T1: A DEEP LEARNING CONVOLUTIONAL NEURAL NETWORK METHOD TO DETECT SKIN PATHOLOGY ASSOCIATED WITH DELAYED-TYPE HYPERSENSITIVITY REACTION IN MONKEY SKIN T2: DETERMINING OPTIMAL EXPOSURE INTERVALS FOR NAPTHALENE-INDUCED AIRWAY FIBROSIS T3: ADVERSE REPRODUCTIVE OUTCOMES IN PREGNANT AND LACTATING BITCHES EXPOSED TO AFLATOXINS T4: DEVELOPMENT OF A DEEP LEARNING ALGORITHM FOR PRECLINICAL HISTOPATHOLOGICAL EVALUATION OF GRAFT-VS-HOST DISEASE IN A HUMANIZED MOUSE MODEL T5: CELLULAR DENSITY MAP OVERLAYS DERIVED FROM AI BASED NUCLEAR SEGMENTATION CAN BE USED TO IDENTIFY TOXICOLOGIC PATHOLOGY OUTCOMES SUCH AS LIVER HYPERTROPHY. T6: HISTOPATHOLOGY AS A RISK ASSESSMENT TOOL FOR GONADOTOXICITY IN HONEY BEE DRONES T7: EVALUATION OF GENE TARGETED EDITING TO DISABLE THE ONCOGENIC RETROVIRUS HTLV-1 USING IN VITRO CELLULAR SCREENING AND IN VIVO NOG MICE MODELS T8: COMPARISON OF ACUTE DEHYDROPYRROLIZIDINE ALKALOID TOXICOSIS IN C57BL MICE GAVAGED WITH RIDDELLIINE, RIDDELLIINE N-OXIDE, SENECIONINE, SENECIONINE N-OXIDE, SENECIPHYLLINE, LASIOCARPINE OR HELIOTRINE.
