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3. List of contributors

Author

Akortia, Eric, primary, Alla, Sai Radha Mani, additional, Alves, Vinicius M., additional, Andrade, Carolina H., additional, Avram, Speranta, additional, Bao, Tong, additional, Benfenati, Emilio, additional, Braga, Rodolpho C., additional, Buiu, Catalin, additional, Chakravarti, Suman K., additional, Chen, Jingwen, additional, Chen, Minjun, additional, Ciura, Krzesimir, additional, Colombo, Erika, additional, Cross, Kevin P., additional, Cui, Shixuan, additional, del Giudice, Giusy, additional, Dong, Fan, additional, Duchowicz, Pablo R., additional, Egbi, Courage, additional, Egodawatta, Prasanna, additional, Elakkiya, Elango, additional, Federico, Antonio, additional, Fratello, Michele, additional, Fu, Zhiqiang, additional, Furuhama, Ayako, additional, Gao, Yuchen, additional, Garro Martinez, Juan C., additional, Gbeddy, Gustav, additional, Giner, Beatriz, additional, Glover, Eric, additional, Goonetilleke, Ashantha, additional, Greco, Dario, additional, Gromelski, Maciej, additional, Gu, Yaxin, additional, Gui, Binxin, additional, Guo, Jing, additional, Guo, Wenjing, additional, He, Jiale, additional, He, Minghui, additional, Hong, Huixiao, additional, Honma, Masamitsu, additional, Huang, Shuheng, additional, Huang, Ruili, additional, Huang, Meiling, additional, Jaeger, Martin, additional, Jillella, Gopala Krishna, additional, Johnson, Candice, additional, Kasamatsu, Toshio, additional, Khan, Pathan Mohsin, additional, Koster, Sander, additional, Kusko, Rebecca, additional, Lee, Myeongsang, additional, Li, Chao, additional, Li, Fei, additional, Li, Bohao, additional, Li, Menglong, additional, Li, Dongying, additional, Li, Jinjie, additional, Li, Xuehua, additional, Li, Zoe, additional, Liao, Tsung-Jen, additional, Liu, Yuan, additional, Liu, Huihui, additional, Liu, Jie, additional, Liu, Wenjia, additional, Lomba, Laura, additional, Lou, Chaofeng, additional, Ma, Guangcai, additional, Manganelli, Serena, additional, Mei, Hu, additional, Mendonca, Sabrina S., additional, Mizuno, Tadahaya, additional, Myatt, Glenn J., additional, Ngan, Deborah K., additional, Ning, Baitang, additional, Pandit, Shraddha, additional, Parthasarathi, Ramakrishnan, additional, Patterson, Tucker A., additional, Pavel, Alisa, additional, Prabhu, Paulraj, additional, Puzyn, Tomasz, additional, Qu, Jiao, additional, Roncaglioni, Alessandra, additional, Roy, Kunal, additional, Saarimäki, Laura Aliisa, additional, Saavedra, Laura M., additional, Sanches, Igor H., additional, Schilter, Benoit, additional, Selvaraj, Chandrabose, additional, Serra, Angela, additional, Shi, Wei, additional, Singh, Prakrity, additional, Singh, Sanjeev Kumar, additional, Sogor, Catalina, additional, Song, Meng, additional, Sosnowska, Anita, additional, Su, Limin, additional, Sugiyama, Kei-ichi, additional, Swirog, Marta, additional, Tang, Yun, additional, Teng, Yuefa, additional, Tong, Weida, additional, Tropsha, Alexander, additional, Udrea, Ana-Maria, additional, Velmurugan, Devadasan, additional, Voigt, Melanie, additional, Wang, Haobo, additional, Wang, Xiaoqing, additional, Wang, Zhongyu, additional, Wang, Xueyu, additional, Wei, Xiaoxuan, additional, Wen, Zhining, additional, Wu, Yiqu, additional, Wyrzykowska, Ewelina, additional, Xiao, Fang, additional, Xie, Hong-Bin, additional, Xu, Tuan, additional, Xu, Liang, additional, Yang, Xianhai, additional, Yu, Haiying, additional, Zhang, Yuxuan, additional, Zhang, Jiachen, additional, Zhao, Jingwen, additional, Zhao, Yuanhui, additional, Zhu, Minghua, additional, Zhuang, Shulin, additional, and Zou, Wen, additional

Published
2024
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4. Decision forest—a machine learning algorithm for QSAR modeling

Author

Hong, Huixiao, primary, Liu, Jie, additional, Guo, Wenjing, additional, Dong, Fan, additional, Lee, Myeongsang, additional, Xu, Liang, additional, Li, Zoe, additional, Song, Meng, additional, Chen, Minjun, additional, Zou, Wen, additional, Tong, Weida, additional, and Patterson, Tucker A., additional

Published
2024
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6. AI-powered drug repurposing for developing COVID-19 treatments

Author

Liu, Zhichao, primary, Chen, Xi, additional, Carter, Wendy, additional, Moruf, Alicia, additional, Komatsu, Takashi E., additional, Pahwa, Sonia, additional, Chan-Tack, Kirk, additional, Snyder, Kevin, additional, Petrick, Nicholas, additional, Cha, Kenny, additional, Lal-Nag, Madhu, additional, Hatim, Qais, additional, Thakkar, Shraddha, additional, Lin, Yu, additional, Huang, Ruili, additional, Wang, Dong, additional, Patterson, Tucker A., additional, and Tong, Weida, additional

Published
2022
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8. List of Contributors

Author

Abreu-Villaça, Yael, primary, Adams, Jane, additional, Agans, Richard, additional, Ali, Syed F., additional, Aschner, Michael, additional, Barbaresi, William J., additional, Bellinger, David C., additional, Bickel, Julie, additional, Bogičević, Lilly, additional, Borchelt, Jolene E., additional, Burbacher, Thomas M., additional, Calderon, Johanna, additional, Cerniglia, Carl E., additional, Chang, Louis W., additional, Chelonis, John J., additional, Cuevas, Elvis, additional, Day, Nancy L., additional, DeSesso, John M., additional, Dos Santos, Alessandra A., additional, Dow-Edwards, Diana, additional, Ferguson, Sherry A., additional, Fisher, Jeffrey W., additional, Friedman, Jan M., additional, Gohlke, Julia M., additional, Golub, Mari, additional, Graham, Devon L., additional, Grant, Kimberly S., additional, Greene, Robert M., additional, Gu, Qiang, additional, Guignet, Michelle, additional, Hanig, Joseph, additional, Hartung, Thomas, additional, Hawthorne, Keli M., additional, He, Zhen, additional, Huddleston, Mary E., additional, Hussain, Saber, additional, Imam, Syed Z., additional, Ito, Shinya, additional, Janulewicz, Patricia A., additional, Jensen, Karl F., additional, Jett, David A., additional, Knudsen, Thomas B., additional, Kraft, Andrew D., additional, Krishnan, Kannan, additional, Lala, Prateek, additional, Lantz, Susan M., additional, Lasley, Stephen M., additional, Lee, Francis S., additional, Leibson, Tom, additional, Lein, Pamela J., additional, Levin, Edward D., additional, Liejun Guo, Grace, additional, Lipscomb, John C., additional, Liu, Fang, additional, Liu, Feiyuan, additional, Liu, Shuliang, additional, Lutes, Jocelyn M., additional, Makris, Susan L., additional, Malin, Ashley J., additional, Mendlein, Alexandra, additional, Meyer, Jerrold S., additional, Miller, Mellessa M., additional, Morgan, Philip G., additional, Negi, Geeta, additional, Nulman, Irena, additional, Olin, Jeanene K., additional, Patterson, Tucker A., additional, Paule, Merle G., additional, Pisano, Michele M., additional, Platholi, Jimcy, additional, Richardson, Gale A., additional, Roper, Courtney, additional, Rosas-Hernandez, Hector, additional, Sable, Helen J.K., additional, Saili, Katerine S., additional, Salisbury, Richard L., additional, Sarkar, Sumit, additional, Sedensky, Margaret M., additional, Sheets, Larry P., additional, Shulman, Talya, additional, Slikker, William, additional, Smirnova, Lena, additional, Snyder, Andrew, additional, Sobin, Christina, additional, Stanwood, Gregg D., additional, Supasai, Suangsuda, additional, Talpos, John C., additional, Tanguay, Robert L., additional, Timchalk, Charles, additional, van Baar, Anneloes, additional, Verhoeven, Marjolein, additional, Walters, Jennifer L., additional, Wang, Cheng, additional, Williams, Amy L., additional, Wright, Robert O., additional, Yang, Xiaoxia, additional, Yin, Qi, additional, Zhang, Xuan, additional, and Zurlinden, Todd J., additional

Published
2018
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10. Determining high priority disinfection byproducts based on experimental aquatic toxicity data and predictive models: Virtual screening and in vivo study.

Author

Zhou N, Sui S, Liu H, Yang X, Hong H, and Patterson TA

Subjects
Animals, Daphnia drug effects, Water Pollutants, Chemical toxicity, Disinfectants toxicity, Disinfection
Abstract

Only about 100 disinfection byproducts (DBPs) have been tested for their potential aquatic toxicity. It is not known which specific DBPs, DBP main groups, and DBP subgroups are more toxic due to the lack of experimental toxicity data. Herein, high priority specific DBPs, DBP main groups, DBP subgroups, most sensitive model aquatic species, potential PBT and PMT (persistent, bioaccumulative/mobile, and toxic) DBPs were virtually screened for 1187 updated DBPs inventory. Priority setting based on experimental and predicted acute and chronic aquatic toxicity data found that the aromatic and alicyclic DBPs in four DBPs main groups showed high priority because larger proportions of aromatic and alicyclic DBPs are in high hazard categories (i.e. Acute and/or Chronic Toxic-1 or Toxic-2) according to the criteria in GHS system compared to the aliphatic and heterocyclic DBPs. The halophenols, estrogen-DBPs, nonhalogenated esters, and nonhalogenated aldehydes were recognized as high priority DBPs subgroups. For specific DBPs, 19 and 31 DBPs should be highly concerned in the future study because both acute and chronic toxicity of those DBPs to all of the three aquatic life (algae, Daphnia magna, fish) were classified as Toxic-1 and Toxic-2, respectively. The Daphnia magna and algae were sensitive to the acute toxicity of DBPs, while the fish and Daphnia magna were sensitive to the chronic toxicity of DBPs. One potential PBT (Tetrachlorobisphenol A) and four potential PMT DBPs were identified. For verification, the acute toxicity of four DBPs on three aquatic organism were performed, and their tested acute toxicity data to three aquatic organisms were consistent with the predictions. Our results could be beneficial to government regulators to adopt effective measures to limit the discharge of high priority DBPs and help the scientific community to develop or improve disinfection processes to reduce the production of high priority DBPs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Published
2024
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11. Lipidomics reveals a systemic energy deficient state that precedes neurotoxicity in neonatal monkeys after sevoflurane exposure.

Author

Wang C, Liu F, Frisch-Daiello JL, Martin S, Patterson TA, Gu Q, Liu S, Paule MG, Hanig JP, Slikker W Jr, Crawford PA, Wang C, and Han X

Subjects
Animals, Macaca mulatta, Energy Metabolism drug effects, Lipid Metabolism drug effects, Neurons drug effects, Sevoflurane pharmacology
Abstract

Although numerous studies have raised public concerns regarding the safety of anesthetics including sevoflurane in children, the biochemical mechanisms leading to anesthetics-induced neurotoxicity remain elusive. Moreover, potential biomarker(s) for early detection of general anesthetics-induced brain injury are urgent for public health. We employed an enabling technology of shotgun lipidomics and analyzed nearly 20 classes and subclasses of lipids present in the blood serum of postnatal day (PND) 5 or 6 rhesus monkeys temporally collected after exposure to sevoflurane at a clinically relevant concentration or room-air as control. Lipidomics analysis revealed numerous significant anesthetic-induced changes of serum lipids and their metabolites as well as short chain acylcarnitines in the brain and cerebrospinal fluid after anesthetic exposure. These include decreased carnitine and acylcarnitines, unchanged triacylglycerol mass but accumulation of 16:0 and 18:1 fatty acyl chains in the triacylglycerol pool, losses of polyunsaturated fatty acids in both non-esterified fatty acid and phospholipid pools, and increased 4-hydroxynonenal content as early as 2 h after sevoflurane exposure. Importantly, the amounts of short chain acylcarnitines in the brain and cerebrospinal fluid were also significantly reduced after anesthetic exposure. We propose that this serum lipidomic profile can serve as indicative of neuronal damage. Our results reveal that sevoflurane exposure induces an energy deficient state in the brain evidenced by reduced free and acyl carnitine contents, as well as the presence of a pro-inflammatory state in the exposed animals, providing deep insights into the underlying mechanisms responsible for anesthetic-induced neurotoxicity., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Published
2018
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12. In vitro screening of NADPH oxidase inhibitors and in vivo effects of L-leucinethiol on experimental autoimmune encephalomyelitis-induced mice.

Author

Kandagaddala LD, Kang MJ, Haque MM, Im HY, Seo JE, Chung BC, Jung BH, Patterson TA, and Kwon OS

Subjects
Animals, Disease Models, Animal, Encephalomyelitis, Autoimmune, Experimental immunology, Female, Leucine pharmacology, Leucine therapeutic use, Mice, Mice, Inbred C57BL, NADH, NADPH Oxidoreductases metabolism, NADPH Oxidase 1, Random Allocation, Sulfhydryl Compounds therapeutic use, Drug Evaluation, Preclinical methods, Encephalomyelitis, Autoimmune, Experimental drug therapy, Encephalomyelitis, Autoimmune, Experimental enzymology, Leucine analogs & derivatives, NADH, NADPH Oxidoreductases antagonists & inhibitors, Sulfhydryl Compounds pharmacology
Abstract

Experimental autoimmune encephalomyelitis (EAE), a Th1 polarized demyelinating disease of the central nervous system, shares many pathological and clinical similarities with multiple sclerosis (MS). The objectives of this study were i) to evaluate the suppressive effects of L-leucinethiol (LeuSH), a metalloprotease inhibitor on EAE-induced mice and ii) to study the effects of LeuSH on matrix metalloproteinase-9 (MMP-9), NADPH oxidase and cytokines (IFN-γ, IL-5 and IL-10) in tissues and plasma of EAE mice as a measure of potential markers associated with EAE disease. C57BL/6 mice were immunized with myelin oligodendrocyte glycoprotein (MOG35-55) peptide in complete Freund's adjuvant to induce EAE. A significant difference was observed in body weights and clinical signs of LeuSH (8 mg/kg) administered EAE-induced mice compared to control mice. The findings of this study include alterations in the enzymatic expression of MMP-9, NADPH oxidase and cytokine levels in the brain, spinal cord, spleen, thymus and plasma of inhibitor-treated EAE mice as well as EAE-induced mice. The enzyme activities of NADPH oxidase were inhibited by LeuSH. From these results, it can be considered that LeuSH acts as one of the antigen candidates in ameliorating the clinical symptoms of EAE disease in mice., (Copyright © 2012. Published by Elsevier B.V.)

Published
2012
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13. Toxicity assessment of pramipexole in juvenile rhesus monkeys.

Author

Patterson TA, Li M, Hotchkiss CE, Mauz A, Eddie M, Greischel A, Stierstorfer B, Deschl U, and Paule MG

Subjects
Administration, Oral, Age Factors, Animals, Benzothiazoles administration & dosage, Benzothiazoles blood, Benzothiazoles urine, Blood Pressure drug effects, Blood Pressure physiology, Dose-Response Relationship, Drug, Female, Heart Rate drug effects, Heart Rate physiology, Macaca mulatta, Male, Pramipexole, Prolactin blood, Benzothiazoles toxicity, Toxicity Tests, Chronic methods
Abstract

Pramipexole (PPX) is a dopamine agonist approved for the treatment of the signs and symptoms of idiopathic Parkinson's disease as well as restless leg syndrome. The objective of this study was to investigate the toxicity of PPX when administered orally to juvenile rhesus monkeys once daily for 30 weeks, and to assess the reversibility of toxicity during a 12-week recovery. Rhesus monkeys (N=4 males and 4 females/group; 22-24 months of age) were orally treated daily for 30 weeks with 0.0, 0.1, 0.5 or 2.0 mg/kg PPX, and subjects were assessed daily using the NCTR Operant Test Battery (OTB). Clinical chemistry, hematology, ophthalmology and other standard postmortem toxicological evaluations, including histopathology and neuropathology as well as toxicokinetics were performed. The systemic exposure to PPX was higher than that at therapeutic doses in man and AUC(0-24 h)-data increased proportionally to dose. Blood pressure significantly decreased over time in all groups including control. Near the end of treatment, there were statistically significant decreases in heart rate for the 0.5 and 2.0 mg/kg/day groups compared to control. After 4 weeks of dosing, serum prolactin was significantly decreased in all treatment groups compared to control. This decrease remained at the end of treatment in the 0.5 and 2.0 mg/kg/day groups. In summary, administration of PPX at doses of up to 2.0 mg/kg/day for 30 weeks to juvenile rhesus monkeys produced adverse findings which were attributable to its pharmacological properties, including hypoprolactinemia., (Published by Elsevier Ireland Ltd.)

Published
2010
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