats, dogs, or m onkeys, possibly by transformation to acrolein rather than cleavage of the cyano group. However, Dudley and Neal (1942) were unable to extract any cyanide from the tissues of animals tha t had succumbed to AN exposure. Knobloch et al. (1971) evaluated the acute toxicit y of AN via inhalation exposure (duration not given) in three species. The LC 50 

### in mice was 0.30 mg/L (138 ppm), in rats 0.47 mg/L (217 ppm), and in guinea pigs 0.99 mg/L ( 456 ppm). These values confirmed the roughly twofold species difference between rats and guinea pigs, but were about threefold lower than values reported by Dudley and Neal (1942). Two studies by Gut et al. (1985, 1984) evaluated t he subchronic toxicity of AN in rats when administered via inhalation. In both studies, male Wistar rats were exposed to 280 mg/m 3 

### AN by inhalation 8 hours/day for 5 days (Gut et al. , 1985, 1984). As shown in Table 4-48, BW was decreased in rats exposed to AN for 5 days. Th e absolute weight of liver decreased, while brain weight remained unchanged. Hence, the relati ve liver weight was significantly decreased, while relative brain weight increased due to the BW decrease. However, there were no significant histopathological changes in the lungs, livers, kidneys, or adrenals. The concentrations of glucose, pyruvate, and lactate we re elevated in the brain and blood of exposed rats (Table 4-48). Treatment-related reductions in the concentrations of serum cholesterol and triglycerides were found in test animals. The stud y authors considered the increase in blood glucose concentration to be the most sensitive indi cator of AN exposure under these experimental conditions (Gut et al., 1984).

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Table 4-48. Effects of AN on organ weight, clinica l chemistry, and biochemical parameters when administered to male Wi star rats via inhalation

Parameter (units) Controls (n) AN (n) BW (g) 341 ± 18 (8) 287 ± 24 a (8) Relative liver weight (g/100 g BW) 3.39 ± 0.29 (8) 2.79 ± 0.08 a (8) Relative brain weight (g/100 g BW) 0.564 ± 0.06 (8) 0.647 ± 0.076 a (8) Serum triglyceride (mmol/L) 2.36 ± 0.51 (10) 1.47 ± 0.47 b (10) Serum cholesterol (mg/dL) 72.3 ± 8.5 (10) 54.6 ± 12 .9 b (10) Pyruvate (mmol/L)
Blood 0.080 ± 0.012 0.128 ± 0.028 a (5)
Brain 0.039 ± 0.007 0.068 ± 0.014 a (5) Lactate (mmol/L)
Blood 2.259 ± 0.577 (5) 4.032 ± 1.061 a (5)
Brain 6.002 ± 0.258 (5) 8.034 ± 0.471 a (5) Glucose (mmol/L) 4.10 ± 0.21 10.22 ± 1.26 c (5)

a Significantly different from controls ( p < 0.05).
b Significantly different from controls ( p < 0.001).

c Significantly different from controls ( p < 0.01).

Source: Gut et al. (1984).



### Gut et al. (1984) further examined the dose-respon se effects of AN on blood glucose levels by giving food-deprived male Wistar rats a s ingle 12-hour exposure of 0, 57, 125, or 271 mg/m 3 

### AN. Blood glucose levels were dose-dependently in creased at the end of the exposure period (4.33 ± 0.64 at 57 mg/m 3 

### ; 10.88 ± 3.74 at 271 mg/m 3 

### vs. 3.46 ± 0.29 mg/m 3 

### in controls) but declined to normal or below normal le vels 24 hours after exposure (1.79 ± 0.84 at 271 mg/m 3 

### vs. 4.73 ± 0.34 mg/m 3 

### in controls). The simultaneous increase in the pyruvate and lactate concentrations suggests that A N affected carbohydrate metabolism on the level of glycolysis as well as on the citric acid c ycle level. In a subsequent study using exposure regimens iden tical to those in Gut et al. (1984), Gut et al. (1985) monitored AN-induced changes in sulfh ydryl concentrations in the liver and brain and the appearance of thioethers (AN-mercapturic ac id) and thiocyanate in the urine. GSH concentrations in the liver were significantly redu ced compared with controls (3.86 ± 0.41 vs.
7.66 ± 0.58 μ mol/g) in rats exposed to AN for five consecutive d aily 8-hour exposures at 280 mg/m 3 

### . No GSH depletion was evident in the brain. The protein sulfhydryl level remained unchanged in the brain but was increased by 17% in the liver, although not statistically significant. One out of 15 treated animals died, a nd the study authors suggested that GSH depletion could have been responsible.

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Urinary excretion of thioethers and thiocyanate was proportional to the inhaled concentration. The ratio between urinary thioether s and thiocyanate in exposed rats was about 2:4 and was not influenced by the exposed AN concen trations (Gut et al., 1985). Bhooma et al. (1992) evaluated the effect of AN on the procoagulant activity in pulmonary alveolar macrophages of rats. Six male W istar rats/group were exposed to 100 ppm AN 5 hours/day for 5 days. Animals were sacrificed at 1–28 days after the last exposure. The lungs were lavaged, and alveolar macrophages were c ollected from the broncho alveolar lavage (BAL) fluid. Procoagulant activity (the ability of a cell or cell products to accelerate the conversion of fibrinogen to fibrin) in macrophage a nd BAL fluid was determined. The procoagulant activity in the isolated macrophages f rom exposed animals was about 10-fold higher than in controls 1 day after AN exposure and then slowly declined to control levels by day 28 after exposure. Procoagulant activity of BA L fluid remained unaltered in rats sacrificed up to 7 days after exposure but was elevated in tho se sacrificed 14 and 28 days after exposure. The study authors noted that acute lung injury ofte n resulted in deposition of fibrin in alveolar spaces (Bachofen and Weibel, 1977) and that fibrin and its degradation products have been implicated in contributing to pulmonary inflammatio n (Malik et al., 1979; Cuterman et al., 1977). Since this study showed macrophage-associat ed procoagulant activity in the lung following inhalation to AN, the study authors sugge sted the alveolar macrophages participated in the pulmonary deposition of fibrin. Other experimental studies have used acute dosing protocols to study toxicological effects of AN on various target organs. These stud ies are summarized in the following sections.

4.4.1.1. Effects of AN on the GI Tract Two studies have reported GI hemorrhage and gastric erosion in rats administered with single doses of AN. In the first report (Ghanayem and Ahmed, 1983), a single dose of 50 mg/kg AN was administered to Sprague-Dawley rats (orally or s.c.). GI bleeding was observed 3 hours after treatment, with no significant difference in the amount of GI blood loss resulting from s.c. or oral administration. Thus, AN-induced GI bleedi ng was not a result of direct irritation of AN on the GI tract. A time-course study of a single 5 0 mg/kg dose of AN administered by the s.c.
route indicated that the amount of blood recovered from the stomach was significantly higher than that of controls at 1, 2, and 3 hours after tr eatment, while the amount recovered from the intestinal contents was significantly higher than i n controls at 2 and 3 hours. Dose-response study of s.c. administration of AN and GI bleeding indicated that significantly higher GI bleeding than in controls occurred at 40, 50, and 7 0 mg/kg AN, with the maximum at 50 mg/kg
AN. Pretreatment of rats with the CYP450 enzyme inducer , PB, decreased the AN-induced GI blood loss by 55%, whereas pretreatment with Aroclo r 1254 increased blood loss by 240% (Ghanayem and Ahmed, 1983). In contrast, pretreatm ent of rats with CYP450 inhibitors, cobalt

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chloride or SKF 525A, prior to AN administration pr oduced significant decreases in blood loss of 10 and 40%, respectively. Pretreatment of rats with diethylmaleate (DEM), a known depletor of GSH, prior to AN administration produced no sign ificant change in GI bleeding. In addition, s.c. administration of a sublethal dose (6 mg/kg) o f KCN did not induce GI bleeding when compared with controls, whereas 50 mg/kg AN produce d significant GI bleeding. The study
authors concluded that metabolic activation of AN t o a reactive metabolite other than cyanide (probably CEO) by CYP450 was a prerequisite for AN to induce gastric hemorrhage. In the second paper, Ghanayem et al. (1985) studie d the mechanism of AN-induced gastric mucosal necrosis in the glandular stomach. Male Sprague-Dawley rats were treated with a single s.c. dose of AN (50 or 30 mg/kg), and the glandular stomach was removed and evaluated for histopathology and GSH concentrations. The liv er was also removed for GSH determination. Gastric erosion severity index (GEI) was obtained f or each exposure group by multiplying the mean severity score by the incidence of gastric nec rosis in the group. Calculated GEI was found to be dose and time dependent: higher at 50 mg/kg than 30 mg/kg AN 3 hours after administration and in rats killed 3 hours as compar ed with rats killed 1 hour after the same dose
of AN. Subcutaneous administration of 30, 40, or 50 mg/kg AN also caused a significant decrease in hepatic GSH concentration 3 hours after treatment, with greater decrease at lower dose (30 mg/kg) than in high dose (50 mg/kg). A si gnificant decrease in gastric GSH
concentrations was observed 3 hours after treatment at 40 and 50 mg/kg AN. Pretreatment of rats with various metabolic modulators (CYP450 mono oxygenase and GSH) before administration showed that there was a significant inverse relationship between gastric GSH concentration and AN-induced gastric erosions. P45 0 inducers (Na PB and Aroclor 1254) alone
increased GSH levels in the liver. Pretreatment of rats with these P450 inducers inhibited AN-induced gastric necrosis, and partially blocked AN-induced gastric GSH depletion. SKF 525A, a CYP450 inhibitor, caused a slight depletion of gastric and hepatic GSH and potentiated the AN-induced gastric necrosis and GSH depletion. In contrast, cobaltous chloride, another inhibitor of CYP450 enzyme, inhibited AN-induced ga stric necrosis and increased both the hepatic and gastric GSH concentrations. In rats tr eated with DEM, a depletor of GSH and AN, or DEM + cysteamine + AN, GEIs were increased up to fivefold when compared with rats treated with AN alone. Mucosal erosion severity in these two groups was also greatly increased, with more than 50% of rats showing severe or extens ive lesions. Pretreatment of rats with sulfhydryl-containing compounds (cysteine or cystea mine) protected against AN-induced gastric necrosis and blocked the depletion of gastric GSH. In addition, AN-induced gastric erosions could be p revented by pretreatment with atropine, a muscarinic receptor blocker, suggesting the involvement of muscarinic receptors in the AN-induced gastric mucosal necrosis (Ghanayem e t al., 1985). Activation of acetylcholine muscarinic receptors is known to increase gastric a cid secretion and cause gastric erosions.

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Because muscarinic receptors are known to contain s ulfhydryl groups in their active site (Ikeda et al., 1980; Aronstam et al., 1978), Ghanayem et a l. (1985) hypothesized that AN inactivated critical sulfhydryl groups and caused gastric erosi ons by locally modulating muscarinic acetylcholine receptors in the stomach. More recently, Ahmed et al. (1996a) showed accumul ation of AN-derived radioactivity
in intestinal contents and intestinal mucosa follow ing i.v. injection of 2-[ 14 

### C]-AN to rats. A recent study by Jacob and Ahmed (2003a) also demons trated that AN and or its metabolites accumulated and covalently interacted in GI mucosa of male F344 rats treated either i.v. or orally with 2-[ 14 

### C]-AN. These studies supported the hypothesis that AN-induced injury of the GI mucosa is not due to direct irritation by AN but by metabolic incorporation and macromolecular
interaction of AN in these tissues.

4.4.1.2. Effects of AN on the Kidney The acute nephrotoxic effect of AN was investigate d in single exposure studies in rats and hamsters by inhalation or i.p. administration. Intraperitoneal injection of Chinese hamsters with 30 mg/kg AN increased kidney weight and renal GSH concentration 24 hours after injection (Zitting et al., 1981). Kidney deethylation activi ty was also decreased. Rouisse et al. (1986) administered i.p. doses (0, 10, 20, 40, 60, or 80 m g/kg) of AN to male F344 rats (six/dose group). Urinary volume was increased two- to threefold duri ng the 24-hour period following administration for all dose groups. Urinary glucos e was about 6 times higher in the 20 mg/kg group than in controls, and 40–60 times higher in t he higher dose groups. Urinary excretion of N-acetyl- β -D-glucosaminidase was increased at the highest dos es, up to 80% over controls in the 80 mg/kg group. An increased number of lysosomes o r dense bodies in renal proximal tubules was seen under the light or electron microscope. I n the inhalation study, a similar array of toxicological and clinical chemistry effects relati ng to kidney structure and function was observed in male rats (seven/group) exposed to 200 ppm AN for 4 hours (Rouisse et al., 1986).

4.4.1.3. Effects of AN on the Adrenal Gland An experimental model for the toxicity of AN inves tigated the capacity of single i.v. doses of AN to induce acute hemorrhagic necrosis of the adrenal gland (Szabo et al., 1976). This condition has a parallel in man, the Waterhouse-Fri derichsen syndrome, which is characterized by thrombocytopenia, disseminated intravascular coa gulation, and the appearance of fibrin degradation products in the circulation (Szabo et a l., 1976). The condition has been induced in female Sprague-Dawley rats by a single injection of 150 mg/kg AN into the jugular vein (Szabo et al., 1980) and typically has been marked by mass ive “bilateral apoplexy,” a usually fatal hemorrhagic necrosis of the adrenal glands that occ urs in 90–100% of the rats within 90– 150 minutes. Thrombocytopenia and a range of assoc iated clinical signs, including tremors, cyanosis, and ultimately respiratory failure, were observed. Light and electron microscopy

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showed that an early event in the onset of this con dition was damage to the vascular endothelium of the adrenal cortex, with parenchymal injury as a late event. However, these AN-induced lesions could be prevented by pretreatment with the α -adrenergic antagonist phenoxybenzamine,
the α , β -blocker labetalo, or the 11- β -hydoxylase inhibitor metyrapone. Elevation of tis sue sulfhydryl levels by cysteine or GSH reduced the ad renal apoplexy. Dopamine concentrations in the adrenals increased over time. Because depletio n of catecholamines by reserpine, or medullectomy, could prevent the chemically induced adrenocortical necrosis, the study authors proposed that cortical damage resulting from AN was associated with vasoactive amines released
from the medulla and/or with metabolites of AN.

4.4.1.4. Effects of AN on Neurological Endpoints Neurotoxic effects were induced in male Sprague-Da wley rats receiving single gavage or s.c. doses of 20, 40, or 80 mg/kg AN (Ghanayem et a l., 1991). Two distinct phases of neurological response were evident. The early phas e was cholinomimetic in nature, with signs such as salivation, lacrimation, polyuria, miosis, vasodilatation, gastric secretion, and diarrhea. The second phase developed 4–5 hours later with tox ic signs, including depression, convulsions, and respiratory failure, followed by death at the h igher doses. These CNS effects were observed in rats treated with 40 and 80 mg/kg and were simil ar to those caused by cyanide. Pretreatment of animals with 1 mg/kg atropine, an acetylcholine muscarinic antagonist, abolished the cholinomimetic toxicity, implicating an involvement of the cholinergic system in some aspects of acute AN neurotoxicity. Since effects were obse rved even at the lowest dose, a NOAEL was not identified, and 20 mg/kg was the LOAEL. In another study, male Sprague-Dawley rats that we re administered s.c. doses of 112 mg/kg AN (LD 90 

### ) showed a biphasic response consisting of an early phase with tremors and
seizures about 100 minutes after dose administratio n, followed by severe clonic convulsions that preceded death at about 3–4 hours (Benz and Nerland , 2005). The effects of preadministered inhibitors of oxidative metabolism by CYP450 (80 mg /kg SKF 525A, 75 mg/kg 1-benzylimidazole, or 100 or 200 mg/kg metyrapone) and an alternative CYP450 substrate, ethanol (5,000 mg/kg), on the acute convulsions wer e examined. Although blood levels of cyanide, and the development of the first phase of tremors and seizures, were inhibited by 1-benzylimidazole or ethanol, treatment with these two agents did not prevent the terminal convulsions or the death of rats injected with 112 mg/kg AN. Ethanol, being a CNS depressant, decreased the incidence of terminal convulsion (5/1 7 vs. 15/17). These results suggested that the initial phase of the acute neurotoxically lethal ef fects may have been due to cyanide, which is released via the CYP450 metabolic pathway for AN, a nd that the second phase was mediated by the parent compound. Because ethanol showed some effect on lessening the second phase response to AN (although it did not prevent lethality), several an ticonvulsants were examined for their ability to

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counteract the acute neurotoxicity and lethality of 112 mg/kg AN. Administration of PB (25 mg/kg) or phenytoin (150 mg/kg) (but not 144 mg /kg valproic acid) markedly inhibited the lethal response to 112 mg/kg AN: 9/10 rats died fo llowing administration of AN alone or AN plus valproic acid, whereas 1/10 and 2/10 rats died following administration of AN plus PB or AN plus phenytoin, respectively. The protection by phenytoin and PB against convulsion and lethality was not due to inhibition of metabolism o f AN to cyanide, since only phenytoin was able to lower blood cyanide levels (by about 32%), and was much less effective than 1-benzylimidazole or ethanol (97 and 94%, respectiv ely).

4.4.1.5. Effects of AN on Hearing AN is one of a number of organic compounds that ha ve been shown to promote noiseinduced hearing loss (NIHL) in rats (Fechter, 2004; Fischel-Ghodsian et al., 2004). The ototoxicity of AN was examined in several experimen ts in male Long-Evans rats exposed by s.c. injection (Fechter et al., 2003). The AN used in t hese experiments was stabilized to minimize the accumulation of peroxides. Ten rats were anest hetized and surgically prepared for the assessment of the compound action potential (CAP), which represents the synchronous neural activity elicited by primary auditory neurons (spir al ganglion cells) and directly measures auditory threshold sensitivity. Auditory threshold s at each test frequency were measured for
each rat under anesthesia on 20 different occasions before treatment with AN to determine baseline auditory thresholds. Auditory thresholds for 11 test frequencies between 2 and 40 kHz were recorded at 5-minute intervals up to 100 minut es postinjection with AN. The acute effect of 50 mg/kg s.c. AN on auditory sensitivity was stu died in five rats; five control rats were injected only with water. In a second study, the e ffects of AN on permanent NIHL were evaluated in six experimental groups (six rats each ) that received the following: no treatment; 50 mg/kg AN alone, two injections of 50 mg/kg-day A N on 2 consecutive days, noise alone (108 dB octave-band noise for 8 hours), single inje ction of 50 mg/kg AN immediately followed by noise, and exposure to noise after a second inje ction of AN. The acute study showed that exposure to 50 mg/kg A N s.c. alone elevated auditory threshold temporily and produced a 10–20 dB loss in auditory threshold sensitivity (temporary threshold shift) in the stimulus range of 8–40 kHz (Fechter et al., 2003). This transient loss reached a maximum within 10–20 minutes after inject ion but returned to control levels within 75–100 minutes. In the study on permanent auditory threshold shifts, when rats were tested 3 weeks following AN and AN + noise treatment, expo sure to AN alone did not produce a persistent loss in auditory threshold sensitivity. AN-treated rats had slightly reduced auditory threshold compared with controls, indicating slight ly increased sensitivity (within 5 dB of controls), but the difference was not statistically significant. Noise treatment alone elevated auditory thresholds by less than 20 dB at all teste d frequencies. However, rats given two injections of AN followed by noise in the high freq uency range of 12–40 kHz exhibited auditory

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impairments averaging 27 dB (maximally 40 dB) compa red with controls; this shift was statistically significant compared with other group s (controls, noise alone, AN alone, or no treatment). Rats given a single injection before e xposure to noise showed an average 11 dB threshold shift in the high-frequency range (12 and 40 kHz). This study demonstrates that exposure to AN exacerbated NIHL. Fechter et al. (2003) also assessed blood cyanide and glutathione levels in brain, liver, and paired cochleae in additional groups of rats ex posed to AN. Groups of five rats given 20, 50, or 80 mg/kg s.c. AN produced peak levels of cyanide , a metabolite of AN, in the blood at 1 hour (for 20 and 50 mg/kg) and 2 hours (for 80 mg/kg) fo llowing injection. Cyanide levels returned to baseline values within 2, 3, and 4 hours, respec tively. Since AN produced maximal auditory threshold impairment within 20 minutes of administr ation, before blood cyanide level peaked at 1 hour, the acute ototoxic effect of AN was not lik ely associated with elevated cyanide levels. When rats were given a single injection of 50 mg/k g, maximal reductions in glutathione levels (measured between 15 minutes and 8 hours pos tinjection) were detected in the brain by 15 minutes (–50%), in the liver by 1 hour (–80%), a nd in the cochlea by 2 hours (–45%). Cochlear glutathione levels remained depressed for about 4 hours. Recovery of glutathione
levels to near control levels was achieved in all t issues by 8 hours. Since AN induced transient cochlear function loss that peaked within 10–20 min utes after injection and recovered within 75– 100 minutes, the acute ototoxic effect of AN could not be associated with GSH level in the cochlea. Fechter et al. (2003) concluded that, whi le AN-induced oxidative stress in the cochlea may play a role by which AN promotes NIHL, the acut e ototoxic effect of AN might reflect
other unidentified toxic action of AN in the cochle a. Fechter et al. (2004) extended their evaluation of the potentiation effect of AN exposure on NIHL. Two experiments were conducted: the firs t experiment studied the effects of a single AN exposure on permanent NIHL, while the second one evaluated the effects with five daily AN and noise exposures. In both experiments, six male Long-Evans rats were assigned to each treatment group: AN alone, noise alone, AN + noise , and untreated controls. AN exposed groups were given s.c. injections of 50 mg/kg-day A N, with or without 4 hours of exposure to noise (105 dB), and then assessed for auditory thre shold sensitivity 4 weeks later. In the single-day treatment study, AN alone did no t alter the auditory threshold, but a single AN exposure in combination with noise signif icantly elevated auditory thresholds by an average of 10 dB above the effect of noise alone. Noise exposure alone increased auditory thresholds compared with controls by an average of 10 dB in the range of 12–40 kHz (Fechter et al., 2004). In the 5 consecutive-day treatment stu dy, AN plus noise treatment exacerbated the impairment induced by noise alone by an average of 30–45 dB at frequencies between 20 and 40 kHz and by no more than 10 dB at frequencies <16 kHz. Similar to the single-exposure study, repeated AN exposure had no effect on audito ry thresholds assessed 4 weeks later. Repeated noise exposure elevated auditory threshold s about 17 dB above control rats.

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When the reactive-oxygen scavenger phenyl-N-tertia ry

- butylnitrone (PBN) (100 mg/kg i.p.) was injected twice daily for 5 days prior to exposure to noise alone and rats were assessed 4 weeks later, PBN reduced the magnitude of hearing loss. When PBN was injected daily prior to the injection of AN and again following noise ex posure, the magnitude of hearing loss was equivalent to that exhibited by rats treated by noi se alone. (No significant difference was found between rats receiving noise alone and those receiv ing PBN plus noise.) These results indicated that reactive oxygen species (ROS) were responsible for the ototoxic effects of AN. These findings are consistent with the suggestion that mi tochondria injury within cochlear cells, primarily or secondarily through oxidative stress, may be a common feature of ototoxicity induced by chemicals and noise (Fischel-Ghodsian et al., 2004). Results from a recent study indicated that hearing loss from AN and noise exposure involves histologic damage to hair cells on the sur face of the organ of Corti (Pouyatos et al., 2005). Groups of five male Long-Evans rats were gi ven s.c. injections of 0 or 50 mg/kg-day AN for 5 consecutive days, with or without exposure 30 minutes later to noise for 4 hours/day (95 or 97 dB octave-band noise at 8 kHz). Hearing dysfunc tion of these rats were then assessed by: (1) distortion product otoacoustic emissions (DPOAE s) before exposure, as well as 1 hour and 4 weeks postexposure; (2) CAP for auditory threshol d sensitivity 4 weeks after the last treatment; and (3) number of hair cells on surface preparation of the organ of Corti 4 weeks after treatment. Permanent effects on these endpoints (i.e., effects observed 4 weeks following the last treatment) were only observed in rats exposed to both AN and n oise and not in rats exposed to AN or noise alone. Permanent effects from combined exposure to AN and noise included auditory threshold shifts (13–16 dB between 7 and 40 kHz), a decrease in DPOAE amplitudes (up to 25 dB at 19 kHz), and significant outer hair cell (OHC) loss in the cochleae. With the AN plus 97 dB treatment, average OHC loss was 20, 16, and 9% in t he first, second, and third rows, respectively, in the areas corresponding to frequen cies ranging from 13 to 47 kHz. Similar effects were found in the AN plus 95 dB treatment g roup. This study demonstrated AN could potentiate NIHL at noise levels that are relevant t o human exposure. Pouyatos et al. (2007) further proposed that AN ex acerbated NIHL by decreasing antioxidant defenses of hair cell. This hypothesis was tested in a study in which the capability of specific antioxidants in the protection of the coch lea of male Long-Evans rats treated with 50 mg/kg AN s.c. 30 minutes prior to the daily nois e exposure of 97 dB sound pressure level 4 hours/day for 5 days. Sixty-five Long-Evans rats (2–12/group) were exposed to different combinations of noise, AN, and antioxidants; AN alo ne or AN + STS (150 mg/kg i.p.), a CN inhibitor; AN + 4-methylpyrazole (4MP,100 mg/kg i.p .), a drug that blocks CN generation by competing with CYP2E1; AN + L-N-acetylcysteine (L-N AC) (4 × 400 mg/kg, orally), a pro-GSH drug; noise (97 dB octave band of noise [OB N]/8 kHz) alone; noise and STS, 4MP, or L-NAC; or noise plus AN and antioxidants. To evalu ate auditory impairment, DPOAEs and CAPs were measured prior to experimental treatment and 3 days and 4 weeks after treatment. At

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the end of exposure, cochleae were harvested for hi stologic examination. Additional rats (n = 64) were used to measure cochlear and liver GSH and blood CN levels at different time points
after treatment. At 3 days postexposure, similar auditory loss was found in animals exposed to AN + noise, STS + AN + noise, 4MP +AN + noise, and L-NAC + AN + noise. The maximum shifts averaged 25–30 dB between 12 and 32 kHz. At 4 week s postexposure, animals exposed to
L-NAC + AN + noise recovered to baseline levels abo ve 25 kHz. However, at lower frequencies, L-NAC did not prevent auditory loss ca used by AN + noise exposure. Animals received combined exposure to AN + noise, and AN + noise + STS or AN + noise + 4MP showed little change in producing auditory loss. In addition, the cochleae from rats exposed to AN and noise demonstrated substantial damage in the basal half of the organ of Corti. Me an OHC loss averaged 35% in the three rows in the region corresponding to frequencies above 12 kHz. Neither STS nor 4MP pretreatment protected against OHC loss caused by AN + noise. H owever, pretreatment with L-NAC reduced the OHC loss caused by AN + noise in the region cor responding to 25 kHz and above. Liver GSH level was depleted by 63% 1 hour after AN injection. Cotreatment with STS
or 4MP reduced GSH level about 80% at 1 hour and 52 % at 3 hours. However, with L-NAC pretreatment, GSH level was reduced only by 23 and 20% at 1 and 3 hours, respectively. Similarly, whereas AN treatment depleted cochlear G SH levels to undetectable levels at 1 hour, STS pretreatment had no effect on GSH depletion. 4 MP pretreatment only slightly reduced GSH depletion. However, L-NAC pretreatment not only pr otected but induced an increase in GSH levels above control levels. Pouyatos et al. (2007 ) concluded that, since L-NAC cotreatment reduced auditory loss and OHC loss from AN + noise treatment, GSH is involved in the protection of the cochlea against ROS generated by moderate noise levels. However, CN did not appear to be involved in this potentiation.

4.4.2. Immunological Effects of AN A case study by Balda (1975) described a human sub ject who developed contact dermatitis following the use of a Plexidur finger s plint. Investigators obtained a positive result in a patch test with AN, which is one of the constitue nts of the polymer Plexidur. This observation suggested that AN might induce immunological respon se in exposed subjects. The immunotoxicity of AN was evaluated in groups of six male CD-1 mice given a single oral dose in water or repeated oral doses fo r 5 or 14 days (Ahmed et al., 1993). In each of these experiments, a positive control group receive d a single immunosuppressive dose of 225 mg/kg of cyclophosphamide i.p. In the first ex periment, mice given a single gavage dose of 0 or 13.5 mg/kg AN in water were evaluated 3 or 5 d ays later for BW, relative organ weights (thymus, spleen, liver, and kidney), number of viab le splenocytes, and total and differential WBC counts in spleen cells suspension (Ahmed et al. , 1993). AN slightly reduced BWs in mice

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(6–7%) after 3 and 5 days, but the difference was n ot biologically significant. In treated mice, relative spleen weights were increased by 50% after 5 days, whereas relative thymus weights were decreased by 42% after 5 days; relative liver weight was decreased by 11% on day 3 but was 9% higher than controls on day 5. AN treatment reduced total leucocytes by 42–57%, lymphocytes by 39 and 65%, monocytes by 38 and 50%, and neutrophils by 67 and 73% on days 5 and 3, respectively. In the second experiment, mice received 0 or 6.75 mg/kg-day of AN in water on 5 consecutive days and were evaluated on day 6 (Ahm ed et al., 1993). In mice treated for 5 days, BWs were reduced by 27%, relative liver wei ghts were decreased by 10%, and relative spleen weights were increased by 25%. Total spleno cytes were decreased by 51%, with total blood leucocytes and lymphocytes reduced by 48 and 68%, respectively; circulating monocytes were increased by 88%. The immunotoxic effects of AN in both studies were comparable to effects elicited by the known immunosuppressant cyc lophosphamide. In a third experiment, groups of male CD-1 mice (s ix/group) were treated with AN by gavage in water for 14 days (Ahmed et al., 1993). There were a total of nine groups: three groups dosed with AN at 1.35, 2.7, or 5.4 mg/kg-day only, three groups dosed the same way but immunized with sheep red blood cells (SRBCs) on day 9 of exposure, and three concurrent control groups (normal, SRBC-immunized, and a posit ive control group treated intraperitoneally with cyclophosphamide [225 mg/kg] 1 day before immu nization). Mice were evaluated for total BW, relative organ weights (thymus, spleen, liver, and lung), number of splenocytes, total and differential WBC counts in spleen cell suspensions, and histopathology of lymph nodes, lung, and intestinal Peyer’s patches. Subsets of spleen lymphocytes (T and B cells) were enumerated by flow cytometry. Spleen cells from mice immunize d with SRBCs were evaluated in a plaqueforming cell assay. In nonimmunized mice, AN decreased BW by 12–15% an d increased relative thymus weights by 43% at 2.7 mg/kg-day and relative lung w eights by 39% at 5.4 mg/kg-day. AN increased splenocyte viability by 49–264% in a dose -independent manner. AN also caused doseindependent increases of 126–293% in relative splee n weight at all doses. Total leukocyte counts/spleen were increased by 171, 119, and 107% at the low to high doses; lymphocyte counts/spleen were significantly reduced by 25–45% at all doses, while monocyte and neutrophil counts/spleen were increased concomitantly by as mu ch as 78-fold. Reductions in lymphocyte subsets were observed at all doses: T-cells by 40– 53%, B-cells by 32–36%, T-helper cells by 40–59%, and T-suppressor cells by 49–62%. Histolog ical examination revealed severe enlargement of mesenteric lymph nodes and intestina l Peyer’s patches, abscesses and massive necrotic damage in the lung, and swellings in the b rachial lymph nodes in mice treated with AN at all doses but more aggressive in the 5.4 mg/kg g roup. No incidence data were reported for
these lesions. Some of the mice treated with 5.4 m g/kg-day died rapidly. Microbiological

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examination revealed the swelling in the lymph node s was related to migration of normal intestinal flora, which the study authors attribute d to immunosuppressive effects of AN. In the SRBC-immunized mice, AN treatment did not a ffect the BW. The relative weight of lung, liver, and thymus showed inconsistent and dose-independent increases. The viable spleen cells showed 77% increases only in the 2.7 m g/kg group. The lymphocytic count showed dose-independent decreases. However, the neutrophi lic and monocytic counts showed large increases at all doses. Decreases in lymphocyte su bsets were found in all three doses of AN: T-cells by 42–45%, B-cells by 37–50%, T-helper by 4 3–54%, and T-suppressors by 40–48%. The IgM antibody plaque forming cell response was d ecreased by 55, 23, and 65 after treatment with 1.35, 2.7, and 5.4 mg/kg AN, respectively. Th e lowest dose used in this study, 1.35 mg/kgday, was a LOAEL for immunotoxicity (suppression of humoral and cell-mediated immunity) in mice treated for 14 days. Hamada et al. (1998) further investigated the immu notoxicity of AN by administering 2.7 mg/kg-day AN (1/10 the LD 50 

### ) to male CD-1 mice orally for either 5, 10, or 15 days. All mice were injected with 100 mg/kg bromodeoxyuridine (BrdU) i.p. 1 hour before sacrifice. An
immunohistochemical assessment of the number of cel ls capable of producing IgA in different intestinal compartments as a result of AN administr ation was conducted. Uptake of

3 

### H-thymidine into splenocytes derived from treated a nimals and stimulated with different mitogens—phytohemagglutinin (PHA), concanavalin-A ( con-A), or lipopolysaccharide (LPS)— was measured. The rate of proliferation of gut epi thelial cells of different intestinal compartments was determined by the incorporation of BrdU in newly synthesized DNA of S-phase cells. The mitogenic response of mouse splenocytes to PHA , con-A, and LPS was affected by AN exposure as shown by a significant decrease in [ 3 

### H]-thymidine incorporation (Table 4-49).
The decreases were 68–79% with con-A and 35–57% wit h LPS, depending on the time intervals. However, uptake of [ 3 

### H]-thymidine by splenocytes after stimulation with PHA was markedly reduced only after 15 days of exposure. These resu lts suggested that AN induced systemic suppression of humoral immunity (by the decrease in mitogen response to LPS) and cellmediated immunity (by the inhibition of mitogen res ponse to con-A and PHA).

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Table 4-49. Time course of the effect of AN admini stration on [ 3 

### H]-thymidine uptake into mouse splenocytes under th e influence of different mitogens in vitro

D of AN treatment Mitogens Control 5 10 15
PHA a 1,331 ± 163 1,203 ± 265 1,434 ± 35 898 ± 32 b

con-A a 14,927 ± 972 4,756 ± 532 b 4,792 ± 946 b 3,198 ± 448 b

LPS a 1,225 ± 112 803 ± 87 b 486 ± 2 b 522 ± 31 b

a Values are counts/min, mean ± standard error of the mean; n = 4.
b Significantly different from controls ( p < 0.05) as calculated by the authors.

Source: Hamada et al. (1998).



### Inhibition of [ 3 

### H]-thymidine uptake by stimulated spleen lymphocyte s may indicate a systemic immunosuppression by AN. Such an effect c ould also occur locally, as indicated by a reduction in the number of IgA-producing cells in a ll intestinal compartments following AN administration. The counts of IgA-producing cells were reduced by 56–77% in the duodenum, 44–67% in the jejunum, and 60–62% in the ileum. An other local effect of AN was demonstrated by the increased incorporation of BrdU into epithel ial cells of the duodenum (threefold) and ileum (1.6-fold) of AN-treated animals. This resul t indicated that the rate of cell proliferation was markedly increased following oral AN administra tion, even as a result of short-term treatment. The study authors considered this to be the result of a regenerative response to chemically induced intestinal injury and suggested that AN-induced immunosuppressive effect systemically and locally in the gut, as well as inc reases in the rate of cell proliferation, may contribute to carcinogenicity of AN in the gut.

Summary AN caused contact dermatitis in a human subject ex posed via the use of Plexidur finger splint. In mice, AN suppressed cell-mediated and h umoral immunity systemically and locally in
the intestine. Table 4-50 summarizes immunotoxicit y studies of AN.

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Table 4-50. Summary of immunotoxicity studies of A N

Test species Endpoint/effect Exposure concentration/condition Exposure duration Results References
Human subject Contact dermatitis Use of a Plexidur finger splint ND Positive patch test Balda, 1975

Study 1: Single dose of 0 or 13.5 mg/kg AN in water (oral)

225 mg/kg cyclophosphamide as positive control 3 or 5 d Increased relative spleen by 50%, decreased relative thymus weight by 42%, reduction in total leucocytes, lymphocytes, monocytes, and neutrophils. Study 2: 0 or 6.75 mg/kg-d AN in
water

225 mg/kg cyclophosphamide as positive control. 5 d Increased relative spleen weights by 25%; decreased total spenocytes by 51%; reduction in total blood leucocytes and lymphocytes by 48 and 68%, respectively. Male CD-1 mice (n = 6) Immunosuppressive

Effect

Study 3:

a. Three groups dosed with 1.35, 2.7, or 5.4 mg/kg-d AN b. Three groups dosed with 1.35, 2.7, or 5.4 mg/kg-d AN, but immunized with SRBCs on d 9 of exposure c. Three concurrent controlgroups (normal, SRBCimmunized) d. a positive control group treated intraperitoneally with cyclophosphamide (225 mg/kg) 1 d before immunization 14 d In nonimmunized mice: increased spleen weight at all doses, increased total leukocyte counts, reduced lymphocyte counts/spleen, and increased monocyte and neutrophil counts/spleen. Enlargement of mesenteric lymph nodes and intestinal Peyer’s patches, swellings in the brachial lymph nodes for all dose groups.

In the SRBC- immunized mice: viable spleen cells showed 77% increase in the 2.7 mg/kg group. Decreases in lymphocyte count, increases in neutrophilic and monocytic counts, and decreases in plaque forming cell response were observed. The LOAEL for immunotoxicity was 1.35 mg/kg-d. Ahmed et al., 1993

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Table 4-50. Summary of immunotoxicity studies of A N

Test species Endpoint/effect Exposure concentration/condition Exposure duration Results References
Male CD-mice Systemic and local

immunosuppression 2.7 mg/kg-d AN orally 5, 10, or 15 d Decrease 3 H-thymidine

incorporation into splenocytes in: (1) mice treated with mitogens con-A or LPS, suggesting systemicsuppression of cellmediated immunity, and (2) mice treated with mitogen PHA, suggesting systemic suppression of humoral immunity.

Local immunosuppression in the gut, as indicated by: (1) reduction in thenumber of IgAproducing cells in all intestinal compartments, and (2) increased proliferation of epithelial cells of the duodenum. Hamada et al., 1998.



### 4.5. MECHANISTIC DATA AND OTHER STUDIES IN SUPPORT OF THE MODE OF
ACTION
4.5.1. Mode-of-Action Studies Studies have been conducted with the primary purpo se of evaluating the potential mechanisms by which AN and/or its metabolites produ ce noncancer and cancer effects in experimental animals. Studies that investigated po tential mechanisms for noncancer effects include GI hemorrhaging, effects on Hb and metaboli sm in RBCs, neurotoxicity, oxidative stress, and immunotoxicity. Studies that investiga ted the potential mechanisms for the carcinogenicity of AN include formation of DNA addu cts, oxidative stress, intercellular communication, and cell proliferation. In addition , genotoxicity studies are described in
Section 4.5.2.

4.5.1.1. Noncancer Endpoints
4.5.1.1.1. GI hemorrhaging. Ghanayem and Ahmed (1983) administered AN to male S pragueDawley rats by both s.c. or oral routes, in each ca se observing significant gastric bleeding (see Section 4.4.1.1). The response appeared to peak at 50 mg/kg, the effect being maximal at 2 hours after a 50 mg/kg s.c. dose. Different CYP4 50 inducers had different effects: Aroclor 1254 more than doubled the effect, while PB reduced the bleeding by half. CYP450

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inhibitors SKF 525A and cobalt chloride were even m ore effective, with cobalt chloride reducing gastric bleeding to almost untreated levels. GSH d epletion by DEM did not prevent hemorrhaging. The effect was not due to cyanide re lease from AN, since KCN administration (6 mg/kg) did not induce bleeding. The results ind icated that the gastric hemorrhaging was caused by metabolic activation of AN to a reactive metabolite other than cyanide (probably CEO). As described in Section 4.4.1.1, the follow-up stu dy by Ghanayem et al. (1985) demonstrated that pretreatment of rats with sulfhyd ryl-containing compounds or atropine protected the rats from AN-induced lesions. The fi ndings suggested that modulation of muscarinic receptors by AN increased gastric acid s ecretion and caused gastric mucosal erosions.

4.5.1.1.2. Effects on Hb and metabolism in RBCs

. Farooqui and Ahmed (1983b) studied the
effect of AN on Hb and metabolism in RBCs both in v ivo and in vitro. Male Sprague-Dawley rats (three/group) were administered a single oral dose of 80 mg/kg aqueous AN, and blood was collected 1 hour after treatment. Other groups of animals were sacrificed at 3, 6, and 24 hours after dosing. Mean cell Hb concentration, hematocr it, and platelet counts were reduced to 78, 79, and 71% of the controls 1 hour after dosing . GSH levels were lowered significantly within 1 hour. Among the metabolic intermediates m easured, a reduction in the intracellular concentration of 2,3-diphosphoglyceric acid and inc reases in intracellular levels of ATP, pyruvate, and lactate were observed. The increase in the levels of pyruvate and lactate, which were end products of glycolysis, suggested an incre ase in the metabolic rate in RBCs as a result of exposure to AN (Table 4-51). A significant decr ease in the activity of 2,3-diphosphoglycerate mutase, an erythrocyte enzyme, was found in treated animals (3.61 ± 0.21 IU/g Hb in treated animals after 1 hour vs. 4.57 ± 0.23 IU/g Hb in con trols). In general, the intermediates studied
returned to normal values between 6 and 24 hours.

Table 4-51. Effect of AN on RBC metabolic intermed iates following a single oral dose

AN treatment Intermediates ( μ mol/mL blood) Control 1 hr 3 hrs 6 hrs 24 hrs 2,3-Diphosphoglycerate 3.6 ± 0.3 2.8 ± 0.2 a 3.0 ± 0.4 3.2 ± 0.3 3.7 ± 0.5 Adenosine triphosphate 0.49 ± 0.04 0.60 ± 0.05 a 0.64 ± 0.06 a 0.66 ± 0.06 a 0.58 ± 0.05 Pyruvate 58 ± 6 227 ± 21 a 187 ± 13 a 175 ± 16 a 167 ± 11 a Lactate 1,478 ± 131 9,932 ± 211 a 1,889 ± 129 a 1,955 ± 160 a 2,079 ± 151 a
GSH 1.39 ± 0.11 0.28 ± 0.02 a 0.34 ± 0.04 a 0.47 ± 0.05 a 1.27 ± 0.15

a Significantly different from controls ( p < 0.05) as calculated by the study authors.

Source: Farooqui and Ahmed (1983b).

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In another study, male Sprague-Dawley rats were tr eated with single oral doses of 46.5 mg/kg [2,3- 14 

### C]-AN (Farooqui and Ahmed, 1983b). RBC GSH concent rations were lowered to 10% of controls in 1 hour, followed by a slow recovery of 10% in 5 hours. Extensive covalent binding of AN to Hb (about 1.7 μ mol equivalents of AN bound/mL RBCs) in 1 hour
was also observed.
For the in vitro study, isolated RBCs from male Sprague-Dawley rats were incubated with 5 mmol/L AN at 37°C to investigate the ability of AN to interact covalently with Hb and deplete GSH, and the effect of such depletion on Hb (Farooqui and Ahmed, 1983b). GSH in the supernatant and in the RBCs was estimated by measur ing nonprotein sulfhydryl groups. In addition, the levels of Hb and MetHb and GSH conjug ates with AN were monitored. Incubation of rat RBCs with AN caused a depletion of more than 85% of intracellular GSH within 1 hour. No hemolysis occurred during th e incubation period. In addition, GSH was
not detected in the incubation media. Most of the GSH in the RBCs was converted to a GSH-AN conjugate, S-cyanoethyl GSH. This conjugate was present in the RBCs after 24 hours, suggesting that it was not metabolized further at l east for 24 hours. Moreover, about 6% of Hb
was converted to MetHb in 1 hour and 8% in 3 hours (Farooqui and Ahmed, 1983b). MetHb levels in controls during this time period were 0.6 1–0.87%.
The rate and extent of MetHb reduction to Hb in AN -treated RBCs was also determined to investigate if this protective mechanism against such oxidative damage to Hb was affected. Incubation of nitrite-treated RBCs (for conversion of Hb in RBCs to MetHb) with AN resulted in a significant decrease in MetHb reduction, with a 7 0% decrease in RBCs treated with 10 mM AN when compared with controls. In the same experi ment, AN initiated hemolysis of RBCs at a
concentration of <0.1 M. Farooqui and Ahmed (1983b) suggested that the effe cts of AN on RBC metabolism were related to the availability of GSH. Oxidative stre ss induced by depletion of GSH as a result of AN exposure may have stimulated the rate of RBC met abolism, based on increase in the end products of glycolysis. Another possible explanati on could be the impaired permeability of the erythrocyte membrane due to extensive covalent bind ing of AN, resulting in the retention of metabolic products. Since the levels of ATP and 2, 3-diphosphoglycerate were altered and these two intermediates regulate the oxygen dissociation curve, it was concluded that chronic exposure to AN may lead to methemoglobinemia, damage to the RBC membrane, and impaired delivery of oxygen to tissues. Farooqui et al. (1990) provided in vitro data on the effect of AN on lipid metabolism in RBCs. Three types of RBC preparations from male Sp rague-Dawley rats were incubated with AN: those containing oxyhemoglobin (HbO), those co ntaining MetHb, and those containing carboxyhemoglobin (HbCO). HbO-containing RBCs were taken directly from the RBC pellet; MetHb-containing RBCs were produced by incubating p acked RBCs with 0.5% sodium nitrite; while RBCs containing HbCO were prepared by blowing carbon monoxide over a 20%

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suspension (volume/volume [v/v]) of RBCs until the visible spectrum of red cell lysate reached a maximum at 570 nm. All preparations of RBCs were i ncubated for 1 hour with 10 mM AN and variable additions of glucose. Following incubatio n, supernatants were removed and used to estimate lipid peroxidation by measuring the concen tration of conjugated dienes, while the red cell pellets were used to determine Hb. In another set of experiments, isolated rat red cell
membranes were incubated with 25 mM AN at different temperatures. Total and Na + 

### /K +



### - ATPase activity were measured in control and AN-inc ubated red cell membranes. Incubation of HbO-containing RBCs with AN resulted in the formation of MetHb, loss of intact Hb, and membrane lipid peroxidation. The av ailability of glucose to HbO-RBC incubation reduced the formation of MetHb by 33% and the loss of intact HbO by 33% but increased lipid peroxidation by 35%. As a positive control, HbO-co ntaining RBCs were incubated with 0.1 mM t-butyl hydroperoxide, a strong GSH depleter. The formation of MetHb and non-intact Hb in the positive control was 3 and 5 times higher than that in AN-incubated RBCs. Incubation of MetHb-containing RBCs with AN also resulted in the loss of intact Hb and membrane lipid peroxidation. However, availability of glucose res ulted in only 13% increase in peroxidation of membrane lipids. Lipid peroxidation was about 3 ti mes higher in incubations of HbCOcontaining RBCs with AN, with or without glucose, t han the other two RBC preparations. The extent of lipid peroxidation in RBCs and isolated R BC membranes was dependent on the
concentrations of AN. Farooqui et al. (1990) also demonstrated an invers e relationship between GSH concentrations and lipid peroxidation in RBCs incub ated with AN. A 75% reduction in GSH
levels in RBCs was observed as a result of AN incub ation for 2 hours, with the half-life of GSH depletion being less than 22 minutes. The concentr ation of lipid peroxides increased by 274% over control levels during the same period. In addition, Farooqui et al. (1990) showed that Na + 

### /K + 

### -ATPase activity was reduced in the isolated RBC membranes incubated with AN (relea se of inorganic phosphate: 87.9 ± 9.1 vs. 145.6 ± 13.1 nmol/mg protein per hour at 37°C; and 4.3 ± 0.7 vs. 87.9 ± 9.1 nmol/mg protein per hour at 15°C). The degree of AN-induced inhibition of ATPase was temperature dependent.
The K m 

### of Na + 

### /K + 

### -ATPase (3.5 mM at 37°C) was barely affected by the AN treatment, while the
V max 

### was significantly lower (–36%) than that of contro ls. This noncompetitive inhibition of
Na + 

### /K + 

### -ATPase by AN was proposed to be the result of chan ges in the physicochemical properties of RBC membrane macromolecules subsequen t to irreversible binding of AN to membrane proteins. In summary, Farooqui et al. (1990) demonstrated th at AN induced GSH depletion, elevated lipid peroxidation, and enhanced concentra tion of MetHb in RBC, as well as inhibited
Na + 

### /K + 

### -ATPase activity in RBC membrane.

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4.5.1.1.3. Neurotoxicity. Campian et al. (2002) evaluated the capacity of AN to inactivate the important glycolytic enzyme, glyceraldehyde-3-phosp hate dehydrogenase (GAPDH) in vitro in
order to elucidate the mechanism for the acute toxi city of AN. GAPDH was incubated with AN (final concentrations ranged from 50 to 400 μ M), and the activity of GAPDH was assayed at different time points. An irreversible inhibition of GAPDH activity was obtained. Incubation of
GAPDH with 200 μ M AN resulted in 90% loss of activity in about 60 m inutes. The secondorder rate constant for inhibition of GAPDH activit y was measured as 0.2 M -1 

### s -1 

### at pH 7.4 and
37°C. The site of AN incorporation was identified by usin g matrix-assisted laser desorption ionization time-of-flight mass spectrometry to anal yze tryptic digests of control and AN-labeled GAPDH (Campian et al., 2002). Inactivation of GAPD H was due to covalent binding of AN to cysteine 149 at the active site of the enzyme. Thi s finding demonstrated the specificity of AN binding to cysteine residues and, more widely, impl ied the ability of AN to impair glycolytic ATP production in vivo. Campian et al. (2002) spec ulated that the combination of glycolytic ATP production impairment with inhibition of mitoch ondrial ATP synthesis by the AN metabolite cyanide could result in metabolic arrest . This might have profound consequences for the toxicity of AN in sensitive tissues such as the brain. In a followup study (Campian et al., 2008), male Sp rague-Dawley rats (3-5/group) were injected subcutaneously with LD 90 

### (115 mg/kg) AN and the brains of treated rats were frozen when respiration ceased via head immersion (HI) in liquid nitrogen or funnel freezing (FF) technique. Only minor decreases in ATP of 5% (FF) and 21% (HI) were found when respiration ceased, although phosphocreatine was decreased by 7 4% (FF) and 80% (HI), possibly due to inhibition of creatine kinase by AN. Campian et al . (2008) concluded that no toxicological relevant depletion of ATP occurred when respiration ceased in AN treated rats. Hence, the acute lethality of AN was not due to brain metabolic arre st. Dorman et al. (1996) investigated the mechanisms b y which AN and CEO exert neurotoxic effects in primary dissociated cerebroco rtical cell cultures prepared from GD16-18 CD rats. Mature 7-day old cultures were exposed to 0-10 mM AN or 1-2 mM CEO for 8 h at
37 ◦ 

### C. Cytotoxicity was evaluated by measuring leakage of LDH, GSH depletion, inhibition of acetylcholinesterase (AChE) and histopathology. Both AN and CEO induced dose-dependent increased i n cytoxicity. Significant increase in LDH-leakage was observed in neural cultures foll owing 8 h exposure to 2.5-10 mM AN or 0.125 – 1 mM CEO. Significant reduction in GSH onl y occurred following exposure to 5 mM AN. Thus, Dorman et al. (1996) concluded that GSH depletion probably played a limited role in the development of AN toxicity. No change in AN-in duced cytotoxicity was observed following cotreatment with the cytochrome P-450 inhibitor 1-p henylimidazole, indicating minimal
metabolism of AN to CEO in the neural cells. AChE inhibition was not observed following 8 h exposure up to 2.5 mM AN. Widespread necrosis of t he small, round cholinergic neurons was

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present in the cultures treated with 2.5 mM AN or 0 .125 mM CEO for 8 h. Astrocytes, pyramidal neurons, and bipolar neurons were mostly unaffected. On the other hand, treatment
of cell cultures with ≥ 0.6 mM cyanide resulted in extensive loss of cytoch rome oxidase activity in the large pyramidal neurons without a concomitan t increase in LDH leakage. Dorman et al. (1996) concluded that AN may selectively destroy ch olinergic neurons and induce neurotoxicity in rats, and that AN metabolism to cyanide was not a prerequisite for the development of ANinduced neurotoxicity. Satayavivad et al. (1998) provided some evidence for the alterations of central muscarinic functions from subchronic exposure to AN . Either 0, 1, or 25 mg/kg AN was injected subcutaneously to male Wistar rats (10/gro up) 5 days/week for 8 weeks. The authors studied the impact of AN on motor behavioral activi ties by using a computerized system to chart the movements of rats within the cage. The system provided information on a total of 11 motor behavioral parameters, such as distance traveled/ti me interval, resting time, time spent moving,
and number of clockwise and counterclockwise rotati ons. This test model can be used to detect subtle changes of central muscarinic receptors duri ng exposure to cholinomimetic agents. Evaluations were carried out on each animal on day 5 of weeks 1, 2, 4, 6, and 8, 1 hour after
treatment with AN.
Both doses of AN were associated with marked decrea ses in all motor activities and a concomitant increase in the resting time of treated rats compared with controls (Satayavivad et al., 1998). There was a decrease in all motor para meter values at weeks 1 and 2, but most of these effects were diminished by weeks 4 and 6. Ho wever, the effects of the high dose of AN were more pronounced and longer lasting. Thus, the incidence of clockwise and counterclockwise rotations in high-dose rats was re duced compared with controls throughout the study (for example, 0.7 ± 0.3 [high dose], 2.6 ± 0. 8 [low dose], and 2.8 ± 0.4 [controls] counterclockwise rotations/10-minute study period a fter 8 weeks). The effects of intramuscular injection of the muscarinic receptor antagonist, at ropine, and the reversible acetylcholinesterase inhibitor, physostigmine, with and without concurre nt AN administration, also were evaluated in this system. Atropine administration (10 mg/kg) wa s associated with increases in motor activity that were enhanced by AN treatment at 25 mg/kg. Ph ysostigmine (0.5 mg/kg) caused reductions in motor activity irrespective of AN administration . Satayavivad et al. (1998) concluded that AN possesses cholinomimetic effects, one of which migh t include the down-regulation of muscarinic receptors. This would explain the marked increase in the response to atropine. Since AN did not inhibit the activity of acetylcholinesterase, the c holinomimetic effect of AN might be mediated by the release of acetylcholine from nerve endings. Jacob and Ahmed (2003b) studied AN-induced neuroto xicity by exposing proliferating normal human astrocytes (NHAs) in culture to 25–400 μ M AN for 12 hours. Assessment was then made on cell viability, levels of endogenous a ntioxidants, GSH, catalase, levels of ROS, and secretion of tumor necrosis factor (TNF- α ), a cellular marker for oxidative stress and oxida tive

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damage to nuclear DNA. Treatment with 25–50 μ M AN had no significant effect on viability of the astrocytes. At 100–400 μ M AN, 15–42% reduction in cell viability was observ ed (as indicated by trypan blue exclusion). Reduced viabi lity was further substantiated by 8–40% increased cytotoxicity (as indicated by leakage of LDH). The morphology of astrocytes was normal at concentrations up to 200 μ M, but cells exposed to 400 μ M AN showed a larger number of swollen nuclei and enlarged membrane stru ctures.
Intracellular levels of GSH were not affected at 2 5 and 50 μ M AN. However, a significant dose-dependent decrease in GSH was obse rved at 100, 200, and 400 μ M AN (18, 28, and 35% lower than controls, respectively). A conc omitant increase in levels of oxidized GSH (glutathione disulfide [GSSG]) was observed (Jacob and Ahmed, 2003b). The ratio of GSH to GSSG was reduced from the control value of 37–18, 7 , 3, and 2 at 50, 100, 200, and 400 μ M AN, respectively. Compared to control level, catal ase activity increased 21% at 100 μ M AN, but
declined to 37% below control levels at 400 μ M. Significant increases in measures of oxidative str ess (four- to sevenfold increase in the generation of ROS) and oxidative DNA damage (greate r than twofold increase in 8-oxodeoxyguanosine [8-oxodG]), were observed at 20 0–400 μ M AN. Treatment at 400 μ M significantly increased the release of the inflamma tory cytokine, TNF- α , by 30% compared with controls. The observation that compromised antioxi dant defense mechanisms (depletion of glutathione, increase in GSSG, inhibition of catala se) occurred at the same exposure concentration as reduced cell viability supported t he hypothesis that oxidative stress in astrocytes was a possible mechanism for neurotoxic effects of AN exposure. In a translated Chinese study (Lu et al., 2005b), levels of monoamine neurotransmitters
and their metabolites were measured in the striatum and cerebellum of the brains of male Sprague-Dawley rats (n = 10 per group, 7 selected r andomly for measurement) exposed to 0, 50, or 200 ppm AN in drinking water for 12 weeks. The study authors estimated the administered doses to be 4.0 and 13.5 mg/kg-day for the 50 and 2 00 ppm groups, respectively. Monoamine oxidase activity in the cerebral cortex was also me asured. Compared with control values, average dopamine leve ls in the striatum were decreased by 76 and 64% in the 50 and 200 ppm groups, respect ively, and by 46 and 18% in the cerebellum. The decreases in dopamine levels were statistically significant only in the striatum. No statistically significant exposure-related chang es were observed in average levels of the dopamine metabolite, 3,4-dihydroxyphenylacetic acid , in the striatum or the cerebellum except for increased levels (by about 32%) for the 50 ppm group in the cerebellum compared with controls. Average concentrations of serotonin were decreased by about 38 and 49% in the striatum in the 50 and 200 ppm groups, respectively , and by about 41 and 68% in the cerebellum. These changes were statistically significant only i n the striatum. No statistically significant exposure-related changes were observed in average l evels of the serotonin metabolite, 5-hydroxyindoleacetic acid, in the striatum or the cerebellum, in average levels of

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norepinephrine in the two brain regions, or in aver age activities of monoamine oxidase. The observed changes in the endpoints examined in this study are of uncertain biological relevance; as such, the study does not identify NOAELs or LOAE Ls suitable for health hazard identification or dose-response assessment. Howeve r, the striatum and cerebellum are major centers for movement control, balance, and coordina tion. Thus, an abnormality in the
neurotransmitters will cause malfunction in the mov ement coordination of an organism. The study authors suggested that a decrease in dopamine will reduce the environmental adaptability of rats and provide neurotransmitter evidence for t he effect of AN exposure on neurobehavior. Serotonin plays a role in the maintenance of sleep and the emotional and psychological states of the body. Thus, reduced serotonin level in the exp osed groups may also have neurobehavioral
effect.

4.5.1.1.4. Oxidative stress. Farooqui and Ahmed (1983b) demonstrated that exposu re of rats to AN resulted in depletion of GSH and induction of ox idative stress in RBCs (see Section 4.5.1.1.2). Farooqui et al. (1990) provided in vit ro data that AN induced GSH depletion, lipid peroxidation, and enhanced concentration of MetHb i n rat RBCs. In another study, the cytotoxic effect of AN-poten tiated oxidative stress in rat alveolar macrophages was investigated (Bhooma and Venkatapra sad, 1997). When alveolar macrophages
isolated from male Wistar rats were incubated with 200 nM to 20 μ M AN at 37°C for up to 4 hours, a dose-dependent loss of viability was obs erved. Incubation of alveolar macrophages
with 10 μ M AN increased the release of H 2 

### O 2 

### by 44% when compared with controls. This effect was abolished by the addition of antioxidant enzyme s superoxide dismutase (SOD) or catalase to the incubation medium. In addition, while exposure of alveolar macrophages to 10 μ M AN resulted in 42% viability, addition of SOD exerted a marked protective effect with a resultant viability of 79%. Thus, cell injury induced by AN is mediated by the production of highly toxic
OH radicals. The role of oxidative stress and lipid peroxidatio n in the induction of the toxic effects of AN was studied by a number of other research groups . In a study designed to evaluate the possible role of free-radical-mediated lipid peroxi dation in the etiology of AN-induced acute adrenal necrosis, Silver and Szabo (1982) monitored the formation of MDA and conjugated diene concentrations in the adrenal glands and othe r tissues (brain, liver, stomach, duodenum) of female Sprague-Dawley rats treated with an i.v. dos e of 150 mg/kg AN. Controls received i.v. injections of aqueous 0.1% Tween 80. Rats were kil led at 15, 30, 60, or 90 minutes after injection of AN, and the liver, adrenal glands, bra in, stomach, and duodenum were removed. While no effects on the monitored parameters were o bserved in the mitochondria or microsomes from adrenal gland, brain, duodenal mucosa, or glan dular stomach mucosa of rats 30 minutes after injection of AN, conjugated diene concentrati ons were elevated by 60% in hepatic microsomes and 30 and 40% in gastric mitochondria a nd microsomes. Therefore, although lipid

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peroxidation is unlikely to be involved in the path ogenesis of AN-induced adrenal necrosis, AN can cause lipid peroxidation in other target organs

. The cytotoxicity and oxidative stress induced by A N were examined in cultured colonocytes from male and female Sprague-Dawley rat s (Mohamadin et al., 2005). These cells were exposed to AN in the concentration range of 0. 1–2.0 mM for 60 minutes or incubated with 1.0 mM (the concentration that reduced viability by 50%) for different time intervals up to 180 minutes and then assayed for LDH leakage, cellu lar GSH levels, and lipid peroxidation. Cell viability was reduced (assessed by trypan blue exclusion method) after 60-minute exposure to 0.5 mM AN and higher; incubation with 1.0 mM red uced viability as early as 60 minutes and by 72% at 180 minutes. Concentration-dependent inc reases in plasma membrane damage, as assessed by leakage of LDH, and enhanced lipid pero xidation (production of thiobarbituric acidreactive substances [TBARS]) were observed followin g 60-minute exposures at all levels (0.1–2 mM); exposure to 1.0 mM AN produced a 2.5-fold incr ease in leakage after 60 minutes. Significant reductions in glutathione levels resul ted from 60-minute exposure to ≥ 1.0 mM AN. The time course study revealed that, by 30 min utes, exposure to 1.0 mM AN caused a significant decrease in GSH concentration that kept decreasing until 180 minutes, when the experiment was terminated. In additional experimen ts, AN-induced membrane damage and lipid peroxidation were reduced, but not totally abolishe d, by cotreatment with thiol-containing compounds (GSH, N-acetyl-L-cysteine (NAC), and dith iothreitol (DTT)), antioxidant enzymes (SOD and catalase), as well as the iron chelator de sferrioxamine (DFO) and the hydroxyl radical scavenger DMSO. Mohamadin et al. (2005) suggested that the observed protective effects of GSH, NAC, and DTT could be attributed to direct int eraction with ROS, direct binding to toxic metabolites, and/or enhancement of cellular GSH syn thesis, while depletion of iron by DFO could indirectly prevent cell damage by inhibiting the generation of hydroxyl radical. Pretreatment of colonocytes with either SOD or cata lase inhibited LDH leakage by about 23 and 54%, respectively, when compared with colonocytes t reated with AN alone. These antioxidant enzymes reduced TBARS production that was induced b y AN by 17 and 45%, respectively.
Since these antioxidants could not restore the norm al level of LDH leakage or TBARS production, Mohamadin et al. (2005) concluded that in addition to lipid peroxidation, other factors contributed to AN-induced cytotoxicity. Mahalakshmi et al. (2003) evaluated the potential protective effect of taurine (TAU) against AN-induced oxidative stress in rat brain. Male Wistar rats (six/group) were exposed to 0 or 100 ppm AN (average intake 8–10 mg/kg-day) in drinking water for 14 or 28 days. Additional groups of rats received TAU (10 g/kg in diet) alone or along with AN treatment for 14 or 28 days. AN had no effect on BW gain or weig hts of liver or brain. AN treatment for 14 days increased levels of TBARS by about 13% in p lasma and 30% in brain and increased levels of lipid hydroperoxides by 38% in plasma and 31% in brain; values after 28 days were similar, except for a 45% increase in lipid hydrope roxides in plasma. AN exposure also

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increased the percentage of DNA fragmentation detec table in brain by 60 and 81% after 14 and 28 days, respectively. TAU completely prevented th e AN-induced increases in levels of TBARS and lipid hydroperoxides in plasma and brain, but a fforded only partial protection from AN-induced increases in DNA fragmentation, which wa s significantly increased to 30 and 19% after 14 and 28 days, respectively. These results demonstrated that, even as TAU completely prevented the formation of ROS and oxidative stress , DNA fragmentation still occurred. Thus,
other factors in addition to oxidative stress cause d DNA fragmentation as a result of AN

exposure. AN significantly reduced activity levels of enzyma tic antioxidants after 14 days (28-day values were similar to 14-day values but slightly l ower): SOD (50% lower in hemolysate, 30% lower in brain), catalase (50% in hemolysate, 62% i n brain), glutathione peroxidase (39% in hemolysate, 60% in brain), and GST (20% in hemolysa te and brain). TAU also partially protected against these AN-induced reductions of en zymatic antioxidant activities, resulting in
reductions of less than 11% in rats treated with AN and TAU for 14 days when compared with
controls. For rats treated with AN and TAU for 28 days, there was insignificant reduction of <5%. AN exposure for 14 days also lowered levels o f nonenzymatic antioxidants, such as ascorbic acid (by 30% in plasma and brain), α -tocopherol (by 40% in plasma and brain), and GSH (by 45% in plasma and 28% in brain); reductions were slightly greater for the 28-day exposure. In animals treated with TAU and AN for 1 4 days, the AN-related reductions in nonenzymatic antioxidants were less than 10% compar ed with controls. These experiments demonstrated that oral exposure to AN in drinking w ater increased oxidative stress in the brain and that TAU partly protected against AN-induced ox idative stress by increasing the activities of enzymatic antioxidants and replenishing nonenzymati c antioxidants. However, Carrera et al. (2007) were not able to re produce the results obtained by Mahalakshimi et al. (2003) when oxidative stress pa rameters were measured in Wistar rats treated with AN in vivo. Male Wistar rats (12/grou p) were treated with 0 or 200 ppm AN in drinking water for 14 days. The estimated daily do se was 30 mg/kg-day, using water factor of 0.15 L/kg-day (USEPA, 1988). Brains were excised a nd homogenized, and lipid peroxidation (as measured by nmol MDA/mg protein), catalase acti vity, GSH levels, and proteins in brain
tissue were measured. No differences were found in lipid peroxidation products, catalase activity, and reduced and oxidized GSH levels in th e control and treated rats. Carrera et al. (2007) concluded that there was no evidence of oxid ative damage in the brain of AN-treated rats
at the studied dose of AN. In another study (El-Sayed et al., 2008), the effe ct of hesperidin (HES), an antioxidant flavonoid, on AN-induced oxidative stress in rat br ain was investigated. Male Swiss rats (8/group) were treated with 50 mg/kg-day AN via ora l gavage for 28 days (Group II). Control rats received distilled water (Group I). Group III rats received 200 mg/kg-day HES i.p. for 28 days. Group IV rats received 200 mg/Kg-day HES i.p . 24 h before starting AN treatment and

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concomitantly with AN treatment. At study terminat ion, brain GSH content, MDA content, and enzymatic antioxidant parameters: SOD, CAT, glutath ione peroxidase (GSH-Px), and GST were measured. Histopathological examination was conduc ted on brain samples from two rats in each

group. Brain lipid peroxides levels measured as MDA was i ncreased by 107% in the AN-treated rats, accompanied by a 63% decrease in brain GSH co ntent as compared with controls (El-Sayed et al., 2008). On the other hand, pretreatment of rats with HES prior to AN administration
resulted in 55% reduction in brain MDA content and 183% increase in brain GSH content when compared with the AN-treated group. In addition, s ignificant decreases in enzymatic antioxidant parameters were found in the brain of AN-treated ra ts, with SOD, CAT, GSH-Px, and GST decreased by 43%, 64%, 52%, & 43%, respectively, wh en compared with controls. Pretreatment
with HES and coadministration with AN attenuated th e reduction of enzymatic antioxidants levels, resulting in elevations of SOD, CAT, GSH-Px , and GST by 73%, 169%, 197%, and 71%, respectively, when compared with the AN-treated gro up. Histopathological examination of brain sections in dicated damage to neuronal cells of the brain in AN-treated rats, as manifested by edema an d interstitial neuronal atrophy with perineuronal vacuolation. Pretreatment of the rats with HES nearly normalized the histopathological changes induced by AN. This stud y indicated that treatment of rats with 50 mg/Kg-day AN via oral gavage induced oxidative stre ss in the brain, and that pretreatment with the antioxidant HES might have protective role agai nst AN-induced oxidative stress in the brain. Zhang et al. (2002) studied the mechanisms by whic h AN induced oxidative stress and found evidence that CYP450 metabolism is required f or AN to affect the activities of antioxidant enzymes, such as catalase, xanthine oxidase, or SOD . Syrian hamster embryo (SHE) cells were incubated for 4, 24, and 48 hours with subcytoletha l doses of AN (0, 25, 50, or 75 μ g/mL), and the effects of AN on enzymatic and nonenzymatic ant ioxidants were monitored. All three concentrations of AN increased ROS (hydroxyl radica ls, measured as 2,3-dihydroxybenzoic acid formation from salicylic acid) levels in SHE cells at all time points, with concurrent depletion of GSH after 4 hours of treatment, ranging from 80 to 66% reduction. GSH levels in all ANtreatment groups returned to control values after 2 4 hours of treatment and increased only in the
SHE cells treated with 75 μ g/mL AN after 48 hours of treatment. Inhibition of the antioxidant enzymes was temporal. Decreased catalase activity was observed following treatment with 50 and 75 μ g/mL AN for 4 hours at 72 and 52%, respectively. However, catalase activity was increased with 25, 5 0, and 75 μ g/mL AN treatment for 24 hours by 82, 138, and 182%, respectively. Similar increa ses were observed with 48 hours of treatment. SOD activity was decreased only in SHE cells treate d with 75 μ g/mL AN for 4 hours. The activity of xanthine oxidase, the enzyme that g enerates the superoxide radical and hydrogen peroxide via the oxidation of hypoxanthine or xanthine by oxygen, was also monitored. Xanthine oxidase activity was increased by 47% in SHE cells treated with 75 μ g/mL

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AN for 24 hours. After 48 hours of treatment, both 50 and 75 μ g/mL AN significantly increased xanthine oxidase activity. The addition of 0.5 mM of ABT (a suicide inhibitor of CYP450) to the system prevented the AN-induced decrease in cat alase activity after 4 and 24 hours.
Cotreatment of AN with ABT also blocked the increas e in xanthine oxidase in SHE cells after
48 hours of treatment. ABT alone had no effect on catalase or xanthine oxidase activity. In addition, AN had no effect on catalase or SOD activ ities in the absence of metabolic source (SHE cell homogenate). Thus, AN-induced oxidative stress in SHE cells involved decrease of antioxidants and activation of the oxidant enzyme x anthine oxidase. Taken together, these data suggest that AN induced oxidative stress via its ox idative metabolism. Nerland et al. (2003) proposed another mechanism by which AN might induce oxidative stress in their study on the covalent binding site of AN to rat liver CAIII. Two-dimensional polyacrylamide gel electrophoresis and autoradiogra phy were used to locate proteins in male rat liver cytosol that were radiolabeled after s.c. adm inistration of 115 mg/kg of [2,3- 14 

### C]-AN to male Sprague-Dawley rats. The intensely labeled sp ots in the autoradiogram were identified as CAIII. Analysis of the trypic fragment established that only cysteine 186 in the CAIII was labeled. Thus, AN selectively bound to the cystein e 186 residue of CAIII in rat liver. Nerland et al. (2003) also showed that over 50% of rat CAIII h ad participated in scavenging the toxicant AN. CAIII has been proposed to protect cells again st oxidative stress by scavenging reactive xenobiotics, thereby reducing covalent binding to m ore critical macromolecules. Thus, AN exposure would impair this protective function by c ovalently binding to cysteine 186 of CAIII. In another study, the cytotoxicity of AN was relat ed to disturbances in intracellular ionic
homeostasis and induction of oxidative stress. Mik hutkina et al. (2004) investigated the role of
disturbance in cell Ca 2+ 

### homeostasis in AN-induced blebbing of thymocyte pl asma membrane and apotosis. Blebbing of cell membrane develops i n the initial stage of cell damage and is a sign of apoptosis and necrosis. A component of apo ptogenic and necrogenic factors on the cell
is Ca 2+ 

### imbalance, a result of disturbed activity of ion c hannels and intracellular Ca 2+ 

### stores.
Exhaustion of intracellular Ca 2+ 

### stores increases the activity of store-activated ( capacitance) Ca 2+



### channels that allow influx of Ca 2+ 

### into cells. Exhaustion of Ca 2+ 

### stores is a stimulus for apoptosis. When exposed to 5 mM AN in vitro for 1 hour

, thymocytes isolated from male albino
mice exhibited twofold increases in the incidence o f blebbing of the plasma membrane, followed by apoptosis (as detected by the expression of phos phatidylserine on the outer membrane) and necrosis (as indicated by membrane permeability to propidium iodide) (Mikhutkina et al., 2004). The initial and terminal blebbing of the plasma mem brane peaked by the 15 th 

### and 45 th 

### minutes of incubation. The dynamics of terminal blebbing cor related with the accumulation of MDA in the incubation medium. Cotreatment with compounds (e.g ., caffeine and procaine) that regulate activity of intracellular Ca 2+ 

### stores modulated the cytotoxic effect of AN, sugges ting to Mikhutkina et al. (2004) that AN induced the releas e of Ca 2+ 

### from the endoplasmic reticulum.

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Preincubation of thymoctyes with 10 μ M isoptin, a blocker of voltage-dependent ion channels, decreased AN-induced apoptosis and necros is but increased the number of cells in AN-induced secondary necrosis and decreased the int ensity of oxidative stress (as indicated by the levels of MDA). This effect was related to the ability of isoptin (an antioxidant) to suppress AN-induced generation of free radicals. Cotreatmen t of AN with 10 μ M SKF 96365, a blocker of calcium release-activated channels that were dep endent on the activity of voltage-dependent ion channels, increased the apoptogenic, but not th e necrogenic, activity of AN. (SKF96365 had low prooxidant activity.) The cells treated with S KF 96365 and AN developed intensive blebbing at various periods of incubation. Mikhutk ina et al. (2004) interpreted the results to be that isoptin, via K + 

### channels, only partially inhibited store-activated Ca 2+ 

### entry into cells through calcium release-activated channels and in turn, pro tected cells from apoptosis. However, secondary necrosis (the process associated with cel ls unable to form apoptotic bodies) developed in thymocytes with suppressed blebbing. On the oth er hand, direct inhibition of these channels with SKF 96365 completely blocked Ca 2+ 

### entry and promoted progression of apoptosis. The results of these experiments suggested that AN caus ed disturbances in intracellular calcium balance that led to plasma membrane blebbing, apopt osis, and necrosis of thymocytes. A recent study on the effects of AN on primary-cul tured astrocytes from Wistar male rats (Carrera et al., 2007) indicated that AN-induced ce llular damage was not due to oxidative stress, since antioxidants did not prevent AN-induced toxic ity. In this study, primary cultured rat astrocytes were treated for 1 hour with or without trolox (TRX) (100 μ M), TAU (5 mM), NAC (20 mM), estradiol (10 μ M), or melatonin (MEL) (10 –3 

### M, 10 –5 

### M, or 10 –7 

### M). They were then exposed to 2.5 mM AN (which induced about 40% cell death) for 24 hours. Cell viability was determined by measuring the activity of LDH release d by damaged cells into the medium. GSH
levels were also measured. Among the antioxidants included in this study, onl y NAC, a sulfhydryl donor, prevented
the decrease of the number of viable cells in the c ulture. None of the other antioxidants prevented cell death induced by AN treatment. More over, 10 –5 

### M MEL and TAU increased the toxicity of AN in astrocytes. Treatment of astrocy tes for 4 hours with AN partially depleted intracellular GSH, whereas pretreatment with 20 mM NAC recovered GSH content to the control levels. Carrera et al. (2007) concluded that prote ctive effect of NAC was due to increase in the intracellular pool of GSH, GSH conjugation with AN, decreasing the availability of AN for being metabolized to CEO and cyanide, halting the t oxicity of AN. Carrera et al. (2007) also concluded cellular toxicity induced by AN could no t be prevented only by antioxidants.

Oxidative stress summary The role of oxidative stress in AN-induced cytotox icity was evaluated in both in vitro and
in vivo studies (Mohamadin et al., 2005). AN was reported to induce oxidative stress and decreased the viability of NHAs in cell cultures (J acob and Ahmed, 2003b) and cultured rat

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colonocytes (Mohamadin et al., 2005). However, oth er causes contributed to AN-induced cytotoxicity as antioxidants could not restore the normal level of LDH leakage or TBARS production. Zhang et al. (2002) studied the mechanisms by whic h AN induced oxidative stress in SHE cells and suggested that AN induced oxidative s tress via its oxidative metabolism. Other proposed mechanisms by which AN might induce oxidat ive stress included covalent binding of AN to cysteine 186 of rat liver CAIII (Nerland et a l., 2003), and disturbances in intracellular ionic homeostasis (Mikhutkina et al., 2004). Drinking water studies in Wistar rats yielded cont radictory results. Mahalakshmi et al. (2003) reported exposure to 8–10 mg/kg-day AN signi ficantly reduced enzymatic antioxidant (SOD, glutathione peroxidase, catalase) levels in r at brain after 14 or 28 days, and that TAU prevented the AN-induced increases in levels of TBA RS and lipid hydroperoxides in plasma and brain. However, Carrera et al. (2007) were unable to reproduce the results obtained by Mahalakshimi et al. (2003) in another 14-day drinki ng water study in Wistar rats. No differences were found in lipid peroxidation products, catalase activity, and reduced and oxidized GSH
levels in the control and treated rats. Carrera et al. (2007) concluded that there was no evidence of oxidative damage in the brain of rats treated wi th 30 mg/kg-day AN for 14 days. In an oral gavage study of male Swiss albino rats, treatment of rats with 50 mg/Kg-day for 28 days induced increased levels of MDA in the brain, and decreased brain GSH content and enzymatic antioxidant levels (El-Sayed et al., 2008 ). Pretreatment with HES (200 mg/Kg, i.p.)
attenuated the effects of AN treatment.

4.5.1.1.5. Immunotoxicity. Zabrodskii et al. (2000) studied the mechanisms for cell and humoral immunosuppressive effect of AN. CBA mice w ere treated by a single s.c. injection at
one-half the LD 50 

### (28 mg/kg) of AN. One day after treatment, mice w ere tested for delayed-type hypersensitivity (DTH) reactions: α -naphthylbutyrate esterase activity in splenocytes, number of antibody-producing cells in spleen, and the paw ede ma test. AN treatment suppressed primary cell immune response, as demonstrated by a 61% redu ction of the DTH reaction (edematous paw weight). Secondary DTH response (the number of est erase-positive splenocytes) was reduced by 28%. Humoral immune response was also decreased, a s shown by a 56% reduction of the number of antibody-producing cells. The cholineste rase reactivator, bispyridinium dioxime (dipyroxime), rehabilitated paw swelling completely but only partially restored the numbers of antibody-producing cells and esterase-positive sple nocytes. The role of cytochrome c oxidase a3 in the mitocho ndrial respiration enzyme system of immunocompetent cells was evaluated using hydrogen cyanide, a metabolite of AN, and its antidote anticyan. Anticyan, an agent that convert s Hb to MetHb, also improved the DTH effects of AN but less efficiently than dipyroxime. A comb ination of both agents reversed the immunotoxic effects of AN completely. Zabrodskii e t al. (2000) suggested that AN-induced

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immunotoxic effects were the result of its antichol inesterase activity targeted at T lymphocytes and general toxicity associated with inhibition of cytochrome c oxidase a3 of the immunocytes.

4.5.1.2. Cancer Effects
4.5.1.2.1. Formation of DNA adducts. There is evidence that AN and its epoxide metabolit e, CEO, can form a number of different DNA adducts in vitro. For example, Solomon and Segal (1985) demonstrated the direct, nonenzymatic alkyla tion of calf thymus DNA by AN. Following a 40-day incubation of AN at 37°C and pH 7.4, the r eaction products were identified as cyanoethyl adducts of guanine and thymine and carbo xyethyl adducts of adenine and cytosine. The major adducts were 1-carboxyethyl adenosine (26 %), 7-cyanoethyl-guanine (26%), imidazole ring-opened 7,9-bis cyanoethyl guanine (1 9%), 3-cyanoethyl thymine (16%), and
N 6 

### -cyanoethyl adenine (8%). CEO formed a number of DNA adducts more quickly wh en incubated with DNA in vitro (Solomon et al., 1993; Yates et al., 1993; Hogy and Guengerich, 1986). When calf thymus DNA was incubated with CEO at pH 7.0–7.5 and 37°C for 3 hours (Solomon et al., 1993),
N 7 

### -(oxoethyl)guanine (110 nmol/mg DNA), N 3 

### -(2-hydroxy-2-carboxyethyl)deoxyuridine (80 nmol/mg DNA), and smaller amounts of adenine and th ymine adducts were produced. Therefore, the adducts formed from CEO were differe nt than those formed from AN. The order of reactivity with CEO was guanine > cytosine > ade nine > thymine. In addition to reacting with N7 of guanine, forming N 7 

### -(oxoethyl)guanine, CEO reacted to a great extent w ith the cytosine residue, resulting in the detection of a major addu ct, N 3 

### -(2-hydroxy-2- carboxyethyl)deoxyuridine. Solomon et al. (1993) p roposed that the uracil adduct was formed from an initial cytosine adduct from hydrolytic dea mination of cytosine to uracil. Yates et al. (1993) also characterized an adduct f ormed when calf thymus DNA was
incubated with 150 mM CEO at 37°C for 3 hours. The adduct was identified as N 3 

### -(2-cyano2-hydroxyethyl)deoxythymidine. This adduct was als o formed when 150 mM [2,3- 14 

### C]-CEO reacted with 10 mM deoxythymidine in vitro (Yates e t al., 1993). Subsequent degradation of this adduct yielded N 3 

### -(2,2-dihydroxyethyl)deoxythymidine. Similarly, Guengerich et al. (1981) showed that wh en 1 mM [1- 14 

### C]-AN and [2,3- 14 

### C]-AN were incubated at 37°C with 1.5 mg/mL calf th ymus DNA in the presence of rat liver microsomes or a reconstituted CYP450 system, DNA adducts were formed as measured by irreversible binding of radioactive label to DNA. Formation of DNA adducts was enhanced by the presence of NADPH. Only trace levels of DNA ad ducts were detected when incubated with rat brain microsomes, and the reaction was not NADP H dependent, probably due to insignificant metabolism of AN by brain microsomes. Guengerich e t al. (1981) also showed nonenzymatic irreversible binding of labeled CEO to calf thymus DNA. The extent of binding for [2,3- 14 

### C]-labeled CEO was three- to fivefold greater than that for [1- 14 

### C]-labeled CEO. Moreover, when 100 mM CEO was incubated with 50 mM adenosine for 24 hours at 37°C,

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1,N 6 

### -ethenoadenosine was formed. In another experiment , an unidentified product was formed when CEO was incubated with cytidine. Data from Peter et al. (1983a) showed the extent o f irreversible binding of AN or its metabolites to DNA to be lower after purification o f isolated DNA and RNA by column chromatography on hydroxyapatite. In their in vitr o incubation experiment, [2,3- 14 

### C]-AN was incubated with rat-liver microsomes, NADPH and DNA or RNA. Irreversible AN binding was found to be 3 nmol/hour per mg DNA, when ethanol pr ecipitation or phenol extraction of DNA was used. When the isolated DNA was further purifi ed by column chromatography on hydroxyapatite, irreversible binding was found to b e 0.15 nmol/hour per mg DNA. Peter et al. (1983a) also administered [2,3- 14 

### C]-AN intraperitoneally to male Wistar rats and mea sured the incorporation of radioactivity into hepatic RNA bas es. The amount of radiolabel from AN associated with hepatic DNA was lower than that fro m labeled vinyl chloride. However, when hepatic DNA from these treated rats was isolated and hydrolyzed, chromatography on PEI-cellulose showed two 14 

### C peaks that did not correspond to known standards. Thus, Peter et al. (1983a) concluded th at AN or its metabolites could alkylate DNA, although these DNA adducts had not yet been identif ied. Yates et al. (1994) also characterized the product s formed when 150 mM CEO reacted with 50 mg/mL nucleotides for 3 hours at 37°C in vi tro. The reaction of CEO with
5 ′ -monophosphates of deoxyguanosine, deoxyadenosine, deoxycytidine, or deoxythymidine
resulted in the formation of at least one adduct fo r each nucleotide. These CEO-nucleotide adducts were characterized as 2-cyano-2-hydroxyethy l phosphodiesters. The reaction of deoxyguanosine-5 ′ -monophosphate (dGMP) also produced a second adduct , N 7 

### -(2-cyano2-hydroxyethyl)-dGMP. Yates et al. (1994) suggeste d that the cyano-hydroxyethylphosphodiester adduct could induce single and doubl e DNA strand breaks (as observed when CEO was incubated with pBR322 plasmid DNA) via inte raction of the adduct’s β -hydroxylgroup with the DNA phosphate backbone. Irreversible binding of AN or its metabolites to D NA in vivo has also been studied. Farooqui and Ahmed (1983a) investigated the ability of [2,3- 14 

### C]-AN or its metabolites to bind to macromolecules in rats in vivo. [2,3- 14 

### C]-AN was administered in a single dose to male Sprague-Dawley rats (three to four per group) via g avage at a dose of 46.5 mg/kg in water. Animals were sacrificed at 1, 6, 24, and 48 hours a fter dosing. Organs, including liver, kidney, brain, spleen, and stomach, were dissected out and frozen rapidly. Nucleic acids extracted from the homogenates were applied to the hydroxyapatite column for separation of RNA and DNA fractions. Radioactivity was detected in the extra cts of RNA and DNA from liver, stomach, and brain. Bound radioactivity (as pmol equivalent AN/ mg DNA) to DNA in the brain was the highest at 24 hours (119 pmol/mg DNA), followed by stomach (81 pmol/mg DNA), and liver (25 pmol/mg DNA). Bound radioactivity in all three organs plateaued at 24 hours and remained unchanged thereafter. RNA from liver showed the hi ghest amount of radioactivity, followed by

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brain and stomach. Bound radioactivity in liver RN A peaked at 6 hours after dosing, whereas
RNA from the brain and stomach showed maximal radio activity at 24 hours. Binding to proteins was extensive and time dependent. In the first hou r after oral dosing, the highest protein binding occurred in spleen and stomach, followed by liver, kidney, and brain. After 6 hours, protein binding plateaued until 48 hours. At 6 hours, the highest protein binding occurred in the spleen, followed by liver, stomach, and kidney, with brain having the lowest protein binding. The study authors developed numerical indices for the AN-deri ved DNA alkylation; covalent binding indices were 5.9, 51.9, and 65.3 for liver, stomach , and brain, respectively, after 24 hours. Ahmed et al. (1992a) demonstrated the covalent bin ding of radiolabel from [2,3- 14 

### C]-AN to testicular DNA after a single oral dose of 46.5 mg/kg of [2,3- 14 

### C]-AN to male SpragueDawley rats. In a time course study, bound activit y was shown to be greatest after 30 minutes (8.93 ± 0.80 μ mol AN bound/mol nucleotide), with covalent binding index of 10.15. Using an identical experimental protocol, Ahmed et al. (1992 b) demonstrated the capacity of AN to bind covalently to DNA in the lung. Covalent binding of radioactivity to DNA increased with time and was maximum at 12 hours after a single oral dos e, with a covalent binding index of 3.48. Binding was associated with a 55–72% decrease in re plicative DNA synthesis at time points up to 24 hours after dosing. Hogy (1986) and Hogy and Guengerich (1986) studied the in vivo interaction of AN and
CEO with DNA. Three male F344 rats were administer ed AN (50 mg/kg, i.p.); three more rats were administered CEO (6 mg/kg, i.p.). The rats we re sacrificed after 2 hours, and the brain and
livers were removed and frozen. DNA and RNA were i solated from these tissues. For detection
of N 7 

### -(2-oxoethyl)guanine, DNA samples were reductively tritiated with NaB 3 

### H 4 

### ; the adduct was released by neutral thermal hydrolysis and puri fied by thin-layer chromatography for subsequent quantitation by liquid scintillation cou nting. N 7 

### -(2-oxoethyl)guanine was detected in
liver DNA at 3.1 × 10 7 

### nucleotides per alkylation in AN-treated rats and 6.9 × 10 7 

### nucleotides per alkylation in CEO-treated rats (Table 4-52). F or brain DNA, N 7 

### -(2-oxoethyl)guanine was
detected at 2.4 × 10 8 

### nucleotides per alkylation in AN-treated rats and at 1.1 × 10 9 

### nucleotides per alkylation for CEO-treated rats. The values ob tained from the brain DNA samples were near the limit of detection. Thus, the presence of thes e adducts in the brain could not be unequivocally verified.

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Table 4-52. Detection of N 7 

### -(2-oxoethyl)guanine after i.p. administration of 50 mg/kg AN or CEO to male F344 rats

Formation of N 7 -(2-oxoethyl)guanine
Liver Brain Compound fmol/mg DNA Nucleotides/alkylation fmol/mg DNA Nucleotides/alkylation
AN 109 ± 71 3.1 × 10 7 14 2.4 × 10 8

CEO 48 ± 15 6.9 × 10 7 3 1.1 × 10 9

Source: Hogy (1986).



### In the same study (Hogy, 1986; Hogy and Guengerich , 1986), rat DNA samples were also analyzed by HPLC with a fluorescence detector for 1,N 6 

### -ethenoadenosine and 1,N 6 

### -ethenodeoxyadenosine. These adducts were not dete cted with limits of detection estimated to be 3 pmol/mg DNA and 1 pmol/mg RNA, respectively

. In another study, Prokopczyk et al. (1988) adminis tered 50 or 100 mg/kg s.c. AN to male F344 rats (10/group). DNA was isolated from liver and brain after 2 hours (50 mg/kg group) or 6 hours (100 mg/kg AN). An HPLC assay with fluores cence detector was used to detect 7-(2-cyanoethyl)guanine (detection limit: 1 per 5 × 10 4 

### guanine) and O 6 

### -cyanoethylguanine (detection limit: 1 per 7 × 10 4 

### guanine). Neither adduct was detected. These two adducts were not formed when CEO was incubated with calf thymus DNA in vitro (Solomon et al., 1993).

4.5.1.2.2. Oxidative stress. Jiang et al. (1998) evaluated the ability of AN to induce oxidative stress in the brain cortex of rats. Male Sprague-D awley rats (at least nine/group) were exposed to 0, 5, 50, 100, or 200 ppm AN in drinking water f or either 14, 28, or 90 days. These
concentrations were selected from those used in chr onic bioassays (see Section 4.2.1.2). As calculated by the study authors, average daily dose s of 0, 0.6, 5.1, 8.9, or 15.0 mg/kg-day were ingested over the 90-day treatment period by the co ntrol to high-dose groups, respectively. At study termination, brains and livers were weighed. The livers and brain cortexes from six rats/group were evaluated for the following oxidati ve endpoints: oxidative DNA damage (8-hydroxy-2 ′ -deoxyguanosine levels), lipid peroxidation (MDA le vels), levels of nonenzymatic antioxidants (glutathione and vitamin E), and the a ctivities of enzymatic antioxidants (catalase, SOD, and glutathione peroxidases). 8-Hydroxy-2 ′ -deoxyguanosine has also been referred to as 8-oxo-7,8-dihyro-2 ′ -guanosine (Murata et al., 2001) and 8-oxodeoxyguan osine (Whysner et al., 1998a) and will be referred to as 8-oxodG in this d ocument. ROS formation—as measured by the formation of 2,3-dihydrobenzoic acid from salic ylic acid in brain cortex and liver—were evaluated in three rats/group injected with salicyl ic acid in saline 12 hours before termination. In rats exposed to AN at concentrations as high as 200 ppm for up to 90 days, no effects were noted on viability. A statistically significa nt reduction of 9% in BW was observed in the 200 ppm group after 90 days. No differences were o bserved in brain or liver weights nor were

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any of the measures of oxidative damage or antioxid ant levels in the liver for all groups at any sampling times. AN exposure resulted in statistica lly significant increases in oxidative stress parameters and decreases in antioxidants levels in the brain cortex. Levels of hydroxy free radicals (ROS) were significantly elevated in a dos e-related manner in the 50–200 ppm groups, beginning at 14 days and persisting until the 90-da y time point; at 200 ppm, the increase was approximately fivefold over controls. Levels of 8- oxodG in the cellular DNA of brain cortex were significantly elevated (three- to fourfold com pared with controls) in a dose-related manner in the 100 and 200 ppm groups, beginning at 14 days of exposure, and two- to threefold in the 50 ppm group, beginning after 28 days of exposure. MDA levels were significantly increased (1.5-fold) in the 200 ppm group after 14 days but a t no other time point. Slight but significant decreases in levels of vitam in E (about 20%) and glutathione (about 20%) in the brain cortex were observed in the 50–20 0 ppm groups but were statistically significant only at the 14-day time point. Statist ically significant, dose-dependent reductions (by up to 60%) in catalase activity were observed in br ain cortex at all exposure levels after 14 days,

at ≥ 100 ppm after 28 days, and at ≥ 50 ppm after 90 days; the transient effect at 5 ppm was not considered to be biologically significant. Reducti ons in SOD levels in the brain (by up to 30% at 200 ppm) were dose related and statistically signif icant at ≥ 50 ppm after 14 days and at 200 ppm after 28 or 90 days. In this study, a NOAEL of 5 p pm (0.6 mg/kg-day) and a LOAEL of 50 ppm (5.1 mg/kg-day) were identified for increases in le vels of oxidative damage (increased ROS and DNA damage) and reductions in the antioxidant enzym es catalase and SOD in the brain of rats exposed to AN in drinking water. Jiang et al. (199 8) suggested that observed oxidative stress in rat brain cortex following AN treatment could be in duced by: (1) direct generation of free radicals from AN or its metabolites, (2) binding of AN or its metabolites to free radical scavengers (e.g., GSH, vitamin E), (3) modulation o f the activity and/or synthesis of antioxidant enzymes (e.g., SOD, catalase), and/or (4) interfere nce with electron flow through the respiratory chain via inhibition of cytochrome C oxidase by the cyanide ion, a metabolite of AN. However, these potential mechanisms need to be further inves tigated. In a follow up study, Pu et al. (2009) examined the potential for AN to induce oxidative DNA damage in rats. These investigators also exami ned whether blood could serve as a surrogate for the biomonitoring of oxidative stress induced by AN in target tissues (in particular brain) of exposed populations. Male Sprague-Dawley rats (9/group) were treated with 0, 3, 30, 100 or 200 ppm AN in drinking water for 28 days. N -acetyl cysteine (NAC), an acetylated precursor of glutathione, was coadministered at a d ietary concentration of 0.3% to one group of rats receiving 200 ppm AN in drinking water to eval uate its protective effect against potential
AN-induced oxidative stress. At the end of treatme nt, animals were sacrificed and blood samples were collected immediately. The alkaline c omet assay was used as a measure of direct DNA damage in 3 rats/group, and the formamidopyrimi dine DNA glycosylase (fpg)-modified comet assay was used as a measure oxidative DNA dam age in brain cortex and white blood cells

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(WBCs) of different treatment groups. 8-oxodG leve ls in brain tissues and WBCs were also measured by HPLC with electrochemical detection. 2 ,3-DHBA was measured in WBCs and brain tissues for the presence of ROS. Pu et al. (2009) observed no increase in DNA damage in rat WBC and brain tissue following exposure to AN with or without NAC coadmi nistration using the alkaline comet assay. Dose-dependent increases in DNA damage were observe d in rat WBC and brain following exposure to AN using the fpg-modified alkaline come t assay. These increases in DNA damage were not observed in WBC and brain of rats exposed to 200 ppm AN and NAC. Pu et al. (2009) interpreted the results as indicative of oxidative DNA damage in AN-exposed rats, and further that the absence of oxidative DNA damage in rats co administered NAC reflected the antioxidant action of NAC. Significant increases in the level of 8-oxodG were found in WBC and brain of rats treated with 100 and 200 ppm AN; no increase w as observed in rats treated with 200 ppm AN and NAC. 2,3-DHBA, a measure of ROS formation, was increased in the WBC of rats treated with AN in a dose-dependent manner, but was not detectable in the brain of treated rats. In addition, the ratios of reduced to oxidized glut athione (GSH/GSSG) were reported to be significantly lower in rats treated with 30, 100 an d 200 ppm AN, but not in a dose dependent manner. Pu et al. (2009) concluded that AN induced oxidative stress and DNA damage in male Sprague-Dawley rats and that the fpg-modified comet assay in WBC correlated with target tissue oxidative DNA damage. EPA identified certain issues with study design and choice of analytical methods that raise questions about the interpretation of the fin dings by Pu et al. (2009). First, Pu et al. (2009) stated that direct DNA damage was not detected in r at WBC and brain of AN-exposed rats based on results in the standard alkaline comet assay. T he standard comet assay detects single and double strand breaks, cross link, oxidative DNA dam age, apurinic/pyrimidinic sites and DNA repair (Smith et al., 2006; Collins, 2007). The in duction of other types of DNA damage not detected by the comet assay cannot be precluded. Second, Pu et al. (2009) utilized the fpg-modified comet assay to detect oxidative DNA damage induced by AN; however, this assay is not sp ecific for the detection of oxidative DNA damage, as this assay also detects alkylation DNA d amage (Speit et al., 2004; Smith et al., 2006). The fpg-modified comet assay has been shown to be e specially sensitive for the detection of DNA damage by N-7 guanine alkylation, which was res ponsible for the observed DNA damage by alkylating agents methylmethanesulfonate (MMS) a nd ethylmethanesulfonate (EMS) (Speit et al., 2004). N-7 guanine adduct was detected in liv er and brain (at the limit of detection) of ANtreated rats (see Section 4.5.1.2.1). Thus, the ob served DNA damage using the fpg-modified comet assay in Pu et al. (2009) cannot necessarily be attributed to oxidative DNA damage, but could also be due to N-7 guanine alkylation. Third, NAC was used by Pu et al. (2009) to demonstr ate the effect of an antioxidant to protect against observed DNA damage. It should be noted that NAC is a precursor of

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glutathione. Glutathione conjugates with AN to N-a cetyl-S-(2-cyanoethyl)cysteine, which can then be excreted in the urine. Glutathione conjuga tion is therefore a detoxification pathway for AN. Thus, the reduction in DNA damage in AN-treate d rats coadministered with NAC observed by Pu et al. (2009) may, in fact, reflect increased detoxification of AN and reduced availability of AN for oxidation to CEO. The protective effect of NAC on AN toxicity was demonstrated by Carrera et al. (2007) (see Section 4.5.1.1.4). Fou rth, Pu et al. (2009) reported that the ratios of reduced to oxidized glutathione (GSH/GSSH) were dec reased in the brain cortex of rats treated with AN in drinking water at concentrations of 30, 100, and 200 ppm for 28 days. This reduction was not dose related; the GSH/GSSG ratio was similar in all three exposure groups [Figure 8 in Pu et al. (2009)]. GSH/GSSG provided the redox status in the brain cortex. It should be noted that in the 2-year drinking water s tudy in Sprague-Dawley rats involving AN drinking water concentrations of 30, 100, and 300 p mm (Quast, 2002), the incidence of tumors increased with increasing exposure. The absence of a dose-related decrease in GSH/GSSG ratio observed by Pu et al. (2009) does not parallel the dose-related increase in tumor incidence observed in AN-exposed rats by Quast (2002). Thus, the GSH/GSSG ratio is not concordant
with an oxidative stress mode of action for the car cinogenicity of AN. Fifth, no ROS was detected in the brain of AN exposed rats in Pu et a l. (2009), as no 2,3-DHBA was detected in the
brain of AN-treated rats. Whysner et al. (1998a) also evaluated oxidative DN A damage (increased levels of 8-oxodG) in the brains of male Sprague-Dawley and F 344 rats exposed to AN in drinking water for durations of either 21 or 94 days. In the firs t experiment, male Sprague-Dawley rats (20/group) were exposed to 0, 3, 30, or 300 ppm AN in drinking water for 21 days (Whysner et al.,1998a). Based on default values for the BW of male Sprague-Dawley rats in a subchronic study (0.267 kg) and an allometric equation linking water consumption to BW (U.S. EPA, 1988), the average intakes of AN were calculated as approx imately 0, 0.43, 4.3, and 43 mg/kg-day for the control to high-dose groups, respectively. At termination, brains, livers, and forestomachs were excised from five rats/group each for DNA isol ation. These tissues were analyzed for GSH, cyst(e)ine, and 8-oxodG levels in nuclear DNA. TBARS levels in brains were determined for another five rats/group. Brain homogenate from another five rats/group were analyzed for cytochrome oxidase activity (in the mitochondria fr action), catalase (in supernatant), and glutathione peroxidase (in homogenate). Tissues fr om another five rats/group were examined for histopathology, but results were to be published se parately. In rats exposed to 30 or 300 ppm AN, statistically significant increases in 8-oxodG levels in nuclear DNA were measured in brains (approximate ly twofold increase compared with control values for both dose groups) and livers (approximat ely 1.4-fold increase for both dose groups when compared with controls). Also observed in the 300 ppm dose group were approximately twofold increases in the levels of glutathione and cyst(e)ine in the forestomach, and approximately 50% increase in cyst(e)ine level in t he brain. There were no exposure-related

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effects on levels of glutathione in the brain and l iver or on levels of cytochrome oxidase, catalase, glutathione peroxidase, or TBARS in the b rain. However, glutathione level in the
forestomach was increased about 1.8-fold in the 300 ppm dose group compared with controls. In this study, a NOAEL of 3 ppm (0.43 mg/kg-day) and a LOAEL of 30 ppm (4.3 mg/kg-day) were identified for increased oxidative DNA damage in th e brains and livers of Sprague-Dawley rats. Whysner et al. (1998a) concluded that the formation of 8-oxodG from AN exposure did not involve disruption of antioxidant defense or lipid peroxidation. In addition, the absence of effect on brain cytochrome oxidase activity in exposed rat s indicated lack of inhibition by cyanide, a metabolite of AN. Thus, Whysner et al. (1998a) con cluded that cyanide-induced metabolic hypoxia did not appear to be involved in the genera tion of ROS by AN administered in drinking

water. Whysner et al. (1998a) conducted a parallel 21-day drinking water study in male F344 rats (10/group). Concentrations of AN in drinking water were of 0, 1, 3, 10, 30, or 100 ppm.
Based on default values for the BW of male F344 rat s in a subchronic study (0.18 kg) and an allometric equation linking water consumption to BW (U.S. EPA, 1988), the average doses of AN were estimated at 0, 0.16, 0.47, 1.6, 4.7, and 1 5.6 mg/kg-day in the control to high-dose groups. An additional group of rats received 5 mg methylnitrosourea (MNU) per kg/week via i.v. injection. At termination, rat brains were ev aluated for levels of 8-oxodG in nuclear DNA, cytochrome oxidase, glutathione, and cyst(e)ine. L evels of all these parameters in the brains of AN-exposed rats and MNU-exposed rats were not signi ficantly different from controls. The levels of 8-oxodG in the brains of 3–100 ppm AN dos e groups were the same, about 1.3-fold higher than control values. However, the increases were not statistically significant. The highest drinking water concentration of 100 ppm AN (15.6 mg /kg-day) was a NOAEL for oxidative effects in the brains of F344 rats (i.e., oxidative stress was not demonstrated in the brains of F344 rats even at the highest dose of 15.6 mg/kg-day). In the subchronic experiment by Whysner et al. (199 8a), male Sprague-Dawley rats (10 rats/group) were exposed to 0 or 100 ppm AN in drinking water for 3, 10, 31, or 94 days. Two additional groups of Sprague-Dawley rats (six/g roup) were exposed to 5 mg MNU/kg/week or 5 mg MNU/kg/week + 100 ppm AN. Brains were assa yed for levels of 8-oxodG, cytochrome oxidase, and glutathione. Levels of 8-oxodG were a lso measured in the livers of rats exposed for 3, 10, or 94 days. No effects on brain levels of cytochrome oxidase or glutathione were observed in any dose group up to 94 days. The 8-oxodG levels were significantly increased by 77% following exposure to 100 ppm AN for 3, 10, and 94 days. Adm inistration of 5 mg/kg MNU (a DNAreactive carcinogen that produces glial cell tumors in rats) did not increase the level of 8-oxodG
in the brain of treated rats but increased 8-oxodG in the liver after 10 days. However, coadministration of 100 ppm AN and MNU increased th e 8-oxodG level in the brain after 31 and 94 days when compared with controls. Whysner et al . (1998a) proposed that AN-induced

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generation of ROS and resultant oxidative DNA damag e represented one possible mode of action for the neoplastic process in the rat brain. Howev er, as discussed in Section 4.7.3.3.1, results from this study did not support the proposed oxidat ive stress mode of action. The ability of AN to induce oxidative stress and o xidative DNA damage was also studied in a rat glial cell line and cultured rat hepatocyt es in vitro (Kamendulis et al., 1999a). In paralle l experiments, DITNC1 rat astrocytes and rat hepatocy tes were incubated with sublethal concentrations (up to 1 mM) AN in vitro for 4 or 24 hours. The 8-oxodG levels in total cel lular (nuclear and mitochondrial) DNA, generation of ROS (measured as increase in generation of 2,3-dihydroxybenzoic acid in salicylic acid), level s of the lipid peroxidation product MDA, GSH, and antioxidant enzymes activity were measured at t he end of the incubation period. In rat astrocytes, significant increases (up to 3. 8-fold) in the production of 8-oxodG over control was observed after 4 hours and up to 3.9-fo ld after 24 hours. No increase in 8-oxodG formation was observed in rat hepatocytes at all AN concentrations and time examined. The induction of 8-oxodG by AN in rat astrocytes was re versible. Following removal of AN after 24 hours of treatment, 8-oxodG levels returned to c ontrol values at all studied concentrations in 24 hours. Intercellular production of ROS was foun d to be increased 2- to 2.6-fold after 4 and
24 hours at 0.1 and 1.0 mM AN. No increase in ROS generation was found in rat hepatocytes at any AN concentration or exposure duration. On the other hand, no significant change in MDA formation (as indicator of lipid peroxidation) was found in either cell type following treatment
with AN. A significant decrease in cellular GSH levels was observed in rat astrocytes treated with 0.1 and 1.0 mM AN for 4 hours (25–36% of control) a nd 24 hour (43–61% of control) and in SOD activity in astrocytes treated for 4 hours with 1 mM AN (39% reduction over control) and for 24 hours with 0.1 and 1 mM AN (38–40% reduction over control). In contrast, no significant decrease in catalase and glutathione peroxidase act ivities was observed in treated astrocytes. Cotreatment with L-2-oxothiazolidine-4-carboxylic a cid (OTC), a precursor to GSH biosynthesis, or with vitamin E, an antioxidant, re duced 8-oxodG and ROS formation induced by
AN treatment. These effects were not evident in is olated hepatocytes treated with AN. Results from this study were in agreement with results from the in vivo study by Jiang et al. (1998) on rat brain cortex. Kamendulis et al. (1999a) suggested that, since the formation of 8-oxodG and ROS observed after AN treatment in this study was tempo ral, dose dependent, and reversible following removal of AN in the culture medium, the se are established properties of tumorpromoting agents. Kamendulis et al. (1999a) propos ed that AN-induced astrocytomas in rats were produced via tumor promotion mechanisms. Jacob and Ahmed (2003b) also demonstrated the abil ity of AN to induce oxidative stress and oxidative DNA damage in NHA culture (see Sectio n 4.5.1.1.3). Pu et al. (2006) measured direct and oxidative DNA damage in cultured D1 TNC1 rat astrocytes treated with 0–2.5 mM AN for 24 hours. Direct DNA damage was measured by the

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comet assay, and oxidative DNA damage was measured with a modified comet assay that included enzymatic digestion with formamidopyrimidi ne glycosylase. 7-Ethoxyresorufin-Odeethylase (EROD) and CYP2E1 activities in the astr ocytes were measured. At 2.5 mM AN, a 40% decrease in cell viability was observed. No increase in direct DNA damage (measured as increase in tail moment) wa s observed at any AN concentration. Hydrogen peroxide (20 μ M) was used as positive control, and significant in crease in DNA damage was found. On the other hand, a threefold i ncrease in oxidative DNA damage was observed in astrocytes treated with 1 mM AN. Suppl ementation of 1 mM AN with three different antioxidants—vitamin E (150 μ M), TRX (water-soluble analog of vitamin E, 150 μ M), and epigallocathechin-3 gallate (a polyphenol from green tea, 5 μ M)—reduced AN-induced oxidative DNA damage by 65, 54, and 65%, respective ly. As expected, only low level CYP2E1 activity was me asured in the astrocytes and was about 10% of that measured in mouse liver. EROD (a n indicator of CYP1A) activity was measured in rat astrocytes and was about 500-fold h igher than that for CYP2E1. In addition, a
90% reduction in the activities of EROD and CYP2E1 was observed when the astrocytes were
cotreated with AN and 0.5 mM ABT for 24 hours. Cot reatment of astrocytes with 1 mM AN and 0.5 mM ABT also prevented the increase in oxidative DNA damage induced by AN, indicating the metabolism of AN by P450 was required for the p roduction of oxidative stress. GSH depletion induced by 4 and 24 hours of treatments w ith DL-buthionine [S,R]-sulfoximine, a
selective inhibitor of γ -glutamylcysteine synthetase, enhanced the oxidativ e DNA damage induced by AN by 44–160% over control). On the oth er hand, cotreatment with 2.5 mM OTC, a precursor for glutathione biosynthesis, reduced AN- induced oxidative DNA damage by 63–85%. Exposure to 0.1–0.5 mM cyanide also increased oxida tive DNA damage (Pu et al., 2006). EPA has identified issues in the study design, ana lytical methods, and data interpretation in Pu et al. (2006). First, as mentioned previousl y in the discussion of Pu et al. (2009), the alkaline comet assay measures DNA strand breaks and alkali-labile sites, and is not limited to the detection of direct DNA damage only. For the alkal ine comet assay, Pu et al. (2006) used hydrogen peroxide as a positive control, demonstrat ing that this assay is not limited to detecting direct DNA damage, but also oxidative DNA damage. Second, Pu et al. (2006) used the fpgmodified comet assay for detection of oxidative DNA damage. As discussed previously, the fpgmodified comet assay is not specific for the detect ion of oxidative DNA damage. Third, CYP2E1 level in astrocytes was known to be low and was found to be about 10% that found in
the mouse liver. Since bioactivation of AN to CEO via CYP2E1 is needed for direct DNA damage to be detected, it is not surprising that di rect DNA damage could not be detected in astrocytes treated with AN (although oxidative DNA damage could have been detected in the alkaline comet assay). As discussed previously in Section 3, CEO is a relatively stable reactive metabolite, with a half-life of about 2 hours; ther efore, most of the CEO detected in rat brain is presumed to be formed in the liver of rats treated with AN and transported to the rat brain.

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Hence, direct DNA damage could not be detected in t his in vitro study. Another weakness in this study concerns the selection of the positive c ontrol. A carcinogen that needs bioactivation
via CYP2E1 to form a reactive metabolite and induce DNA damage would have served as a better positive control than hydrogen peroxide, whi ch does not require bioactivation. Therefore, the findings reported in this in vitro study are no t anticipated to predict what can occur in vivo. Murata et al. (2001) investigated the enhancing eff ect of AN on the formation of 8-oxodG in calf thymus DNA, induced by hydrogen per oxide (H 2 

### O 2 

### ) and Cu(II). Calf thymus
DNA was incubated with various concentrations of H 2 

### O 2 

### plus CuCl 2 

### in the presence or absence of AN for 30 minutes. The level of Cu(II)-mediated 8-oxodG formation increased with increasing concentration of H 2 

### O 2 

### . The addition of AN (0.1–0.5%) enhanced the forma tion of 8-oxodG by hydrogen peroxide and Cu(II) in a dose-d ependent manner, whereas AN itself did not cause DNA damage. The enhancing effect of AN w as more marked in double-stranded than in single-stranded DNA. Further experiments with [ 32 

### P]-labeled DNA showed that addition of AN enhanced the site-specific DNA damage at guanine residues, particularly at the 5 ′ -site of the GG and GGG sequences while H 2 

### O 2 

### /Cu(II) induced piperidine-labile sites at thymine, cytosine, and guanine residues. Electron spin resonance spec troscopy showed that a nitrogen-centered radical was generated from AN during incubation wit h hydrogen peroxide and Cu(II). Murata et al. (2001) proposed that AN enhanced H 2 

### O 2 

### -mediated DNA damage via nitrogen-centered radical formation. Thus, AN may enhance endogenous oxidative stress, although AN itself does not have the ability to induce oxidative DNA damage

.

4.5.1.2.3. Intercellular communication. Kamendulis et al. (1999b) investigated the effect o f AN on gap junction intercellular communication (GJI C) in D1 TNC1 astrocytes (a rat astrocyte transformed cell line) and primary rat hepatocytes in culture. Noncytolethal concentrations of AN (0.01–1.0 mmol/L) were incubated with D1 TNC1 as trocytes or primary rat hepatocytes. GJIC was determined by microinjection of lucifer ye llow CH into cells. Dye coupling was quantitated by determining the number of recipient cells in contact with microinjected cells that showed communication. The reversibility of AN inhi bition of GJIC was also evaluated by replacement of AN with fresh medium. Following 2 hours of treatment, AN at 0.1 and 1 mmo l/L inhibited GJIC in D1 TNC1 astrocytes, which were putative target cells. Afte r treatments for 4 and 24 hours, all concentrations of AN (0.01–1.0 mmol/L) inhibited GJ IC. The inhibitory effect of AN in this system was dose dependent at all time points, rever sible by removal of AN, and partially suppressed by the presence of antioxidants such as vitamin E (0.1 mmol/L). After treatment with both vitamin E and AN for 24 hours, inhibition of G JIC was reduced by 23%. On the other hand, AN did not inhibit GJIC in primary cultured h epatocytes at all concentrations and
durations of treatment.

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AN also caused a concentration-dependent decrease i n cellular GSH content in both D1 TNC1 astrocytes and rat hepatocytes (Kamendulis et al., 1999b). Cotreatment with 5 mmol/L OTC, a precursor of GSH synthesis, reduced inhibition of GJIC by AN in D1 TNC1 astrocytes following 4 and 24 hours of exposure, wi th the greatest reduction observed at 1.0 mmol/L AN (up to 68%). However, depleting GSH by L-BSO (an inhibitor of intracellular GSH synthesis) alone without AN did not affect GJIC in rat astrocytes. Thus, depletion of GSH alone in astrocytes was not sufficient for the obse rved decrease in GJIC by AN. Inhibition of intercellular communication by AN was implied in an inhibition of metabolic cooperation assay. Two studies (Elmore e t al., 1985; Umeda et al., 1985) evaluated AN by using the Chinese hamster V79 cells, which ar e 6-thioguanine (6-TG) sensitive and 6-TG-resistant cloned cells that are the hypoxanthi ne guanine phosphoribosyl transferase (hprt – 

### ) mutant of the V79 cell line. The hprt – 

### mutant cannot phosphorylate several purine analogu es, including 6-TG, and are therefore resistant to cell killing by the purine analogue. When the WT cells are cultured at a density that permits freque nt contact with the mutant cells, metabolic cooperation (i.e., gap junction formed between thes e cells) allows the transfer of nutrients and phosphorylated purine analogue from the WT cells to the mutant cells and decreases probability of recovery of the mutant cells in purine analog se lective medium. The principle of the assay is based on the fact that recovery of 6-TG-resistant c ells cocultivated with 6-TG-sensitive cells in 6-TG-containing medium increased by addition of com pounds that inhibit metabolic cooperation. This assay evaluates if the test agen t can modulate gap junctional communication. AN inhibited gap junction formation slightly and do se dependently (Umeda et al., 1985). Average recovery of the mutant cells was 22% in the control, 33% at 1 mM AN, and 39% at 2 mM AN. Umeda et al. (1985) considered AN as posi tive in the metabolic cooperation assay. In the study by Elmore et al. (1985), AN produced p ositive responses at noncytotoxic
concentrations of 10–50 μ g/mL after incubation for 3 days.

4.5.1.2.4. Cell proliferation. Ghanayem et al. (1997) examined the effects of AN o n forestomach cell proliferation and apoptosis in mal e F344 rats (12/group) administered either 0, 0.22, or 0.43 mmol/kg (0, 11.67, or 22.8 mg/kg) by gavage for 6 weeks. Six rats from each dose group were used to assess BrdU incorporation in the stomach, the remaining six rats from each group were used to assess BrdU incorporation in hep atocytes. Proliferation of forestomach squamous epithelial cells was evaluated with light microscopy by determining the number of cells (nuclei) per unit length muscularis and by qu antitating BrdU-stained cells. AN was shown to induce a dose-dependent increase i n epithelial cell proliferation in the forestomach, as determined by the incorporation of BrdU into S-phase DNA. The increase in forestomach mucosal cell proliferation was signific ant at both the low and high doses of AN. No cellular proliferation was detected in the liver an d glandular stomach, which are not target organs of AN carcinogenicity.

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There was an associated increase in the thickness (hyperplasia) of the forestomach squamous mucosa, also possibly indicative of enhanc ed cell proliferation. Forestomach hyperplasia (expressed as the increase in the total number of epithelial cells per mm muscularis) was significant in the high-dose group and was abou t 60% above vehicle-treated controls. Hyperplasia in the low-dose group was only 7% above controls and was statistically insignificant. The effects of AN on cellular proli feration in the forestomach of treated rats were also evaluated by quantitative determination of Brd U incorporation into S-phase DNA, using immunohistochemical staining. The increase in fore stomach mucosal cell proliferation was significant at both the low- and high-dose groups. In addition, the effect of AN on apoptosis was determined by in situ end labeling of tissue sections. Apoptotic bodies were observed in the forestomach of rats treated with high-dose AN. No increase in apoptosis was detected in the liver or glandular stomach of control or treated ra ts. Thus, AN induced a significant increase in forestomach apoptosis at the high dose, coupled wit h an increase in hyperplasia. Ghanayem et al. (1997) proposed that disruption of the normal balance between cell proliferation and apoptosis in favor of enhanced fo restomach cell proliferation (as reflected by hyperplasia of the forestomach epitheilium) probabl y contributed to the pathogenesis of AN-induced forestomach tumors. This suggestion was supported by the observations that cell proliferation in forestomach squamous mucosa of tre ated rats occurred at doses that caused forestomach tumors in rats and that cell proliferat ion was selective and only occurred in the target organ forestomach but not in liver. In a recent study, Chantara et al. (2006) evaluate d whether AN induced extracellular signal-regulated kinase (ERK) activation in human n euroblastoma SK-N-SH cells. The activation of ERKs belonging to the mitogen-activat ed PK family has been implicated to play crucial roles in cell proliferations and is involve d in many steps of tumor progression (Fang and Richardson, 2005; Platanias, 2003; Seger and Krebs, 1995). Dysfunction of the ERK signaling pathways was shown to play a pivotal role in the de velopment of many cancers, including
leukemia and colon cancer. Active forms of ERK1/2 were found to be dually phosphorylated at threonine and tyrosine. To investigate whether AN could activate ERK, the effect of AN on the activation-association phosphorylation of ERK1/2 wa s measured in SK-N-SH cells. Treatment
with 400 μ g/mL AN for 1 hour increased the activation-associa ted phosphorylation of ERK1/2. Further increase in ERK1/2 phosphorylation was obse rved with 3 and 24 hours of incubation. Furthermore, increase in ERK phosphorylation was fo und to be dependent on AN concentration. When SK-N-SH cells were treated with specific mitog en-activated/ERK-activating kinase (MEK) inhibitors, PD98059 (10 μ M) and U0126 (10 μ M), for 1 hour prior to treatment with
400 μ g/mL AN for 24 hours, activation of ERK by AN was s ignificantly abolished. Thus, Chantara et al. (2006) concluded that AN induced ER K1/2 phosphorylation in SK-N-SH cells via
activation of MEK.

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The role of muscarinic receptors in AN-mediated ER K activation was also investigated by pretreating SK-N-SH cells with or without 10 μ M atropine, a muscarinic receptor antagonist, followed by incubation with AN for 24 hours. Carba chol, a muscarinic receptor agonist, was used as a positive control. Previous studies sugge sted that expression of muscarinic receptors can induce cell proliferation by activating the ERK 1/2 pathway (Jiménez and Montiel, 2005).
The results showed that 1 mM carbachol induced ERK1 /2 activation, and this effect was reduced by atropine pretreatment. However, AN-induced ERK activation was not significantly altered by atropine pretreatment, suggesting that muscarinic r eceptor stimulation may not be directly
involved in the observed AN-induced ERK activation (Chantara et al., 2006). Chantara et al. (2006) also investigated whether o xidative stress generated by various stimuli might result in activation of ERK by studyi ng the effects of antioxidants on AN-induced ERK activation. Three non-enzymatic antioxidants w ere used: NAC, ascorbic acid, and watersoluble vitamin E (TRX) were used. When SK-N-SH ce lls were pretreated with 20 mM NAC
for 10 minutes or 1 mM ascorbic acid or 1 mM TRX fo r 1 hour prior to addition of 400 μ g/mL AN for 24 hours, no reduction in AN-induced ERK act ivation was found. Therefore, Chantara et al. (2006) concluded that the activation of ERK by AN observed in SK-N-SH cells was not mediated via an oxidative stress-dependent mechanis m. To determine if AN-induced ERK activation was medi ated via PKC, PKC was inhibited via several methods. In addition to applying the P KC inhibitors, GF109203X (bisindolymalcimide) and rottlerin, PKC was also de pleted by prolonged incubation of the cells with phorbol 12-myristate 13-acetate (PMA). Inhibi tion of PKC by GF109203X significantly reduced the increase in ERK1/2 phosphorylation to 2 6% of that caused by AN alone. Similarly, rottlerin and prolonged treatment with PMA reduced the activation of ERK by AN. Therefore, the study authors concluded that PKC played an impo rtant role in AN-induced ERK activation in SK-N-SH cells. In summary, this study demonstrated that AN activated ERK1/2 in a PKC-dependent manner and that oxidative stress and muscarinic receptor activation were probably not involved in ERK1/2 activation by AN.

4.5.2. Genotoxicity Studies The following subsections provide a summary of the results of AN and its reactive metabolite, CEO, in in vitro and in vivo mutagenicity/genotoxicity assays. The overall
conclusion that can be drawn from these studies is that AN is genotoxic after metabolic activation to CEO. Table 4-53, which provides a su mmary of studies on the mutagenicity/ genotoxicity of AN, is at the end of this section.

4.5.2.1. Studies in Humans Seven studies have examined the genotoxicity of AN in vivo in humans who may have been occupationally exposed to AN.

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Xu et al. (2003) measured the incidence of DNA str and breakage and sex chromosome aneuploidy in the sperm of 30 workers exposed to AN for 2.8 years. The mean AN concentration at operation sites was 0.8 mg/m 3 

### . Thirty sperm donors of the same approximate age range from the general population were recruite d as controls. Lower sperm density was noted in exposed workers compared with controls (75 × 10 6 

### /mL vs. 140 × 10 6 

### /mL). DNA strand breakage was detected in AN-exposed workers by usin g single-cell gel electrophoresis, with the rate of comet sperm higher in the exposed workers t han in the controls (28.7 vs. 15%). The frequency of sex chromosome disomy was 0.69% in the exposed group and was >0.35% in the control group. There were also significant differe nces in the frequencies of XX-, YY-, and XY-bearing sperm between the exposed and control gr oups. Fan et al. (2006), in an article translated from C hinese, evaluated the application of a micronucleus test by using buccal mucosal cells to detect genetic damages in AN-exposed workers. The low concentration (average concentrat ion 0.522 mg/m 3 

### AN) exposed group consisted of 41 healthy male workers with direct co ntact with AN in a chemical plant that produced AN (by the oxidation of propylene, ammonia , and air) in Shanghai. Since the entire propylene-ammonia oxidation process was carried out in a closed system of pipes and automated technology, the chance of contact with AN was prima rily at the time of on-site sampling and pipe inspection. The average age of this exposed g roup was 37.4 years, and the range and average exposure duration were 1–33 and 15.7 years, respectively. The intermediate (average concentration 1.998 mg/m 3 

### ) exposed group consisted of 47 healthy male workers in an acrylic fiber factory in Shanghai. AN was used as a raw material in the synthesis of polyacrylonitrile by polymeriza tion. The average age of workers was 39.8 years, and the range and average exposure dura tion were 1–33 and 17.2 years, respectively. The control group consisted of 31 healthy male work ers with no exposure to any known mutagen or AN and living in the same community. Their aver age age was 37.2 years, and the average working duration was 16.7 years. The rates of alco hol consumption and cigarette smoking were similar in the exposed and control groups.
Buccal mucosal cells were collected from second sc rapings from the mucous membrane on the inside of both cheeks of study subjects afte r rinsing their mouths with clean water. Blood samples were also collected for measurement of micr onuclei (MN) in peripheral blood lymphocytes. The rates of occurrence of MN in bucc al mucosal cells in the intermediate concentration exposed, low concentration exposed, a nd control groups were 4, 3.68, and 2.03%, respectively. The rates of MN in the low and inter mediate concentration groups were significantly higher than in the control group ( p < 0.05). The rates of occurrence of MN in peripheral blood lymphocytes in the intermediate an d low concentration exposed and control groups were 4.23, 2.44, and 2.48%, respectively. T he rate of occurrence of MN in blood lymphocytes in the intermediate exposed group was s ignificantly different from that in the control group (

p < 0.05).

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To investigate the relationship between AN exposur e and the rate of occurrence of MN and to eliminate the possibility of the presence of other confounding factors, a multivariate linear regression analysis was conducted. The results ind icated that the cumulative exposed amount of AN, the recent exposed amount of AN, and the extent of cigarette smoking were important
factors in the rate of occurrence of MN in buccal m ucosal cells and blood lymphocytes. Fan et al. (2006) concluded that the micronucleus test of buccal mucosal cells could replace the micronucleus test of lymphocytes in the peripheral blood as a screening test for genetic damage in AN-exposed workers. Borba et al. (1996) evaluated urinary genotoxicity of three groups of workers in an AN fiber production plant (exposed group 1: 14 worker s in the continuous polymerization section; exposed group 2: 10 equipment maintenance workers; control group: 20 administrative workers from the same plant). Urine extracts were used in the Ames test (using TA 98, +S9) to assess gene reversion activity. No differences in urinary genotoxicity were found in the three groups. Additionally, there were no significant differences in the incidence of SCE in peripheral lymphocytes among the groups. However, the mainten ance workers had a higher incidence of CAs in lymphocytes, consisting of chromatid and chr omosomal gaps and chromatid and chromosomal breaks, than the controls ( p < 0.003). These effects were also increased in production workers but not to statistically signifi cant levels, possibly due to the comparatively low number of subjects in the study. The significa ntly higher incidence of CAs in maintenance workers were in agreement with the highly significa nt levels of Hb adducts and CEVal in the same population (see Section 4.1.2.2). The mainten ance workers also had significantly higher levels of erythrocyte MDA, an indicator of lipid pe roxidation, than the other two group of
workers. Ding et al. (2003) compared deletion frequencies o f mitochondrial DNA in peripheral lymphocytes in 47 workers exposed to a mean workpla ce concentration of 0.11 ppm AN and 47 nonexposed workers using PCR techniques (this st udy is described more fully in Section 4.1.2.2). No deletions were detected in the nonexp osed group, but a deletion frequency of 17% was detected in the exposed group. In a separate e xperiment on presumably nonexposed individuals, no deletions in mitochondrial DNA were detected in samples from 12 high school students, whereas the deletion frequency was 25% in samples from 12 elderly persons. Consistent with the hypothesis that damage to mitoc hondrial DNA contributes to degenerative diseases related to aging, the study authors sugges ted that occupational exposure to AN may
induce mitochondria DNA deletion in cells that are related to aging. Using the FISH technique with probes for chromosom es 1 and 4, Beskid et al. (2006) examined patterns of CAs in cultured lymphocytes fr om blood samples of 61 AN-exposed male workers involved in the polymerization of Indian ru bber and 49 nonexposed control subjects. Stationary monitoring in the workplaces indicated A N air concentrations of 0.05–0.3 mg/m 3 

### for a group of 39 exposed workers sampled in 2000 and 0.0 5–0.7 mg/m 3 

### for another group of

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22 exposed workers sampled in 2003. A 38% increase in frequency of aberrant cells in AN-exposed workers was found to be statistically in significant. However, the number of reciprocal translocations increased by 53% ( p < 0.05) in the AN-exposed group. In addition, a significant increase in a relative number of insert ions was found in the AN-exposed group. Furthermore, chromosomal specificity was observed i n lymphocytes with aberrations on chromosome #1 and #4. In the AN-exposed group, the proportion of cells with aberrations on chromosome #1 decreased significantly (58.8 vs. 73. 8% in the control subjects, adjusted to age and smoking), but aberrations on chromosome #4 incr eased (47.0 vs. 29.4% in the controls). In an earlier study by the same research group, t he frequency of CAs in peripheral blood samples was studied in 45 male rubber polymerizatio n workers exposed for the last 3 months to 0.05–0.3 mg AN/m 3 

### , 23 matched controls living in the same region (co ntrol group I), and 33 unexposed controls from Prague (control group II ) (Šrám et al., 2004). Subjects were interviewed and completed questionnaires on demogra phic data, occupational and environmental exposures, smoking habits, medications, X-ray exami nations, viral infections, and alcohol consumption within the 3 months before sampling. C ytogenetic analysis was conducted using two methods. Conventional chromosomal analysis was used to quantify CAs (chromatid plus chromosome breaks and chromatid plus chromosome exc hanges), the number of aberrant cells (those with breaks and exchanges, gaps not included ), and the aberration frequency (number of breaks per cell). The FISH technique, using probes for chromosomes 1 and 4, was employed to quantify translocations. Conventional analysis did not detect any differences in the frequency of CAs in exposed workers compared with either control group. FISH detected no differences in the frequencies of aberrations or translocations in exposed workers compared with matched controls (control group I), but the frequencies in both groups were significantly elevated compared with unexposed controls from Prague (contr ol group II). Šrám et al. (2004) concluded that occupational exposure to 0.05–0.3 mg/m 3 

### AN did not present a significant genotoxic risk and attributed higher frequencies in the exposed gr oup and control group I to undetermined factors present in the region in which the petroche mical industries are located but absent in Prague. Thiess and Fleig (1978) surveyed 18 workers at a pl ant that was used for manufacturing copolymers of styrene and AN, styrene, AN, and buta diene and also for synthesis of organic intermediates. The workers had been exposed to AN, on average, for 15.3 years and could have been exposed simultaneously to styrene, ethylbenzen e, butadiene, and other chemicals. The control group consisted of 18 workers who had not b een exposed to AN. Atmospheric monitoring conducted between 1963 and 1974 revealed AN concentration of about 5 ppm, with the possibility of higher peak values occurring in connection with special tasks. Between 1975 and 1977, exposure to AN had been reduced to an ave rage of 1.5 ppm. The incidence of CAs in the lymphocytes was measured in these 18 workers an d in age-matched nonexposed controls. The numbers of aberrant metaphases (gaps and iso-ga ps included) were 5.5 ± 2.5% in exposed

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workers and 5.1 ± 2.3% in controls. When gaps were not included, the numbers dropped to 1.8 ± 1.3% in exposed workers and 2.0 ± 1.6% in con trols. The differences were statistically not significant. This study is of limited value becaus e of mixed exposure in the exposed group, small group size, and uncertainty in exposure level s.

4.5.2.2. In Vivo Tests in Mammals
Rats Oral administration of up to 40 mg/kg AN or i.v. a dministration of up to 98 mg/kg AN to male Sprague-Dawley rats did not induce MN in bone marrow and peripheral blood, respectively (Morita et al., 1997). However, Wakata et al. (199 8) demonstrated induction of MN in bone marrow polychromatic erythrocytes of Sprague-Dawley rats (four/group) treated 2 times with 124.8 mg/kg AN i.v. and sampled 24 hours after trea tment. A negative result was obtained in peripheral blood. In another study (Rabello-Gay an d Ahmed, 1980), male Sprague-Dawley rats treated orally with 16 daily doses of 40 mg/kg-day AN showed no increase in CAs in the bone
marrow over controls. Irreversible binding of radioactivity from [2,3- 14 

### C]-AN to DNA in brain, stomach, and liver of male Sprague-Dawley rats was reported 24 h ours after a single oral dose of 46.5 mg/kg (Farooqui and Ahmed, 1983a). DNA alkylation was si gnificantly higher in the target organs, brain and stomach (119 and 81 pmol/mg DNA at 24 hou rs, respectively), than in the liver (25 pmol/mg DNA). The covalent binding indices in the liver, stomach, and brain at 24 hours after dosing were 5.9, 51.9, and 65.3, respectively . Similarly, covalent binding of [2,3- 14 

### C]-AN or its metabolite to testicular (Ahmed et al., 1992 a), lung (Ahmed et al., 1992b), and gastric tissue DNA (Abdel-Rahman et al., 1994b) has been re ported in male Sprague-Dawley rats treated with a single oral dose of 46.5 mg/kg AN. Maximum covalent binding of radioactivity to gastric DNA occurred at 15 minutes after dosing and occurred at 0.5 and 12 hours for testicular and lung DNA, respectively. Alkylation of hepatic DNA was also reported when a single dose of 0.2 mmol [2,3- 14 

### C]-AN was administered to male Wistar rats intraper itoneally (Peter et al., 1983a). Two 14 

### C peaks that did not cochromatograph with any known standards were observed when the DNA hydrolysate from rat livers was chroma tographed on PEI-cellulose column. In another study, 0.6 mg/kg [2,3- 14 

### C]-CEO was administered to one F344 rat intraperitoneally (Hogy and Guengerich, 1986), and the rat was sacrificed after 1 hour. Covalent binding to both liver and brain protein was found, but no covalent binding to nucleic acids could be detected at the level of 0.3 alkylations per 10 6 

### bases. In the same study, three male F344 rats were administered 50 mg/kg AN i.p., and three other rats were administered 6 mg/kg CEO i.p. (Hogy and Guengerich, 1986). The rats were sacrifi ced after 2 hours. N 7 

### -(2-oxoethyl)guanine
was measured in liver DNA at the level of 0.032 and 0.014 alkylations/10 6 

### bases for CEO- and AN-treated rats, respectively. In the brains of tr eated rats, the levels of N 7 

### -(2-oxoethyl)guanine
were not above the limit of detection. Since DNA a dduct was detected in liver DNA, covalent

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binding to DNA had to occur. The method used in th e study was not sensitive enough to detect low levels of alkylation of nucleic acids, probably because of the small amount of DNA sample from one rat, and the DNA isolation protocol (DNA e xtract purified by hydroxylapatite column chromatography and DNA fraction dialyzed against wa ter and lyophilized then treated with RNAase and proteinase K) and method for correction for contaminating protein via quantitative amino acid analysis in the DNA sample may have allo wed a more stringent determination of
DNA-bound material. When the alkaline comet assay was used to detect DN A lesions, Sekihashi et al. (2002) demonstrated DNA damage in the forestomach, colon, kidney, bladder, and lung of Wistar rats treated with a single dose of 30 mg/kg AN i.p. but not in the brain or bone marrow. Oral exposure to 100 ppm AN in drinking water for 14 or 28 days significantly increased the level of cellular DNA fragmentation in the brai n of male Wistar rats (Mahalakshmi et al., 2003). Other aspects of this study are discussed i n Section 4.5.1.1.4. AN-induced unscheduled DNA synthesis (UDS) was demo nstrated in several studies in rats. In a study by Hogy and Guengerich (1986), ma le F344 rats (12/group) received a single sublethal dose of 50 mg/kg AN in saline by gavage, followed by hydroxyurea to arrest replicative DNA synthesis but allowing excision rep air DNA synthesis. Two hours after dosing, the animals received s.c. methyl [ 3 

### H]-labeled thymidine. This dose was repeated after 2 hours, and half the dose was given again after 2 more hour s for a total dose of 3.0 mCi/kg of BW. The
animals were sacrificed 2 hours after the last meth yl [ 3 

### H]-labeled thymidine. A significant
occurrence of UDS was found in the livers but not i n the brains of AN-treated rats. Hogy and Guengerich (1986) also studied the effect of treatment on DNA synthesis over
4 hours in the liver and brain of male F344 rats 48 hours after an oral dose of 50 mg/kg AN. DNA synthesis was decreased in the brain but not in the liver; replicative indices were 0.29 and 1.30, respectively. Thus, the carcinogenicity of A N in rat brain is not likely from cytotoxicity, followed by an increased rate of DNA replication an d leading to a greater chance of error during the rapid DNA synthesis. UDS was demonstrated in lung (Ahmed et al.,1992a), testis (Ahmed et al., 1992b), and gastric tissue (Abdel-Rahman et al., 1994a) of AN-t reated male Sprague-Dawley rats (12/group). Animals received a single oral dose of 46.5 mg/kg A N in saline, with or without hydroxyurea cotreatment to block the endogenous deoxynucleotide pool. [ 3 

### H]-Thymidine was administered 0.5, 6, or 24 hours after AN dosing, and animals we re sacrificed 2 hours later. The replicative index for DNA synthesis (i.e., the ratio of DNA syn thesis in treated animals over controls) was significantly reduced at all three time points in l ung, while DNA repair in the lung was increased by twofold at 0.5 hour and 1.6-fold at 6 hours foll owing AN oral treatment. Similarly, DNA synthesis was inhibited in testes at 0.5 and 24 hou rs after treatment (but increased at 6 hours), whereas DNA repair increased at 1.5- and 33-fold at 0.5 and 24 hours after treatment. For gastric tissue, DNA replicative synthesis was inhib ited 6 hours after AN administration but was

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rebounded and followed by a twofold increase at 24 hours. A threefold increase in UDS was observed at 24 hours after dosing. On the other hand, Butterworth et al. (1992) follo wed the incorporations of [ 3 

### H]-thymidine into the hepatocytes isolated from mal e F344 rats gavaged with either a single dose of 75 mg/kg AN or five daily doses of 60 mg/kg AN. Single-dosed animals were sacrificed 2 or 12 hours after dosing. Multiple-dosed animals were sacrificed 4 hours after the last dose. Hepatocytes were isolated and plated on cover slips and incubated with [ 3 

### H]-thymidine. Autoradiography was used to detect UDS. No sign of AN-induced UDS was found in hepatocytes from exposed rats. In addition, no UDS was found in the in vivo spermatocyte DNA repair assay with AN, using cells isolated from the seminiferous tubules of the same treated rats (Butterworth et al., 1992). The difference in resu lts from Butterworth et al. (1992) and Hogy and Guengerich (1986) regarding UDS in rat liver may be due to differences in methodology in that incorporation of [ 3 

### H]-thymidine actually took place in vitro in the st udy by Butterworth et al. (1992). AN also produced negative results for dominant let hal assay in male F344 rats (Working et al., 1987). In this assay, groups of 50 male F3 44 rats received AN by gavage at 0 or 60 mg/kg-day in 0.9% saline for 5 days. AN exposur e in males had no effect on the incidence of pre- or postimplantation losses, indicating a negat ive result to germ cells.

Mice When the alkaline comet assay was used to detect DN A lesions, Sekihashi et al. (2002) demonstrated DNA damage in the forestomach, colon, bladder, lung, and brain of male ddY mice treated with 20 mg/kg AN i.p. DNA damage was not detected in the liver, kidney, or bone

marrow. Sharief et al. (1986) determined that AN caused a s light increase on SCE frequencies in bone marrow cells of male C57B1/6 mice (four/dose g roup). No increase in SCE frequencies was observed in mice administered a single dose of up to 30 mg/kg AN intraperitoneally. Higher
doses were lethal to most of the animals. An incre ase in SCE frequency (2 × control) was observed in the only surviving mouse at the 45 mg/k g dose group. However, Fahmy (1999) reported AN-induced SCEs in bone marrow cells of ma le Swiss mice (five/group) treated with 7.5 mg/kg or 10 mg/kg AN i.p. 8 hours following Brd U treatment and with colchicines 2 hours prior to sacrifice. The lowest dose of 5 mg/kg i.p . produced no significant effect on SCE frequency. Earlier CA studies in mice have been largely negat ive. Rabello-Gay and Ahmed (1980) showed that AN did not produce increases in CAs in bone marrow cells of male Swiss mice (six/group) when given orally for 4, 15, or 30 days at doses up to 21 mg/kg-day or by i.p. injection at doses up to 20 mg/kg-day for the same duration. No increase in the incidence of CAs compared with controls was observed in bone mar row cells of NMRI mice that were

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injected intraperitoneally with 20 or 30 mg/kg AN ( Leonard et al., 1981). No increase in CAs in bone marrow cells and spermatogonia was observed in ICR mice treated with 20 or 100 mg/m 3 

### AN for 5 days (Zhurkov et al., 1983). However, Fah my (1999) reported AN-induced CAs in mouse spermatocytes after single oral doses of 15.5 or 31 mg/kg or three or five successive oral doses of 7.75 mg/kg (1/8 LD 50 

### ) in male Swiss mice. In addition, AN induced CAs in mouse bone marrow cells and spleen cells after a single o ral dose of 7.75 mg/kg or three or five successive doses of 7.75 mg/kg. The aberrations we re mainly of chromatid type (gaps, breaks, fragments, and deletions), with metaphases carrying one aberration only being dominant. Leonard et al. (1981) also reported AN did not ind uce MN in polychromatic erythrocytes of male NMRI mice injected intraperitoneally with 2 0 or 30 mg/kg AN. Marginal, but statistically significant, increases in MN were obs erved in bone marrow polychromatic erythrocytes but not in peripheral blood when AN at doses of 5.6–45 mg/kg was administered to male CD-1 mice (five/group) via i.p. administration . Oral or i.v. injection yielded negative results (Morita et al., 1997). Treatment with AN produced negative results for do minant lethal assays in male mice. The dominant lethal assay was used to detect CAs in meiotic and postmeiotic male germ cells. Groups of five male NMRI mice were injected intrape ritoneally with 0 or 30 mg/kg AN in saline or isopropyl methanesulfonate (positive control) an d then mated to untreated females (three per male) for 5 weeks (Leonard et al., 1981); females w ere replaced after 7, 14, 21, and 28 days, and the uterine contents were examined 17 days after ma ting. No evidence for dominant lethal
effects was observed.

4.5.2.3. Short-term Tests: Bacteria, Fungi, Drosophila, Oth ers There are a large number of reports of short-term genotoxicity test results on AN that have been made available through the auspices of th e International Programme on Chemical Safety (IPCS). The IPCS coordinated the investigat ion of eight organic carcinogens known to be
either inactive or difficult to detect in the Salmo nella assay, including AN, benzene, diethylhexylphthalate, diethylstilbestrol, hexameth ylphosphoramide (HMPA), PB, safrole, and o-toluidine, as well as two noncarcinogens in roden t bioassays (benzoin and caprolactam). Most of the available short-term genotoxicity tests were employed, and the work was carried out at some of the major research and testing laboratories throughout the world. The purpose of this endeavor was to evaluate the efficacy of these test s, to evaluate the strengths and weaknesses of such tests, and to identify the assay systems to co mplement the widely used Salmonella assay. All of the results from these studies have been com piled in a 750-page collection (Ashby et al., 1985), and a 56-page synopsis of the results is ava ilable on the Internet (IPCS, 1985). The conclusion from these evaluations was that AN, alon g with HMPA, o-toluidine, and safrole, belonged to a group of genotoxins that were detecte d by most of the eukaryotic assays studied and could easily be found to be nonmutagenic in the Salmonella assay because of protocol

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deficiencies associated with the overall metabolic capacity of the assay system. While several of these studies have been cited in this section, an o verview of the findings as they pertain to AN
follows. AN, at concentrations not overtly toxic in a given assay, was found in 42 of 68 tests to positively cause genotoxicity in bacteria, fungi, Drosophila melanogaster (mutation, gene reversion, mitotic crossing over, aneuploidy), and mammalian cell culture assay systems, both human and animal (single-strand breaks, UDS, CAs, S CEs, MN, and transformation). Among the eight carcinogens studied, AN gave the most pos itive results, inducing genotoxicity responses in 62% of all tests (42 out of 68 tests; 25 were negative and 1 was questionable). That number of positive responses rose to 81% when a mor e stringent selection of assays was applied (IPCS, 1985). Other studies, covering all assay ty pes used in that collaborative study, are listed in the two subsections on short-term assays (Sectio ns 4.5.2.3 and 4.5.2.4).

4.5.2.3.1. Bacterial tests. A number of research groups have examined the capac ity of AN to induce gene reversion in the Ames test. One of the first published papers was Milvy and Wolff (1977), which reported positive results of AN on Salmonella typhimurium strains TA 1535, 1538, and 1978 in the presence of S9 and an NADPH g enerating system. The first strain is sensitive to base substitution mutagens, and the la tter two strains are sensitive to frameshift mutagens. Negative results were obtained when meta bolic activation was excluded from the system. Gene mutation by exposure of bacteria to a n atmosphere containing AN was found to occur at concentrations as low as 57 ppm (equivalen t to 2 μ L of AN), lower than exposure in solution or spotting AN to a “lawn” of bacteria on a plate. This could be because AN vaporized readily in solution such that the actual exposure c oncentrations in solution or by spotting were uncertain. The findings of Milvy and Wolff (1977) were criticized by Venitt (1978) in a letter to the editor. While not disagreeing with the overall conclusion, Venitt (1978) considered the study authors to have calculated mutation frequency incor rectly from the data. Venitt (1978) confirmed AN to be mutagenic in TA 1535 but not in the frameshift strains TA 1538 and 1978. Among other reports of AN activity in the Ames tes t, Lijinsky and Andrews (1980) found AN at doses of 100–1,000 μ g per plate to be positive in S. typhimurium TA 1535 in the presence of S9 but negative in TA 98, 100, 1537, and 1538 in the plate incorporation assay. Similarly, Brams et al. (1987) reported AN (50–750 μ g/L) to be negative for gene reversion in TA 97, 98

, and 100 using plate incorporation assay, irrespecti ve of metabolic activation. The study authors accounted for these negative results with inadequat e experimental conditions. Previously, they had demonstrated that AN was mutagenic in TA 1530, 1535, and 1950 when 0.2% gaseous AN was injected into the dessicator where the plates w ere incubated for 1 hour in the presence of S9 (the plate agar contained 200 μ g AN/plate) (de Meester et al., 1978). A lower mut agenic activity was also detected with strains reversed by frameshi ft mutation (TA 98, 1978, 100), and assays

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conducted by the plate incorporation method gave ne gative results (de Meester et al., 1978; Dow Chemical Co., 1976). Jung et al. (1992) provided data from three labora tories that examined the ability of AN to induce gene reversion in TA 102 in the plate inc orporation assay, with uniformly negative results. Hakura et al. (2005) reported that AN ind uced dose-dependent increases in the number of revertants per plate in strain TA 100 exposed to concentrations ranging from 806 to 12,100 μ g per plate in the presence of rat or human liver S9 preparations, but the maximum response at 12,100 μ g per plate was slightly less than twofold higher t han the number of revertants per plate observed in the negative controls. Although the methodologies of the experiments may have been different, the positive finding of mutagenicity by de Meester et al. (1978) for AN in TA 98 and 100 is in agreement with data from Khudoley et al. (1987) that AN (conc entration not provided) was positive in TA 98 and 100 (with two- to fivefold increase in fr equency of induced mutants), irrespective of the presence of S9. Zhurkov et al. (1983) reported AN to dose-dependently induce mutations in S. typhimurium TA 1535 but not in TA 1538. The presence of comple te S9 fraction was required for this effect, but a 9,000 × g microsomal supernatant without cofactors gave in consistent
results. The concentrations tested were between 0. 1 and 10,000 μ g per dish. The highest concentration was overtly toxic to the bacteria. Other tests of the mutagenicity of AN in bacterial systems were negative. For example, Nakamura et al. (1987) employed the SOS test to eva luate the capacity of AN to induce expression of the umu gene in S. typhimurium TA 1535/pSK1002. This strain contains a umuC-lacZ fused gene, such that a forward mutation results in umu gene expression and the transcription of the lac operon and can be demonstr ated phenotypically by a twofold increase in β -galactosidase activity. AN, at concentrations up to 2,820 μ g/mL, and seven other known mutagens gave negative results in this system. Sim ilarly, AN was negative in the SOS
chromotest in Escherichia coli PQ37 (Brams et al., 1987). It should be noted tha t only 4 out of 14 compounds that were positive in the Ames assay w ere positive in the SOS chromotest kit used. Thus, some technical issues were responsible for the poor performance of the test kit (Brams et al., 1987). Venitt et al. (1977) tested AN for mutagenicity in a gene reversion assay (2–3 days at 37°C), using the tryptophan-dependent E. coli WP2 series of bacteria as indicator organisms.
Doses of 75 and 150 μ mol per plate of AN produced a dose-related increas e in the number of revertant colonies ( trp – 

### → 

### trp + 

### ) compared with untreated bacteria in WP2 (which is D NA repair proficient), WP2 uvrA (which lacks excision repair), and WP2 uvrApolA (which lacks both excision repair and DNA polymerase 1) without a nee d for S9 fraction. The study authors confirmed these results by using a simplified “fluc tuation” assay in which they obtained a dosedependent increase in mutation rate induced by 0.4– 2 mM AN (20- to 40-fold lower than the levels in plate test) in E. coli WP2. An exponential dose response was seen at low er

### 233 DRAFT - DO NOT CITE OR QUOTE

concentrations, 0.1–0.4 mM, with mutant WP2 uvrApol A, which lacked both excision repair and DNA polymerase-1. The effective mutagenic concentr ation range for AN was lowered by an order of magnitude when an error-prone DNA-repair p lasmid, pKM101, was introduced into
E. coli WP2. The study authors concluded from these resul ts that AN caused non-excisable misrepair DNA damage that ultimately gave rise to DNA strand breaks. Venitt et al. (1977) hypothesized that AN might react with thymine resid ues in DNA since AN has been shown to cyanoethylate ring N atoms of minor tRNA nucleoside s and ribothymidine and thymidine (Ofengand, 1967). Lambotte-Vandepaer et al. (1985, 1981, 1980) colle cted urine from male Wistar rats (two/group) and NMRI mice (five/group) that had bee n administered a single dose of AN (30 mg/kg intraperitoneally). The urine samples we re evaluated for potential induction of gene
reversion in S. typhimurium TA 1530. Positive results were obtained in rats a nd mice in the absence of S9. Mutagenic activity in urine was abo lished by the presence of S9 in rats and decreased in mice, a finding that suggests that the mutagenic agent in urine can be inactivated metabolically. Pretreatment with PB (induces CYP45 0 monooxygenase), CoCl 2 

### (inhibits CYP450 monooxygenase), and DEM (depletes GSH), befo re AN treatment, slightly decreased the mutagenic response in urine from mice and compl etely abolished the response in urine from rats. However, the study authors were unable to id entify the genotoxic compound in urine.

4.5.2.3.2. Fungi. Available studies that employed fungi in short-term assays on the mutagenicity/genotoxicity of AN produced mostly pos itive results. AN induced mitotic gene conversion in both stationary-phase and log-phase c ultures at the his 4 

### and trp 5 

### loci of Saccharomyces cerevisiae JD1, in the presence of metabolic activation by S9. Negative results were obtained without metabolic activation (Brooks et al., 1985; Shell Oil, 1984a). AN did not
induce chromosome loss in S. cerevisiae D61.M (Whittaker et al., 1990) but elicited respir atory deficiency, reflecting antimitochondrial activity.

4.5.2.3.3. Drosophila. A range of in vivo experimental systems used the fr uit fly, D. melanogaster , to examine the mutagenicity/genotoxicity of AN. Drosophila can biotransform certain procarcinogens to their reactive metabolite s and are used in short-term tests for identifying carcinogens and in studies on the mecha nism of mutagenesis of chemicals (Vogel et al., 1999). Osgood et al. (1991) used the Drosophila ZESTE sys tem to monitor the potential for AN to induce sex chromosome aneuploidy, following inha lation exposure of adult females to 2.7 ppm for up to 70 minutes. AN induced chromosom e loss after exposure for 50 and 70 minutes. AN was mostly nontoxic at the tested d ose, with only 13% killed after a 70-minute exposure. Similarly, in a Drosophila somatic recom bination and mutation assay, Drosophila larvae were exposed to 5–20 mM AN in water for 9–11 days, and hatching females were scored

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for twin mosaic spots and single mosaic light spots in their eyes (Vogel, 1985). These genetic markers might arise from many types of genetic alte rations. Mitotic recombination and chromosome breakage would result in mosaic twin spo ts, whereas deletions and gene mutations would give rise to mosaic single light spots. AN w as positive for the induction of mosaic single spots at 5 mM (LC 50 

### concentration was 10 mM) and negative for twin spo ts. Since the classification of single spots or twin spots might be subjected to personal bias, the total of twin and single spots was also reported, and AN gave pos itive result. AN was shown to be mutagenic by having marginally positive effects in somatic mutation/recombination assay on wing spots of Droso phila, with gas exposure of larva to 0.5–
1 μ L/1,150 mL for 0.5 or 1 hour (Würgler et al.,1985). AN gave negative results in a sex-linked recessive lethal mutation test on postmeiotic and m eiotic germ cells of male D. melanogaster

, exposed either by feeding of 420 ppm AN or injected with 3,500 ppm AN (Foureman et al., 1994).
The in vitro effect of AN on taxol-purified microtubules from Dr osophila and mouse brain was evaluated by Sehgal et al. (1990). (Taxo l promoted the formation and stability of microtubules.) Microtubules assist in the movement of chromosomes in both mitosis and meiosis. Polymerization and depolymerization of mi crotubules occur in cell division to separate the chromosomes from the metaphase plate during ana phase. In this study, the assembly and disassembly of microtubules was monitored spectroph otometrically in vitro. Previous results from in vivo assays monitoring induced sex chromoso me aneuploidy indicated that effective aneuploidogens affected microtubule assembly. When taxol-purified D. melanogaster microtubule was incubated at 37°C to allow polymeri zation, addition of 5 or 50 mM AN resulted in 28 and 64% inhibition of microtubule assembly, r espectively. When taxol-purified mouse
brain microtubules were incubated with 5 or 50 mM A N, 74 and 96% inhibitions of microtubule assembly were observed, respectively. Thus, these results indicated that AN was an aneuploidogen in vitro. On the other hand, taxol s ignificantly affects microtubule depolymerization assay, probably by stabilizing the formed microtubules. None of the tested aneuploidogens, including colchicine, promoted disa ssembly to taxol-purified microtubules.

4.5.2.3.4. Other short-term tests. Yates et al. (1994) reported on the ability of CEO to induce single- and double-strand DNA breaks in supercoiled DNA plasmid pBR322 DNA. Supercoiled DNA (1 μ g) was incubated for 3 hours at 37°C with ≥ 50 mM CEO and then subjected to agarose gel electrophoresis. The study authors reported th at CEO non-enzymatically induced DNA strand breaks in a dose- and time-dependent manner, but detailed data were not provided. Peter et al. (1983b) found that AN did not induce strand breaks in SV40 phage DNA in vitro, whereas synthetic glycidonitrile (i.e., CEO) was effective in the same system (both agents were incubated with DNA at 1 mmol/L for 17 hours in the dark, at 3 7°C, in a buffered solution without any enzyme addition).

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4.5.2.4. Mammalian Cell Short-term Tests
4.5.2.4.1. Mutations. A number of research groups have examined the abili ty of AN to induce forward mutations in human lymphoblast cell lines a nd the well-known mouse lymphoma
L5178Y Tk +/– 

### system. Crespi et al. (1985) used two human lymphoblast ce ll lines, Tk 6 (which does not contain CYP450 activities) and AHH-1 (which is metabolicall y competent) to assess AN mutagenicity at the thymidine kinase ( Tk +/– 

### ) locus and the hprt locus, respectively. Tk 6 cell cultures were treated
with 0–40 μ g/mL AN for 3 hours with and without externally add ed metabolic activation (rat liver S9). On the third day after treatment, the c ultures were plated in a selective medium containing 2 μ g/mL trifluorothymidine. After incubation for 12 d ays, the plates were scored for the presence of mutant colonies. Similarly, AHH-1 cell cultures were treated with AN for 28 hours, and the cultures were plated on the 6 th 

### and 7 th 

### day after treatment in a selective medium containing 0.6 μ g/mL 6-TG. AN induced dose-dependent mutations at the Tk +/– 

### locus in Tk 6 cells in the presence, but not in the absence, of S 9. AN induced mutations at the hprt locus in
AHH-1 cells. The lowest AN concentrations that wer e mutagenic in these test systems were
40 μ g/mL with Tk 6 cells +S9 and 25 μ g/mL with AHH-1 cells. Similarly, Recio and Skopek (1988a, b) assessed th e mutagenicity of AN and its epoxide metabolite, CEO, at the Tk +/– 

### locus in Tk 6 human lymphoblast cells in the presence and absen ce of rat liver S9. In the presence of S9, 2-hour inc ubations with 1.4 mM AN induced mutations at
the Tk +/– 

### locus as demonstrated by the presence of mutant cl ones when plated in trifluorothymidine selection medium after treatment, but, in the absence of S9, no mutagenic activity was observed over the concentration range of 0.4–1.5 mM (Recio and Skopek, 1988b). In contrast,
2-hour incubation with CEO at concentrations as low as 100 and 150 μM induced a mutagenic response (without metabolic activation) at the Tk +/– 

### locus (Recio and Skopek, 1988b). On a molar basis, CEO was as mutagenic in this system as the well-known mutagen, ethyl methanesulfonate (Recio and Skopek, 1988a).
Two classes of CEO-induced Tk –/– 

### mutant phenotypes were identified that differed in their growth rates: Tk n 

### with normal growth rate and Tk s 

### with slower growth rates. Southern blot analysis of DNA of these two classes indicated that the phenotypes differed genotypically (Recio and Skopek, 1988b). Ninety-six percent (25/26) of Tk s 

### mutants had lost a 14.8 kb DNA fragment corresponding to the active Tk allele, whereas only 8% (1/12) of CEO induced Tk n 

### mutant clones and 22% (2/9) of spontaneous Tk n 

### mutant clones had lost the 14.8 kb fragment (Recio and Skopek, 1988a, b). Recio and Skopek (19 88a) suggested that Tk s 

### mutants resulted from large-scale DNA structural alterations involvi ng the active Tk allele. CEO induced predominantly Tk n 

### mutants. Southern blot analysis of CEO-induced Tk n 

### mutants indicated the majority of these mutants were below the detection limit of <2 kb. Thus, CEO-induced alterations are relatively small DNA alterations. Recio and Skopek (1988a) suggested that

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CEO-induced Tk n 

### mutants resulted from point mutations or small ins ertion/deletions that occurred during the replication or repair of CEO-mo dified DNA. Karyotypic analysis on two
Tk n 

### mutants and 16 Tk s 

### mutants indicated that the majority of Tk mutants were not accompanied by abnormalities of the chromosome on which the Tk gene resides (chromosome 17). CEO also induced mutations at the hprt locus in Tk 6 cells (Recio and Skopek, 1988a). Characterization of the hprt mutations by cDNA sequencing analysis indicated tha t several hprt mutations were formed. A major (8/14) type of CEO- induced mutation was the specific loss of exons from the coding region of hprt

. Remaining mutants (6/14) were single base substitut ions (point mutation) resulting from amino acid changes (A:T base pairs and G:C base pairs). The mutagenicity of AN was evaluated in the mouse l ymphoma L5178Y Tk +/

– 

### forward mutation assay by a number of laboratories. Oberly et al. (1996) demonstrated that AN (activated with S9) was mutagenic at 40 μ g/mL in this assay because of producing a more than twofold increase in mutant frequency when compared to the mutant frequency of the solvent controls. Earlier results in the mouse lymphoma L5 178Y Tk+/- system from several studies all pointed to the capacity of AN at 12.5–200 μ g/mL to induce forward mutations at the Tk +/– 

### with or without S9 (Lee and Webber, 1985; Myhr et al., 1985 ; Amacher and Turner, 1985; Rudd, 1983). Garner and Campbell (1985) also reported that AN in duced mutations to ouabain and 6-TG resistance in the mouse lymphoma L5178 Y cells in t he presence of S9. However, negative results were obtained by Styles et al. (1985) in th e mouse lymphoma L5178Y Tk +/+ 

### cell line (Na + 

### /K + 

### ATPase locus, ouabain was used for mutant selectio n) and Tk +/– 

### cell line (trifluorothymidine was used for mutant selection). Using P388F mouse lymphoma Tk +/– 

### cell line in the presence of S9, Anderson and Cross (1985) al so obtained forward mutations to 5-iodo2-deoxyuridine resistance with AN. However, negati ve results were obtained by Lee and Webber (1985) in Chinese hamster V79/HGPRT assay in which AN did not induce 8-azaguanine
resistance mutation with or without S9.

4.5.2.4.2. Other DNA effects
UDS AN, at concentrations up to 2.5 mg/mL, was negative for induction of UDS in HeLa cells with or without the presence of S9, using the scint illometric method (Martin and Campbell, 1985). However, an increase in UDS, as measured by uptake of [ 3 

### H]-thymidine, was reported in cultured human lymphocytes treated with 5 × 10 -1 

### M AN and S9 (Perocco et al., 1982). Negative results were reported for the ability of AN to indu ce DNA repair synthesis (measured by incorporation of [ 3 

### H]-thymidine and autoradiographic techniques) in ra t hepatocyte primary culture (Probst and Hill, 1985; Williams et al., 19 85). However, no UDS, as measured by autoradiography, was observed in any of the culture s treated with the eight tested carcinogens (Probst and Hill, 1985). Similarly, only one of th e eight carcinogens tested by Williams et al. (1985) induced DNA repair synthesis as determined b y autoradiography of [ 3 

### H]-thymidine

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incorporation (AN was negative in this assay). Thu s, IPCS (1985) concluded the rat hepatocyte autoradiographic UDS assay was an insensitive assay for determination of genotoxicity of these chemicals and should be avoided for use as a comple ment to the Ames assay. Butterworth et al. (1992) used incorporation of [ 3 

### H]-thymidine and autoradiographic techniques to study the effect of AN and CEO on uns cheduled DNA repair in vitro in rat hepatocytes, and human mammary epithelial cells. A N and CEO were negative for the induction of DNA repair in hepatocytes in vitro. There was s ome indication of a statistically insignificant response at 0.1 mM CEO. However, CEO was toxic to the hepatocyte culture at 1 mM, the next higher tested concentration. As noted previously, IPCS (1985) has determined that rat hepatocyte autoradiographic UDS assay is insensitiv e for genotoxicity testing of AN and a group of seven other carcinogens. However, CEO, but not AN, was positive for UDS in human mammary epithelial cells in vitro (Butterworth et a l., 1992).

DNA strand breaks DNA single-strand breaks were measured by the alkal ine elution method in the following studies. DNA single-strand breaks were induced in [ 14 

### C]-thymidine-labeled cultured adult human bronchial epithelial cells treated with 200 o r 500 μ g/mL AN for 20 hours (Chang et al., 1990). These concentrations were below the cytotox ic concentration of 600 μ g/mL AN. DNA single-strand breaks were also reported in cultured rat hepatocytes treated with 65.8 μ g/mL AN for 3 hours (Bradley, 1985). Higher concentrations of 197 or 658 μ g/mL AN resulted in cytotoxicity. In another study, AN induced DNA sin gle-strand breaks in cultured Chinese hamster ovary (CHO) cells treated with 3.7 × 10 3 

### or 5.3 × 10 4 

### μ g/mL AN (7 × 10 -2 

### or 1 × 10 -1 

### M AN) with or without S9 mix for 1 hour (Douglas et a l., 1985). These concentrations were above the cytotoxic concentrations of 5.31 and 53.1 μ g/mL AN (10 -5 

### and 10 -4 

### M) with and without S9 mix, respectively. Thus, the observed DNA stran d break effect was relatively weak in CHO cells. Lakhanisky and Hendrickx (1985) reported th at AN (concentrations not reported) did not
in induce DNA strand breaks in cultured CHO cells w ith or without S9. Therefore, cultured CHO cells may not be a sensitive assay system to te st for DNA strand breaks induced by AN when compared with other cell cultures. On the oth er hand, DNA strand breaks was reported in SHE cells treated with AN. Parent and Casto (1979) observed incubation of [ 3 

### H]-thymidinelabeled primary SHE cells with 200 or 400 μ g/mL AN for 18 hours caused a shift in the sedimentation pattern of the labeled cellular DNA w hen subjected to alkaline sucrose gradient.

4.5.2.4.3. Cytogenic effects. AN induced SCE in cultured adult human bronchial ep ithelial cells treated with noncytotoxic concentrations of 150 or 300 μ g/mL AN for 20 hours (Chang et al., 1990). An increase in frequency of SCE was observe d in human lymphocytes from two different
donors incubated for 1 hour with 5 × 10 -4 

### M AN and S9 mix. No increase in SCE was observed without the S9 mix metabolizing system. (Perocco e t al., 1982). AN was negative for the

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induction of SCEs in CHO cells (Ved Brat and Willia ms, 1982). However, when CHO cells were cocultured with freshly isolated rat hepatocyt es, Ved Brat and Williams (1982) observed
that AN at 10 -4 

### M produced a greater than twofold increase in SCEs in the CHO cells, suggesting that the rat hepatocytes metabolized AN to its reac tive metabolite, which was then transported into the CHO cells. Other cytogenetic findings in CHO cells included positive results for the induction of SCEs at 2 mM AN with S9 (Natarajan et al., 1985) and CA at 4 mM AN with or without S9, while Douglas et al. (1985) reported th at AN at 10 -1 

### M induced the formation of MN. AN was reported to induce CAs in Chinese hamster lu ng (CHL) fibroblasts in culture without
metabolic activation at nontoxic concentrations of 12.5 μ g/mL (Ishidate and Sofuni, 1985). AN
induced structural CAs in Chinese hamster liver fib roblast cell line (CH1-L) at the lowest
concentration of 2.5 μ g/mL and higher (Danford, 1985). Sasaki et al. (1980) found that 0.0053 mg/mL AN ind uced chromosome breaks in a pseudodiploid Chinese hamster cell line (Don-6). A N was negative at concentrations up to
10 μ g/mL for the induction of CAs, SCEs, and polyploidy in cultured epithelial-like cells from rat liver (RL4 cell line) (Priston and Dean, 1985; Shell Oil Co., 1984b). Mangir et al. (1991) reported that CHO cells treated with AN demonstrate d a growth and RNA synthesis rate that is similar to that for agents that cause damage to nuc lear DNA in cells. Growth and RNA synthesis of CHO cells was inhibited with 0.001% (v/v) AN and completely inhibited at 0.005% (v/v) AN. Kodama et al. (1989) conducted cytogenetic analyse s on eight spontaneous and eight
CEO-induced Tk s 

### mutant clones in Tk 6 human lymphoblastoid cultures that had lost the 1 4.8 kb polymorphic band corresponding to the active Tk allele. These CEO-induced Tk -/- 

### mutants were reported in the Recio and Skopek (1988a, b) studies . No chromosomal abnormalities were found in the eight spontaneous mutants. On the other han d, a visible abnormality on chromosome 17
was found in one of the CEO-induced tk s 

### mutants and was marked by duplication of the long a rm of chromosome 17, with break points at q11 and q21. The latter break point was close to the
Tk locus, suggesting the observed aberration might be associated with Tk -/- 

### phenotype.

4.5.2.4.4. Transformation assays. Parent and Casto (1979) studied the capacity of AN to induce transformations in primary SHE cells in cult ure by monitoring the incidence of microscopically observed foci of morphologically tr ansformed cells. In two experiments, SHE cell cultures were exposed to 25–200 μ g/mL AN for 18 hours, after which AN was removed an d cultures were subsequently inoculated with 200 focu s-forming units of simian adenovirus SA7 and incubated for 3 hours. Colonies of surviving c ells were counted after 8 days, and virustransformed foci were counted after 21 days. Pretr eatment of cells with AN prior to viral inoculation resulted in only slight enhancement of 1.8-fold in SA7 foci. In another experiment,
SHE cells were treated with the same concentrations of AN 5 hours after viral inoculation. This resulted in an enhancement ratio that was markedly increased (8.9 at AN concentration of 200

μ g/mL vs. 1.0 in controls).

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When SHE cells were treated for 6 days with 12–100 μ g/mL AN without added SA7 virus, foci of morphologically transformed cell s were observed at 50 μ g/mL AN (two foci/six dishes) and 100 μ g/mL AN (three foci/nine dishes). The ability of AN to induce transformation in SHE cells was also evaluated by Barrett and Lamb (1985). AN was considered to give a posit ive response according to the criterion of inducing four or more transformed colonies per 2,00 0 surviving colonies. With a relative survival of unity, the lowest concentration of AN ( 0.01 μ g/mL) generated morphologically transformed colonies at a rate of 4/1,149. Lawrence and McGregor (1985) evaluated the ability of 10 potential carcinogens, including AN, to induce morphological transformatio n in cultured embryonic mouse fibroblasts (C3H/10T1/2, Clone 8) in the presence or absence of S9. Positive response was obtained at
16 μ g/mL AN in the presence of S9, while responses were uniformly negative in its absence. Banerjee and Segal (1986) studied whether AN (0–200 μ g/mL) could produce in vitro
transformation of C3H/10T1/2 and NIH/3T3 mouse fibr oblast cells in culture. AN was cytotoxic at the higher concentrations, with cell s urvival dropping below 75% at ≥ 50 μg/mL in C3H/10T1/2 and NIH/3T3 cells. Optimal transformati on rates were obtained at AN
concentrations of 12.5 μ g/mL in C3H/10T1/2 cells. AN-induced transformatio n was observed at
concentrations between 3 and 100 μ g/mL in NIH/3T3 cells. Matthews et al. (1985) evaluated whether AN induced morphological transformation and
mutation to ouabain resistance in Balb/c-3T3 cells in culture with or without exogenous
metabolic activation. For activation transformatio n assay, Balb/c-3T3 cells were cocultured with lethally X-irradiated primary F344 rat liver cells (RLCs). The RLC-3T3 cocultures were treated
with 0–25 μ g/mL AN for 48 hours. The cocultures were then tre ated biweekly for 3 weeks with
0.05 μ g/mL 12- O -tetradecenoyl-phorbol-13-acetate beginning 1–2 day s after completion of AN treatment. For nonactivation transformation assay, 3T3 cell cultures were incubated with 0–
20 μ g/mL AN for 72 hours. For RLC-3T3 cocultures, sign ificant increase in relative transformation activity was found in coculture trea ted with 8.8 μ g/mL AN (noncytotoxic concentration). At 16.7 μ g/mL AN, relative cell survival was only 22%, and n o significant increase in transformation activity was found. No significant increase in transformation activity
was observed in AN-treated 3T3 cell cultures withou t RLCs. For ouabain resistance (Oua r 

### ) mutation assay, 3T3 cell cultures were treated wi th 0–
150 μ g/mL AN with or without S9 mix for 4 and 24 hours, respectively. After the treatment, AN
was removed and the cultures were refed and maintai ned for 5–6 days for expression and selection, using 2 mM cardiac glycoside ouabain. T he appearance of ouabain-resistant (Qua r 

### ) variants would indicate a mutation arose in the gen e controlling the synthesis of cell membrane
Na + 

### /K + 

### ATPase (Corsaro and Migeon, 1978). Significant in crease in relative Oua r 

### frequency
was observed at 50 μ g/mL AN with S9 activation.

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Yuan and Wong (1991) used a nonfocus transfection- transformation assay to study the capacity of the oxidative metabolite CEO to bring a bout functional changes in a plasmid that would be indicative of a compound-induced mutation. A new plasmid that had been constructed by ligating a human c-HA- ras -1 protooncogene to a pSV2neo mammalian vector was reacted
with CEO in vitro and then transfected into NIH3T3 cells. Cells were selected for neomycin resistance and/or abnormal growth characteristics, the latter serving to discriminate between colonies arising from ras mutations and those from cells that were not trans fected (or that were transfected with nonplasmid DNA). Although CEO-mod ified ras gave rise to two neomycin resistant clones, they were probably not indicative of a ras mutation because their normal growth rate and monolayer density were similar to negative control. Southern blot analysis of transformant DNA also supported this conclusion. F or example, when anti-benzo(a)pyrene7,8-dihydrodiol-9,10-epoxide transformant DNA was e xamined in this system as a positive control, a fragment of 411 base pairs was revealed, indicating a ras mutation at codon 11 or 12. However, both CEO-derived clones and untreated cont rol showed the WT band of 355 base pairs.

4.5.2.4.5. Genotoxicity summary. All identified studies concerning the mutagenicity or genotoxicity of AN are compiled in Table 4-53. The overall weight of evidence from in vitro and in vivo studies is adequate to support direct m utagenicity for the AN metabolite, CEO.

Table 4-53. Summary of studies on the mutagenicity /genotoxicity of AN

Test system Endpoint/effect Exposure concentration Exposure

duration Result a Reference
Humans AN-exposed workers n = 30 DNA strand breaks;

nondisjunction of sex chromosomes in sperm 0.8 mg/m 3 2.8 yrs + Xu et al. (2003)

AN-exposed workers: 31 controls, 41 low, 47 intermediate Increase in MN in

buccal mucosal cells (low and intermediate groups) and blood lymphocytes (intermediate group) of AN-exposed workers. Low =

0.522 mg/m 3 Intermediate = 1.998 mg/m 3 Low = 1–

33 yrs (average 15.7 yrs) Intermediate = 1–33 yrs (average 17.2 yrs) + Fan et al. (2006)

AN-exposed polymerization workers: 14 Maintenance workers: 10 controls: 20 CAs in lymphocytes ND b ND Maintenance workers: + Production workers: (+) Borba et al.

(1996)

AN-exposed workers: 47; 47 controls Deletion of

mitochondrial DNA in lymphocytes 0.11 ppm 17.3 yrs + Ding et al. (2003)

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Table 4-53. Summary of studies on the mutagenicity /genotoxicity of AN

Test system Endpoint/effect Exposure concentration Exposure

duration Result a Reference AN-exposed workers Group 1 = 39 Group 2 = 22 Unexposed controls = 49 CAs (detected by

FISH) in cultured lymphocytes from peripheral blood samples Group 1 = 0.05–

0.3 mg/m 3 Group 2 = 0.05– 0.7 mg/m 3 3 mos (+) Significant increase in the number of reciprocal translocations and relative number of insertions. Increase in frequency of aberrant cells not significant. Beskid et al.

(2006)

AN-exposed workers (n = 45) Matched controls = 23, unexposed controls = 33 CAs in cultured

lymphocytes in peripheral blood samples 0.05–0.3 mg/m 3 3 mos – Srám et al. (2004)

AN-exposed workers (n = 18); controls = 18 CAs in lymphocytes 5 ppm, reduced to 1.5 ppm between 1975 and 1977 (possible exposure to other chemicals) 15.3 yrs – Thiess and Fleig (1978)

Rats Sprague-Dawley (male) (4/group) MN 125 mg/kg i.v. Two
treatments Bone marrow: +

Peripheral blood:

– Wakata et al.

(1998)

MN in bone marrow 10–40 mg/kg oral Single dose – Morita et al. (1997) Sprague-Dawley (male) MN in peripheral

blood 24.5–98 mg/kg

i.v. Single dose – Morita et al. (1997) Sprague-Dawley (male) n = 3 CAs in bone marrow 40 mg/kg oral 16 d – Rabello-Ga y and Ahmed (1980) Sprague-Dawley (male) n = 3–4/group Binding to DNA in

stomach, brain, and liver 46.5 mg/kg oral Single dose + Farooqui and Ahmed (1983a)

Sprague-Dawley n = 4/group Binding to testicular

DNA 46.5 mg/kg oral Single dose + Ahmed et al. (1992a) Sprague-Dawley (male) n = 4/group Binding to lung DNA 46.5 mg/kg oral Single dose + A hmed et al. (1992b) Sprague-Dawley (male) n = 3/group Binding to gastric

tissue DNA 46.5 mg/kg oral Single dose + Abdel-Rahman et al. (1994b) Wistar (male) Alkylation of hepatic

DNA 0.2 mmol i.p. Single dose + Peter et al. (1983a)
F344 n = 1 Binding to liver and

brain DNA 0.6 mg/kg CEO

i.p. Single dose – Hogy and Guengerich (1986)

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Table 4-53. Summary of studies on the mutagenicity /genotoxicity of AN

Test system Endpoint/effect Exposure concentration Exposure

duration Result a Reference
F344 n = 3 DNA adduct formation 50 mg /kg AN i.p. or 6 mg/kg CEO i.p. Single dose Liver: + Brain: (+) Hogy (1986);

Hogy and Guengerich (1986) Wistar DNA damage in

forestomach, colon, kidney, bladder, and lung but not in brain or bone marrow 30 mg/kg i.p. Single dose + Sekihashi et al. (2002)

Wistar, male Fragmentation of brain

DNA 100 ppm AN in

drinking water 14 or 28 d + Mahalakshmi et al. (2003)
F344 n = 12/group UDS in liver but not

brain 50 mg/kg gavage Single dose + Hogy and Guengerich (1986) UDS in lung 46.5 mg/kg oral Single dose Ahmed et al

. (1992a) UDS in gastric tissue 46.5 mg/kg oral Single dose A bdel-Rahman et al. (1994a) Sprague-Dawley

UDS in testis 46.5 mg/kg oral Single dose +

Ahmed et al. (1992b)
F344 UDS in isolated

hepatocytes or spermatocytes a. 75 mg/kg

b. 60 mg/kg oral a. Single dose

b. five daily doses – Butterworth et al. (1992)

F344 n = 50 Dominant lethal

mutations 60 mg/kg 5 d – Working et al. (1987)
Mice ddY DNA damage in

forestomach, colon, bladder, lung, and brain 20 mg/kg i.p. Single dose + Sekihashi et al. (2002)

C57B1/6 n = 1–4/group SCEs in bone marrow 10–45 mg/kg Single dose (+) pos itive at toxic dose of 45 mg/kg Sharief et al.

(1986)

Swiss SCEs in bone marrow 7.5 or 10 mg/kg i.p. Single dose + Fahmy (1999)

CAs in spermatocytes,

bone marrow, and spleen cells a. 15.5 or

31 mg/kg oral b. 7.75 mg/kg a. Single dose

b. three or five doses + Fahmy (1999)

Swiss n = 3–6/group CAs in bone marrow 7, 14, or 21 mg/kg-d oral or 10, 15, or 20 mg/kg-d i.p. 4, 15, or 30 d – Rabello-Gay and Ahmed (1980)

NMRI male n = 4/group CAs in bone marrow 20 or 30 mg/kg i.p. Single dose – Leonard et al. (1981)
C57B1/6 n = 1–4/group CAs in bone marrow 10–45 mg/kg Single dose – Sharie f et al. (1986)
NMRI male n = 4–5/gr oup

MN in erythrocytes 20 or 30 mg/kg

i.p. Single dose – Leonard et al. (1981)

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Table 4-53. Summary of studies on the mutagenicity /genotoxicity of AN

Test system Endpoint/effect Exposure concentration Exposure

duration Result a Reference CD-1 MN in bone marrow 0–45 mg/kg i.p. 0–32 mg/kg oral 0–40 mg/kg i.v. Single dose i.p.: (+) oral and i.v.: – Morita et al.

(1997)

CD-1 MN in peripheral

blood 5.6–45 mg/kg i.p.

or 10–40 mg/kg i.v. Single dose – Morita et al. (1997)

ICR CAs in bone marrow

cells and spermatogonia 100 or 20 mg/m 3 5 d – Zhurkov et al. (1983)

NMR1 n = 5/group Dominant lethal

mutation 30 mg/kg i.p. Single dose – Leonard et al. (1981) Short-term assays—bacteria (–S9 / +S9) S. typhimurium TA 1535 Gene reversion (His +

revertant) 5–20 μ L AN

solution 0.5 h –/+ Milvy and Wolff (1977)
TA 1535 Gene reversion 2–300 μ L AN
vapor 0.5–4 h –/+ Milvy and Wolff (1977)
TA 1538 Gene reversion 200 μ L AN vapor 2 h –/+ Milvy and Wolff (1977)
TA 1978 Gene reversion 5–10 μ L AN solution 0.5 h –/+ Milvy and Wolff (1977) TA 1535 Gene reversion 100–1,000 μ g AN plate incorporation
assay ND –/+ Lijinsky and Andrews (1980)

TA 1537, 1538, 98, 100 Gene reversion Plate incorporation
assay ND –/– Lijinsky and Andrews (1980)
TA 1535 Gene reversion 0.1– 1,000 μ g/dish ND –/+ Zhurkov et al. (1983)
TA 1538 Gene reversion 0.1– 10,000 μ g/dish ND –/– Zhurkov et al. (1983) TA 97, 98, 100 Gene reversion 50–750 μ g/mL plate incorporation
assay 48 h –/– Brams et al. (1987)

TA 102 Gene reversion Up to 5,000 μ g/plate ND –/– Jung et al. (1992) TA 98, 100, 1535, 1537, 1538 Gene reversion 0.1–5,000 μ g/ plate 2 d –/– Dow Chemical Co. (1977) TA 1530, 1535, 1950, 1538, 100, 98, 1978 Gene reversion 0.2% AN vapor (200 μ g/plate) 1 h –/+ (weaker response with TA 100, 98, and 1978) de Meester et

al. (1978); Dow Chemical Co. (1976) TA 98, 100 Gene reversion ND, plate incorporation
assay ND +/+ Khudoley et al. (1987)

TA 100 Gene reversion 806–12,100 μ g/ plate 48 h –/(+) Hakura et al. (2005)

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Table 4-53. Summary of studies on the mutagenicity /genotoxicity of AN

Test system Endpoint/effect Exposure concentration Exposure

duration Result a Reference TA 1535/pSK1002 umu gene expression

(increased β

- galactosidase activity) ND, 0.1 mL AN

in 2.5 mL culture medium 2 h –/– Nakamura et al. (1987)

TA 1530 Gene reversion 0.1 mL 24-hr urine from rats and mice treated with a single dose 30 mg/kg AN i.p. (plate incorporation assay) 48 h + LambotteVandepaer et al. (1985, 1981, 1980)

E. coli WP2 series Gene reversion

( trp – → trp + ) 75 or 150 μ mol/

plate 2–3 d + c Venitt et al. (1977)
E. coli PQ37 SOS chromotest ND 2 h –/– Brams et al. (1987) Short-term assays—fungi
S. cerevisiae JD1 Mitotic gene

conversion 250 or

500 μ g/mL 18 h –/+ Brooks et al. (1985); Shell Oil Co. (1984a)
S. cerevisiae D61.M Chromosome loss 0.8 or 1.36 mg/mL 16 h –/– Whittaker et al. (1990) Short-term assays—fruit fly
Adult female Drosophila ZESTE system Sex chromosome loss Inhalation exposure to 2.7 ppm AN 50 min or

70 min + Osgood et al. (1991)

Mosaic eye in hatching females Somatic recombination

and mutation Treatment of

larvae with 5– 20 mM AN Single dose,

incubate for 9–11 d (+) Vogel (1985)

Germ cells of male D. melanogaster Sex-linked recessive

lethal Feeding:

420 ppm or injection: 3,500 ppm Feeding: 3 d – Foureman et al. (1994)

Wing spots of Drosophila (mwh +/+ flr +/mei-9) Somatic mutation and

recombination Gas exposure of

larvae to 0.5– 1 μ L/1,150 mL 0.5 or 1 h (+) Würgler et al. (1985)

D. melanogaster ZESTE (inhibition of taxol-purified microtubule assembly in vitro) Aneuploidy 5 mM Microtubule assembly monitored for 80 min + Sehgal et al. (1990)

Other short-term assays Supercoiled plasmid DNA pBR322 CEO induced DNA

strand breaks 50 mM CEO

incubated with 1.1 μ g supercoiled pBR322 plasmid DNA 3 h + Yates et al. (1994)

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Table 4-53. Summary of studies on the mutagenicity /genotoxicity of AN

Test system Endpoint/effect Exposure concentration Exposure

duration Result a Reference SV40 phage DNA CEO induced DNA

strand breaks, but not AN 1 mM CEO

incubated with 5,000 dpm [ 3 H]-thymidine labelled SV–40 phage DNA 17 h + Peter et al. (1983b)

In vitro mammalian cell assays
Gene-locus mutations at the Tk (thymidine kinase) locus ( Tk +/– → Tk –/– ) 40 μ g/mL AN 3 h –/+ Crespi et al. (1985)

Mutation at Tk

locus 1.4 mM AN 2 h –/+ Recio and Skopek (1988a, b)
Mutation at Tk

locus 100 μ M and 150 μ M CEO 2 h + Recio and Skopek (1988a, b) Abnormality at chromosome 17 in 1 of 8 CEO-induced tk s mutant clones NA b NA + Kodama et al. (1989) Human lymphoblasts Tk 6

CEO-induced

mutations at the hprt locus NA NA + Recio and Skopek (1988a) Human lymphoblasts AHH-1 Gene-locus mutations

at the hypoxanthine guanine phosphoribosyl transferase locus 25 μ g/mL AN 28 h + Crespi et al. (1985)

Mutation at Tk +/– locus 30 and 40 μ g/mL

AN ND + Oberly et al. (1996)
Mutation at Tk +/– locus 10–40 μ g/mL AN 4 h +/+ Rudd (1983)
Mutation to ouabain or 6-TG resistance 12.5–200 μ g/mL

AN 2 h +/+ Garner and Campbell (1985)
Induction of Tk

–/–

mutants 80–225 μ g/mL

AN 2 h +/+ Lee and Webber (1985)
Induction of Tk

–/–

mutants 30 nL/mL AN 4 h +/+ Myhr et al. (1985) L5178Y mouse lymphoma cells

Induction of Tk –/–

mutants 5–69 μ g/mL AN 3 h +/+ Amacher and Turner (1985)
L5178Y Tk +/+ Mutation to ouabain

resistance (Na + /K + ATPase locus) 12.5–100 μ g/mL

AN 2 h – Styles et al. (1985)

L5178Y Tk +/– Mutation to

trifluorothymidine resistance 12.5–100 μ g/mL

AN 2 h – Styles et al. (1985)

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Table 4-53. Summary of studies on the mutagenicity /genotoxicity of AN

Test system Endpoint/effect Exposure concentration Exposure

duration Result a Reference
P388F mouse lymphoma tk +/– Mutation to 5-iodo2-deoxyuridine resistance 80–160 μ g/mL

AN 24–48 h –/+ Anderson and Cross (1985)

V79/hprt Induction of

8-azaguanine resistance 50–200 μ g/mL

AN 2 h –/– Lee and Webber (1985)

HeLa cells UDS 2.5 mg/mL AN 2.5 h –/– Martin and Campbell (1985) Human lymphocytes UDS 5 × 10 -1 M 4 h –/+ Perocco et al. (1982) Primary cultures of F344 rat hepatocytes UDS 0.026–53 μ g/mL AN 20 h – Probst and Hill (1985) Primary cultures of F344 rat hepatocytes UDS 10 -1 –10 2 μ g/mL AN 18–20 h – Williams et al. (1985) Primary F344 rat hepatocyte UDS 0.01–1 mM AN 17–19 h – Butterworth et al. (1992) Primary F344 rat hepatocyte UDS 0.01–0.1 mM CEO 17–19 h – Butterworth et al. (1992) Human mammary epithelial cell UDS 0.1 mM CEO 24 h + Butterworth et al. (1992)
Human bronchial epithelial cells DNA single-strand

breaks 200 and

500 μ g/mL AN 20 h + Chang et al. (1990) Rat hepatocytes DNA single-strand

breaks 65.8 μ g/mL AN 3 h + Bradley (1985)

CHO cells DNA single-strand

breaks 7 × 10 -2

–

1 × 10 -1 M AN 1 h +/+ Douglas et al. (1985) CHO cells DNA single-strand

breaks ND ND –/– Lakhanisky and Hendrickx (1985) SHE cells DNA single-strand

breaks 200 or

400 μ g/mL AN 18 h + Parent and Castro (1979)
Human bronchial epithelial cells SCEs 150 and 300 μ g/mL AN 20 h + Chang et al. (1990) Human lymphocytes SCEs 5 × 10 -4 M 1 h –/+ Perocco et al. (1982)
CHO cells SCEs 10 -7 –10 -4 M AN 3 h – d Ved Brat and Williams (1982)
CHO cells cocultured with freshly isolated rat hepatocytes SCEs 10 -4 M AN 3 h + d Ved Brat and Williams (1982) CHO cells SCEs 2 mM AN 1 h –/+ Natarajan et al. (1985) CHO cells CAs 4 mM AN 1 h +/+ Natarajan et al. (1985)
CHL fibroblast CAs 12.5 μ g/mL AN 24 and 48 h + d Ishidate and Sofuni (1985)

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Table 4-53. Summary of studies on the mutagenicity /genotoxicity of AN

Test system Endpoint/effect Exposure concentration Exposure

duration Result a Reference
CH1-L liver fibroblast CAs 2.5 μ g/mL AN 36 h + Danford (1985)

Chinese hamster cell line Don-6 CAs 1 × 10 -4 M or 0.0053 mg/mL 26–30 h + Sasaki et al. (1980)
CHO cells MN 10 -1 M AN 1 h +/+ Douglas et al. (1985) Rat liver (RL4) cells CAs, polyploidy,

SCEs 1.25, 2.5, 5.0, or

10 μ g/mL AN 2 h – d Priston and Dean (1985); Shell Oil Co. (1984b)
CHO cells Inhibition of cell

growth and RNA synthesis 0.001, 0.002, and

0.005% (v/v) AN 8 d + d Mangir et al. (1991)

In vitro mammalian cell transformation
SHE cells Cell transformation 50 or 100 μ g/mL AN 6 d + Parent and Castro (1979)
SHE cells Enhancement of viral

transformation 100 or

200 μ g/mL AN 18 hrs before

SA7 or 5 hrs after SA7 inoculation + Parent and Castro (1979)

SHE cells Cell transformation 0.01–1 μ g/mL AN 7 d + Barett and Lamb (1985)
Mouse fibroblasts NIH/3T3 cells Cell transformation 12.5–200 μ g/mL AN 48 h + Banerjee and Segal (1986)
Mouse fibroblasts C3H/10T1/2 cells Cell transformation 3–100 μ g/mL AN 48 h + Banerjee and Segal (1986)
Mouse fibroblasts C3H/10T1/2 cells Cell transformation 16 μ g/mL AN 24 h –/(+) Lawrence and McGregor (1985)
Balb/c-3T3 cells Cell transformation 8.8 μ g/mL AN 48 h –/+ e Matthews et al. (1985)
Balb/c-3T3 cells Ouabain-resistant

mutants 50 μ g/mL AN 24 h –/+ Matthews et al. (1985)
NIH 3T3 cells Cell transformation

after transfection with CEO modified ras DNA NA 14 h – Yuan and Wong (1991)

a NA = not applicable; ND = not determined.
b + = Positive;– = negative; (+) = borderline positiv e.

c S9 activation not needed.
d S9 not included in the assay.

e With or without coculture with lethally X-irradiate d primary F344 RLCs.



### In vitro evidence indicates that AN can be directl y mutagenic, most likely through the
formation of CEO-DNA adducts. In short-term tests with bacteria, AN induced mutations in a majority of test systems, most often requiring exog enous metabolic activation (Table 4-53). In

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mouse lymphoma cell assays, AN induced mutations at the Tk locus in most assays (Table 4-53). In human lymphoblast Tk 6 cells devoid of CYP450 activity, AN induced multi ple mutations at
the Tk locus only in the presence of metabolic activation (Recio and Skopek, 1988a, b; Crespi et al., 1985). CEO was mutagenic in Tk 6 cells at 10-fold lower concentrations than AN its elf and was as mutagenic in this test system as the well-kn own mutagen, ethyl methanesulfonate (Recio and Skopek, 1988a, b). CEO also induced multiple m utations at the hprt locus in Tk 6 cells (Recio and Skopek, 1988a). CEO induced UDS in cult ured human mammary epithelial cells but not in cultured rat hepatocytes (Butterworth, 1992)

. Supporting evidence for the direct mutagenicity of AN and its metabolites comes from in vivo studies (Table 4-53). Increases in the occurr ence of MN in buccal mucosal cells and blood lymphocytes were recently reported in AN exposed wo rkers in China (Fan et al., 2006). Three studies of AN workers reported genotoxic effects su ch as DNA strand breaks, nondisjunction of sex chromosomes, and CAs (Beskid et al., 2006; Xu e t al., 2003; Borba et al., 1996), whereas an earlier study did not find elevated frequency of CA s in exposed workers (Thiess and Fleig, 1978). Increases in cytogenetic aberrations such a s MN were found in assays of exposed rats (Wakata et al., 1998) and a single assay of mice (F ahmy, 1999), but were not evident in other rat and mouse assays (Morita et al., 1997; Zhurkov et a l., 1983; Leonard et al., 1981; Rabello-Gay and Ahmed, 1980). Comet assays found DNA damage in forestomach, colon, bladder, lung, and brain in mice, following single i.p. injections of 20 mg/kg AN, and in forestomach, colon, kidney, bladder, and lung of rats injected with 30 mg/kg (Sekihashi et al., 2002). UDS was detected by following the time course of 3 

### H-thymidine incorporation into DNA in lung, testis, and gastric tissue, following admi nistration of single oral doses of 46.5 mg/kg AN to Sprague-Dawley rats (Ahmed et al., 1996b, 1992a, b; Abdel-Rahman et al., 1994a). Autoradiographic techniques did not detect UDS foll owing incubation of primary cultures of hepatocytes or spermatocytes from F344 rats given s ingle oral doses of 75 mg/kg or five daily doses of 60 mg/kg-day AN (Butterworth et al., 1992) . Dominant lethal effects (from mutations in germ cells) were not found in mice given single i.p. doses of 30 mg/kg AN (Leonard et al., 1981) or rats given five oral doses of 60 mg/kg (Wo rking et al., 1987). DNA binding by AN or its metabolites was indicated by elevated levels of radioactivity in DNA from several tissues in rats given single oral doses of 46.5 mg/kg radiolab eled AN (Abdel-Rahman et al., 1994b; Ahmed et al., 1992a, b; Farooqui and Ahmed, 1983a).
In the European Union Risk Assessment Report on Acrylonitrile (EC 2004), AN was regarded as “genotoxic or at least mutagenic, despi te the recent publication of Whysner et al. (1998a) which argues for a possible nongenotoxic me chanism for the tumour induction in experimental animals.”

4.5.2.5. Indirect Genotoxicity As discussed in Section 4.5.1.2.2, studies are avai lable that investigated the indirect

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genotoxicity of AN resulting from oxidative stress. These studies measured 8-oxodG levels in DNA as biomarkers of oxidative DNA damage from AN e xposure. 8-OxodG is mutagenic (Kamiat et al., 1992; Moriya et al., 1991; Wood et al., 1990) and causes GC → TA transversions during DNA replication.

In vitro studies Zhang et al. (2000) studied AN-induced morphologic al transformation in SHE cells. SHE cell culture was treated in vitro for up to 7 d ays with 0–75 μ g/mL AN in 12.5 μ g/mL increments (75 μ g/mL was cytotoxic, with 50% reduction in cell colo ny number). After 7 days of exposure, there was a dose-dependent increase in morphological transformation at 50, 62.5,
and 75 μ g/mL, reaching a transformation frequency of 1.3% a t 75 μ g/mL. After a 24-hour AN exposure, an increase in transformation was not obs erved at all concentrations. Levels of
8-oxodG in DNA isolated from cells incubated with 7 5 μg/mL were increased to 192 and 186% of control after 2 and 3 days, indicating an associ ation between cell transformation and oxidative DNA damage. However, no increase in 8-oxodG was ob served after 1 or 7 days. AN-induced morphological transformation was inhibited by cotre atment with the antioxidants α -tocopherol (100 μ M: up to 65% inhibition) and (-)-epigallocathechin -3-gallate (5 μ M: up to 87% inhibition) for 7 days. Cotreatment with antioxida nts also inhibited the formation of 8-oxodG in
SHE cell DNA from treatment with 75 μ g/mL AN. In a later study by the same research group, Zhang et al. (2002) investigated the time course of SHE cell morphological transformation in the presence of 75 μ g/mL AN. The results indicated that statistically significant increases in morphological transformation frequency could not be observed until after 2 consecutive days of e xposure; a plateau at a transformation frequency of about 2% was reached after 4–5 days of exposure. In another experiment, coadministration of 0.5 mmol/L ABT, a nonspecific s uicidal CYP450 inhibitor, for 7 days significantly reduced the rate of cell transformati on from about 1.25% to about 0.3% (shown graphically), demonstrating the need for metabolic activation of AN in this test system. Zhang et al. (2002) also showed that AN (25, 50, a nd 75 μ g/mL) increased the amount of ROS (measured by 2,3-dihydroxybenzoic acid producti on) in the SHE cells after 4, 24, and 48 hours of treatment. At the same time, xanthine oxidase (which generates the superoxide radical and hydrogen peroxide via oxidation of hypo xanthine or xanthine by oxygen) activity was increased by 47% in SHE cells after 24 hours of treatment with 75 μ g/mL AN. After 48 hours of treatment, xanthine oxidase activity wa s increased in both 50 and 75 μ g/mL (80%) AN groups. This increase in xanthine oxidase activ ity was blocked by cotreatment with 0.5 mM ABT. On the other hand, antioxidant GSH was deplet ed 66–80% by all doses of AN (25, 50, and
75 μ g/mL) after 4 hours of treatment and returned to co ntrol levels after 24 hours. At 48 hours, a significant increase in GSH was observed with the 7 5 μ g/mL group but not in other dose groups. Antioxidant enzyme catalase activity was significan tly decreased after 4 hours of treatment with

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50 and 75 μ g/mL AN but increased after 24 and 48 hours of trea tment. Cotreatment with ABT prevented the decrease and increase in activity of catalase at 4 and 24 hours after treatment, respectively. A transient decrease in SOD activity was also observed after 4 hours of treatment
with 75 μ g/mL AN.
The effect of AN on catalase and SOD activities wa s also studied in a cell-free system (Zhang et al., 2002). Catalase and SOD activities were determined in samples containing purified catalase or SOD incubated with 75 μ g/mL AN in the presence or absence of SHE cell homogenate. In the absence of a metabolic source o f SHE cell homogenate, no inhibition of catalase activity was seen following incubation up to 60 minutes with AN. In the presence of SHE cell homogenate, AN significantly decreased cat alase activity in a time-dependent manner after 10 minutes of incubation. Similarly, a signi ficant time-dependent decrease in SOD activity was observed following 30 minutes incubation with A N. The study authors concluded that morphological transformation of SHE cells is caused by oxidative stress as a result of oxidative
metabolism of AN. Kamendulis et al. (1999a) also investigated oxidat ive DNA damage induced by AN in DITNC1, a rat glial astrocyte cell line, and primar y rat hepatocytes exposed to AN in vitro (see Section 4.5.1.2.2). AN was cytotoxic at concentrat ions ≥ 2.5 mmol/L (133 μ g/mL) (as measured by the release of LDH from the cells) to both cell lines, following ≥ 4 hours of exposure. Concentrations of 0.01, 0.1, and 1.0 mmol/L AN (0.5 3, 5.3, and 53 μ g/mL, respectively) caused a dose-dependent increase in formation of 8-oxodG i n astrocytes but not in hepatocytes. Corresponding increases in ROS formation were also observed in astrocytes only. However, no oxidative lipid damage (as evaluated by formation o f MDA, a product of lipid peroxidation) was found in either cell type following treatment with AN at all exposure concentrations or durations. The formation of 8-oxodG in rat astrocytes was reve rsible. Following treatment with AN for 24 hours and removal of AN for 24 hours afterwards, 8-oxodG levels returned to control values
in all concentrations examined. Kamendulis et al. (1999a) concluded that this demonstrated property was consistent with tumor promoting agents

. Pu et al. (2006) investigated oxidative DNA damage induced by AN in D1TNC1 rat astrocyte cell line using the fpg-modified comet as say. Increase in oxidative DNA damage was observed in astrocytes treated with 1 mM AN for 24 h. No increase in oxidative DNA damage was observed in astrocytes treated with 0.005 – 0.7 5 mM AN for 24 hours. Jacob and Ahmed (2003b) investigated oxidative str ess in cultured NHA (4631) treated with up to 400 μ M AN for 12 hours. AN was cytotoxic at concentrati ons >50 μ M. Cell viability was 85, 78, and 58%, respectively, at AN concentrat ions of 100, 200, and 400 μ M. Significant
increases in measures of oxidative stress were obse rved at cytotoxic concentrations of 200–400

μ M AN: the production of ROS was increased four- to sevenfold, whereas 8-oxodG levels were
increased more than twofold.

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Esmat et al. (2007) investigated cytoxicity in rat (strain not known) primary glial cells exposed to 0–5.0 mM AN up to 12 hours. Cell membra ne integrity was evaluated by trypan blue exclusion and LDH leakage. About 50% membrane dama ge in primary glial cells was observed in incubations containing 1.0 mM AN for 3 hours. T hus, subsequent studies on AN-induced oxidative stress were performed using 1 mM AN for 3 hours incubation. AN increased MDA levels (indicator of lipid peroxidation) to about n inefold compared with control incubations and depleted GSH level to about 7% of controls., while no change in total glutathione level was
observed. AN induced CN
– 

### formation by glial cells and decreased ATP level b y about 90% as compared with the control. Pretreatment with 5 mM NAC (an acetylated precursor of cysteine and GSH, and an antioxidant), reduced MDA level by 40% as compared with glial cells treated with AN alone and raised GSH and total glutathione level in cell extract to about 2.5-fold of control and AN alone treated group. Pretreatment w ith NAC also caused reduction of CN
– 

### induced by AN to about 15% as compared wth the AN a lone treated group, and raised ATP level to about sixfold, as compared with the AN alone tre ated group. It should be noted that NAC stimulated GSH synthes is, enhanced glutathione-Stransferase activity, and was a powerful nucleophil e capable of scavenging free radicals (De Vries and De Flora, 1993). Observed increases in G SH and total glutathione and decrease in CN 

### formation with NAC pretreatment in Esmat et al. (20 07) would suggest that most of the administered AN could be detoxified via conjugation via the GSH pathway (consistent with findings by Carerra et al., 2007), as less AN was a vailable for oxidation to CN - 

### . Esmat et al. (2007) concluded that AN toxicity was at least part ly mediated by oxidative stress.

In vivo studies As described in Section 4.5.1.2.2, Jiang et al. (19 98) reported increases in measures of
oxidative stress in the brain cortices but not the livers of male Sprague-Dawley rats exposed to AN in drinking water at concentrations of 50–200 pp m for up to 90 days. Increases in ROS and oxidative DNA damage (increased levels of 8-oxodG) and concomitant decreases in antioxidant enzymes (catalase, SOD) were observed in the brain cortices of exposed rats. Transient small decreases in the antioxidants vitamin E and glutath ione were also observed in the brain cortices of AN-exposed rats only at 14 days. A transient in crease in MDA level was observed only at the highest dose group after 14 days but not at other t ime points. Pu et al. (2009) reported oxidative DNA damage in W BC and brain of male SpragueDawley rats treated with 100-200 ppm AN; however, E PA has identified issues with this study (see Section 4.5.1.2.2). In another study, Whysner et al. (1998a) examined the ability of AN to induce oxidative DNA damage in the brain, liver, and forestomach of rats by exposing male Sprague-Dawley and F344 rats up to 300 ppm AN in drinking water for 21 days (see Section 4.5.1.2.2). As shown in Table 4-54, elevated levels of 8-oxodG were found i n DNA from the brain and liver of Sprague-

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Dawley rats. However, 8-oxodG levels in the forest omach of exposed Sprague-Dawley rats and the brain of exposed F344 rats were not statistical ly significantly elevated compared with controls. Significant increase in 8-oxodG levels w as found in the liver of exposed SpragueDawley rats, although the liver is not a target org an for carcinogenicity in adult rats.

Table 4-54. Formation of 8-oxodG in DNA from tissu es of male SpragueDawley and F344 rats exposed to AN in drinking wate r for 21 days

Formation of 8-oxodG (mol/10 5 mol dG) Sprague-Dawley rats F344 rats Dose group Liver Forestomach Brain Brain
Control 0.67 ± 0.22 0.68 ± 0.14 0.62 ± 0.08 0.79 ± 0.37 3 ppm 0.72 ± 0.06 1.77 ± 0.55 0.86 ± 0.41 1.07 ± 0. 41 30 ppm 0.95 ± 0.19 a 1.59 ± 0.30 1.35 ± 0.49 a 1.03 ± 0.38 300 ppm 0.96 ± 0.15 a 1.44 ± 1.22 1.29 ± 0.10 a 1.06 ± 0.48 b

a Significantly different from controls ( p < 0.05) as calculated by the study authors.
b Exposure was at 100 ppm.

Source: Whysner et al. (1998a).



### Whysner et al. (1998a) also exposed male Sprague-D awley rats to 100 ppm AN in drinking water for up to 94 days. (This dose was c arcinogenic in Sprague-Dawley rats in a chronic study [Johannsen and Levinskas, 2002a; Biod ynamics, 1980b].) The rats were divided into four groups and were exposed to distilled wate r, 100 ppm AN, 5 mg MNU (a DNA-reactive carcinogen that produces glial cell tumors in rats) per week, or 100 ppm AN plus 5 mg MNU per
week. Levels of 8-oxodG in brain and liver of rats exposed to 100 ppm AN were significantly greater than those in controls after 10 days (1.31 ± 0.52 in brains of exposed rats vs. 0.65 ± 0.22 mol per 10 5 

### mol dG in controls and 0.70 ± 0.20 in livers of ex posed rats vs. 0.49 ± 0.10 mol per 10 5 

### mol dG in controls). Administration of 5 mg/kg MN U alone did not increase the level of
8-oxodG in the brain of treated rats but increased 8-oxodG in the liver after 10 days. However, coadministration of 100 ppm AN and MNU increased 8- oxodG level in the brain after 31 days and 94 days when compared with the MNU-only group. Whysner et al. (1998a) suggested that AN-induced tu mors may be produced by a mode of action involving 8-oxodG. However, several finding s in this study did not support this proposed mode of action. First, no significant increase in 8-oxodG levels were found in the brain DNA of F344 rats exposed to AN in the 21-day study whereas AN was carcinogenic to F344 rats in a chronic drinking water study (Johannsen and Levinsk as, 2002b). Second, although a significant
increase in 8-oxodG levels was found in the brain D NA of Sprague-Dawley rats exposed to AN for 21 days, no dose-dependent increase was observe d above 30 ppm, which was not the dose producing the highest occurrence of tumors in the c hronic bioassay. Third, no increase in

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8-oxodG levels were found in the forestomach DNA of exposed rats. The forestomach was a target organ for AN carcinogenicity. Finally, incr ease in 8-oxodG levels was found in liver DNA of exposed rats. Liver was not a target organ for AN carcinogenicity in adult rats. Therefore, there was no association between 8-oxodG levels and tumorigenicity in target organs. Results of indirect mutagenicity/genotoxicity stud ies of AN are summarized in
Table 4-55.

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Table 4-55. Summary of studies on the indirect mut agenicity or genotoxicity of AN

Test system Endpoint/effect Exposure concentration Exposure

duration Result Reference In vitro mammalian cell assays
SHE cells Cell

transformation 50–75 μ g/mL AN 7 d + Zhang et al. (2000)
SHE cells 8-oxodG in DNA 75 μ g/mL AN Increased after 2 and 3 d but not after 1 or 7 d (+) Zhang et al. (2000)

SHE cells ROS 25–75 μ g/mL AN 4–48 h + Zhang et al. (2002) DITNC1rat glial astrocytes 8-oxodG in DNA 0.01–1 mM AN (0.53–53 μ g/mL) 4 or 24 h + a Kamendulis et al. (1999a)

D1TNC1 rat astrocytes DNA damage in

fpg-comet assay 1 mM 24 h + Pu et al. (2006)

Rat hepatocytes 8-oxodG in DNA 0.01–1 mM AN 4 or 24 h – Kamendulis et al. (1999a)
NHAs 8-oxodG in DNA 200–400 μ M AN 12 h + Jacob and Ahmed (2003b)
NHAs ROS 200–400 μ M AN 12 h + Jacob and Ahmed (2003b)
In vivo studies in ratsMale SpragueDawley rats 8-oxodG in brain

cortex DNA 0–200 ppm AN in

drinking water 100 and 200 ppm:

+ after 14–90 d 50 ppm: + after 28 and 90 d + Jiang et al. (1998)

Male SpragueDawley rats 8-oxodG in liver

DNA 0–200 ppm AN in

drinking water 14–90 d – Jiang et al. (1998)

Male SpragueDawley rats 8-oxodG in WBC

and brain DNA 100 or 200 ppm

AN in drinking
water 28 days + Pu et al. (2009)

Male SpragueDawley rats 8-oxodG in brain

DNA 30 or 300 ppm

AN in drinking
water 21 d + Whysner et al. (1998a)

Male SpragueDawley rats 8-oxodG in liver

DNA 30 or 300 ppm

AN in drinking
water 21 d + Whysner et al. (1998a)

Male SpragueDawley rats 8-oxodG in

forestomach DNA 0–300 ppm AN in

drinking water 21 d – Whysner et al. (1998a)
Male F344 rats 8-oxodG in brain

DNA 0–100 ppm AN in

drinking water 21 d

– Whysner et al. (1998a)Male SpragueDawley rats 8-oxodG in brain

DNA 100 ppm AN in

drinking water 3–94 d + Whysner et al. (1998a)

a The formation of 8-oxodG was reversible. Following treatment with AN for 24 hrs and removal of AN for 24 hrs afterwards, 8-oxodG levels returned to control valu es.
+ = Positive;– = negative; (+) = borderline positiv e.

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4.6. SYNTHESIS AND EVALUATION OF MAJOR NONCANCER E FFECTS AND
MODE OF ACTION—ORAL AND INHALATION
4.6.1. Oral No studies are available regarding noncancer healt h effects in humans following acute, subchronic, or chronic oral exposure to AN. The chronic oral noncancer toxicity database for A N consists of results from four rat toxicity and cancer bioassays (one with F344 rats a nd three with Sprague-Dawley rats) (see Table 4-56 for references), one toxicity and cancer bioassay with B6C3F 1 

### mice (NTP, 2001), and a three-generation developmental/reproductive t oxicity study with Sprague-Dawley rats (Friedman and Beliles, 2002; Litton Bionetics, 1992 ). NOAELs and LOAELs for noncancer
effects in these studies are summarized in Table 4- 56. Also included in Table 4-56 are summaries of results from a 12-week gavage study of nerve conduction velocities in male Sprague-Dawley rats (Gagnaire et al., 1998), a 60-d ay gavage study of testicular toxicity in male CD-1 mice (Tandon et al., 1988), a 14-week gavage t oxicity bioassay in B6C3F 1 

### mice (NTP, 2001), a developmental toxicity study in Sprague-Da wley rats exposed by gavage during GDs 6– 15 (Murray et al., 1978), and a neurobehavioral stu dy of Sprague-Dawley rats exposed to AN in drinking water for up to 12 weeks (Rongzhu et al., 2007).

Table 4-56. Noncancer effects in animals repeatedl y exposed to AN by the oral route

NOAEL LOAEL Reference Species Exposure conditions, mg/kg-d (mg/kg-d) Effect

Johannsen and Levinskas (2002b); Biodynamics (1980c) F344 rat 0, 0.1, 0.3, 0.8, 2.5, 8.4 (M)

0, 0.1, 0.4, 1.3, 3.7, 10.9 (F) DW, 2 yr s; sacrifices at 6, 12, and 18 mos and termination (99 wks or 699–706 d [F]; 107 wks or 770–777 d [M]) 0.1(M) 0.1 (F)

2.5 (M) 1.3 (F)

2.5 (M) 3.7 (F)

0.4 (F)

2.5 (M) 0.3 a (M)

0.4 a (F)

8.4 b (M) 3.7 b (F)

8.4 a (M) 10.9 a (F)

1.3 b (F)

8.4 b (M) Forestomach squamous cell

hyperplasia and hyperkeratosis, increased incidence

Decreased survival after 18 mos

Decreased BW (>10% compared with control)

Increase in serum alkaline phosphatase (F only)

Increase in epidermal inclusion cysts (M only)
Johannsen and Levinskas (2002a); Biodynamics (1980a) Sprague-Dawley rat 0, 0.09, 8.0 (M)

0, 0.15, 10.7 (F) DW, 22 mos (M); 19 mos (F); sacrifices at 6, 12, and 18 mos and termination ND (M) 0.15 (F)

8.0 (M) 0.15 (F)

0.09 (M) 0.15 (F) 0.09 b (M)

10.7 a (F)

ND (M) 10.7 a (F)

8.0 b (M) 10.7 a (F) Forestomach squamous cell

hyperplasia, increased severity

Renal transitional cell hyperplasia (F only)

Decre ased survival at 10 mos (M + F); decreased BW (10/8% [M/F])

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Table 4-56. Noncancer effects in animals repeatedl y exposed to AN by the oral route

NOAEL LOAEL Reference Species Exposure conditions, mg/kg-d (mg/kg-d) Effect

Johannsen and Levinskas (2002a); Biodynamics (1980b) Sprague-Dawley rat 0, 0.1, 10 (M + F)

Gavage, 7 d/wk for 20 mos; sacrifices at 6, 12, and 18 mos and termination 0.1 (M + F)

0.1

0.1 10 a (M + F)

10 a

10 a Forestomach squamous cell hyperplasia, increased severity

Renal transitional cell hyperplasia at some but not all sacrifices

Decreased survival after 14 mos (M + F); decreased BW (6–13% compared with controls [M only]). Quast (2002); Quast et al. (1980a) Sprague-Dawley rat 0, 3.4, 8.5, 21.3 (M)

0, 4.4, 10.8, 25.0 (F) DW, 2 yrs 3.4 (M) ND (F)

ND (F)

ND (M) 4.4 (F)

8.5 (M) ND (F)

8.5 (M) 10.8 (F) 8.5 b (M)

4.4 b (F)

4.4 b (F)

3.4 b (M) 10.8 b (F)

21.3 b (M) 4.4 b (F)

21.3 b (M) 25.0 b (F) Forestomach squamous cell

hyperplasia and hyperkeratosis, increased incidence

Gliosis in brain with or without perivascular cuffing in females; not significant in males

Chronic nephropathy

Decreased survival after 300 (F) or 480 (M) d

Decreased BW (>10% compared with control); clinical signs of nervous system dysfunction NTP (2001) B6C3F 1 mouse 0, 2.5, 10, 20 (M + F)

Gavage, 5 d/wk for 2 yrs Adjusted doses: 0, 1.8, 7.1, 14.3 mg/kg-d (M + F) 1.8 (M) 7.1 (F)

1.8 (M) 14.3 (F)

ND (F)

7.1 (M + F) 7.1 b (M)

14.3 b (F)

7.1 b (M) ND (F)

1.8 b (F)

14.3 a (M + F) Forestomach squamous cell hyperplasia and hyperkeratosis, increased incidence

Increased incidence of Harderian gland hyperplasia

Increased incidence of ovarian cysts or ovarian atrophy

Decreased survival after 15 wks

NTP (2001) B6C3F 1 mouse 0, 5, 10, 20, 40 60 (M + F)

Gavage, 5 d/wk for 14 wks. Adjusted doses: 0, 3.6, 7.1, 14.3, 28.6, and 42.9 (M + F) 28.6 (M) 14.3 (F)

14.3 (M + F) ND (M)

28.6 a (F)

28.6 b (M + F) Forestomach inflammation, ulceration, and epithelial hyperplasia, increased incidence in F only No histopathology data for 60 mg/kg groups

Increased mortality

Tandon et al. (1988) CD-1 mouse 0, 1, 10 (M only)

Gavage, for 60 d 1 10 b 45% decreased sperm count; 40% of seminiferous tubules examined degenerated

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Table 4-56. Noncancer effects in animals repeatedl y exposed to AN by the oral route

NOAEL LOAEL Reference Species Exposure conditions, mg/kg-d (mg/kg-d) Effect

Friedman and Beliles (2002); Litton Bionetics (1992) Sprague-Dawley rat 0, 11, 37 (M)

0, 20, 40 (F) DW, three-generation reproduction study ND

ND 11 b (M) 20 b (F)

11 b (M) 20 b (F) Decreased viability for F1b pups;

no changes in fertility index or pregnancy outcome for F1a, F1b, F2a, F2b, F3a, or F3b generations

LOAEL for decreased lactation index in F1b parents for F2a pups; small deficits in postnatal pup weights (10–40%, variable across generations) and postnatal survival (about 10%, variable across generations) in higher dosed
groups Murray et al. (1978) Sprague-Dawley rat 0, 10, 25, 65 (F only)

Gavage GDs 6–15 10

10 25

25 Maternal effects: forestomach hyperplasia, 11% increased liver weight, 22% decrease in BW gain

Fetal effects: missing vertebrae in 6/17 litters, 7% decreased BW Gagnaire et al. (1998) Sprague-Dawley rat 0, 12.5, 25, 50 (M only)

Gavage, 5 d/wk for 12 wks 25 50 a SCV decreased beginning wk 6 (-7.5%), –17.8% by wk 12; -10.6% after 8 wks recovery; decreased BW after 4 wks (-17% at wk 12); hind limb weakness in 5/11 surviving high-dose rats after wk 9 Rongzhu et al. (2007) Sprague-Dawley rat 0, 4, 13.5 (M only)

DW for 0, 4, 8, 12 wks ND 4 b Neurobehavioral alterations, as indicated by decreased motor coordination, increased training duration, head twitching, trembling, circling, backwardspedaling, and decreased homecage activities Szabo et al., (1984) Sprague-Dawley rats 0, 0.2, 4, 20, and 100 mg/kgday (F only) DW for up to 60 days 4 (F) 20 (F) Enlarged kidneys, increase in regional hyperplasia of the gastric

mucosa Szabo et al. (1984) Sprague-Dawley rats 0, 0,2, 4, 20 or 100 mg/kgday (F only) Daily gavage for up to 60 days ND 0.2 (F) Adrenocortical hyperplasia

Quast et al. (1975) Beagle dog 0, 10, 16, 17 (M)

0, 8, 17, 18 (F) DW for 6 months 10 (M) 8 (F) 16 (M)

17 (F) Early mortality, histopathological

lesions of the esophagus and tongue.

a significantly different from controls ( p < 0.01).
b significantly different from controls ( p < 0.05).

DW = drinking water; F = female; M = male; ND = not determined

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Forestomach lesions (epithelial hyperplasia and hy perkeratosis) were the most consistently observed noncancer effect associated w ith chronic oral exposure of rats and mice to
AN and were associated with the lowest LOAELs in AN -exposed rats (Table 4-56). The lowest LOAELs were 0.09 and 10.7 mg/kg-day for increased s everity of forestomach lesions in male and female Sprague-Dawley rats exposed by drinking water (Johannsen and Levinskas, 2002a; Biodynamics, 1980a), 0.3 and 0.4 mg/kg-day for incr eased incidence of forestomach lesions in male and female F344 rats exposed in drinking water (Johannsen and Levinskas, 2002b; Biodynamics, 1980c), and 8.5 and 4.4 mg/kg-day for increased incidence of forestomach lesions in male and female Sprague-Dawley rats exposed in d rinking water (Quast, 2002; Quast et al., 1980a). Increased incidences of animals with hyper plasia or hyperkeratosis of the forestomach
were also observed in B6C3F 1 

### mice exposed by gavage (5 days/week) for 2 years t o 10 mg/kgday (males) or 20 mg/kg-day (females) (NTP, 2001), female B6C3F 1 

### mice exposed to 40 mg/kgday by gavage (5 days/week) for 14 weeks (NTP, 2001 ), and pregnant Sprague-Dawley rats exposed to 25 mg/kg-day by gavage on GDs 6–15 (Murr ay et al., 1978). Other effects observed in orally exposed animals generally were observed a t higher doses (Table 4-56). Kidney effects included increased incidence of ren al transitional cell hyperplasia in Sprague-Dawley rats exposed by gavage or in drinkin g water to about 10 mg/kg-day but not 0.1 mg/kg-day (Johannsen and Levinskas, 2002a; Biod ynamics, 1980a) and increased incidence of chronic nephropathy in Sprague-Dawley rats expos ed to drinking water doses of 3.4 mg/kgday (males) or 10.8 mg/kg-day (females) (Quast 2002 ; Quast et al., 1980a).
Decreased survival was observed after 18 months in F344 rats exposed to drinking water at 8.4 mg/kg-day (males) and 3.7 mg/kg-day (females ) (Johnannsen and Levinskas, 2002b) and in Sprague-Dawley rats exposed to drinking water at 21.2 mg/kg-day (males) and 4.4 mg/kg-day (females) (Quast, 2002). In another drinking water study of Sprague-Dawley rats, decreased survival was observed at 8.0 mg/kg-day (males) and 10.7 mg/kg-day (females). Increased incidences of ovarian lesions (cysts or atrophy) were observed in female mice exposed to gavage doses of 2.5, 10, or 20 mg/kg-day (NTP, 2001), but exposure-related ovarian
lesions were not observed in the chronic rat bioass ays. In a reproductive toxicity study in Sprague-Dawley rats exposed to 0, 100, or 500 ppm A N in drinking water (11 or 37 mg/kg-day [males]; 20 or 40 mg/kg-day [females]), small defic its in postnatal pup weights and pup survival without effects on fertility or pregnancy success w ere observed in three generations exposed to either 100 or 500 ppm (Friedman and Beliles, 2002; Litton Bionetics, 1992) (see Table 4-56). Other reproductive effects observed in animals were a reduction of epididymal sperm counts and degeneration of seminiferous tubules in CD-1 mice e xposed to 10 mg/kg-day by gavage for 60 days (Tandon et al., 1988), but no exposure-rela ted lesions in male reproductive organs were
found in B6C3F 1 

### mice exposed by gavage to up to 40 mg/kg-day for 1 4 weeks or up to 20 mg/kg-day for 2 years (NTP, 2001). Likewise, no effects on sperm motility parameters were
found in male B6C3F 1 

### mice exposed to up to 20 mg/kg-day for 14 weeks (N TP, 2001).

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The only oral developmental toxicity study (Murray et al., 1978) identified 10 and 25 mg/kg-day as a NOAEL and LOAEL for maternal effe cts (increased incidence of forestomach hyperplasia, 10% increased absolute liv er weight, and 22% decreased BW gain) and developmental effects (7% decrease in fetal BW and missing vertebrae associated with short tails in 6/17 litters, compared with 1/38 in the controls ). The study involved daily gavage exposure
on GDs 6–15. Neurological effects in animals associated with ch ronic oral exposure to AN were observed in: (1) a report of gross clinical signs of neurological impairment in about 10% of Sprague-Dawley rats (paralysis, head tilt, circling , and seizures) exposed to drinking water concentrations of 500 ppm (providing doses of about 65 and 74 mg/kg-day for males and females) but not in rats exposed to 100 ppm (13 and 15 mg/kg-day, males and females) (Bigner et al., 1986); (2) decreases (8–15%) in SCV in tail nerves and hind-limb weakness in male Sprague-Dawley rats exposed by gavage to 50 mg/kg-d ay (5 days/week) for 6–12 weeks but not in rats exposed to 25 mg/kg-day (Gagnaire et al., 1 998); and (3) neurobehavioral alterations in male Sprague-Dawley rats exposed to 4 and 13.46 mg/ kg-day AN for 4, 8, or 12 weeks (head twitching, trembling, circling, backwards pedaling, decreased home-cage activities, decreased motor coordination, and learning and memory) (Rongs hu et al., 2007). These studies indicated that neurological impairment in AN-exposed rats occ urred at higher administered doses than doses associated with hyperplasia and hyperkeratosi s in forestomach squamous epithelial cells.

4.6.2. Inhalation
Table 4-57 lists the NOAELs and LOAELs from four c ross-sectional health examinations and surveys of subjective symptoms in Japanese and Chinese acrylic fiber workers (Chen et al., 2000; Kaneko and Omae, 1992; Muto et al., 1992; Sak urai et al., 1978), a cross-sectional examination of performance of acrylic fiber workers in a battery of neurobehavioral tests (Lu et al., 2005a), a study on the effect of AN exposure o n the sperm cells of AN production plant workers (Xu et al., 2003), and three cross-sectiona l surveys of reproductive outcomes in Chinese acrylic fiber or AN manufacturing workers (Dong et al., 2000b; Li, 2000; Dong and Pan, 1995). More detailed descriptions of these studies are in Section 4.1.2.2. Each of these epidemiologic studies measured AN concentrations in workplace air samples and compared results of the examinations and surveys in exposed workers with un exposed workers of similar age. The
human LOAELs and NOAELs in Table 4-57 are mean or m idpoint values of the range of concentrations determined for various groups of exp osed workers. Table 4-57 also lists NOAELs and LOAELs identified in the animal toxicity studies involving repeated inhalation exposure to AN.

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Table 4-57. Noncancer effects in human workers and animals repeatedly exposed to AN by inhalation

NOAEL a LOAEL Reference/ Study subjects Exposure conditions a ppm Effect Muto et al. (1992) Acrylic fiber workers Male workers with average 17 yrs of occupational exposure compared with unexposed workers 0.19 1.13 Statistically significantly increased prevalences of subjective symptoms (e.g., heaviness of stomach, poor memory, irritability) but no increases in prevalences of physical signs or abnormal values in urinalytic, hematological, liver function, or blood pressure variables compared with controls. Sakurai et al. (1978) Acrylic fiber workers Male workers with average 10–12 yrs of occupational exposure compared with unexposed workers ND 4.2 Statistically insignificant increase in inci dence of palpable liver, reddening of the conjunctiva and pharynx, and the occurrence of skin rashes compared with unexposed controls. No survey of subjective symptoms. Kaneko and Omae (1992) Acrylic fiber workers Male workers with average 5.6, 7.0, or 8.6 yrs of occupational exposure in three groups of factories (mean AN concentrations at 1.8, 7.4, and 14.1 ppm) were compared with unexposed workers ND 1.8 Statistically significantly increased prevalences of subjective symptoms (e.g., headaches, tongue trouble, choking lump in chest, fatigue) were found in workers from all three groups of factories when compared with controls.

Chen et al. (2000) Acrylic fiber workers Male and female workers with average 13 yrs of occupational exposure compared with unexposed workers ND 0.48 Statistically significantly increased prevalences of subjective symptoms (e.g., headache, dizziness, poor memory, choking feeling in chest, loss of appetite) compared with controls. Lu et al. (2005a) Acrylic fiber workers Male and female workers with >1 yr of occupational exposure (average duration not available) compared with unexposed workers ND 0.11 Small, but statistically significant, defic its in tests of neurobehavior in monomer workers and fiber workers (average air concentrations of 0.11 ppm for monomer workers and 0.91 ppm for fiber workers) compared with controls. Xu et al. (2003) AN production workers Male workers with 2.8 yrs of occupational exposure in a AN production plant, compared with controls of approximate age range in the general population. ND 0.37 Statistically significant decrease in sperm density and sperm number in exposed workers, statistically significant increase in DNA strand breakage and sex chromosome aneuploidy in sperm cells of exposed workers compared with controls Dong and Pan (1995) Acrylic fiber workers Male and female workers with average 3.2 and 10.2 yrs of occupational exposure compared with unexposed controls ND 3.7 Statistically significant increased prevalen ces of adverse reproductive outcomes (premature delivery [10.7 vs. 3.5%, in wives of exposed males], stillbirths [4.5 vs. 0%, in exposed females], and sterility [5.0 vs. 1.8%, in exposed males]) compared with controls. Dong et al. (2000b) Acrylic fiber workers Male and female workers with average 11 and 10.4 yrs of occupational exposure compared with unexposed controls ND 3.6 Statistically significantly increased prevalences of adverse reproductive outcomes (increased stillbirths [2.7 vs. 0%], birth defects [21.3 vs. 4.8%], and premature deliveries [8.2 vs. 3.9%]) in female workers compared with controls.

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Table 4-57. Noncancer effects in human workers and animals repeatedly exposed to AN by inhalation

NOAEL a LOAEL Reference/ Study subjects Exposure conditions a ppm Effect Li (2000) AN manufacturing workers Female workers with average 14 yrs of occupational exposure compared with unexposed controls ND 7.5 Statistically significant increased prevalen ces of adverse reproductive outcomes (sterility [2.6 vs. 0.8%], pregnancy complications [20.8 vs. 7.1%], premature deliveries [11.6 vs. 4.7%], and congenital defects [25.4 vs. 4.2%]) in female exposed workers compared with controls. Quast et al. (1980b) Sprague-Dawley rats (M + F) 0, 20, 80 ppm, 6 hrs/d, 5 d/wk for 2 yrs ND 20 Statistically significant increase in incide nce of lesions in nasal epithelia at 20 ppm in males and females; focal necrosis in liver of females. At 80 ppm, other lesions occurred at increased incidences—gliosis and perivascular cuffing in brain in both sexes, hepatic necrosis in females, focal nephrosis and thyroid cysts in males, and hyperplasia in nonglandular stomach. Gagnaire et al. (1998) Sprague-Dawley rats (M only) 0, 25, 50, 100 ppm, 6 hrs/d, 5 d/wk for 24 wks ND 25 Statistically significant deficits (5% decrea sed compared with controls) in sensory conduction velocity of the tail nerve. Murray et al. (1978)Pregnant SpragueDawley rats 0, 40, or 80 ppm, 6 hrs/d on GDs 6–15 ND

40 40

80 Maternal weight gain decreased by >20% compared with controls.

No increased incidence of litters with a single malformation; 6/35 litters with short tail, short trunk, missing vertebrae, or missing ribs vs. 1/33 in controls. Saillenfait et al. (1993)Pregnant SpragueDawley rats 0, 12, 25, 50, 100 ppm, 6 hrs/d on GDs 6–20 12

12 25

25 Statistically significant decreased maternal weight gain compared with controls.

Statistically significant decreased fetal BW, >5% decreased compared with controls. No exposure-related increased incidences of litters with fetal anomalies.

a ND = cannot be determined



### In acute AN poisoning cases involving humans (Chen et al., 1999), first aid treatment of victims generally included antidotes for cyanide po isoning and pure oxygen to overcome respiratory distress caused by damage to the lung. Other clinical symptoms following such poisoning included blood chemistry changes indicati ve of slight liver damage. In an analysis of 144 case reports of acute AN poisoning, Chen et al. (1999) estimated that exposure levels were in the 18–258 ppm range (40–560 mg/m 3 

### ) for 60 cases and >460 ppm (>1,000 mg/m 3 

### ) for the remaining 84 cases. Subjective symptoms reported f or 92–100% of the cases included dizziness, headache, chest tightness, feebleness, and hyperact ive knee jerk. Sore throat, dyspnea, vomiting, abdominal pain, fainting, and congestion of the pha rynx were reported in 60–87% of cases. Other less frequently reported symptoms or effects (5–32% of cases) included numbness of

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limbs, convulsion, rapid heart rate, cough, hoarsen ess, rough breathing sound, coma, and abnormal liver function (Chen et al., 1999). In the cross-sectional studies of AN-exposed worke rs, subjective symptoms that were reported with increased prevalences compared with u nexposed workers included dizziness, headache, chest tightness, and poor memory, indicat ing respiratory irritation and neurological effects. Average workplace air concentrations asso ciated with increased prevalences of these subjective symptoms were 1.13 ppm (Muto et al., 199 2), 1.8 ppm (Kaneko and Omae, 1992), and 0.48 ppm (Chen et al., 2000) (see Table 4-57). No statistically significant increases in the prevalences of subjective symptoms were found in a group of acrylic fiber workers whose average workplace air concentration was 0.19 ppm (M uto et al., 1992). The studies by Muto et al. (1992) and Sakurai et al. (1978) included clini cal physical examinations, but no statistically significant increases in prevalences of physical si gns (such as reddened conjunctiva or pharynx) or abnormal values in clinical chemistry variables (including activities of liver enzymes) were found in exposed workers (more details of results f rom these studies can be found in Section 4.1.2.2.2 and Table 4-22). To provide support that neurological effects are t he most sensitive identified class of effects from repeated inhalation exposure to AN, st atistically significant deficits in several neurobehavioral tests were measured in exposed work ers in a Chinese acrylic fiber manufacturing plant with mean workplace air concent rations of 0.11 ppm (range 0.00–1.70 ppm) and 0.91 ppm (range 0.00–8.34 ppm) in two different process areas. Deficits in exposed workers compared with nonexposed workers were noted in a Pr ofile of Mood States test (20–68% higher for negative moods such as anger and confusion), a Simple Reaction Time test of attention and response speed (10–16% deficits), and the backward sequence of the Digit Span test of auditory memory (21–24% deficits). Statistically significant increases in the prevale nces of adverse reproductive outcomes were associated with mean workplace air concentrati ons of 3.7 ppm (Dong and Pan, 1995), 3.6 ppm (Dong et al., 2000a), and 7.5 ppm (Li, 2000 ), indicating that reproductive effects from occupational exposure may occur at higher exposure levels than those associated with mild neurobehavioral effects. However, statistically si gnificant decrease in sperm density and number, statistically significant increase in DNA s trand breakage and sex chromosome aneuploidy in sperm cells were reported in workers exposed to 0.37 ppm AN with average 2.8 years of exposure (Xu et al., 2003). An epidemiolo gical study conducted in the area surrounding an AN-using plant in Hungary reported increased ORs for several congenital malformations (e.g., undescended testis), but no exposure data we re provided in this study (Czeizel et al., 2000, 1999). Exposure levels associated with adverse effects in Sprague-Dawley rats were higher than the workplace air concentrations associated with ad verse effects in AN-exposed workers (Table 4-57). The lowest exposure level in the 2-y ear inhalation bioassay, 20 ppm, produced

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increased incidence of lesions in nasal epithelia ( hyperplasia of mucus-secreting cells in males and flattening of the respiratory epithelium in fem ales). At 80 ppm, further increases in incidences of nasal lesions of a wider variety were observed as well as statistically significant increases in the incidences of histopathological le sions at other sites, including gliosis and perivascular cuffing in the brain of males and fema les, focal nephrosis and thyroid cysts in males, hepatic necrosis in females, and hyperplasia and hyperkeratosis of the nonglandular portion of the stomach in both sexes combined (Quas t et al., 1980b). Other effects in SpragueDawley rats associated with repeated inhalation exp osure to AN included deficits in sensory nerve conduction in the tail nerve of rats exposed to 25 ppm AN (Gagnaire et al., 1998) and developmental effects. Statistically significantly increased incidence of litters with missing vertebrae, missing ribs, or anteriorly displaced ov aries were observed in rats exposed to 80 ppm, but not 40 ppm, 6 hours/day on GDs 6–15 (Murray et al., 1978). In another study involving 6 hours/day inhalation exposure of Sprague-Dawley r ats on GDs 6–20, developmental effects were restricted to a statistically significant decr ease in fetal weight gain per litter, compared with controls, associated with exposure to 25 ppm (5% de crease), 50 ppm (8% decrease), or 100 ppm (15% decrease); no effects on fetal weight gain wer e observed at 12 ppm (Saillenfait et al., 1993).

4.6.3. Mode-of-Action Information The precise modes of action whereby AN induces non cancer effects are unknown. However, a general understanding of the processes b y which AN is metabolized within the body allows some conclusions to be drawn about the range of processes that might be involved in bringing about one or more of its toxic responses. Relevant metabolic processes are likely to include partitioning between detoxification and oxi dative activation sub-pathways, conversion of AN to one or more toxic metabolites, depletion of G SH, the association of AN metabolism with the onset of oxidative stress, and the ability of C EO, the reactive metabolite of AN, to covalently bind to macromolecules, such as proteins. In addit ion, other processes related to the parent compound AN, such as its cholinomimetic effects, ma y also be involved.

4.6.3.1. GI Effects The relationship between AN metabolism and GI hemo rrhage in rats was suggested by Ghanayem and Ahmed (1983). GI bleeding was observe d 3 hours after a single dose of 50 mg/kg AN was administered to Sprague-Dawley rats orally or subcutaneously, with no significant difference in the amount of GI blood lo ss resulting from either route of administration. Thus, AN-induced GI bleeding was n ot a result of direct irritation of AN on the
GI tract. Pretreatment of rats with CYP450 enzyme inducer Aro clor 1254 increased blood loss by 240% (Ghanayem and Ahmed, 1983). In contrast, pret reatment of rats with CYP450 inhibitors

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cobalt chloride or SKF 525A prior to AN administrat ion produced significant decreases in blood loss of 10 and 40%, respectively. Pretreatment of rats with DEM, a known depletor of GSH, prior to AN administration produced no significant change in GI bleeding. In addition, administration of a sublethal dose (6 mg/kg s.c.) o f KCN did not induce GI bleeding when compared with controls. Therefore, Ghanayem and Ah med (1983) concluded that metabolic activation of AN by CYP450 to a reactive metabolite other than cyanide (probably CEO) was a prerequisite for AN to induce gastric hemorrhage. Ahmed et al. (1996a) showed irreversibly bound AN-d erived radioactivity in intestinal mucosa following a single i.v. injection of 2-[ 14 

### C]-AN to male F344 rats. A recent study by Jacob and Ahmed (2003a) also demonstrated that AN a nd or its metabolites accumulated and covalently interacted in GI mucosa of male F344 rat s treated either by i.v. or orally with 2-[ 14 

### C]-AN. These studies supported the hypothesis that AN-induced injury of the GI mucosa is not due to direct irritation by AN but by metabolic activation and macromolecular interaction of
AN metabolite in these tissues. Ghanayem et al. (1985) also studied the mechanism of AN-induced gastric mucosal necrosis in the glandular stomach in male Sprague-D awley rats. Subcutaneous administration of 40 or 50 mg/kg AN caused a significant decrease in hepatic and gastric GSH concentration 3 hours after treatment, and induced gastric necros is. Pretreatment of rats with various metabolic modulators (CYP450 monooxygenase and GSH) before ad ministration showed that there was a significant inverse relationship between gastric GS H concentration and AN-induced gastric erosions. Pretreatment of rats with sulfhydryl-con taining compounds (cysteine or cysteamine) protected against AN-induced gastric necrosis and b locked the depletion of gastric GSH. In addition, AN-induced gastric erosions could be p revented by pretreatment with atropine, a muscarinic receptor blocker, suggesting the involvement of muscarinic receptors in the AN-induced gastric mucosal necrosis (Ghanayem e t al., 1985). Activation of acetylcholine muscarinic receptors is known to increase gastric a cid secretion and cause gastric erosions. Because muscarinic receptors are known to contain s ulfhydryl groups in their active site (Ikeda et al., 1980; Aronstam et al., 1978), Ghanayem et a l. (1985) hypothesized that AN inactivated critical sulfhydryl groups and caused gastric erosi ons by locally modulating muscarinic acetylcholine receptors in the stomach.

4.6.3.2. Neurological Effects Increased prevalence of subjective symptoms of neur ological effects was associated with average workplace air concentrations of 1.13 ppm (M uto et al., 1992), 1.8 ppm (Kaneko and Omae, 1992), and 0.48 ppm (Chen et al., 2000), and small deficits in performance in a battery of
neurobehavioral tests were observed in workers from factories with average workplace air concentrations of 0.11 and 0.91 ppm (Lu et al., 200 5a). In a case of acute severe accidental AN poisoning (AN concentration at 62 mg/m 3 

### ) of a worker (Fei and Xu, 2006), impairment of the

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CNS, including diffused damage to the cerebral cort ex layer (pyramidal system) and damage to the subcortical layer (extrapyramidal system), was observed. In addition to poisoning symptoms (dizziness, headache, difficulty breathing, confusi on, convulsion, etc.), cerebral focal damage was also detected in the patient, suggesting Parkin son’s syndrome (static tremor, muscle rigidity, increased muscle tension and lead-pipe rigidity, sl ow motor activity). The clinical symptoms were related to those induced by adverse effects on the cholinergic system and dopaminergic
system. Neurotoxicological effects of AN in animals include d cholinomimetic effects on the peripheral and central muscarinic systems in Spragu e-Dawley rats after administration of nonlethal oral doses of 20, 40, or 80 mg/kg (Ghanay em et al., 1991) and the development of brain lesions in Sprague-Dawley rats (gliosis and p erivascular cuffing) following chronic inhalation exposure to 80 ppm (Quast et al., 1980b) or chronic drinking water exposure to 4.4 mg/kg-day (females only). The neurobehavioral effect of AN was suggested to be related to changes in brain monoamine neurotransmitter levels (Lu et al., 2005b ). In a 12-week drinking water study of male Sprague-Dawley rats (Lu et al., 2005b), dopami ne levels were decreased by 76 and 46% in rats exposed to 50 ppm AN, in the striatum and cere bellum, respectively. Serotonin levels were decreased by 38 and 41% in the striatum and cerebel lum, respectively, for rats exposed to 50 ppm AN. In the case of acute severe AN poisonin g, the development of Parkinson’s syndrome and other CNS impairment in the exposed wo rker would suggest involvement of the cholinergic system and dopaminergic system (Fei and Xu, 2006). The cholinomimetic effects were thought to be due t o an effect of AN on muscarinic receptors, since atropine sulfate (which blocks bot h central and peripheral muscarinic receptors) protected animals against these effects (Ghanayem e t al., 1991). In an earlier study on AN-induced gastric mucosal necrosis (Ghanayem et al ., 1985), it was reported that pretreatment with atropine and sulfhydryl-containing chemicals p rotected against such lesions. Since muscarinic receptors contain sulfhydryls in their a ctive sites (Aronstam et al., 1978) and sulfhydryl-depleting chemicals are known to potenti ate chemically induced activation of muscarinic receptors (Hedlund and Bartfai, 1979), G hanayem et al. (1991) speculated that depletion and/or inactivation of endogenous sulfhyd ryls by AN and/or its metabolite may cause configurational changes of muscarinic receptor bind ing affinity that, in turn, lead to the development of acetylcholine-like (cholinomimetic) toxic effects. It is unlikely that these
cholinomimetic effects are due to inhibition of ace tylcholinesterase activity. Rajendran and Muthu (1981) reported that AN did not inhibit the a ctivity of acetylcholinesterase. In addition, Satayavivad et al. (1998) reported that AN had no e ffect on decreased motor activity induced by physostigmine (an inhibitor of acetylcholinesterase ). Thus, Satayavivad et al. (1998) proposed that the cholinomimetic effect of AN might be media ted by the release of acetylcholine from nerve endings.

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In addition, Ghanayem et al. (1991) proposed that lipid peroxidation may at least partly be involved in AN-induced cholinergic overstimulati on. In noting that AN enhanced lipid peroxidation and inhibited Na + 

### ,K + 

### -ATPase in RBCs in vitro, Farooqui et al. (1990) speculated that disruption of the lipid microenvironment in me mbranes by either or both of these processes might impact the muscarinic receptor function and i nduce cholinergic overstimulation. For acute CNS effects, the signs were similar to t hose produced by cyanide. Ghanayem et al. (1991) proposed that the free cyanide libera ted from AN during its metabolism may
contribute to these effects. It is well establishe d that cyanide causes CNS dysfunction by inhibition of cellular respiration via inactivation of tissue cytochrome c oxidase, which is the terminal electron acceptor in cellular energy produ ction (Klaassen, 2001). Intraperitoneal injection of 30 mg/kg AN in Chinese hamsters decrea sed cerebral succinate dehydrogenase and cytochrome oxidase activities (Zitting et al., 1981 ). These authors suggested that the observed biochemical effects were likely due to the formatio n of cyanide from AN. The neurotoxicity of AN may also result from the c ovalent binding of AN or its metabolites to enzymes. There is abundant evidence that important proteins bearing cysteine residues (e.g., enzymes such as GSTM1) can bind AN, thereby possibly impairing their functions and creating metabolic imbalances leading to toxici ty. For example, AN was shown to covalently bind to the important glycolytic enzyme GAPDH in vitro (Campian et al., 2002). AN specifically targeted and bound to cysteine 149 in the active center of this enzyme, causing irreversible inhibition of its activity. This sugg ested that AN might impair glycolytic ATP production in vivo. Campian et al. (2002) speculat ed that the combination of glycolytic impairment with inhibition of mitochondrial ATP syn thesis by cyanide released from AN could result in metabolic arrest. However, Campian et al . (2008) demonstrated in male SpragueDawley rats that acute lethality of AN was not due to brain metabolic arrest (see Section 4.5.1.1.3),

4.6.3.3. Reproductive/Developmental Effects As discussed in Section 4.5.2.1, lower sperm densit y was noted in workers exposed to 0.8 mg/m 3 

### AN compared with controls of approximate age range from the general population (75 × 10 6 

### /mL vs. 140 × 10 6 

### /mL) (Xu et al., 2003). DNA strand breakage was al so detected in AN-exposed workers using single-cell gel electropho resis, with the rate of comet sperm higher in the exposed workers than in the control (28.7 vs. 1 5%). The frequency of sex chromosome disomy was 0.69% in exposed groups and was higher t han 0.35% in the control group. There were also significant differences in the frequencie s of XX-, YY-, and XY-bearing sperm between exposed and control groups. AN-induced effects on the male reproductive system are restricted to a report that treatment of CD-1 mice for 60 days with gavage dose s of 10 mg/kg-day produced degeneration
of the seminiferous tubules and altered testicular activities of several enzymes (SDH, acid

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phosphatase, LDH, and β -glucuronidase) (Tandon et al., 1988). Exposure-re lated increases in the incidence of lesions in male reproductive organ s were not observed in 14-week or 2-year gavage bioassays with B6C3F 1 

### mice (NTP, 2001) or in the 2-year bioassays with S pragueDawley or F344 rats (see Table 4-56). The potential male reproductive effect of AN may i nvolve the distribution and
metabolism of AN to CEO in the testis and interacti on of CEO with tissue protein and DNA.
Radiolabeled AN distributed to the rat testis after oral and i.v. administration (Ahmed et al., 1996a; Young et al., 1977). The testis has the cap ability to bioactivate AN (Abdel-Aziz et al., 1997). Thus, CEO can either be formed in the liver and transported to the testis or be formed in the testis in situ. AN has been reported to intera ct with testicular DNA in rats treated with a single 46.5 mg/kg oral dose (Ahmed et al., 1992b). Covalent binding of [2,3- 14 

### C]-AN-derived radioactivity to testicular DNA was maximal at 0.5 hours following administration, while DNA synthesis in testicular tissue was decreased (80% o f control). In addition, testicular DNA repair
was increased 1.5-fold at 0.5 hour and more than th reefold at 24 hours after treatment (Ahmed et al., 1992b). Alkylating agents have the potential to produce infertility via destruction of dividing primary spermatogonia (Heinrichs and Juchau, 1980). Thus, any effect of AN on male reproductive tissue may be due to its interference with testicular DNA synthesis and repair processes. The consequence may be reproductive abn ormalities as well as impact on altered heritability in offspring.
No mechanistic studies are available to elucidate the mode of action whereby AN induced ovarian atrophy and cysts in female mice ch ronically exposed by gavage to doses as low as 2.5 mg/kg-day (NTP, 2001). The mild developmental effects associated with ges tational exposure to 80 ppm AN by inhalation or 65 mg/kg-day by gavage (Murray et al. , 1978) may be associated with the release of cyanide during maternal metabolism of AN. Concurre nt administration of thiosulfate, a cyanide antagonist, was shown to protect against the malfor mations induced by i.p. injection of 80 mg/kg AN in hamsters (Willhite et al., 1981). However, S aillenfait et al. (1993) tested for relative developmental toxicities of eight aliphatic mononit riles and proposed that factors other than cyanide liberation from the nitrile may be involved , since teratogenicity of inhaled aliphatic mononitriles in rats could not be predicted based o n the presence of a vinyl moiety in their
molecular structure.

4.6.3.4. Hematological Effects Farooqui and Ahmed (1983b) conducted work to elucid ate the mechanism of the hematological effects of AN. Their findings pointe d to substantial AN-induced covalent binding of CEO to RBCs, GSH depletion, increase in rate of RBC metabolism, and increase in the formation of two metabolic intermediates, ATP and 2 ,3-diphosphoglycerate, that regulate the oxygen dissociation curve. These authors suggested that chronic exposure to AN may lead to

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methemoglobinemia, damage to RBC membranes, and imp aired delivery of oxygen to the
tissues. Oxidative stress and lipid peroxidation were also suggested as additional factors aiding in the destruction of RBCs, evidenced by a significant decrease of Na + 

### ,K + 

### -ATPase activity in isolated RBC membranes (Farooqui et al., 1990).
AN-Hb adducts have been measured and used as a mar ker of exposure in humans. AN can bind to amino acid residues other than cysteine . Thus, MacNeela et al. (1992) identified the N-terminal cyanoethyl-valine adduct of Hb (CEVal), the formation of which may have implications for the efficiency of oxygen transport to the tissues.

4.6.3.5. Immunological Effects Zabrodskii et al. (2000) suggested a potential mech anism of action for the AN-induced DTH. They found that, in mice, AN reduced the numb er of esterase-positive splenocytes, the number of antibody-producing cells, and the inflamm atory response induced by injection of SRBCs in the paws of animals. Treatment of the ani mals with an esterase activity-restoring drug restored the paw-response completely but not the nu mbers of immune-competent cells. However, a combination of the esterase-restoring dr ug and a cyanide-trapping drug restored immune function completely. Therefore, the study a uthors concluded that the immunotoxic
effect of AN was due to combined inhibition of este rase and cytochrome c oxidase a 3 

### activities.

4.6.3.6. Covalent Binding to Sulfhydryl Groups The capacity of AN to bind to proteins may be an im portant determinant of its toxicological effects. AN has been shown to have h igh affinity for cysteine residues on proteins and polypeptides. There is abundant evidence that AN will bind to the cysteine-bearing tripeptide, GSH, even without the contribution of e nzymes such as GST. As discussed in Chapter 3, the formation of 2-(cyanoethyl)glutathio ne and the appearance of 2-(cyanoethyl)cysteine and N-acetyl 2-(cyanoethyl)c ysteine in the urine have been taken as an indication of the ready interaction of AN and GSH. However, the presence of excess AN can cause GSH to become depleted. This will tend to ch annel AN into an oxidative reaction with CYP2E1 and result in formation of CEO and other pro ducts. Perturbing the balance between detoxification of AN with GSH and oxidation by CYP2 E1 (for example, by blockade of CYP2E1) may facilitate the binding of AN to other c ysteine-bearing proteins when GSH levels
are low. AN also has been shown to bind to the cysteine 186 residue of the enzyme CAIII in rat liver in vivo. Nerland et al. (2003) pointed out t hat this enzyme may play a role in protecting cells from oxidative stress. AN binding to this co mponent, with possible conformational changes in tertiary structure and functionality, mi ght abolish this protective ability and increase cell vulnerability to oxidative stress. In a simil ar study, Nerland et al. (2001) demonstrated that

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AN can bind also with high selectivity to cysteine 86 of GSTM1. However, in this case, the binding did not exert an effect on the catalytic ac tivity of the enzyme.

4.7. EVALUATION OF CARCINOGENICITY—SYNTHESIS OF HU MAN, ANIMAL, AND OTHER SUPPORTING EVIDENCE, CONCLUSIONS ABOUT HU MAN CARCINOGENICITY, AND LIKELY MODE OF ACTION 4.7.1. Summary of Overall Weight of Evidence Following EPA’s Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005a), AN is “likely to be carcinogenic to humans,” based predom inantly on consistent results showing that lifetime inhalation or oral exposure caused a stati stically significantly increased incidence of tumors at multiple tissue sites in rats and mice. The most consistently observed tissue sites with tumors were the brain, forestomach, Zymbal gland in the ear canal in rats, and forestomach and ocular Harderian gland in mice. In addition, rats exposed during gestation and throughout adulthood showed higher incidences of brain tumors, Zymbal gland tumors, and extrahepatic angiosarcomas than did rats with exposure throughou t adulthood only; hepatomas, which were not observed in exposed adult rats, were reported i n rats exposed during gestation and throughout adulthood. Epidemiological studies of AN-exposed w orkers provide no strong evidence that mortality from any type of cancer is causally relat ed to occupational exposure to AN, but limited evidence from the largest and best-designed epidemi ologic study (Blair et al., 1998) indicated that workers with the longest duration and highest exposures to AN had a small, but statistically significant, increased risk for dying from lung can cer. The available weight of evidence is adequate for a direct mutagenic mode of action involving DNA modification by reactive metabolite C EO. Other modes of action, including
oxidative stress and inhibition of intercellular co mmunication, may also contribute. Currently, no mechanistic explanations are available for the f act that AN induces brain tumors in rats but not in mice, although this may be related to higher CEO levels in rat brains and the more rapid clearance of CEO in mice than in rats (see Section 3.2). Mouse liver GST has a greater capacity for conjugating AN or CEO than rat liver GST (see S ection 3.3.2). The modes of action involved in tumors induced by AN at other sites in animals (e.g., forestomach squamous epithelium in rats and mice and Zymbal gland in rat s) have not received adequate investigation. The mutagenic mode of action for AN-induced tumors is considered to be relevant to
humans.The metabolism of AN in rats and humans is s imilar and there is evidence for mutagenicity of AN in exposed humans.

4.7.2. Synthesis of Human, Animal, and Other Suppo rting Evidence Section 4.1.2.2 presents an historical perspective and evaluation of the epidemiologic studies of possible relationships between occupatio nal exposure to AN and elevated risks for cancer. The early studies were of small cohorts wi th limited follow-up periods and limited

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assessment of actual exposures. Elevations for inc idence and death from lung cancer and incidence of prostate cancer were sufficiently cons istent among the early studies to provoke the conduct of several additional studies over a 20-yea r period. The later studies had increased power due to increased number of workers, longer pe riods of follow-up, increased sophistication and quantification of exposure assessments, or incl usion of information on smoking habits. Small excess risks for lung and prostate cancer wer e identified in a few of these studies, but consistently and statistically significantly elevat ed risks were not observed across studies (see Tables 4-3 and 4-9). Other studies reported small excess risks for other types of cancer (e.g., bladder, colon, and brain cancers), but these findi ngs were even less consistent across studies than the findings for lung and prostate cancer (see Tables 4-8, 4-11, 4-12 and 4-13). The most informative study in the later generation of studies was the large, welldocumented study by Blair et al. (1998). This stud y was strong because it examined a large cohort and attempted to adjust for known problems w ith earlier studies by quantifying exposures, estimating the effect of smoking, and using an inte rnal control group of unexposed workers. The AN-exposed cohort as a whole experienced fewer deat hs from lung cancer than those expected from the experience of the general U.S. population (probably reflecting a healthy worker effect), but when the exposed workers were grouped into quin tiles of cumulative exposure, the lung cancer rate in the highest quintile of exposure (>8 ppm-years) for those who were followed for 20 or more years was about two times the rate in th e unexposed group of workers (RR = 2.1; 95% CI = 1.2–3.8). Conclusions regarding the assoc iation between AN exposure and other cancer types (stomach, brain, breast) are limited d ue to the small number of site-specific cancer deaths (Blair et al., 1998). As concluded in Section 4.1.2.2, there is no stron g evidence from the body of epidemiologic studies that mortality from any type of cancer is causally related to exposure to AN at the levels that have been measured in workpla ces utilizing this chemical. However, based on these epidemiology studies, there is suggestive evidence of a possible association between occupational exposure to AN and increased risk of l ung cancer. In rat and mouse bioassays, AN has been demonstrat ed to be a multiple-site carcinogen. Chronic oral exposure to AN induced tumors in the b rain or spinal cord, Zymbal gland in the ear canal, the forestomach, and, to a lesser degree and less consistently, the female mammary gland, tongue, and intestine in several oral bioassays wit h F344 rats (Johanssen and Levinskas, 2002b; Biodynamics, 1980c) and Sprague-Dawley rats (Johann sen and Levinskas, 2002a; Quast, 2002; Biodynamics, 1980a, c; Quast et al., 1980a). In ad dition, lifetime inhalation cancer bioassays with Sprague-Dawley rats found exposure-related inc reased incidences of brain tumors, Zymbal gland tumors, intestinal tumors, malignant mammary gland tumors, and tongue tumors (Dow Chemical Co., 1992a; Maltoni et al., 1988, 1977; Qu ast et al., 1980b). Strong evidence exists for dose-response relationships for the carcinogenic re sponses in the CNS, Zymbal gland, and the forestomach of rats, especially in the lifetime dri nking water studies with multiple exposure

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levels. The lowest drinking water concentrations a ssociated with significant increased incidence of forestomach and brain tumors were 3 and 30 ppm, respectively, corresponding to daily doses of about 0.3 and 2.5 mg/kg-day in F344 rats (Johans sen and Levinskas, 2002b; Biodynamics, 1980c). With chronic inhalation exposure of Sprague-Dawley rats, increased incidences of brain
tumors occurred at air concentrations of 20 and 80 ppm, whereas the incidences of Zymbal gland tumors, mammary gland adenocarcinomas and intestina l tumors were increased only at the 80 ppm level (Quast et al., 1980b). In mice, a sin gle gavage lifetime bioassay identified the forestomach and the Harderian gland as sites of tum or development, but elevated incidences of brain, Zymbal gland, or mammary gland tumors were n ot found (NTP, 2001). A significant increase in lung tumors was found in the female mid -dose group of exposed mice but not in the female high-dose group or in any of the male expose d groups. NTP (2001) concluded that the evidence for carcinogenicity in the mouse lung was equivocal; this conclusion is consistent with the small magnitude of the increase, lack of a mono tonic dose-response relationship, and lack of a demonstrated carcinogenic response in exposed mal e mice. No consistent evidence was found for carcinogenicity in the rat lung or the prostate or bladder tumors in rats or mice. Results from two rat studies provide evidence that chronic exposure starting during earlylife periods may result in increased susceptibility to the carcinogenicity of AN, compared with lifetime exposure during adulthood only (see Sectio ns 4.2.2.2.2 and 4.2.1.2.8 for more details). The possible human relevance of the rodent carcinog enic responses to AN is not fully understood. The brain is the only organ for which there is a direct human counterpart among rodent organs showing strong carcinogenic responses to AN, but the forestomach squamous epithelium and Zymbal gland have analogous tissues in humans. Although humans do not have a forestomach, the human esophagus is lined with sq uamous epithelial cells morphologically similar to those in which tumors develop in rats, w ith the exception that the rat cells are keratinized and the human cells are not (Cohen, 200 4; Wester and Kroes, 1988). Likewise, although humans do not have a Zymbal gland, a sebac eous gland in the ear canal, they do have sebaceous glands. In contrast, humans and other pr imates do not have tissue analogous to the Harderian gland, an ocular gland in rodents that se cretes lipids and porphyrins (Cohen, 2004; Sheldon, 1994; Albert et al., 1986). However, give n that mutagenic modes of carcinogenic action are plausible for AN or its metabolites (see Section 4.6.3), formation of tumors in these organs may be indicative of a more generic carcinog enic hazard (Cohen, 2004). Chemicals with a mutagenic mode of action are frequently observed to cause cancers in many sites in one species, as well as to have different sites of tumo r formation in different species. Therefore, it is reasonable to consider the tumor responses in these rodent organs as indicators of AN-induced carcinogenicity in humans. In addition, the Nation al Academy of Sciences (NAS) (2008) in its Science and Decisions: Advancing Risk Assessment, stated on page 134 that “...the target organ in a rodent species, such as the forestomach or Zym bal gland, may not have an exact human

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counterpart. However, the presence of carcinogenic action in tissues for which there is no correspondence in humans or that may be regulated d ifferently in humans does not mean that the toxicity or tumor finding in animals is irrelevant. That the rodent tissue is sensitive to the toxicant signifies that the toxicant MOAs operate i n a mammalian system that has characteristics in common with similar or even not obviously relate d tissues in humans or human subpopulations...it is typically impossible to rule o ut the relevance of an effect seen in a particular rodent tissue unless there is detailed m echanistic information on why humans would not be affected...In general, tissues that are respon sive to a toxicant should be considered
relevant to human risk assessment unless mechanisti c information demonstrates that the processes occurring in the tissues could not occur in humans.”

4.7.3. Mode-of-Action Information The U.S. EPA (2005a) Guidelines for Carcinogen Risk Assessment defines mode of action as a sequence of key events and processes, s tarting with the interaction of an agent with a cell, proceeding through operational and anatomical changes, and resulting in cancer formation.
Mode of action is distinct from “mechanism of actio n,” a term that implies greater understanding and description of events, including those at the m olecular level. Toxicokinetic processes leading to the formation or distribution of the act ive agent (i.e., parent material or metabolite) to the target tissue are not part of the mode of actio n. Examples of possible modes of carcinogenic action include mutagenic, mitogenic, anti-apoptotic (inhibition of programmed cell death), cytotoxic with reparative cell proliferation, and i mmunologic suppression. AN has been demonstrated to be a multiple-site carc inogen in rats and mice, inducing tumors in the forestomach, brain, and Zymbal gland in two strains of rats following chronic oral exposure; in the forestomach and Harderian gland in a mouse strain following chronic oral exposure; and in the forestomach, brain, Zymbal gla nd, intestinal tract, and tongue in one rat strain following chronic inhalation exposure. Carc inogenic responses have also been reported less consistently across studies in the female mamm ary gland and small intestine. Several hypothesized modes of action by which AN causes can cer in the brain of rats have been investigated to varying degrees and are discussed w ithin the context of the modified Hill criteria of causality as recommended in the most recent Agen cy guidelines (U.S. EPA, 2005a). These discussions are followed by discussion of possible modes of action involved in the development of forestomach tumors and hepatomas in rats and lun g cancer in humans. Modes of action by which AN may induce tumors in the Zymbal gland, Har derian gland, mammary gland, and tongue have not been investigated. The generic mut agenic modes of action probably apply to these organs also, unless there is information to i ndicate otherwise.

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4.7.3.1. Hypothesized Mode of Action: Direct Mutagenic Mode -of-Action Key Events This mode of action hypothesizes that AN is first a ctivated by CYP2E1 (mostly in the liver but also at other sites, such as intestinal m ucosa or squamous epithelium of the forestomach) to its reactive metabolite, CEO. CEO is then distributed to target organs (e.g., rat brain) where it reacts with DNA, forming DNA adduct s. DNA adduct formation results in genetic damage, especially the formation of point m utations. Other types of DNA damage by CEO are also observed in vivo, including DNA strand breaks, SCEs, and MN formation. Mutagenicity is a well-established cause of carcino genicity.

AN 

# ↓ CYP 2E1 

### CEO 

# ↓

Interaction with DNA 

# ↓

Gene mutation for tumor initiation

Following these key events, tumor growth may be pro moted by any one or combination of a number of cell-signaling pathways, leading to enhanced cell proliferation or inhibition of programmed cell death.

4.7.3.2. Experimental Support for the Hypothesized Mode of A ction
4.7.3.2.1. Strength, consistency, specificity of association. The evidence that supports a mutagenic mode of action is strong and consistent ( as summarized in Table 4-53). In addition to positive findings in blood lymphocytes, buccal muco sal cells, and sperm in five epidemiologic studies, DNA alkylation by AN was found in numerous tissues in rats or mice (brain, liver, testes, forestomach, colon, kidney, bladder, and lu ng) treated with a single dose of AN. AN or its reactive metabolite CEO yielded positive result s in in vitro mutation assays using bacteria, fungi, and insects, as well as animal and human cel l cultures. The mutagenicity/genotoxicity is specific and occurs in the absence of cytotoxicity or other overt toxicity. Although the temporal relationship of adduct formation and mutagenicity w ith carcinogenicity has not been adequately explored, these effects are seen in short-term assa ys (before tumor formation). Dose-response concordance is observed between mutagenic doses in vivo and tumorigenic doses in rats and mice. A mutagenic mode of action also comports wit h notions of biological plausibility and
coherence because AN is metabolized to an epoxide intermedia te. Such agents are generally capable of forming DNA adducts, which in turn have the potential to cause genetic damage,

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including mutations, and mutagenicity, in its turn, is a well-established cause of carcinogenicity. This chain of key events is consistent with current understanding of the biology of cancer. The possible association between a direct mutagenic action of CEO, the epoxide metabolite of AN, and brain tumors in rats is suppo rted by the detection of CEO in rat brains after oral administration of 10 mg/kg AN to rats (K edderis et al., 1993b), reported binding of CEO to brain DNA after oral administration of [2,3- 14 

### C]-AN to rats (Farooqui and Ahmed, 1983a), results from studies of in vitro DNA reacti vity, positive results from in vitro tests of mutagenicity and cytogenetic effects, and positive results from in vivo studies of DNA damage and repair assays and other genotoxic endpoints in rats and mice. Studies that demonstrate the mutagenicity of AN in occupational exposed workers are also available. In the following subsections, experimental evidence supporting the mutagenic mode of action of AN using different test systems is summar ized.

In vitro DNA binding AN itself reacts very slowly with DNA in vitro at v ery high, nonphysiological concentrations (>1 M) (Solomon et al., 1984), but C EO forms different adducts in vitro with DNA (Solomon et al., 1993; Yates et al., 1993) or n ucleotides (Yates et al., 1994) more rapidly (see Section 4.5.1.2.1). When calf thymus DNA was incubated with CEO for 3 hours (Solomon et al., 1993), the main adducts formed included N 7 

### -(oxoethyl)guanine, N 3 

### -(2-hydroxy-2-carboxyethyl)deoxyuridine, and smaller amounts of adenine and thymine adducts. Yates et al. (1993)
also identified the formation of N 3 

### -(2-cyano-2-hydroxylethyl)deoxythymidine when CEO w as incubated with calf thymus DNA in vitro.

Mutations in bacteria In short-term tests with bacteria, AN induced mutat ions in a majority of test systems, often requiring the presence of exogenous metabolic systems (Table 4-53). AN induced
mutation in S. typhimurium strains TA 1530, 1535, 1538, 1937, and 1950 with st rong response when AN was tested in the vapor phase in the presen ce of S9. AN induced a weak response for TA 98, 100, and 1978. Thus, AN induced gene revers ion mainly by base substitution and induced lower mutagenic activity with strains rever sed by frameshift mutation. AN also produced a dose-related increase in the number of r evertant colonies compared with untreated
bacteria in E. coli WP2 (which is DNA repair proficient), WP2uvrA (whic h lacks excision repair), and WP2 uvrApolA (which lacks both excision repair and DNA polymeras e 1) without a need for S9 fraction (Venitt et al., 1977).

Mutations in fungi and Drosophila As shown in Table 4-53, AN induced mitotic gene con version in S. cerevisiae JD1 (Brooks et al., 1985). AN also induced sex chromos ome loss in the adult female Drosophila

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ZESTE system (Osgood et al., 1991), as well as soma tic recombination and mutation in hatching Drosophila with exposure in the larvae stage (Vogel , 1985; Würgler et al., 1985).

Mutations in mammalian cell culture
AN also induced mutations in mammalian cells in vit ro. In the mouse lymphoma cell assay, AN induced forward mutations at the Tk +/– 

### locus in most assays (Table 4-53). In human lymphoblastoid Tk 6 cells devoid of CYP450 activity, AN induced mutat ions at the Tk locus only in the presence of an exogenous S9 metabolic system (Crespi et al., 1985), and CEO was effective at 10-fold lower concentrations than AN ( Recio and Skopek, 1988a, b).
Characterization of the Tk
– 

### mutants in human lymphoblastoid Tk 6 cultures by Recio and Skopek (1988b) identified two classes of CEO-induce d Tk

– /– 

### mutant phenotypes that differed in their growth rates. CEO-induced predominantly Tk n 

### mutant with normal growth rate and Tk s 

### with slower growth rate. Southern blot analysis of CEO-induced Tk n 

### mutants indicated that the majority of these mutants were below the detection limit of <2 kb. Thus, CEO-induced alterations are relatively small DNA alterations. Recio and Skopek (1988a) suggested that CEO
induced Tk

n 

### mutants resulted from point mutations or small ins ertions/deletions that occurred during the replication or repair of CEO-modified DN A. Kodama et al. (1989) conducted cytogenetic analyses of eight CEO-induced Tk s 

### mutant clones reported in Recio and Skopek (1988a, b). A visible abnormality on chromosome 17 was found in one of the CEO-induced Tk s 

### mutants and was marked by duplication of the long a rm of chromosome 17, with break points at q11 and q21. The latter break point was close to t he Tk locus, suggesting that the observed aberration might be associated with Tk

– /– 

### phenotype. CEO also induced mutations at the hprt locus in Tk 6 cells (Recio and Skopek, 1988a). Characterization of the hprt mutations by cDNA sequencing analysis indicated tha t several hprt mutations were formed. The majority of CEO-induced mutations were the specific loss of exons from the coding region of hprt. Remaining mutants were single base substitutions (point mutation) resulting from amino acid changes (A:T ba se pairs and G:C base pairs).

Cytogenetic effects in vitro Additional evidence of mutagenicity included AN-ind uced cytogenetic changes, such as SCEs or CAs in a majority of assays with CHO or CHL cells (Natarajan et al., 1985; VedBrat and Williams,1982; Ishidate et al., 1981) and human lymphocytes in vitro (Perocco et al., 1982) but not in epithelial-like cells from rat liver (RL 4 cell line) (see Table 4-53). AN also induced DNA single-strand breaks in rat hepatocytes (Bradle y, 1985) and CHO cells (Douglas et al., 1985). Of note is that AN induced SCEs and DNA sin gle-strand breaks in human bronchial epithelial cells in culture without S9 (Chang et al ., 1990), indicating that human bronchial epithelial cells have the metabolic capabilities to activate AN to CEO.

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DNA repair in vitro In DNA repair assays, neither AN nor CEO induced UD S in cultured rat hepatocytes (Butterworth et al., 1992; Probst and Hill, 1985; W illiams et al., 1985) (as measured by incorporation of [ 3 

### H]-thymidine and autoradiographic techniques) or in HeLa cells with or without the presence of S9 (using liquid scintillat ion spectrometry) (Martin and Campbell, 1985). However, IPCS (1985) concluded that the rat hepatoc yte autoradiographic UDS assay was too insensitive for determination of genotoxicity of th e eight tested carcinogens, including AN. On the other hand, CEO, but not AN, induced UDS in hum an mammary epithelial cells in vitro (Butterworth et al., 1992).

DNA repair in vivo Unscheduled DNA repair activity was detected by fol lowing the time course of [ 3 

### H]-thymidine incorporation into DNA isolated from l ung (Ahmed et al., 1992a), testis (Ahmed et al., 1992b), and gastric tissue (Ahmed et al., 1 996b; Abdel-Rahman et al., 1994a) after exposure of Sprague-Dawley rats to single oral dose s of 46.5 mg/kg AN. In a study by Hogy and Guengerich (1986), UDS was found in the liver of ma le F344 rats administered 50 mg/kg AN or 6 mg/kg CEO i.p. but was not found in the brain. T he absence of detected UDS in the brain could reflect the absence of DNA damage. Alternati vely, this absence could reflect differences in the repair rate of CEO-DNA adducts and could acc ount for the observed target organ specificity of AN in rat brain but not liver. Sinc e the difference in DNA repair rates in brain and liver is well known (Kleihues et al., 1977), the se cond explanation may be more sound. In another study, UDS activity was not detected by aut oradiographic techniques following incubation of primary cultures of hepatocytes or sp ermatocytes from F344 rats given single oral doses of 75 mg/kg or five daily doses of 60 mg/kg-d ay with [ 3 

### H]-thymidine (Butterworth et al., 1992). This difference in results from those by Ho gy and Guengerich (1986) was probably due to differences in methodology.

DNA binding in vivo Several studies examining the amounts of radioacti vity in DNA fractions of tissues following acute in vivo exposure of rats to radiola beled AN provide evidence of in vivo DNA reactivity of AN or its metabolites. Maximal amoun ts of radioactivity covalently bound to hydroxyapatite-purified DNA from the liver, stomach , and brain showed the following order 24 hours after male Sprague-Dawley rats were given single oral doses of 46.5 mg/kg [2,3- 14 

### C]-AN: brain ( ≈ 120 pmol AN equivalent/mg DNA) > stomach ( ≈ 80 pmol/mg) > liver ( ≈ 25 pmol/mg) (Farooqui and Ahmed, 1983a). Other stu dies from the same group of investigators found elevated covalent binding of ra dioactivity in gastric, testicular, and lung DNA from similarly exposed rats (Abdel-Rahman et al ., 1994b; Ahmed et al., 1992a, b). The results from these studies provided some evidence o f associations between covalent DNA

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binding following acute exposure and sites of tumor development following chronic exposure. The methods to isolate DNA in these studies may not have been stringent enough to exclude covalent binding of radiolabel to proteins (Whysner et al., 1998b; Geiger et al., 1983); however, the degree to which these alternative processes may have contributed to the measured amounts of radioactivity in the DNA fractions is unknown. Whe n 0.6 mg/kg [2,3- 14 

### C]-CEO was administered to one F344 rat i.p., covalent binding to both liver and brain protein was found, but no covalent binding to both liver and brain nucleic acids could be detected at the level of 0.3 alkylations per 10 6 

### base (Hogy and Guengerich, 1986). However, the N 7 

### -(2-oxoethyl) guanine adduct was detected in liver DNA of F344 ra ts treated with 6 mg/kg CEO or 50 mg/kg AN i.p. in the same experiment. Thus, covalent bin ding of CEO to DNA had to occur. No DNA binding was detected in the Hogy and Guengerich (19 86) study, presumably due to the small DNA sample from one rat, low CEO concentration (0.6 vs. 6 mg/kg CEO), stringent DNA isolation procedure, and overcorrection of protein binding.

DNA adducts in vivo Limited attempts to detect CEO-DNA adducts in brai n tissues following acute in vivo exposure protocols have been largely unsuccessful, but in vitro studies indicate that the
formation of other DNA adducts from AN and its meta bolites are possible (Yates et al., 1994; Solomon et al., 1993; Hogy and Guengerich, 1986; So lomon et al., 1984). N 7 

### -(2-oxoethyl)- guanine, a CEO-DNA adduct formed in vitro following incubation of calf thymus DNA with CEO, was detected in DNA isolated from the livers o f male F344 rats, following single i.p. administration of doses of 50 mg/kg AN or 6 mg/kg C EO, but was found only equivocally at
detection limit in DNA isolated from the brains of exposed rats (Hogy and Guengerich, 1986). In another study, 7-(2-cyanoethyl)guanine and O 6 

### -(2-cyanoethyl)deoxyguanosine adducts were
not detected in DNA isolated from the liver or brai n of male F344 rats given s.c. or i.v. injections of 50 or 100 mg/kg AN (Prokopczyk et al., 1988). T he DNA samples were analyzed for the presence of the two adducts using HPLC with fluores cence detection. The detection limits were
20 μ mol/mol guanine for 7-(2-cyanoethyl)guanine and 15 μ mol/mol guanine for O 6 

### -(2-cyanoethyl)deoxyguanosine. These detection limits may b e not sensitive enough. More importantly,
these two DNA adducts were not formed from incubati on of CEO with calf thymus DNA in vitro. Hence, the limitations of these studies wer e that not all the major adducts formed in in
vitro incubation of CEO with DNA were measured. As discussed previously, the main adducts found aft er 3 hours of incubation of CEO with calf thymus DNA were N 7 

### -(oxoethyl)guanine, N 3 

### -(2-hydroxy-2-carboxyethyl)deoxyuridine (Solomon et al., 1993), and N 3 

### -(2-cyano-2-hydroxylethyl)deoxythymidine (Yates et al., 1993). Yet only N 7 

### -(oxoethyl)guanine has been measured in available s tudies. Thus, it is highly likely
that the actual adducts formed from interaction of CEO with brain DNA have not yet been looked for. It is also likely that the analytical methods used to measure DNA adducts in

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available studies were not sensitive enough for the ir detection. In addition, DNA adducts were measured only in single-dose studies not repeated-d ose studies.

DNA damage in rats and mice Evidence of DNA damage after AN exposure in rats a nd mice is available. Comet assays showed DNA damage in various tissues in both rats a nd mice exposed to AN (Sekihashi et al., 2002). Single i.p. injections of 20 mg/kg AN induc ed DNA damage in forestomach, bladder, and brain but not in colon, liver, kidney, or bone marr ow of ddY mice, whereas single doses of 30 mg/kg induced DNA damage in forestomach, colon, kidney, bladder, and lung but not in brain or bone marrow of Wistar rats (Sekihashi et a l., 2002). Increased frequencies of MN in bone marrow were fo und in Sprague-Dawley rats, following i.v. injection of 98 or 124 mg/kg AN (Wak ata et al., 1998) but were not found in Sprague-Dawley rats following administration of ora l doses up to 40 mg/kg (Morita et al., 1997) or in male CD-1 mice following administration of or al, i.p., or i.v. doses up to 45 mg/kg (Morita et al., 1997). Increases in CAs in bone marrow cel ls were not found in Swiss albino mice exposed to oral doses up to 20 mg/kg-day for 4, 15, or 30 days (Rabello-Gay and Ahmed, 1980); in Sprague-Dawley rats given 16 daily doses of 40 m g/kg-day (Rabello-Gay and Ahmed, 1980); in NMRI mice given single i.p. doses of 30 mg/kg (L eonard et al., 1981); or in ICR mice exposed in inhalation chambers to 20 or 100 mg/m 3 

### for 5 days (Zhurkov et al., 1983). In contrast, Fahmy (1999) reported that increased CAs occurred in spermatocytes of Swiss mice following single oral doses of 15.5 or 31 mg/kg AN or five daily doses of 7.75 mg/kg and in spleen cells and bone marrow cells after a single o ral dose of 7.75 mg/kg.

Dominant lethal mutations in rats and mice Dominant lethal mutations were not increased by tr eating male NMRI mice with single i.p. doses of 30 mg/kg AN (Leonard et al., 1981) or male F344 rats with five oral doses of 60 mg/kg-day AN (Working et al., 1987), indicating no AN-induced germ cell mutations.

Chromosomal mutations in humans There is sufficient evidence of AN-induced mutageni city in occupationally exposed workers. Fan et al. (2006) reported significant in crease in the occurrence of MN in buccal mucosal cells of workers exposed to 0.52 or 1.99 mg /m 3 

### AN for an average duration of 15.7– 17.2 years and significant increase in MN in periph eral blood lypmphocytes in workers exposed to 1.99 mg/m 3 

### AN for an average of 17.2 years. The workers in t he Fan et al. (2006) study were exposed to higher concentrations than those in a pr evious study by Srám et al. (2004), in which the exposure concentration range was 0.05–0.3 mg/m 3 

### AN, thus explaining the negative results reported in Srám et al. (2004) or in other studies where exposure concentrations were not reported. Evidence of CAs in AN-exposed workers wa s also reported by Borba et al. (1996), and

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DNA strand breakage and sex chromosome aneuploidy i n the sperm of AN-exposed workers were reported by Xu et al. (2003). In addition, Be skid et al. (2006) reported an increase in the number of reciprocal translocations and the relativ e number of insertions in the chromosomes of cultured lymphocytes of AN-exposed male workers. Therefore, the overall in vitro and in vivo eviden ce in support of the direct mutagenicity of CEO is strong, consistent, and specific.

4.7.3.2.2. Dose-response concordance. Chronic exposures of rats to AN in drinking water
concentrations ≥ 30 ppm ( ≥ 2.5 mg/kg-day) or air concentrations ≥ 20 ppm were associated with significantly increased incidences of brain tumors. No published studies are available that have measured CEO-DNA adducts or other endpoints pertine nt to mutagenicity in brain tissues following acute-, subchronic-, or chronic-duration oral or inhalation exposures of rats to AN, mainly because in vivo DNA adduct studies were cond ucted before the Solomon et al. (1993) and Yates et al. (1993) studies that reported on DN A adducts formed from CEO in vitro. Hence, these DNA adduct studies were not looking for the a dducts formed in vitro from CEO. The
available studies that looked for CEO-DNA adducts i n brain or other tissues involved single i.p. (Hogy and Guengerich, 1986), s.c., or i.v. (Prokopc zyk et al., 1988) administration protocols at dose levels (50 or 100 mg/kg-day AN) that were high er than the chronic oral doses associated with brain tumors in rats (0.3 to 40 mg/kg-day). H owever, no repeated-dose studies have been conducted for detection of DNA adducts. The single oral dose of 46.5 mg/kg used in studies that demonstrated UDS in the lung, gastric tissue, and t estis of treated Sprague-Dawley rats (AbdelRahman et al., 1994b; Ahmed et al., 1992a, b) was c omparable to the high dose of 40 mg/kg-day used in studies by Friedman and Beliles (2002), pro viding evidence that the dose that caused DNA repair was carcinogenic. A study in mice by Fahmy (1999) showed that increa sed CAs occurred in spermatocytes of Swiss mice, following single oral doses of 15.5 or 31 mg/kg AN or five daily doses of 7.75 mg/kg, and in spleen cells, and bone marrow ce lls after a single oral dose of 7.75 mg/kg. Fahmy (1999) also reported increases in SCEs in bon e marrow cells of male Swiss mice after a single i.p. dose of 7.5 or 10 mg/kg of AN. These d oses were all in the range of, or comparable to, the tumorigenic doses in B6C3F 1 

### mice of 2.5–20 mg/kg-day in a 2-year bioassay. The single doses employed by Sekihashi et al. (200 2) that demonstrated DNA damage in forestomach, colon, kidney, bladder, and lung of ra ts treated with 30 mg/kg i.p. and in colon, bladder, lung, and brain of male ddY mice treated w ith 20 mg/kg i.p. were also within the range of tumorigenic doses in the 2-year bioassay. Therefore, the doses that demonstrated DNA damage or chromosome mutations in singledose studies are in concordance with tumorigenic do ses in chronic bioassays.

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4.7.3.2.3. Temporal relationships. Currently available examinations of DNA damage, chromosome mutations, SCEs, UDS, or CEO-DNA adducts in brain or other tissues are restricted to single-dose acute administration prot ocols. Studies designed to examine temporal relationships of key events, such as the presence o f CEO-DNA adducts in brain tissue, are not available. Nevertheless, results from the rat bioa ssays indicated that most AN tumors occur after 12–14 months of exposure or longer. Thus, the obse rved mutagenic effects of AN occurred before tumor formation and provide support for a mu tagenic mode of action.

4.7.3.2.4. Biological plausibility and coherence. The hypothesis that the key primary event in
AN induction of brain tumors is the formation of CE O-DNA adducts that lead to mutations that initiate tumor formation is plausible based on in v itro and in vivo evidence for the direct mutagenicity of the AN metabolite, CEO. However th e available data do not establish that this is the only mode of action by which AN may induce brai n tumors in rats. Notably lacking in the database are studies designed to detect a range of DNA adducts or mutations associated with tumor initiation in brain tissues following prolong ed oral or inhalation exposures at levels that induced brain tumors in the chronic rat bioassays. In vitro studies by Solomon et al. (1993) reported that CEO interacted with calf thymus DNA a nd, in addition to N 7 

### -(oxoethyl)guanine,
formed N 3 

### -(2-hydroxy-2-carboxyethyl)deoxyuridine from an ini tial cytosine adduct. Other adenine and thymine adducts were also formed. Yate s et al. (1993) demonstrated that CEO reacted calf thymus DNA formed N 3 

### -(2-cyano-2-hydroxylethyl)-deoxythymidine. Yet, on ly
N 7 

### -(oxoethyl)guanine has been measured in exposed rat s in available studies (Hogy, 1986). The available data do not provide an explanation of why AN induces brain tumors in F344 and Sprague-Dawley rats but not in B6C3F 1 

### mice. Kedderis et al. (1993b) reported that
when male F344 rats and male B6C3F 1 

### mice were administered 10 mg/kg AN in water by gavage, higher CEO concentrations were found in blo od and brains of rats than in mice (13% higher in blood, 23% higher in brain). Higher CEO concentrations in rat brain may at least partially explain why tumors were only found in the brains of exposed rats but not in mice. In addition, the clearance of CEO in mice was more rap id than in rats (Roberts et al., 1991). It may also be that mice are more efficient in repairing D NA damage since DNA damage has been detected in the brain of ddY mice exposed to 20 mg/ kg AN, i.p. (Sekihashi et al., 2002). It has
been noted that the B6C3F 1 

### mouse is generally insensitive to chemically induc ed neurogenesis in NTP carcinogenesis bioassays (Radovsky & Mahler,199 9). The difference in susceptibility to AN induction of brain tumors between mice and rats is similar to that observed for glycidol, an aliphatic epoxide structurally similar to CEO (Irwin et al., 1996). Glycidol is a direct acting alkylating agent, which induces tumors at a variety of sites in both rats and mice. However, although significa nt induction of gliomas was observed in both sexes of F344 rats after glycidol treatment, no bra in tumors were induced in B6C3F 1 

### mice. Ethylene oxide also shows a similar pattern of tumo rigenesis, inducing brain tumors in both

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sexes of exposed rats (Garmin et al., 1985; 1986), but no brain tumors in exposed mice (NTP, 1987). Thus, induction of brain tumors in rats but not in mice by known genotoxic carcinogenic appears to reflect primarily a species difference i n inherent susceptibility to brain tumorigenesis. There have been no investigations to attempt to exp lain the apparent susceptibility of early-life plus chronic adult exposures compared wi th adult-only exposures. It is possible that mutations are established more effectively in rapid ly dividing tissues such as the fetal brain, since the higher rate of cell division increases th e number of cells in S phase (Slikker et al., 2004), which tends to make the cell population more vulnerable to the genotoxic effects of chemicals. It is also possible that the lack of ke y DNA repair mechanisms in embryonic tissues may be involved. However, DNA repair was not found in adult rat brain after administration of 6 mg/kg CEO i.p. (Hogy and Guengerich, 1986). It w ould appear that the rapid cell division in earlier stages of development is a determining fact or for the greater mutagenic and subsequent carcinogenic sensitivity of perinatal life (Slikker et al., 2004). Data for another chemical, ethylene oxide, that ca uses brain tumors (gliomas) in rats show a different accumulation pattern for N 7 

### -(2-oxoethyl)guanine adducts than that observed following i.p. administration of AN or CEO. In rat s exposed to 500 ppm ethylene oxide for 1 day, higher levels of N 7 

### -(2-oxoethyl)guanine adducts were detected in DNA f rom brain than in DNA from liver (Walker et al., 1990), whereas N 7 

### -(2-oxoethyl)guanine adducts were detected in brain at detection limit and only at low levels in the liver of rats given single i.p. injections of 50 mg/kg AN or 6 mg/kg CEO (Hogy and Guengerich, 19 86). Whysner et al. (1998b) suggested that these and other results indicated that glioma formation from chronic exposure to AN may
not involve the formation of N 7 

### -(2-oxoethyl)guanine adducts; however, several alte rnative explanations are possible. The lack of unequivocal detection of CEO-DNA adducts in rat brain may indicate that the detection limits of the metho ds used were not sensitive enough. More sensitive methods of detection, such as liquid chro matography-mass spectrometry (Poirier, 2004), have not been used in AN-induced DNA adduct studies. Alternatively, the stringent methods used to isolate purified DNA (without assoc iated proteins) in the experiments by Hogy and Guengerich (1986) may have caused the loss of a dducts or inhibited the recovery of adducted DNA (Meek et al., 2003). Another possibil ity is that N 7 

### -(2-oxoethyl)guanine adduct may not be involved in mutations leading to AN-indu ced brain tumors, and other, as yet uninvestigated, DNA adducts that were reported by S olomon et al. (1993) and Yates et al. (1993) may be involved. Still another possibility is that CEO-DNA adducts and resultant mutations in target tissues may occur only after prolonged expos ure to AN. Notably absent from the available mode-of-action database are experiments designed to detect a range of possible DNA adducts in target tissues following repeated oral or inhalatio n exposure at exposure levels producing tumors in the chronic bioassays. Guengerich et al. (1986) discussed the findings in which AN was metabolized by liver
microsomes but not brain microsomes to form CEO. N 7 

### -(2-oxoethyl)guanine DNA adducts were

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detected in liver but not the brain, yet AN induced tumors in the rat brain with chronic exposure but not in the adult rat liver. In addition, AN-in duced UDS was demonstrated in rat liver but not brain (Hogy and Guengerich, 1986). Guengerich et a l. (1986) proposed that AN was
metabolized in the liver to CEO. Since CEO formed by liver microsomes from AN has a halflife of about 2 hours in neutral buffer, it can be transported easily via blood from liver to the brain. Although DNA adducts have not yet been dete cted unequivocally in rat brains, CEO has been measured in rat brains (Kedderis et al., 1993b ) and shown to bind to brain DNA (Farooqui and Ahmed, 1983b). Liver cells are efficient in re pairing DNA damage via UDS, while brain cells do not have this capability. This could help to explain why the rat brain is a target tissue of AN carcinogenicity but the adult rat liver is not. It should be noted that hepatomas were found in rats that were exposed to AN during gestation and e xtending through adulthood (Maltoni et al., 1988). It is conceivable that the rat fetal and ne onatal liver do not have sufficient capability to repair DNA damage. Meek et al. (2003) noted that there are several as pects of the development of AN-induced tumors that are characteristic of tumors induced by compounds or metabolites that directly interact with DNA. These comparisons add support t o the evidence of a direct mutagenic mode of carcinogenic action.

• Tumors are systemic and occur at multiple sites. Exposure-related increased incidences were found for forestomach tumors, CNS tumors, and Zymbal gland tumors in chronic oral exposure bioassays with F344 rats and Sprague- Dawley rats (which also showed exposure-related increased incidence of tongue tumo rs); for forestomach and Harderian gland tumors in a chronic oral exposure bioassay wi th B6C3F 1 

### mice; for brain tumors, Zymbal gland tumors, intestinal tumors, and tongue tumors in a chronic inhalation exposure bioassay with Sprague-Dawley rats; and for brain tumors, Zymbal gland tumors, hepatomas, and extrahepatic angiosarcomas i n a chronic inhalation bioassay with Sprague-Dawley rats exposed during gestation and ex tending throughout adulthood. Particularly noteworthy is that Zymbal gland tumors in rats commonly occur with carcinogens that are also mutagens. Of the 27 chem icals associated with site-specific tumor induction in this gland found in NTP database , 23 were mutagenic in the Salmonella assay. The NTP database indicated that these chemicals were multisite carcinogens.

• Tumors sometimes occur at nontoxic doses or concent rations. Elevated incidences for CNS tumors occurred in Sprague-Dawley (Quast, 2002; Quast et al., 1980a) and F344 (Johannsen and Levinskas, 2002b; Biodynamics, 1980c ) rats chronically exposed to drinking water concentrations (30 or 35 ppm) that d id not induce elevated incidences of nonneoplastic CNS lesions in interim sacrifices at 6, 12, or 18 months.

• Tumors sometimes occur after less-than-lifetime exp osure durations. In an inhalation study by Maltoni et al. (1977), Sprague-Dawley rats were exposed to 0–40 ppm AN via

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inhalation for 52 weeks. The animals were then all owed to complete their natural life spans, with the final deaths occurring in week 136 (Maltoni et al., 1977). Gliomas were developed in 20 and 40 ppm males at 84 and 63.5 wee ks, respectively, and not in other dose groups. In addition, forestomach papillomas a nd acanthomas (latency 103– 124 weeks) and Zymbal gland carcinomas (latency 77– 102 weeks) were developed in exposed rats. Thus, these tumors were developed lo ng after exposure was terminated, indicating the carcinogenic effect from AN exposure was not reversible. Although the
incidence of these tumors did not reach statistical significance, development of these tumors does not support the hypothesis that AN-indu ced tumors are due to the promoting
action of AN alone.

• Tumors developed as early as 7–12 months following AN exposure. In the SpragueDawley chronic drinking water bioassay, the number of high-dose (300 ppm) female rats dying or sacrificed with CNS tumors were 1/1 during months 0–6, 5/13 during months 7–12, 14/23 during months 13–18, and 11/11 during m onths 19–24 (Quast, 2002). At the lower exposure levels in this study (35 and 100 ppm ), nearly all of the tumors in female rats were detected after 13 months of exposure. In all groups of exposed SpragueDawley male rats, all but one tumor were detected a fter 13 months of exposure (Quast, 2002). In the F344 chronic drinking water bioassay , the time of first detection of a rat with a brain tumor was 481 days for male rats and 4 95 days for female rats, approximately 16 months (Johannsen and Levinskas, 2 002b; Biodynamics, 1980c). In the three-generation reproductive toxicity study in volving 46 weeks of exposure to AN in drinking water, brain tumors were detected in 0/19, 1/20, and 2/24 F0 breeding females exposed to 0, 100, or 500 ppm, respectively. In th e other generations, incidences of brain tumors were 0/20, 1/19, and 4/17 for the F1 breedin g females and 0/20, 1/20, and 1/20 for the F2 breeding females (Friedman and Beliles, 2002 ). Statistically significantly elevated incidences of brain tumors occurred in Sprague-Dawl ey rats exposed by inhalation to 60 ppm AN during gestation and extending chronicall y throughout adulthood, but rats exposed during gestation followed by a subchronicsu bchronic-duration exposure during
adulthood showed an elevated incidence of brain tum ors that was not statistically significant when compared only with control (Malton i et al., 1988). The weight of the
available evidence indicates that most AN-induced b rain tumors require at least a halflifetime duration of exposure to develop, but assoc iations with shorter durations of exposure have been observed, specifically in female Sprague-Dawley rats exposed to 300 ppm in drinking water.

• The ratio of benign to malignant tumors is small. The brain tumors noted in AN-exposed Sprague-Dawley or F344 rats were astrocytomas, whic h were malignant tumors. Most of the Zymbal gland tumors were also malignant tumors.

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4.7.3.2.5. Human relevance. The metabolic scheme of AN in rats and humans is si milar.
Humans are known to be able to activate AN to its r eactive metabolite, CEO. As discussed in Section 4.5.2.1, studies that demonstrate the mutag enicity of AN in humans are available. There is sufficient evidence for mutagenicity of AN in ex posed humans, and the direct mutagenic mode of action of AN-induced carcinogenicity is consider ed to be relevant to humans.

4.7.3.3. Other Possible Modes of Action Other modes of action may contribute, along with th e direct mutagenic mode of action, to tumorigenesis. These additional modes of action ar e evaluated in the following subsections. The
results of these evaluations indicate that these mo des of action are not likely to be prinicipal modes of action or to contribute to the carcinogeni city in a significant manner.

4.7.3.3.1. Oxidative stress Key events This mode of action hypothesizes that ROS are gener ated either directly from the oxidant or are indirectly produced via activation of endoge nous sources when the oxidant or its metabolite is distributed to the target organ. Oxi dative stress is induced. These free radical ROS can interact with DNA and produce DNA damage leadin g to gene mutation for tumor initiation. ROS can also interact with lipids via lipid peroxid ation, resulting in cell damage. One of the most prevalent biomarkers of oxidative D NA damage is 8-oxodG. This DNA lesion has been found to produce mutations involvin g GC → TA transversions due to base mispairing and AT → CG transversions due to misincorporation during DNA synthesis (Cheng et al., 1992). G-C base pairs provide a common target for activating point mutations (e.g., in both p53 and retinoblastoma tumor suppressor genes and in t he ras family of oncogenes). Thus, G-C base pairs in both tumor suppressor genes and o ncogenes may represent a vulnerable target for mutation by oxidative stress (Guyton and Kensle r, 1993). The induction of base changes in the DNA sequence of these genes may be the basis fo r tumor initiation by the oxidant. Another role that oxidants may play in carcinogenes is is tumor promotion. ROS generating systems are known to possess some of the biochemical actions of tumor promoters, such as promoting a rapid and sustained decrease in antioxidant defenses, including SOD, catalase, and glutathione peroxidase activities (O’ Connell et al., 1986; Slaga et al., 1981). Tumor growth may also be promoted by oxidative stre ss via modification of gene expression through induction of gene transcription factors (e. g., NF К 

### B or transcription factor protein [AP-1]) or change in DNA methylation status by ROS. Signal transduction pathways, including
AP-1 and NF

К 

### B, are known to be activated by ROS, and they lead to the transcription of genes involved in cell growth regulatory pathway. Oxidat ive DNA damage can also result in DNA hypomethylation by interfering with the ability of methyltransferases to interact with DNA, allowing the expression of normally quiescent genes and promoting tumor growth. ROS can

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also induce the release of calcium from intracellul ar stores, resulting in the activation of kinases, including PKC (Larsson and Cerrutti, 1989), which i s known to regulate many intracellular processes, including those related to growth and di fferentiation. Hence, any one or a combination of these events may lead to enhanced ce ll proliferation or inhibition of programmed
cell death. The plausibility of an indirect mutagenicity mode of action for AN-induced tumors is evaluated in the following discussion.

Strength, consistency, specificity of association Experimental data for indirect mutagenicity of AN a re discussed in Section 4.5.2.5 and summarized in Table 4-55. These studies are only b riefly discussed here.

In vitro studies
There is some in vitro experimental evidence that supports an indirect mut agenic mode of
action for AN. When SHE cells were treated in vitr o with 0–75 μ g/mL AN in 12.5 μ g/mL increments, there was a dose-dependent increase in morphological transformation at 50, 62.5,
and 75 μ g/mL after 7 days of exposure (Zhang et al., 2000). Levels of 8-oxodG isolated from
cells incubated with 75 μ g/mL AN were increased to 192 and 186% of control a fter 2 and 3 days. However, no increase in 8-oxodG was observed after 1 or 7 days.
AN-induced oxidative stress in SHE cells was confir med in a later study by Zhang et al. (2002). AN at 25, 50, or 75 μ g/mL increased the amount of ROS in SHE cells after 4, 24, and
48 hours of treatment and increased xanthine oxidas e activity 24 and 48 hours after treatment
with 75 μ g/mL AN. AN also caused temporal changes in GSH le vels and antioxidant enzyme
catalase and SOD activities. The involvement of CY P450 metabolism of AN in the production of oxidative stress was indicated by the observatio n that inclusion of a nonspecific suicidal inhibitor of CYP450 enzyme, ABT (0.5 mM), in the me dium resulted in a significant reduction (about 77%) in the cell transformation activity of 75 μ g/mL AN (Zhang et al., 2002). In another study, when cultured rat astrocytes were exposed for 4 or 24 hours to 0.01, 0.1, or 1 mM AN, up to a 3.9-fold increase in 8-oxodG wa s found in cellular DNA of the rat astrocytes (Kamendulis et al., 1999a). No increase in 8-oxodG was found in rat hepatocytes exposed to 0.01, 0.1, or 1 mM AN for 4 or 24 hours (Kamendulis et al., 1999a). Pu et al. (2006) also reported a 3-fold increase in oxidative DNA da mage (as measured by the fpg-modified comet assay) in cultured D1TNC1 rat astrocytes trea ted with 1 mM AN for 24 hours. When
NHAs were treated with 200–400 μ M AN for 12 hours, a four- to sevenfold increase in the generation of ROS and a greater than twofold increa se in 8-oxodG were observed (Jacob and Ahmed, 2003b).

In vivo studies

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Three studies on rats are available that investigat ed oxidative DNA damage in the brain after exposure to AN in drinking water (Jiang et al ., 1998; Whysner et al., 1998a). A two- to
threefold increase in 8-oxodG levels was found in c ellular DNA from brain cortex of SpragueDawley rats exposed to 50, 100, or 200 ppm AN in dr inking water for 28 or 90 days (Jiang et al., 1998). Levels of 8-oxodG in DNA increased with inc reasing exposure levels in this study. At 90 days, levels of 8-oxodG were more than twofold h igher in DNA from 50 ppm rat brain cortex compared with controls (Jiang et al., 1998). In ad dition, no increased levels of 8-oxodG were found in the liver DNA of exposed rats at all dose levels following 14, 28, or 90 days of exposure (Jiang et al., 1998). The liver is not a target organ for AN-induced carcinogenicity in adult rats. In a follow-up study, Pu et al. (2009) reported an increase in 8-oxodG levels in brain DNA of male Sprague-Dawley rats exposed to 100 or 2 00 ppm AN in drinking water for 28 days. However, EPA has identified issues with Pu e t al. (2009) (see Section 4.5.1.2.1); therefore, this study was not discussed separately here. In another study, levels of 8-oxodG in brain nucle ar DNA were increased by about twofold in Sprague-Dawley rats exposed to 30 or 300 ppm AN in drinking water for 21 days and by about 1.5-fold in rats exposed to 100 ppm AN for 94 days (Whysner et al., 1998a). However, no significant increase in 8-oxodG levels was found in F344 rats exposed to 10, 30, or 100 ppm for 21 days (Whysner et al., 1998a). (A statistica lly insignificant increase of about 30% was found in the 3–100 ppm AN dose groups.) Levels of 8-oxodG in liver DNA were increased by about 1.4-fold in Sprague-Dawley rats exposed to 30 or 300 ppm for 21 days and by about 1.3- and 2-fold following exposure to 100 ppm for 1 0 and 94 days, respectively (Whysner et al., 1998a). Levels of 8-oxodG in liver DNA were not me asured in F344 rats in this study. No significant increase in 8-oxodG levels in DNA of fo restomach (a target organ of AN carcinogenicity) were found in Sprague-Dawley rats exposed to 3–300 ppm AN (see Table 4-54).
Several inconsistencies can be found in the result s of Jiang et al. (1998) and Whysner et al. (1998a). While a dose-related increase in 8-ox odG levels in brain cortex DNA of SpragueDawley rats exposed up to 200 ppm AN was reported b y Jiang et al. (1998), a twofold increase in 8-oxodG levels in brain DNA was found for Spragu e-Dawley rats exposed to either 30 or 300 ppm in the study by Whysner et al. (1998a). Th us, there was no increase in 8-oxodG level with a 10-fold increase in exposure concentration i n Sprague-Dawley rats (Whysner et al., 1998a). While 8-oxodG levels were measured via dif ferent sample preparation methods in these two studies (i.e., 8-oxodG level was measured in nu clear DNA in whole brain in Whysner et al. [1998a] and in cellular DNA from brain cortex in Ji ang et al. [1998]), 8-oxodG level measured in Sprague-Dawley rats exposed to 3 or 30 ppm AN for 2 1 days in Whysner et al. (1998a) was comparable to that measured in Sprague-Dawley rats exposed to 5 or 50 ppm AN for 28 days in Jiang et al. (1998) (0.86/10 5 

### and 1.35/10 5 

### dG vs. 1.8/10 5 

### and 2.5/10 5 

### dG). Thus, inconsistencies

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in the two studies regarding 8-oxodG levels in rat brain are not likely due to differences in sample preparation.
Inconsistencies were also found in 8-oxodG levels i n livers in the two rat studies. Jiang et al. (1998) reported no increase in 8-oxodG level s in liver DNA of exposed rats, but Whysner et al. (1998a) reported a 1.4-fold increase in 8-ox odG levels in liver DNA of Sprague-Dawley rats exposed to 30 or 300 ppm for 21 days and a 1.3 - and twofold increase following exposure to 100 ppm AN for 10 and 94 days, respectively. Moreo ver, the increase in 8-oxodG levels in brain DNA was not much higher than that in liver DNA (see Table 4-55). The rat brain is a target organ for AN-induced carcinogenicity but not adult rat liver. In addition no significant increase
in 8-oxodG levels in forestomach DNA was found. Th us, no specificity is indicated regarding increased 8-oxodG levels (oxidative DNA damage) in target organ DNA and tumor formation. Inconsistencies were also found regarding AN-induce d disruption of antioxidant defense. While Jiang et al. (1998) reported increases in ROS and concomitant persistent decreases in antioxidant enzyme catalase activity in the brain c ortex of Sprague-Dawley rats exposed to 50– 200 ppm AN in drinking water after 14, 28, and 90 d ays, as well as decrease in SOD activity and GSH level in all dose groups after 14 days of treat ment, Whysner et al. (1998a) reported no changes in catalase and glutathione peroxidase acti vities and GSH levels in the brains of Sprague-Dawley rats treated with 3, 30, or 300 ppm AN in drinking water for 21 days. Whysner et al. (1998a) did report a dose-related increase i n cysteine levels in the brains of SpragueDawley rats exposed to AN for 21 days, and the incr ease was significant for the 300 ppm dose groups. However, no changes in GSH and cysteine le vels were found in the brains of F344 rats exposed to 0, 1, 3, 10, 30, or 300 ppm AN in the dr inking water for 21 days (Whysner et al., 1998a). Since F344 rats exposed to these dose leve ls of AN also developed brain tumors in chronic bioassay, the formation of these tumors can not be explained by oxidative stress resulting from disruption of antioxidant defense. Whysner et al. (1998a) also found no changes in cytochrome oxidase activities in the brain mitochon dria of both exposed Sprague-Dawley rats and F344 rats. Cyanide, a metabolite of AN, is a n oncompetitive inhibitor of cytochrome oxidase. No change in cytochrome oxidase activity indicated that no metabolic hypoxia occurred
in brain mitochondria as a result of inhibition of the enzyme by cyanide. Therefore, cyanideinduced metabolic hypoxia did not appear to be invo lved in the mechanism of ROS generation by AN. Moreover, Whysner et al. (1998a) reported no change s in TBARS in the brains of all groups of AN-exposed Sprague-Dawley rats, indicatin g the absence of lipid peroxidation,
another biomarker of oxidative stress and oxidative lipid damage. Jiang et al. (1998) reported significant increase in MDA only in the brain corte x of rats exposed to 200 ppm AN for 14 days and not in other dose groups at 14 days. No increa se was found in all dose groups at 28 and 90 days. Since lipid peroxidation is another bioma rker of oxidative stress, there is no strong evidence for occurrence of significant oxidative st ress in the brain of AN-exposed rats.

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In addition, Chantara et al. (2006) demonstrated th at AN induced ERK activation via PKC in SK-N-SH neuroblastoma cells. However, oxida tive stress was found not to be involved in AN-induced ERK1/2 activation, which played a cru cial role in cell proliferation and tumor progression. Thus, the potential tumor promotion e ffect of AN has not been related to oxidative

stress.

Dose-response concordance Levels of 8-oxodG in DNA from brain cortex of Sprag ue-Dawley rats (Jiang et al., 1998) or rat astrocytes (Kamendulis et al., 1999a) increa sed with increasing in vivo (50, 100, 200 ppm) or in vitro (0.01, 0.1, 1.0 mM) exposure levels. H owever, 8-oxodG in DNA from brain of F344 rats exposed to 1–100 ppm AN were not significantly increased. In addition, 8-oxodG levels in
DNA from brain of F344 rats did not show a dose-res ponse relationship (see Table 4-54), and no
correlation can be found between 8-oxodG levels in brain DNA of these rats and brain tumor incidence of F344 rats exposed to the same concentr ation of AN in drinking water for 2 years (Table 4-58). Thus, experimental data do not suppo rt the hypothesis that brain tumors from F344 rats are the result of oxidative DNA damage.

Table 4-58. 8-OxodG in brain DNA and brain tumor i ncidence in male F344 rats exposed to AN in drinking water

Dose group (ppm) 8-oxodG (mol/10 5 mol dG) a Incidence of brain astrocytomas b

0 0.79 ± 0.37 2/160
1 0.84 ± 0.25 2/80
3 1.07 ± 0.41 1/78
10 1.04 ± 0.30 2/80
30 1.03 ± 0.38 10/79
100 1.06 ± 0.48 21/76

a Data are from 21-d drinking water study by Whysner et al. (1998a).
b Data are from 2-yr drinking water study by Biodynam ics (1980b) and Johannsen and Levinskas (2002b). T he denominators for incidence of brain astrocytomas ex cluded rats from the 6- and 12-mo interim sacrifice s and rats that died before the appearance of the first tumor for this site.



### Moreover, although Whysner et al. (1998a) demonstr ated a significant increase in levels of 8-oxodG in brain DNA of Sprague-Dawley rats expo sed to AN for 21 days, no correlation can
be found between 8-oxodG levels in brain and tumor incidence in the 2-year bioassay (Table 4-59). Therefore, dose-response data on Spr ague-Dawley rats from Whysner et al. (1998a) did not support oxidative DNA damage as the mode of action for AN-induced brain
tumor formation.

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Table 4-59. 8-OxodG in brain DNA and brain tumor i ncidence in male Sprague-Dawley rats exposed to AN in drinking water

Dose group (ppm) 8-oxodG (mol/10 5 mol dG) a Incidence of brain astrocytomas b

0 0.62 ± 0.08 1/80
1 0.86 ± 0.41 ND
3 1.35 ± 0.49 ND
10 ND 8/47
30 ND 19/48
100 1.29 ± 0.10 23/48

a Data are from 21-d drinking water study by Whysner et al. (1998a).
b Data are from 2-yr drinking water study by Quast (2 002).

ND = cannot be determined



### Temporal relationships
The detection of increased 8-oxodG levels in brains of Sprague-Dawley rats exposed for subchronic durations (Jiang et al., 1998; Whysner e t al., 1998a) is temporally consistent with oxidative DNA damage being a plausible key precurso r event in the development of laterappearing tumors. However, no significant increase in 8-oxodG levels in the brain of exposed
F344 rats was found.

Biological plausibility and coherence The demonstration of AN-induced oxidative DNA damag e in rat brain cortexes following subchronic-duration exposure to AN at dose levels p roducing brain tumors with chronic exposure would have provided support for the involv ement of an indirect mutagenic mode of action in AN carcinogenicity. However, no increase in oxidative DNA damage was found in F344 rats exposed to AN in drinking water. Brain t umors were found in F344 rats at similar frequencies as Sprague-Dawley rats in chronic bioas says. Thus, brain tumors in F344 rats cannot be explained by oxidative DNA damage, and the predi cted greater sensitivity of Sprague-Dawley
rats vs. F344 rats based on 8-oxodG levels measured in short-term studies is not reflected in cancer bioassays. In addition, the presence of inc reased oxidative DNA damage in the livers of Sprague-Dawley rats exposed to AN in drinking water in one study (Whysner et al., 1998a) but not in another (Jiang et al., 1998) also raised the question regarding a significant association between oxidative DNA damage and tumor formation. The origin of oxidative stress is unclear. Propos ed molecular mechanisms that may be
involved in AN induction of oxidative stress in the brain (or other toxicity targets) include direct generation of free radicals by AN (or its metabolit es), stimulation by AN or its metabolites of systems that generate free radicals, binding of AN to free radical scavengers (e.g., GSH, vitamins C or E) and depletion of stores of these antioxidan ts, inhibition of the expression or activities of

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antioxidant enzymes, and interference of mitochondr ial respiratory electron flow via cyanide inhibition of cytochrome c oxidase (Zhang et al., 2 002; Jiang et al., 1998). As discussed previously, some of these potential mechanisms have been ruled out. As with the direct mutagenic mode of action, there are no data currently available to indicate how or if this indirect mutagenic mode of action may explain the occurrence of brain tumors in rats but not in mice, following chronic e xposure to AN.

Human relevance Humans possess the biochemical pathways for the key steps of this proposed mode of action. This hypothetical mode of action, if it oc curs, is considered to be relevant to humans.

Conclusion While plausible, this postulated mode of action is not supported by in vivo studies in rats. Studies on oxidative DNA damage or oxidative lipid damage in the brain of exposed rats do not provide sufficient evidence to support this mode of action. In addition, Chantara et al. (2006)
demonstrated AN-induced ERK activation via PKC in S K-N-SH neuroblastoma cells. Oxidative
stress was found to be not involved in AN-induced E RK1/2 activation, which played a crucial role in cell proliferation and tumor progression. Therefore, while this mode of action may play a role, it is not likely to be the principal mode of action for AN-induced carcinogenicity.

4.7.3.3.2. Other modes of action for brain tumors Key events Other hypothesized modes involve actions by AN or i ts metabolites to directly or indirectly alter the expression of genes (either at the level of translation, post-translation, or protein activity), leading to the loss of control o f cell growth and the ultimate promotion of
initiated cells into brain tumors. Possible modes of AN carcinogenic action include stimulation of cell proliferation (mitogenic), cytotoxicity wit h subsequent reparative cell proliferation (cytotoxic), inhibition of programmed cell death (a nti-apoptotic), and inhibition of GJIC. Studies specifically designed to examine these pos sible modes of action are restricted to a study of GJIC in rat astrocytes (Kamendulis et al., 1999b).

Strength, consistency, and specificity of associati on No studies are available that examine cellular pro liferation indices in brain cells following in vivo exposure to tumor-producing doses of AN. In in vitro studies with rat astrocytes, indices of cytolethality after 24 hours of exposure occurred at higher AN concentrations (2.5, 5.0, and 10.0 mM) than increas ed 8oxodG levels in DNA (0.01, 0.1, and 1.0 mM) (Kamendulis et al., 1999a). The available data do not support a prominent role for cytotoxic or mitogenic modes of action in AN-induce d rat brain tumors.

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Inhibition of GJIC has been shown to correlate wit h tumor promotion activity (i.e., the loss of control of growth) and to be induced by var ious chemical agents thought to operate via other modes of carcinogenic action, such as phorbol esters and PB (Kamendulis et al., 1999b). Exposure of rat astrocytes to 0.01, 0.1, or 1 mM AN for 4–48 hours statistically significantly inhibited GJIC compared with controls (Kamendulis e t al., 1999b). The inhibition was reversible and prevented by the presence of an antioxidant, α -tocopherol, or a precursor for the synthesis of glutathione, OTC, in the culture medium. The resul ts are consistent with the involvement of
AN-induced oxidative stress in the inhibition of GJ IC. The inhibitory concentrations were the same as those that produced oxidative DNA damage in a companion experiment (Kamendulis et al., 1999a). The specificity of the inhibitory res ponse to rat astrocytes was demonstrated by the lack of inhibition of GJIC in rat hepatocytes expos ed to 0.01, 0.1, or 1.0 mM AN (Kamendulis et al., 1999b).

Dose-response concordance The inhibition of GJIC in rat astrocytes increased with increasing sublethal concentrations in the range of 0.01–1 mM (Kamenduli s et al., 1999b). A concordance of these
concentrations to dose levels associated with brain tumors is not available.

Temporal relationships
The acute nature of the observed inhibition of GJIC is consistent with the hypothesis that this action may be one of a number of precursor eve nts involved in tumor promotion.

Biological plausibility and coherence Other potential modes of action for AN-induced brai n tumors have not been adequately studied. The involvement of inhibition of GJIC by oxidative stress induced by AN or its metabolites is plausible, based on the limited evid ence with rat astrocytes (Kamendulis et al., 1999b). However, the available histopathology data from interim sacrifices of the chronic rat bioassays do not support the involvement of a mode of action involving brain cell cytotoxicity followed by reparative cell proliferation.

4.7.3.3.3. Conclusions 

### about modes of action for brain tumors. Data gaps still exist in the current understanding of the mode of action for carcinogeni city of AN. However, there is sufficient experimental evidence to support direct mutagenicit y as the principal mode of action. Key events are the generation of direct DNA damage by t he AN metabolite, CEO, and interaction
with DNA. There is in vitro and in vivo evidence t o support the occurrence of key events in the brain following AN exposure. Other modes of action may contribute, along with direct mutagenesis, to tumorigenesis. For example, AN-ind uced ERK activation via PKC may play a role in cell proliferation and tumor progression. However, limited experimental evidence does

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not support them as alternatives. Available data a re inadequate to establish an oxidative stress mode of action for AN-induced carcinogenicity. The available data do not provide an explanation fo r AN induction of brain tumors in F344 and Sprague-Dawley rats but not in B6C3F 1 

### mice. However, it should be noted that generally mice are much less susceptible than rats in developing brain tumors resulting from exposure to chemical carcinogens (Rice and Wilbourn , 2000; Radovsky and Mahler, 1999). Hence, this species difference in response is not l imited to AN alone. In addition, there have been no investigations to attempt to explain the ap parent susceptibility of early-life plus chronic adult exposures compared with adult-only exposures. It is possible that a higher rate of cell division in the fetal brain and the resultant great er sensitivity to direct mutagenic damage may be involved (Slikker et al., 2004). Possible differen ces between early-life and adult stages of rat development in pertinent physiologic processes, suc h as distribution of AN or its metabolites to the brain, levels of antioxidants, activities of an tioxidant enzymes, or repair of DNA damage, have not been investigated to explain this apparent susceptibility of early-life stages to AN carcinogenicity.
Possible differences between rats and humans in di stribution of AN or its metabolites to the brain, susceptibility to oxidative stress, or r epair of DNA damage have not been investigated.
Identified differences between rats and humans in A N disposition are restricted to the finding of higher rates of metabolic oxidation of AN in human vs. rat hepatic microsomes, presumably due to a more active EH in humans (Kedderis and Batra, 1993; Kedderis et al., 1993c). The relevance of this apparent difference in AN metabol ism to possible species differences in susceptibility to AN carcinogenicity in the brain i s not understood. Within the framework of the hypothesized direct mutagenic mode of action, the b alance between the formation of CEO by CYP2E1 and its hydrolysis by EH is thought to be im portant in determining the levels of CEO that might be available to bind DNA or GSH. Experi mental comparison of this balance in
human and rat brain tissues is not available.

4.7.3.4. Possible Modes of Action for Forestomach Tumors There is evidence to suggest that, once delivered t o forestomach epithelial cells, AN or its metabolites shift the normal balance between cell p roliferation and apoptosis, leading to hyperplasia and eventually, with continued exposure and sustained net cellular proliferation, to tumor formation. Sustained increased cellular prol iferation is viewed as the key precursor event in this hypothesized mode of carcinogenic action. Exposure of male F344 rats to gavage doses of about 12 and 23 mg/kg-day AN for 6 weeks produce d minimal to mild hyperplasia and hyperkeratinization of the squamous mucosa of the f orestomach but not the epithelium of the glandular stomach or the liver (Ghanayem et al., 19 97). The early induction of hyperplasia by
AN doses that resulted in forestomach tumors in chr onic rat bioassays is temporally consistent with the involvement of sustained cell proliferatio n in the development of these tumors. A dose-

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related increase in cell proliferation (as determin ed by BrdU incorporation into DNA) was observed in the forestomach epithelium, but no incr eases were found in the glandular stomach or the liver, which are not targets of AN toxicity or carcinogenicity from chronic exposure to AN during adulthood. At the high-dose level, an incre ase in apoptotic cells was found. These results suggest that AN stimulation of cellular proliferati on overcame the apparent stimulation of apoptosis at the higher dose, since hyperplasia was observed. Whether or not the stimulation of cellular proliferation was due to a reparative resp onse to cytotoxicity or to a direct mitogenic action is uncertain. Acute administration of a hig her dose of AN (50 mg/kg) caused gastric mucosal necrosis in rats, which was shown to involv e CYP-mediated metabolism of AN (Ghanayem et al., 1985; Ghanayem and Ahmed, 1983). Whether or not these findings relate to the stimulation of cellular proliferation and devel opment of hyperplasia at the lower doses is
uncertain. Possible direct or indirect mutagenic modes of acti on for forestomach tumors, such as those investigated for brain tumors, have not been investigated. However, DNA damage, as detected by the comet assay, was reported in the st omach of rats and mice exposed by i.p. injection (Sekihashi et al., 2002). No significant oxidative DNA damage (levels of 8-oxodG) was measured in the forestomach of rats exposed to 3, 30, or 300 ppm in drinking water for 21 days (Whysner et al., 1998a). In addition, AN w as reported to bind to DNA in the stomach of rats following a single oral dose of 46.5 mg/kg (Fa rooqui and Ahmed, 1983a). Given that a mutagenic MOA is hypothesized for AN induced brain tumors in rats, that mutagenic carcinogens usually cause tumors in multiple sites, and evidence of DNA damage in the forestomach of AN treated rats, direct mutagenicity is a likely mode of action for AN-induced
forestomach tumors.

4.7.3.5. Possible Modes of Action for Hepatomas Although adult female Sprague-Dawley rats exposed t o 60 ppm AN by inhalation during adulthood did not develop hepatomas, these tumors w ere found in 5/67 male offspring and 1/54 female offspring exposed during gestation and extending throughout adulthood (Maltoni et al., 1988). In unexposed offspring in this study, hepatomas were found in 1/158 males and 0/149 females. This apparent susceptibility of ear ly-life stages to the initiation of liver tumors may be suggestive of a direct mutagenic mode of act ion in which embryonic DNA repair mechanisms are inadequate to repair AN-induced DNA damage during this stage of development when cells are rapidly dividing. N 7 

### -(2-oxoethyl)guanine-DNA adducts have been measured in the livers of adult rats following i.p. exposure to AN (Hogy and Guengerich, 1986). Increased
levels of 8-oxodG have also been measured in DNA fr om the livers of adult Sprague-Dawley rats exposed to AN in drinking water for 21 or 94 d ays (Whysner et al., 1998a). Thus, indirect mutagenic mode of action may also contribute. Howe ver, possible modes of action for the

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development or initiation of liver tumors during ea rly stages of development have not been investigated.

4.7.3.6. Possible Modes of Action for Tumors of Intestines, Tongue, Zymbal Gland, and
Harderian Gland Based on analogy to other direct-acting mutagens th at cause tumors at multiple sites in animal bioassays, it is possible that a direct muta genic mode of action may be involved in the
formation of AN-induced tumors at these sites in ra ts and mice. Although possible modes of carcinogenic actions of AN at these sites have not been investigated, direct mutagenic mode of action is the most likely mode of action. CYP2E1 e nzymes occur in intestinal mucosa, and CEO
can form in intestine and bind to DNA. In addition , there is no evidence that AN would have a tissue specificity that would lead to mutagenesis i n brain but not other organs. Moreover, AN appears to act systemically with DNA damage, and tu mors occur in multiple tissues of treated animals. The direct mutagenic mode of action is co nsidered relevant to all tumor sites
4.7.3.7. Possible Modes of Action for Lung Cancer Evidence of a possible association between occupati onal exposure to AN and lung cancer is found in some studies, including the best availa ble epidemiologic study that workers in the highest exposure category (>8 ppm-years) with more than 20 years of employment displayed a twofold increased risk for lung cancer compared wit h unexposed workers (Blair et al., 1998). Human bronchial epithelium has CYP2E1 metabolic act ivities. In a short-term mutagenicity assay, AN induced SCEs and DNA single-strand breaks in human bronchial epithelial cells without the addition of S9 mix (Chang et al., 1990) . Thus, a direct mutagenic mode of action is supported for potential AN-induced lung cancer. In contrast, there is no convincing evidence of lun g cancer in rodents chronically exposed by the oral or inhalation routes. The possible mod e of action by which AN may induce lung
tumors in humans and not in rodents has not been in vestigated but may involve species
differences in inhalation rates and anatomical feat ures of the respiratory tract.

4.8. SUSCEPTIBLE POPULATIONS AND LIFE STAGES 4.8.1. Possible Childhood Susceptibility Evidence that children may be more susceptible to the acute or chronic toxicity of AN is restricted to a report that children died after sle eping in rooms fumigated with a commercial form of AN called Ventox, whereas adults sharing the sam e rooms only experienced skin or eye irritation (Grunske, 1949; see Section 4.1.3.1). Animal studies specifically designed to examine wh ether or not early-life stages of development are more susceptible than adult stages to the induction of noncancer or cancerrelated effects by AN include a lifetime inhalation cancer bioassay in Sprague-Dawley rats (Maltoni et al., 1988) and a three-generation drink ing water reproductive toxicity bioassay in

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Sprague-Dawley rats that provides evidence of incre ased tumor incidences in F1 and F2 female breeders after 46 weeks of exposure starting in ute ro (Friedman and Beliles, 2002). In addition, a subacute study on Sprague-Dawley rats (Szabo et a l., 1984) also found weanling rats to be more susceptible than adult rats to the action of A N on the adrenals (see Section 4.2.1.1). Results from the lifetime inhalation bioassay show ed that rats that were chronically exposed starting in utero had higher incidences of tumors at several sites (b rain, Zymbal gland, mammary gland, liver, and blood vessels) compared w ith rats chronically exposed during adulthood only (Maltoni et al., 1988; see Section 4 .2.2.2.2 for details). For example, brain tumors occurred in 5.5% of rat dams chronically exp osed to 60 ppm AN compared with no brain tumors in unexposed controls (Table 4-42). In cont rast, 16.4% of male and 18.5% of female offspring of the exposed dams had brain tumors comp ared with 1.3% of male and 1.3% of unexposed female rats exposed starting in utero, ot herwise under the same exposure protocol as the dams. The responses for brain tumors (male and female offspring), extrahepatic angiosarcomas (female offspring), Zymbal gland (mal e offspring), and mammary gland (female offspring) with chronic exposure were about threefo ld higher than those observed in female rats exposed only during adulthood (Table 4-42). In add ition, although none of the exposed or unexposed dams had hepatomas, 5/67 male offspring w ith early-life plus chronic exposure had hepatomas compared with 1/158 unexposed male offspr ing; hepatomas were observed in 1/54 exposed female offspring compared with 0/149 u nexposed female offspring. Rats with early-life plus subchronic (8-week) adult exposure did not show elevated incidences for these tumors compared with adults with chronic adult expo sure (Table 4-42). Comparison of the results from the two chronic pha ses of this experiment indicated that, compared with chronic exposure to 60 ppm during onl y adult stages of development, chronic exposure to 60 ppm AN starting during gestation inc reased the risk for development of extrahepatic angiosarcomas and malignant mammary gl and tumors in females, hepatomas and Zymbal gland carcinomas in males, and encephalic gl iomas in males and females. Although testing in adult male rats was not included in this study, the increase in hepatomas in male offspring may indicate differences in detoxificatio n and DNA repair mechanisms between fetal
and adult livers. In the drinking water bioassay involving 46-week e xposures of each of three generations of female breeder Sprague-Dawley rats, there were s lightly increased incidences of tumors in F0 or F2b female breeders in the 100 or 500 ppm gro ups compared with controls, which were not statistically significant, while F1b female breeder s in the 500 ppm group showed statistically significantly increased incidences of brain and Zym bal gland tumors compared with control, at 24 (4/17) vs. 0 and 18 (3/17) vs. 0%, respectively (Friedman and Beliles, 2002). Compared with the 500 ppm F0 breeders that were exposed starting in adulthood, there was an approximate twofold increase in Zymbal gland tumor incidence an d a threefold increase in brain tumor incidence in the 500 ppm F1b female breeders, expos ed starting in utero (Table 4-35). The

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results provide evidence for the increased suscepti bility to the carcinogenicity of AN during early-life exposure, positive evidence being in the F1 generation. Increases in tumor incidence in the F2 generation were not as pronounced and were n ot statistically significant. As discussed in Sections 4.5.1 and 4.6.3, toxic ef fects from acute or chronic exposure to AN have been associated with inhibition of glutathi one-mediated detoxification of AN by conjugation (e.g., glutathione depletion), transfor mations in the CYP2E1 metabolic pathway to CEO and cyanide, and oxidative stress. Differences in enzymatic activities (e.g., CYP2E1, EH, DNA repair enzymes, or antioxidant enzymes such as catalase or SOD) or pool sizes of reactive oxygen scavengers (e.g., levels of vitamin E or C) or glutathione between early-life and adult stages may result in life stage differences in susc eptibility to AN toxicity. For CYP2E1, immunoreactive CYP2E1 protein has been detected in human liver microsomes as early as the second trimester (GDs 93 –186) (Johnsrud et al., 2003). CYP2E1 enzyme activity increases shortly after birth but l ess in neonates than in older infants, children, and adults (Johnson, 2003; Johnsrud et al., 2003; V ieira et al., 1996). However, in the fetal brain, CYP2E1 activity is seen as early as 50 days gestation, with increasing levels seen to at least the end of the first trimester (Brzezkinski e t al., 1999). In rats, CYP2E1 protein is not significantly expressed in fetal hepatic tissues, a lthough an elevation of CYP2E1 mRNA was seen within a few hours after birth, coincident wit h the transcriptional activation of the gene (Borlakoglu et al., 1993). Moreover, only neonates expressed small quantities of the CYP2E1 protein, despite the large quantities of CYP2E1 mRN A found in perinatal and neonatal rats. For EH, fetal immunoreactive enzyme content in huma n livers averages only 25% of that found in adults with corresponding less enzyme acti vity (Cresteil et al., 1985). EH activity in fetal liver and adrenal glands are about threefold higher than in kidney and lung with only a weak correlation with gestational age between 10 an d 25 weeks. Overall, EH activity in fetal tissue is about 30–40% of that in adults (Pacifici and Rane, 1983b; Pacifici et al., 1983a). In another study (Omiecinski et al., 1994), human micr osomal EH (mEH) was detected in fetal liver as early as 7.2 weeks, although at a much lower lev el of mEH protein, and demonstrated a linear increase with gestational age to a level at 77 week s that is about half of that observed in adult liver. However, mEH activity in the fetal lung did not correlate with increasing age. Lung mEH activity from days 85 to 130 of gestation was maint ained at consistent levels, at about the same level as fetal hepatic EH at 53 days, and varied on ly by threefold. In addition, Omiecinski et al. (1994) reported that mEH activities in liver or lun g, from either fetal or adult tissues, did not correlate with corresponding mRNA levels. The overall balance of pertinent enzymatic activiti es (AN metabolizing enzymes and antioxidant enzymes) and pool sizes of reactive oxy gen scavengers and glutathione will determine the relative susceptibility of an individ ual or a life stage. The relatively high activity of CYP2E1 in the brain compared to the liver of the developing human fetus, and low EH activity for detoxification raise concern for incre ased susceptibility in early life to lung tumors,

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and brain tumors from AN exposure, as seen in rats. Additional research examining agedependent changes in these physiological variables and responses to AN may help to provide explanations for the observed susceptibility of ear ly-life stages in rats to the carcinogenicity of AN, and is outside the scope of this assessment. The importance of CYP2E1 metabolism in the acute t oxicity and lethality of AN has been demonstrated by the lack of lethality or gross sign s of intoxication in CYP2E1-null male mice given single gavage doses up to 40 mg/kg, whereas a ll WT male mice given doses of 40 mg/kg died within 3 hours of administration (Wang et al., 2002). This type of research approach (i.e., the comparison of pertinent endpoints in WT and CYP 2E1-null animals) may be useful in helping to better understand the physiologic basis of the apparent susceptibility of early-life stages to the carcinogenicity of AN, which was demo nstrated in the rat study by Maltoni et al. (1988). SubchronicSubchronic 

### 4.8.2. Possible Geriatric Susceptibility Age-related reductions in antioxidant or glutathio ne pool sizes may increase susceptibility of elderly people to the tissue-dama ging actions of AN and reactive metabolites, but specific studies of the possible increased susc eptibility of aged people or rats to AN are not available. A 35% decrease in glutathione levels in the liver of aged F344 rats compared with younger animals was associated with an age-related decrease in the levels and activity of

γ -glutamylcysteine ligase, a key enzyme in the synth esis of glutathione (Suh et al., 2004). In Wistar rats, the liver and kidney of 22-month-old r ats showed significant decreases, compared with 10-week-old rats, in glutathione and glutathio ne peroxidase and increased levels of biomarkers of lipid peroxidation (Martin et al., 20 03). In another study with F344 rats (Tian et al., 1998), activities of several antioxidant enzym es in several tissues displayed an age-dependent decline. Enzymatic activities showing significant decline with age included SOD in the heart, kidney, and serum; glutathione peroxidase in the se rum and kidney; and catalase activities in the brain, liver, and kidney. These changes indicated a lower resistance to oxidative stress in older
animals. The possible toxicological impact of an age-relate d decline in glutathione could be offset by an age-related decline in CYP2E1-mediated metabo lism of AN leading to reactive metabolites (CEO), cyanide, or ROS. Many studies h ave reported that hepatic enzymatic activities of CYP2E1 are lower in elderly human sub jects (>65 years) compared with younger adults (see Tanaka, 1998, for review). Decreased h epatic CYP2E1 enzyme activities have also been reported in aged rats. For example, hepatic C YP2E1 enzyme activities were decreased by 46% in 18-month-old rats compared with 8-month-old rats, whereas no age-related changes in CYP2E1 mRNA or protein content were evident (Wauthi er et al., 2004). Such age-related declines in CYP2E1 enzyme activities may lead to lo wer tissue levels of reactive metabolites or cyanide but also may lead to elevated levels or inc reased residence time of AN in aged tissues compared with younger tissues. No definitive concl usions about the possible susceptibility of

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the elderly to AN toxicity can be drawn without mor e specific studies designed to examine the effects of age on susceptibility to AN toxicity. As studied in a small number of individuals (n = 4 7), long-term occupational exposure to
AN increased the deletion rate in mitochondrial DNA to a level equivalent to that seen in a group of elderly nonexposed subjects (n = 12) (Ding et al ., 2003) (see Section 4.1.2.2). The study authors suggested that AN may have an effect on the molecular processes of aging.

4.8.3. Possible Gender Differences No reports of gender differences in susceptibility of humans to AN toxicity are available. No consistent gender-related differences in carcino genic responses were observed in rats or mice, following chronic oral exposure to AN, or in rats, following chronic inhalation exposure. With oral exposure, male and female groups showed s imilarly increased incidences of brain astrocytomas (rats: Quast, 2002; Bigner et al., 19 86; Biodynamics, 1980a, b, c; Quast et al., 1980a), forestomach tumors (rats: Quast, 2002; Big ner et al., 1986; Biodynamics, 1980a, b, c; Quast et al., 1980a; mice: NTP, 2001), Zymbal’s gl and tumors (rats: Quast, 2002; Bigner et al., 1986; Biodynamics, 1980a, b, c; Quast et al., 1980a ), and Harderian gland tumors (mice: NTP, 2001). Following inhalation exposure to 80 ppm AN for 2 years, male and female exposed groups of rats showed similarly increased incidence s of brain/CNS tumors and Zymbal’s gland tumors compared with the respective control groups (Quast et al., 1980b). No marked gender-related differences in noncarcino genic responses were observed in the rat chronic oral toxicity study reported by Quast ( 2002). Groups of male and female rats were exposed to AN in drinking water at concentrations o f 0, 35, 100, or 300 ppm. At the 1-year interim sacrifice, the only exposure-related noncan cer histopathologic finding was an increase in the incidence of forestomach squamous cell hyperpla sia in rats exposed to concentrations of 100 ppm (4/10 males, 7/10 females) or 300 ppm (10/1 0 males, 9/10 females). At the 2-year sacrifice, incidences of stomach lesions (nonglandu lar hyperplasia and/or hyperkeratosis) were similar in male (15/80, 15/47, 44/48, and 45/80 for the control through high-concentration groups, respectively) and female (20/80, 23/48, 41/ 48, and 47/48) rats at the same exposure level (Quast, 2002). These data, however, give some indi cation that the forestomach epithelium of female rats may have been slightly more susceptible than that of male rats: at the 1-year sacrifice, 7/10 100 ppm females (70%) had lesions c ompared with 4/10 100 ppm males (40%); at 2 years, 23/48 35 ppm females (48%) had lesions com pared with 15/47 35 ppm males (32%). In contrast to the lack of apparent gender differe nces in carcinogenic or noncarcinogenic responses in rodents with chronic exposure, male mi ce appear to be more susceptible to the acute oral toxicity of AN than female mice (Chanas et al. , 2003; NTP, 2001). In a 14-week study, groups of 10 male and 10 femal e mice were given 0, 5, 10, 20, 40, or 60 mg/kg AN in deionized water by gavage 5 days/wee k (NTP, 2001). Exposure-related
mortalities were restricted to the first week of th e study and occurred in the 40- and 60-mg/kg

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groups. Both male and female groups showed mortali ty, but only at 40 mg/kg was the incidence of deaths higher in male mice compared with females (9/10 and 10/10, males, and 3/10 and 10/10, females, at 40 and 60 mg/kg, respectively). In a subsequent study, groups of three to four mal e and three to four female WT or CYP2E1-null mice (mixed 129/Sv and C57BL) were give n single gavage doses of 0, 2.5, 10, 20, or 40 mg/kg in tap water and sacrificed 1 or 3 hour s later (Chanas et al., 2003). All male WT mice exposed to 40 mg/kg died within 3 hours, showi ng gross signs typical of cyanide poisoning (rapid shallow breathing, cyanosis, trembling, and convulsions). In contrast, exposed female WT mice showed milder gross signs of poisoning, and no ne died within the 3-hour period. One hour after dose administration, concentrations of cyanid e in blood were statistically significantly elevated, compared with vehicle controls, in WT mal e mice given doses ≥ 2.5 mg/kg. At doses
≥ 10 mg/kg, female WT mice also showed elevated cyani de levels in blood, compared with controls, but cyanide levels were <50% that in male WT mice. Exposed CYP2E1-null mice of both genders showed no elevation in blood cyanide c oncentrations compared with vehicle controls. Cyanide levels in brain and kidney tissu es were also higher in WT males compared with females; cyanide levels in liver and lung tiss ues showed less distinct differences between
male and female mice. Expression of hepatic, renal, and pulmonary CYP2E1, soluble EH, and microsomal EH were measured in male and female WT mice using West ern blot analysis (Chanas et al., 2003). In the liver, WT males showed greater expression of EH, both soluble and microsomal, than did females; CYP2E1 levels were similar in males and fe males. In the kidney, male WT mice showed markedly higher levels of CYP2E1 (about four fold), moderately higher levels of soluble EH (about twofold), and comparable levels of micros omal EH compared with female mice. Higher CYP2E1 and soluble EH in the kidney of male mice provided explanation for higher blood cyanide levels in the kidney and acute lethal ity in male mice. In the lung, no gender differences in the expression of these enzymes were apparent. The results indicated that male mice were more susceptible than female mice to the acute toxicity and lethality of AN and that this difference was associated with higher blood, k idney, and brain levels of cyanide in males shortly after dose administration. Chanas et al. ( 2003) noted that another possible explanation was that female mice had greater detoxification cap ability of converting cyanide to thiocyanate, as demonstrated by excretion of greater amount of t hiocyanate in urine than males after repeated administration of equal doses of AN (NTP, 2001). In a subsequent study, male mice (mixed 129/Sv and C57BL) showed higher blood levels of cyanide than female mice 1 hour after gavage adm inistration of 0.047, 0.095, 0.19, or 0.38 mmol/kg (2.5, 5, 10, or 20 mg/kg) AN (El Hadri et al., 2005). This difference between genders was evident in WT mice and in microsomal EH -null (mEH-null) mice, but blood levels of cyanide were lower in exposed mEH-null mice, com pared with comparably exposed WT mice. As in the previous experiments reported by C hanas et al. (2003), exposure to AN induced

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no elevation of blood levels of cyanide in CYP2E1-n ull mice of either gender. Western blot analysis revealed no gender differences in expressi on of CYP2E1 in the liver of WT or mEHnull mice or in expression of mEH in WT or CYP2E1-n ull mice. However, expression of soluble EH in the liver was greater in WT males, co mpared with females. No gender differences in expression of this enzyme was observed in mEH-nu ll mice or in CYP2E1-null mice. The effect of gender on the expression of CYP2E1 an d EH have been investigated in humans and rats. Gender was reported to have no in fluence on the level of CYP2E1 in human liver (George et al., 1995). Sex-related patterns in the activity of hepatic EH activity was studied in Sprague-Dawley rats (Chengelis, 1988). At week 4, epoxide activity in both male and female rats was equivalent (3.5–4.0 nmol/minute per mg pro tein, or 85–100 nmol/minute per g liver). However, there were consistent increases in activit y in males from week 4 to 78, while activity in females actually decreased, but returned to week 4 levels during the later stages (week 78–103). EH activity in male liver peaked at week 78 (about 10 nmol/minute per mg protein, or 350 nmol/minute per g liver). There was a sharp de cline in EH activity in aged male rats to about 6 nmol/minute per mg protein, or 200 nmol/min ute per g liver at 104 weeks. Cornet et al. (1994) studied gender-related changes in microsomal and cytosolic EH activity in male and female Brown Norway rats. At 15 week, microsomal E H activity was about the same for male and female rats at 4.5 nmol/mg protein/minute. The microsomal EH activity decreased strongly as a function of age in female rats, and in the 125 -week-old females, the activity was only half of that found in 15-week-old rats. However, there was no age-related change in males, although the activity in the 83- and 125-week age groups was sig nificantly lower than that in 28-week-old males. The activity of EH activity was higher in m ales than in females in these aged animals. In another study that compared hepatic microsomal EH i n different strains of adult rats (170–250 g) (Oesch et al., 1983), EH activities in females were found to be 71–88% of those in males in all strains. Denlinger and Vesell (1989) studied the h ormonal regulation on the developmental pattern of EH in F344 rats, and found that EH activ ities in males increased gradually until puberty, when activities in males rose rapidly to b e from 1.5- to twofold higher than those in females. The higher activity in males was not seen if the males were castrated 24 hours after birth. When castrated males and females were injec ted with testosterone propionate (0.5 mg s.c.) on days 1, 3, and 5 postpartum, increased mEH an cE H activities were observed at adulthood. Thus, Denlinger and Vesell (1989) concluded that fu ll adult expression of EH activities depends on hormonal influences exerted neonatally.
Gender-related differences were also observed in c ytosolic EH activity of Brown Norway rats (Cornet et al., 1994). Significant gender-rel ated differences in the cytosolic EH activity were found in 15-, 28-, and 83-week-old rats with t he male animals showing the highest values. In the oldest animals and in 56-week-old rats compa rable cytosolic EH activities were found in both genders.

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In summary, the available data from animal studies provide no evidence of consistent or marked gender differences in susceptibility to nonc ancer or cancer-related effects from chronic exposure to AN. There is evidence that male mice a re more susceptible than female mice to the acute, cyanide-induced toxicity and lethality of AN , but whether or not this apparent gender dimorphism extends to other species is uncertain at the present time.

4.8.4. Genetic Polymorphisms
4.8.4.1. CYP450 In humans, CYP2E1 exists in several modifications t hat differ in amino acid sequence (alleles). Human variability in their susceptibili ty to the toxic effects of AN likely exists since CYP2E1 activities may fluctuate between one person and another.
Microsomal CYP2E1 activities varied from 6- to 20-f old in human livers (Lucas et al., 1993). Environmental factors, diet habits, and/or genetic factors may account for the observed interindividual variations observed. In addition, CYP2E1 is elevated in obese overfed rats (Salazar et al., 1988) and diabetic rats (Song et a l., 1987), suggesting induction by increased plasma levels of ketone bodies (Bellward et al., 19 88). Moreover, CYP2E1 is elevated in lymphocytes from poorly controlled insulin-dependen t diabetics (Song et al., 1990). Thus, obese and diabetic individuals may have elevated levels o f CYP2E1. Besides induction, polymorphism of the human CYP2E 1 gene may have an impact on AN metabolism in humans. Stephens et al. (1994) co mpared two restriction fragment length polymorphic sites of the CYP2E1 gene (Rsa 1 and Dra 1), in 695 Africa n-American, EuropeanAmerican, and Taiwanese subjects. Rare alleles at these two loci have been associated with a reduced risk for lung cancer in Japanese and Swedis h population s . Stephens et al. (1994) demonstrated that rare alleles (c2 and C) at the Rs a 1 and Dra 1 sites were at least twice as frequent in Taiwanese populations (28 and 24%, resp ectively) compared with AfricanAmericans (1–8%) or European-Americans (4–11%), rai sing the possibility of differential susceptibility to chemically induced cancers across ethnic groups. However, when Carrière et al. (1996) measured the allele frequencies for Ras 1, D ra 1, and Taq 1 polymorphic sites in liver CYP2E1 from kidney donors (n = 93) in Geneva, they failed to find a correlation between frequencies of rare alleles and CYP2E1 activity. T his implied that observed differences in enzyme activity in humans were more likely to be th e result of different levels of induction by environmental factors or other genetic factors. McCarver et al. (1998) identified a 100-bp inserti on mutation in the regulatory region of CYP2E1 gene. Associated with an elevated CYP2E1 me tabolic activity, this insertion mutation appears to be present only in obese people or perso ns who had recently consumed alcohol. The
incidence of this mutation was seen in 31% of 65 Af rican-American samples but only in 6.9% of 58 Caucasian samples (McCarver et al., 1998). If t umor formation is determined by the activity

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of CYP2E1, this mutation might put affected individ uals at a higher risk of cancer from tumorigenic agents that are metabolized by CYP2E1. Thier et al. (2002) were unable to detect any infl uence of six genetic CYP2E1 polymorphisms (G -1259 

### C, A -316 

### G, T -297 

### A, G -35 

### T, G 4804 

### A, and T 7668 

### A) on the formation of N-(cyanoethyl)valine Hb adducts of AN. Conversely, in a study confined to a cohort of individuals from ethnic minorities (African-America ns and Mexican-Americans), Wu et al. (1998) observed an increased incidence of the CYP2E 1 DraI DD genotype in peripheral WBC DNA in 126 patients with untreated lung cancer comp ared with 193 unaffected controls. This could imply an etiological association between the CYP2E1 DraI polymorphism and tumor formation in the lung. Altered toxicokinetic chara cteristics of CYP2E1 in persons exposed to AN might result in some persons being more vulnerab le than others to the tumorigenic effects of the compound, with concomitant changes to the rate and amount of formation of the toxic metabolite and associated changes in susceptible in dividuals. Kim et al. (1996), investigating the differences i n CYP2E1 activities between 20 Caucasian and 20 Japanese men, pointed out that the significantly lower activity of CYP2E1 in Japanese men might account for the lower rate of some cancers in Japanese compared to
Caucasian men.

4.8.4.2. Glutathione S-transferases Thier et al. (1999) studied the formation of Hb add ucts of AN (N-[cyanoethyl]valine, N-[methyl]valine, and N-[hydroxyethyl]valine) in a group of 59 people occupationally exposed to the chemical. They reported their findings in r elation to subjects’ smoking habits and their genetic status with respect to the GST isozymes GST M1 and GSTT1. Included in the study was an evaluation of smoking habits, since elevated add uct levels of AN in Hb have been reported in
smokers. There was no correlation between adduct l evels and either the subjects’ status of GST isozymes or smoking habit. Thus, neither GSTM1 norGSTT1 appears as a major ANmetabolizing isoenzyme in humans. However, in a fo llow-up study with the same group of 59 workers, Thier et al. (2001) reported that polym orphism of the GSTP1 gene at codon 104 was associated with a higher level of N-(cyanoethyl) va line adducts, while GSTM3 variants had no effect on Hb adduct formation. Any potential effec t arising from such polymorphisms on the health risk to AN-exposed humans awaits to be evalu ated. However, Zielinska et al. (2004) reported an increase in the frequency of the GSTP1b /b genotype in children with cancer (OR = 5.7, CI = 2.4–13.8).

4.8.4.3. EH Two major polymorphisms of mEH have been identified in human population (Hasset et al., 1997). One is a polymorphism in exon 3 that c hanges the tyrosine residue 113 (Tyr113) to histidine (His113), and the other is an A → G substitution in exon 4 that changes the histidine

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residue 139 (His 139) to arginine (Arg139). In vit ro expression studies demonstrated that with the Tyr113His polymorphism, the corresponding mEH e nzymatic activity is decreased by about 40% (Hasset et al., 1997). On the other hand, the His139Arg polymorphism results in increased enzyme activity. Population studies have demonstra ted that the low activity 113His allele correlates with an increased risk for lung cancer ( Benhamou et al., 1998), colon cancer (Harrison et al., 1999), hepatocellular carcinoma developed a fter aflatoxin exposure (McGlynn et al., 1995), and chronic obstructive pulmonary disease (S mith and Harrison, 1997). The mEH genotypes was shown to play a significant r ole in human sensitivity to the genotoxic effects of exposure to 1,3-butadiene (Abd el-Rahman et al., 2003, 2001). The carcinogenic and mutagenic effects of 1,3-butadiene are thought to be due to its epoxide metabolites, and the hydrolytic pathway involving m EH is the main detoxification pathway for 1,3-butadiene-reactive intermediates in humans (Jac kson et al., 2000). In a study of 49 nonsmoking workers from two styrene-butadiene ru bber plants, the hprt gene mutation assay was used as a biomarker of genotoxic effect of BD ( Abdel-Rahman et al., 2003, 2001). AbdelRahman et al. (2003, 2001) evaluated the effect of polymorphisms in both exon 3 and exon 4 of the mEH gene as modifiers of individual susceptibil ity to the mutagenic response associated with exposure to 1,3-butadiene, and found a progressive increase in hprt mutant frequency with declining mEH activity in the high exposure group ( >150 ppb). The highest frequency of hprt mutant lymphocytes occurred in the group with the m EH low-activity genotype. Individuals with low mEH activity had three- and twofold increa ses in hprt mutant frequency compared to individuals with high and intermediate mEH activity , respectively. In the low exposure group, there was no difference in hprt mutant frequency be tween high-, intermediate-, and low-activity individuals. Although there are no studies that ev aluate the role played by mEH genotypes in human sensitivity to the toxicity of AN, since EH i s involved in the hydrolysis of CEO and its elimination, polymorphisms in exon 3 and exon 4 of the mEH gene are likely to have a role in human susceptibility.

### 304 DRAFT - DO NOT CITE OR QUOTE 5. DOSE-RESPONSE ASSESSMENTS

5.1. ORAL REFERENCE DOSE (RfD) 5.1.1. Choice of Principal Study and Critical Effe ct As previously discussed in Section 4, no human stu dies currently exist that involve oral exposures to AN. The primary route of AN exposure in humans is via inhalation. The available animal oral toxicity studies, however, identify fo restomach lesions (i.e., squamous cell epithelial hyperplasia and hyperkeratosis) as the most sensiti ve, prevalent, and consistent noncancer effect associated with chronic oral exposure to AN (see Ta ble 4-56 and Figure 5-1). Although, benchmark dose (BMD) modeling of dose-response data is preferred, several of the endpoints under consideration (i.e., incidences of chronic ne phropathy, ovarian cysts, and gliosis in the brain in rodents) were not amenable to modeling bec ause either there was no evidence of a dose response or the response was not a monotonically in creasing function of dose. A NOAEL/LOAEL approach was used as a common basis for comparison. Using this approach,
forestomach lesions were selected as the critical e ffect on which to base the derivation of the RfD. Although, anatomically, humans do not possess a forestomach, they do have comparable squamous cell epithelial tissues in their oral cavi ty and in the upper two-thirds of their esophagus (IARC, 1999). Moreover, the forestomach lesions ob served in animals were not likely due to the direct irritating effect of AN on gastric tissue. GI bleeding has been observed with single s.c. or oral administration of AN in rats (Ghanayem and Ahm ed, 1983) that likely resulted from the
distribution of AN metabolites from blood into the GI mucosa. Jacob and Ahmed (2003a) have
also demonstrated that AN or its metabolites accumu lated and covalently interacted with the GI mucosa of F344 rats treated either orally or intrav enously with 2-[ 14 

### C]-AN, supporting the theory of metabolic incorporation and macromolecular inter action of AN or its metabolites with gastric
tissue. Two 2-year drinking water studies, one in Sprague- Dawley rats (Quast, 2002; Quast et al., 1980a) and the other in F344 rats (Johannsen a nd Levinskas, 2002b; Biodynamics 1980c), and a 2-year gavage study in B6C3F 1 

### mice (NTP, 2001) provided the best available doseresponse data on which to base the RfD (Table 5-1 for rats and Table 5-2 for mice). In SpragueDawley rats, significantly elevated incidences of h yperplasia and hyperkeratosis in squamous epithelium of the forestomach occurred in both male s and females exposed to AN in drinking water at the two highest concentrations administere d (i.e., 100 and 300 ppm) with incidences approaching 100% at the highest dose. Female Sprag ue-Dawley rats also exhibited statistically significantly elevated incidences at the lowest con centration of AN administered (i.e., 35 ppm). In F344 rats, both males and females exposed to 3, 10, and 30 ppm AN in drinking water exhibited statistically significantly elevated inci dences of forestomach lesions with incidences of approximately 20–30%. Male and female F344 rats ex posed to the lowest and highest

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concentrations of AN in drinking water (i.e., 1 and 100 ppm) did not show statistically significantly elevated incidences of forestomach le sions.

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Table 5-1. Incidences of forestomach lesions (hype rplasia or hyperkeratosis) in Sprague-Dawley and F344 rats exp osed to AN in drinking water for 2 years

Predicted internal dose metrics b

Sex Administered

concentration (ppm in drinking water) Administered

dose a (mg/kg-d) AN-AUC in rat

blood (mg/L) CEO-AUC in rat

blood (mg/L) Incidence of

forestomach lesions c Sprague-Dawley rats (Sources: Quast, 2002; Quast et al., 1980a) 0 0 0 0 15/80 (19%)
35 3.4 2.06 × 10 -2 1.83 × 10 -3 15/47 (32%)
100 8.5 5.36 × 10 -2 4.36 × 10 -3 44/48 (92%) c Male

300 21.3 1.46 × 10 -1 9.70 × 10 -3 45/48 (94%) c

0 0 0 0 20/80 (25%)
35 4.4 2.37 × 10 -2 2.07 × 10 -3 23/48 (48%) c

100 10.8 6.18 × 10 -2 4.87 × 10 -3 41/48 (85%) c Female

300 25.0 1.56 × 10 -1 1.01 × 10 -2 47/48 (98%) c

F344 rats d (Sources: Johannsen and Levinskas, 2002b; Biodynam ics, 1980c) 0 0 0 0 11/159 (7%)
1 0.08 4.33 × 10 -4 4.06 × 10 -5 3/80 (4%)
3 0.25 1.35 × 10 -3 1.27 × 10 -4 18/75 (24%) c

10 0.83 4.52 × 10 -3 4.19 × 10 -4 13/80 (16%) c

30 2.48 1.37 × 10 -2 1.23 × 10 -3 17/80 (22%) c Male

100 8.37 4.85 × 10 -2 3.97 × 10 -3 9/77 (12%)

0 0 0 0 4/156 (3%)
1 0.12 5.73 × 10 -4 5.32 × 10 -5 2/80 (3%)
3 0.36 1.72 × 10 -3 1.59 × 10 -4 16/80 (20%) c

10 1.25 6.02 × 10 -3 5.49 × 10 -4 23/74 (31%) c

30 3.65 1.79 × 10 -2 1.58 × 10 -3 13/80 (16%) c Female

100 10.90 5.63 × 10 -2 4.46 × 10 -3 5/74 (7%)

a Administered doses were averages calculated by the study authors based on animal BW and drinking water intake.
b The EPA-modified rat physiologically based pharmaco kinetic (PBPK) model of Keddaris et al. (1996) was employed to predict a rat internal dose (i.e., eith er AN-AUC or CEO-AUC concentration in blood, where AUC = area under the curve) resulting from the ingestion of the specified administered dose of AN consumed i n six bolus episodes/d.

c Indicates significantly different (at p < 0.05) from control incidence by Fisher’s exact te st. d Incidences for F344 rats do not include animals fro m the 6- and 12-mo sacrifices and were further adju sted to exclude (from the denominators) rats that died betw een 0 and 12 mos in the study. Rats dying during t his time period were determined from page 6 of Appendix H an d Table 1 in Biodynamics (1980c) and Table 8 in Johannsen and Levinskas (2002b). Unschedu led deaths between 0 and 12 mos in the study occurr ed in two female controls, two males at 3 ppm, three females at 10 p pm, and three males and three females at 100 ppm.

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Table 5-2. Incidences of forestomach lesions (hype rplasia or hyperkeratosis) in male and female B6C3F 1 

### mice administered AN via gavage for 2 years

Dose (mg/kg-d) a Lesion site and type 0 2.5 10 20
Males Forestomach hyperplasia or hyperkeratosis 2/50 (4%) 4/50

(8%) 10/50 a

(20%) 13/50 b

(26%)
Females Forestomach hyperplasia or hyperkeratosis 2/50 (4%) 2/50

(4%) 5/50

(10%) 8/50 a

(16%)

a Significantly elevated above vehicle control as det ermined by EPA using Fisher’s exact test ( p ≤ 0.05).
b Significantly elevated above vehicle control as det ermined by EPA using Fisher’s exact test ( p ≤ 0.01).

Source: NTP (2001).



### In B6C3F 1 

### mice, males exhibited statistically significantly elevated incidences of forestomach lesions (hyperplasia or hyperkeratosis) at the two highest doses administered (i.e., 10 and 20 mg/kg-day), while females showed statisti cally significantly elevated incidences of forestomach lesions at the highest dose only. While the Johannsen and Levinskas (2002b) drinking water study with F344 rats was selected as the principal study on which to base th e RfD, candidate RfDs were also developed from studies in Sprague-Dawley rats (Quast, 2002) a nd B6C3F 1 

### mice (NTP, 2001) for comparison purposes. The Johannsen and Levinskas ( 2002b) study was selected as the principal study primarily because it employed five doses of A N, ranging from 1 to 100 ppm, and thus tested a more complete range of doses, especially i n the low-dose region, than did either the Quast (2002) study in Sprague-Dawley rats or the NT P (2001) study in B6C3F 1 

### mice, which both employed three doses (i.e., 35, 100, and 300 p pm in rats and 2.5, 10, and 20 mg/kg-day in mice). In addition, Johannsen and Levinskas (2002b ) and Quast (2002) are both drinking water studies, which are preferred over the NTP (2001) ga vage study in B6C3F 1 

### mice because drinking water exposure is more relevant to humans. Finally , of these three studies 1 

### , the Johannsen and Levinskas (2002b) study identified the lowest LOAEL s based on an increased incidence of nonneoplastic stomach lesions (i.e., 0.3 mg/kg-day for males and 0.4 mg/kg-day for females). Therefore, hyperplasia or hyperkeratosis in F344 ra ts was selected as critical effect for derivation
of RfD.

1 Although SD male rats in the Johannsen and Levinska s (2002a) study exhibited the lowest LOAEL (0.1 mg/ kg-d) for all endpoints across all studies considered for RfD derivation (see Figure 5-1), this study experi enced significant mortality, especially in the high-dose groups, rend ering the results of this study highly suspect, and thus, it was deemed not suitable for RfD derivation.

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5.1.2. Methods of Analysis—Including Use of PBTK M odeling
Candidate RfDs for AN were derived from the incide nce of forestomach lesions in Sprague-Dawley rats, F344 rats, and B6C3F 1 

### mice using a BMD approach. Incidences of forestomach lesions from chronic drinking water stu dies in male and female Sprague-Dawley rats (Quast, 2002) and F344 rats (Johannsen and Lev inskas, 2002b) provided four sets of doseresponse data from which to derive candidate RfDs ( see Table 5-1), while incidences of forestomach lesions from a chronic gavage study in male and female B6C3F 1 

### mice provided an additional two sets of dose-response data (see Tabl e 5-2). The incidence data from rats in Table 5-1 were not combined across strains for purposes o f dose-response modeling because response
levels were different across the two strains. As d escribed further below, dose-response modeling of the incidence of forestomach lesions after 2 yea rs of AN exposure was carried out using BMD modeling. For rats, in addition to administered do se, two alternative internal dose metrics (AN in blood and CEO in blood), as estimated by PBTK mo deling, were employed in BMD modeling. In mice, only administered dose was empl oyed as a dose metric for BMD modeling

purposes.

5.1.2.1. PBTK Modeling In deriving candidate RfDs from the rat studies, in ternal dose metrics generated using PBTK models developed by EPA (see Section 3.5; Appe ndix C) based on the rat and human PBTK models of Kedderis et al. (1996) and Sweeney e t al. (2003), respectively, were employed. The EPA-modified PBTK models included many realisti c features, each of them leading to a different dose metric. The primary features of int erest were estimated daily average internal concentrations of AN or CEO in blood (area under th e curve [AUC] expressed on a 24-hour basis) and estimates based on continuous versus epi sodic exposure, with episodic exposure more realistically reflecting how rats (and humans) actu ally consume drinking water. As indicated above, two potentially useful chemical markers of internal exposure were selected (i.e., the concentration in blood of the p arent compound, AN, and its reactive metabolite, CEO). These two internal dose metrics were evaluat ed under an episodic exposure pattern because rats (and humans) consume drinking water in an episodic manner. In addition, for rats and mice, the externally administered AN dose was a lso used for deriving candidate RfDs for purposes of comparison with the candidate RfDs deri ved based on internal doses of AN and
CEO estimated from the PBTK model. For this assessment, internal dose metrics were eva luated for use in cross-species extrapolation from rats because of the following:

• The rat and human PBTK models incorporated species differences in physiological processes influencing the disposition of AN and CEO and were developed with rat in vivo toxicokinetic data, human in vitro metabolic d ata, and rat-to-human allometric

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scaling (Section 3.5; Appendix C; Sweeney et al., 2 003; Kedderis et al., 1996). As such, approaches using these models were expected to prov ide more accurate bases for extrapolation of dose-response relationships from r ats to humans than approaches based
on administered animal dose alone.

• For oral exposures, PBTK model predictions of AN or CEO concentrations in blood appear to provide a more accurate basis for extrapo lation than predictions based on
forestomach AN-AUC or forestomach CEO-AUC concentra tions because the stomach compartment in the PBTK model was not calibrated wi th measurements of AN or CEO in the stomach epithelium, the site of the forestomach lesions. Thus, more research is needed before a more physiologically meaningful sto mach compartment can be incorporated into the model. Blood AN concentratio ns predicted by the rat PBTK model were fairly close to measured AN concentrations in rats following oral exposure, but the model consistently predicted higher CEO concentrati ons in blood than was reported in studies of orally exposed rats (see Figure 3 in Ked deris et al., 1996).

Given the relative uncertainties in the PBTK predic tions noted above, especially for CEO, both internal dose metrics (AN and CEO in bloo d) were used in deriving candidate RfDs based on the rat data, in addition to administered dose. The concentration of AN administered in the bioassay, in terms of mg/kg-day, was used as in put into the EPA-modified rat PBTK model of Kedderis et al. (1996) in order to predict a rat internal dose (either AN-AUC or CEO-AUC concentration in blood) resulting from the ingestio n of the total daily administered dose of AN consumed in six bolus episodes per day. The result ing predicted AN-AUC or CEO-AUC
concentrations in rat blood are shown in Table 5-1 for male and female SD and F344 rats.

5.1.2.2. BMD Modeling
The incidences of forestomach lesions observed fol lowing 2 years of AN exposure in male and female SD and F344 rats were modeled using AN and CEO in blood, expressed in mg/L, as internal dose metrics. In addition, incid ences of these same lesions were modeled in male and female SD and F344 rats, as well as male a nd female B6C3F 1 

### mice, employing
administered dose. For B6C3F 1 

### mice, administered doses were multiplied by 5/7 to convert 5 day/week gavage exposures to 7 day/week continuous exposures. In all cases, all of the dichotomous dose-response models available in EPA’s BMD Software (BMDS, version 2.0) (i.e., the gamma, logistic, log-logistic, probit, l og-probit, multistage, Weibull, and quantal-linear models) were fit to these incidence data. Because the incidence of forestomach lesions in male and female F344 rats did not increase monotonically across all administered concentrations, however, only incidence data from the three lowest concentrations (i.e., 0, 1, and 3 ppm) were ultimately used in dose-response modeling. Althoug h the incidence of forestomach lesions did

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increase from 20 to 31% at 3 and 10 ppm, respective ly, in female F344 rats, this dose-response relationship could still not be adequately describe d by any of the existing dichotomous doseresponse models in BMDS, and thus, the 10 ppm dose group was dropped in females prior to modeling. For the same reason, the incidence data from the highest dose group in male SpragueDawley rats needed to be dropped prior to BMD model ing. In most cases, several models fit the data equally well (i.e., exhibited χ 2 

### goodness-of-fit

p values >0.1). Of those models exhibiting adequate fit, the selected model was the one with the lowest Akaike’s Information Criterion (AIC) value. BMDL 10 

### and BMDL 05 

### estimates were then
derived from this selected model. If more than one model shared the lowest AIC, the mean
BMDL 10 

### and BMDL 05 

### were calculated, as per the EPA’s Benchmark Dose Technical Guidance
Document

(U.S. EPA, 2000b). Appendix B-1 provides addition al details regarding the BMD modeling results used in the derivation of the RfD. Although BMDL 10 

### values were derived for comparison purposes, a ben chmark response (BMR) of 5% extra risk was selected as the point of departure (POD) for deriving the RfD based on both biological and statistical considerations. Biologically, the endpoint selected on which to base the RfD derivation (i.e., forestomach lesions —hyperplasia or hyperkeratosis) is considered severe. Although the severity of the hyperplasia o bserved was generally not reported, Johannsen and Levinskas (2002b) concluded that, “This [forest omach] lesion has been described as progressing from hyperplasia and hyperkeratosis to papilloma, and ultimately to carcinoma, following chronic oral exposure....” Statistical ly, the dose at 5% extra risk identifies a POD near the lower end of the observed data. Consequen tly, 5% extra risk appears to be a reasonable
choice for the POD for RfD derivation. For the two internal dose metrics selected (AN and CEO in blood), once the BMDL 10 

### and
BMDL 05 

### estimates (or their means) were derived from the s elected model(s), these estimates, expressed as rat internal AUCs (in mg/L), were then input into the EPA-modified human PBTK model of Sweeney et al. (2003) in order to predict the human equivalent administered dose of
AN that would result in a human 24-hour blood AN-AU C or CEO-AUC equivalent to the corresponding rat AUC, again assuming six bolus ing estion episodes per day. The resulting predicted 95% lower bounds on the human equivalent administered dose of AN, expressed in mg/kg-day, represent potential PODs for deriving ca ndidate RfDs. In the case of administered dose, the BMDL 10 

### and BMDL 05 

### estimates (or their means) are already expressed a s human equivalent doses (HEDs) in mg/kg-day, and are thus used directly as potential PODs for deriving
candidate RfDs. The BMDL 10 

### and BMDL 05 

### estimates and their corresponding PODs across the three dose metrics are presented in Tables 5-3, 5-4 , and 5-5 for Sprague-Dawley rats, F344 rats,
and B6C3F 1 

### mice, respectively.311DRAFT - DO NOT CITE OR QUOTETable 5-3. Candidate RfDs based on BMD modeling ofthe incidence of forestomach lesions (hyperplasiaorhyperkeratosis) in male and female Sprague-Dawley rats exposed to AN in drinking water for 2 yearsSex Endpoint Dose metric BMRaBMDLbPODc(mg/kg-d) UFCandidate RFDd(mg/kg-d)5% 0.72 mg/kg-d 0.72 1007.20×10-3Administereddose(mg/kg-d)10% 1.27 mg/kg-d 1.27 1001.27×10-25%4.32×10-3mg/L1.27 304.23×10-2Predicted AN inblood(mg/L)10%7.72×10-3mg/L2.17 307.23×10-25%3.90×10-4mg/L 3.86×10-2301.29×10-3MaleForestomachlesionsPredicted CEOin blood(mg/L)10%6.82×10-4mg/L 6.75×10-2302.25×10-35% 0.64 mg/kg-d 0.64 1006.39×10-3Administereddose(mg/kg-d)10% 1.24 mg/kg-d 1.24 1001.24×10-25%1.76×10-3mg/L 5.35×10-1301.78×10-2Predicted AN inblood(mg/L)10%3.62×10-3mg/L1.07 303.57×10-25%2.88×10-4mg/L 2.84×10-2309.48×10-4FemaleForestomachlesionsPredicted CEOin blood(mg/L)10%5.58×10-4mg/L 5.51×10-2301.84×10-3aBMR refers to the 95% lower confidence limit on theadministered or PBPK-predicted internal dose in the rat associated with a 5 or 10% extra risk for theincidence offorestomach lesions.bAll dichotomous models in EPA’s BMDS (version 2.0)were fit to the incidence of forestomach lesions (hyperplasia or hyperkeratosis) in Sprague-Dawley rats using thedata presented in Table 5-1. For BMD modeling, three different dose metrics were employed: (1) administered animal dose expressed in mg/kg-d, (2) AN inblood(predicted) expressed in mg/L, and (3) CEO in blood(predicted) expressed in mg/L. Adequate fit of amodel was achieved if theχ2goodness-of-fit statistic yielded ap-value>0.1. Of those models exhibiting adequate fit, theselected model was the model with the lowest AIC value. BMDL10and BMDL05estimates were derived fromthe selected model. If more than one model sharedthe lowest AIC, the mean BMDL10and BMDL05were calculated and are presented, as per the EPA’sBenchmarkDose Technical Guidance Document(U.S. EPA, 2000b). Appendix B-1 provides additional details regarding these BMD modeling results.cFor administered dose, the POD is the BMDL05or BMDL10based on BMD modeling using administered animal dose as the dose metric. For the internal dose metrics(AN and CEO in blood), the PODs are PBPK model-derived human equivalent administered doses of AN thatwould result in a human 24-hr blood AN-AUC or CEOAUC equivalent to the corresponding rat BMDL05or BMDL10values, assuming AN ingestion in six bolus episodes/d.dRfD = POD/UF.Sources: Quast (2002); Quast et al. (1980a).312DRAFT - DO NOT CITE OR QUOTETable 5-4. Candidate RfDs based on BMD modeling ofthe incidence of forestomach lesions (hyperplasiaorhyperkeratosis) in male and female F344 rats exposed to AN in drinking water for 2 yearsSex Endpoint Dose metric BMRaBMDLbPODc(mg/kg-d) UFCandidate RFDd(mg/kg-d)5%9.97×10-2mg/kg-d 9.97×10-21009.97×10-4Administereddose(mg/kg-d)10% 0.151 mg/kg-d 0.151 1001.51×10-35%5.39×10-4mg/L 1.66×10-1305.55×10-3Predicted AN inblood(mg/L)10%8.14×10-4mg/L 2.50×10-1308.35×10-35%5.06×10-5mg/L 5.00×10-3301.67×10-4MaleForestomachlesionsPredicted CEOin blood(mg/L)10%7.65×10-5mg/L 7.56×10-3302.52×10-45% 0.117 mg/kg-d 0.117 1001.17×10-3Administereddose(mg/kg-d)10% 0.209 mg/kg-d 0.209 1002.09×10-35%5.58×10-4mg/L 1.72×10-1305.74×10-3Predicted AN inblood(mg/L)10%9.97×10-4mg/L 3.06×10-1301.02×10-25%5.17×10-5mg/L 5.11×10-3301.70×10-4FemaleForestomachlesionsPredicted CEOin blood(mg/L)10%9.23×10-5mg/L 9.12×10-3303.04×10-4aBMR refers to the 95% lower confidence limit on theadministered or PBPK-predicted internal dose in the rat associated with a 5 or 10% extra risk for theincidence offorestomach lesions.bAll dichotomous models in EPA’s BMDS (version 2.0)were fit to the incidence of forestomach lesions (hyperplasia or hyperkeratosis) in F344 rats using the datapresented in Table 5-1. For BMD modeling, three different dose metrics were employed: (1) administered animal dose expressed in mg/kg-d, (2) AN in blood(predicted) expressed in mg/L, and (3) CEO in blood(predicted) expressed in mg/L. Adequate fit of amodel was achieved if theχ2goodness-of-fit statistic yielded ap-value>0.1. Of those models exhibiting adequate fit, theselected model was the model with the lowest AIC value. BMDL10and BMDL05estimates were derived fromthe selected model. If more than one model sharedthe lowest AIC, the mean BMDL10and BMDL05were calculated and are presented, as per the EPA’sBenchmarkDose Technical Guidance Document(U.S. EPA, 2000b). Appendix B-1 provides additional details regarding these BMD modeling results.cFor administered dose, the POD is the BMDL05or BMDL10based on BMD modeling using administered animal dose as the dose metric. For the internal dose metrics(AN and CEO in blood), the PODs are PBPK model-derived human equivalent administered doses of AN thatwould result in a human 24-hr blood AN-AUC or CEOAUC equivalent to the corresponding rat BMDL05or BMDL10values, assuming AN ingestion in six bolus episodes/d.dRfD = POD/UF.Sources: Johannsen and Levinskas (2002b); Biodynamics (1980c).313DRAFT - DO NOT CITE OR QUOTETable 5-5. Candidate RfDs based on BMD modeling ofthe incidence of forestomach lesions (hyperplasiaorhyperkeratosis) in male and female B6C3F1mice exposed to AN via gavage for 2 yearsSex Endpoint Dose metric BMRaBMDLb(mg/kg-d)PODc(mg/kg-d) UFCandidate RfDd(mg/kg-d)5% 1.43 1.43 1001.43×10-2MaleForestomachlesionsAdministereddose(mg/kg-d)10% 3.01 3.01 1003.01×10-25% 3.02 3.02 1003.02×10-2FemaleForestomachlesionsAdministereddose(mg/kg-d)10% 6.20 6.20 1006.20×10-2aBMR refers to the 95% lower confidence limit on theadministered dose in the mouse associated with either a 5 or 10% extra risk for the incidence of forestomachlesions.bAll dichotomous models in EPA’s BMDS (version 2.0)were fit to the incidence of forestomach lesions (hyperplasia or hyperkeratosis) in B6C3F1mice using the datapresented in Table 5-2. For BMD modeling, administered animal dose, expressed in mg/kg-d, was employed. Adequate fit of a model was achieved if theχ2goodnessof-fit statistic yielded ap-value>0.1. Of those models exhibiting adequate fit, theselected model was the model with the lowest AIC value. BMDL10and BMDL05estimates were derived from the selected model. Ifmore than one model shared the lowest AIC, the mean BMDL10and BMDL05were calculated and are presented, asper the EPA’sBenchmark Dose Technical Guidance Document(U.S. EPA, 2000b). Appendix B-1 provides additional details regarding these BMD modeling results.cThe POD is the BMDL05or BMDL10based on BMD modeling using administered animal dose as the dose metric. No internal dose metrics were employed for micebecause of the absence of a PBPK model for this species.dRfD = POD/UF.Source: NTP (2001).

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5.1.3. RfD Derivation—Including Application of Unc ertainty Factors (UFs) In Tables 5-3 and 5-4, the candidate PODs based on the internal dose metrics (i.e., CEOAUC in blood and AN-AUC in blood) were divided by a composite UF of 30 to account for two areas of uncertainty. An UF of 3 (i.e., 10 0.5 

### ) was used to account for uncertainty associated wi th extrapolating from rats to humans. A factor of 3 w as chosen instead of the default value of 10, because toxicokinetic uncertainty was decreased by the application of the rat and human PBTK models. The applied factor of 3 was selected to ac count for any remaining toxicokinetic uncertainties in the dosimetric extrapolation, and possible differences in the response of rat and human target tissues to AN or its metabolites (i.e. , toxicodynamic differences). A default UF of 10 was then used to account for uncertainty associa ted with extrapolation to individuals or groups within the human population who may be espec ially sensitive or susceptible to the noncancer toxicity of AN.
The candidate PODs based on administered dose in Ta bles 5-3, 5-4, and 5-5 were divided by a composite UF of 100 to again account for two a reas of uncertainty. First, a UF of 10 was used to account for uncertainty associated with ext rapolating from rats to humans because no PBTK model was employed, and thus, a default factor of 10 was needed to account for both toxicokinetic and toxicodynamic uncertainties. Sec ondly, as above, a default UF of 10 was used to account for uncertainty associated with extrapol ation to individuals or groups within the human population who may be especially sensitive or susceptible to the noncancer toxicity of AN. Considerations in selecting individual UFs are discussed in greater detail below.
A default UF of 10 was used to account for uncerta inty associated with extrapolation to individuals or groups within the human population w ho may be especially sensitive or susceptible to the noncancer toxicity of AN. As di scussed in Section 4.8, available data on AN are inadequate to reliably identify populations tha t may be especially susceptible to the noncancer toxicity of AN. There is one human case report indicating that children are more susceptible to AN toxicity. These data at least su ggest that juvenile populations may be especially susceptible to the noncancerous effects of AN exposure. An UF to account for extrapolation from subchronic to chronic exposure was not necessary because of the availability of chronic or al studies in both rats and mice. An UF to account for LOAEL to NOAEL extrapolation w as not applied because the BMR selected for BMD modeling, a 5% extra risk of f orestomach lesions, was judged to have minimal biological significance. A database deficiency UF was not used in the devel opment of the RfD. Although studies of health effects in humans exposed to AN by the or al route are not available, the animal oral toxicity database is particularly robust. As discu ssed in Section 4.6.1, there are nine rat toxicity and cancer bioassays, one toxicity and cancer bioas say with B6C3F 1 

### mice, a three-generation (46-week) developmental/reproductive rat toxicity s tudy with Sprague-Dawley rats, a 12-week gavage study of nerve conduction velocities in male Sprague-Dawley rats, a 14-week gavage

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toxicity bioassay in B6C3F 1 

### mice, a developmental toxicity study in Sprague-Da wley rats exposed by gavage during GDs 6–15, and a 90-day stu dy of oxidative stress indicators in the
brain and liver of F344 rats. These animal data id entify forestomach lesions as the most sensitive, prevalent, and consistent noncancer effe ct in animals associated with repeated oral exposure to AN, and thus provide evidence that an R fD based on this effect will be protective for other potential noncancer effects, including neurol ogical, reproductive, and developmental effects. In addition, the data for forestomach les ions in rats and mice provide an adequate characterization of the dose-response relationship for the development of these lesions with chronic exposure, which, coupled with the applicati on of the PBTK models for cross-species dosimetric extrapolation, adds to the confidence in the estimation of a chronic oral human dose expected to be without risk in the general populati on for the development of gastric lesions. For the purpose of this assessment, CEO-AUC in bloo d is considered to be the most appropriate dose metric to use in deriving an RfD. CEO is believed to be the reactive metabolite most likely responsible for the noncancer (and canc er) effects observed following AN exposure. Results from acute exposure studies in rats indicat e that CEO plays a key role in the mode of action by which AN elicits stomach lesions. Resear ch has shown that pretreatment with inhibitors of CYP2E1 inhibited the development of G I ulceration, following acute exposure of rats to AN, and doses of KCN equivalent to toxic do ses of AN did not induce GI bleeding in a similar manner to AN (Ghanayem et al., 1985; Ghanay em and Ahmed, 1983). For oral exposures, then, the use of CEO-AUC as the internal dose metric for cross-species extrapolation is recommended. Therefore, while the PBTK model do es not predict CEO in blood as accurately as it predicts AN in blood, CEO in blood provides t he most biologically relevant dose metric for modeling the incidence of forestomach lesions and f or extrapolating from orally exposed rats to
humans. In comparing the candidate RfDs for the preferred d ose metric of predicted CEO in blood across Tables 5-3 and 5-4, the candidate RfDs based on the forestomach lesion incidence data in F344 rats are about an order of magnitude lower tha n those candidate RfDs based on forestomach lesion incidence data in Sprague-Dawley rats. This comparison confirms what had previously been predicted (i.e., F344 rats are more sensitive to AN exposure than SpragueDawley rats). Moreover, these same candidate RfDs in F344 rats are approximately two orders of magnitude lower than the candidate RfDs based on administered dose in B6C3F 1 

### mice. Therefore, for the critical endpoint (i.e., foresto mach lesions), F344 rats are the most sensitive species and strain. Consequently, the RfD is 2 × 10 -4 

### mg/kg-day. This RfD is consistent with the candidate RfDs derived for both male (1.67 × 10 -4 

### mg/kg-day) and female (1.70 × 10 -4 

### mg/kg-day) F344 rats using predicted CEO in blood a s the dose metric and based on the incidence of forestomach lesions following chronic oral exposure to AN.

5.1.4. Oral Data Array for Noncancer Endpoints

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LOAELs based on selected animal studies presented i n Table 4-56 are arrayed for comparison in Figure 5-1, and provide a perspective on the RfD developed in the previous section from data in F344 rats (Johannsen and Levin skas, 2002b). Figure 5-1 should be interpreted with caution, however, because the LOAE Ls across studies are not necessarily comparable due to the lack of any indication regard ing the confidence in the data sets from which the LOAELs were derived. In addition, the na ture, severity, and incidence of effects at a LOAEL are also likely to vary. For example, the in cidence of forestomach squamous cell hyperplasia in male and female F344 rats at the LOA EL were both 17% (see Figure 5-1), while in Sprague-Dawley rats, the incidence of the same l esions at the LOAEL in males and females were 73 and 23%, respectively. Figure 5-1 provides a graphical comparison of organ-specific LOAELs from chronic studies in experimental animals . The predominant noncancer effect of chronic oral exposure to AN is hyperplasia and hype rkeratosis of squamous cell epithelial tissue in the forestomach. The LOAELs for this endpoint a re lower than those observed for chronic nephropathy, gliosis, ovarian cysts, or development al effects. Therefore, the RfD based on hyperplasia and hyperkeratosis of squamous cell epi thelial tissue in the forestomach should be protective of other effects resulting from oral ex posure to AN.317 DRAFT - DO NOT CITE OR QUOTEFigure 5-1. Comparison of LOAELs for noncancer effects across target organs following oral exposure to AN in animals.0.30.48.54.40.110.77.114.33.410.81.84.402468101214161820Squamouscellhyperplasiain F344 malerats[Johannsen& Levinskas,2002b]Squamouscellhyperplasiain F344female rats[Johannsen& Levinskas,2002b]Squamouscellhyperplasiain SD malerats [Quast,2002]Squamouscellhyperplasiain SD femalerats [Quast,2002]Squamouscellhyperplasiain SD malerats[Johannsen& Levinskas,2002a]Squamouscellhyperplasiain SD femalerats[Johannsen& Levinskas,2002a]Squamouscellhyperplasiain B6C3F1male mice[NTP, 2001]Squamouscellhyperplasiain B6C3F1female mice[NTP, 2001]Chronicnephropathy(severe) inSD male rats[Quast, 2002]Chronicnephropathy(minimal) inSD femalerats [Quast,2002]Ovariancysts inB6C3F1female mice[NTP, 2001]Gliosis in thebrain of SDfemale rats[Quast, 2002]Target Organ Effects

Acrylonitrile Dose (mg/kg-day)[73%][23%][18%][10%][10%][14%][31%][16%][14%][5%][17%] [17%][ ] = Percent of animals with effects atthe LOAEL (corrected for background)

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5.1.5. Previous RfD Assessment No RfD was derived in the previous IRIS assessment of AN.

5.2. INHALATION RfC 5.2.1. Choice of Principal Study and Critical Effe ct As discussed in Section 4.1.2, results from severa l cross-sectional health examinations and surveys of AN-exposed workers (Chen et al., 200 0; Kaneko and Omae, 1992; Muto et al., 1992; Sakurai et al., 1978) and a study of the perf ormance on a battery of neurobehavioral tests by exposed workers (Lu et al., 2005a) identified in creased prevalence of subjective neurological symptoms (e.g., headache, poor memory, and irritabi lity) and small performance deficits in
neurobehavioral tests as the critical effects from chronic occupational inhalation exposure to AN. An increased prevalence of subjective symptoms was associated with average workplace air concentrations of 1.13 ppm (Muto et al., 1992), 1.8 ppm (Kaneko and Omae, 1992), and 0.48 ppm (Chen et al., 2000). Deficits in the neur obehavioral tests were associated with average workplace air concentrations of 0.11 ppm for a grou p of workers designated as monomer workers and 0.91 ppm for a group of workers designa ted as fiber workers (Lu et al., 2005a). Cross-sectional epidemiologic surveys of reproduct ive outcomes in AN-exposed workers found increased prevalence of adverse reproductive outcomes associated with somewhat higher average workplace air concentrations of 3.7 ppm (Do ng and Pan, 1995), 3.6 ppm (Dong et al., 2000a), and 7.5 ppm (Li, 2000). Adverse outcomes w ith statistically significantly increased prevalence compared with unexposed workers included the following:

• Premature deliveries —10.7% in unexposed wives of exposed males vs. 3.5% in controls (implying the sperm of exposed males may b e affected) (Dong and Pan, 1995); 8.2% in exposed females vs. 3.9% in controls (Dong et al., 2000b); and 11.6% in exposed females vs. 4.7% in controls (Li, 2000)

• Stillbirths —4.5% in exposed females vs. 0% in controls (Dong a nd Pan, 1995); 2.7% in exposed females vs. 0% in controls (Dong et al., 2000b)

• Sterility —5.0% in wives of exposed males vs. 1.8% in wives o f controls (Dong and Pan, 1995); 2.6% in exposed females vs. 0.8% in con trols (Li, 2000)

• Birth defects —21.3% in exposed females vs. 4.8% in controls (Don g et al., 2000b); 25.4% in exposed females vs. 4.2% in controls (Li, 2000)

• Pregnancy complications —20.8% in exposed females vs. 7.1% in controls (Li, 2000)

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Exposure levels associated with adverse effects in the available animal inhalation toxicity studies were higher than the workplace air concentr ations associated with adverse effects in AN-exposed workers (see Table 4-57). With repeated inhalation exposure to AN, effects noted with the lowest exposure levels were as follows:

• Increased incidence of nasal epithelial lesions in Sprague-Dawley rats exposed for 2 years to 20 ppm AN (Quast et al., 1980b)

• Deficits in sensory nerve conduction in the tail ne rve of Sprague-Dawley rats exposed for
12 weeks to AN concentrations ≥ 50 ppm, but not 25 ppm (Gagnaire et al., 1998)

• Increased incidence of litters with short tail, sho rt trunk, missing vertebrae, or anteriorly displaced ovaries (combined) in Sprague-Dawley rats exposed to AN concentrations of 80 ppm, but not 40 ppm, on GDs 6–15 (Murray et al., 1978)

• Decreased fetal weight gain per litter in Sprague-D awley rats exposed to AN
concentrations ≥ 25 ppm, but not to 12 ppm, on GDs 6–20 (Saillenfait et al., 1993)

The cross-sectional study of neurobehavioral perfo rmance in acrylic fiber workers by Lu et al. (2005a) was selected as the principal study for deriving the RfC because it is the best available study that identified neurobehavioral eff ects in workers exposed to AN. Previous occupational studies by Kaneko and Omae (1992) and Muto et al. (1992) reported subjective neurological symptoms (e.g., poor memory and irrita bility) in exposed workers. Lu et al. (2005a) utilized the WHO-recommended NCTB administe red by trained physicians to evaluate these neurobehavioral effects systematically. Henc e, the results were more reliable when compared with those based on self reporting. In ad dition, neurobehavioral effects were also reported in AN-treated rats (Rongzhu et al., 2007; Ghanayem et al. 1991). Confounding by other workplace exposures is not considered likely. The distribution of employment duration for the mon omer workers was 1–10 years, 23%; 11–20 years, 42%; and >20 years, 35%. For fiber wo rkers, the distribution was 1–10 years, 47%; 11–20 years, 23%; and >20 years, 30%. Geometr ic mean workplace AN air concentrations were 0.11 ppm for the monomer operations areas (ran ge 0–1.70 ppm based on 390 stationary air samples collected between 1997 and 1999) and 0.91 p pm for the acrylic fiber operations areas (range 0.00–8.34 ppm based on 570 samples). For mo nomer workers, the following statistically significant deficits, compared with unexposed contr ols, were measured:

• 41–68% higher scores for negative moods (i.e., ange r, confusion, depression, fatigue, and tension) in the Profile of Mood States Test.

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• 16% longer times in the Simple Reaction Time Test o f attention and visual response speed.

• 21% lower scores in the backward sequence of the Di git Span Test of auditory memory.

• 4% lower scores in the Benton Visual Retention Test , a measure of visual perception and

memory.

• 14% lower scores in the Pursuit Aiming II Test, a m easure of motor steadiness.

Statistically significant deficits were not found in the Santa Ana Test for manual dexterity or in the Digital Symbol Test for perceptual motor speed. Fiber workers showed deficits of a similar magnitude in many of the same tests (20–44% higher in Profile of Mood States Test, 10% longer in the Simple Reaction Time Test, 24% lo wer score in the backward sequence of the Digit Span Test, 4% lower scores in the Benton Visu al Retention Test, and 10% lower scores in the Pursuit Aiming II Test), with the exception tha t scores in the forward sequence of the Digit Span Test were significantly better than those of u nexposed workers. Lu et al. (2005a) reported that air in these workp laces also presented potential exposures to cyanide in the monomer operations areas and meth yl methacrylate in the fiber areas, but measurements of these chemicals in air samples were not made. Cyanide is a breakdown product of AN. Its concentration in the monomer plant shou ld be low compared with AN. Methyl methacrylate was generally used as a minor componen t in the production of acrylic fiber. With an RfC of 0.7 mg/m 3 

### (U.S. EPA, 1998b), its toxicity is much lower than that for AN. Therefore, potential exposure to these confounders was determi ned to be an insufficient limitation to preclude using Lu et al. (2005a) to identify neurol ogical effects as potential health hazards from occupational exposure to AN and derive an RfC for c hronic inhalation exposure to AN. Both groups of workers showed deficits, despite being ex posed to different potentially confounding chemicals, and the results from this study are cons istent with the increased prevalence of subjective symptoms in other studies of AN-exposed workers.
An RfC based on the results from the chronic inhal ation bioassay with Sprague-Dawley rats (Quast et al., 1980b) was also derived for com parison purposes. As discussed in Section 4.6.2, statistically significant increased incidence of inflammatory and degenerative nasal lesions (i.e., hyperplasia of mucus-secreting cells in males and flattening of respiratory epithelium in females) occurred in rats exposed to the lowest level of AN in this two-year bioassay, 20 ppm (6 hours/day, 5 days/week), and re present the critical effects in animals exposed to AN chronically by inhalation. At the hi gher exposure level, 80 ppm, other nasal lesions with elevated incidences were suppurative r hinitis and focal erosion of the mucous lining

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in females and hyperplasia of respiratory epitheliu m in males and females. Other lesions with elevated incidences at the 80 ppm exposure level we re gliosis and perivascular cuffing in the brain of males and females, focal nephrosis and thy roid cysts in males, and hepatic necrosis in females (which was also elevated at 20 ppm).

5.2.2. Methods of Analysis A NOAEL/LOAEL approach to the human data was used to derive the RfC. The performance deficits measured in monomer and fiber workers were judged to be adverse and the geometric mean of the range of air concentrations m easured for the monomer work areas, 0.11 ppm (0.24 mg/m 3 

### ), was selected as the POD for deriving the RfC. For the animal data, a BMD approach was used. Dos e-response models available in EPA’s BMDS (version 1.3.2) were fit to incidence da ta for flattening of the respiratory epithelium in female rats and hyperplasia of mucus- secreting cells in male rats. Prior to modeling, animal exposure data were converted to hu man equivalent concentrations (HECs) using U.S. EPA (1994) methods for extrathoracic res piratory effects from a category 1 gas (Table 5-6). A BMR of 10% extra risk was selected as the POD for deriving the RfC based on both biological and statistical considerations. Bi ologically, the endpoints selected on which to derive the RfC (i.e., flattening of the respiratory epithelium in female rats and hyperplasia of mucus-secreting cells in male rats) are relatively benign. Statistically, the dose at 10% extra risk
identifies a POD near the lower end of the data ran ge. Thus, a BMR of 10% extra risk was selected for this analysis consistent with the U.S. EPA (. Benchmark concentrations (BMCs) and the 95% lower bounds on the BMCs (BMCL 10 

### s) for the best-fitting models are shown in Table 5

- 6. Potential PODs for the animal-based RfC are the BMCL 10 

### s of 0.082 and 0.059 mg/m 3 

### for nasal effects in male and female rats, respectively . More detailed information on these BMD modeling results is presented in Appendix B-2.

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Table 5-6. Results of dose-response analyses of in cidence data for selected nasal lesions in male and female Sprague-Dawley rat s exposed by inhalation to AN for 2 years

Nasal lesion Administered

concentration (mg/m 3 ) HEC

(mg/m 3 ) a Lesion

incidence BMC 10

(mg/m 3 ) b BMCL 10

(mg/m 3 ) b Candidate

RfC (mg/m 3 ) c 0 0 0/11 (0%) 43.4 2.1 7/12 (58%) dHyperplasia of mucussecreting cells in males
173.6 8.5 8/10 (80%) d 0.187 0.082 3 × 10 -3

0 0 1/11 (9.1%) 43.4 2.1 7/10 (70%) d Flattening of respiratory epithelium in females
173.6 8.5 8/10 (80%) d 0.162 0.059 2 × 10 -3

a HEC as per U.S. EPA (1994) methods for a category 1 gas producing an upper respiratory effect. Sample calculation: 43.4 mg/m 3 × 6h/24h × 5d/7d × RGDR ET = 2.1 mg/m 3 , where RGDR ET = 0.275 = [VE/SA ET ] rat ÷ [VE/SA ET ] human; VE = minute volume = 0.281 L/min rat, 13.8 L/min human; SA ET = extrathoracic surface area = 15 cm 2 rat, 200 cm 2 human.
b BMC 10 and BMCL 10 refer to the BMD model-predicted air concentration and its 95% lower confidence limit, associated with a 10% extra risk for having nonneop lastic nasal lesions. BMC 10 s and BMCL 10 s are estimated from the best-fitting model among those fit to the data. More detailed information on the BMD modeling res ults is presented in Appendix B-2.

c RfC = BMCL 10 /UF, where the UF is 30.
d Statistically significantly different from control value as reported by Quast et al., 1980b.

Source: Quast et al. (1980b).



### 5.2.3. RfC Derivation—Including Application of UFs The LOAEL of 0.11 ppm (0.24 mg/m 3 

### ) from Lu et al. (2005a) for statistically signific ant performance deficits in neurobehavioral tests of mo od, attention and speed, auditory memory, visual perception and memory, and motor steadiness in humans occupationally exposed to AN
via inhalation was used for derivation of the RfC. Since the LOAEL was from an occupational study, the adjusted LOAEL for continuous exposure w as obtained by multiplying the study LOAEL by a factor of 0.36 (5 days/7 days × 10 m 3 

### /day ÷ 20 m 3 

### /day). This adjusted LOAEL (LOAEL ADJ 

### ) of 0.03 ppm (0.086 mg/m 3 

### ) was divided by a composite UF of 100 to arrive at an RfC of 9 × 10 -4 

### mg/m 3 

### . This two-step calculation is illustrated below:

1. LOAEL ADJ 

### = 0.24 mg/m 3 

### × 0.36 = 0.086 mg/m 3



### 2. RfC = 0.086 mg/m 3 

### ÷ 100 = 0.00086 mg/m 3 

### or 0.9 μ g/m 3



### An UF of 10 was used for extrapolating from a LOAE L to a NOAEL. The RfC is derived from an occupational study. A default UF o f 10 was used to account for sensitive or susceptible members of the general population, incl uding children. A database UF was not

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applied since the database for AN is robust, and oc cupational exposure studies exist that evaluated reproductive effects in AN-exposed worker s. Comparative animal-based RfCs of 3 × 10 -3 

### mg/m 3 

### (or 3 μ g/m 3 

### ) and 2 × 10 -3 

### mg/m 3 

### (or
2 μ g/m 3 

### ) were derived by dividing the BMDL 10 

### s of 0.082 mg/m 3 

### and 0.059 mg/m 3 

### for nasal lesions in male and female rats, respectively, by U Fs of 30 (3 for extrapolating from rats to humans using the default U.S. EPA [1994] dosimetric adjustment and 10 to protect sensitive subpopulations). These candidate RfCs are displaye d in Table 5-6. Extrapolating the results from animal toxicity studies to derive an RfC has i nherently greater uncertainty than using the
results from the cross-sectional studies of health effects in human workers; however, the humanbased and animal-based RfCs differ by about twofold . For this assessment, the human-based
RfC of 9 × 10 -4 

### mg/m 3 

### or 0.9 μ g/m 3 

### is the recommended value.

5.2.4. Inhalation Data Array for Noncancer Endpoin ts
LOAELs based on selected studies included in Table 4-57 are arrayed in Figure 5-2 and provide perspective on the RfC derived from Lu et a l. (2005a). Figure 5-2 should be interpreted
with caution because the LOAELs across studies are not necessarily comparable, due to inherent limitations in NOAEL/LOAEL determination (U.S. EPA, 2000b), nor is the confidence in the
data sets from which the LOAELs were derived the sa me. The nature, severity, and incidence of effects occurring at a LOAEL are likely to vary. T he text in Section 5.2.1 should be consulted for a more complete understanding of the issues ass ociated with each data set and the rationale for the selection of the critical effect and princi pal study used to derive the RfC. The most sensitive endpoint is the neurobehavioral effects i dentified in Lu et al. (2005a) and this endpoint provides the basis for the derivation of the RfC.324 DRAFT - DO NOT CITE OR QUOTE1.81.10.50.10.43.73.67.5012345678910SubjectiveSymptoms in Males[Kaneko & Omae,1992]SubjectiveSymptoms in Males[Muto et al., 1992]SubjectiveSymptoms in Malesand Females[Chen et al., 2000]NeurobehavioralDeficits in Malesand Females[Lu et al., 2005a]Decrease in SpermDensity andNumber and SexChromosomeAneuploidy in Males[Xu et al., 2003]AdverseReproductiveOutcomes in Malesand Females[Dong & Pan, 1995]AdverseReproductiveOutcomes in Malesand Females[Dong et al., 2000b]AdverseReproductiveOutcomes inFemales[Li et al., 2000]Observed Effects

Acrylonitrile Exposure (ppm in air)Figure 5-2. Comparison of LOAELs for noncancer effects in human workers following inhalationexposure to AN.

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5.2.5. Previous Inhalation Assessment Previously, EPA derived an RfC of 2 × 10 -3 

### mg/m 3 

### from the low exposure level (i.e., 20 ppm AN, duration-adjusted to a LOAEL HEC 

### of 1.9 mg/m 3 

### ) in the Quast et al. (1980b) animal study, which was identified as a LOAEL for the onse t of hyperplasia of the mucus-secreting
cells. The LOAEL HEC 

### was adjusted with a combined UF of 1,000 to derive the RfC. This composite UF was made up of 10 for intraspecies var iability; 3 for interspecies variability, where dosimetric adjustments had already been applied to account for part of this area of uncertainty; 3 for extrapolation from a minimally adverse LOAEL to a NOAEL; and 10 for database deficiencies. The latter UF was applied because of the lack of an inhalation bioassay in a second species and the absence of reproductive data by the inhalation route where an oral study existed that showed reproductive effects. New pertinent information, available since the pre vious RfC was developed, includes: (1) several cross-sectional health examinations and surveys of subjective symptoms and reproductive outcomes in AN-exposed workers; (2) a published cross-sectional study of performance in a battery of neurobehavioral tests b y AN-exposed workers (Lu et al., 2005a) (the principal study for the current RfC); (3) toxicokin etic information and the development of PBTK models for AN; and (4) two inhalation developmental toxicity studies in rats.
5.3. UNCERTAINTIES IN THE ORAL RfD AND INHALATION RfC The following discussion identifies uncertainties a ssociated with the RfD or RfC for AN. As presented earlier in this chapter (Sections 5.1. 2 and 5.1.3; and 5.2.2 and 5.2.3), the UF approach, following EPA methodology for RfC and RfD development (U.S. EPA, 2002, 1994), was applied to a POD. For the RfD, the POD was det ermined as BMDL 05 

### of internal dose estimated from rats and subsequently converted to a HED. For the RfC, a LOAEL was derived from an epidemiologic study for neurobehavioral eff ects. Factors accounting for uncertainties associated with a number of steps in the analyses w ere adopted to account for extrapolating from the POD, the starting point in the analysis, to a n o-adverse-effect level (LOAEL to NOAEL) given insufficient data in the principal study for BMD modeling, to a diverse population of varying susceptibilities. These extrapolations are carried out with default approaches instead of data on AN, given the paucity of experimental AN da ta to inform individual steps.

Selection of principal study and critical effect fo r reference value determination Hyperplasia and hyperkeratosis of squamous epitheli um of the forestomach was selected
as the critical effect for RfD. This effect is the most prevalent, consistent, and most sensitive effect in rats and mice. Since GI bleeding occurs after s.c. injection of AN in rats, this effect is probably not due to local irritation on gastric tis sues, but is likely due to binding of CEO to GI mucosa. Although humans do not possess a forestoma ch, humans do have comparable squamous cell epithelial tissues in their oral cavi ty and the upper two-thirds of their esophagus (IARC, 1999). Thus, there is little uncertainty th at this effect is relevant to humans.

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For derivation of the RfC, both a 2-year rat inhal ation study and epidemiologic studies are available. To reduce uncertainty in extrapolat ing from animals to humans, epidemiologic studies are preferred. Several earlier cross-secti onal health surveys of AN-exposed workers reported subjective neurological symptoms. In addi tion, adverse reproductive outcomes were also found in cross-sectional epidemiologic surveys of AN-exposed workers in China. Neurobehavioral effects of AN-exposed workers were selected as the critical effect since this effect was observed from several occupational studi es with workers chronically exposed to AN
via the inhalation route. Lu et al. (2005a) mentioned several limitations of this study. One was that the cited exposure data represented estimates of previous exp osure levels and no contemporaneous personal monitoring data were available. Furthermo re, as the NCTB was developed for populations in Europe and North America, it is not known to what extent cultural differences may have affected results of the Profile of Mood St ates Test, shown to be sensitive to cultural differences. In addition, the study authors could not rule out the possibility that examiner drift may have affected the results. Selection bias amon g volunteers in different groups was mentioned as a possible confounding effect, but was discounted on the basis that the participation among exposed workers was so high. M oreover, the largest measures of neurobehavioral effects occurred in the acrylic fib er workers, who had lower average AN exposure levels.

Animal to human extrapolation No human oral exposure studies are available for de rivation of the RfD. For derivation of the RfD, extrapolating dose-response data from anim als to humans is a source of uncertainty. A PBTK model, which has its own associated uncertaint ies, was used to address toxicokinetic
differences between animals and humans. Uncertaint ies of the PBTK model are discussed as part of the overall uncertainty discussion (Section 5.4.4.5), with quantitative details given in Appendix D. Residual uncertainties pertaining to u nknown interspecies differences in pharmacodynamics were addressed by application of a UF of 3. A human occupational exposure study (Lu et al., 20 05a) was used for derivation of the RfC, eliminating uncertainty associated with extrap olation from animals to humans. An RfC was also derived from a two-year inhalation study o f rats based on increased incidence of inflammatory and degenerative nasal lesions. This alternative RfC was, at most, threefold higher than the RfC derived from Lu et al. (2005a).

Dose-response modeling BMD modeling was used to estimate the POD for the R fD. While models with better biological support may exist, the selected models p rovided adequate mathematical fits to the experimental data sets. BMD modeling has advantage s over a POD based on a NOAEL or

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LOAEL because NOAELs/LOAELs are a reflection of the particular exposure concentration or dose at which a study was conducted, they do not ma ke use of the dose-response curve, and they do not address the variability of the study populat ion. NOAELs and LOAELs also are less amenable to quantitative uncertainty analysis.
The RfC was based on a LOAEL identified from an occ upational epidemiology study. As stated above, there are several reasons to prefe r a POD obtained from BMD modeling. However, the available data only supported a LOAEL. A UF to address extrapolation to a less adverse response level was applied.

Intrahuman variability Heterogeneity among humans is another source of unc ertainty. Uncertainty related to human variation needs consideration, also, in extra polation from a small subset of presumably healthy humans (i.e., workers) to a larger, more di verse general population. Available data from animal studies provide no evidence of gender differ ences in susceptibility to toxicity of AN, although no data are available regarding possible g ender differences in susceptibility. Human genetic polymorphisms in CYP2E1 activities likely c ontribute to variability in human susceptibility to the toxic effects of AN (see Sect ion 4.8.4.1). A UF of 10 was used to account for intrahuman variability for derivation of RfD an d RfC. A factor of 10 has been found to be generally sufficient to account for human variabili ty in response to chemical exposure (Renwick and Lazarus, 1998).

5.4. CANCER ASSESSMENT 5.4.1. Choice of Study/Data—with Rationale and Jus tification As previously discussed in Section 4.1.2.2, evidenc e of a possible association between exposure to AN and cancer in humans has been found in some studies. The best available occupational epidemiologic study (Blair et al., 199 8) reported that workers exposed to AN via inhalation in the highest cumulative exposure categ ory (i.e., >8 ppm-years) with more than 20 years of employment displayed a twofold increase d risk of death from lung cancer compared with unexposed workers (RR = 2.1, 95% CI = 1.2–3.8) . To date, Blair et al. (1998) is largest cohort study to assess the relationship between AN and cancer, following 25,460 workers in eight AN-producing facilities, with two-thirds of t his cohort having a follow-up period of over 20 years. The large sample size and the duration o f follow-up time in this study provides a good opportunity to detect any substantial elevation of case-specific cancer deaths. The findings from Blair et al. (1998) are not inconsistent with other studies evaluating carcinogenic endpoints from AN exposure. However, Blair et al. (1998) addresse d known problems with earlier studies by quantifying exposures, examining potential confound ing from smoking, and employing an internal control group of unexposed workers. And a lthough only 5% of the cohort had died by the time of analysis, this study has a large number of observed deaths that can be used to assess

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the relationship between AN-exposure and cancer bas ed on cancer mortality. Also, Blair et al. (1998) utilized a detail job-exposure matrix as par t of the exposure assessment. For these reasons, data from Blair et al. (1998) were chosen to derive an inhalation unit risk (IUR) for AN. Additionally, the use of epidemiology data for the derivation of the IUR, versus using data from an animal bioassay, reduces uncertainty inherent to animal to human extrapolation.
Sections 4.6.1 and 4.6.2 summarized the current ani mal data on AN indicating that it is a multiple-site carcinogen in chronic oral and inhala tion bioassays with rats and mice. The best available animal studies for evaluating the dose-re sponse relationship between AN exposures and forestomach, CNS, Zymbal gland, tongue, and mam mary gland tumors were two chronic drinking water studies, one with Sprague-Dawley rat s exposed to 0, 35, 100, or 300 ppm AN in drinking water for 2 years (Quast, 2002; Quast et a l., 1980a) and the other with F344 rats exposed to 0, 1, 3, 10, 30, or 100 ppm AN in drinki ng water for 2 years (Johannsen and Levinskas, 2002b; Biodynamics, 1980c). In addition , data from another bioassay with SpragueDawley rats exposed to AN in drinking water at conc entrations of 0, 1, or 100 ppm for 2 years were also considered (Johannsen and Levinskas, 2002 a; Biodynamics, 1980a). In the absence of definitive human studies demonstrating the carcinog enicity of chronic oral exposure to AN, developing an oral cancer slope factor (CSF) from t hese animal studies is reasonable, especially because the application of the AN PBTK models descr ibed in Chapter 3 can decrease the toxicokinetic uncertainty in the interspecies extra polation and in the mode of action of carcinogenicity of AN in rodents versus humans. Animal data from the only available chronic inhalat ion cancer bioassay with multiple exposure levels (Dow Chemical Co., 1992a; Quast et al., 1980b) were also used to develop an IUR to compare with the one derived from AN-exposed workers (Blair et al., 1998). In this animal study, male and female Sprague-Dawley rats w ere exposed to 0, 20, or 80 ppm AN in air, 6 hours/day, 5 days/week, for 2 years. At 80 ppm, significantly increased incidences of astrocytomas and glial cell proliferation and Zymba l gland tumors in males and females, malignant mammary gland tumors (adenocarcinomas) in females, as well as intestinal and tongue tumors in males, were found. At 20 ppm, male and f emale rats showed increased incidences of astrocytomas and glial cell proliferation and Zymba l gland tumors. IUR estimates were derived based on dose-response data for these tumors using the AN PBTK models previously described to dosimetrically extrapolate from rats to humans.

5.4.2. Dose-Response Data
5.4.2.1. Human Occupational Data An analysis of the lung cancer mortality and AN exp osure data from the Blair et al. (1998) study was conducted to derive an IUR estimat e for AN. This analysis used the approach described by Starr et al. (2004) in which the risk of death from lung cancer in AN-exposed workers was characterized using a semi-parametric C ox regression model with time-dependent

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covariates. The Cox regression model has several a dvantages in that it allows inclusion of individual exposure histories and utilizes internal controls, thus avoiding confounding by the “healthy worker” effect. In contrast to the analys is done by Starr et al. (2004), the analysis
conducted for this assessment included the entire c ohort (not just white male workers), and the final model only had cumulative exposure as a covar iate. Starr et al. (2004) included a second covariate in their final model, plant of employment . This analysis is further described in Appendix B-7.

5.4.2.2. Rat Oral Data Incidence data for forestomach, CNS, Zymbal gland, tongue, and mammary gland tumors in Sprague-Dawley and F344 rats exposed to AN in dr inking water for 2 years were used to develop site-specific oral CSFs for AN (Tables 5-7– 5-9). Tumor incidences in F344 rats were adjusted to exclude animals dying before the first appearance of each tumor type, which ranged from day 419 to 495. No early mortality adjustment s were made to the cumulative tumor incidences from the Sprague-Dawley bioassay (Quast, 2002) because CNS and Zymbal gland tumors were seen in some high-dose female rats as e arly as 7 months (210 days) after exposure began, and no differences in survival were observed across the dose groups during the first 6 months of the study.

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Table 5-7. Incidence of CNS tumors in Sprague-Dawl ey and F344 rats exposed to AN in drinking water for 2 years

Sprague-Dawley rats (Quast, 2002; Quast et al., 1980a) a

Sex AN drinking water

concentration (ppm) Glial cell proliferation b Astrocytomas Overall CNS tumors
0 0/80 1/80 1/80
35 4/47 c 8/47 c 12/47 c
100 3/48 19/48 22/48 c Male

300 7/48 c 23/48 c 30/48 c
0 0/80 1/80 1/80
35 3/48 17/48 c 20/48 c
100 3/48 22/48 c 25/48 c Female

300 7/48 c 24/48 c 31/48 c
F344 rats (Johannsen and Levinskas, 2002b; Biodynamics, 1980c ) d

Glial cell proliferation b Astrocytomas Sex AN drinking water

concentration (ppm) Brain Spinal cord Brain Spinal cord Overall CNS tumors

0 0/160 0/156 2/160 1/156 3/160
1 0/80 0/79 2/80 0/79 2/80
3 0/78 0/70 1/78 0/70 1/78
10 0/80 0/78 2/80 0/78 2/80
30 0/79 0/79 10/79 c 0/79 10/79 c Male

100 0/76 0/70 21/76 c 4/70 c 25/76 c

0 0/157 0/155 1/157 0/155 1/157
1 0/80 0/78 1/80 0/78 1/80
3 0/80 0/79 2/80 0/79 2/80
10 0/77 0/72 4/75 1/72 5/75
30 0/80 0/87 6/80 c 0/77 6/80 c Female

100 0/76 0/69 23/76 c 1/69 24/76 c

a Incidence denominators were calculated from the tot al number of animals examined from the beginning of the study. Numerators for CNS tumor incidences (glial cell proliferation, astrocytomas, or overall incide nce of glial cell proliferation or astrocytomas) for these Sprag ue-Dawley rats were reported as combined brain and spinal cord lesions by Quast et al. (1980a).
b Glial cell proliferation is a smaller- sized lesion, either focal or multifocal, than astr ocytomas, suggestive of an early
tumor.

c Statistically significantly different from controls ( p < 0.05) as calculated by the study authors.
d The denominators for incidences in these F344 rats exclude rats from the 6- and 12-mo sacrifices and u nscheduled deaths prior to the 12-mo sacrifice. Numerators fo r t he overall incidences were the number of rats with astrocytomas in brain or spinal cord. Reviews of summaries of i ndividual animal pathology reports for this study ( Appendix H, Biodynamics, 1980c) indicated that five of the seve n F344 rats showing spinal cord astrocytomas also s howed a brain astrocytoma; thus, the number was not always as great as the sum of the numerators for the incid ences of these lesions in the two tissues (e.g., 21/76 male 100-pp m brain tissues had astrocytomas and 4/70 male 100- ppm spinal cord tissues had astrocytomas, but all four rats wi th astrocytomas also had brain astrocytomas). Beca use the response to AN was predominately in brain tissue an d a few spinal cord tissue samples were missing in each exposure group, denominators for the overall incidences were taken as the number of rats examined for brain lesions.

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Table 5-8. Incidence of mammary gland tumors in F3 44 and SpragueDawley rats exposed to AN in drinking water for 2 y ears

Sex AN drinking water

concentration (ppm) Be nign mammary gland tumors a Malignant

mammary gland tumors b Benign and/or

malignant mammary gland tumors
F344 rats (Johannsen and Levinskas, 2002b; Biodynamics, 1980c ) c,d

0
1
3
10
30 Male

100 No statistically significantly elevated incidences of mammary gland tumors were found in exposed groups compared with c ontrols.

0 12/156 3/156 14/156
1 5/80 4/80 8/80
3 6/80 0/80 6/80
10 8/79 1/78 9/80
30 9/80 3/80 12/80 Female

100 9/73 6/73 e 14/73 e Sprague-Dawley rats (Quast, 2002; Quast et al., 1980a) f

0
35
100 Male

300 Not reported Not

reported Not reported

0 52/80 1/80 58/80
35 35/48 1/48 42/48 e
100 33/48 3/48 42/48 e Female

300 22/48 10/48 e 35/48

a Incidence includes fibroadenomas for F344 rats and fibroadenomas/adenofibromas/adenomas for Sprague-Da wley
rats. b Incidence includes adenocarcinomas and carcinomas.

c The denominators for tumor incidences in F344 rats excluded rats from the 6- and 12-mo sacrifices and rats that died prior to 12 mos. Mammary gland tumor incidenc es are for animals scheduled for the 18-mo and term inal sacrifices. Microscopic examinations were only con ducted on mammary glands showing gross signs of tum ors— the inclusion of all rats living for >52 wks in the denominators assumes that rats without gross signs of tumors were also without microscopic neoplastic changes.
d Animals with multiple tumor types within a tissue w ere counted only once.

e Statistically significantly different from controls (at p < 0.05) via Fisher’s exact test.
f Denominators were calculated from the total number of animals examined from the beginning of the study

. Incidences were reported as total number of rats wi th benign-only, malignant-only, or benign and/or ma lignant
tumors.

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Table 5-9. Tumor incidences Sprague-Dawley and F34 4 in rats exposed to AN in drinking water for 2 years

Sex AN drinking

water concentration (ppm) Forestomach

tumors CNS

tumors Zymbal gland

tumors Tongue

tumors Intestinal

tumors Mammary gland

tumors Sprague-Dawley rats (Quast, 2002; Quast et al., 1980a)
0 0/80 1/80 3/80 1/80
35 2/47 12/47 a 4/47 2/47
100 23/48 a 22/48 a 3/48 4/48 Male

300 39/48 a 30/48 a 16/48 a 5/48 a Not reported Not reported

0 1/80 1/80 1/80 0/80 0/80 58/80
35 1/48 20/48 a 5/48 a 1/48 1/48 42/48 a
100 12/48 a 25/48 a 9/48 a 2/48 4/48 a 42/48 a Female

300 30/48 a 31/48 a 18/48 a 12/48 a 4/48 a 35/48

F344 rats (Johannsen and Levinskas, 2002b; Biodynamics, 1980c ) b

0 0/159 3/160 1/147 3/159
1 1/80 2/80 1/76 2/80
3 4/78 a 1/78 0/73 2/78
10 3/80 a 2/80 0/67 2/80
30 4/80 a 10/79 c 2/71 c 0/80 Male

100 1/77 25/76 c 14/68 c Not examined

2/77

0 1/157 1/157 0/157 14/156
1 1/80 1/80 0/73 8/80
3 2/79 2/80 0/73 6/80
10 2/77 5/75 0/70 9/80
30 4/80 a 6/80 c 2/73 c 12/80 Female

100 2/75 24/76 c 8/62 c Not examined

14/73 a

a Significantly different from controls ( p < 0.05).
b The denominators for tumor incidences in F344 rats excluded rats from the 6- and 12-mo sacrifices and unscheduled deaths prior to the 12-mo sacrifice. N umerators for the incidences of CNS tumors were der ived by adding the number of rats with brain or spinal astr ocytomas; denominators were taken as the greater of the number of rats examined for brain or spinal cord lesions a fter the 12-mo sacrifice. Numerators for Zymbal gl and tumor incidences included squamous cell papillomas and ca rcinomas designated to occur in the ear canal. Mam mary gland tumor incidences are for fibroadenomas and ad enocarcinomas in animals sacrificed or found dead a fter 12 mos. Tongues were not routinely histopathologic ally examined for tumors in this bioassay.

c Significantly different from controls ( p < 0.01).

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As previously noted, a second 2-year AN drinking wa ter study employing SpragueDawley rats has been conducted (Johannsen and Levin skas, 2002a; Biodynamics, 1980a). To determine whether these data should also be employe d in the cancer assessment, an analysis was performed to evaluate the statistical validity of p ooling tumor incidence data from the two Sprague-Dawley rat chronic AN drinking water studie s. The first study (Quast, 2002; Quast et al., 1980a) exposed animals to AN drinking water co ncentrations of 0, 35, 100, and 300 ppm, while the second study (Johannsen and Levinskas, 20 02a) employed AN drinking water concentrations of 0, 1, and 100 ppm. The dichotomo us multistage model in BMDS was fit to the tumor incidence data from three sites (i.e., forest omach, CNS, and Zymbal gland) in each sex across both studies, using administered animal dose expressed in mg/kg-day. A statistical test described by Stiteler et al. (1993), which employs a maximum likelihood ratio statistic
distributed as a χ 2 

### , was then used to test the null hypothesis that th e two data sets are compatible with a common dose-response model. If the null hyp othesis is not rejected, this provides evidence that the results from the two studies may be pooled. As discussed in more detail in Appendix B-5, the st atistical tests indicated that some, but not all, of the data sets from the two studies were consistent with a common dose-response model. More specifically, the results of this anal ysis showed that forestomach and Zymbal gland tumors in both male and female Sprague-Dawley rats were not compatible with a common doseresponse model, while CNS tumors in male and female Sprague-Dawley rats were compatible with a common dose-response model. Because of thes e conflicting results, it was decided that the results from the two Sprague-Dawley rat drinkin g water studies would not be pooled. Therefore, the final dose-response analysis for der iving the oral slope factor for AN focused on the two rat drinking water studies containing the m ost dose groups (i.e., the Sprague-Dawley rat bioassay reported by Quast [2002] and the F344 rat bioassay reported by Johannsen and Levinskas [2002b]).

5.4.2.3. Rat Inhalation Data Incidence data for intestinal, CNS, Zymbal gland, t ongue, and mammary gland tumors in Sprague-Dawley rats exposed to AN via inhalation we re used for deriving site-specific IURs for AN (Table 5-10). With the exception of one male in the 80 ppm exposure group that died with a CNS tumor after 7–12 months on study, all of the re maining tumors occurred in rats that died or were sacrificed after at least 12 months of AN expo sure. Denominators for the incidences in
Table 5-10 excluded animals that died without a tum or before 12 months on study because these animals were not exposed long enough to be at risk for tumor development. Although a statistically significantly elevated incidence in t ongue tumors was observed in male rats at 80 ppm, tongues from only 14 of the males in the 20 pp m exposure group were examined. No data on the incidence of tongue tumors in female rats we re presented in the original study report by Quast et al. (1980b).

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Table 5-10. Incidences of intestinal, CNS, Zymbal gland, tongue, and mammary gland tumors in Sprague-Dawley rats exposed to AN via inhalation for 2 years

Sex AN air

concentration (ppm) Intestinal

tumors a CNS

tumors a,b Zymbal gland

tumors a Tongue

tumors a Mammary gland

adenocarcinomas a
0 4/96 0/96 2/96 1/95 – 20 3/93 4/93 4/93 0/14 – Male
80 17/82 c 22/82 c 11/82 c 7/82 c
–

0 – 0/93 0/93 – 9/93
20 – 8/99 c 1/98 – 8/98 Female
80 – 20/89 c 11/89 c – 20/99 c

a For all incidence data, the denominators excluded r ats dying earlier than 12 mos in the study. These data were ascertained from Tables 22, 25, 31, 34, and 35 in t he original study report by Quast et al. (1980b).
b Incidences for CNS tumors (brain and spinal cord) i n Sprague-Dawley rats listed in this table, as repo rted by Quast et al. (1980b), include both glial cell proli feration and astrocytomas.

c Statistically significantly different from controls ( p < 0.05) as calculated by the study authors.

Sources: Dow Chemical (1992a); Quast et al. (1980b ).



### 5.4.3. Dose-Response Modeling
5.4.3.1. Human Occupational Data A Cox regression model was developed based on an an alysis of the Blair et al. (1998) lung cancer mortality data for AN-exposed workers. This model yielded a regression coefficient ( β ) estimate of 1.2 × 10 -3 

### with an associated estimated standard error of 2.4 7 × 10 -3 

### and a corresponding p value of 0.61. The 95% upper confidence limit (UC L) on the parameter estimate, β , was 5.3 × 10 -3 

### . The parameter estimate, β , in this model was about threefold greater than the same parameter estimate in the final model developed by Starr et al. (2004), but the UCL was similar. The Cox regression model describe d above was used to predict an AN exposure concentration (EC) and its associated 95% lower confidence limit (LEC), associated
with a 10 -2 

### (1%) risk of dying from lung cancer at age 80 (EC 01 

### and LEC 01 

### , respectively). Conversions of occupational exposures to continuous environmental exposures were performed to account for differences in the number of days ex posed per year (240 vs. 365 days) and in the amount of air inhaled during an 8-hour workday vers us a 24-hour day (10 and 20 m 3 

### /day, respectively). The resulting AN exposure estimates (by age 80) were EC 01 

### = 0.992 ppm (or 2.2 mg/m 3 

### ) and LEC 01 

### = 0.238 ppm (or 0.524 mg/m 3 

### ). The IUR estimate was then derived by linear extrapolation from the LEC 01 

### . The corresponding unit risk was calculated to be 4.2 × 10 -2 

### ppm -1



### or 2 × 10 -2 

### per mg/m 3 

### . As previously noted, Appendix B-7 provides more details on this Cox regression analysis.

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5.4.3.2. Rat Oral Data Within each rat strain, sex, and tumor site, the mu ltistage model, employing EPA’s BMDS (version 1.4.1), was fit to the tumor incidenc e data from the bioassays in SpragueDawley (Quast, 2002) and F344 (Johannsen and Levins kas, 2002b) rats shown in Table 5-9 using two internal dose metrics, CEO concentration in blood (AUC/24 hours) and AN concentration in blood (AUC/24 hours). As already discussed, CEO is a DNA-reactive epoxide metabolite thought to play a key role in the carcin ogenic mode of action of AN. The EPA-modified PBTK model employed consistently predi cted higher CEO concentrations in blood and brain than were reported in studies of or ally exposed rats (see Figures 3 and 4 in Kedderis et al., 1996). In contrast, AN concentrat ions in blood, brain, and liver predicted by the same PBTK model were fairly close to measured AN co ncentrations in rats following oral exposure. Ultimately, CEO levels in blood were cho sen as the internal dose metric of choice for the oral cancer dose-response assessment because CE O is believed to be the most biologically relevant dose metric, and it is also consistent wit h the dose metric employed in derivation of the RfD. As with the RfD, CEO concentration in blood r epresents a reasonable internal dose metric for extrapolating from orally exposed rats to human s. The AN concentrations in drinking water (in ppm) em ployed in the Quast (2002) and Johannsen and Levinskas (2002b) rat studies were co nverted to AN administered doses (in mg/kg-day) by the study authors, using water intake data recorded during the study. These administered doses of AN were then used as input in to the EPA-modified rat PBTK model of Kedderis et al. (1996) in order to predict a rat in ternal dose (either CEO-AUC or AN-AUC concentration in blood) resulting from the ingestio n of a total daily dose of AN equivalent to the administered dose consumed in six bolus episodes pe r day that reflect the daily drinking water consumption pattern of rats. The resulting predict ed CEO-AUC or AN-AUC concentrations in rat blood were then employed in dose-response model ing. Table 5-11 displays the relationship between AN drinking water concentrations (in ppm), administered animal doses (in mg/kg-day), and two internal dose metrics (i.e., CEO in blood a nd AN in blood, both expressed in mg/L) predicted from the PBTK model.

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Table 5-11. Four different dose metrics, two exter nal and two internal, based on doses employed in studies of Sprague-Dawley and F344 rats exposed to AN in drinking water for 2 years

External dose Predicted internal dose a Species, strain (reference) Sex
Concentration in drinking water (ppm) Administered

dose b (mg/kg-d) CEO in blood

(mg/L) AN in blood

(mg/L)
0 0 0 0
35 3.4 1.83 × 10 -3 2.06 × 10 -2

100 8.5 4.36 × 10 -3 5.36 × 10 -2 Male

300 21.3 9.70 × 10 -3 1.46 × 10 -1

0 0 0 0
35 4.4 2.07 × 10 -3 2.37 × 10 -2

100 10.8 4.87 × 10 -3 6.18 × 10 -2 Rat, Sprague-Dawley (Quast, 2002)

Female

300 25.0 1.01 × 10 -2 1.56 × 10 -1

0 0 0 0
1 0.08 4.06 × 10 -5 4.33 × 10 -4

3 0.25 1.27 × 10 -4 1.35 × 10 -3

10 0.83 4.19 × 10 -4 4.52 × 10 -3

30 2.48 1.23 × 10 -3 1.37 × 10 -2 Male

100 8.37 3.97 × 10 -3 4.85 × 10 -2

0 0 0 0
1 0.12 5.32 × 10 -5 5.73 × 10 -4

3 0.36 1.59 × 10 -4 1.72 × 10 -3

10 1.25 5.49 × 10 -4 6.02 × 10 -3

30 3.65 1.58 × 10 -3 1.79 × 10 -2 Rat, F344 (Johannsen and Levinskas, 2002b)

Female

100 10.90 4.46 × 10 -3 5.63 × 10 -2

a The EPA-modified rat PBPK model of Keddaris et al. (1996) was employed to predict a rat internal dose (i.e., either AN-AUC or CEO-AUC concentration in blood) re sulting from the ingestion of an administered dose of AN consumed in six bolus episodes/d.
b Administered doses were averages calculated by the study authors based on animal BW and drinking water intake.



### Employing the internal dose metrics in Table 5-11 ( i.e., CEO in blood and AN in blood), successive stages of the multistage model, starting with stage 1 and ending with the stage equal to the number of dose groups minus one, were fit to the tumor incidence data at a particular site for each rat strain and sex. Then, all stages of t he multistage model that did not show a significant lack of fit (i.e., p > 0.1) were compared using AIC. The stage of the multistage model
with the lowest AIC was selected as the “best-fit” model. For most tumor sites, the one-stage
model exhibited the best fit.
A BMR of 10% extra risk was selected for all tumor sites, consistent with the Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005a), which recommend identifying the POD near the lower end of the observed data. Using the best -fit model, the resulting BMD 10 

### s and

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BMDL 10 

### s were estimated for each tumor site within each ra t strain and sex. A summary of the results of this BMD modeling is shown in Table 5-12 . Additional details regarding doseresponse modeling used in the derivation of the ora l CSFs are provided in Appendix B-3.

Table 5-12. BMD modeling results using tumor incid ence data from male and female Sprague-Dawley and F344 rat studies in w hich animals were exposed to AN in drinking water for 2 years

BMD modeling results a

Strain/species Sex Tumor site Dose metric BMD 10 (mg/L) BMDL 10

(mg/L)
CEO 1.87 × 10 -3 1.44 × 10 -3 Forestomach AN 2.26 × 10 -2 1.70 × 10 -2

CEO 8.87 × 10 -4 7.16 × 10 -4 CNS AN 8.82 × 10 -3 6.64 × 10 -3

CEO 5.46 × 10 -3 3.15 × 10 -3 Zymbal gland AN 8.94 × 10 -2 4.26 × 10 -2

CEO 8.78 × 10 -3 4.90 × 10 -3 Male

Tongue AN 1.29 × 10 -1 6.97 × 10 -2

CEO 3.29 × 10 -3 2.38 × 10 -3 Forestomach AN 4.22 × 10 -2 2.49 × 10 -2

CEO 5.79 × 10 -4 4.51 × 10 -4 CNS AN 7.12 × 10 -3 5.55 × 10 -3

CEO 2.40 × 10 -3 1.78 × 10 -3 Zymbal gland AN 3.41 × 10 -2 2.52 × 10 -2

CEO 6.70 × 10 -3 4.74 × 10 -3 Tongue AN 9.67 × 10 -2 6.10 × 10 -2

CEO 5.50 × 10 -4 2.98 × 10 -4 Sprague-Dawley rats

Female

Mammary gland AN 7.05 × 10 -3 3.77 × 10 -3

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Table 5-12. BMD modeling results using tumor incid ence data from male and female Sprague-Dawley and F344 rat studies in w hich animals were exposed to AN in drinking water for 2 years

BMD modeling results a

Strain/species Sex Tumor site Dose metric BMD 10 (mg/L) BMDL 10

(mg/L)
CEO 6.03 × 10 -4 3.55 × 10 -4 Forestomach AN 6.48 × 10 -3 3.81 × 10 -3

CEO 1.16 × 10 -3 8.74 × 10 -4 CNS AN 1.37 × 10 -2 1.03 × 10 -2

CEO 2.73 × 10 -3 2.19 × 10 -3 Male

Zymbal gland AN 3.31 × 10 -2 2.59 × 10 -2

CEO 3.65 × 10 -3 1.69 × 10 -3 Forestomach AN 4.13 × 10 -2 1.90 × 10 -2

CEO 1.39 × 10 -3 1.05 × 10 -3 CNS AN 1.70 × 10 -2 1.28 × 10 -2

CEO 3.78 × 10 -3 2.97 × 10 -3 Zymbal gland AN 5.41 × 10 -2 3.35 × 10 -2

CEO 3.58 × 10 -3 1.97 × 10 -3 F344 rats

Female

Mammary gland AN 4.51 × 10 -2 2.45 × 10 -2

a The multistage model in EPA’s BMDS (version 1.4.1) was fit to each set of tumor incidence data from th e Sprague-Dawley and F344 rat bioassays, as shown in Table 5-9, using the two internal dose metrics, CEO in blood and AN in blood, expressed in mg/L. An adequate fi t of the MS model was achieved if the χ 2 goodness-of-fit statistic yielded p > 0.1. In the case of CNS tumors in Sprague-Dawley female rats, an adequate fit of the multistage model to the data could not be achieved; therefore, the best fitting of the other models av ailable in BMDS (assessed by AIC), the log-logistic model, was used. Numbers in parentheses indicate the number of dose groups dropped in order to obtain an adequate fit ( starting with the highest dose group). Appendix B- 3 provides further details on these BMD modeling results.

Sources: Johannsen and Levinskas (2002b) (F344); Q uast (2002) (Sprague-Dawley).



### After completion of the dose-response modeling, the BMDL 10 

### s estimated for each tumor
site within each rat strain and sex for each intern al dose metric were input into the EPA-modified human PBTK model of Sweeney et al. (2003) in order to predict the human equivalent administered dose of AN that corresponds to the est imated BMDL 10 

### , assuming six bolus ingestion episodes of AN per day. The resulting pr edicted human equivalent administered dose of AN, expressed in mg/kg-day, are shown in the thi rd column of Table 5-13 for the internal
dose metric CEO in blood and Table 5-14 for the int ernal dose metric AN in blood. Finally, for each rat strain, sex, and tumor site, the site-spec ific oral CSFs shown in the last column of Table 5-13 (based on CEO concentration in blood) and Tabl e 5-14 (based on AN concentration in blood) were derived by dividing the BMR (i.e., 10% or 0.1) by the human equivalent administered dose of AN (in mg/kg-day), displayed i n the third column of Tables 5-13 and 5-14.

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Table 5-13. Site-specific oral CSFs for AN based o n BMD modeling of tumor incidence data in rats and predicted CEO leve ls in blood (AUC/24 hours) of rats and humans assuming episodic exposure to AN

Rat strain, gender Tumor site Rat BMDL 10 a (mg/L) BMDL 10/HED b

(mg/kg-d) CSF c

(mg/kg-d) -1 Sprague-Dawley males
Forestomach 1.44 × 10 -3 0.142 0.704
CNS 7.16 × 10 -4 0.071 1.410 Zymbal gland 3.15 × 10 -3 0.312 0.320 Tongue 4.90 × 10 -3 0.486 0.206 Sprague-Dawley females
Forestomach 2.38 × 10 -3 0.236 0.424
CNS 4.51 × 10 -4 0.045 2.222 Zymbal gland 1.78 × 10 -3 0.176 0.567 Tongue 4.74 × 10 -3 0.470 0.213 Mammary gland 2.98 × 10 -4 0.029 3.390
F344 males
Forestomach 3.55 × 10 -4 0.035 2.850
CNS 8.74 × 10 -4 0.086 1.160 Zymbal gland 2.19 × 10 -3 0.217 0.462 F344 females
Forestomach 1.69 × 10 -3 0.167 0.599
CNS 1.05 × 10 -3 0.104 0.963 Zymbal gland 2.97 × 10 -3 0.294 0.340 Mammary gland 1.97 × 10 -3 0.195 0.514

a Rat BMDL 10 refers to the estimated 95% lower confidence limit on the internal dose of CEO in blood in the rat associated with a 10% extra risk for the in cidence of tumors at the specified site in the asso ciated strain and sex. This value is taken from the last column of Table 5-12.
b PBTK model-derived HED of AN that would result in a human 24-hr blood CEO-AUC equivalent to the rat CEO-AUC presented in the previous column of the table, assuming AN ingestion in six bolus episodes/d.

c CSF = BMR/BMDL 10/HED or 0.1/BMDL 10/HED . Sources: Johannsen and Levinskas (2002b) (F344); Q uast (2002) (Sprague-Dawley).

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Table 5-14. Site-specific oral CSFs for AN based o n BMD modeling of tumor incidence data in rats and predicted AN level s in blood (AUC/24 hours) of rats and humans assuming episodic exposure to AN

Rat strain, gender Tumor site Rat BMDL 10 a (mg/L) BMDL 10/HED b

(mg/kg-d) CSF c

(mg/kg-d) -1 Sprague-Dawley males
Forestomach 1.70 × 10 -2 4.30 0.023
CNS 6.64 × 10 -3 1.89 0.053 Zymbal gland 4.26 × 10 -2 8.59 0.012 Tongue 6.97 × 10 -2 11.85 0.008 Sprague-Dawley Females
Forestomach 2.49 × 10 -2 5.82 0.017
CNS 5.55 × 10 -3 1.60 0.062 Zymbal gland 2.52 × 10 -2 5.87 0.017 Tongue 6.10 × 10 -2 10.90 0.009 Mammary gland 3.77 × 10 -3 1.11 0.090
F344 males
Forestomach 3.81 × 10 -3 1.12 0.089
CNS 1.03 × 10 -2 2.82 0.036 Zymbal gland 2.59 × 10 -2 5.99 0.017 F344 females
Forestomach 1.90 × 10 -2 4.71 0.021
CNS 1.28 × 10 -2 3.38 0.030 Zymbal gland 3.35 × 10 -2 7.26 0.014 Mammary gland 2.45 × 10 -2 5.75 0.017

a Rat BMDL 10 refers to the estimated 95% lower confidence limit on the internal dose of AN in blood in the rat associated with a 10% extra risk for the incide nce of tumors at the specified site in the associat ed strain and sex. This value is taken from the last column of Table 5-12.
b PBTK model-derived HED of AN that would result in a human 24-hr blood AN-AUC equivalent to the rat AN-AUC presented in the previous column of the table, assuming AN ingestion in six bolus episodes/d.

c CSF = BMR/BMDL 10/HED or 0.1/BMDL 10/HED .
Sources: Johannsen and Levinskas (2002b) (F344); Q uast (2002) (Sprague-Dawley).



### In comparing Tables 5-13 and 5-14, the CEO-based si te-specific oral CSF estimates in Table 5-13 are higher than those based on AN blood levels in Table 5-14. This occurs because
the V max 

### C/K m 

### for AN oxidation to CEO is estimated to be about 1 0 times higher in humans than in the rat. AN enzymatic GSH conjugation is estima ted to be 1.5 times higher in the rat, but the
2 nd 

### -order removal constant for non-enzymatic reaction of AN and GSH is assumed to be the same and the GSH tissue levels are roughly the same (and lower in the larger tissue groups). The result, for example, with a steady oral “infusion” of 30 mg/kg-day, is that AN is removed somewhat faster overall, leading to physiologically based pharmacokinetic (PBPK) predicted

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steady-state blood level of 0.114 mg/L AN in humans vs. 0.151 in the rat, but a much higher portion of this goes to CEO in the human yielding a CEO blood level of 0.297 vs. 0.013 mg/L in the rat. Thus, AN:CEO = 11.4 in the rat and 0.385 in the human, and so the CEO-based risk estimates are approximately 50 times higher than th e AN-based estimates. For comparative purposes, in Table 5-15, the BMDL 10 

### estimates generated from the BMD modeling of the incidence of tumors in male and female Sprague-Dawley and F344 rats using administered animal dose (modeling results no t shown) were converted to human equivalent administered doses of AN using BW scalin g to the 3⁄4 power. Then, as in Tables 5-13 and 5-14, oral CSFs were derived by dividing the BM R (i.e., 10% or 0.1) by the human equivalent administered dose of AN (in mg/kg-day).

Table 5-15. Site-specific oral CSFs for AN based o n BMD modeling of tumor incidence data in rats and BW scaling to the 3⁄4 power to convert from rat to human administered doses

Rat strain, gender Tumor site Rat BMDL 10 a (mg/kg-d) BMDL 10/HED b (mg/kg-d) CSF c (mg/kg-d) -1 Sprague-Dawley males
Forestomach 2.76 0.812 0.123
CNS 1.48 0.436 0.229 Zymbal gland 5.17 1.52 0.066 Tongue 10.4 3.04 0.033 Sprague-Dawley females
Forestomach 4.81 1.27 0.079
CNS 0.99 0.262 0.382 Zymbal gland 4.19 1.11 0.090 Tongue 8.30 2.19 0.046 Mammary gland 0.66 0.174 0.575
F344 males
Forestomach 0.70 0.193 0.517
CNS 1.81 0.493 0.203 Zymbal gland 3.43 0.932 0.107 F344 females
Forestomach 3.89 0.926 0.108
CNS 2.52 0.602 0.166 Zymbal gland 6.64 1.59 0.063 Mammary gland 4.77 1.14 0.088

a Rat BMDL 10 is the estimated 95% lower confidence limit on the administered dose of AN in the rat associated with a 10% extra risk for the incidence of tumors at the specified site in the associated s train and sex. This value is generated from the “best-fi t” dose-response model in BMDS (version 1.4.1).
b The HED of AN equal to the rat BMDL 10 in the previous column converted through use of BW scaling to the 3⁄4 power.

c CSF = BMR/BMDL 10/HED or 0.1/BMDL 10/HED . Sources: Johannsen and Levinskas (2002b) (F344); Q uast (2002) (Sprague-Dawley).

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5.4.3.3. Rat Inhalation Data Within each sex and for each tumor site, the multis tage model, employing EPA’s BMDS (version 1.4.1), was fit to the tumor incidence dat a from the AN inhalation bioassay in SpragueDawley rats (Quast et al., 1980b) shown in Table 5- 10 using the internal dose metric, CEO concentration in blood (AUC/24 hours). In contrast to the approach used for oral exposure, only
one internal dose metric was selected on which to b ase site-specific IURs (i.e., CEO in blood), because, in contrast to oral exposure, the EPA-modi fied PBTK model adequately predicted
measured blood and brain concentrations of CEO in r ats exposed to AN via inhalation (Kedderis et al., 1996). Furthermore, as mentioned previousl y, CEO is the DNA-reactive metabolite thought to be key in the carcinogenic mode of actio n of AN. Prior to dose-response modeling, the AN concentrati ons in air (in ppm) administered in the Quast et al. (1980b) rat study were input into the EPA-modified rat PBTK model of Kedderis et al. (1996) in order to predict a rat internal do se (CEO-AUC concentration in blood) resulting from inhalation exposure to the administered air co ncentration of AN. The resulting predicted CEO-AUC concentrations in rat blood were then emplo yed in dose-response modeling. Table 5-16 displays the relationship between AN con centrations in air (expressed in ppm) and the internal dose metric, CEO in blood (expressed i n mg/L), predicted from the PBTK model.

Table 5-16. Two different dose metrics, one extern al and one internal, based on administered air concentrations of AN employed i n a 2-year bioassay in Sprague-Dawley rats

Species, strain Sex Exposed AN concentration in air (ppm) Predicted CEO concentration in blood a (mg/L)
0 0
20 2.17 × 10 -3 Male
80 8.20 × 10 -3

0 0
20 2.18 × 10 -3 Rat, Sprague-Dawley

Female

80 8.24 × 10 -3

a See Table 5-11.

Source: Quast et al. (1980b).



### After completion of the dose-response modeling, the BMC 10 

### s and BMCL 10 

### s estimated within each sex for each tumor site using CEO in bl ood as the dose metric from Table 5-17 were input into the EPA-modified human PBTK model of Swe eney et al. (2003) in order to predict the HEC of AN in air that corresponds to the estimated BMC 10 

### and BMCL 10 

### in animals. The resulting predicted 95% lower bounds of the HECs (B MCL 10/HEC 

### ) of AN in air, expressed in

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mg/m 3 

### , are shown in the third column of Table 5-18 for t he internal dose metric CEO in blood. Finally, for each sex and tumor site, the site-spec ific IURs shown in the last column of Table 5-19 (based on CEO concentration in blood) we re derived by dividing the BMR (i.e., 10% or 0.1) by the BMCL 10/HEC


### .

Table 5-17. BMD modeling results using tumor incid ence data from male and female Sprague-Dawley rats exposed to AN via in halation for 2 years and CEO concentration in blood predicted from an EP A-modified PBTK model

BMD modeling results

Strain, species Sex Tumor site Dose metric BMC 10 (mg/L) BMCL 10

(mg/L)
Intestine CEO 6.06 × 10 -3 4.47 × 10 -3

CNS CEO 3.14 × 10 -3 2.31 × 10 -3 Male Zymbal gland CEO 7.26 × 10 -3 4.40 × 10 -3

Tongue CEO 9.48 × 10 -3 6.39 × 10 -3

CNS CEO 3.21 × 10 -3 2.39 × 10 -3 Zymbal gland CEO 7.90 × 10 -3 5.09 × 10 -3Rat, SpragueDawley

Female

Mammary gland CEO 7.31 × 10 -3 4.33 × 10 -3

a The multistage model in EPA’s BMDS (version 1.4.1) was fit to each set of tumor incidence data from th e Sprague-Dawley rat bioassay, as shown in Table 5-10 , using the internal dose metric, CEO in blood, exp ressed in mg/L. An adequate fit of the multistage model was achieved if the χ 2 goodness-of-fit statistic yielded p > 0.1. Appendix B-4 provides further details on these BMD modeling results.

Source: Quast et al. (1980b).

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Table 5-18. Site-specific IURs for AN based on BMD modeling of tumor incidence data in Sprague-Dawley rats and PBTK mode ling of CEO levels in blood (AUC/24 hours) of rats and humans

Gender Tumor site Rat BMCL 10 a (mg/L) BMCL 10/HEC b (mg/m 3 

### ) IUR c

(mg/m 3 ) -1

Males
Intestine 4.47 × 10 -3 6.00 0.017
CNS 2.31 × 10 -3 3.10 0.032 Zymbal gland 4.40 × 10 -3 5.91 0.017 Tongue 6.39 × 10 -3 8.58 0.012
Females
CNS 2.39 × 10 -3 3.21 0.031 Zymbal gland 5.09 × 10 -3 6.83 0.015 Mammary gland 4.33 × 10 -3 5.81 0.017

a Rat BMCL 10 refers to the estimated 95% lower confidence limit on the concentration of CEO in blood of the rat associated with a 10% extra risk for the in cidence of tumors at the specified site based on BM D modeling. This value is taken from the last column of Table 5-17.
b PBTK model-derived HEC of AN in air that would resu lt in a human 24-hr blood CEO-AUC concentration equivalent to the rat BMCL 10 in the previous column of the table assuming conti nuous exposure to AN. The human PBTK model employed did not contain the human in vitro to in vivo modifying factor for CEO hydrolysis proposed by Swe eney et al. (2003).

c IUR = BMR/BMCL 10/HEC or 0.1/BMCL 10/HEC .



### Table 5-19. Site-specific IURs for AN based on BMD modeling of tumor incidence data in Sprague-Dawley rats exposed to AN via inhalation

Gender Tumor site Rat BMCL 10 a (ppm) BMCL 10/HEC b

(mg/m 3 

### ) IUR c

(mg/m 3 ) -1

Males
Intestine 42.68 93.58 1.07 × 10 -3

CNS 22.23 48.74 2.05 × 10 -3 Zymbal gland 42.53 93.25 1.07 × 10 -3 Tongue 59.41 130.26 7.68 × 10 -4

Females
CNS 22.89 50.19 1.99 × 10 -3 Zymbal gland 48.74 106.87 9.36 × 10 -4 Mammary gland 37.82 82.92 1.21 × 10 -3

a Rat BMCL 10 refers to the estimated 95% lower confidence limit on the concentration of AN in air associated with a 10% extra risk for the incidence of tumors at the specified site based on BMD modeli ng. b The HEC of AN in air equivalent to the rat BMCL 10 in the previous column of the table generated thro ugh use of the following conversion equation: mg/m 3 = [ppm × molecular weight]/24.20, where molecular weight = 53.06.

c IUR = BMR/BMCL 10/HEC or 0.1/BMCL 10/HEC .

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5.4.4. Cancer Risk Values
5.4.4.1. Oral CSFs Because AN has been demonstrated to produce tumors at multiple sites in rats, the estimation of risk based on only one tumor site may underestimate the overall carcinogenic potential of AN. Under the assumption that AN caus es tumors by a mutagenic mode of action, estimates of the composite risk of etiologically di stinct tumor types in each rat strain/sex
combination considered in Section 5.4.3.2 were deri ved employing the Bayesian approach described in Appendix B-6. This approach is consistent with the recommendations of the NRC (1994) and the Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005a), which recommends “adding risk estimates derived from diff erent tumor sites (NRC, 1994) as an option for “how best to represent the human cancer risk.” This composite risk is associated with the potential for developing tumors, not at all of the sites, but at any combination of the sites observed in male or female rats. For this analysis , the etiologically distinct tumor sites associated with AN exposure were assumed to be stat istically independent. This assumption cannot currently be verified, but if not correct co uld lead to an overestimate of risk. NRC (1994) concluded that a general assumption of statistical independence of tumors within animals was not likely to introduce substantial error in assess ing carcinogenic potency from rodent bioassay
data. Table 5-20 presents the estimated human equivalent oral CSFs for both site-specific risks and composite risks from multiple tumor types from each rat strain and sex exposed to AN via drinking water based on the internal dose metric, C EO concentration in blood (AUC over 24 hours).

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Table 5-20. Estimated human equivalent oral CSFs f or composite risk based on tumor incidence in AN-exposed rats and predicted CEO-AUC levels in blood

Rat strain and gender Tumor sites included Site-specific oral CSF a (mg/kg-d) -1 Oral CSF for composite risk across sites (mg/kg-d) -1 Sprague-Dawley Male
Forestomach 0.704
CNS 1.410 Zymbal gland 0.320 Tongue 0.206 2.8

Sprague-Dawley Female
Forestomach 0.424
CNS 2.222 Zymbal gland 0.567 Tongue 0.213 Mammary gland 3.390 5.0

F344 Male
Forestomach 2.850
CNS 1.160 Zymbal gland 0.462 3.1

F344 Female
Forestomach 0.599
CNS 0.963 Zymbal gland 0.340 Mammary gland 0.514 1.9

a These site-specific oral CSFs are taken from the la st column of Table 5-13.



### In Sprague-Dawley rats, males showed statistically significantly increased incidences of tumors at four sites (i.e., forestomach, CNS, Zymba l gland, and tongue), while females showed statistically significantly increased incidences of tumors at five sites (i.e., forestomach, CNS, Zymbal gland, tongue, and mammary gland), following chronic oral exposure to AN. The composite oral CSF based on tumor incidences in mal e Sprague-Dawley rats chronically exposed to AN (using CEO concentration in blood) is estimat ed to be 2.8 per mg/kg-day, about twice as high as the estimated slope factor resulting from t he most sensitive single site in this strain and sex. For female Sprague-Dawley rats, the composite oral CSF (based on CEO concentration in blood) was 5.0 per mg/kg-day, approximately 50% hig her than the estimated slope resulting from the most sensitive single site in this strain and sex. In F344 rats, males showed statistically significan t increased incidences of tumors at three sites (i.e., forestomach, CNS, and Zymbal gla nd), while females showed statistically significant increased incidences of tumors at four sites (i.e., forestomach, CNS, Zymbal gland, and mammary gland), following oral exposure to AN i n drinking water for 2 years. Again, under

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the assumption that the tumors at these sites are s tatistically independent, the composite oral CSF in F344 males (based on CEO concentration in blood) was 3.1 per mg/kg-day, slightly higher than the estimated slope factor of 2.8 per mg/kg-da y based on tumors in the forestomach alone, the most sensitive single site in this strain and s ex. For female F344 rats, the composite oral CSF (based on CEO concentration in blood) was 1.9 per m g/kg-day, about twice the estimated slope factor of 0.96 per mg/kg-day from tumors of the CNS , the most sensitive single site in this strain
and sex. The slope factors obtained from male and female Spr ague-Dawley rats and F344 rats ranged from 2 to 5 (mg/kg-day) -1 

### . While female Sprague-Dawley rats had the highest slope factor due to increase in mammary gland tumor risk, the increase in mammary gland tumor risk in female F344 rats was not as high. There is no information as to which rat strain may be most similar to humans. Both strains of rats developed same tumors in response to AN exposure. For the purpose of this assessment, the slope factor of 5 per mg/kg-day is recommended for use in
humans because it is the value obtained from the mo st sensitive species, strain, and sex (i.e., female Sprague-Dawley rats). This slope factor sho uld not be used with exposures greater than 0.04 mg/kg-day (the lowest POD supporting the compo site risk) because above this level the slope factor cannot be expected to be an adequate a pproximation to the dose-response relationship. The fitted dose-response relationshi p and pharmacokinetic models should be used to estimate risk above this exposure level. See Se ction 5.6 regarding the application of agedependent adjustment factors (ADAFs).

Previous IRIS Assessment In the previous IRIS assessment completed in 1991, EPA derived an oral CSF of
5 × 10 -1 

### (mg/kg-day) -1 

### by application of the linearized multistage model to incidence data from rats with astrocytomas, Zymbal gland carcinomas, or forestomach papillomas or carcinomas from the three 2-year drinking water studies in rat s considered under the current assessment (Biodynamics, 1980a,c; Quast et al., 1980a). At th at time, no PBTK models were available for generating internal dose metrics or informing inter species extrapolation; therefore, interspecies extrapolation was accomplished using BW 2/3 

### scaling. The final slope factor of 5 × 10 -1 

### (mg/kgday) -1 

### was the geometric mean of the slope factors derive d from each of these three studies, i.e.,
4 × 10 -1 

### (mg/kg-day) -1 

### (Biodynamics, 1980a), 4 × 10 -1 

### (mg/kg-day) -1 

### (Biodynamics, 1980c), and
10 × 10 -1 

### (mg/kg-day) -1 

### (Quast et al., 1980a).

5.4.4.2. Inhalation Unit Risk Employing human data, the EC 01 

### and LEC 01 

### , defined as the AN exposure concentration and its associated 95% lower confidence limit, resp ectively, that result in a 1% increase in the risk of dying from lung cancer at age 80 were estim ated from the Cox regression model derived from the Blair et al. (1998) occupational epidemiol ogy study. These EC 01 

### and LEC 01 

### values

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were 0.992 and 0.238 ppm, respectively (or 2,187 an d 524 μ g/m 3 

### , respectively). From the
LEC 01 

### , an IUR of 4.2 × 10 -2 

### ppm -1 

### or 2 × 10 -2 

### (mg/m 3 

### ) -1 

### was derived. For inhalation exposures to AN in animals, as with oral exposures, estimates of composite risk addressing multiple tumor sites (within strain and sex) based on BMD modeling results from a chronic inhalation rodent bioassay in Sprague-Daw ley rats (Dow Chemical 1992a; Quast et al., 1980b) were generated. These estimates were derive d employing the same Bayesian approach described in Appendix B-6 for oral exposures. Table 5-21 presents the human equivalent IURs for b oth site-specific risks and composite risks from multiple tumor types observed in each se x of Sprague-Dawley rat exposed to AN using the internal dose metric, CEO concentration i n blood (AUC for 24 hours).

Table 5-21. Estimated human equivalent composite I URs based on tumor incidence in AN-exposed rats and predicted CEO-AUC levels in blood

Rat strain and gender Tumor sites included Site-specific IUR a (mg/m 3 ) -1 Composite IUR (mg/m 3 ) -1 Sprague-Dawley male
Intestine 0.017
CNS 0.032 Zymbal gland 0.017 Tongue 0.012 6.8 × 10 -2

Sprague-Dawley female
CNS 0.031 Zymbal gland 0.015 Mammary gland 0.017 5.7 × 10 -2

a These site-specific IURs are taken from the last co lumn of Table 5-18.



### From the inhalation bioassay, male rats showed sta tistically significant elevated tumor incidences at four sites (i.e., intestine, CNS, Zym bal gland, and tongue), while female rats showed statistically significant elevations at thre e tumor sites (i.e., CNS, Zymbal gland, and mammary gland), when exposed to AN via inhalation f or 2 years. Under the assumption that tumors at these sites are statistically independent , the estimated composite IUR in male rats was
6.8 × 10 -2 

### per mg/m 3 

### , approximately 2 times higher than the site-specif ic IUR estimate of 3.2 × 10 -2 

### per mg/m 3 

### based on the most sensitive single site in males (i .e., CNS). For female rats, the composite IUR was 5.7 × 10 -2 

### per mg/m 3 

### , about 2 times higher than the site-specific estim ate of
3.1 × 10 -2 

### per mg/m 3 

### from the most sensitive single site in females (i.e ., CNS). These unit risks should not be used with exposures greater than 3 mg /m 3 

### (the lowest POD supporting the composite risk), because above this level the unit risk cannot be expected to be an adequate approximation of the dose-response relationship. T he fitted dose-response relationship and pharmacokinetic models should be used to estimate r isk above this exposure level.

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The IUR recommended for use in estimating cancer ri sks associated with chronic inhalation exposures to AN during adult stages of d evelopment is 2 × 10 -2 

### per mg/m 3 

### (or

2 × 10 -5 

### per μ g/m 3 

### )—the value based on human data (i.e., the occupati onal epidemiology study by Blair et al., 1998). See Section 5.4.4.3 regard ing the application of ADAFs.

Previous IRIS assessment In the previous IRIS assessment, an IUR was also de rived based on human data. This IUR was based on an increase in lung cancer inciden ce in humans occupationally exposed to AN, as described by O’Berg (1980). A value of 6.8 × 10 -5 

### per μ g/m 3 

### was derived by the application of an RR model, which was adjusted for smoking and was based on a continuous lifetime equivalent of occupational exposure to AN.

5.4.4.3. Quantitative Analysis of Early Life Exposure Scenar ios The mode of action for carcinogenicity of AN is det ermined to be mutagenic (Section 4.7.3.1), which raises concern for increas ed early life cancer susceptibility. Consistent with this possibility, two studies in Sprague-Dawle y rats provide evidence of increased cancer susceptibility associated with chronic AN exposure that begins in early periods of development—a chronic-duration inhalation cancer bi oassay (Maltoni et al., 1988) and a threegeneration drinking water reproductive toxicity stu dy (Friedman and Beliles, 2002). This
evidence was summarized in Section 4.8.1. Accordin g to the Supplemental Guidance for Assessing Susceptibility from Early-Life Exposure t o Carcinogens (U.S. EPA, 2005b), “when developing quantitative estimates of cancer risk, t he Agency recommends integration of agespecific values for both exposure and toxicity/pote ncy where such data are available and appropriate” (also see Box 5 in Figure 3 in U.S. EPA [2005b]). The available evidence is
considered below.

5.4.4.3.1. Summary of Maltoni et al. (1988)

. Maltoni et al. (1988) exposed pregnant SpragueDawley rats to 60 ppm AN by inhalation for 104 week s (see Section 4.2.2.2.2 for a complete description). In addition, the offspring of these dams were exposed to AN starting at GD 12 for a
total of either 15 or 104 weeks. All animals were observed until natural death. As noted in Section 4.2.2.2.2, Maltoni et al. (198 8) reported statistically significant
increases in tumor incidences for both male and fem ale offspring exposed for 104 weeks compared with their controls. Female offspring sho wed statistically significant increases in malignant mammary tumors, encephalic gliomas, and e xtra-hepatic angiosarcomas, while male offspring showed statistically significant increase s in encephalic gliomas, Zymbal gland carcinomas, and hepatomas. While there were no sta tistically significant increases for the exposed dams, their responses were slightly increas ed over background for most of these sites— mammary tumors at 2.3% extra risk, encephalic gliom as at 5.6%, extra-hepatic angiosarcomas at

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1.9%, and Zymbal gland tumors at 3.8%. No hepatoma s were observed in the dams. These
results are summarized in Table 5-22. Note that th ere were no concurrently exposed or control adult male rats with which to compare the male offs pring incidences; comparisons with the female adult data involve assuming that adult male responses would have been concordant. Although this profile of responses is similar to th at seen for the female rats in Quast et al. (1980b), 2 

### the Quast study was not considered to be a suitabl e baseline for analyzing the male offspring responses. For offspring exposed for a total of 15 weeks, alth ough there were no statistically significantly elevated tumor incidences at any of t he evaluated sites, the responses at these sites were elevated over respective controls and were con sistent with a linear or even supralinear increase in response with increasing length of expo sure to 60 ppm. Figure 5-3 shows the responses for both sets of offspring and the dams f or the sites with statistically significant responses after chronic exposure. Note that while the extra-hepatic angiosarcoma response in the male offspring was not statistically significant fo r either exposure group, the responses were of a similar magnitude to the response of the female off spring exposed for 104 weeks. Although the study did not have sufficient power to find individ ual group responses of about 5% and below statistically significant, the mostly statistically significant trends and their consistency across sites, as well as across sexes for the angiosarcoma s, add weight to the overall conclusion of increased early-life susceptibility to the carcinog enicity of AN.

2 Assuming a continuous equivalent lifetime exposure concentration of 12.1 ppm for the administered conc entration in the Maltoni et al. (1988) study, dose-response r elationships developed from the Quast et al. (1980b ) inhalation study (without considering pharmacokinetics) predic t a similar incidence profile for the adult female rats, at about 2% extra risk predicted vs. 2.3% observed for mamma ry tumors, 10 vs. 5.6% observed for gliomas, and 0 % predicted vs. 1.9% observed for extra-hepatic angio sarcomas. The differences between the female adult rats in the two studies are not large and can be explained by d ifferences between animal colonies and husbandry pr actices, including diet. This analysis provides some assura nce that any early-life susceptibility estimates de rived from Maltoni et al. (1988) are compatible with the unit risks derived from the Quast et al. (1980b) bioassa y.351 DRAFT - DO NOT CITE OR QUOTETable 5-22. Tumor incidences in Sprague-Dawley rats following inhalation exposure to 60 ppm AN for 104 weeks,starting either in utero (GD 12) or as adults at 13wks of ageLength of exposure to 60 ppm0 weeks (control) 15 weeks 104 weeksTumor siteAge at start ofexposurex/na% x/na% Extra riskx/na% Extra riskTrend testp-valuebRatio ofGD 12 and 13-weekgroups’extra risksat 104 weeksFemale ratsGD 12 8/149 5.4 4/60 6.7 1.4 9/5416.7 11.9 0.008Malignant mammarytumors13 wks 2/60 3.3 – – – 3/54 5.6 2.3 >0.055.1GD 12 2/149 1.3 2/60 3.3 2.0 10/5418.5 17.4 <0.001Encephalic gliomas13 wks 0/60 0.0 – – – 3/54 5.6 5.6 >0.053.1GD 12 0/149 0.0 1/60 1.7 1.7 3/545.6 5.6 0.005Extrahepaticangiosarcomas13 wks 0/60 0.0 – – – 1/54 1.9 1.9 >0.053.0Male ratsGD 12 2/158 1.3 3/60 5.0 3.8 11/67 16.4 15.3 <0.001Encephalic gliomas13 wksc0/600.0– – –3/54 5.6 5.6 >0.052.8GD 12 2/158 1.3 4/60 6.7 5.5 10/67 14.9 13.8 <0.001Zymbal glandcarcinomas13 wks 1/60 1.7– – –3/54 5.6 3.8 >0.053.5GD 12 1/158 0.6 1/60 1.7 1.0 5/67 7.5 6.9 0.002Hepatomas13 wks 0/60 0.0– – –0/54 0.0 0.0 >0.05NAGD 12 1/158 0.6 3/60 5.0 4.4 3/67 4.5 3.9 >0.05Extrahepaticangiosarcomas13 wks 0/60 0.0 – – – 1/54 1.9 1.9 >0.052.1ax = number of animals with specified tumor, n = number of animals at start of exposure.bCochran-Armitage trend test for datasets with 3 ormore groups (early-life exposures); Fisher’s exacttest otherwise (adult exposures).cValues in italics rely on adult female rat data; nomale rats were exposed starting at age 13 wks in this study.Source: Maltoni et al. (1988).

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Error bars denote 95% CIs for each response.

Figure 5-3. Comparison of tumor responses to inhal ation exposure of acrylonitrile, by age at start of exposure (offspr ing at GD 12, adults at 13 weeks), sex, and length of exposure, for Sprague -Dawley rats (Maltoni et al., 1988). Gliomas

0.00 0.05 0.10 0.15 0.20 0.25 0.30

-10 0 10 20 30 40 50 60 70 80 90 100 110 Weeks of exposureProportion responding female offspring female adults male offspring Malignant mammary tumors

0.00 0.05 0.10 0.15 0.20 0.25 0.30

-10 0 10 20 30 40 50 60 70 80 90 100 110 Weeks of exposureProportion responding female offspring female adults

Extra-hepatic angiosarcomas

-0.05 0.00 0.05 0.10 0.15 0.20 0.25 0.30

-10 0 10 20 30 40 50 60 70 80 90 100 110

Weeks of exposureProportion responding female offspring female adults male offspring

Hepatomas

0.00 0.05 0.10 0.15 0.20 0.25 0.30

-10 0 10 20 30 40 50 60 70 80 90 100 110 Weeks of exposureProportion responding male offspring female adults Zymbal's gland tumors

0.00 0.05 0.10 0.15 0.20 0.25 0.30

-10 10 30 50 70 90 110 Weeks of exposureProportion responding male offspring female adults

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Figure 5-3 shows linear trends with increasing leng th of exposure among the offspring for malignant mammary tumors (females), gliomas (ma les and females), extrahepatic angiosarcomas (females) and hepatomas (males), whil e supralinear trends are suggested for extrahepatic angiosarcomas and Zymbal gland tumors in males. Linear trends suggest that offspring responses to the 15-week exposure are pro portional to offspring responses resulting from the chronic exposure; that is, that the expect ed response is about 1/7 (15 weeks/104 weeks) of the response to chronic exposure starting in ute ro. The overall response after 104 weeks of exposure is markedly higher than that of the chroni cally exposed adult rats, suggesting that once the susceptible process (or processes) has started it continues well into adulthood. For each site,
the ratios of the extra risk associated with chroni c exposure starting at GD 12 relative to starting at age week 13 ranged from about 3 to 5 for individ ual sites in female rats, supported by a factor of 3 for gliomas in male rats (see Table 5-22). In contrast, the supralinear trends suggest greater than proportional susceptibility in the early-life period which decreases over time, or whi ch does not occur after the early-life period, as possibly illustrated by the male offspring angio sarcomas. On the other hand, the 15-week period used in this study includes a nontrivial per iod that cannot be considered early-life, given that rats are generally considered sexually mature by about 8 weeks of age. Consequently the magnitude of the early-life sensitivity, at least f or two tumor sites, may be underestimated by
these data without further characterization of the most sensitive timeframe. The low numbers of responses from the 15-week exposures (1–4 offspring and 0–3 adults responding per site) likely impact the resolution of early-life susceptibility estimates for these sites. From an overall point of view, however, note that the 15-week responses c onsidered collectively are generally similar to the female adult responses following 104 weeks o f exposure. Because these early-life responses result from sevenfold less exposure, they demonstrate approximately 7 times (or approximately one order of magnitude) more sensitiv ity than the adult responses.

5.4.4.3.2. Summary of Friedman and Beliles (2002). Supporting evidence of increased earlylife susceptibility was also seen in the three-gene ration reproduction study reported by Friedman and Beliles (2002). There were statistically signi ficant increases in Zymbal gland carcinomas and astrocytomas after approximately 51 weeks of ex posure to 500 ppm AN in drinking water for F1 Sprague-Dawley female rats relative to F1 co ntrols, while the incidences for F0 female rats were not significantly elevated at 500 ppm. T he incidences for F2 female rats, exposed in utero like the F1 females, were not considered to b e significantly elevated. Section 4.2.1.2.8 provides details of the study design, and Table 5-2 3 summarizes the results.

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Table 5-23. Tumor incidences in female Sprague-Daw ley rats exposed to AN in drinking water for approximately 46 weeks, st arting either in utero or at 5 weeks of age

Tumor incidence, and percent, at AN in drinking water, ppm
Tumor site Generation 0 100 500 Trend test p -value a Ratio of

early life + adult to adult extra risks at 500 ppm F0 (adult exposure) 0/19 (0%) 1/20 (5%) 2/24 (8%) 0 .247 –
F1b 0/20 (0%) 1/19 (5%) 4/17 (24%) 0.005 2.8
F2b 0/20 (0%) 1/20 (5%) 1/20 (5%) 0.506 – Brain astrocytomas

F1b + F2b 0/40 (0%) 2/39 (5%) 5/37 (14%) 0.007 1.8

F0 (adult exposure) 0/19 (0%) 0/20 (0%) 2/24 (8%) 0 .036 –
F1b 0/20 (0%) 2/19 (11%) 3/17 (18%) 0.088 2.1
F2b 0/20 (0%) 0/20 (0%) 3/20 (15%) 0.007 1.9 Zymbal gland

F1b + F2b 0/40 (0%) 2/39 (5%) 6/37 (16%) 0.005 2.0

a Cochran-Armitage test for linear trend.

Sources: Friedman and Beliles (2002); Litton Bione tics (1992).



### Ratios of extra risks of astrocytomas and Zymbal gl and tumors were estimated for the 500 ppm F1b and F2b groups if there was a statistic ally significant linear trend. These results suggest an increased early-life cancer susceptibili ty of about two- to threefold at the high dose. However, these results do not support a quantitativ e estimate of relative susceptibility because several factors contribute to underestimating any s usceptibility. First, with only 20 animals per treatment group, this study had limited power to de tect tumor increases, relative to the Maltoni et al. (1988) study and most other carcinogencity stud ies, with the consequence that any increased susceptibility at the low dose (100 ppm) may be les s readily apparent. For example, an apparent effect of 0/20 is consistent with a tumor response as high as 17%, the 95% UCL on a response of
0/20. Second, while it is notable that tumors were observ ed as early as they were, after no more than 51 weeks without another year of follow-up, th ese data do not inform lifetime risk estimates adequately. Although cancer incidence is expected to increase with increasing age (Doll, 1971), dose-response relationships starting at different a ges may not be parallel. Given the short exposure and follow-up in this study, the data from this group are better considered as supporting early-life susceptibility qualitatively.

5.4.4.3.3 Analysis to support estimation of early-life susc eptibility adjustment factors. In summary, two data sets support the conclusion of in creased susceptibility to carcinogenicity with AN exposure in early life. One data set conducted by Maltoni et al. (1988), in female rats with

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chronic exposure starting in early life or starting as adults, provides a sufficient basis for developing quantitative estimates of susceptibility . Due to the lack of adult male referent groups (control or exposed), the male offspring data provi de support for early-life susceptibility. The female data supported point estimates for susceptib ility adjustment factors of 5, based on malignant mammary tumors, and 3, based on gliomas o r extra-hepatic angiosarcomas. In other words, cancer potency for specific tumor sites foll owing chronic exposure to 60 ppm AN appears to be three- to fivefold higher if exposure starts in early-life rather than during adulthood. Before recommending ADAFs based on these data, imp ortant considerations include the impact of experimental variability and overall risk encompassing multiple tumors. Given the incomplete understanding of the operant modes of ac tion, it is unknown whether the tumor types observed in the Maltoni et al. (1988) study are ind ependent of each other. They were not reported as metastases, which would clearly not be independent. Under the assumption that these tumor sites are independent, an analysis was undertaken focusing on overall risk as well as characterizing the impact of experimental variabili ty. A Monte Carlo analysis was conducted to obtain the distribution of the ratio of combined
extra risk from the three tumor sites for the chron ically exposed female offspring to the analogous combined extra risk from adult-only expos ure. For each simulation, the outcome in each control and dose group was simulated by drawin g a binomial B( n,p ) random variable with

n equal to the number of animals in the group and p obtained by dividing number of animals with tumor in the original dataset by the total number o f animals. Since data for only one dose group was available for each tumor site, the individual b inomial probabilities for this simulation run were estimated by dividing the number of animals wi th tumors by the total number of animals, rather than by fitting a dose-response model to the responses for each pair of control and exposed group. Then the risks from the three individual tu mor sites were combined assuming independence of different tumor outcomes, as noted above. The standard formula for the probability of the union of multiple sets was used to compute the combined probability of tumor (dose d = 60 ppm was the same for all three tumor t ypes):

P AorBorC 

### (d) = P A 

### (d) + P B 

### (d) + P C 

### (d) – P A 

### (d) * P B 

### (d) – P A 

### (d) * P C 

### (d) – (1)

P B 

### (d) * P C 

### (d) + P A 

### (d) * P B 

### (d) * P C 

### (d).

Then the combined extra risk was computed as:

ER AorBorC 

### (d) = [P AorBorC 

### (d) – P AorBorC 

### (0)]/ [1 - P AorBorC 

### (0)]. (2)

Only the individual extra risks where probabilities in the control group did not exceed the probability in dose group were retained, in order n ot to create negative estimates of extra risk. If

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only two tumor results were combined in a particula r realization, the combined probability in equation (1) was adapted for two tumors

P AorB 

### (d) = P A 

### (d) + P B 

### (d) – P A 

### (d) * P B 

### (d).

Finally, the ratio of the extra risks is given by:

ER AorBorC 

### (d | adult & early-life)/ ER AorBorC 

### (d | adult only) (3)

was calculated and retained for each simulation. T he simulation was repeated 10,000 times and
results are summarized in the first row of 5-24. S imulations were done in R language (www.r-project.org). Because some of the control groups did not have an y observed tumors, the approach above assigns no variability to such groups. As hi storic background rates are not available, a sensitivity analysis was conducted to evaluate if a ssigning a small probability of tumor (1/2n) to these control groups and the resulting variability influences the distribution of the ratio (eq 3). The simulations were performed as described above. Results are summarized in the second row
of Table 5-24.

Table 5-24. Overall extra risks of multiple tumor incidence, for chronic exposure beginning either in early-life or in adult hood; based on SpragueDawley rats exposed to AN

Number of simulations with k tumors retained Percentiles of the distribution of the ratio of extra risks Treatment of 0% tumors in referent groups Start of

exposure period k = 3 k = 2 k = 1 5th Median Mean a 95 th
Adult 7,578 2,422 0 0.037 0.095 0.100 0.178 Early-life 9,903 97 0 0.204 0.314 0.314 0.423 Zero background as observed Ratio 1.543 3.232 4.219 (9,957) 9.628

Adult 5,483 3,923 574 0.021 0.085 0.089 0.166 Early-life 9,685 314 1 0.199 0.311 0.311 0.421 Zero background replaced by 1/2n b Ratio 1.610 3.594 6.373 (9,929) 15.627

a For calculation of means, the figure in parentheses indicates the number of finite ratios; the other p ercentiles were based on 10,000 simulations.
b For n = 60, 1/2n = 1/120 = 0.0083.

Source: Maltoni et al. (1988).



### Extra risks for chronic exposure starting in early- life are not sensitive to the assumption regarding background probabilities, as shown by the similar percentiles for both cases. But the

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extra risks for adult-only exposure decrease slight ly when some variability at 0% response is assumed, resulting in slightly higher ratios. Beca use the second analysis is more realistic, allowing a background response in two of the sites and addressing plausible variability, it is used to derive the data-specific adjustment factors. Ni nety-five percent of the values fell between
1.6 and 15.6. Note that the analogous composite adjustment factor resulting from the default factors in the SG for chronic exposure beginning in early life is 1.7; the analysis provides a distribution of adjustment factors with about 95% of the possible v alues being larger than the default adjustment factors. The median and mean ratios, at 3.6 and 6. 4, respectively, are far enough apart to indicate a nonsymmetrical distribution. The median of 3.6 is a better estimate of central tendency in this case. Recommended early life susceptibility factors. The derived early-life susceptibility factor of 3.6 is to be used in assessing oral or inhalatio n exposures to AN that begin at birth (or earlier) and extend to or beyond 70 years of age. When expo sures involving shorter periods of early-life exposure to AN are assessed, a modification consist ent with the SG framework is recommended,
as outlined in this section. The available information for identifying appropria te ADAF(s) to apply to specific earlylife periods is limited. While U.S. EPA’s SG (U.S. EPA, 2005b) separates the pre-adult period into two age ranges, 0−<2 and 2−<16 years, the Malt oni et al. (1988) study design did not address age periods corresponding to these windows of human susceptibility. The offspring exposed for 15 weeks were about 14 weeks old at the time their exposure stopped (estimated by subtracting 9 days (GDs 21−12) from 15 weeks); fema le rats reach sexual maturity at about 8 weeks (35 days), so 14 weeks in rats would correspo nd to a higher age in humans than 16 years. Therefore, the Maltoni et al. (1988) data can suppo rt only one ADAF for the entire pre-adult
window. An ADAF for the pre-adult window can be derived fr om the derived lifetime estimate by treating it as a weighted sum of ADAFs for separate windows of susceptibility, consistent with the general framework in the SG for applying the de fault ADAFs, using a simplification of the SG framework for estimating human risk from exposur e including early-life periods:

ADAF for lifetime exposure starting at birth = 3.6 = [ADAF P 

### × t P 

### + ADAF A 

### × (70 yr – t P 

### )]/70, (4)

where the subscripts P and A denote pre-adult and a dult, respectively, and t P 

### = duration (in years) of exposure during the pre-adult period. By conven tion, ADAF A 

### must be 1. With two unknowns, ADAF P 

### and t P 

### , one value must be inferred so that the other can be estimated. Because the Maltoni et al. (1988) data from offspri ng exposed for 15 weeks are consistent with a 10-fold increased sensitivity relative to rats expo sed only as adults (see Figure 5-3 and accompanying text), and the default ADAF of 10 in t he SG for the most sensitive period (0–

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<2 years of age) is also 10, an ADAF P 

### of 10 seems a reasonable starting point. Substitu ting these two ADAFs in (eq 4) and solving for t P 

### leads to an empirical age cutpoint of 20 years. This cutpoint is necessarily somewhat arbitrary—it is not an assertion that 14 weeks of age in a rat is equivalent to 20 years in a human—b ut appears to be a straightforward interpretation of the available data. Other interp retations are possible, such as that sensitivity at the earliest ages (i.e., before 2 years of age) cou ld be relatively higher than later pre-adult ages, but further manipulation of the AN-specific data to align more closely with the SG early-life periods and relative sensitivities (i.e., that the earlier period might be about 3 times more sensitive that the second pre-adult period) is judg ed to be too speculative. Illustrations of applying the derived ADAFs for es timating human cancer risk from lifetime exposures starting at birth are provided i n Table 5-25.

Table 5-25. Application of ADAFs for estimating hu man cancer risk from 70-year oral or inhalation exposures to AN from age s 0 to 70

Age Group (yrs) Duration adjustment ADAF Age group risk For oral exposure to 0.01 mg/kg-d, with oral slope factor of 5 (mg/kg-day) -1 for adult lifetime exposure: 0–<20 20 yrs/70 yrs = 0.29 10 0.14 a 20–70 50 yrs/70 yrs = 0.71 1 0.04 Total: 0–70 70 yrs/70 yrs = 1 3.6 0.18 For inhalation exposure to 1 mg/m 3 , with IUR of 2 

### × 10 -2 (mg/m 3 ) -1 

### [ or 2 

### × 10 -5 ( μ g/m 3 ) -1 

### ] for adult lifetime
exposure: 0–<20 0.29 10 0.057

20–70 0.71 1 0.014

Total: 0–70 1 3.6 0.072

a Age group risk = duration adjustment × ADAF × expos ure × CSF or unit risk.



### Equation (4) provides the framework for estimating risks from exposures involving shorter earlylife periods. Two examples are provided:

• If calculating the cancer risk for a 30-year exposu re to a constant oral exposure level of 0.01 mg/kg-day from ages 0 to 30, the duration adju stments would be 20/70 and 10/70, and the age group risks would be 0.14 and 0.01, res ulting in a total risk estimate of 0.15.

• If calculating the cancer risk for a 30-year exposu re to a constant oral exposure level of 0.01 mg/kg-day from ages 20–50, the duration adjust ments would be 0/70 and 30/70, and the age group risks would be 0 and 0.02, resulting in a total risk estimate of 0.02.

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5.4.4.3.4. Uncertainties in early-life susceptibility estimate s. Unlike many of the studies supporting the default adjustment factors recommend ed in the SG, the available early-life studies for AN include gestational exposure. The pharmacod ynamics and pharmacokinetics of AN during the perinatal period are not well understood , nor are the time frame and nature of the response leading to the apparent susceptibility; it is possible that gestational exposure is a necessary component of the increased susceptibility

. Regarding the level of exposure, it is not known wh ether perinatal exposure was comparable to adult exposure. If perinatal exposur e was greater than adult exposure, the apparent susceptibility would be at least partly at tributable to higher exposure; if lower, the apparent susceptibility would be underestimated.
Other uncertainties associated with the recommended data-derived early-life susceptibility adjustment factor include: (1) whet her the relative susceptibility is dosedependent, leading to different values for other pa rts of the dose-response range; (2) whether the relative susceptibility estimated from female data characterizes the relative susceptibility for males; note particularly the observation of hepatom as in male offspring exposed chronically beginning in early life; (3) the relevance of extra polating these results to humans; and (4) possible underestimation of risk associated wit h the lack of knowledge of individual times of death if tumors in the exposed animals tended to oc cur earlier than in control animals or if tumors in the animals exposed perinatally tended to occur earlier than in those exposed starting at age 13 weeks. Some uncertainty in cancer risk estimates can gene rally be characterized by fitting a dose-response model to the incidence data in order to provide a CI on the risk estimate. In this case, however, there was only one exposed group for each exposure pattern. Other methods for characterizing the statistical uncertainty in these data are currently being investigated.

5.4.5. Uncertainties in Cancer Risk Values Risk estimates have inherent uncertainties. This subsection discusses the uncertainties that may be associated with cancer risk values for oral and
inhalation cancer assessments.

5.4.5.1. Oral Cancer Assessment
Uncertainties related to the oral cancer assessment are discussed below and summarized in Table 5-26 and Figure 5-4.

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Table 5-26. Summary of uncertainty in the AN oral cancer risk assessment

Consideration/ approach Impact on cancer risk estimate Decision Justification
Low-dose extrapolation procedure The selected model does not

represent all possible models one might fit, and other models could conceivably be selected to yield more extreme results consistent with the observed data, both higher and lower than those included in this assessment. Multistage model to determine POD, linear low-dose extrapolation from POD. Available mode of action data support direct mutagenicity as the key mode of action and low-dose linear extrapolation approach. EPA’s Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005a): mutagens “are assessed with a linear approach.” Mutagenic mode of action functions systemically at multiple tumor sites. PBTK model Oral slope factor based on

PBTK modeling and internal CEO levels is about sixfold higher than slope factor based on the default approach. EPA- revised model was used. The revised PBTK model includes EH activity in rats and provides better estimates of internal dose.

Dose metric Alternatives could decrease

oral slope factor (e.g., use ofAN-AUC instead of CEOAUC could lower slope factor by 30-fold). CEO-AUC was used. CEO is the reactive metabolite that binds to DNA and initiates tumor formation. AN is not the causal agent for cancer.

Statistical uncertainty at POD Oral slope factor will be

reduced 1.3-fold if BMD used as POD instead of BMDL. BMDL (approach for calculating reasonable upper bound). Limited size of bioassay results in sampling variability; BMDL is lower 95% confidence limit of BMD.

Bioassay Oral slope factor would be

the same if study on F344 rats were used (Johannsen and Levinskas, 2002b). Quast (2002) study on Sprague-Dawley rats was used. Quast (2002) has separate interim sacrifice groups and examined more endpoints than the Biodynamics (1980c) data sets. Species/gender combination Human risk could decrease

or increase, depending on relative sensitivity. Oral slope factor derived from study onfemale SpragueDawley rats. It was assumed that humans are as sensitive as the most sensitive rodent gender/species tested; true correspondence is unknown. The carcinogenic response occurs across species. Generally, direct site concordance is not assumed; consistent with this view, some rodent tumors are not found in humans (e.g., Zymbal’s gland tumors, Harderian gland tumors) and rat and mouse tumor types also differ. Human population variability in metabolism and response/sensitive subpopulations Low-dose risk increase to an

unknown extent. Considered qualitatively. Increased early life susceptibility demonstrated in rat studies. Variability in human susceptibility likely exists due to differences in microsomal CYP2E1 activities and possibly GST activity.

### 361 DRAFT- DO NOT CITE OR QUOTE 2.8 5.0

3.1

1.9

0.40 1.03

0.68
0.36

0 1 2 3 4 5 6

Male Sprague-Dawley

Rats Female SpragueDawley Rats Male F344 Rats Female F344 Rats

Sex/Strain/SpeciesOral Cancer Slope Factor(mg/kg-day)-1 CSF - CEO in Blood
CSF - Administered Dose



### Figure 5-4. Comparison of composite oral CSFs deri ved from tumor incidence data in four different sex/strain/species of rats exposed chronically to AN. For each sex/strain/species combination, tw o different dose metrics were employed: (1) CEO concentration in blood, and (2) human equivalent administered dose.

Choice of study Several bioassays by the oral route are available. The 2-year drinking water studies of Sprague-Dawley rats (Quast, 2002; Quast et al., 198 0a) and F344 rats (Johannsen and Levinskas, 2002a; Biodynamics, 1980a) were selected as princip al studies. These two studies have sufficient numbers of animals, investigate a thorou gh set of endpoints, and are considered well conducted. The tumor types observed and incidence of treatment-related tumors were similar in these two studies. Moreover, cancer risk estimates from these two studies differed only by a
factor of 1.5. Similarities in these results incre ase the level of confidence of estimated cancer risk. The Quast (2002) study of Sprague-Dawley rat s investigated more endpoints and is therefore a slightly stronger study.

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PBTK model Use of the PBTK model to extrapolate from rodents to humans also introduces some uncertainty. An extensive quantitative analysis of the PBPK model uncertainty is presented in Appendix D. Briefly, PBPK models are computational tools used to predict chemical/drug disposition and are comprised of three distinct typ es of information: physiological, physicochemical, and biochemical. The physiologica l data are independent of chemical-specific data, and describe such parameters as organ volumes and blood flows. Physicochemical parameters are chemical-specific and specify parame ters, such as PCs or permeability. Biochemical parameters define the rates of chemical transformation or binding. Because the physiological data are considered to be well-charac terized, analysis focused on uncertainties in the chemical-specific parameters employed in the PB PK model used to predict AN dosimetry in humans, which is adapted from that of Sweeney et al . (2003). (Only a small number of (metabolic) parameters were changed in the EPA's ad aptation.) Uncertainty analysis and
characterization of the human model lead to the fol lowing conclusions.

• Blood:air and tissue:air PCs as measured directly ( in rodents) vs. estimated by a computational tool were compared, and the impact on model predictions of peak AN and peak CEO levels in brain and blood was found to be less than 30% (difference between predictions using the alternate sets of PCs).

• Comparison of model predictions to the limited huma n data of Jakubowski et al. (1987) shows that the model over-predicts the inhalation r espiratory retention measured (predicted ~ 70%; measured 44–58%). This over-predi ction may be due to the fact that the model does not fully describe the exposure appa ratus (which can introduce additional airway “dead-space”) or that the model does not des cribe gas absorption/desorption in the conducting airways that can reduce uptake rates. H owever, since the error (if any) is in the direction of over-prediction of uptake, the err or is health-protective.

• Once absorbed, the model predicts that 8.4% of AN i s converted to CEO and then hydrolyzed, while 30% is converted to CEO and then conjugated with GSH. These
values bracket the observation of 16.3% of retained AN being excreted in urine as “CEO” (after acid extraction). Thus, this limited observ ation is in line with model predictions subsequent to AN predictions, though the exact leve l of agreement or error cannot be
determined due to the distinction between observed quantity (CEO in urine) and what the model predicts (CEO metabolic rates).

• The PBTK model over-predicts CEO levels in the rat at early time-points after i.v. injection (Figure 3-3) and in blood and brain at al l time points measured after oral exposure (Figure 3-5a). Kedderis et al. (1996) sug gest that the overestimation of CEO by the rat model at the early time points (which also occurs in the EPA’s revision) may be due to an intrahepatic first pass effect, as occurs with other epoxides formed in situ from

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their parent olefins (Filser and Bolt, 1984). Howe ver, this explanation is unlikely and a more plausible explanation is that the model does n ot account for time-dependence in GSH levels. Inclusion of GSH dynamics would be a m uch more significant and intensive change to the model structure than single variation implemented here (addition of EH to the rat model with parameter re-estimation) and so has not been considered.

• Parametric sensitivity analysis of human prediction s showed a shift in importance between the EH and GSH pathways for CEO elimination from being approximately equal in the implementation of Sweeney et al. (2003) to l ower significance for EH (now low but significant) and high significance for GSH with the revised parameters. The oxidation of AN to CEO has a significant effect on AN predictions but only a small effect on CEO in both model versions, reflecting the high dependence of CEO concentrations on CEO metabolic removal. Not surprisingly, brain: tissue PCs significantly affect predictions in brain tissue, and the rate constant for oral absorption affects peak AN concentrations in blood, but not the AUC. While th e human parameters are largely derived from human in vitro data, which gives a muc h higher confidence than would occur had they only been extrapolated from rats, th e high dependence of CEO concentrations on GSH conjugation rates, together w ith the hypothesis above regarding the lack of GSH dynamics in the model, point to tha t pathway description in particular as being the greatest source of quantitative uncertain ty.

• Estimated coefficients of variation for predicted c oncentrations in brain and blood after inhalation exposure are ~0.6–0.7 for AN and 0.9–1.2 for CEO; after oral exposure these
are 0.8–0.9 for AN and 0.7–1.0 for CEO. Based on t hese values, the human model predictions are expected to be accurate to within a factor of approximately 3, which is the standard assumption for pharmacokinetic variability among humans.

It can be noted that the oral CSFs are larger when based on blood levels of CEO versus
blood levels of AN. The VmaxC/Km for AN oxidation in humans is estimated to be about 10 times higher than in the rat. AN enzymatic GSH conjugation is estimated to be 1.5 times higher in the rat, but the 2 nd 

### -order removal constant is the same and the GSH tis sue levels are roughly the same (and lower in the larger tissue gr oups). The result, for example, with a steady oral “infusion” of 30 mg/kg-day, is that AN is remo ved somewhat faster overall, leading to steady-state blood level of 0.114 mg/L in the human vs. 0.151 in the rat. However, a much higher portion of this goes to CEO in the human yie lding a CEO blood level of 0.297 vs. 0.013 mg/L in the rat. Thus, CEO:AN = 0.088 in the rat and 2.6 in the human so that the CEO-based risk estimate is higher than the AN-based estimate.

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Dose metric AN is activated by CYP2E1 into its reactive metabol ite, CEO, which binds to DNA and initiates tumor formation. Therefore, AUC CEO conc entration in blood was selected as the internal dosimetric for PBTK modeling. AN is not a nticipated to be the causal agent for carcinogenesis. Uncertainty in the risk estimate r elated to the dose metric is primarily associated
with PBTK model estimation.

Statistical uncertainty at the POD Parameter uncertainty within the chosen model refle cts the sample size of the cancer bioassay. For the multistage model applied to this data set, there is a relatively small degree of uncertainty at the BMDL 10 

### (the POD for linear low-dose extrapolation)

, 

### which is approximately
1.4-fold lower than the BMD 10 

### (Appendix B, Table B-37). The highest value was se lected in order to provide a reasonable upper-bound risk esti mate. With regard to the combined risk estimate, under th e assumption of independence of the tumor type/site considered, no additional uncertain ty is added to the estimated POD. Each combined estimate is a statistically rigorous resta tement of the statistical uncertainty associated
with the risk estimates derived from the individual sites. The only assumption in the combining tumors approach is independence of tumors. This as sumption is consistent with NRC (1994)
recommendations.

Choice of low dose extrapolation approach The mode of action is a key consideration in decidi ng how risks should be estimated for low-dose exposure. The mode of action for cancer e ffects of AN is discussed extensively in Section 4.7.3.1 and is determined to be mainly due to direct mutagenicity. Other modes of action are plausible, but the evidence suggests they may n ot be key to the carcinogenicity of AN. The pattern of tumors is consistent with DNA-reactive c hemicals. When the mode of action is determined to be direct mutagenicity, a linear appr oach is used to estimate low-exposure risk, in
accordance with EPA’s Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005a).

Choice of species/gender No human cancer epidemiology study via the oral rou te is available. Cancer risk is estimated for both male and female rats, and cancer risk for the strain and gender with the highest risk, Sprague-Dawley females, was selected. Mammary gland tumors were observed in female rats of both studies. Although a cancer bio assay in B6C3F 1 

### mice is also available, the exposure was via gavage and no PBTK model is availa ble for mice. It was assumed that humans are as sensitive overall as rats, although the true correspondence is unknown. Site concordance is not assumed, nor is it necessary (U.S. EPA, 2005 a).

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Human population variability Heterogeneity among humans is another source of unc ertainty, in that human risk can be higher or lower than that estimated from rats, depe nding on relative sensitivity. Human genetic polymorphisms in CYP2E1 activities likely contribut e to variability in susceptibility to the toxic effects of AN (see Section 4.8.4.1). In addition, increased early-life susceptibility was demonstrated in two studies in rats exposed gestati onally (see Section 5.4.4.3).

5.4.5.2. Inhalation Cancer Assessment
Uncertainties related to the IUR assessment are dis cussed below and summarized in Table 5-27 and Figure 5-5.

Table 5-27. Summary of uncertainty in the AN inhal ation cancer risk assessment

Consideration/ approach Impact on cancer risk

estimate a Decision Justification Choice of study Cancer risk estimate

could increase because only lung cancer deaths evaluated. Lung cancer mortality and exposure data from Blair et al. (1998) study was used to derive IUR. IUR derived from best available cancer epidemiological study of AN exposed workers has fewer inherent uncertainties than IUR derived from rat study (Quast et al., 1980b).
Low-dose extrapolation procedure The selected model does

not represent all possible models one might fit, and other models could conceivably be selected to yield more extreme results consistent with the observed data, both higher and lower than those included in this
assessment. Low-dose linear. EPA’s Guidelines for Carcinogen Risk Assessment

(U.S. EPA, 2005a ): mutagens “are assessed with a linear approach.”

Statistical uncertainty at POD IUR would be reduced

fourfold if BMD used as POD instead of BMDL. BMDL, approach for calculating reasonable upper bound. Limited size of study results in sampling variability; BMCL is lower 95% confidence limit on EC 01 . Choice of species/gender IUR estimated from

exposed male and female workers. IUR estimated from entire cohort was used. No apparent gender difference between male and female workers; male and female rats were also similar. Human population variability in metabolism and response/sensitive subpopulations Low-dose risk for general

population can increase to an unknown extent due to underestimation of human variability (healthy worker effect). Semi-parametric Coxregression model with timedependent covariates was used. The Cox model allows inclusion of individual exposure histories and utilizes internal controls, thus avoiding confounding by the healthy worker effect. Increased early-life susceptibility demonstrated in rat studies. Human variability in susceptibility likely exists due to differences in microsomal CYP2E1 activities, and possibly GST activity.

### 366 DRAFT- DO NOT CITE OR QUOTE 0.070

0.060

0.0040 0.0035 0.020

0.000 0.010 0.020 0.030 0.040 0.050 0.060 0.070 0.080 0.090 0.100

Male Sprague-Dawley Rats Female Sprague-Dawley Rats H umans Exposed Occupationally

Sex/Strain/SpeciesInhalation Unit Risk(mg/m3)-1 IUR - CEO in Blood
IUR - Human Equivalent Administered Concentration



### Figure 5-5. Comparison of composite IURs derived f rom: (1) tumor incidence data in male and female Sprague-Dawley ra ts exposed chronically to AN, and (2) neurological effects in humans expos ed to AN occupationally. In deriving the animal-based IURs, two different do se metrics were employed: (1) predicted CEO concentration in blood , and (2) human equivalent administered AN concentration in air.

Choice of study As mentioned previously, the Blair et al. (1998) co hort study is the largest cohort assessment of the relationship between AN exposure and cancer. This study had the distinct advantage of quantifying exposure and using an inte rnal control group of unexposed workers, all factors identified as shortcomings in previous stud ies. Information on smoking history, a potential confounder when lung cancer is the outcom e of interest, was available, but only for a small subset within the Blair et al. (1998) cohort. Blair et al. (1998) limited their analysis to the white male population and noted that adjustment for smoking reduced the risk of lung cancer slightly. The data used in this assessment to deri ve the IUR included the entire cohort; consequently, the smoking history data were incompl ete for this analysis, leading to an area of uncertainty surrounding this risk estimate.

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Another source of uncertainty stems from the use of only lung cancer mortality for the derivation of the IUR. As previously described, ot her studies reported small, but not consistent, excess risks for other types of cancer (prostate, b ladder, brain cancers) associated with AN exposure. Thus, basing the IUR on only lung cancer mortality may underestimate the carcinogenic potential of AN. Further, as the IUR is based on mortality rather than lung cancer incidence, though in the case of lung cancer mortal ity is a good surrogate of lung cancer incidence, there may be potential for underestimati on of carcinogenic potential with this approach. Additional uncertainties related to the statistical analysis of these data are further discussed in Appendix B-7. Briefly, uncertainties of the statistical approach include: (1) Cox model that was fit to the data is not a biologicall y based model; (2) the estimator of the
cumulative hazard does not account for the covariat e path and hence is only an approximation; and (3) the estimate of risk is obtained using the first-order “linearized” approximation. However, obtained results are consistent with assum ptions of the first-order approximation validity.
Other uncertainties associated with the NCI/NIOSH cohort include nondifferential exposure misclassification, lung cancer misdiagnosi s among the internal controls, the relatively short follow-up period (reflected by the relatively small proportion of mortality within the cohort), and the extrapolation of continuous enviro nmental exposure from 8-hour occupational exposure without consideration of potential recover y mechanisms between daily exposures. The nondifferential exposure misclassification contribu tes to an underestimation of risk, while the impacts of short follow-up and extrapolation to a c ontinuous exposure scenario are unclear. Nonetheless, the NCI/NIOSH cohort provides the most robust data set in terms of sample size and exposure assessment for the derivation of the I UR.

Statistical uncertainty at the POD Parameter uncertainty within the chosen model refle cts the limited sample size of the cancer bioassay. For the results relying on the co hort study, the EC 01 

### is approximately fourfold higher than the LEC 01


### . For the multistage model applied to the rat data, i n support of the human-based results, there is a reasonably small degree of uncertainty a t the 10% incidence level (the POD for linear low-dose extrapolation). Composite BMC 10 

### s for overall cancer risk are approximately 1.3-fol d higher than their corresponding BMCL 10 

### s for both male and female rats. With regard to the combined risk estimate, under th e assumption of independence of the tumor type/site considered no additional uncertaint y is added to the estimated POD. Each combined estimate is a statistically rigorous resta tement of the statistical uncertainty associated
with the risk estimates derived from the individual sites. This assumption is consistent with NRC (1994) recommendations.

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Low-dose extrapolation procedure As discussed previously, the key mode of action for carcinogenicity of AN is determined to be direct mutagenicity. A linear approach is us ed to estimate low-exposure risk, in accordance
with EPA’s Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005a). Nonlinear low-dose extrapolation approach is not used since data do no t support other modes of action at this time.

Choice of species/gender A human study was selected for quantification of IU R. Both male and female workers were evaluated. A 2-year inhalation study of male and female rats was used for comparison. Estimates of IURs from the human study and from the rat studies were similar. IURs estimated from male and female rats were also similar, althou gh there was a suggestion of higher cancer risk in females associated with mammary gland tumor s.

Human population variability Heterogeneity among humans is another source of unc ertainty. Uncertainty related to human variation needs consideration, also, in extra polation from a small subset of human population to a larger, more diverse population. T he study population in Blair et al. (1998) was AN-exposed workers in the United States. To counte r the healthy worker effect, internal controls were used in the study. Available data fr om animal studies provide no evidence of gender differences in susceptibility to toxicity of AN, although no data is available regarding possible gender differences in susceptibility. Pol ymorphisms in the CYP2E1 gene that affect enzyme activity likely contribute to the variabilit y of human susceptibility towards the toxic effect of AN (see Section 4.8.4.1).

### 369 DRAFT- DO NOT CITE OR QUOTE 6. MAJOR CONCLUSIONS IN THE CHARACTERIZATION

OF HAZARD AND DOSE-RESPONSE

6.1. HUMAN HAZARD POTENTIAL AN (CASRN 107-13-1) is a colorless, flammable, and volatile liquid with a weakly pungent onion- or garlic-like odor. It is a commercially i mportant chemical used in the manufacture of acrylic and modacrylic fibers, plastics (ABS and AN -styrene resins), and nitrile rubbers and as an intermediate in the synthesis of other chemicals , such as adiponitrile and acrylamide. Exposure to airborne AN is possible for people livi ng in the vicinity of emission sources such as acrylic fiber or chemical manufacturing plants or w aste sites. AN is rapidly and nearly completely absorbed, wide ly distributed to tissues, and biochemically transformed into metabolites that are excreted in the urine and, to a much lesser extent, in feces and expired air. Two major metabo lic pathways for AN have been identified: detoxification of AN by conjugation with GSH, formi ng the urinary metabolite N-acetyl-S- (2-cyanoethyl)cysteine, and oxidation of AN to its epoxide metabolite, CEO, via CYP2E1. CEO can bind to tissue macromolecules, such as proteins and DNA. CEO can be hydrolyzed to cyanide with further transformation to thiocyanate, which is excreted in urine. Alternatively, CEO can interact with GSH, resulting in the formati on of a number of other urinary metabolites. There are no studies directly identifying health h azards in humans following oral exposures of any duration, but results from a robus t array of studies in rats and mice identify noncancer lesions in the gastric squamous epitheliu m and tumors in multiple tissues as potential health hazards to humans exposed to AN by the oral route for chronic durations. Results from cross-sectional epidemiologic studies of AN-exposed workers identify increased prevalences of neurological symptoms and adverse reproductive outc omes in occupationally exposed workers as potential health hazards from chronic inhalation ex posure. Cancer is another potential human health hazard from chronic inhalation exposure, as indicated by increased incidences of tumors at
several tissue sites in rat chronic inhalation bioa ssays. Studies of AN-exposed workers have provided no strong evidence that mortality from any type of cancer is casually related to occupational exposure, but limited evidence from th e best-designed epidemiologic study found a small, but statistically significant, increased ris k for dying from lung cancer in workers with the longest durations and highest exposures to AN. The animal toxicity database identifies hyperplasi a and hyperkeratosis of the squamous epithelium of the forestomach as the most sensitive noncancer effects associated with repeated oral exposure to AN. Following chronic oral exposu re, these lesions have been observed in rats at drinking water concentrations as low as 1–3 ppm (0.09–0.3 mg/kg-day) (Johannsen and Levinskas, 2002a, b; Biodynamics, 1980a, b). Other effects have been observed in repeatedly exposed animals, generally at higher exposure level s. These include ovarian atrophy in female

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mice exposed to doses ≥ 2.5 mg/kg-day for 2 years (NTP, 2001); chronic neph ropathy in male and female rats exposed for 2 years to 3.4 and 10.8 mg/kg-day AN, respectively (Quast et al., 1980a); gliosis in the brain of female Sprague-Dawl ey rats at 4.4 mg/kg-day (Quast et al., 1980a); decreased sperm count in male mice exposed to 10 mg/kg-day for 60 days (Tandon et al., 1988); hind-limb weakness and decreased sensor y nerve conduction velocity in male rats exposed to 50 mg/kg-day AN for 12 weeks (Gagnaire e t al., 1998); and neurobehavioral effects in male rats exposed to 4 mg/kg-day AN in drinking water for 8 or 12 weeks (Rongzhu et al., 2007). No changes in fertility index or pregnancy success were found in a three-generation study of rats exposed to drinking water doses as high as 39 mg/kg-day (Friedman and Beliles, 2002; Litton Bionetics, 1992). Mild developmental effect s were observed at 11 and 20 mg/kg-day (small deficits in postnatal pup weight or survival ) in this three-generation rat study and at 25 mg/kg-day (increased litters with pups with missing vertebrae) but not at 10 mg/kg-day in rat fetuses exposed on GDs 6–15 (Murray et al., 1978). Repeated inhalation exposure to AN in the workplac e has been associated with increased prevalence of subjective neurological symptoms, suc h as headache, poor memory, and irritability (Chen et al., 2000; Kaneko and Omae, 1992; Muto et al., 1992; Sakurai et al., 1978) and small performance deficits in neurobehavioral tests of mo od, attention and speed, auditory memory, visual perception and memory, and motor steadiness (Lu et al., 2005a). Such effects have been associated with average workplace air concentration s of 0.1 or 0.9 ppm and appear to be the most sensitive noncancer effects from repeated inhalatio n exposure to AN. Adverse reproductive outcomes, such as increased prevalences of prematur e deliveries, stillbirths, sterility, birth defects, and pregnancy complications, have been ass ociated with occupational exposure to average workplace concentrations ranging from 3.6 t o 7.5 ppm (Dong et al., 2000a; Li, 2000; Dong and Pan, 1995). SubchronicSubchronic and chro nic inhalation toxicity studies in rats identified other noncancer effects at higher exposu re levels, including nasal epithelial lesions in rats exposed to concentrations of 20 or 80 ppm for 2 years (Quast et al., 1980b), decreased nerve conduction velocity and hind-limb weakness in rats exposed to ≥ 25 ppm AN (Gagnaire et al., 1998), increased incidence of rat fetuses with miss ing vertebrae, missing ribs, or anteriorly displaced ovaries following exposure of pregnant Sp rague-Dawley rats to 80 ppm on GDs 6–15 (Murray et al., 1978), and decreased rat fetal weig ht gain following exposure of pregnant Sprague-Dawley rats to concentrations ≥ 25 ppm on GDs 6–20 (Saillenfait et al., 1993). The genotoxicity of AN has been evaluated in multi ple systems in vitro and in vivo. In addition to positive findings in blood lymphocytes, buccal mucosal cells, and sperm in five epidemiologic studies, DNA alkylation by AN was fou nd in numerous tissues in rats or mice (brain, liver, testes, forestomach, colon, kidney, bladder, and lung) treated with a single dose of AN. AN or its reactive metabolite, CEO, yielded po sitive results in in vitro mutation assays using bacteria, fungi, and insects, as well as anim al and human cell cultures. The weight of evidence from these studies suggests that AN is mut agenic after metabolic activation to CEO.

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Following EPA Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005a), AN is “likely to be carcinogenic to humans,” based predom inantly on consistent results showing that lifetime inhalation or oral exposure caused statist ically significantly increased incidence of tumors at multiple tissue sites in rats and mice. Lifetime oral exposure to AN caused increased incidences of tumors at multiple tissue sites, incl uding the brain, forestomach, and Zymbal gland,
in several rat studies and the forestomach and Hard erian gland in a gavage study in mice (NTP, 2001). Lifetime inhalation bioassays with Sprague- Dawley rats found exposure-related increases in the incidences of brain tumors, Zymbal gland tum ors, intestinal tumors, tongue tumors, and malignant mammary gland tumors (Dow Chemical Co., 1 992a; Maltoni et al., 1988, 1977; Quast et al., 1980b). Also, there is some association be tween AN exposure and lung cancer deaths in occupationally exposed workers. Rats exposed durin g gestation and through adulthood displayed higher incidences of tumors at several ti ssue sites than did rats exposed throughout adulthood only (Friedman and Beliles, 2002; Maltoni et al., 1988). The latter results suggest that exposure to AN during gestation and childhood may p resent increased risk of developing cancer compared with exposure during adulthood alone. Although data gaps still exist in the current under standing of the mode of action for carcinogenicity of AN, there is adequate experiment al evidence to support a direct mutagenic mode of action as the key mode of action for AN-ind uced tumors. Other modes of action may contribute, but limited data do not appear supporti ve at this time. Indirect mutagenicity via oxidative DNA damage is plausible, but oxidative st ress was not supported by experimental evidence as a key mode of action.

6.2. DOSE-RESPONSE
6.2.1. Oral RfD The available oral toxicity studies in animals ide ntify nonneoplastic forestomach lesions (i.e., squamous cell epithelial hyperplasia and hyp erkeratosis) as the most sensitive noncancer effect associated with chronic oral exposure to AN. These lesions are expected to be relevant to humans because, although humans do not possess a fo restomach, they do have comparable squamous cell epithelial tissue in their oral cavit y and in the upper two-thirds of their esophagus. A 2-year drinking water study with F344 rats (Joha nssen and Levinskas, 2002b) was selected as the principal study on which to base th e RfD because it provided the best available dose-response data. This study included five drink ing water exposure levels ranging from 1 to 100 ppm, and it also identified the lowest administ ered-dose LOAEL of the available chronic animal toxicity studies based on an increased incid ence of forestomach lesions (i.e., LOAELs of 0.3 and 0.4 mg/kg-day for males and females, respec tively, with associated NOAELs of 0.1 mg/kg-day for both sexes).
An RfD of 2 × 10 -4 

### mg/kg-day (or 0.2 μg/kg-day) is derived for use in humans because it
is the lowest value derived based on the observed c ritical effect in the selected principal study

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(i.e., incidence of nonneoplastic forestomach lesio ns in F344 rats in a 2-year drinking water study). This RfD was derived using a BMD approach based on incidence data for forestomach lesions in male and female F344 rats exposed chroni cally to AN via drinking water and pharmacokinetic data from EPA-modified rat and huma n PBTK models (Section 3.5; Appendix C; Sweeney et al., 2003; Kedderis et al., 1996). The RfD derivation process involved first fitting all available dichotomous models in BMDS (version 2.0) to the incidence data for male a nd female rats, separately, employing two different internal dose metrics (i.e., AN in blood and CEO in blood). These two internal dose metrics were derived by converting administered rat doses of AN to internal rat doses (either AN or CEO in blood) using the rat PBTK model of Kedder is et al. (1996), as modified by EPA (Section 3.5; Appendix C). Then, for each sex, the BMDL associated with both a 5 and 10% extra risk for gastric epithelial lesions was deriv ed based on the best-fitting model. This BMDL
based on rat internal dose was then converted to th e human equivalent administered dose of AN by using the human PBTK model of Sweeney et al. (20 03) (with EPA-modified parameters; Section 3.5; Appendix C). As discussed in more det ail in Section 5.1, CEO in blood was
selected as the best available internal dose metric for cross-species extrapolation with oral exposure, while 5% extra risk was chosen as the mos t appropriate BMR level. The human equivalent administered dose of AN represents a POD for noncancer effects and was then divided by a UF of 30 (3 to account for uncertainty in extrapolating from rats to humans with dosimetric adjustment and 10 to account for variati on in response from average humans to sensitive humans) to arrive at an RfD. Confidence in the principal study selected for the RfD is high. The principal study, Johannsen and Levinskas (2002b), was selected from eight chronic rat studies and one gavage study in exposed mice. The study employed five exp osure levels of AN, ranging from 1 to 100 ppm, and thus provided a more complete descript ion of the dose-response relationship in the low-dose region than did either the Quast (2002) st udy in Sprague-Dawley rats or the NTP (2001) study in B6C3F 1 

### mice, which started at higher dose levels, and bot h employed only three dose groups. Johannsen and Levinskas (2002b) ident ified the lowest LOAELs based on an increased incidence of hyperplasia and hyperkeratos is in squamous epithelium of forestomach (0.4 mg/kg-day for males and 0.4 mg/kg-day for fema les). No human exposure study is
available for derivation of the RfD. Overall confi dence in the RfD is medium, reflecting these
considerations.

6.2.2. Inhalation RfC Results from several cross-sectional epidemiologic studies of AN-exposed workers identified increased prevalence of neurological sym ptoms and small performance deficits in
neurobehavioral tests as the critical effects resul ting from chronic inhalation exposure to AN. The cross-sectional study of neurobehavioral perfor mance measures in acrylic fiber workers by

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Lu et al. (2005a) was selected as the principal stu dy for RfC derivation because it identified the lowest reliable exposure level in humans associated with adverse neurological effects. A NOAEL/LOAEL approach was used to derive the RfC from the human data. The average workplace AN air concentration of 0.11 ppm for workers in the monomer work areas of the acrylic fiber plant was selected as the LOAEL o r POD for RfC derivation. This LOAEL of 0.11 ppm (0.24 mg/m 3 

### ) for small, but statistically significant, perform ance deficits in neurobehavioral tests of mood, attention and speed, auditory memory, visual perception and memory, and motor steadiness was divided by a UF of 100 (10 for extrapolating from a LOAEL to a NOAEL and 10 to account for extrapolating from healthy workers to sensitive humans), after conversion to an equivalent continuous exposu re of 0.086 mg/m 3 

### , to arrive at an RfC for
AN of 0.9 μ g/m 3



### . As discussed in more detail in Section 5.2, compa rative animal-based RfCs for AN of 3
× 10 -3 

### mg/m 3 

### (or 3 μ g/m 3 

### ) and 2 × 10 -3 

### mg/m 3 

### (or 2 μ g/m 3 

### ) were derived based on PODs from BMD modeling of nasal lesions observed in male and female rats, respectively, exposed to AN via inhalation for 2 years (Quast et al., 1980b). In deriving these RfCs, the PODs were divided by a composite UF of 30 (3 for extrapolating from r ats to humans using the default U.S. EPA (1994) dosimetric adjustment and 10 to account for variation from average humans to sensitive humans). These animal-based RfCs are quite consist ent with the human-based value. However,
the human-based value of 0.9 μ g/m 3 

### is selected as the RfC, because extrapolating from animals has greater associated uncertainty than extrapolati ng from humans. The principal study is given medium confidence bec ause it is the best available study
that identified neurobehavioral effects of AN in oc cupationally exposed workers. Previous occupational studies by Kaneko and Omae (1992) and Muto et al. (1992) reported subjective neurological symptoms in exposed workers. Lu et al . (2005a) utilized the WHO-recommended NCTB administered by trained physicians to evaluate these neurobehavioral effects systemically. Hence, the results were more reliable when compared with those based on self reporting. The confidence in the principal study is medium because there are several limitations in the study. One was that the cited exposure data represented es timates of previous exposure levels and no contemporaneous personal monitoring data were avail able. In addition, the study authors could not rule out the possibility that examiner drift ma y have affected the results. Moreover, largest
measures of neurobehavioral effect occurred on the acrylic fiber workers, who had lower average exposure level. Confidence in the database is medium to high. An R fC based on the results from a chronic inhalation study with Sprague-Dawley rats w as also derived for comparison. Statistically significant increased incidence of in flammatory and degenerative nasal lesions occurred in rats exposed to the lowest level in thi s 2-year bioassay. The alternative RfC derived from the rat study is only about threefold higher t han the RfC derived from the occupational exposure study. Overall confidence in the RfC is m edium to high, reflecting these

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considerations.

6.2.3. Oral CSF Incidence data for forestomach, CNS, Zymbal gland, tongue, and mammary gland tumors in male and female Sprague-Dawley (Quast, 2002) and F344 (Johanssen and Levinskas, 2002a) rats were used to develop site-specific oral CSFs f or AN, employing EPA-modified rat and human PBTK models for cross-species dosimetric extr apolation (Section 3.5; Appendix C; Sweeney et al., 2003; Kedderis et al., 1996). Thes e animal studies were selected for the development of oral CSFs because human data are not available, and these studies are the best available chronic bioassays for characterizing the dose-response relationships for these AN-induced tumors. Weight-of-evidence evaluation f ollowing U.S. EPA (2005a) guidelines determined that a direct mutagenic mode of action, most likely via the reactive AN metabolite CEO, was the principal mode of action. Consequentl y, a linear low-dose extrapolation approach was used in the development of the oral CSFs. As discussed in more detail in Section 5.4, CEO in blood and AN in blood were both
evaluated as internal dose metrics for use in cross -species extrapolation with oral exposure. The multistage dose-response model in BMDS (version 1.4 .1) was fit to the male and female rat tumor incidence data, using internal animal dose ex pressed as either CEO or AN in blood. Rat
administered doses were converted to rat internal d oses (either CEO or AN in blood) by using the rat PBTK model of Kedderis et al. (1996), as mo dified by EPA (Section 3.5; Appendix C). For each of these two dose metrics, the resulting b est-fit model for each endpoint was then used
to derive a 95% lower confidence limit on the dose associated with 10% extra risk (i.e., a
BMDL 10 

### ). These BMDLs, based on internal rat doses, were then converted to human equivalent administered doses of AN using the human PBTK model of Sweeney et al. (2003), as modified by EPA (Section 3.5; Appendix C). The site-specifi c oral CSFs based on incidence data from each tumor site were derived by linear extrapolatio n from the human equivalent administered doses down to the origin (oral CSF = 0.1/BMDL 10/HED 

### ). Within rat strain and sex, an oral slope factor for the composite risk across these tumor si tes, based on CEO in blood, was then estimated by employing the procedure described in Section 5.4 .4.1. The highest composite slope factor of 5 per mg/kg-d ay is recommended for use in humans because it has the highest potency based on the observed critical effect in the selected principal study (i.e., incidence of tumors in male and female Sprague-Dawley rats). This slope factor is recommended for estimating composite canc er risks in humans who experience chronic oral exposures to AN during adulthood. This slope factor should not be used with exposures greater than 0.04 mg/kg-day (the lowest POD support ing the composite risk) because above this level, the slope factor cannot be expected to be an adequate approximation to the dose-response relationship. The fitted dose-response relationshi p and pharmacokinetic models should be used to estimate risk above this exposure level.

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Results from a chronic rat inhalation cancer bioass ay (Maltoni et al., 1988) and a threegeneration rat drinking water reproductive toxicity study (Friedman and Beliles, 2002) indicate that AN exposure during gestation and early periods of development may increase risks for cancer by at least threefold compared with chronic AN exposures during adulthood only. A chemical-specific early life susceptibility factor of 3.6 was developed for assessing cancer risks associated with lifetime exposure beginning at birt h, based on the incidence data in the Maltoni et al. (1988) bioassay for mammary tumors, brain tu mors, and extra-hepatic angiosarcomas in
female rats.

6.2.4. Cancer Inhalation Unit Risk An analysis of the human lung cancer mortality data from the Blair et al. (1998) cohort study of AN-exposed workers was conducted to derive an IUR estimate for AN based on human data. This analysis employed the approach presente d by Starr et al. (2004) and is further described in Appendix B-7. In brief, the risk of d eath from lung cancer in AN-exposed workers was characterized by using a semi-parametric Cox re gression model with a cumulative exposure metric (i.e., ppm-working years) as the only time-d ependent covariate. In contrast to the analysis by Starr et al. (2004), the entire cohort was inclu ded in the analysis conducted for this assessment (not just white male workers), and the final model only included cumulative exposure as the
covariate. The Cox regression model described above was used to estimate an AN exposure level
and its associated 95% lower confidence limit corre sponding to a 1% risk of dying from lung cancer by age 80 (i.e., EC 01 

### and LEC 01 

### , respectively). Conversion of occupational exposu res to continuous environmental exposures was accomplished by adjusting for differences in the amount of air inhaled during an 8-hour workday vers us a 24-hour day (10 and 20 m 3 

### /day, respectively). The IUR estimate was derived by lin ear extrapolation from the LEC 01 

### . The predicted EC 01 

### and LEC 01 

### derived from the Cox regression model based on the Blair et al. (1998) data were 0.992 and 0.238 ppm (2,168 and 524 μ g/m 3 

### ) AN, respectively. From the LEC 01 

### , an IUR estimate of 0.042 per ppm (2 × 10 -5 

### per μ g/m 3 

### ) was derived. Some uncertainty is associated with this IUR estim ate because of the study on which it is based. More specifically, no adjustment for smokin g was applied in the Blair et al. (1998) study. The investigators collected smoking information on only about 10% of the exposed and unexposed members of the cohort and found similar i ncidences of smoking in the two groups. Because their statistical analysis compared exposed and unexposed groups of workers, Blair et al. (1998) noted that the adjustment for smoking ma de only a slight difference in the results of their analysis. Other uncertainties associated wit h the Blair et al. (1998) data set included nondifferential exposure misclassification and a re latively short follow-up period, an average of 21 years. Additionally, the outcome of the study w as lung cancer mortality, not lung cancer

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incidence. Additional uncertainties related to the statistical analysis of these data are discussed further in Appendix B-7.
Tumor incidence data from the best available animal inhalation study (Dow Chemical Co., 1992a) were selected for describing the dose-r esponse relationship between intestinal, CNS, Zymbal’s gland, tongue, and mammary gland tumors an d AN exposure. These dose-response relationships were used to derive animal-based IURs for AN for comparative purposes. As with the animal-based oral slope factor, a direct mutage nic mode of action, most likely via the reactive AN metabolite CEO, was assumed, because av ailable information was inadequate to establish AN’s mode of carcinogenic action in these tissues in animals. Consequently, a linear low-dose extrapolation approach was used in the dev elopment of the animal-based IURs. Based on the assumption that the epoxide metabolite , CEO, is critical to AN’s carcinogenic mode of action, the selected internal dose metric was CEO in blood. In contrast to oral exposure, the EPA-modified PBTK model adequate ly predicted measured blood and brain concentrations of CEO in rats exposed to AN by inha lation (Kedderis et al., 1996). The multistage model was fit to the rat tumor incidence and CEO concentration in blood predicted by the PBTK model of Kedderis et al. (1996), as modifi ed by EPA (Section 3.5; Appendix C). The best-fitting stage of the model was used to derive 95% lower bounds on rat internal blood
concentrations of CEO associated with 10% extra ris k (BMCL 10 

### s). The human PBTK model of Sweeney et al. (2003) (parameters modified; Section 3.5; Appendix C), was then used to calculate human equivalent administered concentrati ons of AN, corresponding to the rat
BMCL 10 

### s. These human equivalent administered concentrati ons of AN were used as the POD for the IUR estimates via linear extrapolation down to the origin (i.e., IUR = 0.1/BMCL 10/HEC 

### ). The IUR estimates for multiple tumor sites were der ived within each rat sex by employing the procedure described in Section 5.4.4. 1. The resulting composite IUR estimates

were 7 × 10 -2 

### and 6 × 10 -2 

### per mg/m 3 

### (7 × 10 -5 

### and 6 × 10 -5 

### per μ g/m 3 

### ) and were derived based on tumor incidence data from male and female Sprague-D awley rats, respectively. These unit risks should not be used with exposures greater than 3 mg /m 3 

### (the lowest POD supporting the composite risk), because above this level, the slop e factor cannot be expected to be an adequate approximation of the dose-response relationship. T he fitted dose-response relationship and pharmacokinetic models should be used to estimate r isk above this exposure level.
Given that the IUR of 2 × 10 -5 

### per μ g/m 3 

### is based on human data and is consistent with the IUR derived from the animal data, it is the IUR recommended for estimating cancer risks associated with chronic inhalation exposures to AN during adult stages of development. As described for the oral slope factor, a chemical- specific early-life adjustment factor of 3.6 was developed for assessing cancer risks associ ated with lifetime exposure beginning at birth, based on the multisite tumor incidence data for female rats in the Maltoni et al. (1988) bioassay.
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APPENDIX A. SUMMARY OF EXTERNAL PEER REVIEW AND PU BLIC

COMMENTS AND DISPOSITION

### B-1 DRAFT- DO NOT CITE OR QUOTE APPENDIX B. BENCHMARK DOSE CALCULATIONS

APPENDIX B-1. NONCANCER ORAL DOSE-RESPONSE ASSESSM ENT (RfD):
BENCHMARK DOSE MODELING RESULTS EMPLOYING THE INCID ENCE OF FORESTOMACH LESIONS (HYPERPLASIA AND HYPERKERATOSIS ) IN MALE AND FEMALE SPRAGUE-DAWLEY RATS, F344 RATS, AND B6C3 F 1 

### MICE
CHRONICALLY EXPOSED ORALLY TO AN FOR 2 YEARS

As previously discussed in Section 4, no human stud ies currently exist that involve oral exposures to AN. The available animal oral toxicit y data, however, identify forestomach lesions (i.e., squamous cell epithelial hyperplasia and hyp erkeratosis) as the most sensitive, prevalent,
and consistent noncancer effect associated with chr onic oral exposure to AN. Therefore, this endpoint was selected as the critical effect on whi ch to base derivation of the RfD. Two 2-year drinking water studies, one in Sprague- Dawley rats (Quast, 2002; Quast et al., 1980a) and the other in F344 rats (Johannsen a nd Levinskas, 2002b; Biodynamics 1980c), and a 2-year gavage study in B6C3F 1 

### mice (NTP, 2001) provided the best available doseresponse data on which to base the RfD. Candidate RfDs for AN were derived from the incidence of forestomach lesions in Sprague-Dawley rats, F344 rats, and B6C3F 1 

### mice using a BMD approach. Incidences of forestomach lesions fr om chronic drinking water studies in male and female Sprague-Dawley rats (Quast, 2002) and F3 44 rats (Johannsen and Levinskas, 2002b) provided four sets of dose-response data from which to derive candidate RfDs, while incidences of forestomach lesions from a chronic gavage study in male and female B6C3F 1 

### mice provided an additional two sets of dose-response data. Thes e six data sets are presented in Tables B-1 (for rats) and B-2 (for mice).

Table B-1. Incidences of forestomach lesions (hype rplasia or hyperkeratosis) in Sprague-Dawley and F344 rats exp osed to AN in drinking water for 2 years

Predicted internal dose metrics b

Sex Administered

concentration (ppm in drinking water) Administered

dose a (mg/kg-d) AN-AUC in rat

blood (mg/L) CEO-AUC in rat

blood (mg/L) Incidence of

forestomach lesions c Sprague-Dawley rats (Sources: Quast, 2002; Quast et al., 1980a) 0 0 0 0 15/80 (19%)
35 3.4 2.06 × 10 -2 1.83 × 10 -3 15/47 (32%)
100 8.5 5.36 × 10 -2 4.36 × 10 -3 44/48 (92%) c Male

300 21.3 1.46 × 10 -1 9.70 × 10 -3 45/48 (94%) c

0 0 0 0 20/80 (25%) Female
35 4.4 2.37 × 10 -2 2.07 × 10 -3 23/48 (48%) c

### B-2 DRAFT- DO NOT CITE OR QUOTE

Table B-1. Incidences of forestomach lesions (hype rplasia or hyperkeratosis) in Sprague-Dawley and F344 rats exp osed to AN in drinking water for 2 years

Predicted internal dose metrics b

Sex Administered

concentration (ppm in drinking water) Administered

dose a (mg/kg-d) AN-AUC in rat

blood (mg/L) CEO-AUC in rat

blood (mg/L) Incidence of

forestomach lesions c

100 10.8 6.18 × 10 -2 4.87 × 10 -3 41/48 (85%) c

300 25.0 1.56 × 10 -1 1.01 × 10 -2 47/48 (98%) c

F344 rats d (Sources: Johannsen and Levinskas, 2002b; Biodynam ics, 1980c) d
0 0 0 0 11/159 (7%)
1 0.08 4.33 × 10 -4 4.06 × 10 -5 3/80 (4%)
3 0.25 1.35 × 10 -3 1.27 × 10 -4 18/75 (24%) c

10 0.83 4.52 × 10 -3 4.19 × 10 -4 13/80 (16%) c

30 2.48 1.37 × 10 -2 1.23 × 10 -3 17/80 (22%) c Male

100 8.37 4.85 × 10 -2 3.97 × 10 -3 9/77 (12%)

0 0 0 0 4/156 (3%)
1 0.12 5.73 × 10 -4 5.32 × 10 -5 2/80 (3%)
3 0.36 1.72 × 10 -3 1.59 × 10 -4 16/80 (20%) c

10 1.25 6.02 × 10 -3 5.49 × 10 -4 23/74 (31%) c

30 3.65 1.79 × 10 -2 1.58 × 10 -3 13/80 (16%) c Female

100 10.90 5.63 × 10 -2 4.46 × 10 -3 5/74 (7%)

a Administered doses were averages calculated by the study authors based on animal BW and drinking water intake.
b The EPA-modified rat PBPK model of Keddaris et al. (1996) was employed to predict a rat internal dose (i.e., either AN-AUC or CEO-AUC concentration in blood) re sulting from the ingestion of the specified adminis tered dose of AN consumed in six bolus episodes/d.

c Indicates significantly different (at p < 0.05) from control incidence by Fisher’s exact te st performed by Syracuse Research Corporation.
d Incidences for F344 rats do not include animals fro m the 6- and 12-mo sacrifices and were further adju sted to exclude (from the denominators) rats that died betw een 0 and 12 mos in the study. Rats dying during t his time period were determined from page 6 of Appendix H an d Table 1 in Biodynamics (1980c) and Table 8 in Joh annsen and Levinskas (2002b). Unscheduled deaths between 0 and 12 mos in the study occurred in two female co ntrols, two males at 3 ppm, three females at 10 ppm, and th ree males and three females at 100 ppm.

### B-3 DRAFT- DO NOT CITE OR QUOTE

Table B-2. Incidences of forestomach lesions (hype rplasia or hyperkeratosis) in male and female B6C3F 1 

### mice administered AN via gavage for 2 years

Dose (mg/kg-d) a

Lesion site and type 0 2.5 10 20
Males Forestomach hyperplasia or hyperkeratosis 2/50 (4%) 4/50

(8%) 10/50 a

(20%) 13/50 b

(26%)
Females Forestomach hyperplasia or hyperkeratosis 2/50 (4%) 2/50

(4%) 5/50

(10%) 8/50 a

(16%)

a Significantly elevated above vehicle control as det ermined by EPA using Fisher’s exact test ( p ≤ 0.05).
b Significantly elevated above vehicle control as det ermined by EPA using Fisher’s exact test ( p ≤ 0.01).

Source: NTP (2001).



### The incidences of forestomach lesions observed foll owing 2 years of AN exposure in male and female SD and F344 rats were modeled using AN and CEO in blood, expressed in mg/L, as internal dose metrics. In addition, incid ences of these same lesions were modeled in male and female SD and F344 rats, as well as male a nd female B6C3F 1 

### mice, employing administered dose. In all cases, all of the dichot omous dose-response models available in EPA’s BMDS software (version 2.0) (i.e., the gamma, logis tic, log-logistic, probit, log-probit, multistage, Weibull, and quantal-linear models) wer e fit to these incidence data. Because the
incidence of forestomach lesions in male and female F344 rats did not increase monotonically across all administered concentrations, however, on ly incidence data from the three lowest concentrations (i.e., 0, 1, and 3 ppm) were used in dose-response modeling. Similarly, in male Sprague-Dawley rats, the incidence data from the hi ghest dose group needed to be dropped prior to BMD modeling. In most cases, several models fit the data equally well (i.e., exhibited χ 2 

### goodness-of-fit p values greater than 0.1). Of those models exhibit ing adequate fit, the selected
model was the one with the lowest AIC value. BMDL 10 

### and BMDL 05 

### estimates were derived
from the selected model. If more than one model sh ared the lowest AIC, the mean BMDL 10 

### and
BMDL 05 

### were calculated, as per the EPA’s Benchmark Dose Technical Guidance Document (U.S. EPA, 2000b). In this appendix, detailed results of the dose-resp onse modeling for forestomach lesions in male and female SD and F344 rats, and B6C3F 1 

### mice are presented. For each species, strain, and sex, summaries of the dose-response data (i.e., animal administered and internal doses and incidence data) are presented (Table B-1 for rats a nd Table B-2 for mice). Then, again for each species, strain, and sex, Tables B-3 (Sprague-Dawle y rats), B-4 (F344 rats), and B-5 (B6C3F 1 

### mice) summarize the results of the dose-response mo deling. Each of these tables is then

### B-4 DRAFT- DO NOT CITE OR QUOTE

followed by the standard output from EPA’s BMDS, ve rsion 2.0, for the dose-response models that did not exhibit statistically significant lack of fit.

Table B-3. Summary of the BMD modeling results bas ed on the incidence of forestomach lesions (hyperplasia or hyperkeratosis) in male and female Sprague-Dawley rats exposed to AN in drinking water for 2 years

Sex Endpoint Dose metric Selected model(s) a χ 2

p -value AIC BMDL 10 b BMDL 05 b

Estimated administered dose (mg/kg-d) Two-stage multistage

(1) 0.18 169.45 1.27 7.20 × 10 -1

Predicted AN in blood (mg/L) Two-stage multistage

(1) 0.24 169.01 7.72 × 10 -3 4.32 × 10 -3 Male Forestomach

lesions

Predicted CEO

in blood (mg/L) Two-stage multistage

(1) 0.12 170.09 6.82 × 10 -4 3.90 × 10 -4

### B-5 DRAFT- DO NOT CITE OR QUOTE

Table B-3. Summary of the BMD modeling results bas ed on the incidence of forestomach lesions (hyperplasia or hyperkeratosis) in male and female Sprague-Dawley rats exposed to AN in drinking water for 2 years

Sex Endpoint Dose metric Selected model(s) a χ 2

p -value AIC BMDL 10 b BMDL 05 b gamma 0.38 212.77 6.87 × 10 -1 3.34 × 10 -1 logistic 0.45 211.31 1.24 6.39 × 10 -1 log-logistic 0.98 212.03 1.41 9.17 × 10 -1 log-probit 0.74 212.14 1.38 9.61 × 10 -1 one-stage multistage 0.31 212.40 6.30 × 10 -1 3.07 × 10 -1

Weibull 0.31 213.07 6.74 × 10 -1 3.28 × 10 -1 Estimated administered dose (mg/kg-d)

quantal linear 0.31 212.40 6.30 × 10 -1 3.07 × 10 -1

gamma 0.32 212.96 3.76 × 10 -3 1.83 × 10 -3 logistic 0.23 212.00 7.07 × 10 -3 3.64 × 10 -3 log-logistic 0.98 212.03 6.93 × 10 -3 4.36 × 10 -3 log-probit 0.70 212.18 7.02 × 10 -3 4.88 × 10 -3 one-stage multistage 0.42 211.79 3.62 × 10 -3 1.76 ×

10 -3

Weibull 0.28 213.19 3.72 × 10 -3 1.81 × 10 -3 Predicted AN in blood (mg/L)

quantal linear 0.42 211.79 3.62 × 10 -3 1.76 ×

10 -3 gamma 0.51 212.45 3.53 × 10 -4 1.74 × 10 -4 logistic 0.69 210.72 5.58 × 10 -4 2.88 ×

10 -4 log-logistic 0.87 212.06 7.25 × 10 -4 4.87 × 10 -4 probit 0.33 211.86 5.87 × 10 -4 3.00 × 10 -4 Female Forestomach

lesions

Predicted CEO

in blood (mg/L)
log-probit 0.86 212.06 7.17 × 10 -4 5.15 × 10 -4

a All dichotomous models in EPA’s BMDS (version 2.0) were fit to the incidence of forestomach lesions (hyperplasia or hyperkeratosis) in Sprague-Dawley r ats using the data presented in Table B-1. For BMD modeling, three different dose metrics were employed: (1) ad ministered animal dose (estimated) expressed in mg/ kg-d, (2) AN in blood (predicted) expressed in mg/L, and (3) CEO in blood (predicted) expressed in mg/L. Adequa te fit of a model was achieved if the χ 2 goodness-of-fit statistic yielded a p -value > 0.1. The numbers in parentheses indicate the number of dose groups dropped in order to obtai n an adequate fit, starting with the highest dose g roup. Of those models exhibiting adequate fit, the selected model was the model with the lowest AIC value, and is ind icated in bold in the table.
b BMDL 10 and BMDL 05 estimates were derived from the selected model. I f more than one model shared the lowest AIC, the mean BMDL 10 and BMDL 05 were calculated, as per the EPA’s Benchmark Dose Technical Guidance Document

(U.S. EPA, 2000b).

Sources: Quast (2002); Quast et al. (1980a).

### B-6 DRAFT- DO NOT CITE OR QUOTE

SD Male Rats: Forestomach lesions (administered dos e)

0.2 0.4 0.6 0.8 1

0 1 2 3 4 5 6 7 8Fraction Affected

dose Multistage Model with 0.95 Confidence Level

16:25 10/03 2008 BMD

BMDL Multistage

================================================== ================== Multistage Model. (Version: 3.0; Date: 05/16 /2008) Input Data File: C:\USEPA\BMDS2\Temp\tmpAB.(d) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm pAB.plt Fri Oct 03 16:25:01 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1-beta2*dose^2)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = DOSE

Total number of observations = 3 Total number of records with missing values = 0 Total number of parameters in model = 3 Total number of specified parameters = 0 Degree of polynomial = 2

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008

### B-7 DRAFT- DO NOT CITE OR QUOTE

Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values Background = 0.110075 Beta(1) = 0 Beta(2) = 0.0325391

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Beta(1) have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Background Beta(2)

Background 1 -0.37

Beta(2) -0.37 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.170685 * * * Beta(1) 0 * * * Beta(2) 0.0278185 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -81.807 3 Fitted model -82.7268 2 1.8 3969 1 0.175 Reduced model -119.21 1 74. 8052 2 <.0001

AIC: 169.454

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.1707 13.655 15.000 80 0.400 3.4000 0.3987 18.741 15.000 47 -1.114 8.5000 0.8889 42.666 44.000 48 0.613

Chi^2 = 1.78 d.f. = 1 P-value = 0.1825

### B-8 DRAFT- DO NOT CITE OR QUOTE

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 1.35789

BMDL = 0.719865

BMDU = 1.59564

Taken together, (0.719865, 1.59564) is a 90 % t wo-sided confidence interval for the BMD

### B-9 DRAFT- DO NOT CITE OR QUOTE

SD Male Rats: Forestomach lesions (AN in blood)

0.2 0.4 0.6 0.8 1

0 0.01 0.02 0.03 0.04 0.05Fraction Affected

dose Multistage Model with 0.95 Confidence Level

11:55 10/06 2008 BMD

BMDL Multistage

================================================== ================== Multistage Model. (Version: 3.0; Date: 05/16 /2008) Input Data File: C:\USEPA\BMDS2\Temp\tmpBB.(d) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm pBB.plt Mon Oct 06 11:55:17 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1-beta2*dose^2)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = DOSE

Total number of observations = 3 Total number of records with missing values = 0 Total number of parameters in model = 3 Total number of specified parameters = 0 Degree of polynomial = 2

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-10 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.121757 Beta(1) = 0 Beta(2) = 815.045

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Beta(1) have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Background Beta(2)

Background 1 -0.36

Beta(2) -0.36 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.172109 * * * Beta(1) 0 * * * Beta(2) 714.086 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -81.807 3 Fitted model -82.5048 2 1.3 9565 1 0.2375 Reduced model -119.21 1 74. 8052 2 <.0001

AIC: 169.01

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.1721 13.769 15.000 80 0.365 0.0206 0.3885 18.261 15.000 47 -0.976 0.0536 0.8936 42.892 44.000 48 0.519

Chi^2 = 1.35 d.f. = 1 P-value = 0.2445

### B-11 DRAFT- DO NOT CITE OR QUOTE

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.0084753

BMDL = 0.0043156

BMDU = 0.0099743

Taken together, (0.0043156, 0.0099743) is a 90 % two-sided confidence interval for the BMD

### B-12 DRAFT- DO NOT CITE OR QUOTE

SD Male Rats: Forestomach lesions (CEO in blood)

0.2 0.4 0.6 0.8 1

0 0.0005 0.001 0.0015 0.002 0.0025 0.003 0.0035 0.004 0.0045Fraction Affected

dose Multistage Model with 0.95 Confidence Level

12:07 10/06 2008 BMD

BMDL Multistage

================================================== ================== Multistage Model. (Version: 3.0; Date: 05/16 /2008) Input Data File: C:\USEPA\BMDS2\Temp\tmpCC.(d) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm pCC.plt Mon Oct 06 12:07:44 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1-beta2*dose^2)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = DOSE

Total number of observations = 3 Total number of records with missing values = 0 Total number of parameters in model = 3 Total number of specified parameters = 0 Degree of polynomial = 2

Maximum number of iterations = 250

### B-13 DRAFT- DO NOT CITE OR QUOTE

Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values Background = 0.0947166 Beta(1) = 0 Beta(2) = 124268

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Beta(1) have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Background Beta(2)

Background 1 -0.37

Beta(2) -0.37 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.169148 * * * Beta(1) 0 * * * Beta(2) 102914 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -81.807 3 Fitted model -83.0465 2 2.4 7897 1 0.1154 Reduced model -119.21 1 74. 8052 2 <.0001

AIC: 170.093

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.1691 13.532 15.000 80 0.438 0.0018 0.4114 19.334 15.000 47 -1.285 0.0044 0.8825 42.362 44.000 48 0.734

Chi^2 = 2.38 d.f. = 1 P-value = 0.1228

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.000705982

BMDL = 0.000390266

BMDU = 0.000828151

Taken together, (0.000390266, 0.000828151) is a 90 % two-sided confidence interval for the BMD

### B-14 DRAFT- DO NOT CITE OR QUOTE

SD Female Rats: Forestomach lesions (administered d ose)

0.2 0.4 0.6 0.8 1

0 5 10 15 20 25Fraction Affected

dose Gamma Multi-Hit Model with 0.95 Confidence Level

14:42 10/06 2008

BMDL BMD Gamma Multi-Hit

================================================== ================== Gamma Model. (Version: 2.13; Date: 05/16/200 8) Input Data File: C:\USEPA\BMDS2\Temp\tmpD9.(d) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm pD9.plt Mon Oct 06 14:42:46 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response]= background+(1-background)*CumGamma[ slope*dose,power], where CumGamma(.) is the cummulative Gamma distr ibution function

Dependent variable = Response Independent variable = DOSE Power parameter is restricted as power >=1

Total number of observations = 4 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

Default Initial (and Specified) P arameter Values Background = 0.253086 Slope = 0.194377

### B-15 DRAFT- DO NOT CITE OR QUOTE

Power = 1.66787

Asymptotic Correlation Matrix of Paramet er Estimates

Background Slope Power

Background 1 0.13 0.25

Slope 0.13 1 0.95

Power 0.25 0.95 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.247085 0.0476211 0.153749 0.340421 Slope 0.22327 0.0913548 0.0442181 0.402322 Power 1.72213 0.704799 0.340745 3.10351

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -103.017 4 Fitted model -103.386 3 0.73 8711 1 0.3901 Reduced model -152.026 1 98. 0188 3 <.0001

AIC: 212.772

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.2471 19.767 20.000 80 0.060 4.4000 0.5044 24.212 23.000 48 -0.350 10.8000 0.8219 39.451 41.000 48 0.584 25.0000 0.9879 47.420 47.000 48 -0.555

Chi^2 = 0.78 d.f. = 1 P-value = 0.3785

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 1.12

BMDL = 0.334344

### B-16 DRAFT- DO NOT CITE OR QUOTE 0.2 0.4 0.6 0.8 1

0 5 10 15 20 25Fraction Affected

dose Logistic Model with 0.95 Confidence Level

14:44 10/06 2008

BMDL BMD Logistic

================================================== ================== Logistic Model. (Version: 2.12; Date: 05/16/2 008) Input Data File: C:\USEPA\BMDS2\Temp\tmpDB.(d) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm pDB.plt Mon Oct 06 14:44:22 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = 1/[1+EXP(-intercept-slope*dose)]

Dependent variable = Response Independent variable = DOSE Slope parameter is not restricted

Total number of observations = 4 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values background = 0 Sp ecified intercept = -0.808992 slope = 0.180053

Asymptotic Correlation Matrix of Paramet er Estimates

### B-17 DRAFT- DO NOT CITE OR QUOTE

( *** The model parameter(s) -backgroun d have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

intercept slope

intercept 1 -0.66

slope -0.66 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit intercept -1.07104 0.225024 -1.51208 -0.630006 slope 0.23795 0.0368793 0.165668 0.310232

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -103.017 4 Fitted model -103.655 2 1.2 7604 2 0.5283 Reduced model -152.026 1 98. 0188 3 <.0001

AIC: 211.31

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.2552 20.416 20.000 80 -0.107 4.4000 0.4940 23.711 23.000 48 -0.205 10.8000 0.8174 39.235 41.000 48 0.659 25.0000 0.9924 47.637 47.000 48 -1.062

Chi^2 = 1.62 d.f. = 2 P-value = 0.4456

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.78799

BMDL = 0.639403

### B-18 DRAFT- DO NOT CITE OR QUOTE 0.2 0.4 0.6 0.8 1

0 5 10 15 20 25Fraction Affected

dose Log-Logistic Model with 0.95 Confidence Level

14:46 10/06 2008

BMDL BMD Log-Logistic

================================================== ================== Logistic Model. (Version: 2.12; Date: 05/16/2 008) Input Data File: C:\USEPA\BMDS2\Temp\tmpDD.(d) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm pDD.plt Mon Oct 06 14:46:39 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background+(1-background)/[1+EXP(- intercept-slope*Log(dose))]

Dependent variable = Response Independent variable = DOSE Slope parameter is restricted as slope >= 1

Total number of observations = 4 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

User has chosen the log transformed model

Default Initial Parameter Values background = 0.25 intercept = -4.55921 slope = 2.51883

### B-19 DRAFT- DO NOT CITE OR QUOTE

Asymptotic Correlation Matrix of Paramet er Estimates

background intercept slope

background 1 -0.3 0.2

intercept -0.3 1 -0.96

slope 0.2 -0.96 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit background 0.250085 * * * intercept -4.54432 * * * slope 2.51011 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -103.017 4 Fitted model -103.017 3 0.00074 9029 1 0.9782 Reduced model -152.026 1 98. 0188 3 <.0001

AIC: 212.034

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.2501 20.007 20.000 80 -0.002 4.4000 0.4785 22.970 23.000 48 0.009 10.8000 0.8550 41.041 41.000 48 -0.017 25.0000 0.9788 46.981 47.000 48 0.019

Chi^2 = 0.00 d.f. = 1 P-value = 0.9782

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 1.89151

BMDL = 0.917407

### B-20 DRAFT- DO NOT CITE OR QUOTE 0.2 0.4 0.6 0.8 1

0 5 10 15 20 25Fraction Affected

dose LogProbit Model with 0.95 Confidence Level

14:50 10/06 2008

BMDL BMD

LogProbit

================================================== ================== Probit Model. (Version: 3.1; Date: 05/16/200 8) Input Data File: C:\USEPA\BMDS2\Temp\tmpDE.(d) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm pDE.plt Mon Oct 06 14:50:13 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = Background + (1-Background) * CumNorm(Intercept +Slope*Log(Dose)),

where CumNorm(.) is the cumulative normal distri bution function

Dependent variable = Response Independent variable = DOSE Slope parameter is restricted as slope >= 1

Total number of observations = 4 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

User has chosen the log transformed model

Default Initial (and Specified) P arameter Values

### B-21 DRAFT- DO NOT CITE OR QUOTE

background = 0.25 intercept = -2.53925 slope = 1.39624

Asymptotic Correlation Matrix of Paramet er Estimates

background intercept slope

background 1 -0.31 0.21

intercept -0.31 1 -0.96

slope 0.21 -0.96 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit background 0.248842 0.0480048 0.154755 0.34293 intercept -2.58881 0.657292 -3.87708 -1.30054 slope 1.42762 0.288071 0.86301 1.99223

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -103.017 4 Fitted model -103.07 3 0.10 6572 1 0.7441 Reduced model -152.026 1 98. 0188 3 <.0001

AIC: 212.14

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.2488 19.907 20.000 80 0.024 4.4000 0.4876 23.406 23.000 48 -0.117 10.8000 0.8427 40.448 41.000 48 0.219 25.0000 0.9832 47.192 47.000 48 -0.216

Chi^2 = 0.11 d.f. = 1 P-value = 0.7415

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 1.93713

BMDL = 0.961058

### B-22 DRAFT- DO NOT CITE OR QUOTE 0.2 0.4 0.6 0.8 1

0 5 10 15 20 25Fraction Affected

dose Multistage Model with 0.95 Confidence Level

14:52 10/06 2008 BMD

BMDL Multistage

================================================== ================== Multistage Model. (Version: 3.0; Date: 05/16 /2008) Input Data File: C:\USEPA\BMDS2\Temp\tmpDF.(d) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm pDF.plt Mon Oct 06 14:52:05 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = DOSE

Total number of observations = 4 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-23 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.18073 Beta(1) = 0.14774

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1)

Background 1 -0.46

Beta(1) -0.46 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.235056 * * * Beta(1) 0.131634 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -103.017 4 Fitted model -104.199 2 2.3 6383 2 0.3067 Reduced model -152.026 1 98. 0188 3 <.0001

AIC: 212.397

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.2351 18.804 20.000 80 0.315 4.4000 0.5714 27.425 23.000 48 -1.291 10.8000 0.8154 39.139 41.000 48 0.692 25.0000 0.9715 46.633 47.000 48 0.318

Chi^2 = 2.35 d.f. = 2 P-value = 0.3095

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.389667

BMDL = 0.306761

BMDU = 0.505425

Taken together, (0.306761, 0.505425) is a 90 % two-sided confidence interval for the BMD

### B-24 DRAFT- DO NOT CITE OR QUOTE 0.2 0.4 0.6 0.8 1

0 5 10 15 20 25Fraction Affected

dose Weibull Model with 0.95 Confidence Level

14:55 10/06 2008

BMDL BMD Weibull

================================================== ================== Weibull Model using Weibull Model (Version: 2 .12; Date: 05/16/2008) Input Data File: C:\USEPA\BMDS2\Temp\tmpE2.(d) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm pE2.plt Mon Oct 06 14:55:23 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP (-slope*dose^power)]

Dependent variable = Response Independent variable = DOSE Power parameter is restricted as power >=1

Total number of observations = 4 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

Default Initial (and Specified) P arameter Values Background = 0.253086 Slope = 0.0679496 Power = 1.19621

Asymptotic Correlation Matrix of Paramet er Estimates

### B-25 DRAFT- DO NOT CITE OR QUOTE

Background Slope Power

Background 1 -0.31 0.23

Slope -0.31 1 -0.97

Power 0.23 -0.97 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.245056 0.0471325 0.152678 0.337434 Slope 0.0673284 0.0436908 -0.018304 0.152961 Power 1.27711 0.255412 0.776514 1.77771

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -103.017 4 Fitted model -103.534 3 1.0 3516 1 0.3089 Reduced model -152.026 1 98. 0188 3 <.0001

AIC: 213.069

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.2451 19.604 20.000 80 0.103 4.4000 0.5170 24.816 23.000 48 -0.525 10.8000 0.8150 39.118 41.000 48 0.700 25.0000 0.9876 47.404 47.000 48 -0.526

Chi^2 = 1.05 d.f. = 1 P-value = 0.3051

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.808158

BMDL = 0.327975

### B-26 DRAFT- DO NOT CITE OR QUOTE 0.2 0.4 0.6 0.8 1

0 5 10 15 20 25Fraction Affected

dose Quantal Linear Model with 0.95 Confidence Level

14:57 10/06 2008

BMDLBMD Quantal Linear

=================================================== ================= Quantal Linear Model using Weibull Model (Ver sion: 2.12; Date: 05/16/2008) Input Data File: C:\USEPA\BMDS2\Temp\tmpE4.(d) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm pE4.plt Mon Oct 06 14:57:14 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP (-slope*dose)]

Dependent variable = Response Independent variable = DOSE

Total number of observations = 4 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

Default Initial (and Specified) P arameter Values Background = 0.253086 Slope = 0.127782 Power = 1 Sp ecified

Asymptotic Correlation Matrix of Paramet er Estimates

### B-27 DRAFT- DO NOT CITE OR QUOTE

( *** The model parameter(s) -Power have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Background Slope

Background 1 -0.31

Slope -0.31 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.235057 0.0449515 0.146954 0.323161 Slope 0.131633 0.019868 0.0926927 0.170574

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -103.017 4 Fitted model -104.199 2 2.3 6383 2 0.3067 Reduced model -152.026 1 98. 0188 3 <.0001

AIC: 212.397

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.2351 18.805 20.000 80 0.315 4.4000 0.5714 27.425 23.000 48 -1.291 10.8000 0.8154 39.139 41.000 48 0.692 25.0000 0.9715 46.633 47.000 48 0.318

Chi^2 = 2.35 d.f. = 2 P-value = 0.3095

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.389668

BMDL = 0.306761

### B-28 DRAFT- DO NOT CITE OR QUOTE

SD Female Rats: Nonneoplastic forestomach lesions ( AN in blood)

0.2 0.4 0.6 0.8 1

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16Fraction Affected

dose Gamma Multi-Hit Model with 0.95 Confidence Level

15:59 10/06 2008

BMDL BMD Gamma Multi-Hit

================================================== ================== Gamma Model. (Version: 2.13; Date: 05/16/200 8) Input Data File: C:\USEPA\BMDS2\Temp\tmpF1.(d) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm pF1.plt Mon Oct 06 15:59:50 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response]= background+(1-background)*CumGamma[ slope*dose,power], where CumGamma(.) is the cummulative Gamma distr ibution function

Dependent variable = Response Independent variable = DOSE Power parameter is restricted as power >=1

Total number of observations = 4 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

Default Initial (and Specified) P arameter Values Background = 0.253086

### B-29 DRAFT- DO NOT CITE OR QUOTE

Slope = 28.0854 Power = 1.40734

Asymptotic Correlation Matrix of Paramet er Estimates

Background Slope Power

Background 1 0.12 0.24

Slope 0.12 1 0.94

Power 0.24 0.94 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.24677 0.0475578 0.153558 0.339981 Slope 32.9782 13.6708 6.18402 59.7725 Power 1.45925 0.592225 0.298512 2.61999

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -103.017 4 Fitted model -103.482 3 0.93 1283 1 0.3345 Reduced model -152.026 1 98. 0188 3 <.0001

AIC: 212.965

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.2468 19.742 20.000 80 0.067 0.0237 0.5082 24.395 23.000 48 -0.403 0.0618 0.8175 39.238 41.000 48 0.658 0.1560 0.9886 47.454 47.000 48 -0.617

Chi^2 = 0.98 d.f. = 1 P-value = 0.3220

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.00495567

BMDL = 0.00183293

### B-30 DRAFT- DO NOT CITE OR QUOTE 0.2 0.4 0.6 0.8 1

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16Fraction Affected

dose Logistic Model with 0.95 Confidence Level

16:01 10/06 2008

BMDL BMD Logistic

================================================== ================== Logistic Model. (Version: 2.12; Date: 05/16/2 008) Input Data File: C:\USEPA\BMDS2\Temp\tmpF2.(d) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm pF2.plt Mon Oct 06 16:01:31 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = 1/[1+EXP(-intercept-slope*dose)]

Dependent variable = Response Independent variable = DOSE Slope parameter is not restricted

Total number of observations = 4 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values background = 0 Sp ecified intercept = -0.712868 slope = 28.3794

Asymptotic Correlation Matrix of Paramet er Estimates

### B-31 DRAFT- DO NOT CITE OR QUOTE

( *** The model parameter(s) -backgroun d have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

intercept slope

intercept 1 -0.65

slope -0.65 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit intercept -1.0292 0.221998 -1.46431 -0.594092 slope 40.4482 6.53178 27.6462 53.2503

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -103.017 4 Fitted model -104.001 2 1. 9683 2 0.3738 Reduced model -152.026 1 98. 0188 3 <.0001

AIC: 212.002

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.2632 21.059 20.000 80 -0.269 0.0237 0.4824 23.153 23.000 48 -0.044 0.0618 0.8131 39.030 41.000 48 0.729 0.1560 0.9949 47.757 47.000 48 -1.539

Chi^2 = 2.98 d.f. = 2 P-value = 0.2258

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.00450626

BMDL = 0.00363943

### B-32 DRAFT- DO NOT CITE OR QUOTE 0.2 0.4 0.6 0.8 1

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16Fraction Affected

dose Log-Logistic Model with 0.95 Confidence Level

16:03 10/06 2008

BMDL BMD Log-Logistic

================================================== ================== Logistic Model. (Version: 2.12; Date: 05/16/2 008) Input Data File: C:\USEPA\BMDS2\Temp\tmpF3.(d) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm pF3.plt Mon Oct 06 16:03:04 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background+(1-background)/[1+EXP(- intercept-slope*Log(dose))]

Dependent variable = Response Independent variable = DOSE Slope parameter is restricted as slope >= 1

Total number of observations = 4 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

User has chosen the log transformed model

Default Initial Parameter Values background = 0.25 intercept = 7.87595 slope = 2.32252

### B-33 DRAFT- DO NOT CITE OR QUOTE

Asymptotic Correlation Matrix of Paramet er Estimates

background intercept slope

background 1 0.11 0.2

intercept 0.11 1 0.98

slope 0.2 0.98 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit background 0.249911 * * * intercept 7.9009 * * * slope 2.32966 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -103.017 4 Fitted model -103.017 3 0.00053 3199 1 0.9816 Reduced model -152.026 1 98. 0188 3 <.0001

AIC: 212.034

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.2499 19.993 20.000 80 0.002 0.0237 0.4797 23.025 23.000 48 -0.007 0.0618 0.8535 40.966 41.000 48 0.014 0.1560 0.9795 47.017 47.000 48 -0.017

Chi^2 = 0.00 d.f. = 1 P-value = 0.9816

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.00951077

BMDL = 0.00435683

### B-34 DRAFT- DO NOT CITE OR QUOTE 0.2 0.4 0.6 0.8 1

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16Fraction Affected

dose LogProbit Model with 0.95 Confidence Level

16:04 10/06 2008

BMDL BMD LogProbit

================================================== ================== Probit Model. (Version: 3.1; Date: 05/16/200 8) Input Data File: C:\USEPA\BMDS2\Temp\tmpF5.(d) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm pF5.plt Mon Oct 06 16:04:48 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = Background + (1-Background) * CumNorm(Intercept +Slope*Log(Dose)),

where CumNorm(.) is the cumulative normal distri bution function

Dependent variable = Response Independent variable = DOSE Slope parameter is restricted as slope >= 1

Total number of observations = 4 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

User has chosen the log transformed model

Default Initial (and Specified) P arameter Values

### B-35 DRAFT- DO NOT CITE OR QUOTE

background = 0.25 intercept = 4.35171 slope = 1.28667

Asymptotic Correlation Matrix of Paramet er Estimates

background intercept slope

background 1 0.12 0.21

intercept 0.12 1 0.97

slope 0.21 0.97 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit background 0.248635 0.0479558 0.154644 0.342627 intercept 4.47618 0.818254 2.87243 6.07993 slope 1.32091 0.267134 0.797338 1.84448

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -103.017 4 Fitted model -103.09 3 0.1 4675 1 0.7017 Reduced model -152.026 1 98. 0188 3 <.0001

AIC: 212.18

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.2486 19.891 20.000 80 0.028 0.0237 0.4892 23.484 23.000 48 -0.140 0.0618 0.8406 40.348 41.000 48 0.257 0.1560 0.9838 47.222 47.000 48 -0.253

Chi^2 = 0.15 d.f. = 1 P-value = 0.6982

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.00971634

BMDL = 0.00488108

### B-36 DRAFT- DO NOT CITE OR QUOTE 0.2 0.4 0.6 0.8 1

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16Fraction Affected

dose Multistage Model with 0.95 Confidence Level

16:06 10/06 2008 BMD

BMDL Multistage

================================================== ================== Multistage Model. (Version: 3.0; Date: 05/16 /2008) Input Data File: C:\USEPA\BMDS2\Temp\tmpF7.(d) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm pF7.plt Mon Oct 06 16:06:24 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = DOSE

Total number of observations = 4 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-37 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.2349 Beta(1) = 23.4597

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1)

Background 1 -0.46

Beta(1) -0.46 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.237678 * * * Beta(1) 22.7713 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -103.017 4 Fitted model -103.895 2 1.7 5601 2 0.4156 Reduced model -152.026 1 98. 0188 3 <.0001

AIC: 211.789

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.2377 19.014 20.000 80 0.259 0.0237 0.5556 26.670 23.000 48 -1.066 0.0618 0.8134 39.042 41.000 48 0.725 0.1560 0.9782 46.951 47.000 48 0.048

Chi^2 = 1.73 d.f. = 2 P-value = 0.4207

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.00225254

BMDL = 0.00176165

BMDU = 0.00294313

Taken together, (0.00176165, 0.00294313) is a 90 % two-sided confidence interval for the BMD

### B-38 DRAFT- DO NOT CITE OR QUOTE 0.2 0.4 0.6 0.8 1

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16Fraction Affected

dose Weibull Model with 0.95 Confidence Level

16:08 10/06 2008

BMDL BMD Weibull

=================================================== ================= Weibull Model using Weibull Model (Version: 2 .12; Date: 05/16/2008) Input Data File: C:\USEPA\BMDS2\Temp\tmpF9.(d) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm pF9.plt Mon Oct 06 16:08:23 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP (-slope*dose^power)]

Dependent variable = Response Independent variable = DOSE Power parameter is restricted as power >=1

Total number of observations = 4 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

Default Initial (and Specified) P arameter Values Background = 0.253086 Slope = 24.7803 Power = 1.10265

Asymptotic Correlation Matrix of Paramet er Estimates

### B-39 DRAFT- DO NOT CITE OR QUOTE

Background Slope Power

Background 1 0.14 0.23

Slope 0.14 1 0.97

Power 0.23 0.97 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.244833 0.0470971 0.152525 0.337142 Slope 36.5794 23.8993 -10.2624 83.4211 Power 1.17393 0.234182 0.71494 1.63291

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -103.017 4 Fitted model -103.595 3 1.1 5727 1 0.282 Reduced model -152.026 1 98. 0188 3 <.0001

AIC: 213.191

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.2448 19.587 20.000 80 0.107 0.0237 0.5195 24.938 23.000 48 -0.560 0.0618 0.8125 38.998 41.000 48 0.740 0.1560 0.9879 47.417 47.000 48 -0.550

Chi^2 = 1.18 d.f. = 1 P-value = 0.2783

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.00371148

BMDL = 0.00181169

### B-40 DRAFT- DO NOT CITE OR QUOTE 0.2 0.4 0.6 0.8 1

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16Fraction Affected

dose Quantal Linear Model with 0.95 Confidence Level

16:10 10/06 2008

BMDLBMD Quantal Linear

================================================== ================== Quantal Linear Model using Weibull Model (Ver sion: 2.12; Date: 05/16/2008) Input Data File: C:\USEPA\BMDS2\Temp\tmpFA.(d) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm pFA.plt Mon Oct 06 16:10:19 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP (-slope*dose)]

Dependent variable = Response Independent variable = DOSE

Total number of observations = 4 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

Default Initial (and Specified) P arameter Values Background = 0.253086 Slope = 20.4779 Power = 1 Sp ecified

Asymptotic Correlation Matrix of Paramet er Estimates

### B-41 DRAFT- DO NOT CITE OR QUOTE

( *** The model parameter(s) -Power have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Background Slope

Background 1 -0.31

Slope -0.31 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.237678 0.0452051 0.149078 0.326278 Slope 22.7713 3.5337 15.8454 29.6972

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -103.017 4 Fitted model -103.895 2 1.7 5601 2 0.4156 Reduced model -152.026 1 98. 0188 3 <.0001

AIC: 211.789

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.2377 19.014 20.000 80 0.259 0.0237 0.5556 26.670 23.000 48 -1.066 0.0618 0.8134 39.042 41.000 48 0.725 0.1560 0.9782 46.951 47.000 48 0.048

Chi^2 = 1.73 d.f. = 2 P-value = 0.4207

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.00225254

BMDL = 0.00176165

### B-42 DRAFT- DO NOT CITE OR QUOTE

SD Female Rats: Nonneoplastic forestomach lesions ( CEO in blood)

0.2 0.4 0.6 0.8 1

0 0.002 0.004 0.006 0.008 0.01Fraction Affected

dose Gamma Multi-Hit Model with 0.95 Confidence Level

09:34 10/07 2008

BMDL BMD Gamma Multi-Hit

================================================== ================== Gamma Model. (Version: 2.13; Date: 05/16/200 8) Input Data File: C:\USEPA\BMDS2\Temp\tmp1E.(d) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm p1E.plt Tue Oct 07 09:34:01 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response]= background+(1-background)*CumGamma[ slope*dose,power], where CumGamma(.) is the cummulative Gamma distr ibution function

Dependent variable = Response Independent variable = DOSE Power parameter is restricted as power >=1

Total number of observations = 4 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

Default Initial (and Specified) P arameter Values Background = 0.253086

### B-43 DRAFT- DO NOT CITE OR QUOTE

Slope = 550.799 Power = 2.0706

Asymptotic Correlation Matrix of Paramet er Estimates

Background Slope Power

Background 1 0.15 0.26

Slope 0.15 1 0.96

Power 0.26 0.96 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.24778 0.0477681 0.154157 0.341404 Slope 600.839 241.065 128.36 1073.32 Power 2.07213 0.851839 0.402552 3.7417

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -103.017 4 Fitted model -103.226 3 0.41 9043 1 0.5174 Reduced model -152.026 1 98. 0188 3 <.0001

AIC: 212.453

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.2478 19.822 20.000 80 0.046 0.0021 0.4972 23.867 23.000 48 -0.250 0.0049 0.8304 39.860 41.000 48 0.438 0.0101 0.9863 47.341 47.000 48 -0.423

Chi^2 = 0.44 d.f. = 1 P-value = 0.5092

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.000640233

BMDL = 0.000173836

### B-44 DRAFT- DO NOT CITE OR QUOTE 0.2 0.4 0.6 0.8 1

0 0.002 0.004 0.006 0.008 0.01Fraction Affected

dose Logistic Model with 0.95 Confidence Level

09:32 10/07 2008

BMDL BMD Logistic

================================================== ================== Logistic Model. (Version: 2.12; Date: 05/16/2 008) Input Data File: C:\USEPA\BMDS2\Temp\tmp110.(d ) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm p110.plt Mon Nov 10 10:51:57 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = 1/[1+EXP(-intercept-slope*dose)]

Dependent variable = Response Independent variable = DOSE Slope parameter is not restricted

Total number of observations = 4 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values background = 0 Sp ecified intercept = -0.929208 slope = 452.992

Asymptotic Correlation Matrix of Paramet er Estimates

### B-45 DRAFT- DO NOT CITE OR QUOTE

( *** The model parameter(s) -backgroun d have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

intercept slope

intercept 1 -0.66

slope -0.66 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit intercept -1.11487 0.227873 -1.56149 -0.668246 slope 547.334 80.7582 389.05 705.617

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -103.017 4 Fitted model -103.359 2 0.68 4912 2 0.71 Reduced model -152.026 1 98. 0188 3 <.0001

AIC: 210.718

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.2470 19.757 20.000 80 0.063 0.0021 0.5045 24.217 23.000 48 -0.351 0.0049 0.8250 39.600 41.000 48 0.532 0.0101 0.9880 47.425 47.000 48 -0.565

Chi^2 = 0.73 d.f. = 2 P-value = 0.6946

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.000352967

BMDL = 0.000287581

### B-46 DRAFT- DO NOT CITE OR QUOTE 0.2 0.4 0.6 0.8 1

0 0.002 0.004 0.006 0.008 0.01Fraction Affected

dose Log-Logistic Model with 0.95 Confidence Level

09:30 10/07 2008 BMDL BMD Log-Logistic

================================================== ================== Logistic Model. (Version: 2.12; Date: 05/16/2 008) Input Data File: C:\USEPA\BMDS2\Temp\tmp16.(d) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm p16.plt Tue Oct 07 09:30:55 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background+(1-background)/[1+EXP(- intercept-slope*Log(dose))]

Dependent variable = Response Independent variable = DOSE Slope parameter is restricted as slope >= 1

Total number of observations = 4 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

User has chosen the log transformed model

Default Initial Parameter Values background = 0.25 intercept = 16.1818 slope = 2.75711

### B-47 DRAFT- DO NOT CITE OR QUOTE

Asymptotic Correlation Matrix of Paramet er Estimates

background intercept slope

background 1 0.17 0.21

intercept 0.17 1 0.99

slope 0.21 0.99 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit background 0.250617 * * * intercept 15.839 * * * slope 2.69969 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -103.017 4 Fitted model -103.03 3 0.02 7282 1 0.8688 Reduced model -152.026 1 98. 0188 3 <.0001

AIC: 212.061

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.2506 20.049 20.000 80 -0.013 0.0021 0.4757 22.833 23.000 48 0.048 0.0049 0.8592 41.243 41.000 48 -0.101 0.0101 0.9766 46.875 47.000 48 0.119

Chi^2 = 0.03 d.f. = 1 P-value = 0.8699

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.000951374

BMDL = 0.000486765

### B-48 DRAFT- DO NOT CITE OR QUOTE 0.2 0.4 0.6 0.8 1

0 0.002 0.004 0.006 0.008 0.01Fraction Affected

dose Probit Model with 0.95 Confidence Level

09:47 10/07 2008

BMDL BMD

Probit

================================================== ================== Probit Model. (Version: 3.1; Date: 05/16/200 8) Input Data File: C:\USEPA\BMDS2\Temp\tmp21.(d) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm p21.plt Tue Oct 07 09:47:22 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = CumNorm(Intercept+Slope*Dose),

where CumNorm(.) is the cumulative normal distri bution function

Dependent variable = Response Independent variable = DOSE Slope parameter is not restricted

Total number of observations = 4 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

Default Initial (and Specified) P arameter Values background = 0 Sp ecified intercept = -0.580731 slope = 266.006

### B-49 DRAFT- DO NOT CITE OR QUOTE

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -backgroun d have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

intercept slope

intercept 1 -0.65

slope -0.65 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit intercept -0.645576 0.132116 -0.904519 -0.386633 slope 306.891 41.902 224.765 389.018

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -103.017 4 Fitted model -103.929 2 1.8 2488 2 0.4015 Reduced model -152.026 1 98. 0188 3 <.0001

AIC: 211.858

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.2593 20.742 20.000 80 -0.189 0.0021 0.4959 23.803 23.000 48 -0.232 0.0049 0.8021 38.499 41.000 48 0.906 0.0101 0.9929 47.661 47.000 48 -1.139

Chi^2 = 2.21 d.f. = 2 P-value = 0.3315

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.000360199

BMDL = 0.000300191

### B-50 DRAFT- DO NOT CITE OR QUOTE 0.2 0.4 0.6 0.8 1

0 0.002 0.004 0.006 0.008 0.01Fraction Affected

dose LogProbit Model with 0.95 Confidence Level

09:38 10/07 2008 BMDL BMD LogProbit

================================================== ================== Probit Model. (Version: 3.1; Date: 05/16/200 8) Input Data File: C:\USEPA\BMDS2\Temp\tmp1F.(d) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm p1F.plt Tue Oct 07 09:38:17 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = Background + (1-Background) * CumNorm(Intercept +Slope*Log(Dose)),

where CumNorm(.) is the cumulative normal distri bution function

Dependent variable = Response Independent variable = DOSE Slope parameter is restricted as slope >= 1

Total number of observations = 4 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

User has chosen the log transformed model

### B-51 DRAFT- DO NOT CITE OR QUOTE

Default Initial (and Specified) P arameter Values background = 0.25 intercept = 8.97119 slope = 1.53079

Asymptotic Correlation Matrix of Paramet er Estimates

background intercept slope

background 1 0.18 0.22

intercept 0.18 1 0.99

slope 0.22 0.99 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit background 0.249403 0.0481401 0.15505 0.343756 intercept 9.07823 1.71894 5.70916 12.4473 slope 1.54835 0.310846 0.939107 2.1576

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -103.017 4 Fitted model -103.031 3 0.029 2544 1 0.8642 Reduced model -152.026 1 98. 0188 3 <.0001

AIC: 212.063

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.2494 19.952 20.000 80 0.012 0.0021 0.4834 23.203 23.000 48 -0.059 0.0049 0.8482 40.715 41.000 48 0.115 0.0101 0.9814 47.106 47.000 48 -0.113

Chi^2 = 0.03 d.f. = 1 P-value = 0.8634

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.000982443

BMDL = 0.000515017

### B-52 DRAFT- DO NOT CITE OR QUOTE

Table B-4 . Summary of the BMD modeling results based on the incidence of forestomach lesions (hyperplasia or hyperkeratosis) in male and female F344 rats exposed to AN in drinking water for 2 years

Sex Endpoint Dose metric Selected model(s) a χ 2

p -value AIC BMDL 10 b BMDL 05 b gamma (3) 0.32 193.27 1.51 × 10 -1 9.97 ×

10 -2 Estimated administered dose (mg/kg-d) two-stage multistage

(3) 0.14 194.76 1.40 × 10 -1 8.02 × 10 -2

gamma (3) 0.32 193.27 8.14 × 10 -4 5.39 ×

10 -4 Predicted AN in blood (mg/L) two-stage multistage

(3) 0.14 194.77 7.56 × 10 -4 4.34 × 10 -4

gamma (3) 0.32 193.27 7.65 × 10 -5 5.06 ×

10 -5 Male Forestomach lesions

Predicted CEO

in blood (mg/L) two-stage multistage

(3) 0.14 194.76 7.10 × 10 -5 4.07 × 10 -5

logistic (3) 0.32 141.06 2.31 × 10 -1 1.54 × 10 -1 two-stage multistage (3) 0.39 140.80 2.09 × 10 -1 1.17 ×

10 -1 Estimated administered dose (mg/kg-d) probit (3) 0.26 141.38 2.18 × 10 -1 1.40 × 10 -1

logistic (3) 0.32 141.06 1.11 × 10 -3 7.34 × 10 -4 two-stage multistage (3) 0.39 140.80 9.97 × 10 -4 5.58 ×

10 -4 Predicted AN in blood (mg/L) probit (3) 0.26 141.38 1.04 × 10 -3 6.69 × 10 -4

logistic (3) 0.32 141.07 1.02 × 10 -4 6.78 × 10 -5 two-stage multistage (3) 0.39 140.81 9.23 × 10 -5 5.17 ×

10 -5 Female Forestomach lesions

Predicted CEO

in blood (mg/L) probit (3) 0.26 141.40 9.63 × 10 -5 6.19 × 10 -5

a All dichotomous models in EPA’s BMDS (version 2.0) were fit to the incidence of forestomach lesions (hyperplasia or hyperkeratosis) in F344 rats using the data presented in Table B-1. For BMD modeling, three different dose metrics were employed: (1) administ ered animal dose (estimated) expressed in mg/kg-d, (2) AN in blood (predicted) expressed in mg/L, and (3) CEO in blood (predicted) expressed in mg/L. Adequate fit of a model was achieved if the χ 2 goodness-of-fit statistic yielded a p -value > 0.1. The numbers in parentheses indicate the number of dose groups dropped in order to obtain an adequate fit, starting with the highest dose group . Of those models exhibiting adequate fit, the selected model was the model with the lowest AIC value, and is ind icated in bold in the table.
b BMDL 10 and BMDL 05 estimates were derived from the selected model. I f more than one model shared the lowest AIC, the mean BMDL 10 and BMDL 05 were calculated, as per the EPA’s Benchmark Dose Technical Guidance Document

(U.S. EPA, 2000b).

Sources: Johannsen and Levinskas (2002b); Biodynam ics (1980c).

### B-53 DRAFT- DO NOT CITE OR QUOTE

F344 Male Rats: Forestomach lesions (administered d ose)

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

0 0.05 0.1 0.15 0.2 0.25Fraction Affected

dose Gamma Multi-Hit Model with 0.95 Confidence Level

14:10 10/07 2008 BMDL BMD Gamma Multi-Hit

=================================================== ================= Gamma Model. (Version: 2.13; Date: 05/16/200 8) Input Data File: C:\USEPA\BMDS2\Temp\tmp104.(d ) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm p104.plt Tue Oct 07 14:10:45 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response]= background+(1-background)*CumGamma[ slope*dose,power], where CumGamma(.) is the cummulative Gamma distr ibution function

Dependent variable = Response Independent variable = DOSE Power parameter is restricted as power >=1

Total number of observations = 3 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

Default Initial (and Specified) P arameter Values Background = 0.071875

### B-54 DRAFT- DO NOT CITE OR QUOTE

Slope = 5.59733 Power = 2.91574

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Power have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Background Slope

Background 1 -0.24

Slope -0.24 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0585772 0.0151899 0.0288055 0.0883489 Slope 57.0862 2.86678 51.4674 62.705 Power 18 NA

NA - Indicates that this parameter has hit a bound implied by some inequality constraint and thus has no standard error.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -94.1158 3 Fitted model -94.6364 2 1.0 4132 1 0.3075 Reduced model -103.388 1 18. 5446 2 <.0001

AIC: 193.273

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0586 9.314 11.000 159 0.569 0.0800 0.0586 4.686 3.000 80 -0.803 0.2500 0.2400 18.000 18.000 75 0.000

Chi^2 = 0.97 d.f. = 1 P-value = 0.3250

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.203802

BMDL = 0.0996986

### B-55 DRAFT- DO NOT CITE OR QUOTE 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

0 0.05 0.1 0.15 0.2 0.25Fraction Affected

dose Multistage Model with 0.95 Confidence Level

14:12 10/07 2008 BMD BMDL Multistage

================================================== ================== Multistage Model. (Version: 3.0; Date: 05/16 /2008) Input Data File: C:\USEPA\BMDS2\Temp\tmp105.(d ) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm p105.plt Tue Oct 07 14:12:49 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1-beta2*dose^2)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = DOSE

Total number of observations = 3 Total number of records with missing values = 0 Total number of parameters in model = 3 Total number of specified parameters = 0 Degree of polynomial = 2

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-56 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.0438965 Beta(1) = 0 Beta(2) = 3.62384

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Beta(1) have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Background Beta(2)

Background 1 -0.49

Beta(2) -0.49 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0563684 * * * Beta(1) 0 * * * Beta(2) 3.20151 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -94.1158 3 Fitted model -95.381 2 2.5 3038 1 0.1117 Reduced model -103.388 1 18. 5446 2 <.0001

AIC: 194.762

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0564 8.963 11.000 159 0.701 0.0800 0.0755 6.041 3.000 80 -1.287 0.2500 0.2275 17.062 18.000 75 0.258

Chi^2 = 2.21 d.f. = 1 P-value = 0.1368

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.126576

BMDL = 0.0802271

BMDU = 0.173506

Taken together, (0.0802271, 0.173506) is a 90 % two-sided confidence interval for the BMD

### B-57 DRAFT- DO NOT CITE OR QUOTE

F344 Male Rats: Forestomach lesions (AN in blood))

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

0 0.0002 0.0004 0.0006 0.0008 0.001 0.0012 0.0014Fraction Affected

dose Gamma Multi-Hit Model with 0.95 Confidence Level

14:46 10/07 2008 BMDL BMD Gamma Multi-Hit

================================================== ================== Gamma Model. (Version: 2.13; Date: 05/16/200 8) Input Data File: C:\USEPA\BMDS2\Temp\tmp107.(d ) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm p107.plt Tue Oct 07 14:46:28 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response]= background+(1-background)*CumGamma[ slope*dose,power], where CumGamma(.) is the cummulative Gamma distr ibution function

Dependent variable = Response Independent variable = DOSE Power parameter is restricted as power >=1

Total number of observations = 3 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

Default Initial (and Specified) P arameter Values Background = 0.071875 Slope = 1039.5

### B-58 DRAFT- DO NOT CITE OR QUOTE

Power = 2.92132

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Power have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Background Slope

Background 1 -0.24

Slope -0.24 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0585772 0.01519 0.0288053 0.088349 Slope 10571.5 530.886 9531.01 11612 Power 18 NA

NA - Indicates that this parameter has hit a bound implied by some inequality constraint and thus has no standard error.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -94.1158 3 Fitted model -94.6364 2 1.0 4133 1 0.3075 Reduced model -103.388 1 18. 5446 2 <.0001

AIC: 193.273

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0586 9.314 11.000 159 0.569 0.0004 0.0586 4.686 3.000 80 -0.803 0.0014 0.2400 18.000 18.000 75 0.000

Chi^2 = 0.97 d.f. = 1 P-value = 0.3250

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.00110053

BMDL = 0.00053936

### B-59 DRAFT- DO NOT CITE OR QUOTE 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

0 0.0002 0.0004 0.0006 0.0008 0.001 0.0012 0.0014Fraction Affected

dose Multistage Model with 0.95 Confidence Level

14:54 10/07 2008 BMD BMDL Multistage

================================================== ================== Multistage Model. (Version: 3.0; Date: 05/16 /2008) Input Data File: C:\USEPA\BMDS2\Temp\tmp10C.(d ) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm p10C.plt Tue Oct 07 14:54:25 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1-beta2*dose^2)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = DOSE

Total number of observations = 3 Total number of records with missing values = 0 Total number of parameters in model = 3 Total number of specified parameters = 0 Degree of polynomial = 2

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-60 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.043854 Beta(1) = 0 Beta(2) = 124287

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Beta(1) have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Background Beta(2)

Background 1 -0.49

Beta(2) -0.49 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0563637 * * * Beta(1) 0 * * * Beta(2) 109747 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -94.1158 3 Fitted model -95.3848 2 2.5 3803 1 0.1111 Reduced model -103.388 1 18. 5446 2 <.0001

AIC: 194.77

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0564 8.962 11.000 159 0.701 0.0004 0.0756 6.047 3.000 80 -1.289 0.0014 0.2274 17.057 18.000 75 0.260

Chi^2 = 2.22 d.f. = 1 P-value = 0.1363

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.000683652

BMDL = 0.000433678

BMDU = 0.000937168

Taken together, (0.000433678, 0.000937168) is a 90 % two-sided confidence interval for the BMD

### B-61 DRAFT- DO NOT CITE OR QUOTE

F344 Male Rats: Forestomach lesions (CEO in blood)

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

0 2e-005 4e-005 6e-005 8e-005 0.0001 0.00012Fraction Affected

dose Gamma Multi-Hit Model with 0.95 Confidence Level

16:32 10/07 2008 BMDL BMD Gamma Multi-Hit

================================================== ================== Gamma Model. (Version: 2.13; Date: 05/16/200 8) Input Data File: C:\USEPA\BMDS2\Temp\tmp115.(d ) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm p115.plt Tue Oct 07 16:32:49 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response]= background+(1-background)*CumGamma[ slope*dose,power], where CumGamma(.) is the cummulative Gamma distr ibution function

Dependent variable = Response Independent variable = DOSE Power parameter is restricted as power >=1

Total number of observations = 3 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

Default Initial (and Specified) P arameter Values Background = 0.071875

### B-62 DRAFT- DO NOT CITE OR QUOTE

Slope = 11005 Power = 2.91337

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Power have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Background Slope

Background 1 -0.24

Slope -0.24 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0585772 0.0151899 0.0288055 0.0883489 Slope 112374 5643.28 101314 123435 Power 18 NA

NA - Indicates that this parameter has hit a bound implied by some inequality constraint and thus has no standard error.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -94.1158 3 Fitted model -94.6364 2 1.0 4132 1 0.3075 Reduced model -103.388 1 18. 5446 2 <.0001

AIC: 193.273

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0586 9.314 11.000 159 0.569 0.0000 0.0586 4.686 3.000 80 -0.803 0.0001 0.2400 18.000 18.000 75 0.000

Chi^2 = 0.97 d.f. = 1 P-value = 0.3250

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.000103532

BMDL = 5.06073e-005

### B-63 DRAFT- DO NOT CITE OR QUOTE 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

0 2e-005 4e-005 6e-005 8e-005 0.0001 0.00012Fraction Affected

dose Multistage Model with 0.95 Confidence Level

16:39 10/07 2008 BMD BMDL Multistage

================================================== ================== Multistage Model. (Version: 3.0; Date: 05/16 /2008) Input Data File: C:\USEPA\BMDS2\Temp\tmp11A.(d ) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm p11A.plt Tue Oct 07 16:39:04 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1-beta2*dose^2)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = DOSE

Total number of observations = 3 Total number of records with missing values = 0 Total number of parameters in model = 3 Total number of specified parameters = 0 Degree of polynomial = 2

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-64 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.0439146 Beta(1) = 0 Beta(2) = 1.40418e+007

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Beta(1) have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Background Beta(2)

Background 1 -0.49

Beta(2) -0.49 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0563704 * * * Beta(1) 0 * * * Beta(2) 1.2408e+007 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -94.1158 3 Fitted model -95.3793 2 2.5 2713 1 0.1119 Reduced model -103.388 1 18. 5446 2 <.0001

AIC: 194.759

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0564 8.963 11.000 159 0.700 0.0000 0.0755 6.038 3.000 80 -1.286 0.0001 0.2275 17.064 18.000 75 0.258

Chi^2 = 2.21 d.f. = 1 P-value = 0.1371

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 6.42953e-005

BMDL = 4.07373e-005

BMDU = 8.81314e-005

Taken together, (4.07373e-005, 8.81314e-005) is a 9 0 % two-sided confidence interval for the
BMD

### B-65 DRAFT- DO NOT CITE OR QUOTE

F344 Female Rats: Forestomach lesions (administered dose)

0 0.05 0.1 0.15 0.2 0.25 0.3

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35Fraction Affected

dose Logistic Model with 0.95 Confidence Level

13:49 10/08 2008 BMDL BMD Logistic

================================================== ================== Logistic Model. (Version: 2.12; Date: 05/16/2 008) Input Data File: C:\USEPA\BMDS2\Temp\tmpA62.(d ) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm pA62.plt Wed Oct 08 13:49:00 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = 1/[1+EXP(-intercept-slope*dose)]

Dependent variable = Response Independent variable = DOSE Slope parameter is not restricted

Total number of observations = 3 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values background = 0 Sp ecified intercept = -3.79894 slope = 6.38252

### B-66 DRAFT- DO NOT CITE OR QUOTE

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -backgroun d have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

intercept slope

intercept 1 -0.88

slope -0.88 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit intercept -3.92594 0.477082 -4.86101 -2.99088 slope 6.94669 1.60094 3.80891 10.0845

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -67.9873 3 Fitted model -68.5288 2 1.0 8303 1 0.298 Reduced model -79.8392 1 23. 7038 2 <.0001

AIC: 141.058

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0193 3.017 4.000 156 0.571 0.1200 0.0434 3.474 2.000 80 -0.809 0.3600 0.1939 15.509 16.000 80 0.139

Chi^2 = 1.00 d.f. = 1 P-value = 0.3175

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.189157

BMDL = 0.153543

### B-67 DRAFT- DO NOT CITE OR QUOTE 0 0.05 0.1 0.15 0.2 0.25 0.3

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35Fraction Affected

dose Multistage Model with 0.95 Confidence Level

13:58 10/08 2008 BMD BMDL Multistage

================================================== ================== Multistage Model. (Version: 3.0; Date: 05/16 /2008) Input Data File: C:\USEPA\BMDS2\Temp\tmpA65.(d ) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm pA65.plt Wed Oct 08 13:58:05 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1-beta2*dose^2)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = DOSE

Total number of observations = 3 Total number of records with missing values = 0 Total number of parameters in model = 3 Total number of specified parameters = 0 Degree of polynomial = 2

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-68 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.0147377 Beta(1) = 0 Beta(2) = 1.59649

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Beta(1) have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Background Beta(2)

Background 1 -0.51

Beta(2) -0.51 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0216322 * * * Beta(1) 0 * * * Beta(2) 1.47012 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -67.9873 3 Fitted model -68.401 2 0.82 7463 1 0.363 Reduced model -79.8392 1 23. 7038 2 <.0001

AIC: 140.802

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0216 3.375 4.000 156 0.344 0.1200 0.0421 3.370 2.000 80 -0.763 0.3600 0.1914 15.308 16.000 80 0.197

Chi^2 = 0.74 d.f. = 1 P-value = 0.3901

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.18679

BMDL = 0.116832

BMDU = 0.243753

Taken together, (0.116832, 0.243753) is a 90 % two-sided confidence interval for the BMD

### B-69 DRAFT- DO NOT CITE OR QUOTE 0 0.05 0.1 0.15 0.2 0.25 0.3

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35Fraction Affected

dose Probit Model with 0.95 Confidence Level

14:01 10/08 2008 BMDL BMD Probit

================================================== ================== Probit Model. (Version: 3.1; Date: 05/16/200 8) Input Data File: C:\USEPA\BMDS2\Temp\tmpA66.(d ) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm pA66.plt Wed Oct 08 14:01:52 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = CumNorm(Intercept+Slope*Dose),

where CumNorm(.) is the cumulative normal distri bution function

Dependent variable = Response Independent variable = DOSE Slope parameter is not restricted

Total number of observations = 3 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

Default Initial (and Specified) P arameter Values background = 0 Sp ecified intercept = -2.03888 slope = 3.08079

### B-70 DRAFT- DO NOT CITE OR QUOTE

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -backgroun d have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

intercept slope

intercept 1 -0.81

slope -0.81 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit intercept -2.0746 0.1976 -2.46189 -1.68732 slope 3.33316 0.739981 1.88282 4.78349

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -67.9873 3 Fitted model -68.6922 2 1.4 0991 1 0.2351 Reduced model -79.8392 1 23. 7038 2 <.0001

AIC: 141.384

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0190 2.966 4.000 156 0.606 0.1200 0.0470 3.760 2.000 80 -0.930 0.3600 0.1909 15.270 16.000 80 0.208

Chi^2 = 1.28 d.f. = 1 P-value = 0.2588

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.175274

BMDL = 0.140136

### B-71 DRAFT- DO NOT CITE OR QUOTE

F344 Female Rats: Forestomach lesions (AN in blood)

0 0.05 0.1 0.15 0.2 0.25 0.3

0 0.0002 0.0004 0.0006 0.0008 0.001 0.0012 0.0014 0.0016 0.0018Fraction Affected

dose Logistic Model with 0.95 Confidence Level

16:01 10/08 2008 BMDL BMD Logistic

=================================================== ================= Logistic Model. (Version: 2.12; Date: 05/16/2 008) Input Data File: C:\USEPA\BMDS2\Temp\tmpA6F.(d ) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm pA6F.plt Wed Oct 08 16:01:43 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = 1/[1+EXP(-intercept-slope*dose)]

Dependent variable = Response Independent variable = DOSE Slope parameter is not restricted

Total number of observations = 3 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values background = 0 Sp ecified intercept = -3.79881

### B-72 DRAFT- DO NOT CITE OR QUOTE

slope = 1335.91

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -backgroun d have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

intercept slope

intercept 1 -0.88

slope -0.88 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit intercept -3.92577 0.477035 -4.86074 -2.9908 slope 1453.89 335.047 797.213 2110.57

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -67.9873 3 Fitted model -68.5281 2 1. 0816 1 0.2983 Reduced model -79.8392 1 23. 7038 2 <.0001

AIC: 141.056

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0193 3.018 4.000 156 0.571 0.0006 0.0434 3.473 2.000 80 -0.808 0.0017 0.1939 15.509 16.000 80 0.139

Chi^2 = 1.00 d.f. = 1 P-value = 0.3178

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.00090371

BMDL = 0.000733555

### B-73 DRAFT- DO NOT CITE OR QUOTE 0 0.05 0.1 0.15 0.2 0.25 0.3

0 0.0002 0.0004 0.0006 0.0008 0.001 0.0012 0.0014 0.0016 0.0018Fraction Affected

dose Multistage Model with 0.95 Confidence Level

16:07 10/08 2008 BMD BMDL Multistage

================================================== ================== Multistage Model. (Version: 3.0; Date: 05/16 /2008) Input Data File: C:\USEPA\BMDS2\Temp\tmpA72.(d ) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm pA72.plt Wed Oct 08 16:07:08 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1-beta2*dose^2)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = DOSE

Total number of observations = 3 Total number of records with missing values = 0 Total number of parameters in model = 3 Total number of specified parameters = 0 Degree of polynomial = 2

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-74 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.0147497 Beta(1) = 0 Beta(2) = 69935.2

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Beta(1) have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Background Beta(2)

Background 1 -0.51

Beta(2) -0.51 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.021634 * * * Beta(1) 0 * * * Beta(2) 64407.8 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -67.9873 3 Fitted model -68.4002 2 0.82 5863 1 0.3635 Reduced model -79.8392 1 23. 7038 2 <.0001

AIC: 140.8

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0216 3.375 4.000 156 0.344 0.0006 0.0421 3.369 2.000 80 -0.762 0.0017 0.1914 15.310 16.000 80 0.196

Chi^2 = 0.74 d.f. = 1 P-value = 0.3905

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.000892403

BMDL = 0.000558013

BMDU = 0.00116455

Taken together, (0.000558013, 0.00116455) is a 90 % two-sided confidence interval for the BMD

### B-75 DRAFT- DO NOT CITE OR QUOTE 0 0.05 0.1 0.15 0.2 0.25 0.3

0 0.0002 0.0004 0.0006 0.0008 0.001 0.0012 0.0014 0.0016 0.0018Fraction Affected

dose Probit Model with 0.95 Confidence Level

16:11 10/08 2008 BMDL BMD Probit

================================================== ================== Probit Model. (Version: 3.1; Date: 05/16/200 8) Input Data File: C:\USEPA\BMDS2\Temp\tmpA73.(d ) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm pA73.plt Wed Oct 08 16:11:23 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = CumNorm(Intercept+Slope*Dose),

where CumNorm(.) is the cumulative normal distri bution function

Dependent variable = Response Independent variable = DOSE Slope parameter is not restricted

Total number of observations = 3 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

Default Initial (and Specified) P arameter Values background = 0 Sp ecified intercept = -2.03885 slope = 644.864

### B-76 DRAFT- DO NOT CITE OR QUOTE

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -backgroun d have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

intercept slope

intercept 1 -0.81

slope -0.81 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit intercept -2.07454 0.197583 -2.4618 -1.68729 slope 697.628 154.868 394.091 1001.16

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -67.9873 3 Fitted model -68.6913 2 1.4 0812 1 0.2354 Reduced model -79.8392 1 23. 7038 2 <.0001

AIC: 141.383

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0190 2.966 4.000 156 0.606 0.0006 0.0470 3.759 2.000 80 -0.929 0.0017 0.1909 15.271 16.000 80 0.207

Chi^2 = 1.27 d.f. = 1 P-value = 0.2590

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.000837374

BMDL = 0.000669495

### B-77 DRAFT- DO NOT CITE OR QUOTE

F344 Female Rats: Forestomach lesions (CEO in blood )

0 0.05 0.1 0.15 0.2 0.25 0.3

0 2e-005 4e-005 6e-005 8e-005 0.0001 0.00012 0.00014 0.00016Fraction Affected

dose Logistic Model with 0.95 Confidence Level

09:45 10/09 2008 BMDL BMD Logistic

================================================== ================== Logistic Model. (Version: 2.12; Date: 05/16/2 008) Input Data File: C:\USEPA\BMDS2\Temp\tmp10.(d) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm p10.plt Thu Oct 09 09:45:26 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = 1/[1+EXP(-intercept-slope*dose)]

Dependent variable = Response Independent variable = DOSE Slope parameter is not restricted

Total number of observations = 3 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values background = 0 Sp ecified intercept = -3.79973

### B-78 DRAFT- DO NOT CITE OR QUOTE

slope = 14448.5

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -backgroun d have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

intercept slope

intercept 1 -0.88

slope -0.88 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit intercept -3.92703 0.4774 -4.86272 -2.99135 slope 15733 3627.17 8623.9 22842.1

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -67.9873 3 Fitted model -68.5334 2 1.0 9233 1 0.296 Reduced model -79.8392 1 23. 7038 2 <.0001

AIC: 141.067

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0193 3.014 4.000 156 0.573 0.0001 0.0435 3.482 2.000 80 -0.812 0.0002 0.1938 15.504 16.000 80 0.140

Chi^2 = 1.01 d.f. = 1 P-value = 0.3155

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 8.35696e-005

BMDL = 6.78392e-005

### B-79 DRAFT- DO NOT CITE OR QUOTE 0 0.05 0.1 0.15 0.2 0.25 0.3

0 2e-005 4e-005 6e-005 8e-005 0.0001 0.00012 0.00014 0.00016Fraction Affected

dose Multistage Model with 0.95 Confidence Level

14:46 10/09 2008 BMD BMDL Multistage

================================================== ================== Multistage Model. (Version: 3.0; Date: 05/16 /2008) Input Data File: C:\USEPA\BMDS2\Temp\tmpFC.(d) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm pFC.plt Thu Oct 09 14:46:41 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1-beta2*dose^2)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = DOSE

Total number of observations = 3 Total number of records with missing values = 0 Total number of parameters in model = 3 Total number of specified parameters = 0 Degree of polynomial = 2

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-80 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.0146597 Beta(1) = 0 Beta(2) = 8.18648e+006

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Beta(1) have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Background Beta(2)

Background 1 -0.51

Beta(2) -0.51 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0216202 * * * Beta(1) 0 * * * Beta(2) 7.53198e+006 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -67.9873 3 Fitted model -68.4062 2 0.83 7895 1 0.36 Reduced model -79.8392 1 23. 7038 2 <.0001

AIC: 140.812

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0216 3.373 4.000 156 0.345 0.0001 0.0423 3.380 2.000 80 -0.767 0.0002 0.1913 15.301 16.000 80 0.199

Chi^2 = 0.75 d.f. = 1 P-value = 0.3873

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 8.25232e-005

BMDL = 5.17106e-005

BMDU = 0.000107687

Taken together, (5.17106e-005, 0.000107687) is a 90 % two-sided confidence interval for the
BMD

### B-81 DRAFT- DO NOT CITE OR QUOTE 0 0.05 0.1 0.15 0.2 0.25 0.3

0 2e-005 4e-005 6e-005 8e-005 0.0001 0.00012 0.00014 0.00016Fraction Affected

dose Probit Model with 0.95 Confidence Level

14:50 10/09 2008 BMDL BMD Probit

================================================== ================== Probit Model. (Version: 3.1; Date: 05/16/200 8) Input Data File: C:\USEPA\BMDS2\Temp\tmpFD.(d) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm pFD.plt Thu Oct 09 14:50:46 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = CumNorm(Intercept+Slope*Dose),

where CumNorm(.) is the cumulative normal distri bution function

Dependent variable = Response Independent variable = DOSE Slope parameter is not restricted

Total number of observations = 3 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

Default Initial (and Specified) P arameter Values background = 0 Sp ecified intercept = -2.03906 slope = 6972.11

### B-82 DRAFT- DO NOT CITE OR QUOTE

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -backgroun d have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

intercept slope

intercept 1 -0.81

slope -0.81 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit intercept -2.075 0.197714 -2.46251 -1.68749 slope 7547.46 1676.24 4262.09 10832.8

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -67.9873 3 Fitted model -68.6981 2 1.4 2158 1 0.2331 Reduced model -79.8392 1 23. 7038 2 <.0001

AIC: 141.396

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0190 2.963 4.000 156 0.608 0.0001 0.0471 3.769 2.000 80 -0.934 0.0002 0.1908 15.264 16.000 80 0.209

Chi^2 = 1.29 d.f. = 1 P-value = 0.2569

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 7.74403e-005

BMDL = 6.19187e-005

### B-83 DRAFT- DO NOT CITE OR QUOTE

Table B-5. Summary of the BMD modeling results bas ed on the incidence of forestomach lesions (hyperplasia or hyperkeratosis) in male and female B6C3F 1 

### mice exposed to AN via gavage for 2 years

Sex Endpoint Dose metric Selected model(s) a χ 2

p -value AIC BMDL 10 b BMDL 05 b

gamma 0.80 156.45 3.45 1.68 logistic 0.37 158.01 6.37 3.72 log-logistic 0.87 156.30 3.01 1.43 probit 0.42 157.74 5.96 3.42 log-probit 0.33 158.23 5.53 3.85
one-stage multistage 0.80 156.45 3.45 1.68

Weibull 0.80 156.45 3.45 1.68 Male Forestomach lesions Estimated

administered dose (mg/kg-d)

quantal linear 0.80 156.45 3.45 1.68

gamma 0.74 116.17 6.24 3.04 logistic 0.87 114.33 8.95 5.60 log-logistic 0.75 116.17 5.98 2.83 probit 0.90 114.28 8.51 5.19 log-probit 0.81 114.48 8.12 5.65 one-stage multistage 0.92 114.24 6.20 3.02

Weibull 0.74 116.18 6.24 3.04 Female Forestomach lesions Estimated

administered dose (mg/kg-d)

quantal linear 0.92 114.24 6.20 3.02

a All dichotomous models in EPA’s BMDS (version 2.0) were fit to the incidence of forestomach lesions (hyperplasia or hyperkeratosis) in B6C3F 1 mice using the data presented in Table B-2. For B MD modeling, animal dose (estimated), expressed in mg/kg-d, was employe d. Adequate fit of a model was achieved if the χ 2 goodnessof-fit statistic yielded a p -value > 0.1. Of those models exhibiting adequate fit, th e selected model was the model with the lowest AIC value, and is indicated in bold in the table.

b BMDL 10 and BMDL 05 estimates were derived from the selected model. I f more than one model shared the lowest AIC, the mean BMDL 10 and BMDL 05 were calculated, as per the EPA’s Benchmark Dose Technical Guidance Document

(U.S. EPA, 2000b).

Source: NTP (2001).

### B-84 DRAFT- DO NOT CITE OR QUOTE

B6C3F 1 Male Mice: Forestomach lesions (administered dose)

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4

0 2 4 6 8 10 12 14Fraction Affected

dose Gamma Multi-Hit Model with 0.95 Confidence Level

13:51 11/14 2008 BMDL BMD Gamma Multi-Hit

================================================== ================== Gamma Model. (Version: 2.13; Date: 05/16/200 8) Input Data File: C:\USEPA\BMDS2\Temp\tmp111.(d ) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm p111.plt Fri Nov 14 13:51:24 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response]= background+(1-background)*CumGamma[ slope*dose,power], where CumGamma(.) is the cummulative Gamma distr ibution function

Dependent variable = Response Independent variable = DOSE Power parameter is restricted as power >=1

Total number of observations = 4 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

Default Initial (and Specified) P arameter Values Background = 0.0490196

### B-85 DRAFT- DO NOT CITE OR QUOTE

Slope = 0.0449456 Power = 1.3

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Power have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Background Slope

Background 1 -0.53

Slope -0.53 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0444165 0.025521 -0.00560381 0.0944368 Slope 0.0201613 0.00593774 0.00852351 0.031799 Power 1 NA

NA - Indicates that this parameter has hit a bound implied by some inequality constraint and thus has no standard error.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -76.0086 4 Fitted model -76.2255 2 0.43 3714 2 0.805 Reduced model -82.7874 1 13. 5576 3 0.003574

AIC: 156.451

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0444 2.221 2.000 50 -0.152 1.8000 0.0785 3.924 4.000 50 0.040 7.1000 0.1719 8.593 10.000 50 0.527 14.3000 0.2838 14.188 13.000 50 -0.373

Chi^2 = 0.44 d.f. = 2 P-value = 0.8019

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 2.54415

BMDL = 1.68095

### B-86 DRAFT- DO NOT CITE OR QUOTE 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4

0 2 4 6 8 10 12 14Fraction Affected

dose Logistic Model with 0.95 Confidence Level

14:00 11/14 2008 BMDL BMD Logistic

================================================== ================== Logistic Model. (Version: 2.12; Date: 05/16/2 008) Input Data File: C:\USEPA\BMDS2\Temp\tmp113.(d ) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm p113.plt Fri Nov 14 14:00:33 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = 1/[1+EXP(-intercept-slope*dose)]

Dependent variable = Response Independent variable = DOSE Slope parameter is not restricted

Total number of observations = 4 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values background = 0 Sp ecified intercept = -2.67373 slope = 0.130289

Asymptotic Correlation Matrix of Paramet er Estimates

### B-87 DRAFT- DO NOT CITE OR QUOTE

( *** The model parameter(s) -backgroun d have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

intercept slope

intercept 1 -0.83

slope -0.83 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit intercept -2.63925 0.372305 -3.36896 -1.90955 slope 0.121074 0.0365284 0.04948 0.192669

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -76.0086 4 Fitted model -77.0042 2 1.9 9121 2 0.3695 Reduced model -82.7874 1 13. 5576 3 0.003574

AIC: 158.008

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0667 3.333 2.000 50 -0.756 1.8000 0.0816 4.078 4.000 50 -0.040 7.1000 0.1443 7.217 10.000 50 1.120 14.3000 0.2874 14.372 13.000 50 -0.429

Chi^2 = 2.01 d.f. = 2 P-value = 0.3660

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 4.80697

BMDL = 3.72464

### B-88 DRAFT- DO NOT CITE OR QUOTE 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4

0 2 4 6 8 10 12 14Fraction Affected

dose Log-Logistic Model with 0.95 Confidence Level

14:04 11/14 2008 BMDL BMD Log-Logistic

================================================== ================== Logistic Model. (Version: 2.12; Date: 05/16/2 008) Input Data File: C:\USEPA\BMDS2\Temp\tmp116.(d ) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm p116.plt Fri Nov 14 14:04:51 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background+(1-background)/[1+EXP(- intercept-slope*Log(dose))]

Dependent variable = Response Independent variable = DOSE Slope parameter is restricted as slope >= 1

Total number of observations = 4 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

User has chosen the log transformed model

Default Initial Parameter Values background = 0.04 intercept = -3.73286 slope = 1

### B-89 DRAFT- DO NOT CITE OR QUOTE

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -slope have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

background intercept

background 1 -0.54

intercept -0.54 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit background 0.0421528 * * * intercept -3.76687 * * * slope 1 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -76.0086 4 Fitted model -76.1489 2 0.28 0564 2 0.8691 Reduced model -82.7874 1 13. 5576 3 0.003574

AIC: 156.298

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0422 2.108 2.000 50 -0.076 1.8000 0.0804 4.021 4.000 50 -0.011 7.1000 0.1772 8.862 10.000 50 0.422 14.3000 0.2802 14.009 13.000 50 -0.318

Chi^2 = 0.28 d.f. = 2 P-value = 0.8674

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 2.27602

BMDL = 1.42584

### B-90 DRAFT- DO NOT CITE OR QUOTE 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4

0 2 4 6 8 10 12 14Fraction Affected

dose Probit Model with 0.95 Confidence Level

14:27 11/14 2008 BMDL BMD Probit

================================================== ================== Probit Model. (Version: 3.1; Date: 05/16/200 8) Input Data File: C:\USEPA\BMDS2\Temp\tmp124.(d ) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm p124.plt Fri Nov 14 14:27:57 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = CumNorm(Intercept+Slope*Dose),

where CumNorm(.) is the cumulative normal distri bution function

Dependent variable = Response Independent variable = DOSE Slope parameter is not restricted

Total number of observations = 4 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

Default Initial (and Specified) P arameter Values background = 0 Sp ecified intercept = -1.57644 slope = 0.0736548

### B-91 DRAFT- DO NOT CITE OR QUOTE

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -backgroun d have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

intercept slope

intercept 1 -0.8

slope -0.8 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit intercept -1.52854 0.189536 -1.90002 -1.15706 slope 0.0679152 0.0200887 0.028542 0.107288

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -76.0086 4 Fitted model -76.8681 2 1.7 1884 2 0.4234 Reduced model -82.7874 1 13. 5576 3 0.003574

AIC: 157.736

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0632 3.159 2.000 50 -0.674 1.8000 0.0798 3.991 4.000 50 0.005 7.1000 0.1477 7.385 10.000 50 1.042 14.3000 0.2886 14.432 13.000 50 -0.447

Chi^2 = 1.74 d.f. = 2 P-value = 0.4189

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 4.44923

BMDL = 3.4216

### B-92 DRAFT- DO NOT CITE OR QUOTE 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4

0 2 4 6 8 10 12 14Fraction Affected

dose LogProbit Model with 0.95 Confidence Level

14:16 11/14 2008 BMDL BMD LogProbit

================================================== ================== Probit Model. (Version: 3.1; Date: 05/16/200 8) Input Data File: C:\USEPA\BMDS2\Temp\tmp11E.(d ) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm p11E.plt Fri Nov 14 14:16:36 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = Background + (1-Background) * CumNorm(Intercept +Slope*Log(Dose)),

where CumNorm(.) is the cumulative normal distri bution function

Dependent variable = Response Independent variable = DOSE Slope parameter is restricted as slope >= 1

Total number of observations = 4 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

User has chosen the log transformed model

Default Initial (and Specified) P arameter Values

### B-93 DRAFT- DO NOT CITE OR QUOTE

background = 0.04 intercept = -3.00109 slope = 1

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -slope have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

background intercept

background 1 -0.53

intercept -0.53 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit background 0.0650367 0.0264604 0.0131753 0.116898 intercept -3.3131 0.219612 -3.74353 -2.88267 slope 1 NA

NA - Indicates that this parameter has hit a bound implied by some inequality constraint and thus has no standard error.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -76.0086 4 Fitted model -77.1132 2 2.2 0909 2 0.3314 Reduced model -82.7874 1 13. 5576 3 0.003574

AIC: 158.226

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0650 3.252 2.000 50 -0.718 1.8000 0.0680 3.402 4.000 50 0.336 7.1000 0.1473 7.367 10.000 50 1.051 14.3000 0.3053 15.263 13.000 50 -0.695

Chi^2 = 2.21 d.f. = 2 P-value = 0.3304

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 5.30287

BMDL = 3.84888

### B-94 DRAFT- DO NOT CITE OR QUOTE 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4

0 2 4 6 8 10 12 14Fraction Affected

dose Multistage Model with 0.95 Confidence Level

14:22 11/14 2008 BMD BMDL Multistage

================================================== ================== Multistage Model. (Version: 3.0; Date: 05/16 /2008) Input Data File: C:\USEPA\BMDS2\Temp\tmp121.(d ) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm p121.plt Fri Nov 14 14:22:26 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = DOSE

Total number of observations = 4 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-95 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.0536508 Beta(1) = 0.018443

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1)

Background 1 -0.71

Beta(1) -0.71 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0444165 * * * Beta(1) 0.0201613 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -76.0086 4 Fitted model -76.2255 2 0.43 3714 2 0.805 Reduced model -82.7874 1 13. 5576 3 0.003574

AIC: 156.451

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0444 2.221 2.000 50 -0.152 1.8000 0.0785 3.924 4.000 50 0.040 7.1000 0.1719 8.593 10.000 50 0.527 14.3000 0.2838 14.188 13.000 50 -0.373

Chi^2 = 0.44 d.f. = 2 P-value = 0.8019

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 2.54415

BMDL = 1.68095

BMDU = 4.75191

Taken together, (1.68095, 4.75191) is a 90 % tw o-sided confidence interval for the BMD

### B-96 DRAFT- DO NOT CITE OR QUOTE 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4

0 2 4 6 8 10 12 14Fraction Affected

dose Weibull Model with 0.95 Confidence Level

14:36 11/14 2008 BMDL BMD Weibull

================================================== ================== Weibull Model using Weibull Model (Version: 2 .12; Date: 05/16/2008) Input Data File: C:\USEPA\BMDS2\Temp\tmp127.(d ) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm p127.plt Fri Nov 14 14:36:13 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP (-slope*dose^power)]

Dependent variable = Response Independent variable = DOSE Power parameter is restricted as power >=1

Total number of observations = 4 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

Default Initial (and Specified) P arameter Values Background = 0.0490196 Slope = 0.0179876 Power = 1

Asymptotic Correlation Matrix of Paramet er Estimates

### B-97 DRAFT- DO NOT CITE OR QUOTE

( *** The model parameter(s) -Power have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Background Slope

Background 1 -0.53

Slope -0.53 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0444162 0.0255203 -0.00560266 0.0944351 Slope 0.0201613 0.00593763 0.00852374 0.0317988 Power 1 NA

NA - Indicates that this parameter has hit a bound implied by some inequality constraint and thus has no standard error.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -76.0086 4 Fitted model -76.2255 2 0.43 3714 2 0.805 Reduced model -82.7874 1 13. 5576 3 0.003574

AIC: 156.451

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0444 2.221 2.000 50 -0.152 1.8000 0.0785 3.924 4.000 50 0.040 7.1000 0.1719 8.593 10.000 50 0.527 14.3000 0.2838 14.188 13.000 50 -0.373

Chi^2 = 0.44 d.f. = 2 P-value = 0.8019

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 2.54415

BMDL = 1.68095

### B-98 DRAFT- DO NOT CITE OR QUOTE 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4

0 2 4 6 8 10 12 14Fraction Affected

dose Quantal Linear Model with 0.95 Confidence Level

14:42 11/14 2008 BMDL BMD Quantal Linear

================================================== ================== Quantal Linear Model using Weibull Model (Ver sion: 2.12; Date: 05/16/2008) Input Data File: C:\USEPA\BMDS2\Temp\tmp12A.(d ) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm p12A.plt Fri Nov 14 14:42:54 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP (-slope*dose)]

Dependent variable = Response Independent variable = DOSE

Total number of observations = 4 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

Default Initial (and Specified) P arameter Values Background = 0.0490196 Slope = 0.0179876 Power = 1 Sp ecified

Asymptotic Correlation Matrix of Paramet er Estimates

### B-99 DRAFT- DO NOT CITE OR QUOTE

( *** The model parameter(s) -Power have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Background Slope

Background 1 -0.53

Slope -0.53 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0444162 0.0255203 -0.00560266 0.0944351 Slope 0.0201613 0.00593763 0.00852374 0.0317988

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -76.0086 4 Fitted model -76.2255 2 0.43 3714 2 0.805 Reduced model -82.7874 1 13. 5576 3 0.003574

AIC: 156.451

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0444 2.221 2.000 50 -0.152 1.8000 0.0785 3.924 4.000 50 0.040 7.1000 0.1719 8.593 10.000 50 0.527 14.3000 0.2838 14.188 13.000 50 -0.373

Chi^2 = 0.44 d.f. = 2 P-value = 0.8019

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 2.54415

BMDL = 1.68095

### B-100 DRAFT- DO NOT CITE OR QUOTE

B6C3F 1 Female Mice: Forestomach lesions (administered dos e)

0 0.05 0.1 0.15 0.2 0.25 0.3

0 2 4 6 8 10 12 14Fraction Affected

dose Gamma Multi-Hit Model with 0.95 Confidence Level

15:44 11/14 2008 BMDL BMD Gamma Multi-Hit

================================================== ================== Gamma Model. (Version: 2.13; Date: 05/16/200 8) Input Data File: C:\USEPA\BMDS2\Temp\tmp131.(d ) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm p131.plt Fri Nov 14 15:44:47 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response]= background+(1-background)*CumGamma[ slope*dose,power], where CumGamma(.) is the cummulative Gamma distr ibution function

Dependent variable = Response Independent variable = DOSE Power parameter is restricted as power >=1

Total number of observations = 4 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

Default Initial (and Specified) P arameter Values Background = 0.0490196 Slope = 0.0133015

### B-101 DRAFT- DO NOT CITE OR QUOTE

Power = 1.18093

Asymptotic Correlation Matrix of Paramet er Estimates

Background Slope Power

Background 1 0.39 0.47

Slope 0.39 1 0.99

Power 0.47 0.99 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0367793 0.0231276 -0.00854987 0.0821085 Slope 0.0180646 0.0405793 -0.0614694 0.0975986 Power 1.28374 1.22475 -1.11674 3.68421

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -55.0321 4 Fitted model -55.0866 3 0.10 9064 1 0.7412 Reduced model -58.1629 1 6.2 6165 3 0.09955

AIC: 116.173

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0368 1.839 2.000 50 0.121 1.8000 0.0468 2.342 2.000 50 -0.229 7.1000 0.0924 4.618 5.000 50 0.187 14.3000 0.1639 8.197 8.000 50 -0.075

Chi^2 = 0.11 d.f. = 1 P-value = 0.7429

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 6.31104

BMDL = 3.03872

### B-102 DRAFT- DO NOT CITE OR QUOTE 0 0.05 0.1 0.15 0.2 0.25 0.3

0 2 4 6 8 10 12 14Fraction Affected

dose Logistic Model with 0.95 Confidence Level

15:48 11/14 2008 BMDL BMD Logistic

================================================== ================== Logistic Model. (Version: 2.12; Date: 05/16/2 008) Input Data File: C:\USEPA\BMDS2\Temp\tmp134.(d ) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm p134.plt Fri Nov 14 15:48:45 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = 1/[1+EXP(-intercept-slope*dose)]

Dependent variable = Response Independent variable = DOSE Slope parameter is not restricted

Total number of observations = 4 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values background = 0 Sp ecified intercept = -3.00612 slope = 0.102222

Asymptotic Correlation Matrix of Paramet er Estimates

### B-103 DRAFT- DO NOT CITE OR QUOTE

( *** The model parameter(s) -backgroun d have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

intercept slope

intercept 1 -0.84

slope -0.84 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit intercept -3.16594 0.471287 -4.08965 -2.24224 slope 0.108988 0.0453905 0.0200238 0.197951

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -55.0321 4 Fitted model -55.1666 2 0 .269 2 0.8742 Reduced model -58.1629 1 6.2 6165 3 0.09955

AIC: 114.333

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0405 2.023 2.000 50 -0.017 1.8000 0.0488 2.441 2.000 50 -0.289 7.1000 0.0838 4.189 5.000 50 0.414 14.3000 0.1669 8.347 8.000 50 -0.132

Chi^2 = 0.27 d.f. = 2 P-value = 0.8725

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 7.64457

BMDL = 5.59724

### B-104 DRAFT- DO NOT CITE OR QUOTE 0 0.05 0.1 0.15 0.2 0.25 0.3

0 2 4 6 8 10 12 14Fraction Affected

dose Log-Logistic Model with 0.95 Confidence Level

15:51 11/14 2008 BMDL BMD Log-Logistic

================================================== ================== Logistic Model. (Version: 2.12; Date: 05/16/2 008) Input Data File: C:\USEPA\BMDS2\Temp\tmp137.(d ) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm p137.plt Fri Nov 14 15:51:59 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background+(1-background)/[1+EXP(- intercept-slope*Log(dose))]

Dependent variable = Response Independent variable = DOSE Slope parameter is restricted as slope >= 1

Total number of observations = 4 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

User has chosen the log transformed model

Default Initial Parameter Values background = 0.04 intercept = -5.35004 slope = 1.30201

### B-105 DRAFT- DO NOT CITE OR QUOTE

Asymptotic Correlation Matrix of Paramet er Estimates

background intercept slope

background 1 -0.53 0.46

intercept -0.53 1 -0.98

slope 0.46 -0.98 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit background 0.0366811 * * * intercept -5.29891 * * * slope 1.2835 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -55.0321 4 Fitted model -55.0846 3 0.10 4995 1 0.7459 Reduced model -58.1629 1 6.2 6165 3 0.09955

AIC: 116.169

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0367 1.834 2.000 50 0.125 1.8000 0.0468 2.340 2.000 50 -0.228 7.1000 0.0928 4.639 5.000 50 0.176 14.3000 0.1637 8.186 8.000 50 -0.071

Chi^2 = 0.10 d.f. = 1 P-value = 0.7477

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 6.26147

BMDL = 2.83097

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0 2 4 6 8 10 12 14Fraction Affected

dose Probit Model with 0.95 Confidence Level

16:05 11/14 2008 BMDL BMD Probit

================================================== ================== Probit Model. (Version: 3.1; Date: 05/16/200 8) Input Data File: C:\USEPA\BMDS2\Temp\tmp140.(d ) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm p140.plt Fri Nov 14 16:05:36 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = CumNorm(Intercept+Slope*Dose),

where CumNorm(.) is the cumulative normal distri bution function

Dependent variable = Response Independent variable = DOSE Slope parameter is not restricted

Total number of observations = 4 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

Default Initial (and Specified) P arameter Values background = 0 Sp ecified

### B-107 DRAFT- DO NOT CITE OR QUOTE

intercept = -1.75537 slope = 0.0561083

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -backgroun d have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

intercept slope

intercept 1 -0.8

slope -0.8 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit intercept -1.7601 0.219358 -2.19003 -1.33017 slope 0.0553914 0.0228374 0.0106309 0.100152

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -55.0321 4 Fitted model -55.1419 2 0.21 9734 2 0.896 Reduced model -58.1629 1 6.2 6165 3 0.09955

AIC: 114.284

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0392 1.960 2.000 50 0.029 1.8000 0.0484 2.421 2.000 50 -0.277 7.1000 0.0858 4.292 5.000 50 0.357 14.3000 0.1665 8.326 8.000 50 -0.124

Chi^2 = 0.22 d.f. = 2 P-value = 0.8955

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 7.2597

BMDL = 5.19213

### B-108 DRAFT- DO NOT CITE OR QUOTE 0 0.05 0.1 0.15 0.2 0.25 0.3

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dose LogProbit Model with 0.95 Confidence Level

15:56 11/14 2008 BMDL BMD LogProbit

================================================== ================== Probit Model. (Version: 3.1; Date: 05/16/200 8) Input Data File: C:\USEPA\BMDS2\Temp\tmp13A.(d ) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm p13A.plt Fri Nov 14 15:56:14 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = Background + (1-Background) * CumNorm(Intercept +Slope*Log(Dose)),

where CumNorm(.) is the cumulative normal distri bution function

Dependent variable = Response Independent variable = DOSE Slope parameter is restricted as slope >= 1

Total number of observations = 4 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

User has chosen the log transformed model

Default Initial (and Specified) P arameter Values

### B-109 DRAFT- DO NOT CITE OR QUOTE

background = 0.04 intercept = -3.50754 slope = 1

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -slope have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

background intercept

background 1 -0.51

intercept -0.51 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit background 0.0436672 0.0205583 0.00337363 0.0839607 intercept -3.75124 0.270066 -4.28056 -3.22192 slope 1 NA

NA - Indicates that this parameter has hit a bound implied by some inequality constraint and thus has no standard error.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -55.0321 4 Fitted model -55.2386 2 0.41 3147 2 0.8134 Reduced model -58.1629 1 6.2 6165 3 0.09955

AIC: 114.477

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0437 2.183 2.000 50 -0.127 1.8000 0.0444 2.221 2.000 50 -0.151 7.1000 0.0787 3.935 5.000 50 0.559 14.3000 0.1753 8.765 8.000 50 -0.284

Chi^2 = 0.43 d.f. = 2 P-value = 0.8054

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 8.21852

BMDL = 5.64968

### B-110 DRAFT- DO NOT CITE OR QUOTE 0 0.05 0.1 0.15 0.2 0.25 0.3

0 2 4 6 8 10 12 14Fraction Affected

dose Multistage Model with 0.95 Confidence Level

16:01 11/14 2008 BMD BMDL Multistage

================================================== ================== Multistage Model. (Version: 3.0; Date: 05/16 /2008) Input Data File: C:\USEPA\BMDS2\Temp\tmp13D.(d ) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm p13D.plt Fri Nov 14 16:01:58 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = DOSE

Total number of observations = 4 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-111 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.032589 Beta(1) = 0.00986338

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1)

Background 1 -0.7

Beta(1) -0.7 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0341442 * * * Beta(1) 0.00957473 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -55.0321 4 Fitted model -55.1226 2 0.18 1118 2 0.9134 Reduced model -58.1629 1 6.2 6165 3 0.09955

AIC: 114.245

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0341 1.707 2.000 50 0.228 1.8000 0.0506 2.532 2.000 50 -0.343 7.1000 0.0976 4.881 5.000 50 0.057 14.3000 0.1577 7.887 8.000 50 0.044

Chi^2 = 0.18 d.f. = 2 P-value = 0.9162

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 5.35715

BMDL = 3.01931

BMDU = 16.4514

Taken together, (3.01931, 16.4514) is a 90 % tw o-sided confidence interval for the BMD

### B-112 DRAFT- DO NOT CITE OR QUOTE 0 0.05 0.1 0.15 0.2 0.25 0.3

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dose Weibull Model with 0.95 Confidence Level

16:09 11/14 2008 BMDL BMD Weibull

================================================== ================== Weibull Model using Weibull Model (Version: 2 .12; Date: 05/16/2008) Input Data File: C:\USEPA\BMDS2\Temp\tmp143.(d ) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm p143.plt Fri Nov 14 16:09:11 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP (-slope*dose^power)]

Dependent variable = Response Independent variable = DOSE Power parameter is restricted as power >=1

Total number of observations = 4 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

Default Initial (and Specified) P arameter Values Background = 0.0490196 Slope = 0.00467913 Power = 1.25557

Asymptotic Correlation Matrix of Paramet er Estimates

### B-113 DRAFT- DO NOT CITE OR QUOTE

Background Slope Power

Background 1 -0.54 0.47

Slope -0.54 1 -0.99

Power 0.47 -0.99 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0366324 0.0230239 -0.00849362 0.0817585 Slope 0.00530377 0.0138578 -0.021857 0.0324646 Power 1.23448 1.00512 -0.735513 3.20447

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -55.0321 4 Fitted model -55.0891 3 0.11 4024 1 0.7356 Reduced model -58.1629 1 6.2 6165 3 0.09955

AIC: 116.178

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0366 1.832 2.000 50 0.127 1.8000 0.0471 2.357 2.000 50 -0.238 7.1000 0.0924 4.620 5.000 50 0.186 14.3000 0.1638 8.188 8.000 50 -0.072

Chi^2 = 0.11 d.f. = 1 P-value = 0.7375

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 6.28482

BMDL = 3.03737

### B-114 DRAFT- DO NOT CITE OR QUOTE 0 0.05 0.1 0.15 0.2 0.25 0.3

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dose Quantal Linear Model with 0.95 Confidence Level

16:13 11/14 2008 BMDL BMD Quantal Linear

================================================== ================== Quantal Linear Model using Weibull Model (Ver sion: 2.12; Date: 05/16/2008) Input Data File: C:\USEPA\BMDS2\Temp\tmp146.(d ) Gnuplot Plotting File: C:\USEPA\BMDS2\Temp\tm p146.plt Fri Nov 14 16:13:01 2008

================================================== ==================

BMDS Model Run

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP (-slope*dose)]

Dependent variable = Response Independent variable = DOSE

Total number of observations = 4 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

Default Initial (and Specified) P arameter Values Background = 0.0490196 Slope = 0.00923495 Power = 1 Sp ecified

Asymptotic Correlation Matrix of Paramet er Estimates

### B-115 DRAFT- DO NOT CITE OR QUOTE

( *** The model parameter(s) -Power have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Background Slope

Background 1 -0.53

Slope -0.53 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0341442 0.0203958 -0.00583081 0.0741193 Slope 0.00957473 0.00414213 0.0014563 0.0176932

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -55.0321 4 Fitted model -55.1226 2 0.18 1118 2 0.9134 Reduced model -58.1629 1 6.2 6165 3 0.09955

AIC: 114.245

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0341 1.707 2.000 50 0.228 1.8000 0.0506 2.532 2.000 50 -0.343 7.1000 0.0976 4.881 5.000 50 0.057 14.3000 0.1577 7.887 8.000 50 0.044

Chi^2 = 0.18 d.f. = 2 P-value = 0.9162

Benchmark Dose Computation

Specified effect = 0.05

Risk Type = Extra risk

Confidence level = 0.95

BMD = 5.35715

BMDL = 3.01931

### B-116 DRAFT- DO NOT CITE OR QUOTE

APPENDIX B-2. NONCANCER INHALATION DOSE-RESPONSE A SSESSMENT (RfC): BMD MODELING RESULTS EMPLOYING THE INCIDENC E DATA FOR
NONNEOPLASTIC NASAL LESIONS IN RATS EXPOSED TO AN B Y INHALATION FOR 2 YEARS (TABLES B-6 THROUGH B-9)

For these modeling exercises, a BMR of 10% extra r isk was selected due to the limited number of rats in each exposure group. BMC and BMC L refer to the model-predicted concentration and its lower 95% confidence limit, r espectively, associated with a 10% extra risk for developing the lesion.

Table B-6. Incidence data for selected nasal lesio ns in Sprague-Dawley rats exposed by inhalation to AN for 2 years

Nasal lesion Exposure level (ppm) Exposure level (mg/m 3 ) HEC

(mg/m 3 ) a Incidence

0 0 0 0/11 (0%) 20 43.4 2.1 7/12 (58%) b Hyperplasia of mucus- secreting cells in males 80 173.6 8.5 8/10 (80%) b
0 0 0 1/11 (9%) 20 43.4 2.1 7/10 (70%) b Flattening of respiratory epithelium in females 80 173.6 8.5 8/10 (80%) b

a HEC as per U.S. EPA (1994b) methods for a category 1 gas producing an upper respiratory effect. Sample calculation: 43.4 mg/m 3 × 6h/24h × 5d/7d × RGDR ET = 2.1 mg/m 3 , where RGDR ET = 0.275 = [VE/SA ET ] rat ÷ [VE/SA ET ] human; VE = minute volume = 0.281 L/min rat; 13.8 L/min human; and SA ET = extrathoracic surface area = 5 cm 2 rat, 200 cm 2 human.
b Statistically significantly different from control value as reported by the authors.

Source: Quast et al. (1980b).

### B-117 DRAFT- DO NOT CITE OR QUOTE

Table B-7. A summary of BMDS (version 1.3.2) model ing results based on incidence of hyperplasia of mucus-secreting cells i n male Sprague-Dawley rats exposed to AN via inhalation for 2 years

Model χ 2 p -value a AIC BMC 10 b (mg/m 3 ) BMCL 10 c

(mg/m 3 )
Gamma 0.34 30.27 0.396 0.252 Logistic 0.02 38.05 1.17 0.718 Log-logistic 0.94 28.43 0.187 0.082 Multistage 0.34 30.27 0.396 0.252
Probit 0.01 37.99 1.17 0.776 Log-probit 0.37 29.98 0.625 0.382
Weibull 0.34 30.27 0.396 0.252

a χ 2 p -value from the χ 2 test for lack of fit. Values <0.1 fail to meet co nventional goodness-of-fit criteria.
b BMC 10 = BMC associated with 10% extra risk for nonneopla stic nasal lesions.

c BMCL 10 = 95% lower confidence limit on the BMC 10 for nonneoplastic nasal lesions.

Source: Quast et al. (1980b).

### B-118 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.3.2) model output for the best-fit model (i.e., log-logistic) based on incidence of hyperplasia of mucus-secreting cells i n male Sprague-Dawley rats exposed to AN via inhalation for 2 years

0 0.2 0.4 0.6 0.8 1

0 2 4 6 8Fraction Affected



### dose

Log-Logistic Model with 0.95 Confidence Level

13:38 05/16 2007 BMDL BMD Log-Logistic

=================================================== ================= Logistic Model $Revision: 2.1 $ $Date: 2000/0 2/26 03:38:20 $ Input Data File: G:\ACN DOSE-RESPONSE MODELING\NONCANCER\INHALATION\SD_MALE_NASAL_INHALAT ION.(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\NONCANCER\INHALATION\SD_MALE_NASAL_INHALAT ION.plt Wed May 16 13:38:57 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background+(1-background)/[1+EXP(- intercept-slope*Log(dose))]

Dependent variable = Response Independent variable = Dose Slope parameter is restricted as slope >= 1

Total number of observations = 3 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

User has chosen the log transformed model

### B-119 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values background = 0 intercept = -0.581093 slope = 1

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -backgroun d -slope have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlation matrix )

intercept

intercept 1

Parameter Estimates

Variable Estimate Std. Err. background 0 N A intercept -0.522564 0.47 9706 slope 1 N A

NA - Indicates that this parameter has hit a bound implied by some inequality constraint and thus has no standard error.

Analysis of Deviance Table

Model Log(likelihood) Deviance Test D F P-value Full model -13.1543 Fitted model -13.2153 0.121833 2 0.9409 Reduced model -22.7373 19.1659 2 <.0001

AIC: 28.4305

Goodness of Fit

Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0000 0.000 0 11 0 2.1000 0.5546 6.655 7 12 0.2001 8.5000 0.8345 8.345 8 10 -0.2931

Chi-square = 0.13 DF = 2 P-value = 0.9390

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.187372

BMDL = 0.0818673

### B-120 DRAFT- DO NOT CITE OR QUOTE

Table B-8. A summary of BMDS (version 1.3.2) model ing results based on incidence of flattening of respiratory epithelium i n female Sprague-Dawley rats exposed to AN via inhalation for 2 years

Model χ 2 p -value a AIC BMC 10 b (mg/m 3 ) BMCL 10 c

(mg/m 3 )
Gamma 0.08 35.78 0.419 0.245 Logistic 0.02 38.47 1.02 0.610 Log-logistic 0.43 33.50 0.162 0.059 Multistage 0.08 35.78 0.419 0.245
Probit 0.02 38.54 1.05 0.683 Log-probit 0.08 35.53 0.616 0.340
Weibull 0.08 35.78 0.419 0.245

a χ 2 p -value from the χ 2 test for lack of fit. Values <0.1 fail to meet co nventional goodness-of-fit criteria.
b BMC 10 = BMC associated with 10% extra risk for nonneopla stic nasal lesions.

c BMCL 10 = 95% lower confidence limit on the BMC 10 for nonneoplastic nasal lesions.

Source: Quast et al. (1980b).

### B-121 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.3.2) model output for the best-fit model (log-logistic) based on incidence of flattening of respiratory epithelium in female S prague-Dawley rats exposed to AN via inhalation for 2 years

0 0.2 0.4 0.6 0.8 1

0 2 4 6 8Fraction Affected

dose

Log-Logistic Model with 0.95 Confidence Level

16:25 05/14 2007 BMDL BMD Log-Logistic

================================================== ================== Logistic Model $Revision: 2.1 $ $Date: 2000/0 2/26 03:38:20 $ Input Data File: G:\ACN DOSE-RESPONSE MODELING \NONCANCER\SD_FEMALE_NASAL_INHALATION.(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\NONCANCER\SD_FEMALE_NASAL_INHALATION.plt Mon May 14 16:25:24 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background+(1-background)/[1+EXP(- intercept-slope*Log(dose))]

Dependent variable = Response Independent variable = Dose Slope parameter is restricted as slope >= 1

Total number of observations = 3 Total number of records with missing values = 0 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1 e-008 Parameter Convergence has been set to: 1e-008

User has chosen the log transformed model

Default Initial Parameter Values background = 0.0909091 intercept = -0.457634 slope = 1

### B-122 DRAFT- DO NOT CITE OR QUOTE

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -slope have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

background intercept

background 1 -0.27

intercept -0.27 1

Parameter Estimates

Variable Estimate Std. Err. background 0.0938695 0.08 9458 intercept -0.374871 0.58 6482 slope 1 N A

NA - Indicates that this parameter has hit a bound implied by some inequality constraint and thus has no standard error.

Analysis of Deviance Table

Model Log(likelihood) Deviance Test D F P-value Full model -14.4637 Fitted model -14.751 0.574692 1 0.4484 Reduced model -21.4714 14.0155 2 0.0009048

AIC: 33.502

Goodness of Fit

Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0939 1.033 1 11 -0.03367 2.1000 0.6292 6.292 7 10 0.4637 8.5000 0.8676 8.676 8 10 -0.6305

Chi-square = 0.61 DF = 1 P-value = 0.4334

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.161645

BMDL = 0.0593975

### B-123 DRAFT- DO NOT CITE OR QUOTE

APPENDIX B-3. CANCER ORAL DOSE-RESPONSE ASSESSMENT : BMD DOSE
MODELING RESULTS FOR TUMOR INCIDENCE DATA FROM RATS
CHRONICALLY EXPOSED TO AN IN DRINKING WATER

As summarized in Section 4.6.1, AN is a multisite c arcinogen in chronic oral rodent bioassays. Oral carcinogenicity studies of animals chronically exposed to AN include drinking water studies in two strains of rats, Sprague-Dawle y (Johannsen and Levinskas, 2002a; Quast, 2002; Biodynamics, 1980a; Quast et al., 1980a) and F344 (Johannsen and Levinskas, 2002b; Biodynamics, 1980b). In Sprague-Dawley rats, signi ficantly increased incidences of forestomach, CNS, Zymbal gland, tongue, and mammary gland (females only) tumors were found. In F344 rats, significantly increased incid ences of forestomach, CNS, Zymbal gland, and mammary gland (females only) tumors were found. Two of these chronic drinking water studies were s elected for dose-response modeling using the BMD approach and derivation of oral CSFs for AN. In one study by Quast (2002), Sprague-Dawley rats were exposed to 0, 35, 100, or 300 ppm of AN in drinking water for 2 years. In the second study by Johannsen and Levi nskas (2002b), F344 rats were exposed to 0, 1, 3, 10, 30, or 100 ppm of AN in drinking water fo r 2 years. In this appendix, detailed results of the dose-res ponse modeling for each of the tumor sites listed above are presented (Tables B-9 though B-26). For each tumor site, first a summary of the dose-response data is presented, followed by a table summarizing the results of the doseresponse modeling. Finally, the standard output fr om EPA’s BMDS, version 1.4.1, for the selected dose-response model for each tumor site is presented. In general, the multistage model was fit to all of the data sets with the BMR set at 0.1 (i.e., 10% extra risk). In fitting this model, successive stages of the multistage model, starting with stage 1 and ending with the stage equ al to the number of dose groups minus one, were fit to the tumor incidence data at a particula r site for each rat strain and sex employing the
internal dose metrics CEO in blood and AN in blood. Then, for each dose metric, all stages of the multistage model that did not show a significan t lack of fit (i.e., p > 0.1) were compared using AIC. The stage of the multistage model with the lowest AIC was selected as the best-fit model. For most tumor sites, the one-stage model e xhibited the best fit. For data sets that exhibited a significant lack of fit for all stages of the multistage model, dose groups were dropped (starting with the highest dose group) unti l an adequate fit was achieved.

### B-124 DRAFT- DO NOT CITE OR QUOTE

Sprague-Dawley Rats (Quast, 2002; Quast et al., 1980a)

Tumor Site: Forestomach

Table B-9. Incidence of forestomach (nonglandular) tumors in SpragueDawley rats exposed to AN in drinking water for 2 y ears

Predicted internal dose metrics

Sex Administered

animal dose (ppm in drinking water) Equivalent

administered animal dose a (mg/kg-d) AN-AUC in blood

(mg/L) CEO-AUC in blood

(mg/L) Incidence of

forestomach tumors b
0 0 0 0 0/80 (0%)
35 3.42 2.06 × 10 -2 1.83 × 10 -3 2/47 (4%)
100 8.53 5.36 × 10 -2 4.36 × 10 -3 23/48 (48%) c Male

300 21.2 1.46 × 10 -1 9.70 × 10 -3 39/48 (81%) c

0 0 0 0 1/80 (1%)
35 4.36 2.37 × 10 -2 2.07 × 10 -3 1/48 (2%)
100 10.8 6.18 × 10 -2 4.87 × 10 -3 12/48 (25%) c Female

300 25.0 1.56 × 10 -1 1.01 × 10 -2 30/48 (62%) c

a Administered doses were averages calculated by the study authors based on animal BW and drinking water intake.
b Incidences for Sprague-Dawley rats do not include a nimals from the 6- and 12-mo sacrifices and were fu rther adjusted to exclude (from the denominators) rats th at died between 0 and 12 mos in the study.

c Significantly different from controls ( p < 0.05) as calculated by the study authors.

Sources: Quast (2002); Quast et al. (1980a).



### Table B-10. Summary of BMD modeling results based on incidence of forestomach (nonglandular) tumors in Sprague-Dawley rats exposed to AN in drinking water for 2 years

Dose metric Best-fit model a χ 2 p- value b AIC BMD 10 c BMDL 10 d

Males
Administered dose 2 ° MS e 0.46 86.82 3.62 mg/kg-d 2.76 mg/kg-d
CEO 2 ° MS e 0.39 87.28 1.87 × 10 -3 mg/L 1.44 × 10 -3 mg/L
AN 2 ° MS e 0.54 86.45 2.26 × 10 -2 mg/L 1.70 × 10 -2 mg/L
Females
Administered dose 2 ° MS 0.17 145.97 7.76 mg/kg-d 4.81 mg/kg-d
CEO 2 ° MS 0.52 143.50 3.29 × 10 -3 mg/L 2.38 × 10 -3 mg/L
AN 2 ° MS 0.13 146.45 4.22 × 10 -2 mg/L 2.49 × 10 -2 mg/L

a Dose-response models were fit using BMDS, version 1 .4.1. “2 ° MS” indicates a two-stage multistage model.
b p value from the χ 2 goodness-of-fit test. Values <0.1 indicate a sign ificant lack of fit.

c BMD 10 = BMD at 10% extra risk.
d BMDL 10 = 95% lower confidence limit on the BMD at 10% ext ra risk.

e Highest dose dropped prior to model fitting.

### B-125 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for forestomach tumors in Sprague-Dawley male rats

employing administered dose as a dose metric

0 0.1 0.2 0.3 0.4 0.5 0.6

0 1 2 3 4 5 6 7 8Fraction Affected



### dose

Multistage Cancer Model with 0.95 Confidence Level

15:40 01/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

================================================== ================== Multistage Cancer Model. (Version: 1.5; Date : 02/20/2007) Input Data File: M:\ACN DOSE-RESPONSE MODELING \CANCER\ORAL\SD_MALE_FORESTOMACH_DW.(d) Gnuplot Plotting File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_MALE_FORESTOMACH_DW.plt Fri Jan 23 15:40:45 2009

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1-beta2*dose^2)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 3 Total number of records with missing values = 0 Total number of parameters in model = 3 Total number of specified parameters = 0 Degree of polynomial = 2

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-126 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0 Beta(1) = 0 Beta(2) = 0.00929613

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Backgroun d -Beta(1) have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Beta(2)

Beta(2) 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0 * * * Beta(1) 0 * * * Beta(2) 0.00803192 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -41.5002 3 Fitted model -42.4099 1 1.8 1939 2 0.4026 Reduced model -71.7704 1 60. 5403 2 <.0001

AIC: 86.8198

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0000 0.000 0 80 0.000 3.4200 0.0897 4.214 2 47 -1.131 8.5300 0.4426 21.243 23 48 0.511

Chi^2 = 1.54 d.f. = 2 P-value = 0.4633

### B-127 DRAFT- DO NOT CITE OR QUOTE

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 3.62184

BMDL = 2.75694

BMDU = 4.3186

Taken together, (2.75694, 4.3186 ) is a 90 % tw o-sided confidence interval for the BMD

Multistage Cancer Slope Factor = 0.0362721

### B-128 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for forestomach tumors in Sprague-Dawley male rats

employing CEO in blood as an internal dose metric

0 0.1 0.2 0.3 0.4 0.5 0.6

0 0.0005 0.001 0.0015 0.002 0.0025 0.003 0.0035 0.004 0.0045Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

13:46 09/27 2007 BMD BMDL Multistage

================================================== ================== Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_MALE_FORESTOMACH_BLOOD_CEO. (d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_MALE_FORESTOMACH_BLOOD_CEO. plt Thu Sep 27 13:46:37 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1-beta2*dose^2)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 3 Total number of records with missing values = 0 Total number of parameters in model = 3 Total number of specified parameters = 0 Degree of polynomial = 2

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-129 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0 Beta(1) = 0 Beta(2) = 35739.1

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Backgroun d -Beta(1) have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlation matrix )

Beta(2)

Beta(2) 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0 * * * Beta(1) 0 * * * Beta(2) 30229.1 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -41.5002 3 Fitted model -42.6376 1 2.2 7473 2 0.3207 Reduced model -71.7704 1 60. 5403 2 <.0001

AIC: 87.2752

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0000 0.000 0 80 0.000 0.0018 0.0963 4.525 2 47 -1.249 0.0044 0.4371 20.981 23 48 0.588

Chi^2 = 1.90 d.f. = 2 P-value = 0.3859

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.00186692

BMDL = 0.00143604

BMDU = 0.00222594

Taken together, (0.00143604, 0.00222594) is a 90 % two-sided confidence interval for the BMD

### B-130 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for forestomach tumors in Sprague-Dawley male rats

employing AN in blood as an internal dose metric

0 0.1 0.2 0.3 0.4 0.5 0.6

0 0.01 0.02 0.03 0.04 0.05Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

10:32 09/27 2007 BMD BMDL Multistage

================================================== ================== Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_MALE_FORESTOMACH_BLOOD_AN.( d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_MALE_FORESTOMACH_BLOOD_AN.p lt Thu Sep 27 10:32:01 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1-beta2*dose^2)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 3 Total number of records with missing values = 0 Total number of parameters in model = 3 Total number of specified parameters = 0 Degree of polynomial = 2

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values

### B-131 DRAFT- DO NOT CITE OR QUOTE

Background = 0 Beta(1) = 0 Beta(2) = 234.473

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Backgroun d -Beta(1) have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlation matrix )

Beta(2)

Beta(2) 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0 * * * Beta(1) 0 * * * Beta(2) 206.388 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -41.5002 3 Fitted model -42.2261 1 1.4 5174 2 0.4839 Reduced model -71.7704 1 60. 5403 2 <.0001

AIC: 86.4522

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0000 0.000 0 80 0.000 0.0206 0.0839 3.941 2 47 -1.022 0.0536 0.4473 21.470 23 48 0.444

Chi^2 = 1.24 d.f. = 2 P-value = 0.5377

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.0225942

BMDL = 0.0170019

BMDU = 0.0269423

Taken together, (0.0170019, 0.0269423) is a 90 % two-sided confidence interval for the BMD

### B-132 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for forestomach tumors in Sprague-Dawley female rats

employing administered dose as a dose metric

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

0 5 10 15 20 25Fraction Affected



### dose

Multistage Cancer Model with 0.95 Confidence Level

16:14 01/23 2009 BMD

BMDL Multistage Cancer Linear extrapolation

================================================== ================== Multistage Cancer Model. (Version: 1.5; Date : 02/20/2007) Input Data File: M:\ACN DOSE-RESPONSE MODELING \CANCER\ORAL\SD_FEMALE_FORESTOMACH_DW.(d) Gnuplot Plotting File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_FEMALE_FORESTOMACH_DW.plt Fri Jan 23 16:14:45 2009

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1-beta2*dose^2)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 4 Total number of records with missing values = 0 Total number of parameters in model = 3 Total number of specified parameters = 0 Degree of polynomial = 2

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-133 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0 Beta(1) = 0.0138175 Beta(2) = 0.00104033

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1) Beta(2)

Background 1 -0.57 0.39

Beta(1) -0.57 1 -0.93

Beta(2) 0.39 -0.93 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0107986 * * * Beta(1) 0.000833319 * * * Beta(2) 0.00164062 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -68.9836 4 Fitted model -69.9834 3 1.9 9958 1 0.1573 Reduced model -110.972 1 83. 9771 3 <.0001

AIC: 145.967

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0108 0.864 1 80 0.147 4.3600 0.0447 2.143 1 48 -0.799 10.8000 0.1904 9.139 12 48 1.052 25.0000 0.6525 31.321 30 48 -0.401

Chi^2 = 1.93 d.f. = 1 P-value = 0.1652

### B-134 DRAFT- DO NOT CITE OR QUOTE

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 7.76379

BMDL = 4.81488

BMDU = 9.11082

Taken together, (4.81488, 9.11082) is a 90 % tw o-sided confidence interval for the BMD

Multistage Cancer Slope Factor = 0.0207689

### B-135 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for forestomach tumors in Sprague-Dawley female rats

employing CEO in blood as an internal dose metric

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

0 0.002 0.004 0.006 0.008 0.01Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

14:24 09/27 2007 BMD

BMDL Multistage

================================================== ================== Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_FEMALE_FORESTOMACH_BLOOD_CE O.(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_FEMALE_FORESTOMACH_BLOOD_CE O.plt Thu Sep 27 14:24:06 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1-beta2*dose^2)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 4 Total number of records with missing values = 0 Total number of parameters in model = 3 Total number of specified parameters = 0 Degree of polynomial = 2

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values

### B-136 DRAFT- DO NOT CITE OR QUOTE

Background = 0 Beta(1) = 14.7147 Beta(2) = 8253.52

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Beta(1) have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Background Beta(2)

Background 1 -0.48

Beta(2) -0.48 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.00991437 * * * Beta(1) 0 * * * Beta(2) 9752.18 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -68.9836 4 Fitted model -69.7499 2 1.5 3257 2 0.4647 Reduced model -110.972 1 83. 9771 3 <.0001

AIC: 143.5

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0099 0.793 1 80 0.233 0.0021 0.0504 2.421 1 48 -0.937 0.0049 0.2144 10.289 12 48 0.602 0.0101 0.6339 30.426 30 48 -0.128

Chi^2 = 1.31 d.f. = 2 P-value = 0.5192

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.00328691

BMDL = 0.00238295

BMDU = 0.0037821

Taken together, (0.00238295, 0.0037821) is a 90 % two-sided confidence interval for the BMD

### B-137 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for forestomach tumors in Sprague-Dawley female rats

employing AN in blood as an internal dose metric

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

10:49 09/27 2007 BMD

BMDL Multistage

================================================== ================== Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_FEMALE_FORESTOMACH_BLOOD_AN .(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_FEMALE_FORESTOMACH_BLOOD_AN .plt Thu Sep 27 10:49:49 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1-beta2*dose^2)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 4 Total number of records with missing values = 0 Total number of parameters in model = 3 Total number of specified parameters = 0 Degree of polynomial = 2

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-138 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0 Beta(1) = 3.15264 Beta(2) = 20.8062

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1) Beta(2)

Background 1 -0.57 0.4

Beta(1) -0.57 1 -0.93

Beta(2) 0.4 -0.93 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0105127 * * * Beta(1) 0.96299 * * * Beta(2) 36.4178 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -68.9836 4 Fitted model -70.2231 3 2.4 7911 1 0.1154 Reduced model -110.972 1 83. 9771 3 <.0001

AIC: 146.446

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0105 0.841 1 80 0.174 0.0237 0.0524 2.516 1 48 -0.982 0.0618 0.1887 9.060 12 48 1.085 0.1560 0.6490 31.154 30 48 -0.349

Chi^2 = 2.29 d.f. = 1 P-value = 0.1300

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.0421673

BMDL = 0.0249138

BMDU = 0.055287

Taken together, (0.0249138, 0.055287) is a 90 % two-sided confidence interval for the BMD

### B-139 DRAFT- DO NOT CITE OR QUOTE

Tumor Site: CNS (Quast, 2002; Quast et al., 1980a)

Table B-11. Incidence of CNS tumors in Sprague-Daw ley rats exposed to AN in drinking water for 2 years

Predicted internal dose metrics

Sex Administered animal dose (ppm in drinking water) Equivalent

administered animal dose a (mg/kg-d) AN-AUC in blood

(mg/L) CEO-AUC in blood

(mg/L) Incidence of CNS

tumors b

0 0 0 0 1/80 (1%)
35 3.42 2.06 × 10 -2 1.83 × 10 -3 12/47 (26%) c

100 8.53 5.36 × 10 -2 4.36 × 10 -3 22/48 (46%) c Male

300 21.2 1.46 × 10 -1 9.70 × 10 -3 30/48 (62%) c

0 0 0 0 1/80 (1%)
35 4.36 2.37 × 10 -2 2.07 × 10 -3 20/48 (42%) c

100 10.8 6.18 × 10 -2 4.87 × 10 -3 25/48 (52%) c Female

300 25.0 1.56 × 10 -1 1.01 × 10 -2 31/48 (65%) c

a Administered doses were averages calculated by the study authors based on animal BW and drinking water intake.
b Incidences for Sprague-Dawley rats do not include a nimals from the 6- and 12-mo sacrifices and were fu rther adjusted to exclude (from the denominators) rats th at died between 0 and 12 mos in the study.

c Significantly different from controls ( p < 0.05) as calculated by the study authors.



### Table B-12. Summary of BMD modeling results based on incidence of CNS tumors in Sprague-Dawley rats exposed to AN in drin king water for 2 years

Dose metric Best-fit model a χ 2 p -value b AIC BMD 10 c BMDL 10 d

Males
Administered dose 1 ° MS 0.16 201.38 1.84 mg/kg-d 1.48 mg/kg-d
CEO 1 ° MS 0.37 199.81 8.87 × 10 -4 mg/L 7.16 × 10 -4 mg/L
AN 1 ° MS e 0.59 134.64 8.82 × 10 -3 mg/L 6.64 × 10 -3 mg/L
Females
Administered dose 1 ° MS e 0.06 149.85 1.26 mg/kg-d 0.99 mg/kg-d
CEO 1 ° MS e 0.08 149.29 5.79 × 10 -4 mg/L 4.51 × 10 -4 mg/L
AN 1 ° MS e 0.04 150.45 7.12 × 10 -3 mg/L 5.55 × 10 -3 mg/L

a Dose-response models were fit using BMDS, version 1 .4.1. “1 ° MS” indicates a one-stage multistage model.
b p value from the χ 2 goodness of fit test. Values <0.1 indicate a sign ificant lack of fit.

c BMD 10 = BMD at 10% extra risk.
d BMDL 10 = 95% lower confidence limit on the BMD at 10% ext ra risk.

e Highest dose dropped prior to model fitting.

### B-140 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for CNS tumors in Sprag ue-Dawley male rats employing administered dose as a dose metric

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

0 5 10 15 20Fraction Affected



### dose

Multistage Cancer Model with 0.95 Confidence Level

15:48 01/23 2009 BMD

BMDL Multistage Cancer Linear extrapolation

================================================== ================== Multistage Cancer Model. (Version: 1.5; Date : 02/20/2007) Input Data File: M:\ACN DOSE-RESPONSE MODELING \CANCER\ORAL\SD_MALE_CNS_DW.(d) Gnuplot Plotting File: M:\ACN DOSE-RESPONSE M ODELING\CANCER\ORAL\SD_MALE_CNS_DW.plt Fri Jan 23 15:48:14 2009

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 4 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values

### B-141 DRAFT- DO NOT CITE OR QUOTE

Background = 0.108455 Beta(1) = 0.0435027

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1)

Background 1 -0.62

Beta(1) -0.62 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0160781 * * * Beta(1) 0.0572137 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -96.9359 4 Fitted model -98.6909 2 3.5 1012 2 0.1729 Reduced model -134.574 1 75. 2765 3 <.0001

AIC: 201.382

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0161 1.286 1 80 -0.254 3.4200 0.1909 8.974 12 47 1.123 8.5300 0.3960 19.010 22 48 0.882 21.2000 0.7075 33.958 30 48 -1.256

Chi^2 = 3.68 d.f. = 2 P-value = 0.1587

### B-142 DRAFT- DO NOT CITE OR QUOTE

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 1.84153

BMDL = 1.4836

BMDU = 2.34034

Taken together, (1.4836 , 2.34034) is a 90 % tw o-sided confidence interval for the BMD

Multistage Cancer Slope Factor = 0.0674034

### B-143 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for CNS tumors in Sprag ue-Dawley male rats employing

CEO in blood as an internal dose metric

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

0 0.002 0.004 0.006 0.008 0.01Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

09:11 09/25 2007 BMD

BMDL Multistage

================================================== ================== Multistage Model. $Revision: 2.1 $ $Date: 200 0/08/21 03:38:21 $ Input Data File: G:\ACN DOSE-RESPONSE MODELING \CANCER\ORAL\SD_MALE_CNS_BLOOD_CEO.(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_MALE_CNS_BLOOD_CEO.plt Tue Sep 25 09:11:57 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 4 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values Background = 0.0859878 Beta(1) = 97.0212

### B-144 DRAFT- DO NOT CITE OR QUOTE

**** WARNING: Completion code = -3. Optimum not f ound. Trying new starting point  ** ** WARNING 0: Completion code = -3 trying new st art  ** ** WARNING 1: Completion code = -3 trying new st art  ** ** WARNING 2: Completion code = -3 trying new st art  ** ** WARNING 3: Completion code = -3 trying new st art  ** ** WARNING 4: Completion code = -3 trying new st art  ** ** WARNING 5: Completion code = -3 trying new st art  ** ** WARNING 6: Completion code = -3 trying new st art  ** ** WARNING 7: Completion code = -3 trying new st art  ** ** WARNING 8: Completion code = -3 trying new st art  ** ** WARNING 9: Completion code = -3 trying new st art****

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1)

Background 1 -0.62

Beta(1) -0.62 1

Parameter Estimates

Variable Estimate Std. Err. Background 0.0146577 0.10 0785 Beta(1) 118.766 28. 4627

Analysis of Deviance Table

Model Log(likelihood) Deviance Test D F P-value Full model -96.9359 Fitted model -97.9055 1.93933 2 0.3792 Reduced model -134.574 75.2765 3 <.0001

AIC: 199.811

Goodness of Fit

Dose Est._Prob. Expected Observed Size Chi^2 Res.

------------------------------------------------- ---------------------- i: 1 0.0000 0.0147 1.173 1 80 -0.149 i: 2 0.0018 0.2071 9.736 12 47 0.293 i: 3 0.0044 0.4129 19.820 22 48 0.187 i: 4 0.0097 0.6886 33.055 30 48 -0.297

Chi-square = 2.01 DF = 2 P-value = 0.3669

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.00088713

BMDL = 0.00071632

### B-145 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for CNS tumors in Sprag ue-Dawley male rats employing AN in blood as an internal dose metric

0 0.1 0.2 0.3 0.4 0.5 0.6

0 0.01 0.02 0.03 0.04 0.05Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

10:40 09/27 2007 BMD

BMDL Multistage

================================================== ================== Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING \CANCER\ORAL\SD_MALE_CNS_BLOOD_AN.(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_MALE_CNS_BLOOD_AN.plt Thu Sep 27 10:40:46 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 3 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-146 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.032766 Beta(1) = 11.0585

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1)

Background 1 -0.61

Beta(1) -0.61 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0130586 * * * Beta(1) 11.9435 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -65.1808 3 Fitted model -65.3204 2 0.27 9194 1 0.5972 Reduced model -87.5704 1 44. 7792 2 <.0001

AIC: 134.641

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0131 1.045 1 80 -0.044 0.0206 0.2283 10.731 12 47 0.441 0.0536 0.4797 23.025 22 48 -0.296

Chi^2 = 0.28 d.f. = 1 P-value = 0.5940

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.00882158

BMDL = 0.00664413

BMDU = 0.0121508

Taken together, (0.00664413, 0.0121508) is a 90 % two-sided confidence interval for the BMD

### B-147 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for CNS tumors in Sprag ue-Dawley female rats employing administered dose as a dose metric

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

0 2 4 6 8 10Fraction Affected



### dose

Multistage Cancer Model with 0.95 Confidence Level

16:19 01/23 2009 BMD

BMDL Multistage Cancer Linear extrapolation

================================================== ================== Multistage Cancer Model. (Version: 1.5; Date : 02/20/2007) Input Data File: M:\ACN DOSE-RESPONSE MODELING \CANCER\ORAL\SD_FEMALE_CNS_DW.(d) Gnuplot Plotting File: M:\ACN DOSE-RESPONSE M ODELING\CANCER\ORAL\SD_FEMALE_CNS_DW.plt Fri Jan 23 16:19:26 2009

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 3 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values

### B-148 DRAFT- DO NOT CITE OR QUOTE

Background = 0.0993663 Beta(1) = 0.0642026

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1)

Background 1 -0.62

Beta(1) -0.62 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0141417 * * * Beta(1) 0.0833707 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -71.2064 3 Fitted model -72.9251 2 3.4 3738 1 0.06374 Reduced model -101.108 1 59. 8036 2 <.0001

AIC: 149.85

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0141 1.131 1 80 -0.124 4.3600 0.3146 15.100 20 48 1.523 10.8000 0.5993 28.768 25 48 -1.110

Chi^2 = 3.57 d.f. = 1 P-value = 0.0589

### B-149 DRAFT- DO NOT CITE OR QUOTE

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 1.26376

BMDL = 0.985061

BMDU = 1.66456

Taken together, (0.985061, 1.66456) is a 90 % t wo-sided confidence interval for the BMD

Multistage Cancer Slope Factor = 0.101517

### B-150 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for CNS tumors in Sprag ue-Dawley female rats employing CEO in blood as an internal dose metric

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

0 0.001 0.002 0.003 0.004 0.005Fraction Affected



### dose

Multistage Cancer Model with 0.95 Confidence Level

09:03 12/03 2008 BMD

BMDL Multistage Cancer Linear extrapolation

=================================================== ================= Multistage Cancer Model. (Version: 1.5; Date : 02/20/2007) Input Data File: M:\ACN DOSE-RESPONSE MODELING \CANCER\ORAL\SD_FEMALE_CNS_BLOOD_CEO.(d) Gnuplot Plotting File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_FEMALE_CNS_BLOOD_CEO.plt Wed Dec 03 09:03:51 2008

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 3 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-151 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.0914603 Beta(1) = 144.025

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1)

Background 1 -0.62

Beta(1) -0.62 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0138803 * * * Beta(1) 182.002 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -71.2064 3 Fitted model -72.6449 2 2.8 7694 1 0.08986 Reduced model -101.108 1 59. 8036 2 <.0001

AIC: 149.29

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0139 1.110 1 80 -0.106 0.0021 0.3234 15.525 20 48 1.381 0.0049 0.5936 28.491 25 48 -1.026

Chi^2 = 2.97 d.f. = 1 P-value = 0.0848

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.000578899

BMDL = 0.000451438

BMDU = 0.000761804

Taken together, (0.000451438, 0.000761804) is a 90 % two-sided confidence interval for the BMD

Multistage Cancer Slope Factor = 221.515

### B-152 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for CNS tumors in Sprag ue-Dawley female rats employing AN in blood as an internal dose metric

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

0 0.01 0.02 0.03 0.04 0.05 0.06Fraction Affected



### dose

Multistage Cancer Model with 0.95 Confidence Level

09:12 12/03 2008 BMD

BMDL Multistage Cancer Linear extrapolation

=================================================== ================= Multistage Cancer Model. (Version: 1.5; Date : 02/20/2007) Input Data File: M:\ACN DOSE-RESPONSE MODELING \CANCER\ORAL\SD_FEMALE_CNS_BLOOD_AN.(d) Gnuplot Plotting File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_FEMALE_CNS_BLOOD_AN.plt Wed Dec 03 09:12:32 2008

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 3 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-153 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.106975 Beta(1) = 11.0861

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1)

Background 1 -0.62

Beta(1) -0.62 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0144346 * * * Beta(1) 14.7901 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -71.2064 3 Fitted model -73.2271 2 4.0 4128 1 0.0444 Reduced model -101.108 1 59. 8036 2 <.0001

AIC: 150.454

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0144 1.155 1 80 -0.145 0.0237 0.3058 14.681 20 48 1.666 0.0618 0.6049 29.034 25 48 -1.191

Chi^2 = 4.22 d.f. = 1 P-value = 0.0400

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.0071237

BMDL = 0.00554992

BMDU = 0.00939265

Taken together, (0.00554992, 0.00939265) is a 90 % two-sided confidence interval for the BMD

Multistage Cancer Slope Factor = 18.0183

### B-154 DRAFT- DO NOT CITE OR QUOTE

Tumor Site: Zymbal Gland (Quast, 2002; Quast et al., 1980a)

Table B-13. Incidence of Zymbal gland tumors in Sp rague-Dawley rats exposed to AN in drinking water for 2 years

Predicted internal dose metrics

Sex Administered

animal dose (ppm in drinking water) Equivalent

administered animal dose a (mg/kg-d) AN-AUC in blood

(mg/L) CEO-AUC in blood

(mg/L) Incidence of

Zymbal gland tumors b
0 0 0 0 3/80 (4%)
35 3.42 2.06 × 10 -2 1.83 × 10 -3 4/47 (9%)
100 8.53 5.36 × 10 -2 4.36 × 10 -3 3/48 (6%) Male

300 21.2 1.46 × 10 -1 9.70 × 10 -3 16/48 (33%) c

0 0 0 0 1/80 (1%)
35 4.36 2.37 × 10 -2 2.07 × 10 -3 5/48 (10%) c

100 10.8 6.18 × 10 -2 4.87 × 10 -3 9/48 (19%) c Female

300 25.0 1.56 × 10 -1 1.01 × 10 -2 18/48 (38%) c

a Administered doses were averages calculated by the study authors based on animal BW and drinking water intake.
b Incidences for Sprague-Dawley rats do not include a nimals from the 6- and 12-mo sacrifices and were fu rther adjusted to exclude (from the denominators) rats th at died between 0 and 12 mos in the study.

c Significantly different from controls ( p < 0.05) as calculated by the study authors.



### Table B-14. Summary of BMD modeling results based on incidence of Zymbal gland tumors in Sprague-Dawley rats exposed to AN in drinking water for 2 years

Dose metric Best-fit model a χ 2 p -value b AIC BMD 10 c BMDL 10 d

Males
Administered dose 2 ° MS 0.43 142.15 11.80 mg/kg-d 6.29 mg/kg-d
CEO 2 ° MS 0.38 142.46 5.46 × 10 -3 mg/L 3.15 × 10 -3 mg/L
AN 3 ° MS 0.28 143.58 8.94 × 10 -2 mg/L 4.26 × 10 -2 mg/L
Females
Administered dose 1 ° MS 0.94 156.80 5.66 mg/kg-d 4.19 mg/kg-d
CEO 1 ° MS 0.95 156.77 2.40 × 10 -3 mg/L 1.78 × 10 -3 mg/L
AN 1 ° MS 0.85 156.98 3.41 × 10 -2 mg/L 2.52 × 10 -2 mg/L

a Dose-response models were fit using BMDS, version 1 .4.1. “1 ° MS” indicates a one-stage multistage model, “2 ° MS” indicates a two-stage multistage model, and “3 ° MS” indicates a three-stage multistage model.
b p value from the χ 2 goodness of fit test. Values <0.1 indicate a sign ificant lack of fit.

c BMD 10 = BMD at 10% extra risk.
d BMDL 10 = 95% lower confidence limit on the BMD at 10% ext ra risk.

### B-155 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for Zymbal gland tumors in Sprague-Dawley male rats

employing administered dose as a dose metric

0 0.1 0.2 0.3 0.4 0.5

0 5 10 15 20Fraction Affected



### dose

Multistage Cancer Model with 0.95 Confidence Level

16:01 01/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

================================================== ================== Multistage Cancer Model. (Version: 1.5; Date : 02/20/2007) Input Data File: M:\ACN DOSE-RESPONSE MODELING \CANCER\ORAL\SD_MALE_ZYMBAL_DW.(d) Gnuplot Plotting File: M:\ACN DOSE-RESPONSE M ODELING\CANCER\ORAL\SD_MALE_ZYMBAL_DW.plt Fri Jan 23 16:01:39 2009

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1-beta2*dose^2)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 4 Total number of records with missing values = 0 Total number of parameters in model = 3 Total number of specified parameters = 0 Degree of polynomial = 2

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values

### B-156 DRAFT- DO NOT CITE OR QUOTE

Background = 0.042253 Beta(1) = 0 Beta(2) = 0.00079507

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Beta(1) have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Background Beta(2)

Background 1 -0.49

Beta(2) -0.49 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0449236 * * * Beta(1) 0 * * * Beta(2) 0.000756128 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -68.2481 4 Fitted model -69.0738 2 1.6 5141 2 0.4379 Reduced model -80.2977 1 24. 0991 3 <.0001

AIC: 142.148

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0449 3.594 3 80 -0.321 3.4200 0.0533 2.507 4 47 0.969 8.5300 0.0960 4.610 3 48 -0.789 21.2000 0.3201 15.364 16 48 0.197

Chi^2 = 1.70 d.f. = 2 P-value = 0.4267

### B-157 DRAFT- DO NOT CITE OR QUOTE

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 11.8043

BMDL = 6.28905

BMDU = 15.532

Taken together, (6.28905, 15.532 ) is a 90 % tw o-sided confidence interval for the BMD

Multistage Cancer Slope Factor = 0.0159007

### B-158 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for Zymbal gland tumors in Sprague-Dawley male rats

employing CEO in blood as an internal dose metric

0 0.1 0.2 0.3 0.4 0.5

0 0.002 0.004 0.006 0.008 0.01Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

14:09 09/27 2007 BMD BMDL Multistage

================================================== ================== Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING \CANCER\ORAL\SD_MALE_ZYMBAL_BLOOD_CEO.(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_MALE_ZYMBAL_BLOOD_CEO.plt Thu Sep 27 14:09:41 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1-beta2*dose^2)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 4 Total number of records with missing values = 0 Total number of parameters in model = 3 Total number of specified parameters = 0 Degree of polynomial = 2

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values Background = 0.0373755

### B-159 DRAFT- DO NOT CITE OR QUOTE

Beta(1) = 0 Beta(2) = 3819.76

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Beta(1) have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Background Beta(2)

Background 1 -0.51

Beta(2) -0.51 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0429942 * * * Beta(1) 0 * * * Beta(2) 3535.6 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -68.2481 4 Fitted model -69.231 2 1.9 6583 2 0.3742 Reduced model -80.2977 1 24. 0991 3 <.0001

AIC: 142.462

### B-160 DRAFT- DO NOT CITE OR QUOTE

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0430 3.440 3 80 -0.242 0.0018 0.0543 2.550 4 47 0.934 0.0044 0.1052 5.050 3 48 -0.964 0.0097 0.3138 15.063 16 48 0.291

Chi^2 = 1.94 d.f. = 2 P-value = 0.3781

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.00545893

BMDL = 0.00315099

BMDU = 0.00717256

Taken together, (0.00315099, 0.00717256) is a 90 % two-sided confidence interval for the BMD

### B-161 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for Zymbal gland tumors in Sprague-Dawley male rats

employing AN in blood as an internal dose metric

0 0.1 0.2 0.3 0.4 0.5

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

10:44 09/27 2007 BMD BMDL Multistage

================================================== ================== Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING \CANCER\ORAL\SD_MALE_ZYMBAL_BLOOD_AN.(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_MALE_ZYMBAL_BLOOD_AN.plt Thu Sep 27 10:44:18 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1-beta2*dose^2-beta3*d ose^3)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 4 Total number of records with missing values = 0 Total number of parameters in model = 4 Total number of specified parameters = 0 Degree of polynomial = 3

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values Background = 0.0542857 Beta(1) = 0.0987621 Beta(2) = 0

### B-162 DRAFT- DO NOT CITE OR QUOTE

Beta(3) = 107.536

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Beta(2) have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Background Beta(1) Beta(3)

Background 1 -0.71 0.58

Beta(1) -0.71 1 -0.95

Beta(3) 0.58 -0.95 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0460186 * * * Beta(1) 0.432974 * * * Beta(2) 0 * * * Beta(3) 93.2629 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -68.2481 4 Fitted model -68.7881 3 1.0 7988 1 0.2987 Reduced model -80.2977 1 24. 0991 3 <.0001

AIC: 143.576

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0460 3.681 3 80 -0.364 0.0206 0.0553 2.597 4 47 0.896 0.0536 0.0812 3.897 3 48 -0.474 0.1460 0.3301 15.843 16 48 0.048

Chi^2 = 1.16 d.f. = 1 P-value = 0.2812

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.0894055

BMDL = 0.0425525

BMDU = 0.117269

Taken together, (0.0425525, 0.117269) is a 90 % two-sided confidence interval for the BMD

### B-163 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for Zymbal gland tumors in Sprague-Dawley female rats

employing administered dose as a dose metric

0 0.1 0.2 0.3 0.4 0.5

0 5 10 15 20 25Fraction Affected



### dose

Multistage Cancer Model with 0.95 Confidence Level

16:28 01/23 2009 BMD

BMDL Multistage Cancer Linear extrapolation

================================================== ================== Multistage Cancer Model. (Version: 1.5; Date : 02/20/2007) Input Data File: M:\ACN DOSE-RESPONSE MODELING \CANCER\ORAL\SD_FEMALE_ZYMBAL_DW.(d) Gnuplot Plotting File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_FEMALE_ZYMBAL_DW.plt Fri Jan 23 16:28:50 2009

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 4 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-164 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.0190401 Beta(1) = 0.0180112

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1)

Background 1 -0.64

Beta(1) -0.64 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.013388 * * * Beta(1) 0.0186127 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -76.3334 4 Fitted model -76.3975 2 0.12 8259 2 0.9379 Reduced model -93.6397 1 34. 6128 3 <.0001

AIC: 156.795

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0134 1.071 1 80 -0.069 4.3600 0.0903 4.334 5 48 0.335 10.8000 0.1931 9.266 9 48 -0.097 25.0000 0.3805 18.263 18 48 -0.078

Chi^2 = 0.13 d.f. = 2 P-value = 0.9357

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 5.66068

BMDL = 4.19199

BMDU = 8.10463

Taken together, (4.19199, 8.10463) is a 90 % tw o-sided confidence interval for the BMD

Multistage Cancer Slope Factor = 0.023855

### B-165 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for Zymbal gland tumors in Sprague-Dawley female rats

employing CEO in blood as an internal dose metric

0 0.1 0.2 0.3 0.4 0.5

0 0.002 0.004 0.006 0.008 0.01Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

14:43 09/27 2007 BMD

BMDL Multistage

================================================== ================== Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_FEMALE_ZYMBAL_BLOOD_CEO.(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_FEMALE_ZYMBAL_BLOOD_CEO.plt Thu Sep 27 14:43:02 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 4 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values

### B-166 DRAFT- DO NOT CITE OR QUOTE

Background = 0.00883347 Beta(1) = 44.8786

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1)

Background 1 -0.65

Beta(1) -0.65 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0125628 * * * Beta(1) 43.9052 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -76.3334 4 Fitted model -76.385 2 0.10 3357 2 0.9496 Reduced model -93.6397 1 34. 6128 3 <.0001

AIC: 156.77

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0126 1.005 1 80 -0.005 0.0021 0.0983 4.721 5 48 0.135 0.0049 0.2026 9.727 9 48 -0.261 0.0101 0.3662 17.580 18 48 0.126

Chi^2 = 0.10 d.f. = 2 P-value = 0.9501

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.00239973

BMDL = 0.00178178

BMDU = 0.00341242

Taken together, (0.00178178, 0.00341242) is a 90 % two-sided confidence interval for the BMD

### B-167 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for Zymbal gland tumors in Sprague-Dawley female rats

employing AN in blood as an internal dose metric

0 0.1 0.2 0.3 0.4 0.5

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

10:55 09/27 2007 BMD

BMDL Multistage

================================================== ================== Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_FEMALE_ZYMBAL_BLOOD_AN.(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_FEMALE_ZYMBAL_BLOOD_AN.plt Thu Sep 27 10:55:27 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 4 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-168 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.0269441 Beta(1) = 2.86115

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1)

Background 1 -0.63

Beta(1) -0.63 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0143198 * * * Beta(1) 3.08705 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -76.3334 4 Fitted model -76.4902 2 0.31 3733 2 0.8548 Reduced model -93.6397 1 34. 6128 3 <.0001

AIC: 156.98

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0143 1.146 1 80 -0.137 0.0237 0.0839 4.025 5 48 0.508 0.0618 0.1855 8.905 9 48 0.035 0.1560 0.3910 18.770 18 48 -0.228

Chi^2 = 0.33 d.f. = 2 P-value = 0.8481

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.0341298

BMDL = 0.0251994

BMDU = 0.0492353

Taken together, (0.0251994, 0.0492353) is a 90 % two-sided confidence interval for the BMD

### B-169 DRAFT- DO NOT CITE OR QUOTE

Tumor Site: Tongue (Quast, 2002; Quast et al., 1980a)

Table B-15. Incidence of tongue tumors in Sprague- Dawley rats exposed to AN in drinking water for 2 years

Predicted internal dose metrics

Sex Administered

animal dose (ppm in drinking water) Equivalent

administered animal dose a (mg/kg-d) AN-AUC in blood

(mg/L) CEO-AUC in blood

(mg/L) Incidence of

tongue tumors b
0 0 0 0 1/80 (1%)
35 3.42 2.06 × 10 -2 1.83 × 10 -3 2/47 (4%)
100 8.53 5.36 × 10 -2 4.36 × 10 -3 4/48 (8%) Male

300 21.2 1.46 × 10 -1 9.70 × 10 -3 5/48 (10%) c

0 0 0 0 0/80 (0%)
35 4.36 2.37 × 10 -2 2.07 × 10 -3 1/48 (2%)
100 10.8 6.18 × 10 -2 4.87 × 10 -3 2/48 (4%) Female

300 25.0 1.56 × 10 -1 1.01 × 10 -2 12/48 (25%) c

a Administered doses were averages calculated by the study authors based on animal BW and drinking water intake.
b Incidences for Sprague-Dawley rats do not include a nimals from the 6- and 12-mo sacrifices and were fu rther adjusted to exclude (from the denominators) rats th at died between 0 and 12 mos in the study.

c Significantly different from controls ( p < 0.05) as calculated by the study authors.



### Table B-16. Summary of BMD modeling results based on incidence of tongue tumors in Sprague-Dawley rats exposed to AN in drinking water for 2 years

Dose metric Best-fit model a χ 2 p -value b AIC BMD 10 c BMDL 10 d

Males
Administered dose 1 ° MS 0.69 91.62 18.89 mg/kg-d 10.35 mg/kg-d
CEO 1 ° MS 0.78 91.40 8.78 × 10 -3 mg/L 4.90 × 10 -3 mg/L
AN 1 ° MS 0.62 91.83 1.29 × 10 -1 mg/L 6.97 × 10 -2 mg/L
Females
Administered dose 3 ° MS 0.92 84.51 15.99 mg/kg-d 10.64 mg/kg-d
CEO 3 ° MS 0.88 84.59 6.70 × 10 -3 mg/L 4.74 × 10 -3 mg/L
AN 3 ° MS 0.93 84.48 9.67 × 10 -2 mg/L 6.10 × 10 -2 mg/L

a Dose-response models were fit using BMDS, version 1 .4.1. “1 ° MS” indicates a one-stage multistage model and “3 ° MS” indicates a three-stage multistage model.
b p value from the χ 2 goodness of fit test. Values <0.1 indicate a sign ificant lack of fit.

c BMD 10 = BMD at 10% extra risk.
d BMDL 10 = 95% lower confidence limit on the BMD at 10% ext ra risk.

### B-170 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for tongue tumors in Sp rague-Dawley male rats employing administered dose as a dose metric

0 0.05 0.1 0.15 0.2 0.25

0 5 10 15 20Fraction Affected



### dose

Multistage Cancer Model with 0.95 Confidence Level

15:53 01/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

================================================== ================== Multistage Cancer Model. (Version: 1.5; Date : 02/20/2007) Input Data File: M:\ACN DOSE-RESPONSE MODELING \CANCER\ORAL\SD_MALE_TONGUE_DW.(d) Gnuplot Plotting File: M:\ACN DOSE-RESPONSE M ODELING\CANCER\ORAL\SD_MALE_TONGUE_DW.plt Fri Jan 23 15:53:59 2009

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 4 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values

### B-171 DRAFT- DO NOT CITE OR QUOTE

Background = 0.0269073 Beta(1) = 0.00434306

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1)

Background 1 -0.69

Beta(1) -0.69 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0162768 * * * Beta(1) 0.00557883 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -43.4536 4 Fitted model -43.8112 2 0.71 5245 2 0.6993 Reduced model -46.7384 1 6.5 6959 3 0.08696

AIC: 91.6224

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0163 1.302 1 80 -0.267 3.4200 0.0349 1.639 2 47 0.287 8.5300 0.0620 2.976 4 48 0.613 21.2000 0.1260 6.048 5 48 -0.456

Chi^2 = 0.74 d.f. = 2 P-value = 0.6916

### B-172 DRAFT- DO NOT CITE OR QUOTE

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 18.8858

BMDL = 10.3512

BMDU = 62.8005

Taken together, (10.3512, 62.8005) is a 90 % tw o-sided confidence interval for the BMD

Multistage Cancer Slope Factor = 0.00966069

### B-173 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for tongue tumors in Sp rague-Dawley male rats employing CEO in blood as an internal dose metric

0 0.05 0.1 0.15 0.2 0.25

0 0.002 0.004 0.006 0.008 0.01Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

14:19 09/27 2007 BMD BMDL Multistage

=================================================== ================= Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING \CANCER\ORAL\SD_MALE_TONGUE_BLOOD_CEO.(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_MALE_TONGUE_BLOOD_CEO.plt Thu Sep 27 14:19:57 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 4 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-174 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.0241886 Beta(1) = 9.76289

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1)

Background 1 -0.7

Beta(1) -0.7 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0150764 * * * Beta(1) 11.9992 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -43.4536 4 Fitted model -43.6998 2 0.49 2394 2 0.7818 Reduced model -46.7384 1 6.5 6959 3 0.08696

AIC: 91.3995

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0151 1.206 1 80 -0.189 0.0018 0.0365 1.714 2 47 0.223 0.0044 0.0653 3.133 4 48 0.506 0.0097 0.1233 5.918 5 48 -0.403

Chi^2 = 0.50 d.f. = 2 P-value = 0.7772

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.00878063

BMDL = 0.00489829

BMDU = 0.0274259

Taken together, (0.00489829, 0.0274259) is a 90 % two-sided confidence interval for the BMD

### B-175 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for tongue tumors in Sp rague-Dawley male rats employing AN in blood as an internal dose metric

0 0.05 0.1 0.15 0.2 0.25

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

10:47 09/27 2007 BMD BMDL Multistage

================================================== ================== Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING \CANCER\ORAL\SD_MALE_TONGUE_BLOOD_AN.(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_MALE_TONGUE_BLOOD_AN.plt Thu Sep 27 10:47:13 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 4 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-176 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.0289604 Beta(1) = 0.615459

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1)

Background 1 -0.68

Beta(1) -0.68 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0174494 * * * Beta(1) 0.814352 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -43.4536 4 Fitted model -43.9131 2 0.91 9024 2 0.6316 Reduced model -46.7384 1 6.5 6959 3 0.08696

AIC: 91.8261

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0174 1.396 1 80 -0.338 0.0206 0.0338 1.588 2 47 0.332 0.0536 0.0594 2.852 4 48 0.701 0.1460 0.1276 6.124 5 48 -0.486

Chi^2 = 0.95 d.f. = 2 P-value = 0.6210

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.12938

BMDL = 0.0696872

BMDU = 0.4562

Taken together, (0.0696872, 0.4562 ) is a 90 % two-sided confidence interval for the BMD

### B-177 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for tongue tumors in Sp rague-Dawley female rats employing administered dose as a dose metric

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4

0 5 10 15 20 25Fraction Affected



### dose

Multistage Cancer Model with 0.95 Confidence Level

16:26 01/23 2009 BMD BMDL Multistage Cancer Linear extrapolation

=================================================== ================= Multistage Cancer Model. (Version: 1.5; Date : 02/20/2007) Input Data File: M:\ACN DOSE-RESPONSE MODELING \CANCER\ORAL\SD_FEMALE_TONGUE_DW.(d) Gnuplot Plotting File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_FEMALE_TONGUE_DW.plt Fri Jan 23 16:26:08 2009

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1-beta2*dose^2-beta3*d ose^3)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 4 Total number of records with missing values = 0 Total number of parameters in model = 4 Total number of specified parameters = 0 Degree of polynomial = 3

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-178 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.00365935 Beta(1) = 0.00218662 Beta(2) = 0 Beta(3) = 1.46642e-005

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Backgroun d -Beta(2) have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Beta(1) Beta(3)

Beta(1) 1 -0.93

Beta(3) -0.93 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0 * * * Beta(1) 0.00329024 * * * Beta(2) 0 * * * Beta(3) 1.28922e-005 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -40.1666 4 Fitted model -40.2528 2 0.17 2251 2 0.9175 Reduced model -55.0401 1 29. 7469 3 <.0001

AIC: 84.5055

### B-179 DRAFT- DO NOT CITE OR QUOTE

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0000 0.000 0 80 0.000 4.3600 0.0153 0.734 1 48 0.313 10.8000 0.0505 2.422 2 48 -0.278 25.0000 0.2470 11.856 12 48 0.048

Chi^2 = 0.18 d.f. = 2 P-value = 0.9151

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 15.9932

BMDL = 10.6421

BMDU = 19.9332

Taken together, (10.6421, 19.9332) is a 90 % tw o-sided confidence interval for the BMD

Multistage Cancer Slope Factor = 0.00939663

### B-180 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for tongue tumors in Sp rague-Dawley female rats employing CEO in blood as an internal dose metric

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4

0 0.002 0.004 0.006 0.008 0.01Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

14:49 09/27 2007 BMD BMDL Multistage

================================================== ================== Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_FEMALE_TONGUE_BLOOD_CEO.(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_FEMALE_TONGUE_BLOOD_CEO.plt Thu Sep 27 14:49:16 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1-beta2*dose^2-beta3*d ose^3)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 4 Total number of records with missing values = 0 Total number of parameters in model = 4 Total number of specified parameters = 0 Degree of polynomial = 3

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values Background = 0.0043768 Beta(1) = 2.92561 Beta(2) = 0 Beta(3) = 245868

### B-181 DRAFT- DO NOT CITE OR QUOTE

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Backgroun d -Beta(2) have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Beta(1) Beta(3)

Beta(1) 1 -0.92

Beta(3) -0.92 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0 * * * Beta(1) 6.26329 * * * Beta(2) 0 * * * Beta(3) 211165 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -40.1666 4 Fitted model -40.2953 2 0.25 7381 2 0.8792 Reduced model -55.0401 1 29. 7469 3 <.0001

AIC: 84.5907

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0000 0.000 0 80 0.000 0.0021 0.0147 0.707 1 48 0.351 0.0049 0.0534 2.564 2 48 -0.362 0.0101 0.2448 11.752 12 48 0.083

Chi^2 = 0.26 d.f. = 2 P-value = 0.8776

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.00669671

BMDL = 0.00473574

BMDU = 0.00818609

Taken together, (0.00473574, 0.00818609) is a 90 % two-sided confidence interval for the BMD

### B-182 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for tongue tumors in Sp rague-Dawley female rats employing AN in blood as an internal dose metric

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

10:57 09/27 2007 BMD BMDL Multistage

================================================== ================== Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_FEMALE_TONGUE_BLOOD_AN.(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_FEMALE_TONGUE_BLOOD_AN.plt Thu Sep 27 10:57:41 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1-beta2*dose^2-beta3*d ose^3)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 4 Total number of records with missing values = 0 Total number of parameters in model = 4 Total number of specified parameters = 0 Degree of polynomial = 3

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values Background = 0.0034253 Beta(1) = 0.462467

### B-183 DRAFT- DO NOT CITE OR QUOTE

Beta(2) = 0 Beta(3) = 55.8325

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Backgroun d -Beta(2) have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Beta(1) Beta(3)

Beta(1) 1 -0.93

Beta(3) -0.93 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0 * * * Beta(1) 0.629858 * * * Beta(2) 0 * * * Beta(3) 49.1667 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -40.1666 4 Fitted model -40.2395 2 0.14 5677 2 0.9298 Reduced model -55.0401 1 29. 7469 3 <.0001

AIC: 84.479

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0000 0.000 0 80 0.000 0.0237 0.0155 0.742 1 48 0.302 0.0618 0.0493 2.365 2 48 -0.244 0.1560 0.2479 11.900 12 48 0.033

Chi^2 = 0.15 d.f. = 2 P-value = 0.9271

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.0966976

BMDL = 0.0610292

BMDU = 0.122886

Taken together, (0.0610292, 0.122886) is a 90 % two-sided confidence interval for the BMD

### B-184 DRAFT- DO NOT CITE OR QUOTE

Tumor Site: Mammary Gland (Quast, 2002; Quast et al., 1980a)

Table B-17. Incidence of mammary gland tumors in S prague-Dawley rats exposed to AN in drinking water for 2 years

Predicted internal dose metrics

Sex Administered

animal dose (ppm in drinking water) Equivalent

administered animal dose a (mg/kg-d) AN-AUC in blood

(mg/L) CEO-AUC in blood

(mg/L) Incidence of

mammary gland tumors b

0 0 0 0 58/80 (72%)
35 4.36 2.37 × 10 -2 2.07 × 10 -3 42/47 (89%) c

100 10.8 6.18 × 10 -2 4.87 × 10 -3 42/48 (88%) c Female

300 25.0 1.56 × 10 -1 1.01 × 10 -2 35/48 (73%)

a Administered doses were averages calculated by the study authors based on animal BW and drinking water intake.
b Incidences for Sprague-Dawley rats do not include a nimals from the 6- and 12-mo sacrifices and were fu rther adjusted to exclude (from the denominators) rats th at died between 0 and 12 mos in the study.

c Significantly different from controls ( p < 0.05) as calculated by the study authors.



### Table B-18. Summary of BMD modeling results based on incidence of mammary gland tumors in Sprague-Dawley rats exposed to AN in drinking water for 2 years

Dose metric Best-fit model a χ 2 p -value b AIC BMD 10 c BMDL 10 d

Females
Administered dose 1 ° MS e 0.25 171.81 1.22 mg/kg-d 0.66 mg/kg-d
CEO 1 ° MS e 0.27 171.69 5.50 × 10 -4 mg/L 2.98 × 10 -4 mg/L
AN 1 ° MS e 0.24 171.93 7.05 × 10 -3 mg/L 3.77 × 10 -3 mg/L

a Dose-response models were fit using BMDS, version 1 .4.1. “1 ° MS” indicates a one-stage multistage model.
b p value from the χ 2 goodness of fit test. Values <0.1 indicate a sign ificant lack of fit.

c BMD 10 = BMD at 10% extra risk.
d BMDL 10 = 95% lower confidence limit on the BMD at 10% ext ra risk.

e Highest dose dropped prior to model fitting.

### B-185 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for mammary gland tumor s in Sprague-Dawley female rats

employing administered dose as a dose metric

0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95

0 2 4 6 8 10Fraction Affected



### dose

Multistage Cancer Model with 0.95 Confidence Level

16:34 01/23 2009 BMD

BMDL Multistage Cancer Linear extrapolation

================================================== ================== Multistage Cancer Model. (Version: 1.5; Date : 02/20/2007) Input Data File: M:\ACN DOSE-RESPONSE MODELING \CANCER\ORAL\SD_FEMALE_MAMMARY_DW.(d) Gnuplot Plotting File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_FEMALE_MAMMARY_DW.plt Fri Jan 23 16:34:25 2009

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 3 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-186 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.771359 Beta(1) = 0.0674842

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1)

Background 1 -0.58

Beta(1) -0.58 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.741898 * * * Beta(1) 0.0860351 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -83.2234 3 Fitted model -83.9062 2 1.3 6543 1 0.2426 Reduced model -86.3815 1 6.3 1609 2 0.04251

AIC: 171.812

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.7419 59.352 58 80 -0.345 4.3600 0.8226 39.486 42 48 0.950 10.8000 0.8981 43.108 42 48 -0.529

Chi^2 = 1.30 d.f. = 1 P-value = 0.2540

### B-187 DRAFT- DO NOT CITE OR QUOTE

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 1.22462

BMDL = 0.659237

BMDU = 4.94647

Taken together, (0.659237, 4.94647) is a 90 % t wo-sided confidence interval for the BMD

Multistage Cancer Slope Factor = 0.151691

### B-188 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for mammary gland tumor s in Sprague-Dawley female rats

employing CEO in blood as an internal dose metric

0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95

0 0.001 0.002 0.003 0.004 0.005Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

14:53 09/27 2007 BMD

BMDL Multistage

================================================== ================== Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_FEMALE_MAMMARY_BLOOD_CEO.(d ) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_FEMALE_MAMMARY_BLOOD_CEO.pl t Thu Sep 27 14:53:05 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 3 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-189 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.768564 Beta(1) = 152.668

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1)

Background 1 -0.58

Beta(1) -0.58 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.740346 * * * Beta(1) 191.729 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -83.2234 3 Fitted model -83.8471 2 1.2 4732 1 0.2641 Reduced model -86.3815 1 6.3 1609 2 0.04251

AIC: 171.694

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.7403 59.228 58 80 -0.313 0.0021 0.8254 39.619 42 48 0.905 0.0049 0.8979 43.101 42 48 -0.525

Chi^2 = 1.19 d.f. = 1 P-value = 0.2748

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.000549528

BMDL = 0.000298184

BMDU = 0.00214159

Taken together, (0.000298184, 0.00214159) is a 90 % two-sided confidence interval for the BMD

### B-190 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for mammary gland tumor s in Sprague-Dawley female rats

employing AN in blood as an internal dose metric

0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95

0 0.01 0.02 0.03 0.04 0.05 0.06Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

11:00 09/27 2007 BMD

BMDL Multistage

================================================== ================== Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_FEMALE_MAMMARY_BLOOD_AN.(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\SD_FEMALE_MAMMARY_BLOOD_AN.plt Thu Sep 27 11:00:59 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 3 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values

### B-191 DRAFT- DO NOT CITE OR QUOTE

Background = 0.773999 Beta(1) = 11.5581

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1)

Background 1 -0.58

Beta(1) -0.58 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.743458 * * * Beta(1) 14.9428 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -83.2234 3 Fitted model -83.9649 2 1.4 8294 1 0.2233 Reduced model -86.3815 1 6.3 1609 2 0.04251

AIC: 171.93

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.7435 59.477 58 80 -0.378 0.0237 0.8200 39.358 42 48 0.992 0.0618 0.8981 43.110 42 48 -0.529

Chi^2 = 1.41 d.f. = 1 P-value = 0.2354

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.00705091

BMDL = 0.00376506

BMDU = 0.0295793

Taken together, (0.00376506, 0.0295793) is a 90 % two-sided confidence interval for the BMD

### B-192 DRAFT- DO NOT CITE OR QUOTE

F344 Rats (Johannsen and Levinskas, 2002b; Biodynamics, 1980b )

Tumor Site: Forestomach

Table B-19. Incidence of forestomach (nonglandular ) tumors in F344 rats exposed to AN in drinking water for 2 years

Predicted internal dose metrics

Sex Administered

animal dose (ppm in drinking water) Equivalent

administered animal dose a (mg/kg-d) AN-AUC in blood

(mg/L) CEO-AUC in blood

(mg/L) Incidence of

forestomach tumors b
0 0 0 0 0/159 (0%) 1 0.08 4.33 × 10 -4 4.06 × 10 -5 1/80 (1%) 3 0.25 1.35 × 10 -3 1.27 × 10 -4 4/78 (5%) c
10 0.83 4.52 × 10 -3 4.19 × 10 -4 3/80 (4%) c
30 2.48 1.37 × 10 -2 1.23 × 10 -3 4/80 (5%) c Male

100 8.37 4.85 × 10 -2 3.97 × 10 -3 1/77 (1%)

0 0 0 0 0/157 (0%) 1 0.12 5.73 × 10 -4 5.32 × 10 -5 1/80 (1%) 3 0.36 1.72 × 10 -3 1.59 × 10 -4 2/79 (3%) 10 1.25 6.02 × 10 -3 5.49 × 10 -4 2/77 (3%) 30 3.65 1.79 × 10 -2 1.58 × 10 -3 4/80 (5%) c Female

100 10.90 5.63 × 10 -2 4.46 × 10 -3 2/75 (3%)

a Administered doses were averages calculated by the study authors based on animal BW and drinking water intake.
b Incidences for F344 rats do not include animals fro m the 6- and 12-mo sacrifices and were further adju sted to exclude (from the denominators) rats that died betw een 0 and 12 mos in the study.

c Significantly different from controls ( p < 0.05) as calculated by the study authors.

### B-193 DRAFT- DO NOT CITE OR QUOTE

Table B-20. Summary of BMD modeling results based on incidence of forestomach (nonglandular) tumors in F344 rats expo sed to AN in drinking water for 2 years

Dose metric Best-fit model a χ 2 p -value b AIC BMD 10 c BMDL 10 d

Males
Administered dose 1 ° MS e 0.18 74.08 1.19 mg/kg-d 0.70 mg/kg-d

CEO 1 ° MS e 0.19 74.04 6.03 × 10 -4 mg/L 3.55 × 10 -4 mg/L
AN 1 ° MS e 0.18 74.12 6.48 × 10 -3 mg/L 3.81 × 10 -3 mg/L
Females
Administered dose 1 ° MS f 0.83 96.64 8.43 mg/kg-d 3.89 mg/kg-d

CEO 1 ° MS f 0.83 96.62 3.65 × 10 -3 mg/L 1.69 × 10 -3 mg/L
AN 1 ° MS f 0.82 96.65 4.13 × 10 -2 mg/L 1.90 × 10 -2 mg/L

a Dose-response models were fit using BMDS, version 1 .4.1. “1 ° MS” indicates a one-stage multistage model.
b p value from the χ 2 goodness of fit test. Values <0.1 indicate a sign ificant lack of fit.

c BMD 10 = BMD at 10% extra risk.
d BMDL 10 = 95% lower confidence limit on the BMD at 10% ext ra risk.

e Two highest doses dropped prior to model fitting.
f Highest dose dropped prior to model fitting.

### B-194 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for forestomach tumors in F344 male rats employing administered dose as a dose metric

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14

0 0.2 0.4 0.6 0.8 1 1.2Fraction Affected



### dose

Multistage Cancer Model with 0.95 Confidence Level

14:29 01/26 2009 BMD BMDL Multistage Cancer Linear extrapolation

================================================== ================== Multistage Cancer Model. (Version: 1.5; Date : 02/20/2007) Input Data File: M:\ACN DOSE-RESPONSE MODELING \CANCER\ORAL\F344_MALE_FORESTOMACH_DW.(d) Gnuplot Plotting File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_MALE_FORESTOMACH_DW.plt Mon Jan 26 14:29:05 2009

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 4 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-195 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.0148134 Beta(1) = 0.0377128

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Backgroun d have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Beta(1)

Beta(1) 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0 * * * Beta(1) 0.0883999 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -33.9463 4 Fitted model -36.0377 1 4.1 8282 3 0.2424 Reduced model -39.1548 1 10 .417 3 0.01533

AIC: 74.0755

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0000 0.000 0 159 0.000 0.0800 0.0070 0.564 1 80 0.583 0.2500 0.0219 1.705 4 78 1.777 0.8300 0.0707 5.660 3 80 -1.160

Chi^2 = 4.84 d.f. = 3 P-value = 0.1836

### B-196 DRAFT- DO NOT CITE OR QUOTE

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 1.19186

BMDL = 0.701326

BMDU = 3.81474

Taken together, (0.701326, 3.81474) is a 90 % t wo-sided confidence interval for the BMD

Multistage Cancer Slope Factor = 0.142587

### B-197 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for forestomach tumors in F344 male rats employing CEO in blood as an internal dose metric

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14

0 0.0001 0.0002 0.0003 0.0004 0.0005 0.0006Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

14:57 09/27 2007 BMD BMDL Multistage

================================================== ================== Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_MALE_FORESTOMACH_BLOOD_CE O.(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_MALE_FORESTOMACH_BLOOD_CE O.plt Thu Sep 27 14:57:13 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 4 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-198 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.0147622 Beta(1) = 74.9311

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Backgroun d have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Beta(1)

Beta(1) 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0 * * * Beta(1) 174.815 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -33.9463 4 Fitted model -36.0209 1 4.1 4909 3 0.2458 Reduced model -39.1548 1 10 .417 3 0.01533

AIC: 74.0417

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0000 0.000 0 159 0.000 0.0000 0.0071 0.566 1 80 0.579 0.0001 0.0220 1.713 4 78 1.767 0.0004 0.0706 5.650 3 80 -1.157

Chi^2 = 4.80 d.f. = 3 P-value = 0.1873

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.000602696

BMDL = 0.000354643

BMDU = 0.00191036

Taken together, (0.000354643, 0.00191036) is a 90 % two-sided confidence interval for the BMD

### B-199 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for forestomach tumors in F344 male rats employing AN in blood as an internal dose metric

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14

0 0.001 0.002 0.003 0.004 0.005 0.006Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

11:04 09/27 2007 BMD BMDL Multistage

================================================== ================== Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_MALE_FORESTOMACH_BLOOD_AN .(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_MALE_FORESTOMACH_BLOOD_AN .plt Thu Sep 27 11:04:04 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 4 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values

### B-200 DRAFT- DO NOT CITE OR QUOTE

Background = 0.0148807 Beta(1) = 6.89727

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Backgroun d have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Beta(1)

Beta(1) 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0 * * * Beta(1) 16.2684 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -33.9463 4 Fitted model -36.0601 1 4.2 2747 3 0.2379 Reduced model -39.1548 1 10 .417 3 0.01533

AIC: 74.1201

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0000 0.000 0 159 0.000 0.0004 0.0070 0.562 1 80 0.587 0.0014 0.0217 1.694 4 78 1.791 0.0045 0.0709 5.672 3 80 -1.164

Chi^2 = 4.91 d.f. = 3 P-value = 0.1788

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.00647638

BMDL = 0.00381089

BMDU = 0.0209986

Taken together, (0.00381089, 0.0209986) is a 90 % two-sided confidence interval for the BMD

### B-201 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for forestomach tumors in F344 female rats employing administered dose as a dose metric

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14

0 1 2 3 4 5 6 7 8Fraction Affected



### dose

Multistage Cancer Model with 0.95 Confidence Level

14:49 01/26 2009 BMD BMDL Multistage Cancer Linear extrapolation

================================================== ================== Multistage Cancer Model. (Version: 1.5; Date : 02/20/2007) Input Data File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_FEMALE_FORESTOMACH_DW.(d) Gnuplot Plotting File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_FEMALE_FORESTOMACH_DW.plt Mon Jan 26 14:49:27 2009

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 5 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-202 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.0127929 Beta(1) = 0.0107517

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1)

Background 1 -0.58

Beta(1) -0.58 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0101696 * * * Beta(1) 0.0125023 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -45.9122 5 Fitted model -46.3178 2 0.8 1118 3 0.8468 Reduced model -48.4586 1 5.0 9287 4 0.2779

AIC: 96.6356

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0102 1.597 1 157 -0.475 0.1200 0.0117 0.932 1 80 0.071 0.3600 0.0146 1.155 2 79 0.793 1.2500 0.0255 1.965 2 77 0.025 3.6500 0.0543 4.346 4 80 -0.171

Chi^2 = 0.89 d.f. = 3 P-value = 0.8283

### B-203 DRAFT- DO NOT CITE OR QUOTE

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 8.42727

BMDL = 3.88972

BMDU = 48.9918

Taken together, (3.88972, 48.9918) is a 90 % tw o-sided confidence interval for the BMD

Multistage Cancer Slope Factor = 0.0257088

### B-204 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for forestomach tumors in F344 female rats employing CEO in blood as an internal dose metric

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14

0 0.0005 0.001 0.0015 0.002 0.0025 0.003 0.0035Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

15:07 09/27 2007 BMD BMDL Multistage

================================================== ================== Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_FEMALE_FORESTOMACH_BLOOD_ CEO.(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_FEMALE_FORESTOMACH_BLOOD_ CEO.plt Thu Sep 27 15:07:15 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 5 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-205 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.0127198 Beta(1) = 24.8654

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1)

Background 1 -0.58

Beta(1) -0.58 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0101112 * * * Beta(1) 28.8833 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -45.9122 5 Fitted model -46.3121 2 0.79 9693 3 0.8495 Reduced model -48.4586 1 5.0 9287 4 0.2779

AIC: 96.6241

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0101 1.587 1 157 -0.469 0.0001 0.0116 0.930 1 80 0.072 0.0002 0.0146 1.157 2 79 0.789 0.0005 0.0257 1.978 2 77 0.016 0.0016 0.0543 4.342 4 80 -0.169

Chi^2 = 0.88 d.f. = 3 P-value = 0.8310

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.0036478

BMDL = 0.00168696

BMDU = 1361.26

Taken together, (0.00168696, 1361.26) is a 90 % two-sided confidence interval for the BMD

### B-206 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for forestomach tumors in F344 female rats employing AN in blood as an internal dose metric

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14

0 0.005 0.01 0.015 0.02 0.025 0.03 0.035 0.04Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

11:30 09/27 2007 BMD BMDL Multistage

================================================== ================== Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_FEMALE_FORESTOMACH_BLOOD_ AN.(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_FEMALE_FORESTOMACH_BLOOD_ AN.plt Thu Sep 27 11:30:39 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 5 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values

### B-207 DRAFT- DO NOT CITE OR QUOTE

Background = 0.0128833 Beta(1) = 2.18924

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1)

Background 1 -0.58

Beta(1) -0.58 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0102427 * * * Beta(1) 2.54885 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -45.9122 5 Fitted model -46.3252 2 0.82 6038 3 0.8432 Reduced model -48.4586 1 5.0 9287 4 0.2779

AIC: 96.6505

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0102 1.608 1 157 -0.482 0.0006 0.0117 0.935 1 80 0.068 0.0017 0.0146 1.151 2 79 0.797 0.0060 0.0253 1.949 2 77 0.037 0.0179 0.0544 4.351 4 80 -0.173

Chi^2 = 0.90 d.f. = 3 P-value = 0.8246

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.0413364

BMDL = 0.0190324

BMDU = 0.242436

Taken together, (0.0190324, 0.242436) is a 90 % two-sided confidence interval for the BMD

### B-208 DRAFT- DO NOT CITE OR QUOTE

Tumor Site: CNS (Johannsen and Levinskas, 2002b; Biodynamics, 198 0b)

Table B-21. Incidence of CNS tumors in F344 rats e xposed to AN in drinking water for 2 years

Predicted internal dose metrics

Sex Administered

animal dose (ppm in drinking water) Equivalent

administered animal dose a (mg/kg-d) AN-AUC in blood

(mg/L) CEO-AUC in blood

(mg/L) Incidence of CNS

tumors b
0 0 0 0 0/160 (0%) 1 0.08 4.33 × 10 -4 4.06 × 10 -5 2/80 (3%) 3 0.25 1.35 × 10 -3 1.27 × 10 -4 1/78 (1%) 10 0.83 4.52 × 10 -3 4.19 × 10 -4 2/80 (3%) 30 2.48 1.37 × 10 -2 1.23 × 10 -3 10/79 (13%) c Male

100 8.37 4.85 × 10 -2 3.97 × 10 -3 25/76 (33%) c

0 0 0 0 1/157 (1%) 1 0.12 5.73 × 10 -4 5.32 × 10 -5 1/80 (1%) 3 0.36 1.72 × 10 -3 1.59 × 10 -4 2/80 (3%) 10 1.25 6.02 × 10 -3 5.49 × 10 -4 5/75 (7%) 30 3.65 1.79 × 10 -2 1.58 × 10 -3 6/80 (8%) c Female

100 10.90 5.63 × 10 -2 4.46 × 10 -3 24/76 (32%) c

a Administered doses were averages calculated by the study authors based on animal BW and drinking water intake.
b Incidences for F344 rats do not include animals fro m the 6- and 12-mo sacrifices and were further adju sted to exclude (from the denominators) rats that died betw een 0 and 12 mos in the study.

c Significantly different from controls ( p < 0.01) as calculated by the study authors.



### Table B-22. Summary of BMD modeling results based on incidence of CNS tumors in F344 rats exposed to AN in drinking water for 2 years

Dose metric Best-fit model a χ 2 p- value b AIC BMD 10 c BMDL 10 d

Males
Administered dose 1 ° MS 0.73 240.57 2.41 mg/kg-d 1.81 mg/kg-d
CEO 1 ° MS 0.70 240.75 1.16 × 10 -3 mg/L 8.74 × 10 -4 mg/L
AN 1 ° MS 0.74 240.44 1.37 × 10 -2 mg/L 1.03 × 10 -2 mg/L
Females
Administered dose 1 ° MS 0.68 222.13 3.34 mg/kg-d 2.52 mg/kg-d
CEO 1 ° MS 0.66 222.30 1.39 × 10 -3 mg/L 1.05 × 10 -3 mg/L
AN 1 ° MS 0.68 222.04 1.70 × 10 -2 mg/L 1.28 × 10 -2 mg/L

a Dose-response models were fit using BMDS, version 1 .4.1. “1 ° MS” indicates a one-stage multistage model.
b p value from the χ 2 goodness of fit test. Values <0.1 indicate a sign ificant lack of fit.

c BMD 10 = BMD at 10% extra risk.
d BMDL 10 = 95% lower confidence limit on the BMD at 10% ext ra risk.

### B-209 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for CNS tumors in F344 male rats employing administered dose as a dose metric

0 0.1 0.2 0.3 0.4

0 1 2 3 4 5 6 7 8Fraction Affected



### dose

Multistage Cancer Model with 0.95 Confidence Level

14:34 01/26 2009 BMD

BMDL Multistage Cancer Linear extrapolation

================================================== ================== Multistage Cancer Model. (Version: 1.5; Date : 02/20/2007) Input Data File: M:\ACN DOSE-RESPONSE MODELING \CANCER\ORAL\F344_MALE_CNS_DW.(d) Gnuplot Plotting File: M:\ACN DOSE-RESPONSE M ODELING\CANCER\ORAL\F344_MALE_CNS_DW.plt Mon Jan 26 14:34:10 2009

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 6 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values

### B-210 DRAFT- DO NOT CITE OR QUOTE

Background = 0.00946328 Beta(1) = 0.0466

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1)

Background 1 -0.47

Beta(1) -0.47 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0149509 * * * Beta(1) 0.0437933 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -117.105 6 Fitted model -118.287 2 2.3 6443 4 0.6691 Reduced model -151.112 1 68. 0145 5 <.0001

AIC: 240.574

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0150 2.392 3 160 0.396 0.0800 0.0184 1.472 2 80 0.440 0.2500 0.0257 2.003 1 78 -0.718 0.8300 0.0501 4.009 2 80 -1.030 2.4800 0.1163 9.190 10 79 0.284 8.3700 0.3172 24.110 25 76 0.219

Chi^2 = 2.05 d.f. = 4 P-value = 0.7258

### B-211 DRAFT- DO NOT CITE OR QUOTE

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 2.40586

BMDL = 1.8134

BMDU = 3.32187

Taken together, (1.8134 , 3.32187) is a 90 % tw o-sided confidence interval for the BMD

Multistage Cancer Slope Factor = 0.0551449

### B-212 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for CNS tumors in F344 male rats employing CEO in blood as an internal dose metric

0 0.1 0.2 0.3 0.4

0 0.0005 0.001 0.0015 0.002 0.0025 0.003 0.0035 0.004Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

15:00 09/27 2007 BMD

BMDL Multistage

================================================== ================== Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING \CANCER\ORAL\F344_MALE_CNS_BLOOD_CEO.(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_MALE_CNS_BLOOD_CEO.plt Thu Sep 27 15:00:12 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 6 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values

### B-213 DRAFT- DO NOT CITE OR QUOTE

Background = 0.00793445 Beta(1) = 98.3167

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1)

Background 1 -0.47

Beta(1) -0.47 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0147547 * * * Beta(1) 90.9591 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -117.105 6 Fitted model -118.375 2 2.5 4113 4 0.6373 Reduced model -151.112 1 68. 0145 5 <.0001

AIC: 240.75

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0148 2.361 3 160 0.419 0.0000 0.0184 1.471 2 80 0.440 0.0001 0.0261 2.034 1 78 -0.734 0.0004 0.0516 4.128 2 80 -1.075 0.0012 0.1190 9.404 10 79 0.207 0.0040 0.3134 23.817 25 76 0.293

Chi^2 = 2.19 d.f. = 4 P-value = 0.7002

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.00115833

BMDL = 0.000873641

BMDU = 0.00159795

Taken together, (0.000873641, 0.00159795) is a 90 % two-sided confidence interval for the BMD

### B-214 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for CNS tumors in F344 male rats employing AN in blood as an internal dose metric

0 0.1 0.2 0.3 0.4

0 0.01 0.02 0.03 0.04 0.05Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

11:07 09/27 2007 BMD

BMDL Multistage

================================================== ================== Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING \CANCER\ORAL\F344_MALE_CNS_BLOOD_AN.(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_MALE_CNS_BLOOD_AN.plt Thu Sep 27 11:07:15 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 6 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values

### B-215 DRAFT- DO NOT CITE OR QUOTE

Background = 0.0109984 Beta(1) = 8.0341

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1)

Background 1 -0.46

Beta(1) -0.46 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0151616 * * * Beta(1) 7.67068 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -117.105 6 Fitted model -118.218 2 2.2 2757 4 0.694 Reduced model -151.112 1 68. 0145 5 <.0001

AIC: 240.437

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0152 2.426 3 160 0.371 0.0004 0.0184 1.474 2 80 0.437 0.0014 0.0253 1.974 1 78 -0.702 0.0045 0.0487 3.898 2 80 -0.986 0.0137 0.1134 8.959 10 79 0.369 0.0485 0.3211 24.405 25 76 0.146

Chi^2 = 1.95 d.f. = 4 P-value = 0.7447

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.0137355

BMDL = 0.0103458

BMDU = 0.0189838

Taken together, (0.0103458, 0.0189838) is a 90 % two-sided confidence interval for the BMD

### B-216 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for CNS tumors in F344 female rats employing administered dose as a dose metric

0 0.1 0.2 0.3 0.4

0 2 4 6 8 10Fraction Affected



### dose

Multistage Cancer Model with 0.95 Confidence Level

14:55 01/26 2009 BMD

BMDL Multistage Cancer Linear extrapolation

================================================== ================== Multistage Cancer Model. (Version: 1.5; Date : 02/20/2007) Input Data File: M:\ACN DOSE-RESPONSE MODELING \CANCER\ORAL\F344_FEMALE_CNS_DW.(d) Gnuplot Plotting File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_FEMALE_CNS_DW.plt Mon Jan 26 14:55:28 2009

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 6 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-217 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.00525608 Beta(1) = 0.0331149

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1)

Background 1 -0.49

Beta(1) -0.49 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.00823648 * * * Beta(1) 0.0315054 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -107.86 6 Fitted model -109.065 2 2.4 1059 4 0.6607 Reduced model -140.644 1 65. 5686 5 <.0001

AIC: 222.13

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0082 1.293 1 157 -0.259 0.1200 0.0120 0.958 1 80 0.043 0.3600 0.0194 1.554 2 80 0.362 1.2500 0.0465 3.490 5 75 0.828 3.6500 0.1160 9.278 6 80 -1.144 10.9000 0.2965 22.534 24 76 0.368

Chi^2 = 2.33 d.f. = 4 P-value = 0.6753

### B-218 DRAFT- DO NOT CITE OR QUOTE

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 3.34421

BMDL = 2.51554

BMDU = 4.64166

Taken together, (2.51554, 4.64166) is a 90 % tw o-sided confidence interval for the BMD

Multistage Cancer Slope Factor = 0.0397529

### B-219 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for CNS tumors in F344 female rats employing CEO in blood as an internal dose metric

0 0.1 0.2 0.3 0.4

0 0.0005 0.001 0.0015 0.002 0.0025 0.003 0.0035 0.004 0.0045Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

15:10 09/27 2007 BMD

BMDL Multistage

================================================== ================== Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_FEMALE_CNS_BLOOD_CEO.(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_FEMALE_CNS_BLOOD_CEO.plt Thu Sep 27 15:10:31 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 6 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-220 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.00362563 Beta(1) = 80.7118

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1)

Background 1 -0.5

Beta(1) -0.5 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.00790184 * * * Beta(1) 75.5979 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -107.86 6 Fitted model -109.148 2 2.5 7752 4 0.6308 Reduced model -140.644 1 65. 5686 5 <.0001

AIC: 222.297

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0079 1.241 1 157 -0.217 0.0001 0.0119 0.951 1 80 0.051 0.0002 0.0198 1.580 2 80 0.337 0.0005 0.0482 3.618 5 75 0.745 0.0016 0.1196 9.568 6 80 -1.229 0.0045 0.2919 22.181 24 76 0.459

Chi^2 = 2.44 d.f. = 4 P-value = 0.6554

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.0013937

BMDL = 0.00104985

BMDU = 0.00193063

Taken together, (0.00104985, 0.00193063) is a 90 % two-sided confidence interval for the BMD

### B-221 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for CNS tumors in F344 female rats employing AN in blood as an internal dose metric

0 0.1 0.2 0.3 0.4

0 0.01 0.02 0.03 0.04 0.05Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

11:34 09/27 2007 BMD

BMDL Multistage

================================================== ================== Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING \CANCER\ORAL\F344_FEMALE_CNS_BLOOD_AN.(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_FEMALE_CNS_BLOOD_AN.plt Thu Sep 27 11:34:20 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 6 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values

### B-222 DRAFT- DO NOT CITE OR QUOTE

Background = 0.00679319 Beta(1) = 6.4212

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1)

Background 1 -0.49

Beta(1) -0.49 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.00859669 * * * Beta(1) 6.19715 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -107.86 6 Fitted model -109.017 2 2.3 1525 4 0.678 Reduced model -140.644 1 65. 5686 5 <.0001

AIC: 222.035

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0086 1.350 1 157 -0.302 0.0006 0.0121 0.969 1 80 0.032 0.0017 0.0191 1.529 2 80 0.385 0.0060 0.0449 3.368 5 75 0.910 0.0179 0.1127 9.015 6 80 -1.066 0.0563 0.3006 22.846 24 76 0.289

Chi^2 = 2.29 d.f. = 4 P-value = 0.6828

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.0170014

BMDL = 0.0127694

BMDU = 0.0236456

Taken together, (0.0127694, 0.0236456) is a 90 % two-sided confidence interval for the BMD

### B-223 DRAFT- DO NOT CITE OR QUOTE

Tumor Site: Zymbal’s Gland (Johannsen and Levinskas, 2002b; Biodynamics, 1980 b)

Table B-23. Incidence of Zymbal gland tumors in F3 44 rats exposed to AN in drinking water for 2 years

Predicted internal dose metrics

Sex Administered

animal dose (ppm in drinking water) Equivalent

administered animal dose a (mg/kg-d) AN-AUC in blood

(mg/L) CEO-AUC in blood

(mg/L) Incidence of

Zymbal’s gland tumors b
0 0 0 0 1/147 (1%)
1 0.08 4.33 × 10 -4 4.06 × 10 -5 1/76 (1%)
3 0.25 1.35 × 10 -3 1.27 × 10 -4 0/73 (0%)
10 0.83 4.52 × 10 -3 4.19 × 10 -4 0/67 (0%)
30 2.48 1.37 × 10 -2 1.23 × 10 -3 2/71 (3%) c Male

100 8.37 4.85 × 10 -2 3.97 × 10 -3 14/68 (21%) c

0 0 0 0 0/157 (0%)
1 0.12 5.73 × 10 -4 5.32 × 10 -5 0/73 (0%)
3 0.36 1.72 × 10 -3 1.59 × 10 -4 0/73 (0%)
10 1.25 6.02 × 10 -3 5.49 × 10 -4 0/70 (0%)
30 3.65 1.79 × 10 -2 1.58 × 10 -3 2/73 (3%) c Female

100 10.90 5.63 × 10 -2 4.46 × 10 -3 8/62 (13%) c

a Administered doses were averages calculated by the study authors based on animal BW and drinking water intake.
b Incidences for F344 rats do not include animals fro m the 6- and 12-mo sacrifices and were further adju sted to exclude (from the denominators) rats that died betw een 0 and 12 mos in the study.

c Significantly different from controls ( p < 0.01) as calculated by the study authors.



### Table B-24. Summary of BMD modeling results based on incidence of Zymbal gland tumors in F344 rats exposed to AN in d rinking water for 2 years

Dose metric Best-fit model a χ 2 p -value b AIC BMD 10 c BMDL 10 d

Males
Administered dose 2 ° MS 0.78 116.51 5.73 mg/kg-d 4.55 mg/kg-d
CEO 2 ° MS 0.77 116.53 2.73 × 10 -3 mg/L 2.19 × 10 -3 mg/L
AN 2 ° MS 0.78 116.52 3.31 × 10 -2 mg/L 2.59 × 10 -2 mg/L
Females
Administered dose 2 ° MS 0.95 70.80 9.16 mg/kg-d 7.17 mg/kg-d
CEO 2 ° MS 0.99 68.68 3.78 × 10 -3 mg/L 2.97 × 10 -3 mg/L
AN 1 ° MS 0.89 70.82 5.41 × 10 -2 mg/L 3.35 × 10 -2 mg/L

a Dose-response models were fit using BMDS, version 1 .4.1. “1 ° MS” indicates a one-stage multistage model and “2 ° MS” indicates a two-stage multistage model.
b p value from the χ 2 goodness of fit test. Values <0.1 indicate a sign ificant lack of fit.

c BMD 10 = BMD at 10% extra risk.
d BMDL 10 = 95% lower confidence limit on the BMD at 10% ext ra risk.

### B-224 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for Zymbal gland tumors in F344 male rats employing administered dose as a dose metric

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

0 1 2 3 4 5 6 7 8Fraction Affected



### dose

Multistage Cancer Model with 0.95 Confidence Level

14:41 01/26 2009 BMD BMDL Multistage Cancer Linear extrapolation

================================================== ================== Multistage Cancer Model. (Version: 1.5; Date : 02/20/2007) Input Data File: M:\ACN DOSE-RESPONSE MODELING \CANCER\ORAL\F344_MALE_ZYMBAL_DW.(d) Gnuplot Plotting File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_MALE_ZYMBAL_DW.plt Mon Jan 26 14:41:15 2009

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1-beta2*dose^2)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 6 Total number of records with missing values = 0 Total number of parameters in model = 3 Total number of specified parameters = 0 Degree of polynomial = 2

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-225 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.00522088 Beta(1) = 0 Beta(2) = 0.00321913

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Beta(1) have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Background Beta(2)

Background 1 -0.37

Beta(2) -0.37 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.00563419 * * * Beta(1) 0 * * * Beta(2) 0.00321262 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -54.9964 6 Fitted model -56.2568 2 2.5 2093 4 0.6409 Reduced model -77.5815 1 45. 1702 5 <.0001

AIC: 116.514

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0056 0.828 1 147 0.189 0.0800 0.0057 0.430 1 76 0.872 0.2500 0.0058 0.426 0 73 -0.654 0.8300 0.0078 0.525 0 67 -0.727 2.4800 0.0251 1.781 2 71 0.166 8.3700 0.2060 14.010 14 68 -0.003

Chi^2 = 1.78 d.f. = 4 P-value = 0.7758

### B-226 DRAFT- DO NOT CITE OR QUOTE

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 5.72676

BMDL = 4.54678

BMDU = 7.26717

Taken together, (4.54678, 7.26717) is a 90 % tw o-sided confidence interval for the BMD

Multistage Cancer Slope Factor = 0.0219936

### B-227 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for Zymbal gland tumors in F344 male rats employing CEO in blood as an internal dose metric

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

0 0.0005 0.001 0.0015 0.002 0.0025 0.003 0.0035 0.004Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

15:02 09/27 2007 BMD BMDL Multistage

================================================== ================== Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_MALE_ZYMBAL_BLOOD_CEO.(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_MALE_ZYMBAL_BLOOD_CEO.plt Thu Sep 27 15:02:53 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1-beta2*dose^2)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 6 Total number of records with missing values = 0 Total number of parameters in model = 3 Total number of specified parameters = 0 Degree of polynomial = 2

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-228 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.00480523 Beta(1) = 0 Beta(2) = 14327.9

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Beta(1) have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Background Beta(2)

Background 1 -0.38

Beta(2) -0.38 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.00556639 * * * Beta(1) 0 * * * Beta(2) 14170.3 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -54.9964 6 Fitted model -56.2667 2 2.5 4061 4 0.6374 Reduced model -77.5815 1 45. 1702 5 <.0001

AIC: 116.533

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0056 0.818 1 147 0.201 0.0000 0.0056 0.425 1 76 0.885 0.0001 0.0058 0.423 0 73 -0.652 0.0004 0.0080 0.538 0 67 -0.737 0.0012 0.0267 1.893 2 71 0.079 0.0040 0.2046 13.913 14 68 0.026

Chi^2 = 1.80 d.f. = 4 P-value = 0.7727

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.00272678

BMDL = 0.00218772

BMDU = 0.00345798

Taken together, (0.00218772, 0.00345798) is a 90 % two-sided confidence interval for the BMD

### B-229 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for Zymbal gland tumors in F344 male rats employing AN in blood as an internal dose metric

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

0 0.01 0.02 0.03 0.04 0.05Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

11:27 09/27 2007 BMD BMDL Multistage

================================================== ================== Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_MALE_ZYMBAL_BLOOD_AN.(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_MALE_ZYMBAL_BLOOD_AN.plt Thu Sep 27 11:27:02 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1-beta2*dose^2)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 6 Total number of records with missing values = 0 Total number of parameters in model = 3 Total number of specified parameters = 0 Degree of polynomial = 2

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values Background = 0.00503997 Beta(1) = 0.191539

### B-230 DRAFT- DO NOT CITE OR QUOTE

Beta(2) = 91.9968

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Beta(1) have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Background Beta(2)

Background 1 -0.37

Beta(2) -0.37 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.00571347 * * * Beta(1) 0 * * * Beta(2) 96.3581 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -54.9964 6 Fitted model -56.2582 2 2.5 2365 4 0.6404 Reduced model -77.5815 1 45. 1702 5 <.0001

AIC: 116.516

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0057 0.840 1 147 0.175 0.0004 0.0057 0.436 1 76 0.858 0.0014 0.0059 0.430 0 73 -0.658 0.0045 0.0077 0.514 0 67 -0.720 0.0137 0.0235 1.671 2 71 0.258 0.0485 0.2074 14.101 14 68 -0.030

Chi^2 = 1.78 d.f. = 4 P-value = 0.7755

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.033067

BMDL = 0.0258907

BMDU = 0.0419928

Taken together, (0.0258907, 0.0419928) is a 90 % two-sided confidence interval for the BMD

### B-231 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for Zymbal gland tumors in F344 female rats employing administered dose as a dose metric

0 0.05 0.1 0.15 0.2 0.25

0 2 4 6 8 10Fraction Affected



### dose

Multistage Cancer Model with 0.95 Confidence Level

15:01 01/26 2009 BMD BMDL Multistage Cancer Linear extrapolation

================================================== ================== Multistage Cancer Model. (Version: 1.5; Date : 02/20/2007) Input Data File: M:\ACN DOSE-RESPONSE MODELING \CANCER\ORAL\F344_FEMALE_ZYMBAL_DW.(d) Gnuplot Plotting File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_FEMALE_ZYMBAL_DW.plt Mon Jan 26 15:01:22 2009

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1-beta2*dose^2)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 6 Total number of records with missing values = 0 Total number of parameters in model = 3 Total number of specified parameters = 0 Degree of polynomial = 2

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-232 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0 Beta(1) = 0.00476273 Beta(2) = 0.000742952

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Backgroun d have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Beta(1) Beta(2)

Beta(1) 1 -0.95

Beta(2) -0.95 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0 * * * Beta(1) 0.000111429 * * * Beta(2) 0.00124232 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -33.0086 6 Fitted model -33.4019 2 0.78 6523 4 0.9402 Reduced model -49.1799 1 32. 3425 5 <.0001

AIC: 70.8038

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0000 0.000 0 157 0.000 0.1200 0.0000 0.002 0 73 -0.048 0.3600 0.0002 0.015 0 73 -0.121 1.2500 0.0021 0.145 0 70 -0.382 3.6500 0.0168 1.227 2 73 0.703 10.9000 0.1383 8.573 8 62 -0.211

Chi^2 = 0.70 d.f. = 4 P-value = 0.9511

### B-233 DRAFT- DO NOT CITE OR QUOTE

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 9.16446

BMDL = 7.17181

BMDU = 13.5889

Taken together, (7.17181, 13.5889) is a 90 % tw o-sided confidence interval for the BMD

Multistage Cancer Slope Factor = 0.0139435

### B-234 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for Zymbal gland tumors in F344 female rats employing CEO in blood as an internal dose metric

0 0.05 0.1 0.15 0.2 0.25

0 0.0005 0.001 0.0015 0.002 0.0025 0.003 0.0035 0.004 0.0045Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

15:13 09/27 2007 BMD BMDL Multistage

================================================== ================== Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_FEMALE_ZYMBAL_BLOOD_CEO.( d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_FEMALE_ZYMBAL_BLOOD_CEO.p lt Thu Sep 27 15:13:27 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1-beta2*dose^2)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 6 Total number of records with missing values = 0 Total number of parameters in model = 3 Total number of specified parameters = 0 Degree of polynomial = 2

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-235 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0 Beta(1) = 9.4165 Beta(2) = 4928.95

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Backgroun d -Beta(1) have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Beta(2)

Beta(2) 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0 * * * Beta(1) 0 * * * Beta(2) 7382.1 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -33.0086 6 Fitted model -33.3423 1 0.66 7255 5 0.9847 Reduced model -49.1799 1 32. 3425 5 <.0001

AIC: 68.6845

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0000 0.000 0 157 0.000 0.0001 0.0000 0.002 0 73 -0.039 0.0002 0.0002 0.014 0 73 -0.117 0.0005 0.0022 0.156 0 70 -0.395 0.0016 0.0183 1.333 2 73 0.583 0.0045 0.1366 8.467 8 62 -0.173

Chi^2 = 0.54 d.f. = 5 P-value = 0.9905

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.00377789

BMDL = 0.00297198

BMDU = 0.00541558

Taken together, (0.00297198, 0.00541558) is a 90 % two-sided confidence interval for the BMD

### B-236 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for Zymbal gland tumors in F344 female rats employing AN in blood as an internal dose metric

0 0.05 0.1 0.15 0.2 0.25

0 0.01 0.02 0.03 0.04 0.05Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

11:37 09/27 2007 BMD BMDL Multistage

=================================================== ================= Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_FEMALE_ZYMBAL_BLOOD_AN.(d ) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_FEMALE_ZYMBAL_BLOOD_AN.pl t Thu Sep 27 11:37:11 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 6 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-237 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0 Beta(1) = 2.5025

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Backgroun d have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Beta(1)

Beta(1) 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0 * * * Beta(1) 1.94599 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -33.0086 6 Fitted model -34.4088 1 2.8 0031 5 0.7307 Reduced model -49.1799 1 32. 3425 5 <.0001

AIC: 70.8176

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0000 0.000 0 157 0.000 0.0006 0.0011 0.081 0 73 -0.285 0.0017 0.0033 0.244 0 73 -0.495 0.0060 0.0116 0.815 0 70 -0.908 0.0179 0.0342 2.499 2 73 -0.321 0.0563 0.1038 6.434 8 62 0.652

Chi^2 = 1.68 d.f. = 5 P-value = 0.8915

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.0541423

BMDL = 0.0335374

BMDU = 0.0957005

Taken together, (0.0335374, 0.0957005) is a 90 % two-sided confidence interval for the BMD

### B-238 DRAFT- DO NOT CITE OR QUOTE

Tumor Site: Mammary Gland (Johannsen and Levinskas, 2002b; Biodynamics, 1980 b)

Table B-25. Incidence of mammary gland tumors in F 344 rats exposed to AN in drinking water for 2 years

Predicted internal dose metrics

Sex Administered

animal dose (ppm in drinking water) Equivalent

administered animal dose a (mg/kg-d) AN-AUC in blood

(mg/L) CEO-AUC in blood

(mg/L) Incidence of

mammary gland tumors b
0 0 0 0 14/156 (9%)
1 0.12 5.73 × 10 -4 5.32 × 10 -5 8/80 (10%)
3 0.36 1.72 × 10 -3 1.59 × 10 -4 6/80 (8%)
10 1.25 6.02 × 10 -3 5.49 × 10 -4 9/80 (11%)
30 3.65 1.79 × 10 -2 1.58 × 10 -3 12/80 (15%) Female

100 10.90 5.63 × 10 -2 4.46 × 10 -3 14/73 (19%)

a Administered doses were averages calculated by the study authors based on animal BW and drinking water intake.
b Incidences for F344 rats do not include animals fro m the 6- and 12-mo sacrifices and were further adju sted to exclude (from the denominators) rats that died betw een 0 and 12 mos in the study.



### Table B-26. Summary of BMD modeling results based on incidence of mammary gland tumors in F344 rats exposed to AN in drinking water for 2
years

Dose metric Best-fit model a χ 2 p -value b AIC BMD 10 c BMDL 10 d

Females
Administered dose 1 ° MS 0.94 388.94 8.73 mg/kg-d 4.77 mg/kg-d
CEO 1 ° MS 0.94 388.88 3.58 × 10 -3 mg/L 1.97 × 10 -3 mg/L
AN 1 ° MS 0.93 389.00 4.51 × 10 -2 mg/L 2.45 × 10 -2 mg/L

a Dose-response models were fit using BMDS, version 1 .4.1. “1 ° MS” indicates a one-stage multistage model.
b p value from the χ 2 goodness of fit test. Values <0.1 indicate a sign ificant lack of fit.

c BMD 10 = BMD at 10% extra risk.
d BMDL 10 = 95% lower confidence limit on the BMD at 10% ext ra risk.

### B-239 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for mammary gland tumor s in F344 female rats employing administered dose as a dose metric

0.05 0.1 0.15 0.2 0.25 0.3

0 2 4 6 8 10Fraction Affected



### dose

Multistage Cancer Model with 0.95 Confidence Level

15:04 01/26 2009 BMD BMDL Multistage Cancer Linear extrapolation

================================================== ================== Multistage Cancer Model. (Version: 1.5; Date : 02/20/2007) Input Data File: M:\ACN DOSE-RESPONSE MODELING \CANCER\ORAL\F344_FEMALE_MAMMARY_DW.(d) Gnuplot Plotting File: M:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_FEMALE_MAMMARY_DW.plt Mon Jan 26 15:04:09 2009

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 6 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-240 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.093497 Beta(1) = 0.0112514

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1)

Background 1 -0.52

Beta(1) -0.52 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0913697 * * * Beta(1) 0.0120689 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -192.056 6 Fitted model -192.471 2 0.83 0208 4 0.9344 Reduced model -195.631 1 7.1 4977 5 0.2097

AIC: 388.943

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0914 14.254 14 156 -0.070 0.1200 0.0927 7.415 8 80 0.226 0.3600 0.0953 7.625 6 80 -0.619 1.2500 0.1050 8.398 9 80 0.220 3.6500 0.1305 10.442 12 80 0.517 10.9000 0.2034 14.846 14 73 -0.246

Chi^2 = 0.81 d.f. = 4 P-value = 0.9365

### B-241 DRAFT- DO NOT CITE OR QUOTE

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 8.72994

BMDL = 4.77219

BMDU = 27.9615

Taken together, (4.77219, 27.9615) is a 90 % tw o-sided confidence interval for the BMD

Multistage Cancer Slope Factor = 0.0209547

### B-242 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for mammary gland tumor s in F344 female rats employing CEO in blood as an internal dose metric

0.05 0.1 0.15 0.2 0.25 0.3

0 0.0005 0.001 0.0015 0.002 0.0025 0.003 0.0035 0.004 0.0045Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

15:16 09/27 2007 BMD BMDL Multistage

================================================== ================== Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_FEMALE_MAMMARY_BLOOD_CEO. (d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_FEMALE_MAMMARY_BLOOD_CEO. plt Thu Sep 27 15:16:49 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 6 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-243 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.0927789 Beta(1) = 27.631

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1)

Background 1 -0.53

Beta(1) -0.53 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0908696 * * * Beta(1) 29.4458 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -192.056 6 Fitted model -192.441 2 0.77 0201 4 0.9424 Reduced model -195.631 1 7.1 4977 5 0.2097

AIC: 388.883

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0909 14.176 14 156 -0.049 0.0001 0.0923 7.383 8 80 0.238 0.0002 0.0951 7.609 6 80 -0.613 0.0005 0.1054 8.436 9 80 0.205 0.0016 0.1322 10.576 12 80 0.470 0.0045 0.2028 14.801 14 73 -0.233

Chi^2 = 0.75 d.f. = 4 P-value = 0.9447

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.00357812

BMDL = 0.00196521

BMDU = 0.011322

Taken together, (0.00196521, 0.011322) is a 90 % two-sided confidence interval for the BMD

### B-244 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for mammary gland tumor s in F344 female rats employing AN in blood as an internal dose metric

0.05 0.1 0.15 0.2 0.25 0.3

0 0.01 0.02 0.03 0.04 0.05Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

11:39 09/27 2007 BMD BMDL Multistage

================================================== ================== Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_FEMALE_MAMMARY_BLOOD_AN.( d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\ORAL\F344_FEMALE_MAMMARY_BLOOD_AN.p lt Thu Sep 27 11:39:30 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 6 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values

### B-245 DRAFT- DO NOT CITE OR QUOTE

Background = 0.0941503 Beta(1) = 2.16751

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1)

Background 1 -0.52

Beta(1) -0.52 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0918429 * * * Beta(1) 2.33757 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -192.056 6 Fitted model -192.5 2 0.88 7943 4 0.9263 Reduced model -195.631 1 7.1 4977 5 0.2097

AIC: 389.001

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0918 14.327 14 156 -0.091 0.0006 0.0931 7.445 8 80 0.214 0.0017 0.0955 7.639 6 80 -0.624 0.0060 0.1045 8.363 9 80 0.233 0.0179 0.1291 10.325 12 80 0.559 0.0563 0.2038 14.880 14 73 -0.256

Chi^2 = 0.87 d.f. = 4 P-value = 0.9282

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.0450726

BMDL = 0.0245301

BMDU = 0.146059

Taken together, (0.0245301, 0.146059) is a 90 % two-sided confidence interval for the BMD

### B-246 DRAFT- DO NOT CITE OR QUOTE

APPENDIX B-4. CANCER INHALATION DOSE-RESPONSE ASSE SSMENT: BMD
MODELING RESULTS FOR TUMOR INCIDENCE DATA FROM RATS
CHRONICALLY EXPOSED TO AN VIA INHALATION

As summarized in Section 4.6.2, AN is a multisite c arcinogen in chronic rodent bioassays. Data from the only available chronic in halation cancer bioassay with multiple exposure levels to AN were used for dose-response a ssessment (Dow Chemical Co., 1992a; Quast et al., 1980b). In this study, male and fema le Sprague-Dawley rats were exposed to AN in air at concentrations of 0, 20, or 80 ppm 6 hours/d ay, 5 days/week for 2 years. At 80 ppm, significantly increased incidences of CNS tumors (i .e., astrocytomas and glial cell proliferation) and Zymbal’s gland tumors were observed in males an d females. Also at this concentration, significantly increased incidences of malignant mam mary gland tumors (i.e., adenocarcinomas) in females, as well as intestinal and tongue tumors in males, were seen. At 20 ppm, male and female rats exhibited increased incidences (althoug h nonsignificant) of CNS tumors (i.e., astrocytomas and glial cell proliferation) and Zymb al’s gland tumors. In this appendix, detailed results of the dose-res ponse modeling for each of the tumor sites listed above are presented (Tables B-27 throu gh B-36). For each tumor site, first a summary of the dose-response data is presented, fol lowed by a table summarizing the results of the dose-response modeling. Finally, the standard output from EPA’s BMDS, version 1.4.1, for the selected dose-response model for each tumor sit e is presented. In general, the multistage model was fit to all of the data sets with the BMR set at 0.1 (i.e., 10% extra risk). In fitting this model, successive stages of the multistage model, starting with stage 1 and ending with the stage equ al to the number of dose groups minus one, were fit to the tumor incidence data at a particula r site for each rat sex employing either
administered dose or the internal dose metric CEO i n blood. Then, for each dose metric, all stages of the multistage model that did not show a significant lack of fit (i.e., p > 0.1) were compared using AIC. The stage of the multistage mo del with the lowest AIC was selected as the best-fit model. For most tumor sites, the one-stag e model exhibited the best fit. For data sets that exhibited a significant lack of fit for all st ages of the multistage model, dose groups were dropped (starting with the highest dose group) unti l an adequate fit was achieved.

### B-247 DRAFT- DO NOT CITE OR QUOTE

Sprague-Dawley Rats (Dow Chemical Co., 1992a; Quast et al., 1980b)

Tumor Site: Intestine

Table B-27. Incidence of intestinal tumors in Spra gue-Dawley rats exposed to AN in air for 2 years

Sex Administered AN concentration

(ppm in air) Predicted CEO-AUC in blood (mg/L) Incidence of intestinal tumors a 0 0 4/96 (4%)
20 2.17 × 10 -3 3/93 (3%) Male
80 8.20 × 10 -3 17/82 (21%) b

a Incidences for Sprague-Dawley rats do not include a nimals from the 6- and 12-mo sacrifices and were fu rther adjusted to exclude (from the denominators) rats th at died between 0 and 12 mos in the study.
b Significantly different from controls ( p < 0.05) as calculated by the study authors.



### Table B-28. Summary of BMD modeling results based on incidence of intestinal tumors in Sprague-Dawley rats exposed to AN in air for 2 years

Dose metric Best-fit model a χ 2 p value b AIC BMD 10 c BMDL 10 d

Males
Administered dose 2 ° MS 0.45 148.05 59.04 ppm 42.68 ppm
CEO 2 ° MS 0.42 148.13 6.06 × 10 -3 mg/L 4.47 × 10 -3 mg/L

a Dose-response models were fit using BMDS, version 1 .4.1. “2 ° MS” indicates a two-stage multistage model
b p value from the χ 2 goodness of fit test. Values <0.1 indicate a sign ificant lack of fit.

c BMD 10 = BMD at 10% extra risk.
d BMDL 10 = 95% lower confidence limit on the BMD at 10% ext ra risk.

### B-248 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for intestinal tumors i n Sprague-Dawley male rats employing administered dose as a dose metric

0 0.05 0.1 0.15 0.2 0.25 0.3

0 10 20 30 40 50 60 70 80Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

13:10 04/13 2007 BMD BMDL Multistage

================================================== ================== Multistage Model. $Revision: 2.1 $ $Date: 200 0/08/21 03:38:21 $ Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\INHALATION\SD_MALE_INTESTINE_INHALE _PPM.(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\INHALATION\SD_MALE_INTESTINE_INHALE _PPM.plt Fri Apr 13 13:10:33 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1-beta2*dose^2)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 3 Total number of records with missing values = 0 Total number of parameters in model = 3 Total number of specified parameters = 0 Degree of polynomial = 2

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-249 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.0312892 Beta(1) = 0 Beta(2) = 3.12226e-005

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Beta(1) have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Background Beta(2)

Background 1 -0.55

Beta(2) -0.55 1

Parameter Estimates

Variable Estimate Std. Err. Background 0.033209 0.073 6218 Beta(1) 0 N A Beta(2) 3.02304e-005 2.28675e -005

NA - Indicates that this parameter has hit a bound implied by some inequality constraint and thus has no standard error.

Analysis of Deviance Table

Model Log(likelihood) Deviance Test D F P-value Full model -71.7319 Fitted model -72.0247 0.585523 1 0.4442 Reduced model -81.082 18.7001 2 <.0001

AIC: 148.049

### B-250 DRAFT- DO NOT CITE OR QUOTE

Goodness of Fit

Dose Est._Prob. Expected Observed Size Chi^2 Res.

------------------------------------------------- ---------------------- i: 1 0.0000 0.0332 3.188 4 96 0.263 i: 2 20.0000 0.0448 4.169 3 93 -0.294 i: 3 80.0000 0.2033 16.669 17 82 0.025

Chi-square = 0.57 DF = 1 P-value = 0.4521

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 59.036

BMDL = 42.6779

### B-251 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for intestinal tumors i n Sprague-Dawley male rats employing CEO in blood as an internal dose metric

0 0.05 0.1 0.15 0.2 0.25 0.3

0 0.001 0.002 0.003 0.004 0.005 0.006 0.007 0.008Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

15:20 09/27 2007 BMD BMDL Multistage

================================================== ================== Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\INHALATION\SD_MALE_INTESTINE_INHALE _BLOOD_CEO.(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\INHALATION\SD_MALE_INTESTINE_INHALE _BLOOD_CEO.plt Thu Sep 27 15:20:06 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1-beta2*dose^2)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 3 Total number of records with missing values = 0 Total number of parameters in model = 3 Total number of specified parameters = 0 Degree of polynomial = 2

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values

### B-252 DRAFT- DO NOT CITE OR QUOTE

Background = 0.0306135 Beta(1) = 0 Beta(2) = 2979.81

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Beta(1) have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Background Beta(2)

Background 1 -0.55

Beta(2) -0.55 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0328821 * * * Beta(1) 0 * * * Beta(2) 2868.6 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -71.7319 3 Fitted model -72.0636 2 0.66 3417 1 0.4154 Reduced model -81.082 1 18. 7001 2 <.0001

AIC: 148.127

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0329 3.157 4 96 0.483 0.0022 0.0459 4.265 3 93 -0.627 0.0082 0.2025 16.609 17 82 0.107

Chi^2 = 0.64 d.f. = 1 P-value = 0.4246

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.00606044

BMDL = 0.004465

BMDU = 0.00809222

Taken together, (0.004465, 0.00809222) is a 90 % two-sided confidence interval for the BMD

### B-253 DRAFT- DO NOT CITE OR QUOTE

Tumor Site: CNS (Dow Chemical Co., 1992a; Quast et al., 1980b)

Table B-29. Incidence of CNS tumors in Sprague-Daw ley rats exposed to AN in air for 2 years

Sex Administered AN concentration

(ppm in air) Predicted CEO-AUC in blood (mg/L) Incidence of CNS tumors a 0 0 0/96 (0%)
20 2.17 × 10 -3 4/93 (4%) Male

80 8.20 × 10 -3 22/82 (27%) b
0 0 0/93 (0%)
20 2.18 × 10 -3 8/99 (8%) b Female

80 8.24 × 10 -3 20/89 (22%) b

a Incidences for Sprague-Dawley rats do not include a nimals from the 6- and 12-mo sacrifices and were fu rther adjusted to exclude (from the denominators) rats th at died between 0 and 12 mos in the study.
b Significantly different from controls ( p < 0.05) as calculated by the study authors.



### Table B-30. Summary of BMD modeling results based on incidence of CNS tumors in Sprague-Dawley rats exposed to AN in air for 2 years

Dose metric Best-fit model a χ 2 p -value b AIC BMD 10 c BMDL 10 d

Males
Administered dose 1 ° MS 0.56 131.64 30.22 ppm 22.23 ppm
CEO 1 ° MS 0.50 131.92 3.14 × 10 -3 mg/L 2.31 × 10 -3 mg/L
Females
Administered dose 1 ° MS 0.80 152.86 30.79 ppm 22.89 ppm
CEO 1 ° MS 0.87 152.70 3.21 × 10 -3 mg/L 2.39 × 10 -3 mg/L

a Dose-response models were fit using BMDS, version 1 .4.1. “1 ° MS” indicates a one-stage multistage model.
b p value from the χ 2 goodness of fit test. Values <0.1 indicate a sign ificant lack of fit.

c BMD 10 = BMD at 10% extra risk.
d BMDL 10 = 95% lower confidence limit on the BMD at 10% ext ra risk.

### B-254 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for CNS tumors in Sprag ue-Dawley male rats employing administered dose as a dose metric

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

0 10 20 30 40 50 60 70 80Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

13:18 04/13 2007 BMD BMDL Multistage

================================================== ================== Multistage Model. $Revision: 2.1 $ $Date: 200 0/08/21 03:38:21 $ Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\INHALATION\SD_MALE_CNS_INHALE_PPM.( d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\INHALATION\SD_MALE_CNS_INHALE_PPM.p lt Fri Apr 13 13:18:45 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 3 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-255 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0 Beta(1) = 0.00403595

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Backgroun d have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Beta(1)

Beta(1) 1

Parameter Estimates

Variable Estimate Std. Err. Background 0 N A Beta(1) 0.00348587 0.0014 7454

NA - Indicates that this parameter has hit a bound implied by some inequality constraint and thus has no standard error.

Analysis of Deviance Table

Model Log(likelihood) Deviance Test D F P-value Full model -64.1853 Fitted model -64.8194 1.26826 2 0.5304 Reduced model -85.6554 42.9402 2 <.0001

AIC: 131.639

Goodness of Fit

Dose Est._Prob. Expected Observed Size Chi^2 Res.

------------------------------------------------- ---------------------- i: 1 0.0000 0.0000 0.000 0 96 0.000 i: 2 20.0000 0.0673 6.263 4 93 -0.387 i: 3 80.0000 0.2434 19.956 22 82 0.135

Chi-square = 1.15 DF = 2 P-value = 0.5617

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 30.225

BMDL = 22.2323

### B-256 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for CNS tumors in Sprag ue-Dawley male rats employing

CEO in blood as an internal dose metric

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4

0 0.001 0.002 0.003 0.004 0.005 0.006 0.007 0.008Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

15:22 09/27 2007 BMD BMDL Multistage

================================================== ================== Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\INHALATION\SD_MALE_CNS_INHALE_BLOOD _CEO.(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\INHALATION\SD_MALE_CNS_INHALE_BLOOD _CEO.plt Thu Sep 27 15:22:30 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 3 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values

### B-257 DRAFT- DO NOT CITE OR QUOTE

Background = 0 Beta(1) = 39.4721

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Backgroun d have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Beta(1)

Beta(1) 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0 * * * Beta(1) 33.5271 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -64.1853 3 Fitted model -64.9602 1 1.5 4975 2 0.4608 Reduced model -85.6554 1 42. 9402 2 <.0001

AIC: 131.92

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0000 0.000 0 96 0.000 0.0022 0.0702 6.525 4 93 -1.025 0.0082 0.2404 19.711 22 82 0.592

Chi^2 = 1.40 d.f. = 2 P-value = 0.4963

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.00314255

BMDL = 0.00231159

BMDU = 0.00442253

Taken together, (0.00231159, 0.00442253) is a 90 % two-sided confidence interval for the BMD

### B-258 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for CNS tumors in Sprag ue-Dawley female rats

employing administered dose as a dose metric

0 0.05 0.1 0.15 0.2 0.25 0.3

0 10 20 30 40 50 60 70 80Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

13:31 04/13 2007 BMD BMDL Multistage

================================================== ================== Multistage Model. $Revision: 2.1 $ $Date: 200 0/08/21 03:38:21 $ Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\INHALATION\SD_FEMALE_CNS_INHALE_PPM .(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\INHALATION\SD_FEMALE_CNS_INHALE_PPM .plt Fri Apr 13 13:31:42 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 3 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-259 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.00947538 Beta(1) = 0.00310229

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Backgroun d have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Beta(1)

Beta(1) 1

Parameter Estimates

Variable Estimate Std. Err. Background 0 N A Beta(1) 0.00342189 0.0014 8795

NA - Indicates that this parameter has hit a bound implied by some inequality constraint and thus has no standard error.

Analysis of Deviance Table

Model Log(likelihood) Deviance Test D F P-value Full model -75.2138 Fitted model -75.4293 0.431111 2 0.8061 Reduced model -91.1284 31.8293 2 <.0001

AIC: 152.859

Goodness of Fit

Dose Est._Prob. Expected Observed Size Chi^2 Res.

------------------------------------------------- ---------------------- i: 1 0.0000 0.0000 0.000 0 93 0.000 i: 2 20.0000 0.0661 6.549 8 99 0.237 i: 3 80.0000 0.2395 21.314 20 89 -0.081

Chi-square = 0.45 DF = 2 P-value = 0.7982

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 30.7901

BMDL = 22.8938

### B-260 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for CNS tumors in Sprag ue-Dawley female rats

employing CEO in blood as an internal dose metric

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

0 0.001 0.002 0.003 0.004 0.005 0.006 0.007 0.008Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

15:38 09/27 2007 BMD BMDL Multistage

================================================== ================== Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\INHALATION\SD_FEMALE_CNS_INHALE_BLO OD_CEO.(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\INHALATION\SD_FEMALE_CNS_INHALE_BLO OD_CEO.plt Thu Sep 27 15:38:25 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 3 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-261 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.00769725 Beta(1) = 30.2917

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Backgroun d have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Beta(1)

Beta(1) 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0 * * * Beta(1) 32.7805 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -75.2138 3 Fitted model -75.3524 1 0.27 7338 2 0.8705 Reduced model -91.1284 1 31. 8293 2 <.0001

AIC: 152.705

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0000 0.000 0 93 0.000 0.0022 0.0690 6.827 8 99 0.465 0.0082 0.2367 21.065 20 89 -0.266

Chi^2 = 0.29 d.f. = 2 P-value = 0.8663

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.00321413

BMDL = 0.00238988

BMDU = 0.00446381

Taken together, (0.00238988, 0.00446381) is a 90 % two-sided confidence interval for the BMD

### B-262 DRAFT- DO NOT CITE OR QUOTE

Tumor Site: Zymbal Gland (Dow Chemical Co., 1992a; Quast et al., 1980b)

Table B-31. Incidence of Zymbal gland tumors in Sp rague-Dawley rats exposed to AN in air for 2 years

Sex Administered AN concentration

(ppm in air) Predicted CEO-AUC in blood (mg/L) Incidence of Zymbal gland tumors a 0 0 2/96 (2%)
20 2.17 × 10 -3 4/93 (4%) Male

80 8.20 × 10 -3 11/82 (13%) b
0 0 0/93 (0%)
20 2.18 × 10 -3 1/98 (1%) Female

80 8.24 × 10 -3 11/89 (12%) b

a Incidences for Sprague-Dawley rats do not include a nimals from the 6- and 12-mo sacrifices and were fu rther adjusted to exclude (from the denominators) rats th at died between 0 and 12 mos in the study.
b Significantly different from controls ( p < 0.05) as calculated by the study authors.



### Table B-32. Summary of BMD modeling results based on incidence of Zymbal’s gland tumors in Sprague-Dawley rats expose d to AN in air for 2 years

Dose metric Best-fit model a χ 2 p -value b AIC BMD 10 c BMDL 10 d

Males
Administered dose 1 ° MS 0.78 121.17 70.29 ppm 42.53 ppm
CEO 1 ° MS 0.73 121.21 7.26 × 10 -3 mg/L 4.40 × 10 -3 mg/L
Females
Administered dose 1 ° MS 0.50 81.47 75.70 ppm 48.74 ppm
CEO 1 ° MS 0.46 81.67 7.90 × 10 -3 mg/L 5.09 × 10 -3 mg/L

a Dose-response models were fit using BMDS, version 1 .4.1. “1 ° MS” indicates a one-stage multistage model.
b p value from the χ 2 goodness of fit test. Values <0.1 indicate a sign ificant lack of fit.

c BMD 10 = BMD at 10% extra risk.
d BMDL 10 = 95% lower confidence limit on the BMD at 10% ext ra risk.

### B-263 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for Zymbal gland tumors in Sprague-Dawley male rats

employing administered dose as a dose metric

0 0.05 0.1 0.15 0.2

0 10 20 30 40 50 60 70 80Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

13:22 04/13 2007 BMD BMDL Multistage

================================================== ================== Multistage Model. $Revision: 2.1 $ $Date: 200 0/08/21 03:38:21 $ Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\INHALATION\SD_MALE_ZYMBAL_INHALE_PP M.(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\INHALATION\SD_MALE_ZYMBAL_INHALE_PP M.plt Fri Apr 13 13:22:06 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 3 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-264 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.0172853 Beta(1) = 0.00156747

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1)

Background 1 -0.66

Beta(1) -0.66 1

Parameter Estimates

Variable Estimate Std. Err. Background 0.0193054 0.081 9561 Beta(1) 0.00149893 0.0018 7956

Analysis of Deviance Table

Model Log(likelihood) Deviance Test D F P-value Full model -58.5432 Fitted model -58.5838 0.0811571 1 0.7757 Reduced model -63.5267 9.9669 2 0.00685

AIC: 121.168

Goodness of Fit

Dose Est._Prob. Expected Observed Size Chi^2 Res.

------------------------------------------------- ---------------------- i: 1 0.0000 0.0193 1.853 2 96 0.081 i: 2 20.0000 0.0483 4.489 4 93 -0.114 i: 3 80.0000 0.1301 10.670 11 82 0.036

Chi-square = 0.08 DF = 1 P-value = 0.7780

### B-265 DRAFT- DO NOT CITE OR QUOTE

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 70.2907

BMDL = 42.5347

### B-266 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for Zymbal gland tumors in Sprague-Dawley male rats

employing CEO in blood as an internal dose metric

0 0.05 0.1 0.15 0.2 0.25

0 0.001 0.002 0.003 0.004 0.005 0.006 0.007 0.008Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

15:25 09/27 2007 BMD BMDL Multistage

================================================== ================== Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\INHALATION\SD_MALE_ZYMBAL_INHALE_BL OOD_CEO.(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\INHALATION\SD_MALE_ZYMBAL_INHALE_BL OOD_CEO.plt Thu Sep 27 15:25:06 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 3 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-267 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.0165179 Beta(1) = 15.3411

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1)

Background 1 -0.66

Beta(1) -0.66 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0190621 * * * Beta(1) 14.5086 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -58.5432 3 Fitted model -58.6032 2 0.12 0008 1 0.729 Reduced model -63.5267 1 9. 9669 2 0.00685

AIC: 121.206

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0191 1.830 2 96 0.127 0.0022 0.0495 4.600 4 93 -0.287 0.0082 0.1291 10.586 11 82 0.136

Chi^2 = 0.12 d.f. = 1 P-value = 0.7323

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.00726195

BMDL = 0.00440461

BMDU = 0.0159076

Taken together, (0.00440461, 0.0159076) is a 90 % two-sided confidence interval for the BMD

### B-268 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for Zymbal gland tumors in Sprague-Dawley female rats

employing administered dose as a dose metric

0 0.05 0.1 0.15 0.2

0 10 20 30 40 50 60 70 80Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

13:35 04/13 2007 BMD BMDL Multistage

================================================== ================== Multistage Model. $Revision: 2.1 $ $Date: 200 0/08/21 03:38:21 $ Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\INHALATION\SD_FEMALE_ZYMBAL_INHALE_ PPM.(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\INHALATION\SD_FEMALE_ZYMBAL_INHALE_ PPM.plt Fri Apr 13 13:35:30 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 3 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-269 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0 Beta(1) = 0.0017365

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Backgroun d have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Beta(1)

Beta(1) 1

Parameter Estimates

Variable Estimate Std. Err. Background 0 N A Beta(1) 0.00139182 0.0012 7839

NA - Indicates that this parameter has hit a bound implied by some inequality constraint and thus has no standard error.

Analysis of Deviance Table

Model Log(likelihood) Deviance Test D F P-value Full model -38.8683 Fitted model -39.7334 1.73007 2 0.421 Reduced model -49.5377 21.3387 2 <.0001

AIC: 81.4668

Goodness of Fit

Dose Est._Prob. Expected Observed Size Chi^2 Res.

------------------------------------------------- ---------------------- i: 1 0.0000 0.0000 0.000 0 93 0.000 i: 2 20.0000 0.0275 2.690 1 98 -0.646 i: 3 80.0000 0.1054 9.378 11 89 0.193

Chi-square = 1.41 DF = 2 P-value = 0.4952

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 75.6997

BMDL = 48.7384

### B-270 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for Zymbal gland tumors in Sprague-Dawley female rats

employing CEO in blood as an internal dose metric

0 0.05 0.1 0.15 0.2

0 0.001 0.002 0.003 0.004 0.005 0.006 0.007 0.008Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

15:41 09/27 2007 BMD BMDL Multistage

================================================== ================== Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\INHALATION\SD_FEMALE_ZYMBAL_INHALE_ BLOOD_CEO.(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\INHALATION\SD_FEMALE_ZYMBAL_INHALE_ BLOOD_CEO.plt Thu Sep 27 15:41:40 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 3 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values

### B-271 DRAFT- DO NOT CITE OR QUOTE

Background = 0 Beta(1) = 16.8864

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Backgroun d have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Beta(1)

Beta(1) 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0 * * * Beta(1) 13.3383 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -38.8683 3 Fitted model -39.8337 1 1.9 3077 2 0.3808 Reduced model -49.5377 1 21. 3387 2 <.0001

AIC: 81.6675

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0000 0.000 0 93 0.000 0.0022 0.0287 2.808 1 98 -1.095 0.0082 0.1041 9.263 11 89 0.603

Chi^2 = 1.56 d.f. = 2 P-value = 0.4579

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.00789912

BMDL = 0.00508579

BMDU = 0.0132303

Taken together, (0.00508579, 0.0132303) is a 90 % two-sided confidence interval for the BMD

### B-272 DRAFT- DO NOT CITE OR QUOTE

Tumor Site: Tongue (Dow Chemical Co., 1992a; Quast et al., 1980b)

Table B-33. Incidence of tongue tumors in Sprague- Dawley rats exposed to AN in air for 2 years

Sex Administered AN concentration

(ppm in air) Predicted CEO-AUC in blood (mg/L) Incidence of tongue tumors a 0 0 1/95 (1%)
20 2.17 × 10 -3 0/14 (0%) Male

80 8.20 × 10 -3 7/82 (9%) b

a Incidences for Sprague-Dawley rats do not include a nimals from the 6- and 12-mo sacrifices and were fu rther adjusted to exclude (from the denominators) rats th at died between 0 and 12 mos in the study.
b Significantly different from controls ( p < 0.05) as calculated by the study authors.



### Table B-34. Summary of BMD modeling results based on incidence of tongue tumors in Sprague-Dawley rats exposed to AN in air for 2 years

Dose metric Best-fit model a χ 2 p -value b AIC BMD 10 c BMDL 10 d

Males
Administered dose 1 ° MS 0.51 63.76 111.06 ppm 59.41 ppm

CEO 2 ° MS 0.63 63.37 9.48 × 10 -3 mg/L 6.39 × 10 -3 mg/L

a Dose-response models were fit using BMDS, version 1 .4.1. “1 ° MS” indicates a one-stage multistage model. “2 ° MS” indicates a two-stage multistage model.
b p value from the χ 2 goodness of fit test. Values <0.1 indicate a sign ificant lack of fit.

c BMD 10 = BMD at 10% extra risk.
d BMDL 10 = 95% lower confidence limit on the BMD at 10% ext ra risk.

### B-273 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for tongue tumors in Sp rague-Dawley male rats employing administered dose as a dose metric

0 0.05 0.1 0.15 0.2

0 20 40 60 80 100 120Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

13:25 04/13 2007 BMD BMDL Multistage

================================================== ================== Multistage Model. $Revision: 2.1 $ $Date: 200 0/08/21 03:38:21 $ Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\INHALATION\SD_MALE_TONGUE_INHALE_PP M.(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\INHALATION\SD_MALE_TONGUE_INHALE_PP M.plt Fri Apr 13 13:25:25 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 3 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-274 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0 Beta(1) = 0.00109944

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1)

Background 1 -0.65

Beta(1) -0.65 1

Parameter Estimates

Variable Estimate Std. Err. Background 0.00947867 0.096 8926 Beta(1) 0.000948673 0.0018 6696

Analysis of Deviance Table

Model Log(likelihood) Deviance Test D F P-value Full model -29.4666 Fitted model -29.8775 0.821799 1 0.3647 Reduced model -33.2127 7.49227 2 0.02361

AIC: 63.755

Goodness of Fit

Dose Est._Prob. Expected Observed Size Chi^2 Res.

------------------------------------------------- ---------------------- i: 1 0.0000 0.0095 0.900 1 95 0.112 i: 2 20.0000 0.0281 0.393 0 14 -1.029 i: 3 80.0000 0.0819 6.713 7 82 0.046

Chi-square = 0.43 DF = 1 P-value = 0.5124

### B-275 DRAFT- DO NOT CITE OR QUOTE

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 111.061

BMDL = 59.4126

### B-276 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for tongue tumors in Sp rague-Dawley male rats employing CEO in blood as an internal dose metric

0 0.05 0.1 0.15 0.2 0.25

0 0.002 0.004 0.006 0.008Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

15:28 09/27 2007 BMD BMDL Multistage

================================================== ================== Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\INHALATION\SD_MALE_TONGUE_INHALE_BL OOD_CEO.(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\INHALATION\SD_MALE_TONGUE_INHALE_BL OOD_CEO.plt Thu Sep 27 15:28:11 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1-beta2*dose^2)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 3 Total number of records with missing values = 0 Total number of parameters in model = 3 Total number of specified parameters = 0 Degree of polynomial = 2

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values

### B-277 DRAFT- DO NOT CITE OR QUOTE

Background = 0.00257667 Beta(1) = 0 Beta(2) = 1279.63

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Beta(1) have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Background Beta(2)

Background 1 -0.64

Beta(2) -0.64 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.00925756 * * * Beta(1) 0 * * * Beta(2) 1172.26 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -29.4666 3 Fitted model -29.6826 2 0.43 1994 1 0.511 Reduced model -33.2127 1 7.4 9227 2 0.02361

AIC: 63.3652

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0093 0.879 1 95 0.129 0.0022 0.0147 0.206 0 14 -0.457 0.0082 0.0844 6.917 7 82 0.033

Chi^2 = 0.23 d.f. = 1 P-value = 0.6339

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.0094804

BMDL = 0.00638558

BMDU = 0.0279407

Taken together, (0.00638558, 0.0279407) is a 90 % two-sided confidence interval for the BMD

### B-278 DRAFT- DO NOT CITE OR QUOTE

Tumor Site: Mammary Gland (Dow Chemical Co., 1992a; Quast et al., 1980b)

Table B-35. Incidence of mammary gland tumors in S prague-Dawley rats exposed to AN in air for 2 years

Sex Administered AN concentration

(ppm in air) Predicted CEO-AUC in blood (mg/L) Incidence of mammary gland tumors a 0 0 9/93 (10%)
20 2.18 × 10 -3 8/98 (8%) Female

80 8.24 × 10 -3 20/99 (20%) b

a Incidences for Sprague-Dawley rats do not include a nimals from the 6- and 12-mo sacrifices and were fu rther adjusted to exclude (from the denominators) rats th at died between 0 and 12 mos in the study.
b Significantly different from controls ( p < 0.05) as calculated by the study authors.



### Table B-36. Summary of BMD modeling results based on incidence of mammary gland tumors in Sprague-Dawley rats exposed to AN in air for 2 years

Dose metric Best-fit model a χ 2 p -value b AIC BMD 10 c BMDL 10 d

Females
Administered dose 1 ° MS 0.28 219.42 66.48 ppm 37.82 ppm
CEO 2 ° MS 0.57 218.52 7.31 × 10 -3 mg/L 4.33 × 10 -3 mg/L

a Dose-response models were fit using BMDS, version 1 .4.1. “1 ° MS” indicates a one-stage multistage model. “2 ° MS” indicates a two-stage multistage model.
b p value from the χ 2 goodness of fit test. Values <0.1 indicate a sign ificant lack of fit.

c BMD 10 = BMD at 10% extra risk.
d BMDL 10 = 95% lower confidence limit on the BMD at 10% ext ra risk.

### B-279 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for mammary gland tumor s in Sprague-Dawley female rats

employing administered dose as a dose metric

0.05 0.1 0.15 0.2 0.25 0.3

0 10 20 30 40 50 60 70 80Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

13:38 04/13 2007 BMD BMDL Multistage

================================================== ================== Multistage Model. $Revision: 2.1 $ $Date: 200 0/08/21 03:38:21 $ Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\INHALATION\SD_FEMALE_MAMMARY_INHALE _PPM.(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\INHALATION\SD_FEMALE_MAMMARY_INHALE _PPM.plt Fri Apr 13 13:38:03 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 3 Total number of records with missing values = 0 Total number of parameters in model = 2 Total number of specified parameters = 0 Degree of polynomial = 1

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

### B-280 DRAFT- DO NOT CITE OR QUOTE

Default Initial Parameter Values Background = 0.0767126 Beta(1) = 0.00173168

Asymptotic Correlation Matrix of Paramet er Estimates

Background Beta(1)

Background 1 -0.68

Beta(1) -0.68 1

Parameter Estimates

Variable Estimate Std. Err. Background 0.0806351 0.078 3644 Beta(1) 0.00158474 0.0017 9372

Analysis of Deviance Table

Model Log(likelihood) Deviance Test D F P-value Full model -107.092 Fitted model -107.71 1.23579 1 0.2663 Reduced model -110.714 7.24319 2 0.02674

AIC: 219.421

Goodness of Fit

Dose Est._Prob. Expected Observed Size Chi^2 Res.

------------------------------------------------- ---------------------- i: 1 0.0000 0.0806 7.499 9 93 0.218 i: 2 20.0000 0.1093 10.713 8 98 -0.284 i: 3 80.0000 0.1901 18.820 20 99 0.077

Chi-square = 1.19 DF = 1 P-value = 0.2754

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 66.4843

BMDL = 37.8172

### B-281 DRAFT- DO NOT CITE OR QUOTE

BMDS (version 1.4.1) output for mammary gland tumor s in Sprague-Dawley female rats

employing CEO in blood as an internal dose metric

0.05 0.1 0.15 0.2 0.25 0.3

0 0.001 0.002 0.003 0.004 0.005 0.006 0.007 0.008Fraction Affected



### dose Multistage Model with 0.95 Confidence Level

15:44 09/27 2007 BMD BMDL Multistage

================================================== ================== Multistage Model. (Version: 2.8; Date: 02/20 /2007) Input Data File: G:\ACN DOSE-RESPONSE MODELING\CANCER\INHALATION\SD_FEMALE_MAMMARY_INHALE _BLOOD_CEO.(d) Gnuplot Plotting File: G:\ACN DOSE-RESPONSE MODELING\CANCER\INHALATION\SD_FEMALE_MAMMARY_INHALE _BLOOD_CEO.plt Thu Sep 27 15:44:26 2007

================================================== ==================

BMDS MODEL RUN

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ ~~~~~~~~~~~~~~~~~~

The form of the probability function is:

P[response] = background + (1-background)*[1-EXP ( -beta1*dose^1-beta2*dose^2)]

The parameter betas are restricted to be positiv e

Dependent variable = Response Independent variable = Dose

Total number of observations = 3 Total number of records with missing values = 0 Total number of parameters in model = 3 Total number of specified parameters = 0 Degree of polynomial = 2

Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e- 008 Parameter Convergence has been set to: 1e-008

Default Initial Parameter Values

### B-282 DRAFT- DO NOT CITE OR QUOTE

Background = 0.0853385 Beta(1) = 0 Beta(2) = 1996.34

Asymptotic Correlation Matrix of Paramet er Estimates

( *** The model parameter(s) -Beta(1) have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlati on matrix )

Background Beta(2)

Background 1 -0.6

Beta(2) -0.6 1

Parameter Estimate s

95.0% Wald Confidence Interval Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit Background 0.0856208 * * * Beta(1) 0 * * * Beta(2) 1971.76 * * *

* - Indicates that this value is not calculated.

Analysis of Deviance Table

Model Log(likelihood) # Param's Devia nce Test d.f. P-value Full model -107.092 3 Fitted model -107.258 2 0.33 2027 1 0.5645 Reduced model -110.714 1 7.2 4319 2 0.02674

AIC: 218.517

Goodness of Fit Scaled Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------- ----------------------- 0.0000 0.0856 7.963 9 93 0.384 0.0022 0.0941 9.226 8 98 -0.424 0.0082 0.2002 19.818 20 99 0.046

Chi^2 = 0.33 d.f. = 1 P-value = 0.5658

Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk

Confidence level = 0.95

BMD = 0.00730992

BMDL = 0.00432882

BMDU = 0.0152838

Taken together, (0.00432882, 0.0152838) is a 90 % two-sided confidence interval for the BMD

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APPENDIX B-5. ANALYSIS TO ASSESS COMBINING TUMOR I NCIDENCE DATA
FROM TWO CANCER BIOASSAYS EMPLOYING SPRAGUE-DAWLEY RATS

A statistical analysis was conducted to determine w hether tumor dose-response data from two 2-year drinking water bioassays in Sprague-Dawl ey rats were similar enough to be combined. The first study employed AN drinking wat er concentrations of 0, 35, 100, and 300 ppm (Quast, 2002; Quast et al., 1980a), while t he second study used AN drinking water concentrations of 0, 1, and 100 ppm (Johannsen and Levinskas, 2002a). To conduct the analysis, the multistage model in BMDS (version 1.3.2) was fi t to the tumor incidence data from three sites (forestomach, CNS, and Zymbal gland) in each sex across both studies, using administered animal dose expressed in mg/kg-day. Using the best -fit model, a statistical test described by Stiteler et al. (1993), which employs a maximum lik elihood ratio statistic distributed as a χ 2 

### , was then used to test the null hypothesis that the corr esponding data sets from the two studies are compatible with a common dose-response model. If t he null hypothesis is not rejected, this analysis provides evidence that the results from th e two studies may be pooled. The results of this analysis showed that forestomac h and Zymbal gland tumors in male and female Sprague-Dawley rats were not compatible with a common dose-response model, while CNS tumors in male and female Sprague-Dawley rats were compatible with a common dose-response model. Because of these conflicting results, it was decided that the results from the two Sprague-Dawley drinking water studies would not be pooled. Therefore, the final doseresponse analysis for deriving the oral slope facto r for AN focused on the two rat drinking water studies containing the most dose groups (i.e., the Sprague-Dawley rat bioassay reported by Quast [2002] and the F344 rat bioassay reported by Johann sen and Levinskas [2002b]). For each tumor site, summaries of the results of the statistical t ests for compatibility are shown below.

Test 1: Forestomach tumors in male Sprague-Dawley rats

Tumor incidence data

(Johannsen and Levinskas, 2002a):

• 0 ppm (0 mg/kg-day): 3/78

• 1 ppm (0.085 mg/kg-day): 3/78

• 100 ppm (8.53 mg/kg-day): 11/77

Best-fit model: 1-stage multistage Log (likelihood) = –57.0113

Tumor incidence data

(Quast, 2002):

• 0 ppm (0 mg/kg-day): 0/80

• 35 ppm (3.42 mg/kg-day): 2/47

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• 100 ppm (8.53 mg/kg-day): 23/48

• 300 ppm (21.20 mg/kg-day): 39/48

Best-fit model: 2-stage multistage (highest dose g roup dropped) Log (likelihood) = –42.4099

Tumor incidence data

(combined):

• 0 ppm (0 mg/kg-day): 3/158

• 1 ppm (0.085 mg/kg-day): 3/78

• 35 ppm (3.42 mg/kg-day): 2/47

• 100 ppm (8.53 mg/kg-day): 34/125

• 300 ppm (21.20 mg/kg-day): 39/48

Best-fit model: 2-stage multistage Log (likelihood) = –132.865

Conclusion : Based on the likelihood ratio test statistic, –2 ln Λ = 2[132.865 – (42.4099 + 57.0113)] = 2 × 33.4438 = 66.89, the data sets are not compatible with a common dose-response
model at p < 0.0001.

Test 2: Forestomach tumors in female Sprague-Dawle y rats

Tumor incidence data

(Johannsen and Levinskas, 2002a):

• 0 ppm (0 mg/kg-day): 1/80

• 1 ppm (0.11 mg/kg-day): 4/79

• 100 ppm (10.80 mg/kg-day): 7/79

Best-fit model: 1-stage multistage Log (likelihood) = –45.8328

Tumor incidence data

(Quast, 2002):

• 0 ppm (0 mg/kg-day): 1/80

• 35 ppm (4.36 mg/kg-day): 1/48

• 100 ppm (10.80 mg/kg-day): 12/48

• 300 ppm (25.00 mg/kg-day): 30/48

Best-fit model: 2-stage multistage Log (likelihood) = –69.9834

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Tumor incidence data

(combined):

• 0 ppm (0 mg/kg-day): 2/160

• 1 ppm (0.11 mg/kg-day): 4/79

• 35 ppm (4.36 mg/kg-day): 1/48

• 100 ppm (10.80 mg/kg-day): 19/127

• 300 ppm (25.00 mg/kg-day): 30/48

Best-fit model: 2-stage multistage Log (likelihood) = –119.054

Conclusion : Based on the likelihood ratio test statistic, –2 ln Λ = 2[119.054 – (69.9834 + 45.8328)] = 2 × 3.2378 = 6.48, the data sets are no t compatible with a common dose-response
model at p = 0.011.

Test 3: CNS tumors in male Sprague-Dawley rats

Tumor incidence data

(Johannsen and Levinskas, 2002a):

• 0 ppm (0 mg/kg-day): 2/78

• 1 ppm (0.085 mg/kg-day): 3/75

• 100 ppm (8.53 mg/kg-day): 23/77

Best-fit model: 1-stage multistage Log (likelihood) = –68.9254

Tumor incidence data

(Quast, 2002):

• 0 ppm (0 mg/kg-day): 1/80

• 35 ppm (3.42 mg/kg-day): 12/47

• 100 ppm (8.53 mg/kg-day): 22/48

• 300 ppm (21.20 mg/kg-day): 30/48

Best-fit model: 1-stage multistage Log (likelihood) = –98.6909

Tumor incidence data

(combined):

• 0 ppm (0 mg/kg-day): 3/158

• 1 ppm (0.085 mg/kg-day): 3/75

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• 35 ppm (3.42 mg/kg-day): 12/47

• 100 ppm (8.53 mg/kg-day): 45/125

• 300 ppm (21.20 mg/kg-day): 30/48

Best-fit model: 1-stage multistage Log (likelihood) = –168.873

Conclusion : Based on the likelihood ratio test statistic, –2 ln Λ = 2[168.873 – (98.6909 + 68.9254)] = 2 × 1.2567 = 2.51, the data sets are co mpatible with a common dose-response model

at p = 0.113.

Test 4: CNS Tumors in female Sprague-Dawley rats

Tumor incidence data

(Johannsen and Levinskas, 2002a):

• 0 ppm (0 mg/kg-day): 0/79

• 1 ppm (0.11 mg/kg-day): 1/80

• 100 ppm (10.80 mg/kg-day): 39/78

Best-fit model: 1-stage multistage Log (likelihood) = –59.5775

Tumor incidence data

(Quast, 2002):

• 0 ppm (0 mg/kg-day): 1/80

• 35 ppm (4.36 mg/kg-day): 20/48

• 100 ppm (10.80 mg/kg-day): 25/48

• 300 ppm (25.00 mg/kg-day): 31/48

Best-fit model: Log-logistic Log (likelihood) = –104.123

Tumor incidence data

(combined):

• 0 ppm (0 mg/kg-day): 1/159

• 1 ppm (0.11 mg/kg-day): 1/80

• 35 ppm (4.36 mg/kg-day): 20/48

• 100 ppm (10.80 mg/kg-day): 64/126

• 300 ppm (25.00 mg/kg-day): 31/48 Best-fit model: Log-logistic

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Log (likelihood) = –164.485

Conclusion : Based on the likelihood ratio test statistic, –2 ln Λ = 2[164.485 – (104.123 + 59.5775)] = 2 × 0.7845 = 1.57, the data sets are co mpatible with a common dose-response model

at p = 0.210.

Test 5: Zymbal gland tumors in male Sprague-Dawley rats

Tumor incidence data

(Johannsen and Levinskas, 2002a):

• 0 ppm (0 mg/kg-day): 1/80

• 1 ppm (0.085 mg/kg-day): 0/71

• 100 ppm (8.53 mg/kg-day): 17/73

Best-fit model: 1-stage multistage Log (likelihood) = –45.815

Tumor incidence data

(Quast, 2002):

• 0 ppm (0 mg/kg-day): 3/80

• 35 ppm (3.42 mg/kg-day): 4/47

• 100 ppm (8.53 mg/kg-day): 3/48

• 300 ppm (21.20 mg/kg-day): 16/48

Best-fit model: 1-stage multistage Log (likelihood) = –70.1142

Tumor incidence data

(combined):

• 0 ppm (0 mg/kg-day): 4/160

• 1 ppm (0.085 mg/kg-day): 0/71

• 35 ppm (3.42 mg/kg-day): 4/47

• 100 ppm (8.53 mg/kg-day): 20/121

• 300 ppm (21.20 mg/kg-day): 16/48

Best-fit model: 1-stage multistage Log (likelihood) = –118.806

Conclusion : Based on the likelihood ratio test statistic, –2 ln Λ = 2[118.806 – (70.1142 + 45.815)] = 2 × 2.8768 = 5.75, the data sets are not compatible with a common dose-response
model at p = 0.016.

### B-288 DRAFT- DO NOT CITE OR QUOTE Test 6: Zymbal gland tumors in female Sprague-Dawl ey rats

Tumor incidence data

(Johannsen and Levinskas, 2002a):

• 0 ppm (0 mg/kg-day): 1/79

• 1 ppm (0.11 mg/kg-day): 0/75

• 100 ppm (10.80 mg/kg-day): 12/78

Best-fit model: 1-stage multistage Log (likelihood) = –39.6428

Tumor incidence data

(Quast, 2002):

• 0 ppm (0 mg/kg-day): 1/80

• 35 ppm (4.36 mg/kg-day): 5/48

• 100 ppm (10.80 mg/kg-day): 9/48

• 300 ppm (25.00 mg/kg-day): 18/48

Best-fit model: 1-stage multistage Log (likelihood) = –76.3975

Tumor incidence data

(combined):

• 0 ppm (0 mg/kg-day): 1/159

• 1 ppm (0.11 mg/kg-day): 0/75

• 35 ppm (4.36 mg/kg-day): 5/48

• 100 ppm (10.80 mg/kg-day): 21/126

• 300 ppm (25.00 mg/kg-day): 18/48

Best-fit model: 1-stage multistage Log (likelihood) = –111.439

Conclusion : Based on the likelihood ratio test statistic, –2 ln Λ = 2[111.439 – (76.3975 + 39.6428)] = 2 × (–4.6013) = –9.20 = 9.20, the data sets are not compatible with a common doseresponse model at p = 0.002.

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APPENDIX B-6. ESTIMATION OF COMPOSITE CANCER RISK FROM EXPOSURE
TO AN BY COMBINING RISK ESTIMATES ACROSS MULTIPLE T UMOR SITES

Increased tumor incidences were observed at multipl e sites in male and female rats following exposure to AN both orally and by inhalat ion. With this multiplicity of tumors, the concern is that a potency or risk estimate based so lely on one tumor site (e.g., the most sensitive site) may underestimate the overall cancer risk ass ociated with exposure to this chemical. The most recent EPA cancer guidelines (U.S. EPA, 2005a) identified two ways to approach this issue: 1) analyze the incidence of tumor-bearing a nimals, or 2) combine the potencies associated with significantly elevated tumors at each site. T he NRC (1994) concluded that an approach
based on counts of animals with one or more tumors would tend to underestimate overall risk when tumor types occur independently, and thus an a pproach based on combining the risk estimates from each separate tumor type should be u sed. Because potencies are typically upper bound estimat es, summing such upper bound estimates across tumor sites is likely to overstate the overall risk. Therefore, following the recommendations of the NRC (1994) and the Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005a), a statistically valid upper bound on c ombined risk was derived in order to gain some understanding of the overall risk resulting fr om tumors occurring at multiple sites. It is important to note that this estimate of overall pot ency describes the risk of developing tumors at any combination of the sites considered and is not the risk of developing tumors at all three sites simultaneously. For modeling individual tumor data, the multistage model is specified as follows:

(1) P(d) = 1 - exp[-(q 0 

### + q 1 

### d + q 2 

### d 2 

### + ... + q m 

### d

m 

### )].

The model for the combined (or composite) tumor ris k is still multistage, with a functional form that has the sum of stage-specific multistage coefficients as the corresponding multistage coefficient.

(2) P c 

### (d) = 1 - exp[-( Σ

q 0i 

### + d Σ q 1i 

### + d

2 

### Σ q 2i 

### + ... + d

m 

### Σ q mi 

### )] , for i=1,..., k,
where k = total number of sites

The resulting equation for fixed extra risk (BMR) i s polynomial in dose (when logarithms of both sides are taken) and can be straightforward ly solved for the combined BMD. However,
confidence bounds for this BMD are not able to be e stimated by the current version of BMDS. Therefore, a Bayesian approach to finding confidenc e bounds on the combined BMD was implemented using WinBugs (Spiegelhalter et al., 20 03). WinBugs software is freely available and implements Markov chain Monte Carlo (MCMC) comp utations. Use of WinBugs has been

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demonstrated for derivation of a distribution of BM Ds for a single multistage model (Kopylev et al., 2007) and can be straightforwardly generalized to derive the distribution of BMDs for the combined tumor load, following the NRC (1994) metho dology described above. The advantage of a Bayesian approach is that it produces a distri bution of BMDs that allows better characterization of statistical uncertainty. For t he current analysis, a diffuse (high variance or low tolerance) Gaussian prior restricted to be nonn egative was used. The posterior distribution was based on three chains with 50,000 burn-in (i.e. , the initial 50,000 simulations were dropped) and a thinning rate of 20, resulting in 150,000 sim ulations total. The median and 5 th 

### percentile of the posterior distribution provided the BMD 10 

### (central estimate) and BMDL 10 

### (lower bound) for combined tumor load, respectively. The methodology above was applied to the dose-respo nse data for the male and female Sprague-Dawley (Quast, 2002) and F344 (Johannsen an d Levinskas, 2002b) rat drinking water studies, as well as to the data from male and femal e Sprague-Dawley rats in the Quast et al. (1980b) inhalation study. As with the risk estimat es generated for individual tumor sites, the combined analysis used the internal dose metric CEO in blood (see Appendices B-3 and B-4). The human equivalent PODs are presented in Tables B -37 (episodic oral exposure) and B-38 (continuous inhalation exposure). Estimates of com posite risk were estimated by dividing the BMR of 10% extra risk by the composite BMDL 10 

### s (0.1/BMDL 10 

### ). Human equivalent composite CSFs are presented in Table B-39, and com posite unit risks are presented in Table B-40. The slopes derived from the composite BMD 10 

### s (0.1/ BMD 10 

### ) are also included in these tables for comparison.

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Table B-37. Summary of PODs for composite cancer r isk associated with episodic oral exposure to AN, using CEO-AUC levels in blood as dose metric and multiple tumor incidence data in rats

PODs based on rat dose-responseusing internal dose metric CEOAUC in blood (mg/L) Human equivalent PODs a (mg/kg-d) Rat strain, sex Tumor site BMD 10 BMDL 10 BMD 10 BMDL 10 Sprague-Dawley, male Forestomach, CNS, Zymbal gland, tongue 4.2 × 10 -4 3.6 × 10 -4 0.042 0.036

Sprague-Dawley, female Forestomach, CNS, Zymbal gland, tongue, mammary gland 2.6 × 10 -4 2.0 × 10 -4 0.026 0.020

F344, male Forestomach, CNS, Zymbal gland 4.6 × 10 -4 3.3 × 10 -4 0.046 0.033
F344, female Forestomach, CNS, Zymbal gland, mammary gland 6.7 × 10 -4 5.2 × 10 -4 0.066 0.051

a Converted using human PBPK model.



### Table B-38. Summary of PODs for composite cancer r isk associated with inhalation exposure to AN, based on multiple tumor incidence data in rats and CEO-AUC levels in blood

PODs for rat dose-response in terms of CEO-AUC in blood

(mg/L) Human equivalent PODs: AN in air a (mg/m 3 ) Rat strain, sex Tumor site BMC 10 BMCL 10 BMC 10 BMCL 10 Sprague-Dawley, male Intestine, CNS, Zymbal gland, tongue 1.4 × 10 -3 1.1 × 10 -3 1.9 1.5
Sprague-Dawley, female CNS, Zymbal gland, mammary gland 1.7 × 10 -3 1.3 × 10 -3 2.3 1.8

a Converted using human PBPK model.

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Table B-39. Estimated human oral CSFs for AN based on multiple tumor incidence data in rats and CEO-AUC levels in blood

Rat strain, sex Tumor site Slope derived from composite BMD 10 a (mg/kg-d) -1 Composite CSF b (mg/kg-d) -1

Sprague-Dawley, male Forestomach, CNS, Zymbal gland, tongue 2.4 2.8
Sprague-Dawley, female Forestomach, CNS, Zymbal gland, tongue, mammary gland 3.8 5.0

F344, male Forestomach, CNS, Zymbal gland 2.2 3.1
F344, female Forestomach, CNS, Zymbal gland, mammary gland 1.5 1.9

a Slope estimated by 0.1/BMD 10 . b CSF = 0.1/BMDL 10 .



### Table B-40. Estimated human IURs for AN based on m ultiple tumor incidence data in rats and CEO-AUC levels in blood

Rat strain, sex Tumor site Slope to background from overall BMC 10 a (mg/m 3 ) -1 Overall IUR b (mg/m 3 ) -1 Sprague-Dawley, male Intestine, CNS, Zymbal gland, tongue 5.4 × 10 -2 6.8 × 10 -2

Sprague-Dawley, female CNS, Zymbal gland, mammary gland 4.4 × 10 -2 5.7 × 10 -2

a Slope estimated by 0.1/BMD 10 . b IUR = 0.1/BMDL 10 .

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APPENDIX B-7. STATISTICAL ANALYSIS OF BLAIR ET AL. (1998)

The Data The data used in this analysis came from the best available epidemiological study (see Section 5.4.1) by Blair et al. (1998). The raw dat a from the study were provided to EPA courtesy of NCI. The process of data collection is described in Blair et al. (1998) and in more detail in Stewart et al. (1998). The full raw data set contains 363 variables on 25,460 subjects. The variables include demographic information, empl oyment information, vital status, and various measures of exposure per study year (1942–1 983), including maximum and minimum estimates, “best estimate,” frequency of peaks, and several other ways of measuring exposure. The raw data provided by NCI did not include the sm oking data that were collected for approximately 10% of the subjects. Therefore, smok ing information was not part of the EPA's statistical analysis. The uncertainty connected to lack of smoking information is discussed in Section 5.4.5.2. The data on dates of exposure and corresponding exposure amounts, dates of mortality due to lung cancer and other causes, a pl ant worked, and the birth year were retained for the statistical analysis. Biological age was c hosen as a time scale. Data handling and statistical analysis were performed using S-PlusTM s tatistical software.

The Statistical Model The semi-parametric Cox proportional hazards model (Cox, 1972) is a widely used model in hazard regression. The Cox model with time-depe ndent covariates was chosen to model the data for to two main reasons. Primarily, it allows taking into account individual covariate history, allowing utilization of the extensive expo sure data collected by Blair et al. (1998). Additionally, the Cox model uses internal controls. Internal controls constitute an appropriate comparison group, given the healthy worker effect o bserved by Blair et al. (1998) and further demonstrated by Marsh et al. (2001). In the Cox model, the conditional hazard function, given the covariate process Z(t), is
assumed to have the form:



# λ λ β ( | ( )) ( )exp( ( )) t Z t t Z t = 0 T



### where β is the vector of regression coefficients and λ 0 

### (t) denotes the baseline hazard function. No particular shape is assumed for the baseline haz ard; it is estimated nonparametrically. The
contributions of covariates to the hazard are multi plicative. When β T 

### Z(t) is small and Z(t) represents exposure, the Cox proportional model is consistent with linearity of dose-response for low doses. When no time-dependent covariates are p resent, the cumulative hazard function Λ 0 

### (t) is estimated using a Breslow (Breslow, 1974) estima tor:

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# $ exp( $ )

( ) { : } 

# Λ 0 

# =

∈

≤ 

# ∑ ∑ d
Z

i

T j j R t i t t

i i 

# β

where Z

j 

### is the (time-independent) covariate vector of the j th 

### individual at age t i 

### , 

# $ 

# β is an estimate

of β from the Cox model, d i 

### is the number of deaths at the age t i 

### , and R(t i 

### ) is the risk set at age t i


### . Risk set is defined as all the individuals who are under observation and at risk of death at age t i


### . The Breslow estimator is piecewise constant with di screte jumps at times of death. The corresponding estimate of the baseline hazard funct ion is the size of the jump of the cumulative hazard at ages of death and zero otherwise. The su rvival function S(t) = exp(- Λ (t)) is estimated by plugging in the Breslow estimator:



# $ $ S(t) = exp(- (t))

Λ

The cumulative probability of death R(t) = 1-S(t) i s estimated by:



# $ $ R(t) = 1- S(t)

With time-dependent covariates, EPA followed the su ggestion by Starr (2004) of a modified
Breslow estimator:



# d
Z t i

T j i j R t i t t

i i 

# exp( $ ( ))

( ) { : } 

# β

∈ ≤ 

# ∑ ∑

The survival function and cumulative probability o f death are then estimated using the
modified cumulative hazard estimator. The modified estimator only approximates the true cumulative hazard since a covariate path is not enc ountered in the estimator. Therneau and Grambsch (2000) discuss clinical examples when this estimator could lead to inappropriate results, but the occupational case is very differen t from clinical examples, since at the baseline, not all workers are exposed and exposure is nondecr easing and often ends well before death.

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Calculations of Excess Risk Following Starr et al. (2004), EPA defined hazard functions for lung cancer mortality
λ lc 

### (t) and other causes of death λ oc 

### (t), with the corresponding cause-specific cumulati ve hazard functions, Λ lc 

### (t) and Λ oc 

### (t). The sum of Λ lc 

### (t) and Λ oc 

### (t) is the all-causes mortality hazard
Λ ac 

### (t) with corresponding survival function S ac 

### (t). Then, the cumulative risk of lung cancer mortality by age t, given covariate path Z(t)=z(t) is:



# R t z t u z t S u z t lc lc ac

u t 

# ( | ( )) ( | ( )) ( | ( )) =

≤ 

# ∑ λ

The cumulative risk of lung cancer mortality by age t in the absence of exposure:



# R t Z t u Z t S u Z t lc lc ac

u t 

# ( | ( ) ) ( | ( ) ) ( | ( ) ) = = = =

≤ 

# ∑ 0 0 0 

# λ

Excess risk, given covariate path Z(t)=z(t), is cal culated by:



# R t Z t z t R t Z t

R t Z t lc lc

lc 

# ( | ( ) ( )) ( | ( ) )

( | ( ) ) = − =

− = 0
1 0

When 

# z t T lc 

# ( ) β 

# << 1 and 

# β oc 

# ≈ 0 , the first order expansion of the numerator simpli fies into approximately:



# β λ λ lc lc ac

u t lc

v u 

# u z t S u z t z u z v v z t ( | ( ) ) ( | ( ) ) ( ) ( ) ( | ( ) ) = = − =

     
≤ ≤ 

# ∑ ∑

0 0 0

Plugging in estimates of β , hazard rate, and survival function into the equat ion above, an estimate of excess risk is obtained. Using estimated UCL on β instead of β results in the upper confidence
bound on the estimated risk.

Results
Model Choice. There were not enough lung cancer deaths in other t han white males sexrace groups, so sex and race were not included as c ovariates. Including time-independent covariates, such as duration and average exposure, was investigated, but time-dependent cumulative exposure was used since it allows taking into account individual exposure history. Neither the birth year (

p = 0.77) nor the plant worked on ( p = 0.061) was significant, so cumulative AN exposure was the only (time-dependent ) covariate used in the model.

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Mortality and Risk Estimates. The coxph function of S-PlusTM was used to obtain
estimates of β . The estimate of β lc 

### was equal to 1.24 × 10 -3 

### with the standard error of 2.47 × 10 -2


### ( p = 0.61). The estimate of β oc 

### was equal to 6.7 × 10 -4 

### with a standard error of 9.66 × 10 -4


### ( p = 0.49). The estimates, covariates, and event time s were then used to construct estimates of cumulative hazard and risks, as described in the pr evious section. The exposures corresponding to excess risks were divided by 2 to account for di fferences in volume of air inhaled during a working day and during a whole day (10 vs. 20 m 3 

### /day). Resulting exposure estimates (by age 80): EC 01 

### = 0.992 ppm and LEC 01 

### = 0.238 ppm. The corresponding unit risk was calc ulated to equal 4.2 × 10 -2 

### ppm -1



### .

Limitations of the Statistical Approach The statistical approach followed the approach of Starr et al. (2004), and it shares the
limitations and uncertainties described there. The limitations and uncertainties include the following:

• The Cox model fit the data adequately, but it was a n empirical model fit rather than a biologically based model.

• The estimator of the cumulative hazard does not acc ount for the covariate path and hence, is only an approximation.

• The estimate of risk is obtained using the first-or der “linearized” approximation. However, the results are consistent with assumption s of the first-order approximation validity.

• The Cox model uses internal controls and hence, it is much more vulnerable than SMR computation to contamination of pool of workers who are free of lung cancer by lung cancer cases. That is caused by misdiagnosis of lu ng cancer as not a lung cancer. Selikoff and Seidman (1992) showed based on histopa thological analysis of a comparably large industrial cohort (17,800 asbestos workers) that as much as 13.7% of lung cancer cases are misdiagnosed on death certifi cates, both as neoplasms and nonmalignant diseases, with about 3% as asbestos on ly diseases (mesothelioma and asbestosis). Therefore, the Blair cohort may have as much as 10% of internal controls that are actually lung cancers. That would cause a strong bias against finding a statistically significant relationship.

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APPENDIX C. PBPK MODEL DESCRIPTIONS AND SOURCE COD E

Model Description
The PBPK models used to calculate rat and human int ernal doses for the development of candidate RfDs, oral CSFs, and IURs were those revi sed from Kedderis et al. (1996) (rat, with EH activity towards CEO added and other parameters revised) and Sweeney et al. (2003) (human). Both models are flow limited, lumped comp artment models that predict amounts and
concentrations of AN and its metabolite of toxicolo gical interest, CEO, in blood and seven tissues: lung, brain, fat, stomach, liver, and rap idly and slowly perfused tissues. Both models include portals of entry for oral, inhalation, and i.v. routes of exposure. Drinking water is
modeled as a continuous infusion to the GI lumen. (The model code allows one to define episodic oral exposure as a series of boluses up to 6 times/day, but the simpler approach of treating the exposure as continuous was chosen.) F or rats, the infusion rate is set such that the total amount consumed equals the average total amou nt ingested during the bioassays as determined from water consumption and administered AN concentration. Inhalation duration and frequency can be explicitly defined. Simulated metabolism of AN and CEO occur only in the liver. Elimination of both compounds is accomp lished via second-order GSH conjugation in various tissues, saturable hepatic metabolism, and pulmonary excretion into exhaled air.
The rat and human models are based on the same stru ctural framework but have two primary differences: (1) physiological and metabol ic parameters for each are species specific, and (2) the human model simulates saturable, enzyme -mediated hydrolysis of CEO, a metabolic process not observed in rats. In the absence of hu man in vivo data for metabolism, human metabolic parameters were estimated from in vitro v alues extrapolated to in vivo values by using
in vitro / in vivo ratios in rats, which is described fully in Sweeney et al. (2003). In the Sweeney et al. (2003) model, a conversion factor for in vit ro to in vivo extrapolation of human metabolic constants is implicitly defined in the calculation of V max 

### values for AN oxidation and CEO hydrolysis. Model parameter values used for both s pecies are given in Table C-1.
The acslXtreme model code as used to calculate the various dose metrics, followed by the corresponding Matlab model code used to perform the optimizations for fitting of the revised parameters, are given at the end of this appendix. The Matlab code is divided into three .m files: the top-level “optACN2.m” file, a secondary “RunACN .m” file that is called by the opt file and returns the value of the objective function, and an “EqACN.m” file that defines the set of differential equations.

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Table C-1. Rat and human PBPK model parameter valu es

Parameter Rat value a Human value a Total BW (kg) 0.25 70 Percentage of BW
Liver 4 2.57
Brain 0.6 2.00
Stomach 0.63 0.21
Fat 7 21.42 Rapidly perfused 3.77 5.22 Slowly perfused 75 58.58
Venous blood 3.9 4.35
Arterial blood 2.1 2.74 Blood flows (L/h/kg 0.74 ) Cardiac output 14.0 13.4
Alveolar ventilation 14.0 12.9 Percentage of cardiac output
Liver 25 21.4
Brain 2.4 11.4
Stomach 1.3 1.3
Fat 9 5.2 Rapidly perfused 47.3 32.5 Slowly perfused 15 28.2 GSH content (mmol/L)
Liver 8.53 5.63
Brain 2.00 2.99
Stomach 4.59 3.61 Rapidly perfused 2.65 2.59 Slowly perfused 0.75 1.13
PCs AN CEO AN CEO
Blood:air 512 1,658 154 1,658
Liver:blood 0.46 0.274 1.51 0.274
Brain:blood 0.40 1.407 1.34 1.407
Stomach:blood 0.46 0.274 1.51 0.274
Fat:blood 0.28 0.785 0.94 0.785 Rapidly perfused:blood 0.46 0.274 1.51 0.274 Slowly perfused:blood 0.35 1.853 1.16 1.853 Blood binding (h -1 ) Hb (k BC , k BC2 ) 1.245 ( 3.66) 1.134 ( 3.33) 1.245 ( 3.66) 1.134 ( 3.33) Blood sulfhydryls (k FBC , k FBC2 ) 2.54 0.68 0.0008 0.84
AN oxidation
V maxC (mg/h/kg 0.7 ) 5.0 ( 7.1 ) 15.6 ( 22.1 )
K m (mg/L) 1.5 ( 2.76 ) 0.8

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Table C-1. Rat and human PBPK model parameter valu es

Parameter Rat value a Human value a CEO hydrolysis
V maxcC2 (mg/h/kg 0.7 ) --- 841 (

--- )
K m2 (mg/L) --- 113 (

--- )
k EHC (L/h/kg 0.7 ) --- (3.92) --- ( 2.20 ) AN-GSH conjugation Enzymatic: k

FC (h/kg 0.3 ) -1 73 ( 50 ) 113 ( 77 ) Spontaneous: k SO (mmol/h) -1 0.2584 0.2584 CEO-GSH conjugation
Liver: k

FC2 (h/kg 0.3 ) -1 500 197 Brain/liver (k

FBRC /k FC2 ) 0.0234 0.0531 Stomach/liver (k FSTC /k FC2 ) 0.0538 0.0641 Rapidly perfused/liver (k FRC /k FC2 ) 0.0311 0.0460 Slowly perfused/liver (k FSC /k FC2 ) 0.00879 0.0201 Oral absorption: Ka (h -1 ) 8.0 (4.2 ) 8.0 (4.2 )

a Revised values used in this assessment are italiciz ed in parentheses.

Sources: Sweeney et al. (2003); Kedderis et al. (1 996).



### Estimation of Internal Doses Corresponding to Bioas say Exposures The model code from Sweeney et al. (2003) was modi fied to enable the explicit definition of desired daily oral intake of AN eithe r as a continuous infusion or in an episodic pattern of up to six episodes (or both continuous a nd episodic). The continuous-infusion oral exposure rate (STDOSE) is simply calculated as bein g equal to the total daily exposure (STEADYODOSE*BW, by continuous oral dosing) divided by 24 hours. The episodic exposure is calculated as the drinking water concentration ( DRCONC) times the standard drinking water volume (DRVOL, based on BW) times the ratio of actu al water consumption to standard consumption (FRACVOL) times the fraction of daily w ater consumed at episode “I” (DRP(I)), with that quantity added as a bolus to the GI lumen compartment at episode time “I” (DRT(I)). The first episodic exposure time is assumed to be T IME = 0, the same time at which a daily gavage dose (ODOSE*BW) is also administered. To simulate inhalation exposures as described in Q uast (1980b), the model was run to provide 6-hour continuous inhalation exposures, rep eating every 24 hours (by setting model variable TCHNG1 = 6.0) for 5 days/week (by setting model variable TCHNG2 = 120, the number of hours in 5 days). Inhalation simulations were run for 800 continuous simulated hours so that the effect of the 5 day/week exposures woul d be included in the calculation of average lifetime daily AUCs. Study-specific rat BWs were u sed. In this way the PBPK model accounted for the dynamics of concentration rise at the begin ning of each exposure and clearance at the end

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of each exposure. The resulting internal dose metr ics for inhalation exposure of the rat are listed
in Table 5-16.

Rat to Human Extrapolations
For inhalation and oral cancer and oral noncancer e ffects, similar approaches were used to extrapolate PODs from rats to humans. Following derivation of PODs for noncancer and cancer endpoints, as weekly average concentrations of AN and CEO in rat blood tissue (C I,tissue,rat 

### (BMCL 10 

### ) in mg/L), HECs were then calculated using the hum an PBPK model and a standard human BW of 70 kg, as the blood or brain c oncentration, assuming steady-state exposure for a set of predefined exposure levels an d that equal internal metrics in rats and humans are associated with the same degree of respo nse. The relationship between exposure level and internal metric as predicted by the human PBPK model was then plotted in Excel and a second-order polynomial of the form, HEC = a × C I 2 

### + b × C I 

### , where C I 

### is the internal dose metric, was fit to the relationship for each metric (blood and brain AN and CEO).

Inhalation Exposure The relationship between inhalation exposure level and internal metric as predicted by the human PBPK model is shown in Figures C-1 and C-2 fo r AN and CEO, respectively. This polynomial form gave an excellent fit and was fit o ver a range of concentrations that bracketed the range of C I,tissue,rat 

### (BMCL 10 

### ) for various cases. The resulting polynomials wer e then used to
convert the rat C I



### values to human equivalent exposures, reported in Chapter 5 for each toxicity
value.

### C-5 DRAFT - DO NOT CITE OR QUOTE AN dosimetry

0.1 1 10 100 1000

0.0001 0.001 0.01 0.1 1 10 100

Internal average / steady state concentration (mg/L )Inhalaion exposure (ppm)



### ACN blood ACN brain
AN blood fit
AN brain fit y = 38.6031·C + [4305.55·C/(26.6520+ C)]

y = 68.3045·C + [1162.47·C/(26.6520 + C)]



### Points are steady-state internal AN concentrations predicted by the human PBPK model for given inhalation exposure concentrations. Curves are polynomial regressions.

Figure C-1. Human inhalation exposure level vs. in ternal AN concentration.

### C-6 DRAFT - DO NOT CITE OR QUOTE y = 26.838x

2 

### + 503.27x
R 2 

### = 1 y = 41.103x

2 

### + 618.54x
R 2 

### = 1



### 0.1 1 10 100

0.0001 0.001 0.01 0.1 Internal average / steady state concentration (mg/L )Inhalaion exposure (ppm) 

### CEO blood CEO brain Poly. (CEO brain) Poly. (CEO blood)



### Points are steady-state internal CEO concentrations predicted by the human PBPK model for given inhalation exposure concentrations. Curves are polynomial regressions.

Figure C-2. Human inhalation exposure level vs. in ternal CEO concentrations.

Oral Cancer Risks For extrapolation of oral cancer risks from exposur e in drinking water, the exact pattern of ingestion of drinking water by the rats in the b ioassay was not measured and will be variable among humans. Therefore, the rat PBPK model was us ed to estimate the internal doses of AN and CEO at the exposure levels of the PODs as deter mined above (in mg/kg-day ingested), while assuming two distinct exposure patterns that are ex pected to bound the truth: continuous ingestion and ingestion in six boluses (“episodic”)

. The continuous pattern is simply described as conti nuous infusion to the stomach lumen compartment (i.e., 24 hours/day) at a rate equal to the total daily ingestion (at the BMDL 10 

### ). This pattern leads to the lowest predicted peak con centration of any possible pattern that would have the same total ingestion and, therefore, the l east saturation of metabolism. The episodic pattern assumes that rats consume their drinking wa ter in six boluses, spaced at 4-hour intervals during each day. The fraction of their total daily ingestion at each of these events is 23.3, 10, 10, 10, 23.3, and 23.4%, respectively. For continuous exposures, the steady-state blood and brain
concentrations of AN and CEO were calculated as int ernal dose metrics, while for the episodic pattern, the daily average concentrations were dete rmined.

### C-7 DRAFT - DO NOT CITE OR QUOTE

Stricker et al. (2003) measured water and food inta ke by Sprague-Dawley rats on diets containing normal (1%) and high (8%) levels of NaCl . On days 5 and 10 of control exposure,
the rats were observed to consume water in 15.9 ± 2 .0 and 19.3 ± 2.4 bouts, with amount consumed per bout being 2.1 ± 0.3 and 1.8 ± 0.3 mL, respectively. Thus, actual consumption by rats occurs in many more than six bouts, and the am ount consumed per bout is much more uniform than the episodic pattern. The data also s how that most of the consumption occurs during the 12-hour dark/waking period (represented by the first and final two boluses in the EPA's pattern), with much less consumed during the light/sleeping period (represented by the second to fourth boluses). Further, data on water consumption relative to controlled meal delivery showed that drinking bouts can last as lon g as 80 seconds, rather than occurring in an instantaneous bolus. Thus, actual consumption lies between an assumed continuous pattern and the idealized episodic pattern. Because episodic c onsumption will lead to model prediction of the greatest metabolic saturation, to obtain the de sired prediction that represents an upper bound of that behavior (including the possibility that wa ter consumption in the bioassays, which included F344 as well as Sprague-Dawley rats, may h ave differed from those observed by Stricker at al. [2003]), this idealized episodic pa ttern rather than one designed to more closely match that reported by Stricker et al. (2003) was c hosen. The results of the PBPK simulations for continuous oral infusion vs. an idealized episo dic ingestion pattern for various oral BMDL values differed by no more than 7%, indicating that for the rat internal dose metrics, the exact exposure pattern was not significant. To calculate the HEDs, similarly two alternate assu mptions of continuous and episodic exposure to the corresponding rat metrics were appl ied. For the episodic pattern, it was again
assumed that this occurred in six bolus doses but o ccurring at 0, 3, 5, 8, 11, and 15 hours computation time (i.e., from the time of first inge stion in the morning, assumed to occur at breakfast), with the amount consumed in each bolus being 25, 10, 25, 10, 25, and 5% of the total daily intake, respectively. As with the inhalation extrapolation, the human PBPK model was run using a range of fixed input dose rates (using both continuous and episodic regimens), the resulting internal doses calculated, and then an em pirical regression performed in Excel to interpolate between those doses. The resulting sim ulation values (points) and regressions (lines) are shown in Figures C-3 to C-6.

### C-8 DRAFT - DO NOT CITE OR QUOTE Continuous Exposure Model

0.01 0.1 1 10 100

0.00001 0.0001 0.001 0.01 0.1 1

Internal steady state concentration (mg/L)Oral exposure rate (mg/kg BW/day) AN blood fits ACN blood
AN brain fits ACN brain

y = 27.0624 ·C + [161.3074·C/(0.569868 + C)]

y = 35.6015 ·C + [138.101·C/(0.657976 + C)]



### Points are PBPK model predictions; curves are polyn omial regressions.

Figure C-3. Human oral exposure level vs. internal AN concentration for continuous exposure.

Continuous Exposure Model

y = 10.185x

2 + 98.2x
R 2 = 1

y = 6.7418x 2 + 79.895x
R 2 = 1

0.01 0.1 1 10 100

0.0001 0.001 0.01 0.1 1

Internal steady state concentration (mg/L)Oral exposure rate (mg/kg BW/day) CEO blood CEO brain Poly. (CEO blood) Poly. (CEO brain)



### Points are PBPK model predictions; curves are polyn omial regressions.

Figure C-4. Human oral exposure level vs. internal CEO concentration for continuous exposure.

### C-9 DRAFT - DO NOT CITE OR QUOTE Episodic Exposure Model -- AN

0.01 0.1 1 10 100

0.00001 0.0001 0.001 0.01 0.1 1 Internal average concentration (mg/L)Oral exposure rate (mg/kg BW/day) AN blood fit
AN blood AN brain fit
AN brain

y = 51.3757 ·C + [15.2250·C/(0.0586390 + C)]

y = 40.6491 ·C + [15.2251·C/(0.074113 + C)]



### Points are PBPK model predictions; curves are nonli near regressions.

Figure C-5. Human oral exposure level vs. internal AN concentration for episodic exposure.

Episodic Exposure Model -- CEO

y = 62.272x

2 + 98.857x
R 2 = 1 y = 41.22x 2 + 80.43x
R 2 = 1

0.01 0.1 1 10

0.0001 0.001 0.01 0.1 Internal average concentration (mg/L)Oral exposure rate (mg/kg BW/day) CEO blood CEO brain Poly. (CEO blood) Poly. (CEO brain)

s



### Points are PBPK model predictions; curves are polyn omial regressions.

Figure C-6. Human oral exposure level vs. internal CEO concentration for episodic exposure.

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## acslXtreme Model Source Code

PROGRAM ! ACRYLONITRILE and CYANOETHYLENE OXIDE MODEL w/ 1s t order epoxide hydrolase ! Model of ACN administration and CEO production! ! Revised model of G.L. Kedderis! ! Original by M.L. Gargas 10/9/89, revised 5/6/92! ! Revised 2/21/94 by G.L. Kedderis! ! Refined 6/28-7/12/95, 8/8/95 by G.L. Kedderis! ! Modified by SMH - 5/2/97! ! Modified for continuous oral dose by LMS 3/7/00! !pst2, pr2, and pb2 revised to Kedderis et al 1996 values! !periodic drinking water reinstated! !modified for revised human scaling by LMS 7/26/01! !built blood flow mass balance into equations LMS 7 /27/01! !built blood mass balance into equations, made bloo d binding! !rates equal in venous and arterial blood LMS 7/31/ 01! !modified to explicitly define DW conc. and daily A CN intake MHL 08/05! !statement added to calculate daily ACN intake (mg/ kg/day) ml 08/05! ! Modified 05/05/06 by Paul Schlosser and Allan Mar cus to include! ! Linear-range approximation to epoxide hydrolase m odel of ACN to CEO! !and to simplify the oral dosing calculations -- to avoid divide-by-zero! !errors and allow for either or both continuous and /or periodic exposure! ! June '06 - Jan '07: Other modifications by P. Sch losser to allow both !continuous and episodic drinking water dosing, and to update default !parameters for rat

INTEGER I !counter for drinking water arrays! REAL DRT(6), DRP(6) !store drink water times, perce nts in array! DIMENSION A0(16) !Set of zeros to force values to be >/= 0! CONSTANT A0 = 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0 CONSTANT QPC = 14. ! Alveolar ventilation rate (L /hr)! CONSTANT QCC = 14. ! Cardiac output (L/hr)! CONSTANT QLC = 0.25 ! Fractional blood flow to li ver! CONSTANT QFC = 0.09 ! Fractional blood flow to fa t! CONSTANT QBRC = 0.024 ! Fractional blood flow to brain! CONSTANT QSTC = 0.013 ! Fractional blood flow to the stomach! CONSTANT QSC = 0.15 ! Fractional blood flow to sl owly perfused tissue

CONSTANT BW = 0.523 ! Body weight (kg) male rat! CONSTANT VLC = 0.04 ! Fraction of liver tissue to total body! CONSTANT VRC = 0.0377 ! Fraction of richly perfus ed tissue to total! CONSTANT VSC = 0.75 ! Fraction of slowly perfused tissue to total! CONSTANT VBRC = 0.006 ! Fraction of brain tissue! CONSTANT VFC = 0.07 ! Fraction of fat tissue! CONSTANT VSTC = 0.0063! Fraction of stomach tissu e! CONSTANT BVC = 0.06 ! Fraction of blood volume! CONSTANT VVBC = 0.65 ! Fraction of venous blood v olume!

CONSTANT PBR = 0.40 ! AN brain/blood partition co efficient! CONSTANT PBR2 = 1.407 ! CEO brain/blood partition coefficient! CONSTANT PL = 0.46 ! AN liver/blood partition coe fficient! CONSTANT PL2 = 0.274 ! CEO liver/blood partition coefficient! CONSTANT PST = 0.46 ! AN stomach/blood partition coefficient! CONSTANT PST2 = 0.274 ! CEO stomach/blood partiti on coefficient! CONSTANT PF = 0.28 ! AN fat/blood partition coeff icient! CONSTANT PF2 = 0.785 ! CEO fat/blood partition co efficient! CONSTANT PS = 0.35 ! AN slowly perfused tissue/bl ood partition! CONSTANT PS2 = 1.853 ! CEO slowly perfused tissue /blood partition!

### C-11 DRAFT - DO NOT CITE OR QUOTE

CONSTANT PR = 0.46 ! AN rapidly perfused tissue/b lood partition! CONSTANT PR2 = 0.274 ! CEO rapidly perfused tissu e/blood partition! CONSTANT PB = 512 ! AN blood/air partition coeffi cient! CONSTANT PB2 = 1658 ! CEO blood/air partition coe fficient!

CONSTANT MW = 53.06 ! ACN molecular weight (g/mol )! CONSTANT MW2 = 69.05 ! CEO molecular weight (g/mo l)!

CONSTANT KEHC = 3.92 ! Effective 1st-order EH rat e, liter/hr/kg^0.7 CONSTANT VMAXC = 7.1 ! Maximum velocity of metabo lism (mg/hr-1kg)! CONSTANT VMAXC2 = 0.0 ! Maximum velocity of metab olism, CEO (mg/hr-1kg)! CONSTANT KM = 2.76 ! Michaelis-Menten constant (m g/L)! CONSTANT KM2 = 113. ! Michaelis-Menten constant, CEO (mg/L)! CONSTANT KFC = 50 ! ACN first order metabolism ra te const (/hr-1kg)! CONSTANT KFC2 = 500 ! CEO first order metabolism rate const (/hr-1kg)! CONSTANT KSO = 0.2584 ! ACN second order reaction with GSH (L/mMol/hr)!

CONSTANT GSHL = 8.53 ! Liver GSH conc (mMol/L)! CONSTANT GSHBR = 2. ! Brain GSH (mMol/L)! CONSTANT GSHST = 4.59 ! Stomach GSH (mMol/L)! CONSTANT GSHS = 0.75 ! Slowly perfused (muscle) G SH (mMol/L)! CONSTANT GSHR = 2.65 ! Rapidly perfused GSH (mMol /L)!

CONSTANT KBC = 3.66 ! ACN 1ST order binding to bl ood hb (/hr)! CONSTANT KBC2 = 3.33 ! CEO 1ST order binding to b lood hb (/hr)! CONSTANT KFBC = 2.54 ! ACN 1ST order binding to b lood RSH (/hr)! CONSTANT KFBC2 = 0.68 ! CEO 1ST order binding to blood RSH (/hr)! CONSTANT KA = 4.2 ! Oral uptake rate (/hr)!

CONSTANT IVDOSE = 0. ! IV dose (mg/kg)! CONSTANT CONC = 0. ! Inhaled concentration (ppm) ACN! CONSTANT CONC2 = 0. ! Inhaled concentration (ppm) CEO! CONSTANT ODOSE= 0. ! Oral dose in mg/kg-day, assu med given at t=0, 24, etc.

! Timing commands! CONSTANT TCHNG1 = 24.0 ! Length of exposure (hrs) ! CONSTANT TCHNG2 = 120.0 ! Allows for 5 day/week e xposure! CONSTANT TINF = .003 ! Length of IV infusion (hr s)!

CONSTANT STEADYODOSE = 0 !daily dose mg/kg-day, if assuming continuous oral infusion

!periodic drinking water section! CONSTANT DRCONC=0.0 ! Conc. of ACN in drinking water (mg/L) CONSTANT DRT=0,2,4,6,8,10 ! Times for multiple oral drinks/day *after* 0 ! Must be ascending, 0 <= times < 24 hr ! DRTIME(1) assumed = 0 and not used CONSTANT DRP=1,0,0,0,0,0 !Percent consumed by drink ing at those times ! Bolus of ODOSE*BW + DRPCT(1)*DRDOSE will be give n at t=0,24,48, etc. CONSTANT FRACVOL = 1.0 ! Actual daily water consumption / nominal or cont rol volume ! used when calculating DRDOSE

INITIAL DRVOL = 0.102*BW**0.7 ! Water consumption (L/d) ! 2L/d water consumption for a 70kg human DRDOSE = DRCONC*DRVOL*FRACVOL DAYDOSE = ODOSE*BW + DRP(1)*DRDOSE ! Once daily oral dose; given at t=0 via initial condition

### C-12 DRAFT - DO NOT CITE OR QUOTE

STDOSE = STEADYODOSE*BW/24 ! Steady oral dosing ra te in mg/hr IVR = IVDOSE*BW/TINF NEWDAY = 0; I = 2 ! First dose given as initial co ndition

SCHEDULE ORALDOSE.AT.DRT(2)

! Scaled parameters!

QC = QCC*BW**0.74 QP = QPC*BW**0.74 QL = QLC*QC QF = QFC*QC QBR = QBRC*QC QST = QSTC*QC QS = QSC*QC QR = QC-QL-QF-QBR-QS-QST VL = VLC*BW VF = VFC*BW VBR = VBRC*BW VST = VSTC*BW VS = VSC*BW VR = VRC*BW BV = BVC*BW VAB = BV*(1-VVBC) !volume arterial bloo d! VVB = BV*VVBC GSHRB = GSHBR/GSHL !ratio of brain GSH t o liver GSH! GSHRST = GSHST/GSHL !ratio of stomach GSH to liver GSH! GSHRS = GSHS/GSHL !ratio of slowly perf used GSH to liver GSH! GSHRR = GSHR/GSHL !ratio of richly perf used GSH to liver GSH! VMAX = VMAXC*BW**0.7 ! Liver P450 ACN to C EO! VMAX2 = VMAXC2*BW**0.7 ! Liver CEO Hydrolysi s! KF = KFC/BW**0.3 ! Liver ACN-GSH rate! KF2 = KFC2/BW**0.3 ! Liver CEO-GSH/RSH rate! KEH = KEHC*BW**0.7 ! Approx. first-order rate in liver! KFBRC = KFC2*.1*GSHRB ! CEO brain reaction - 10% GSH ratio! KFSTC = KFC2*.1*GSHRST ! CEO stomach reactio n - 10% GSH ratio! KFSC = KFC2*.1*GSHRS ! CEO slowly perfused reaction - 10% GSH ratio! KFRC = KFC2*.1*GSHRR ! CEO richly perfused reaction - 10% GSH ratio! KFBR = KFBRC/BW**.3 ! CEO brain RSH rate! KFST = KFSTC/BW**.3 ! CEO stomach RSH rat e! KFS = KFSC/BW**.3 ! CEO SPT RSH rate! KFR = KFRC/BW**.3 ! CEO RPT RSH rate! KFB = KFBC KFB2 = KFBC2 KB = KBC KB2 = KBC2

DAILYDOSE = ODOSE+STEADYODOSE+(DRDOSE/BW)+(AI/BW/(T STOP/24)) !daily dose mg/kg-day via oral and/or inhalation r outes!

END !of INITIAL

DYNAMIC ALGORITHM IALG = 2 !Gear method for stiff systems! MAXTERVAL MAXT = 1.0e-3 MINTERVAL MINT = 1.0e-9 CINTERVAL CINT = 0.5

DERIVATIVE

### C-13 DRAFT - DO NOT CITE OR QUOTE

!-----------------------------------! !--------- ACRYLONITRILE ---------! !-----------------------------------!

! CI = Concentration in inhaled air (mg/L)! CIZONE = PULSE(0.0,24.0,TCHNG1) * PULSE(0.0,168. 0,TCHNG2) CI = CIZONE*CONC*MW/24450.

! AI = Amount inhaled (mg)! RAI = QP*CI AI = INTEG(RAI,0)

! MR = Amount in stomach lumen (mg)! RMR = STDOSE - KA*MR AMR = INTEG(RMR,DAYDOSE) MR = MAX(AMR, A0(1)) !no negative values!

! CAL = Concentration in arterial lung blood ( mg/L)! CAL = (QC*CVB+QP*CI)/(QC+(QP/PB))

! CA = Conc. in systemic arterial blood (mg/l )! RAB = QC*(CAL-CA)-(KB+KFB)*AB AB = INTEG(RAB,A0(2)) CA = AB/VAB

! AX = Amount exhaled (mg)! CX = CAL/PB CXPPM = (0.7*CX+0.3*CI)*24450./MW RAX = QP*CX AX = INTEG(RAX,A0(3))

! AST = Amount in stomach tissue (mg)! RAST = QST*(CA-CVST) - STGSH + KA*MR AST = INTEG(RAST,A0(4)) CVST = AST/(VST*PST) CST = AST/VST STGSH = KSO*CVST*GSHST*VST ASTG = INTEG(STGSH,A0(5))

! AS = Amount in slowly perfused tissues (mg) ! RAS = QS*(CA-CVS) - SGSH AS = INTEG(RAS,A0(6)) CVS = AS/(VS*PS) CS = AS/VS SGSH = KSO*CVS*GSHS*VS ASG = INTEG(SGSH,A0(7))

! AR = Amount in rapidly perfused tissues (mg )! RAR = QR*(CA-CVR) - RGSH AR = INTEG(RAR,A0(8)) CVR = AR/(VR*PR) CR = AR/VR RGSH = KSO*CVR*GSHR*VR ARG = INTEG(RGSH,A0(9))

! AF = Amount in fat tissue (mg)! RAF = QF*(CA-CVF) AF = INTEG(RAF,A0(10)) CVF = AF/(VF*PF) CF = AF/VF

### C-14 DRAFT - DO NOT CITE OR QUOTE

! ABR = Amount in brain tissue (mg)! RABR = QBR*(CA-CVBR) - BRGSH ABR = INTEG(RABR,A0(11)) CVBR = ABR/(VBR*PBR) CBR = ABR/VBR BRGSH = KSO*CVBR*GSHBR*VBR ABRG = INTEG(BRGSH,A0(12))

! AL = Amount in liver tissue (mg) RAL = QL*CA + QST*CVST - (QL+QST)*CVL - RAM1 - RAM2 - LGSH AL = INTEG(RAL,A0(13)) CVL = AL/(VL*PL) CL = AL/VL AUCL = INTEG(CL,0.) LGSH = KSO*CVL*GSHL*VL ALG = INTEG((LGSH+RAM2+(KB*CVB*VVB)+(KFB*CVB* VVB)),A0(14))

! AM1 = Amount metabolized, saturable (P450) a nd linear pathways (mg)! RAM1 = VMAX*CVL/(KM+CVL) RAM1M = RAM1*1000/MW AM1 = INTEG(RAM1,A0(15))

! AM2 = Amount metabolized, first-order pathwa y (GST) (mg)! RAM2 = KF*CVL*VL AM2 = INTEG(RAM2,0)

! CV = Mixed venous blood concentration (mg/L )! IV = IVR*(T<=TINF) ! PULSE(0,24,TINF) CV = (QF*CVF + (QL+QST)*CVL + QS*CVS + QR*CV R + QBR*CVBR + IV)/QC

! CVB = Mixed venous ACN conc. after binding (mg/L)! RVB = QC*(CV-CVB) - (KB+KFB)*VB VB = INTEG(RVB,A0(16)) CVB = VB/VVB

! TMASS = mass balance (mg)! TMASS = ABR+AF+AL+AS+AR+AST+AM1+AM2+AX+MR+ASTG+ ASG+ARG+ABRG+ALG

!----------------------------------------! !----------------- CEO ----------------! !----------------------------------------!

! CI2 = Concentration in inhaled air (mg/L)! CI2 = CIZONE*CONC2*MW2/24450.

! CAL2 = Concentration in arterial lung blood (mg/L)! CAL2 = (QC*CVB2+QP*CI2)/(QC+(QP/PB2))

! CA2 = Conc. in systemic arterial blood (mg /l)! RAB2 = QC*(CAL2-CA2)-(KB2+KFB2)*AB2 AB2 = INTEG(RAB2,0.) CA2 = AB2/VAB

! AS2 = Amount in slowly perfused tissues (mg )! RAS2 = QS*(CA2-CVS2) - KFS*CVS2*VS AS2 = INTEG(RAS2,0.) CVS2 = AS2/(VS*PS2) CS2 = AS2/VS

### C-15 DRAFT - DO NOT CITE OR QUOTE

! AR2 = Amount in rapidly perfused tissues (m g)! RAR2 = QR*(CA2-CVR2) - KFR*CVR2*VR AR2 = INTEG(RAR2,0.) CVR2 = AR2/(VR*PR2) CR2 = AR2/VR

! AST2 = Amount in stomach (mg)! RAST2 = QST*(CA2-CVST2) - KFST*CVST2*VST AST2 = INTEG(RAST2,0.) CVST2 = AST2/(VST*PST2) CST2 = AST2/VST

! AF2 = Amount in fat tissue (mg)! RAF2 = QF*(CA2-CVF2) AF2 = INTEG(RAF2,0.) CVF2 = AF2/(VF*PF2) CF2 = AF2/VF

! ABR2 = Amount in brain tissue (mg)! RABR2 = QBR*(CA2-CVBR2) - KFBR*CVBR2*VBR ABR2 = INTEG(RABR2,0.) CVBR2 = ABR2/(VBR*PBR2) CBR2 = ABR2/VBR

! CEO Hydrolysis! ! VMAX2 = maximum velocity of metabolism (mg/ hr-1kg)! ! KM2 = Michaelis-Menten constant (mg/L)! ! KEH is parameter for linear metabolism in l iver to replace saturable ! AL2 = Amount CEO in liver tissue (mg)! RAM = RAM1M*MW2/1000. RAL2ADD = QL*CA2 + QST*CVST2 + RAM RAL2M = VMAX2*CVL2/(KM2+CVL2) + KEH*CVL2 RAL2 = RAL2ADD - (QL+QST)*CVL2 - KF2*CVL2*VL - RAL2M AL2 = INTEG(RAL2,0.) CVL2 = AL2/(VL*PL2) CL2 = AL2/VL

! CV2 = Mixed venous blood concentration (mg/ L)! CV2 = (QF*CVF2 + (QL+QST)*CVL2 + QS*CVS2 + QR*CVR2 + QBR*CVBR2)/QC

! CVB2 = Mixed venous CEO conc. after binding ! RVB2 = QC*(CV2-CVB2) - (KB2+KFB2)*VB2 VB2 = INTEG(RVB2,0.) CVB2 = VB2/VVB

! Calculation of the AUC for ACN and CEO in th e brain and blood! AUCBR = INTEG(CBR,0.) ! AUC for ACN brain conc.! AUCBR2 = INTEG(CBR2,0.) ! AUC for CEO brain conc. ! AUCB = INTEG(CVB,0.) ! AUC for ACN blood conc.! AUCB2 = INTEG(CVB2,0.) ! AUC for CEO blood conc. ! DAILYSTAUC = INTEG(CST,0.)/(TSTOP/24) !Mean daily stomach AN DAILYST2AUC = INTEG(CST2,0.)/(TSTOP/24) !Mean dai ly stomach CEO

END ! Derivative ! Code that is executed once at each communication interval goes here CONSTANT TSTOP = 24.0 ! Length of experiment ( hrs)! TERMT(T.GE.TSTOP, 'checked on communication interva l: REACHED TSTOP')

DISCRETE ORALDOSE IF (I.EQ.1) THEN

### C-16 DRAFT - DO NOT CITE OR QUOTE

AMR = AMR + DAYDOSE ! Initial dose of day/daily dose ELSE AMR = AMR + DRP(I)*DRDOSE ! Drinking percent
END IF I = MOD((I+1),6) IF (I.EQ.1) THEN SCHEDULE ORALDOSE.AT.NEWDAY ! Go to start of t he next day NEWDAY = NEWDAY + 24 ELSE SCHEDULE ORALDOSE.AT.(NEWDAY+DRT(I)) ! Go to n ext drink time
END IF

END ! DISCRETE ORALDOSE

END ! Dynamic

TERMINAL ! Metrics calculated below! DAILYBRAUC = AUCBR/(TSTOP/24) ! Mean daily stomac h ACN DAILYBR2AUC = AUCBR2/(TSTOP/24) ! Mean daily stoma ch CEO DAILYBAUC = AUCB/(TSTOP/24) ! Mean daily blood ACN DAILYB2AUC = AUCB2/(TSTOP/24) ! Mean daily blood CEO

PEAKPBR = MAX(0, CBR) ! Peak conc. parent compou nd in brain! PEAKPB = MAX(0, CV) ! Peak conc. parent compound in blood! PEAKMBR = MAX(0, CBR2) ! Peak conc. metabolite in brain! PEAKMB = MAX(0, CV2) ! Peak conc. metabolite in b lood!

! Calc. of the avg. values of ACN and CEO in the b rain and blood! AVEBR = AUCBR/TSTOP ! Average of ACN brain conc.! AVEBR2 = AUCBR2/TSTOP ! Average of CEO brain conc. ! AVEB = AUCB/TSTOP ! Average of ACN blood conc.! AVEB2 = AUCB2/TSTOP ! Average of CEO blood conc.!

END ! TERMINAL

END ! PROGRAM

### C-17 DRAFT - DO NOT CITE OR QUOTE 

## Matlab source code – 3 programs (.m files)

% ACN / CEO PBPK model optimization file % % Main program, or SHELL for PBPK model. % % P = optACN2(pin, pvn, datfilena me, switch) % % swtch = optimization choice (see below) % pin = values of *all* parameters (input) % pvn = cell-vector of parameter names TO BE VARIED % datfilename = name of data file (.csv) to use % P = values of the output parameters (optimized) % % where pin is the vector of paramters to input and swtch determines whether % to run the simulation (swtch = 0), or to optimiz e (swtch = 1 neld2 search). % % pvn = {'name1' ; 'name2' ; ... } Note: use curly brackets and semi-colons

%--------------------------------------------------

--------------------------

- function P = optACN(pin,pvn,dfn,sw) format long %-----------------------------------globalize data sets----------------------

- global quan phys prs Ypt pv yname itr datfile pvar pbl j1 jf ncv tsp pex global ICs Ccafpt Ccafc nv Cost C0 ps MW MW2 nv %-------------------load dat set------------------- -- quan.dat=load([dfn,'.csv']); swtch=sw; %close all % The sequence of columns in the data sets are as f ollows: % tspan, CVB, CL, CBR, CVB2, CL2, CBR2, ODOSE(initi al), IVDOSE(initial) ... % % AN-GSH in urine, % CEO-GSH in urine, % Hb-bou nd material yname={'CVB';'CL';'CBR';'CVB2';'CL2';'CBR2';'AGSHU' ;'CGSHU';'PBH';'MassBal'}; ncv=32; %--------------------------find indeces of paramete rs to be varied-----------

- pname={'VmaxC';'Km';'VmaxC2';'Km2';'kEHC';'kFC';'kF C2';'kA';'gammA';'gammC';' kH';'kH2'}; %prs = [5.0; 1; 1.e-18; 113.; 3.9; 73.; 500 .; 8.; 1; 1]; %prs = [3.27;.000425; 1.e-18; 113.; 3.9; 95.7; 5 00.; 8.; .0107; 1]; prs = [.102; 2.76; 1.e-18; 113.; 0.98; 82.3; 14. 1; 4.94; .0107; 0.941; 1.245; 1.134]; prs = [2.24; 2.76; 1.e-18; 113.; 0.98; 82.3; 14. 1; 4.94; .0107; 0.941; 1.245; 1.134]; %prs = [1.86; 1.5; 1.e-18; 113.; 3.9; 15.7; 2240.; 8.; .425; 1.10]; %those above are default values pbl={', ';', ';', ';', ';', ';', ';', ';', ';', ';' , ';', ';', '}; % KEHC = %Effective 1st-order EH rate, liter/hr /kg^0.7 % VMAXC = %Maximum velocity of metabolism (mg/h r-1kg)% % VMAXC2 = %Max. vel. of metabolism, CEO (mg/hr-1k g)% % KM = %Michaelis-Menten constant (mg/L)% % KM2 = %Michaelis-Menten constant, CEO (mg/L)% % KFC = %ACN first order metab rate const (/hr -1kg)% % KFC2 = %CEO first order metab rate const (/hr- 1kg)% % KA = %Oral uptake rate (/hr)%

### C-18 DRAFT - DO NOT CITE OR QUOTE

fname='EqACN'; % file with set of model equations to use is fname.m runfn='RunACN'; % Run file runfn.m quan.ns = length(pname); pv = 1:quan.ns; pvar = pna me; if length(pin)>quan.ns error('input parameter vector is too long') end if sum(pin) % if pin =[], then no optimization, use default params popt=reshape(log(pin),length(pin),1); if strmatch('all',pvn,'exact') if length(pin)~=quan.ns error('length of pin is wrong; must be ',num2str(quan.ns),' to match pvn = all') end prs=pin; else pvar = pvn; quan.ns = length(pvn); pv = zeros(1,quan.ns); if (length(pin)~=quan.ns)&(length(pin)~=len gth(pname)) error(['Length of pin is wrong; must be ',num2str(quan.ns),... ' to match pvn or ',num2str(length( pname)),' to match pname.']) else for i = 1:quan.ns if strmatch(pvn(i),pname,'exact') pv(i) = strmatch(pvn(i),pname,' exact'); else error([char(pvn{i}),' is not in the named list of parameters.']) end end end if length(pin)==length(pname) prs=pin; popt=popt(pv); end end else popt=log(prs); swtch=0; 'No pin so running simu lation only with default params.' end

save pv pv %--------------------------find indeces of start ti mes---------------- quan.t = quan.dat(:,1); tci = (quan.t > 0); datc=quan.dat(:,[2:7,12:14]); % data columns used for fitting nv = size(datc,2); % number of variables to plot, etc Ccafc=zeros(length(quan.t),(nv+1)); nplt=0; for i=1:6 quan.ic{i} = find((datc(:,i)>0) & tci); quan.datc{i} = datc(quan.ic{i},i); if quan.datc{i} nplt=nplt+1; end quan.tc{i} = quan.t(quan.ic{i}); quan.nc(i) = sum((datc(:,i)>0) & tci); end nplt2=0; for i=7:nv

### C-19 DRAFT - DO NOT CITE OR QUOTE

quan.ic{i} = find((datc(:,i)>0) & tci); quan.datc{i} = datc(quan.ic{i},i); if quan.datc{i} nplt2=nplt2+1; end quan.tc{i} = quan.t(quan.ic{i}); quan.nc(i) = sum((datc(:,i)>0) & tci); end

C0=sum(quan.nc)*(log(2*pi)+1); quan.mc=datc>0; sz=length(quan.t); quan.yc=0*[datc,datc(:,1)]; quan.jt = find(quan.t == 0); % jt = vector of indeces of rows in data file start ing with "0" quan.idf= length(quan.jt); quan.jt = [quan.jt;(sz+1)]; % add a pseudo-index to mark the end of the data fi le %------------------------constant parameters------- --------------------- ps.KSO = 0.2584; %ACN second order rxn with GSH (L /mMol/hr)% ps.GSHL = 8.53; %Liver GSH conc (mMol/L)% ps.GSHBR = 2.; %Brain GSH (mMol/L)% ps.GSHST = 4.59; %Stomach GSH (mMol/L)% ps.GSHS = 0.75; %Slowly perfused (muscle) GSH (mM ol/L)% ps.GSHR = 2.65; %Rapidly perfused GSH (mMol/L)%

%ps.KB = 1.245 + 2.54; %ACN 1ST order binding t o blood hb + RSH (/hr)% ps.KB0 = 2.54; %ACN 1ST order binding to blood hb + RSH (/hr)% ps.KB0 %ps.KH = 1.245; ps.KFB = 2.54; %ps.KB2 = 1.134 + 0.68 + 0.413; ps.KB20 = 0.68 + 0.413; %ps.KH2 = 1.134; phys.KHR = 1.134/1.245; ps.KFB2 = 0.68; %CEO 1ST order binding to blood hb + RSH + chem . hydrol. (/hr)%

ps.tinf=.003; %blood infusion time (hr) % ACN PCs phys.PL = 0.46; % liver:blood PC phys.PST = 0.46; % stomach tissue:blood PC, also used for GI phys.PBR = 0.40; % brain tissue:blood PC phys.PF = 0.28; % fat tissue:blood PC phys.PS = 0.35; % slowly tissue:blood PC phys.PR = 0.46; % richly tissue:blodd PC phys.PB = 512; % blood tissue:blodd PC

%CEO PCs phys.PL2 = 0.274; % liver:blood PC phys.PST2 = 0.274; % stomach tissue:blood PC, al so used for GI phys.PBR2 = 1.407; % brain tissue:blood PC phys.PF2 = 0.785; % fat tissue:blood PC phys.PS2 = 1.853; % slowly tissue:blood PC phys.PR2 = 0.274; % richly tissue:blodd PC phys.PB2 = 1658; % blood tissue:blodd PC

QPC = 14.; %Alveolar ventilation rate (L/hr)% QCC = 14.; %Cardiac output (L/hr)%

### C-20 DRAFT - DO NOT CITE OR QUOTE

QBRC = 0.024; % blood flow to brain QSTC = 0.013; % Blood flow rate for stomach tissu e (portal vein) QFC = 0.09; % blood flow to fat tissue QLC = 0.25; % Blood flow rate for liver ) QSC = 0.15; % Blood flow rate for slowly

phys.BW=0.25; %body weight VLC = 0.04; %Fraction of liver tissue to total body% VRC = 0.0377; %Fraction of richly perf tiss to to tal% VSC = 0.75; %Fraction of sloly perf tiss to tot al% VBRC = 0.006; %Fraction of brain tissue% VFC = 0.07; %Fraction of fat tissue% VSTC = 0.0063; %Fraction of stomach tissue% BV = 0.06*phys.BW; %Blood vol% VVBC = 0.65; %Fraction of venous blood vol%

MW = 53.06; %ACN molecular weight (g/mol)% MW2 = 69.05; %CEO molecular weight (g/mol)%

%---------------- preset varying parameters ------- -------------------- phys.QC = QCC*phys.BW^0.74; phys.QP = QPC*phys.BW^0.74; phys.QBR = QBRC*phys.QC; % blood flow to brain phys.QST = QSTC*phys.QC; % Blood flow rate for s tomach tissue (portal vein) phys.QS = QSC*phys.QC; % Blood flow rate for slowl y phys.QL = QLC*phys.QC; % Blood flow rate for liver (hepatic artery) phys.QF = QFC*phys.QC; % blood flow to fat phys.QR = phys.QC-phys.QL-phys.QF-phys.QBR-phys.QS- phys.QST; phys.VBR = VBRC*phys.BW; % brain volume (L) phys.VST = VSTC*phys.BW; % GI volume (use RP de nsity) phys.VL = VLC*phys.BW; phys.VF = VFC*phys.BW; phys.VBR = VBRC*phys.BW; phys.VST = VSTC*phys.BW; phys.VS = VSC*phys.BW; phys.VR = VRC*phys.BW; phys.VAB = BV*(1-VVBC); %volume arterial bloo d% phys.VVB = BV*VVBC; phys.GSHRB = 0.1*ps.GSHBR/ps.GSHL; %ratio of bra in GSH*GST to liver GSH% phys.GSHRST = 0.1*ps.GSHST/ps.GSHL; %ratio of sto mach GSH*GST to liver GSH% phys.GSHRS = 0.1*ps.GSHS/ps.GSHL; %ratio of spt GSH*GST to liver GSH% phys.GSHRR = 0.1*ps.GSHR/ps.GSHL %ratio of rpt GSH*GST to liver GSH%

ICs=[]; for i=1:quan.idf % idf is the number of simulation s/initial conditions in j1(i) = quan.jt(i); % index of initial data row for this experiment/simulation jf(i) = quan.jt(i+1)-1; % index of final data r ow for this expt./simulation tsp{i} = quan.t(j1(i):jf(i)); oral0=quan.dat(j1(i),8)*phys.BW; ps.blood0(i)=quan.dat(j1(i),9)*phys.BW/ps.tinf; ps.cinh(i)=quan.dat(j1(i),10)*MW/24450; ps.tinh (i)=quan.dat(j1(i),11); ICs=[ICs;[oral0,zeros(1,ncv-1)]]; % initial con ditions end save ICs ICs

%----------call simulation or optimization procedur e------------------

### C-21 DRAFT - DO NOT CITE OR QUOTE

quan.pt=0; itr=0; P=prs; if swtch==0 quan.pt=1; y=eval([runfn,'(popt)']); elseif swtch==1 pnew = exp(neld2(popt, runfn, 1e-6, 1000, 50000 )); else options = optimset('MaxFunEvals',8000,'MaxIter', 8000); pnew = exp(fminsearch(runfn,popt,options)); end

if swtch>0 P(pv) = pnew(1:quan.ns); 'Initial Parameter Values, Jinit =' Cst=eval([runfn,'(popt)']); 'Final Parameters, Jopt =' quan.pt=1; Cst=eval([runfn,'(log(P(pv)))']); end

%----------------- final results/plots ------------ -------
co = ['rbkgmcrbkgmcrbkgmcrbkgmcrbkgmcrbkgmcrbkgmcrbkgmcr bkgmcrbkgmcrbkgmcrbkgmcrbk gmcrbkgmcrbkgmcrbkgmc']; %co = ['kkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkk '];
pc = ['+o*xsd^v<>ph+o*xsd^v<>ph+o*xsd^v<>ph+o*xsd^v<>ph+ o*xsd^v<>ph+o*xsd^v<>ph+o* xsd^v<>ph+o*xsd^v<>ph']; linet = ['- ';'--';': ';'-.';'- ';'--';': ';'-.';'- ';'--';': ';'-.';... '- ';'--';': ';'-.';'- ';'--';': ';'-.';'- ';'- -';': ';'-.';... '- ';'--';': ';'-.';'- ';'--';': ';'-.';'- ';'- -';': ';'-.';... '- ';'--';': ';'-.';'- ';'--';': ';'-.';'- ';'- -';': ';'-.';... '- ';'--';': ';'-.';'- ';'--';': ';'-.';'- ';'- -';': ';'-.';... '- ';'--';': ';'-.';'- ';'--';': ';'-.';'- ';'- -';': ';'-.';... '- ';'--';': ';'-.';'- ';'--';': ';'-.';'- ';'- -';': ';'-.';... '- ';'--';': ';'-.';'- ';'--';': ';'-.';'- ';'- -';': ';'-.']; np=min(quan.idf,96); quan.jtp = [find(quan.tp == 0);(length(quan.tp)+1)] ; % jt = vector of indeces of rows in data file start ing with "0"; plus one %close all kf0=30; kf=1+kf0; figure(kf) rows=ceil(nplt/2); set(kf,'Units','inches','Position',[0.1, 0.5, 6.3, (0.1+2.5*rows)]); set(gcf,'DefaultTextFontSize',10,'DefaultAxesFontSi ze',12,'DefaultTextFontNam e','Arial'); npt = -1; for k = 1:6 if quan.datc{k} npt=npt+2; pos=mod(npt,(rows*2))+(npt>(rows*2)); h=subplot(rows,2,pos); set(h,'Units','inches','Position',[(3.5- 2.95*mod(pos,2)),(0.45+2.35*(rows-ceil(pos/2))),2.7 ,2.1]) box on j1=quan.jt(1); j2=quan.jt(2)-1; p1=quan.jtp(1); p2=quan.jtp(2)-1;

### C-22 DRAFT - DO NOT CITE OR QUOTE

dt=quan.t(j1:j2); dp = datc(j1:j2,k); dj = find(dp > 0); dk=find(datc(:,k)>0); xm=ceil(1.01*max(quan.t( dk ))*10)/10; xl=floor(0.99*min(quan.t( dk )*10)-1)/10; if xl<0 xl = - round(2.5*xm)/100; end ym=max(log10(1.1*[Ccafpt(find(Ccafpt(:,k)>0) ,k);datc(dk,k)])); if (10^ceil(ym))/(10^ym) > 2 ym = (10^ceil(ym))/2; else ym = 10^ceil(ym); end set(gca,'YScale','log') if k==1 axis([xl,xm,.03,ym]) end if k==2 axis([xl,xm,.01,ym]) end if k==3 axis([xl,xm,.01,ym]) end if k==4 axis([xl,xm,.001,ym]) end if k==5 axis([xl,xm,.001,ym]) end if k==6 axis([xl,xm,.001,ym]) end hold on if dj plot(dt(dj),dp(dj),['k',pc(1)]); %,[co(1 ),pc(1)]) plot(quan.tp(p1:p2),Ccafpt(p1:p2,k),['k' ,linet(1,:)]); %[co(1),linet(1,:)]); end if np > 1 for i = 2:np j1=quan.jt(i); j2=quan.jt(i+1)-1; dt=quan.t(j1:j2); p1=quan.jtp(i); p2=quan.jtp(i+1)-1; dp = datc(j1:j2,k); dj = find(dp > 0); if dj plot(dt(dj),dp(dj),['k',pc(i)]); %,[co(1),pc(1)]) plot(quan.tp(p1:p2),Ccafpt(p1:p2 ,k),['k',linet(i,:)]); %[co(1),linet(1,:)]); end end end yl=0.1*get(gca,'YLim'); title(yname(k),'Position',[mean(get(gca,'XLi m')),yl(2)],'FontSize',14,

... 'EdgeColor','k','BackgroundColor','w','F ontname','Arial');

### C-23 DRAFT - DO NOT CITE OR QUOTE

if k==2 legend('show') end hold off end end

kf=2+kf0; if quan.datc{7} figure(kf); set(kf,'Units','inches','Position',[0.1, 0.5, 3 .3, 7.6]);

set(gcf,'DefaultTextFontSize',14,'DefaultAxesFontSi ze',12,'DefaultTextFontNam e','Arial'); for k = 7:9 h=subplot(3,1,k-6); set(h,'Units','inches','Position',[.55,(0.45 +2.35*(9-k)),2.7,2.1]) box on; hold on dk=find(datc(:,k)>0); plot(quan.dat(dk-1,8),datc(dk,k),['k',pc(k-6 )]); %,[co(1),pc(1)]) plot(quan.dat(dk-1,8),Ccafc(dk,k),['k',linet (k-6,:)]); %[co(1),linet(1,:)]); yl=0.3*get(gca,'YLim'); title(yname(k),'Position',[mean(get(gca,'XLi m')),yl(2)],'FontSize',14,

... 'EdgeColor','k','BackgroundColor','w','F ontname','Arial'); hold off end end

k=nv+1; % show mass balance figure(k) set(k,'Units','inches','Position',[1,1,4.1,4.1]); hold on title(yname(k)); p1=quan.jtp(1); p2=quan.jtp(2)-1; plot(quan.tp(p1:p2),Ccafpt(p1:p2,k),[co(1),linet(1, :)]); for i = 2:np p1=quan.jtp(i); p2=quan.jtp(i+1)-1; plot(quan.tp(p1:p2),Ccafpt(p1:p2,k),[co(i),line t(i,:)]); end

if swtch>0 'optimized params = ' [num2str([1:length(P)]'),char(pbl),char(pname),char (pbl),num2str(P)] end

%RunACN file to return value of objective function, given input parameters function Cost = RunACN(popt) %----------------------------globals---------------

--------- global phys prs yname quan itr pv pvar pbl j1 jf ia n ICs ncv tsp Ccafpt C0 global Cost Ccafc MW MW2 VMAX VMAX2 KF KF2 KEH KFBR C KFSTC KFSC KFRC KFBR global KFST KFS KFR KA KM KM2 Ccafpt nv ps tol=1.e-8; options = odeset('RelTol',tol,'AbsTol',tol); itr=itr+1;

### C-24 DRAFT - DO NOT CITE OR QUOTE

comp=0; p = reshape(exp(popt),length(popt),1); pu=prs; pu(pv)=p; save ptemp pu [num2str(pv'),char(pbl(pv)),char(pvar),char(pbl(pv) ),num2str(p)] %quan.gam(1:5)=2./exp(exp(-popt((quan.ns+1):(quan.n s+5)) )); %quan.gam(6:11)=quan.gam(5); %quan.gam(1:5) % display current values of parameters being valued (retransformed) Ccafpt=[];Ccafw=[]; quan.tp=[]; comp=comp+1;

VMAXC = pu(1); %Max. vel. of metabolism, CEO (mg/hr -kg^0.7)% KM = pu(2); %Michaelis-Menten constant (mg/L)% VMAXC2=pu(3); %Max. vel of metabolism, CEO (mg/hr -jg^0.7) KM2=pu(4); %CEO M-M constant (mg/L) KEHC = pu(5); %Effective 1st-order EH rate, liter /hr/kg^0.7 KFC = pu(6); %ACN first order metab rate const ( /hr-1kg)% KFC2 = pu(7); %CEO first order metab rate const ( /hr-1kg)% KA = pu(8); %Oral uptake rate (/hr)% gA = min(pu(9),2); % gammA gC = min(pu(10),2); % gammC ps.KH = pu(11); ps.KHR2 = pu(12); ps.KB = ps.KH + ps.KB0; %ACN 1ST order binding to blood hb + RSH (/hr)% ps.KH2 = ps.KH*phys.KHR*ps.KHR2; ps.KB2 = ps.KH2 + ps.KB20 % VMAX = VMAXC*(phys.BW^0.7); %Liver P450 ACN to CEO% VMAX2 = VMAXC2*(phys.BW^0.7); %Liver CEO Hydro lysis% KF = KFC/(phys.BW^0.3); %Liver ACN-GSH r ate% KF2 = KFC2/(phys.BW^0.3); %Liver CEO-GSH/R SH rate% KEH = KEHC*(phys.BW^0.7); % Approx. first- order rate in liver % %CEO rxn rates% KFBR = KF2*phys.GSHRB; %CEO brain RSH rate % KFST = KF2*phys.GSHRST; %CEO stomach RSH ra te% KFS = KF2*phys.GSHRS; %CEO SPT RSH rate% KFR = KF2*phys.GSHRR; %CEO RPT RSH rate%

%-------------------------------loop for running eq uations-------------------

- % figure(15) % set(15,'Units','inches','Position',[1,1,4.1,4.1]) ; % hold on % title('RAM1'); for i=1:quan.idf % idf is the number of simulation s/initial conditions in % the data file this was computed in o ptACN.m ian=i;

tsc = [0:1050]'*quan.t(jf(i))/1000; %ICs(i,[1,16]) [ts,Ys] = ode15s(@EqACN2,tsc,ICs(i,:),options); % %[ts(1:4),Ys(1:4,1:16)]' %[Ys(1:10,13),VMAX*Ys(1:10,13)./(KM+Ys(1:10,13)),(Y s(2:11,15)-Ys(1:10,15))] massb=sum(Ys(:,1:16),2); % plot(ts,Ys(:,15)); %VMAX*Ys(:,13)./(KM+Ys(:,13))) ;

% The sequence of columns in the data sets are as f ollows:

### C-25 DRAFT - DO NOT CITE OR QUOTE

% tspan, CVB, CL, CBR, CVB2, CL2, CBR2, ODOSE(initi al), IVDOSE(initial) Yp=[Ys(:,16)/phys.VVB, Ys(:,13)/phys.VL, Ys(:,11)/p hys.VBR, ... Ys(:,24)/phys.VVB, Ys(:,23)/phys.VL, Ys(:,22)/p hys.VBR, ... Ys(:,30:32)/phys.BW, massb];

Ccafc(j1(i):jf(i),:)=interp1(ts,Yp,tsp{i}); quan.tp=[quan.tp;ts]; Ccafpt=[Ccafpt;Yp]; Ccafw=[Ccafw;[tsp{i},Ccafc(j1(i):jf(i),:)]]; %--------------------------------end loop---------- ------------------------- end %--------------------------------------------------

--------------------------

- if quan.pt==1 yname = {'AN in blood'; 'AN in liver'; 'AN in brain'; ... 'CEO in blood'; 'CEO in liver'; 'CEO in br ain'; ... 'AN-GSH in urine'; 'CEO-GSH in urine'; 'Hb binding'; 'mass balance'}; fid=fopen(['ACN.txt'],'w'); fprintf(fid,['time','\t','CVB','\t','CL','\t', 'CBR','\t',... 'CVB2','\t','CL2','\t','CBR2','\t','mb all','\r']); fprintf(fid,'%g\t%g\t%g\t%g\t%g\t%g\t%g\t%g\r' ,Ccafw'); %[quan.tp,Ccafpt]'); status=fclose(fid); end %Ccafpt=Ccafc;quan.tp=quan.t; % uncomment this line to plot only the fitted %values %----------------------------------cost function---

--------------------------

- Cost=C0+max(0,pu(9)-2)+max(0,pu(10)-2);gamm=[gA gA gA gC gC gC gC gC gC]; for i=1:nv if quan.datc{i} Cost = Cost + gamm(i)*sum(quan.datc{i}) + .

.. quan.nc(i)*log( sum( ((quan.datc{i} - Ccafc (quan.ic{i},i)).^2)./... (Ccafc(quan.ic{i},i).^gamm(i)) )/quan.nc(i) ); end end

['itr = ',num2str(itr),'; Cost = ',num2str(Cost)]

% ACN PBPK model equation file -- returns derivatve dx = dx/dt, given % state variable x and parameters passed through gl obal statements % %-----------------------------function defined-----

---------------------- function dx = eqs(t,x) %------------------------------globals-------------

---------------- global prs phys ICs quan ps ian MW2 MW CINH TINH global VMAX VMAX2 KF KF2 KEH KFBRC KFSTC KFSC KFRC KFBR KFST KFS KFR KA KM KM2

%---------------------------assign parameters to na mes----------------------- dx=zeros(size(x)); % "dx" = dx/dt, where x is the state vector

%-----------------------------------! %--------- ACRYLONITRILE ---------! %-----------------------------------!

### C-26 DRAFT - DO NOT CITE OR QUOTE

% MR = x(1); %MR = Amount in stomach lumen (mg)! % AB = x(2); %Amount in systemic arterial blood (m g)! CA = x(2)/phys.VAB; %concentration %AX = x(3); % ACN exhaled (mg)! %AST = x(4); % ACN in stomach tissue tissue (mg)! CST = x(4)/phys.VST; CVST = CST/phys.PST; % tis sue/venous concn's %ASTG = x(5); % ACN GSH conjugated in stomach tissu e (mg) %AS = x(6); % ACN in slowly perfused (mg) CVS = x(6)/(phys.VS*phys.PS); % venous concentr ation %ASG = x(7); % ACN-GSH conjugated in slowly (mg) %AR = x(8); % ACN in richly (mg) CVR = x(8)/(phys.VR*phys.PR); % venous concentr ation %ARG = x(9); % ACN-GSH conjugated in richly %AF = x(10); % ACN in fat (mg) CVF = x(10)/(phys.VF*phys.PF); % venous concent ration %ABR = x(11); % ACN in brain (mg) CBR = x(11)/phys.VBR; CVBR = CBR/phys.PBR; % ti ssue/venous concn's %ABRG = x(12); % ACN-GSH conjugated in brain %AL = x(13); % ACN in liver (mg) CL = x(13)/phys.VL; CVL = CL/phys.PL; % tissue/ venous concn's % ALG = x(14); ACN-GSH conjugated in liver (mg) % AM1 = x(15); ACN metabolized by P450 in liver (mg ) % AVB = x(16); ACN in mixed venous blood (mg) CVB = x(16)/phys.VVB; % concentration

RMR = KA*x(1); % rate of absorption from stomach CI=ps.cinh(ian)*(t<=ps.tinh(ian)); %Inhaled concent ration CAL = (phys.QC*CVB+phys.QP*CI)/(phys.QC+(phys.QP/ph ys.PB)); %CAL = Concentration in arterial lung blood (mg /L)! %CX = CAL/phys.PB; % concentration in exiting pulmo nary air % CXPPM = (0.7*CX+0.3*CI)*24450./ps.MW %RAB = ps.KB*x(2)CA*phys.VAB; % ACN binding in arte rial blood STGSH = ps.KSO*CVST*ps.GSHST*phys.VST; % stomach GS H conjugation of ACN SGSH = ps.KSO*CVS*ps.GSHS*phys.VS; % slowly GSH con jugation of ACN RGSH = ps.KSO*CVR*ps.GSHR*phys.VR; % richly GSH con jugation of ACN BRGSH = ps.KSO*CVBR*ps.GSHBR*phys.VBR; % brain GSH conjugation of ACN LGSH = ps.KSO*CVL*ps.GSHL*phys.VL; % liver GSH conj ugation of ACN % ACN metabolized,saturable (P450) and linear pathw ays (mg)! RAM1 = VMAX*CVL/(KM+CVL); % (mg/hr) %VMAX,KM,RAM1 %ACN metabolized,first-order pathway (GST) (mg)! RAM2 = KF*CVL*phys.VL; % (mg/hr)
RTV = phys.QF*CVF+(phys.QL+phys.QST)*CVL+phys.QS*CVS+phys .QR*CVR+phys.QBR*CVBR; % mixed venous blood concentration %RVB = ps.KB*CV*phys.VVB; % ACN binding in venous b lood %[t,CVB/(RTV/phys.QC),CAL/CVB,CA/CAL,x(1),RMR] dx(1) = - RMR; % ACN stomach lumen dx(2) = phys.QC*(CAL - CA) - ps.KB*x(2); % ACN art erial blood after binding dx(3) = phys.QP*CAL/phys.PB; % ACN exiting pulmona ry air dx(4) = phys.QST*(CA-CVST) - STGSH + RMR; % ACN st omach tissue dx(5) = STGSH; % ACN-GSH conjugated in stomach tis sue dx(6) = phys.QS*(CA-CVS) - SGSH; % ACN slowly dx(7) = SGSH; % ACN-GSH conjugated in slowly dx(8) = phys.QR*(CA-CVR) - RGSH; % ACN in richly ( mg) dx(9) = RGSH; % ACN-GSH conjugated in richly dx(10) = phys.QF*(CA-CVF); % ACN in fat (mg)! dx(11) = phys.QBR*(CA-CVBR) - BRGSH; % ACN in brain (mg)!

### C-27 DRAFT - DO NOT CITE OR QUOTE

dx(12) = BRGSH; % ACN-GSH conjugated in brain dx(13) = phys.QL*CA + phys.QST*CVST -(phys.QL+phys. QST)*CVL -RAM1 -RAM2 - LGSH; dx(14) = LGSH + RAM2 + ps.KB*(x(2)+x(16)); % ACN-GSH conjugated in liver + bound in blood dx(15) = RAM1; % ACN metabolized by P450 in liver dx(16) = RTV - phys.QC*CVB - ps.KB*x(16) + ps.blood 0(ian)*(t<=ps.tinf); %Mixed ven. ACN conc after binding (mg/L) dx(30) = STGSH + SGSH + RGSH + BRGSH + LGSH + RAM2 + ps.KFB*(x(2)+x(16)); % amount of AN binding to GSH % [x(1:16),dx(1:16)]' %----------------------------------------! %----------------- CEO ----------------! %----------------------------------------!

%AB2 = x(17); % CEO in arterial blood (mg) CA2 = x(17)/phys.VAB; % concentration %AS2 = x(18); % CEO in slowly perfused (mg) CVS2 = x(18)/(phys.VS*phys.PS2); % venous concn SGSH2 = KFS*CVS2*phys.VS; %AR2 = x(19); % CEO in richly (mg) CVR2 = x(19)/(phys.VR*phys.PR2); % venous concn RGSH2 = KFR*CVR2*phys.VR; %AST2 = x(20); % CEO in stomach tissue tissue (mg)! CST2 = x(20)/phys.VST; CVST2 = CST2/phys.PST2; % tissue/venous concn's STGSH2 = KFST*CVST2*phys.VST; %AF2 = x(21); % CEO in fat (mg) CVF2 = x(21)/(phys.VF*phys.PF2); % venous concn %ABR2 = x(22); % CEO in brain (mg) CBR2 = x(22)/phys.VBR; CVBR2 = CBR2/phys.PBR2; % tissue/venous concn's BRGSH2 = KFBR*CVBR2*phys.VBR; %AL2 = x(23); % CEO in liver (mg) CL2 = x(23)/phys.VL; CVL2 = CL2/phys.PL2; % tis sue/venous concn's % AVB2 = x(24); % Mixed ven. CEO conc after binding ! CVB2 = x(24)/phys.VVB; % concentration

RALG2 = (VMAX2*CVL2/(KM2+CVL2)) + KF2*CVL2*phys.VL; % CEO hydrolysis, saturable + linear terms % For fitting, either saturable or linear is se t to zero CV2 = (phys.QF*CVF2 + (phys.QL+phys.QST)*CVL2 + phy s.QS*CVS2 + phys.QR*CVR2

... + phys.QBR*CVBR2)/phys.QC; % CEO mixed venous b lood conc. (mg/L)

CAL2 = (phys.QC*CVB2)/(phys.QC+(phys.QP/phys.PB2)); % CEO in arterial lung blood (mg/L)!

dx(17) = (phys.QC*CAL2)-(phys.QC*CA2)-(ps.KB2*x(17) ); % CEO in systemic arterial after binding dx(18) = phys.QS*(CA2-CVS2) - SGSH2; % CEO in slowl y perfused tissues (mg)! dx(19) = phys.QR*(CA2-CVR2) - RGSH2; % CEO in rapid ly perfused tissues (mg)! dx(20) = phys.QST*(CA2-CVST2) - STGSH2; % CEO in st omach (mg)! dx(21) = phys.QF*(CA2-CVF2); % CEO in fat tissue (m g)! dx(22) = phys.QBR*(CA2-CVBR2) - BRGSH2; % CEO in br ain tissue (mg)! dx(23) = phys.QL*(CA2-CVL2) + phys.QST*(CVST2-CVL2) - KEH*CVL2*phys.VL + ... (RAM1*MW2/MW) - RALG2; dx(24) = phys.QC*CV2 - phys.QC*CVB2 - ps.KB2*x(24); % CEO mixed venous after binding

%Calculation of the AUC for ACN and CEO in liver, b rain, and blood!

### C-28 DRAFT - DO NOT CITE OR QUOTE

dx(25) = CL; % AUC for ACN liver concentration dx(26) = CBR; % AUC for ACN brain conc.! dx(27) = CBR2; % AUC for CEO brain conc.! dx(28) = CVB; % AUC for ACN blood conc.! dx(29) = CVB2; % AUC for CEO blood conc.!

dx(31) = STGSH2 + SGSH2 + RGSH2 + BRGSH2 + RALG2 + ps.KFB2*(x(17)+x(24)); % amount of CEO binding to GSH

dx(32) = (ps.KH*(x(2)+x(16))) + (ps.KH2*(x(17)+x(24 )));

% had problems with state variables going < 0 at on e point (stiff system); % the following is a fix for this.

%dx=(dx.*(x>=0))+(abs(dx).*(x<0));

### D-1 DRAFT - DO NOT CITE OR QUOTE

APPENDIX D. UNCERTAINTIES ASSOCIATED WITH CHEMICAL -SPECIFIC
PARAMETERS EMPLOYED IN THE PBPK MODEL FOR AN DOSIME TRY
IN HUMANS

PBPK models are computational tools used to predic t chemical/drug disposition. Models are comprised of three distinct types of informatio n: physiological, physicochemical, and biochemical. The physiological data are chemically independent and describe such parameters as organ volumes and blood flows. Physicochemical parameters are chemical specific and specify parameters, such as PCs or permeability. B iochemical parameters define the rates of chemical transformation or binding. In Appendix D, the EPA evaluates uncertainties in the chemical-specific parameters employed in the PBPK m odel used to predict AN dosimetry in humans, which is adapted from that of Sweeney et al . (2003). Only a small number of (metabolic) parameters were changed in the EPA's ad aptation, which will be noted below. Otherwise, it should be understood that any discuss ion of the model of Sweeney et al. (2003) applies to the one used in this assessment.

PCs
PCs describe the extent of distribution of chemica l into the body, including target tissues such as the brain and lungs. PCs employed in the m odel of Sweeney et al. (2003) were derived
from rat tissue:air PCs and human blood:air PC for AN or CEO in the following way:

P tissue:blood 

### (human) = P tissue:air 

### (rat)/ P blood:air 

### (human)
This equation assumes that the relative difference in PCs between tissues is the same in rats as in humans. The systematic difference betwe en the two is accounted for by the blood:air PC; for humans, the experimentally determined value for AN (154) differed from the value for the rat (512) by threefold. Due to the absence of experimental data, Sweeney et al. (2003) set the human blood:air PC for CEO equal to the rat value ( 1,658). It may be asked whether the estimates produced by t he above equation are reasonable considering the chemical characteristics of AN and CEO and the distribution of AN- and CEO-soluble components in human tissue. To address these issues, the method of Poulin and Theil (2002) was used to estimate the P tissue:blood 

### (human). The method is based on the additive solubilities of a chemical in lipid and water, and the relative distribution of these substances in tissues. Sensitivity analysis conducted by Sweeney et al. (2003) identified the P stomach:blood 

### and
P brain:blood 

### for AN as influential on AN-related dose metrics a nd the P brain:blood 

### for CEO as
influential on CEO-related dose metrics. Table D-1 provides estimates of PCs for AN and CEO. Note that the critical PCs, the P stomach:blood 

### for AN and the P brain:blood 

### for AN and CEO, as predicted by the method of Poulin and Theil were wi thin a factor of about 1.5 of the values employed by Sweeney et al. (2003).

### D-2 DRAFT - DO NOT CITE OR QUOTE

Table D-1. Tissue:blood PCs

PCs for AN PCs for CEO Comp a Exp b Exp:comp ratio Comp a Exp b Exp:comp ratio Adipose tissue 0.30 0.94 3.11 Adipose tissue 0.22 0 .79 3.52
Brain 1.12 1.34 1.19 Brain 0.99 1.40 1.41
Stomach 1.00 1.51 1.52 Stomach 0.89 0.27 0.31
Liver 1.02 1.51 1.48 Liver 0.94 0.27 0.31
Muscle 0.98 1.16 1.19 Muscle 0.83 1.84 1.97 Richly perfused 1.00 1.51 1.51 Richly perfused 0.97 0.27 0.28

a Computationally derived by Poulin and Theil (2002).
b Experimentally obtained/reported by Sweeney et al. (2003).



### To evaluate the influence of the PC in the model, t he revised human PBPK model was implemented with both sets of PCs (Table D-1, with P blood:air 

### as measured for AN using human blood and for CEO using rat blood). For three diff erent exposure scenarios, the peak AN and CEO did not change by more than 30% of initial valu e (Table D-2). This finding may be explained by consistency between both estimates of PC and a general lack of sensitivity to the PC (see Sweeney et al., 2003). Indeed, the only PC s with normalized sensitivity coefficients that
exceeded 0.2 were the P stomach:blood 

### (AN), P brain:blood 

### (AN), and the P brain:blood 

### (CEO). Consistent with these results, Table D-2 shows a greater impac t of changing the PC in the brain than the blood (an averaged effect of other PCs). All of th e predicted concentration in brain tended to decrease when the model was implemented with PC as per the method of Poulin and Theil (2002).

### D-3 DRAFT - DO NOT CITE OR QUOTE

Table D-2. Impact of method of estimation of PCs o n the peak AN and CEO model predictions

Peak AN ( μ g/L) Peak CEO ( μ g/L) Exposure PC method a Blood Brain Blood Brain
S 4.87 11.4 0.998 1.23
PT 4.87 9.56 0.998 0.863 Inhalation 2 ppm, 8 h 0.0% -16.4% 0.0% -29.6%
S 0.975 2.29 0.200 0.245
PT 0.975 1.91 0.200 0.173 Inhalation 0.4 ppm, 1 wk 0% -16.4% 0% -29.6%
S 2.50 3.11 8.36 10.14
PT 2.68 2.77 8.64 7.44 Oral 6 pulses in 24 h, 0.2 mg/kg total 7.3% -10.9% 3.4% -26.7%

a S = PCs as estimated by Sweeney et al. (2003) (list ed in Appendix C); PT = PCs estimated using the met hod of Poulin and Theil (2002). AN and CEO are from model simulations using other human parameters as listed in Appendix C.



### Parameters of metabolic clearance Sweeney et al. (2003) developed a PBPK model of AN and CEO disposition in humans
based on human in vitro data and the rat model of Kedderis et al. (1996). Human in vivo pharmacokinetic data were not available for model d evelopment; therefore, the authors proposed a rodent-human parallelogram approach to consider u ncertainties in the scaling of in vitro metabolism data. Critical metabolic pathways inclu ded the oxidation of AN to CEO, the conjugation of AN and CEO, and the hydrolysis of CE O. With the exception of the latter, the scaling of in vitro rate constants for these pathways was first investigated by Kedderis et al. (1996), w ho observed that the scaled rate constants (rat model) derived from rat liver microsomes, did not m atch those constants fit from in vivo rat data. Sweeney et al. (2003) employed both in vitro and in vivo data to derive an empirical correction factor (CF) to account for uncertainties in scaling (rat). The scaling constant was assumed to be constant across species; thus, the preexisting rat model, the empirical CF, and human in vitro data were employed to specify a human PBPK model. Because EPA altered a number of the rat metabolic p arameters to accommodate the rate constant for AN hydrolysis extrapolated from in vit ro data and to obtain parameters in a way that was computationally reproducible, while following t he same approach as Sweeney et al. (2003) for metabolic parameter extrapolation, the EPA obta ined different values for humans. First, we
describe the derivation of the human V maxC 

### for the oxidation of AN to CEO in the following equations. The ratio of rates determined by human in vitro data and rat in vitro data is considered (Kedderis et al. 1993c), as well as the allometrically scaled in vivo rate constant for
oxidation of AN in the rat.

### D-4 DRAFT - DO NOT CITE OR QUOTE vitro in V V VLC VLC ] liver g / mgMSP [ ]

liver g / mgMSP [ BW BW

vivo in ) kg/ h / mg ( )

rat ( V

vivo in ) kg/ h / mg ( ) human ( V

human max, human max,

rat human

rat human 3.0

rat human 7.0 C max 7.0 C max        

×        
×        
×        
× =



### 22.1 = 7.1 × 5.422 × 1.4225 × 0.6425 × 0.626

Next, the value (and calculations) of the empirical CF = 5.785 is shown. This value represents
what is not accounted for in the in vitro to in vivo scaling in the rat.

  

 

  

 

× × × × = 3.0 3 7.0 max 7.0 max

/ 10 ] / [ ) / / ( ) ( ) / / ( ) (

rat rat rat C C

vitro in vivo in BW VLC kg g liver g mgMSP
vitro in kg h mg rat V

vivo in kg h mg rat V CF



### 5.785 = 7.1 / (0.001164 × 40 × 1000 × 0.04 × 0.659) The allometrically scaled in vivo rate constant for human pseudo first-order GSH conjugation of AN and CEO was calculated in the sam e way (not shown). The parallelogram method was applied differently to estimate the rate constant for enzymatic hydrolysis by EH in humans. Because the EPA extrapolated the EH rate constant in rats from in vitro to in vivo without use of an adj ustment factor, the same was done for humans. Kedderis and Batra (1993) determined a V max 

### and K m 

### EH-mediated hydrolysis of CEO using liver microsome samples from six individual humans. The lowest estimated K m 

### in the group was
600 μ M, so the EPA chose to describe the metabolism as f irst-order since in vivo concentrations are expected to stay well below that value, using t he ratio of V max 

### /K m 

### . The ratio of V max 

### /K m 

### was first calculated for each individual since V max 

### and K m 

### tend to be statistically correlated due to the way they are estimated, and an average value for th e ratio was then determined to be 7.02 × 10 -6 

### L/minute/mg MP. We can then apply the value of 56. 9 mg MP/g liver from Lipscomb et al. (2003), the liver fraction of 25.7 g/kg BW, and the standard value of 70 kg BW for a human.
The rate constant for a standard human is then k EH 

### = (7.02 × 10 -6 

### L/minute/mg EH) × (56.9 mg MP/g liver) × (25.7 g liver/kg BW) × (70 kg BW) × (60 minutes/hour) = 43.1 L/hour, and assuming it also scales as BW 0.7 

### (because it represents V max 

### /K m 

### , with K m 

### assumed constant),
k EHC 

### = k EH 

### ÷ (0.70 kg) 0.7 

### = 2.20 L/hour-kg 0.7



### . The parallelogram approach described by Sweeney et al. (2003) is provocative, considering that human in vivo pharmacokinetic data are sparse for many compounds. What special assurances are required in using this appro ach? First, what is the basis of the empirical CF? It i s the basis to account for: (1) artifacts of microsomes that may bias the estimation of rate con stants (as suggested by Kedderis et al., 1996) or (2) decay in activity due to handling and storag e. An analysis by Lipscomb et al. (1998) compared the in vivo V max 

### that would be obtained by directly extrapolating t he in vitro metabolism of trichloroethylene to the value obtain ed by fitting in vivo data and found that the

### D-5 DRAFT - DO NOT CITE OR QUOTE

in-vitro-derived value came out to about one half o f an in-vivo-fitted value. Thus, it appears that a CF is appropriate to account for either or both o f these factors. Sweeney et al. (2003) applied the same approach to the enzyme-catalyzed GSH conju gation (cytosolic in origin). One concern that had existed is that Sweeney et al. (2003) had been forced to assume that the same factor holds for distinct enzymes (P450 and EH) that are m embrane bound, because EH activity in the rat was taken to be zero in the original model of K edderis et al. (1996), but that assumption is no longer required since the EPA was able to extrapola te the EH-mediated activity without adjustment. The EPA must still assume that the fac tors for P450 and GST hold across species, but, given that the in-vitro enzyme preparations an d measurements of activity were made in the same way for both animals and humans, this seems a reasonable assumption. Nevertheless, it does represent a source of uncertainty. The human PBPK model (with the EPA's revised parame ters) can be tested by comparing the data of Jakubowski et al. (1987) with mass-bala nce calculations from the PBPK model (Table D-3). Unfortunately, there are some signifi cant discrepancies between the data of Jakubowski et al. (1987) and these simulations. Th e respiratory retention (nominally in the lung) of AN from subjects exposed through a face mask ran ged from 44 to 58%, with an average of 51.8%. The PBPK model predicts 99% uptake of AN in haled to the pulmonary region. Recognizing that ~30% of inhaled air only enters the conducting airways (so-called “dead space”), the PBPK model effectively predicts a rete ntion of 69%, which is considerably higher than measured. The respiration rates of the subjec ts in the Jakubowski et al. (1987) experiment ranged from 366 to 625 L/hour, with an average of 5 08 L/hour, which corresponds to an alveolar ventilation rate of 356 L/hour, while the PBPK mode l utilized a rate of 300 L/hour (for a 70-kg person), but increasing the respiration rate in the model by this amount (while holding all other parameters constant) only decreases the alveolar up take fraction from 98.7 to 98.5%. A possible explanation is that AN is subject to a considerable “wash-in/wash-out” effect, where some of the material inhaled deposits temporarily in the conduc ting airways and then desorbs on expiration,
which is not accounted for in the model.

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Table D-3. PBPK mass balance predictions for an 8- hour human exposure to 2 ppm AN

Parameter Metric Amount (mg) Percent AI AN mass inhaled 10.389 AX AN mass exhaled 0.133 1.3 ATi AN final tissue mass (including blood) 0.725 7. 0 AMt AN metabolized by ... 5.102 49.1 AMo AN oxidized 3.904 37.6 AMgt AN enzymatically conjugated (in liver) 0.280 2 .7 AMgn AN non-enzymatically conjugated 0.918 8.8

Metabolic mass balance (AMo + AMgt + AMgn)/AMt 100.00% ABD AN bound to Hb and sulfhydrils 4.429 42.6

Total AN mass balance (AX + ATi + AMt + ABD)/AI 100.00%

CMo CEO formed from AN oxidation a 5.080 CX CEO mass exhaled 0.001 0.0 CTi CEO final tissue mass 0.097 1.9 CEH CEO hydrolyzed 1.128 22.2 CCl CEO conjugated in liver 2.596 51.1 Ccti CEO conjugated in other tissues 0.283 5.6 CBD CEO bound to Hb and sulfhydrils 0.975 19.2

CEO mass balance (Cti + CEH + CCl + Ccti + CBD)/CMo 100.00%

a CMo = AMo 

### × MW CEO ÷ MW AN .


### The subjects of Jakubowski et al. (1987) were then exposed in a chamber for 8 hours to an average of 10.8 or 5.6 mg/m 3 

### (5 or 2.6 ppm), and the total excretion of CEO in the urine was found to be an average of 26.4 or 16.3% of the reta ined dose (portion not exhaled) at those respective exposure levels. The PBPK model predict s that 38% of the retained AN is oxidized to CEO and that 22% of that CEO is hydrolyzed, with th ese fractions being fairly constant at
≤ 8 ppm. Assuming that all the hydrolysis product wa s excreted in the urine, that the acidextraction method of Jakubowski et al. (1987) would have reversed the hydrolysis, and that the extraction/HPLC technique would have separated that product from the GSH conjugates and other metabolites, the predicted urinary excretion of “CEO” would then be 8.4% of the retained dose. Alternately, if it is assumed that all CEO c onjugated with GSH was excreted in the urine and that the method of Jakubowski et al. (1987) had cleaved the GSH conjugates, then the total CEO predicted in the urine would be 79% of the CEO formed or 30% of the retained AN. Therefore, the measured CEO excretion as a fraction of the retained dose is bracketed by the predicted levels, depending on what is assumed abou t the assay method. These results indicate that the model predictions of AN and CEO metabolism in humans subsequent to absorption are at least in the right range. Kedderis et al. (1996) suggest that the overestimat ion of CEO by the rat model at the early time points (which also occurs in the EPA's r evision) may be due to an intrahepatic first

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pass effects, as occurs with other epoxides formed in situ from their parent olefins (Filser and Bolt, 1984). The introduction of such a structure (“privileged access” as coined by Kohn and Melnick, 2000) would contribute to the efficient cl earance of CEO; however, whether the needed differential reduction of CEO levels in the early p hase would also be accomplished is not clear. The issue is that the model predicts a very rapid r ise for CEO in blood to peak/plateau levels (Figure 3-5a, top panels), while the data show a gr adual rise over the first ~10 minutes. It is not evident that a privileged access model would accoun t for this dynamic difference since the
current model allows for reaction of AN with GSH in stomach tissue and liver before reaching the general circulation. Further, the same lack-of -fit occurs vs. the CEO i.v.-exposure data shown in Figure 3-3, which could not be explained b y a first-pass effect from GI absorption. An alternate explanation is that the model currentl y assumes constant GSH levels, while GSH may be depleted during the early part of the ex posure. A model that includes this depletion could predict that at very short times when GSH is near control levels, relatively little AN would remain unconjugated for conversion to CEO, but, as the depletion occurs, more and more AN would be available for oxidative conversion to CEO, hence the gradual rise. To accurately calibrate parameters that accomplish intrahepatic c learance would require a description of GSH
kinetics. Thus, the inability to fit the rat blood CEO levels over the entire time course and the lack of understanding of the biological basis for those kinetics indicate a level of uncertainty in the model that could be addressed through further resea rch. While the model’s overprediction of AN absorption in humans indicates that the descript ion of gas uptake could be improved, this discrepancy is only 10–30% (much less than the appa rent 3- to 10-fold overprediction of blood and brain CEO levels in rats and [likely] in humans by the oral route). However the model does predict AN and CEO blood and tissue levels from inh alation exposure in rats at the lowest concentration measured (186 ppm) quite well (Figure 3-4a), indicating that the gas-uptake description is adequate for prediction of rat dosim etry, and an adjustment of the description in humans would lower the predicted uptake and hence t he extrapolated risk. Therefore, the use of the model to predict CEO levels after AN inhalation in humans should be adequately protective. For oral exposures, however, the greater accuracy o f the AN predictions vs. CEO (Figure 3-5b vs. 3-5a), suggests greater certainty in the use of AN, although the mode of action suggests that
CEO is the active metabolite.

Sensitivity and Uncertainty Analysis Sensitivity and uncertainty analyses were performe d to investigate the dependence of PBPK model predictions for AN and CEO on specific m odel parameters and to estimate the overall uncertainty in those predictions, given est imates of uncertainty in specific model
parameters.

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The first step was to perform a sensitivity analys is on PBPK model predictions to identify the degree to which model dose metric predictions d epend on model parameters. For this purpose, normalized sensitivity coefficients were c alculated. For example, the sensitivity of a model prediction of concentration (e.g., AN concent ration in blood) to parameter P (e.g.,
metabolic V maxC 

### for AN oxidation), the normalized sensitivity coef ficient is:

S = (dC/dP) × (P/C)

The first term is the derivative of C with respect to P. (C is generally a function of time, so this derivative will also depend on time.) This derivat ive is approximated by alternately increasing and decreasing P by a small fraction, ∆ P (taken to be 1% of P here) and calculating [C(P + ∆ P) – C(P – ∆ P)] ÷ (2 × ∆ P). The second term normalizes the sensitivity wit h respect to the value of C at the normal value of P and with respect to P, ess entially yielding the percent change in C given a 1% change in P. These sensitivities typically va ry between ±1, where values near 1 show high sensitivity and values near 0 show low sensitivity.
Sensitivities were determined for four dose metric s, the blood and brain concentrations of AN and CEO, under an inhalation and an oral exposur e scenario for the human PBPK model. For simplicity, the EPA considered continuous expos ures to either 0.4 ppm AN by inhalation or an oral absorption rate equal to 1 mg/kg-day and an alyzed the values of these metrics at 24 hours, by which time, the human body is predicte d to reach steady state. Under such conditions, the AUC for each metric is just 24 hour s times the steady-state concentration (subsequent to reaching steady state), and hence, t he sensitivity of the AUC is identical to the sensitivity of the concentration, given that the co efficients are normalized as described above. Since these concentrations are in the linear range of the model, they apply across the low-dose, linear range of concentrations. The sensitivity co efficients for each parameter for which at least one coefficient had absolute value greater than 0.1 are listed in Tables D-4 and D-5 for the inhalation and oral scenarios, respectively.

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Table D-4. Sensitivity of AN and CEO metrics for c ontinuous inhalation
exposure

Dose metrics a (concentrations) Parameter AN in blood AN in brain CEO in blood CEO in brain Q CC -0.49 -0.57 0.51 0.64 Q PC 0.99 0.99 0.99 0.98
V LC -0.01 -0.01 -0.64 -0.64
V BRC -0.01 -0.04 -0.04 -0.14
V SC -0.14 -0.10 -0.28 -0.28
V ABC -0.07 -0.07 -0.12 -0.15
V VBC -0.12 -0.08 -0.20 -0.20 Q LC -0.76 -0.53 0.65 0.65 Q BRC 0.00 0.03 0.00 0.10 Q SC -0.02 -0.01 -0.10 -0.10
GSH L 0.00 0.00 0.27 0.38
GSH BR -0.01 -0.04 -0.04 -0.14
GSH S -0.13 -0.09 -0.27 -0.27
V maxC -0.09 -0.06 0.11 0.11
K m 0.09 0.06 -0.11 -0.11
k FC2 0.00 0.00 -0.86 -0.96
k EHC 0.00 0.00 -0.25 -0.25
k BC -0.19 -0.16 -0.16 -0.16
k BC2 0.00 0.00 -0.13 -0.15
P BR 0.00 0.97 0.00 0.00
P BR2 0.00 0.00 0.00 1.00

a Values are normalized sensitivity coefficients (i.e ., (dC/dP) × (P/C), for sensitivity of concentration C to param eter P) for steady state blood and brain concentrations predicted for humans during an exposure to 0.4 ppm AN. Sensitivities are approximated by increasing and de creasing each parameter by 1% of its default value. Values of 0.2 or greater are indicated in bold and values bet ween 0.1 and 0.2 in italics. Parameters for which all coefficients are less than 0.1 are omitted.

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Table D-5. Sensitivity of AN and CEO metrics for c ontinuous oral exposure

Dose metrics a (concentrations) Parameter AN in blood AN in brain CEO in blood CEO in brain
BW 0.21 0.20 0.24 0.24 Q CC 0.30 0.36 0.27 0.39
V LC -0.07 -0.07 -0.64 -0.64
V BRC -0.01 -0.04 -0.03 -0.13
V SC -0.10 -0.10 -0.19 -0.19
V VBC -0.12 -0.12 -0.13 -0.13 Q LC 0.29 0.29 0.35 0.35
GSH L 0.00 0.00 0.27 0.38
GSH BR -0.01 -0.04 -0.03 -0.13
GSH S -0.09 -0.09 -0.18 -0.18
V maxC -0.89 -0.89 0.11 0.11
K m 0.89 0.89 -0.11 -0.11
k FC2 0.00 0.00 -0.86 -0.96
k EHC 0.00 0.00 -0.25 -0.25
k BC -0.17 -0.19 -0.01 -0.01
k BC2 0.00 0.00 -0.13 -0.15
P BR 0.00 0.97 0.00 0.00
P BR2 0.00 0.00 0.00 1.00

a Values are normalized sensitivity coefficients (i.e ., (dC/dP) × (P/C), for sensitivity of concentration C to param eter P), for steady state blood and brain concentrations predicted for humans during a continuous oral infu sion equal to 1 mg/kg-d. Sensitivities are approximated by incre asing and decreasing each parameter by 1% of its de fault value. Values of 0.2 or greater are indicated in bold, and values between 0.1 and 0.2 in italics. Parameters for which all coefficients are less than 0.1 are omitted.



### The EPA’s results can be compared to those of Swee ney et al. (2003), derived for the original model, with previous parameter values. Fo r the inhalation scenario (Table D-4), the EPA's results for AN are essentially identical to t hose of Sweeney et al. (2003), and those for CEO show the same qualitative pattern and only have a few notable differences. The sensitivity to the rate constant for CEO hydrolysis (k EHC 

### in the EPA’s model; V maxC2 

### in Sweeney et al., 2003) is -0.25 in the revised model and −0.5 in the ir previous model, indicating somewhat less importance for this parameter now. On the other ha nd, the sensitivity to CEO-GSH conjugation in the liver parameterized by k FC2 

### increased from ~0.6−0.7 for Sweeney et al. (2003) t o ~0.9 with the revised model, showing more significance now. Thus, there is a shift in the relative importance of these two parameters and the rate con stant for GSH conjugation in humans is an especially important factor in the EPA’s prediction s, while the exact rate of CEO hydrolysis is less influential, though still somewhat important.

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Important factors in comparing the EPA’s results f or an oral exposure to those of Sweeney et al. (2003) are that the EPA held the dos e in mg/kg-day constant, so that it varied in proportion to BW when that parameter was varied, wh ile Sweeney et al. (2003) held the dose in mg/day constant, and they calculated sensitivities of the AUC and peak concentrations for only the AN metrics, while the EPA used steady-state con centrations of AN and CEO. Thus, it is not surprising that Sweeney et al. (2003) had a negativ e sensitivity to BW, since the same total dose given to a larger body would result in a lower conc entration, while the EPA's is positive, reflecting that a proportionately higher dose is ex pected to yield higher-than-proportional
concentrations because the rates of metabolic elimi nation scale as BW 0.7



### . It is interesting to note that the liver volume (fraction), which effects the rates of firstand second-order reactions in the model, and the ra te constants for CEO removal but not CEO production (V maxC 

### ) significantly affect the CEO metrics (absolute va lues from Sweeney et al. (2003) are about 0.17–0.18 for sensitivity of CEO m etrics to V max 

### and K m 

### ). The EPA’s lack of significant dependence on blood flow rates to stoma ch (Q StC 

### ) and slowly-perfused tissues (Q SC 

### ) is due to the fact that the EPA is analyzing a cont inuous infusion, as these do significantly affect the peak concentration after a bolus exposure. Thu s, these are only important for specific dosing
scenarios. Likewise the rate of absorption (k A 

### ) from the stomach significantly affects the peak concentration (verified but not shown for the revis ed model) but has a much smaller affect on the AUC. These results for absorption are not surprisi ng, since changes in k A 

### do not alter the fact that the entirety of an oral bolus is predicted to be absorbed. Whether or not there is an impact on the steady-state concentrations depends on what one believes about oral absorption. In particular, if one assumes 100% absorption, where t he rate of absorption increases with the amount in the GI tract, then at steady state, the r ate of absorption must equal the rate of ingestion and the exact rate of absorption is unimportant. I t is only if orally ingested material may be
eliminated in the feces or otherwise transformed in the gut without absorption that the exact rate constant for absorption would be important. Finally, uncertainty in these steady-state model p redictions was estimated using the equation of Sweeney et al. (2003) for the approxima te coefficient of variation (CV): 

# ( ) ∑

⋅ =

i i

mi m 

### CV

S CV 2



### where CV m 

### is the estimated CV for metric “m,” S mi 

### is the sensitivity coefficient of metric “m” to
parameter p i 

### , as tabulated above, and CV i 

### is the CV of p i 

### . For this calculation, the EPA decided to use the individual parameter CV values as estima ted and used by Sweeney et al. (2003, see Table 3-5 in that paper). The CVs for physiologica l parameters (e.g., blood flow rates, tissue fractions) would indeed be identical, and, while th e EPA reestimated some metabolic parameters

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and k A 

### , the underlying in vitro data on which the human e xtrapolation is based are the same, and hence, they are expected to be approximately the sa me. The resulting CV values for the EPA’s four metrics under the two exposure scenarios are
listed in Table D-6.

Table D-6. Estimated CVs for AN and CEO metrics

Dose metrics (concentrations) Exposure scenario AN in blood AN in brain CEO in blood CEO in brain 0.4 ppm inhalation 0.620 0.656 0.893 1.15 1 mg/kg-d oral 0.790 0.873 0.711 1.01



### The overall CVs in Table D-6 are interesting in the mselves, in that they indicate the overall level of confidence in the model’s predicti on of those dose metrics. But even more interesting is the contribution of the individual p arameters to each of these metrics, as listed in
Tables D-7 and D-8. What those contributions show is that the vast majority of the uncertainty arises from a small number of parameters and that m ost of those parameters are physiological values—alveolar ventilation (Q CC 

### ), cardiac output (Q PC 

### ), and blood flow to the liver (V LC 

### )—and
the brain:blood PC in the case of the brain metrics

.

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Table D-7. Parameter contributions to overall CVs for inhalation exposure

Dose metrics a (concentrations) Parameter AN in blood AN in brain CEO in blood CEO in brain Q CC 9.3 11.5 5.0 4.6 Q PC 37.9 33.9 18.2 11.0
V LC 0.0 0.0 7.7 4.6
V BRC 0.0 0.1 0.1 0.5
V SC 0.7 0.3 1.4 0.9
V ABC 0.4 0.4 0.6 0.5
V VBC 1.1 0.5 1.5 0.9 Q LC 44.4 19.8 15.9 9.6 Q BRC 0.0 0.1 0.0 0.2 Q SC 0.0 0.0 0.4 0.2
GSH L 0.0 0.0 1.1 1.3
GSH BR 0.0 0.2 0.1 0.7
GSH S 0.9 0.4 1.8 1.1
V maxC 1.1 0.5 0.7 0.4
K m 0.4 0.2 0.3 0.2
k FC2 0.0 0.0 39.2 29.8
k EHC 0.0 0.0 3.4 2.1
k BC 2.9 1.8 1.0 0.6
k BC2 0.0 0.0 0.7 0.5
P BR 0.0 30.0 0.0 0.0
P BR2 0.0 0.0 0.0 29.9

a Values are 100 × S mk 2 × CV k / Σ (S mi 2 × CV i ). Values >5 (i.e., 5% contribution) are in bold.

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Table D-8. Parameter contributions to overall CVs for oral exposure

Dose metrics a (concentrations) Parameter AN in blood AN in brain CEO in blood CEO in brain
BW 1.1 0.8 1.7 0.8 Q CC 2.2 2.5 2.1 2.3
V LC 0.1 0.1 12.1 6.0
V BRC 0.0 0.1 0.1 0.5
V SC 0.2 0.2 1.0 0.5
V VBC 0.7 0.5 0.9 0.5 Q LC 4.1 3.4 7.1 3.5
GSH L 0.0 0.0 1.8 1.7
GSH BR 0.0 0.1 0.1 0.8
GSH S 0.3 0.2 1.3 0.6
V maxC 66.1 54.1 1.2 0.6
K m 23.1 18.9 0.4 0.2
k FC2 0.0 0.0 61.9 38.6
k EHC 0.0 0.0 5.4 2.7
k BC 1.4 1.5 0.0 0.0
k BC2 0.0 0.0 1.0 0.7
P BR 0.0 16.9 0.0 0.0
P BR2 0.0 0.0 0.0 38.7

a Values are 100 × S mk 2 × CV k / Σ (S mi 2 × CV i ). Values >5 (i.e., 5% contribution) are in bold.



### Since the PCs are expected to be similar in rats an d humans, and the extrapolation really depends on the rat:human ratio of those, the true r esulting uncertainty is likely to be very small. The nominal uncertainty in cardiac ventilation and blood flows is expected to be a composite of uncertainty and inter-individual variability. And the only metabolic parameter to contribute significantly to the uncertainty for inhalation exp osure is the CEO-GSH conjugation rate. Thus, a significant improvement in the overall uncertaint y can be gained by further investigation of only a small number of parameters, half of which ar e applicable to every PBPK model that might be considered for gases. The distribution of parameter influence for the or al simulation scenario, as shown in Table D-8, is similar to that for inhalation in tha t most of the influence is distributed among a few parameters, with the brain:blood PCs strongly i nfluencing brain concentrations. Also similar is that the CEO-GSH conjugation rate (k FC2 

### ) is a significant factor for the CEO metrics. Unl ike the inhalation case, alveolar ventilation (Q PC 

### ) has negligible influence, which is to be expected

, but also cardiac output (Q CC 

### ) has only small influence. This later case occurs because of the strong first-pass effect for AN as it is absorbed t hrough the liver, which also explains the very high influence of the oxidation parameters, V maxC 

### and K m 

### , on the AN metrics.

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These results for oral exposure are quite similar to the results obtained by Sweeney et al. (2003), except that their results indicate some what higher influence by blood flow to the liver (i.e., 8–12% on AN metrics), liver GSH (6%), and a much higher influence of CEO hydrolysis (k EHC 

### here, parameterized by a V max 

### and K m 

### with influence of 12–30%) on CEO metrics. The shift of influence from hydrolysis to GSH conjugati on for CEO metrics between Sweeney et al. (2003) and the EPA's results arises from the shift in the relative rates through those two pathways, but in both, the rate of CEO removal is a strong determinant of the CEO metric.