ABSTRACT
We previously developed a computer-assisted image analysis algorithm to detect and quantify the microscopic features of rodent progressive cardiomyopathy (PCM) in rat heart histologic sections and validated the results with a panel of five veterinary toxicologic pathologists using a multinomial logistic model. In this study, we assessed both the inter-rater and intra-rater agreement of the pathologists and compared pathologists' ratings to the artificial intelligence (AI)-predicted scores. Pathologists and the AI algorithm were presented with 500 slides of rodent heart. They quantified the amount of cardiomyopathy in each slide. A total of 200 of these slides were novel to this study, whereas 100 slides were intentionally selected for repetition from the previous study. After a washout period of more than six months, the repeated slides were examined to assess intra-rater agreement among pathologists. We found the intra-rater agreement to be substantial, with weighted Cohen's kappa values ranging from k = 0.64 to 0.80. Intra-rater variability is not a concern for the deterministic AI. The inter-rater agreement across pathologists was moderate (Cohen's kappa k = 0.56). These results demonstrate the utility of AI algorithms as a tool for pathologists to increase sensitivity and specificity for the histopathologic assessment of the heart in toxicology studies.
ABSTRACT
Glyphosate, the most heavily used herbicide world-wide, is applied to plants in complex formulations that promote absorption. The National Toxicology Program reported in 1992 that glyphosate, administered to rats and mice at doses up to 50,000 ppm in feed for 13 weeks, showed little evidence of toxicity, and no induction of micronuclei was observed in the mice in this study. Subsequently, mechanistic studies of glyphosate and glyphosate-based formulations (GBFs) that have focused on DNA damage and oxidative stress suggest that glyphosate may have genotoxic potential. However, few of these studies directly compared glyphosate to GBFs, or effects among GBFs. To address these data gaps, we tested glyphosate, glyphosate isopropylamine (IPA), and (aminomethyl)phosphonic acid (AMPA, a microbial metabolite of glyphosate), 9 high-use agricultural GBFs, 4 residential-use GBFs, and additional herbicides (metolachlor, mesotrione, and diquat dibromide) present in some of the GBFs in bacterial mutagenicity tests, and in human TK6 cells using a micronucleus assay and a multiplexed DNA damage assay. Our results showed no genotoxicity or notable cytotoxicity for glyphosate or AMPA at concentrations up to 10 mM, while all GBFs and herbicides other than glyphosate were cytotoxic, and some showed genotoxic activity. An in vitro to in vivo extrapolation of results for glyphosate suggests that it is of low toxicological concern for humans. In conclusion, these results demonstrate a lack of genotoxicity for glyphosate, consistent with observations in the NTP in vivo study, and suggest that toxicity associated with GBFs may be related to other components of these formulations.
Subject(s)
Herbicides , Humans , Mice , Animals , Rats , Herbicides/toxicity , alpha-Amino-3-hydroxy-5-methyl-4-isoxazolepropionic Acid , DNA Damage , GlyphosateABSTRACT
BACKGROUND: When analyzing fetal defect incidence in laboratory animal studies, correlation in responses within litters (i.e., litter effects) can lead to increased false-positive rates if litter effects are not incorporated into the analysis. Studies of fetal defects require analysis methods that are robust across a broad range of defect types, including those with zero or near-zero incidence rates in control groups. METHODS: A simulation study compared power and false-positive rates for six approaches across a range of background defect rates and litter size distributions. Statistical methods evaluated included ignoring the litter effect as well as parametric and nonparametric approaches based on litter proportions, generalized linear mixed models (GLMMs), the Rao-Scott Cochran-Armitage (RSCA) trend test, and a modification to the RSCA (mRSCA) introduced here to improve estimation at low background rates. These methods were also applied to a common and a rare defect from two prenatal developmental toxicology studies conducted by the National Toxicology Program (NTP). RESULTS: At background defect rates of 1%, the mRSCA and parametric litter proportion methods provided gains in power over the nonparametric litter proportion method, the GLMM method, and the RSCA method. Simulations involving litter loss in high-dose groups showed loss of power for both litter proportion methods. CONCLUSIONS: The mRSCA test developed here compares favorably with other litter-based approaches and is robust across a range of background defect rates and litter size distributions, making it a practical choice for prenatal developmental toxicology studies involving both common and rare fetal defects.
Subject(s)
Fetus , Prenatal Care , Animals , Female , Pregnancy , Correlation of Data , Incidence , Litter SizeABSTRACT
Ionic liquids (ILs) are synthetic solvents used as replacements for volatile organic solvents. Human exposure occurs through dermal or oral routes. In rodents, several ILs were reported to induce dermal toxicity, irritation, and sensitization. Due to the potential for occupational exposure, and industrial use as nonvolatile solvents, 1-ethyl-3-methylimidazolium chloride (EMIM, 6.25% to 50% v/v), 1-butyl-3-methylimidazolium chloride (BMIM, 3.12% to 12.5% v/v), 1-butyl-1-methylpyrrolidinium chloride (BMPY, 0.825% to 6.25% v/v), and N-butylpyridinium chloride (NBuPY, 0.825% to 12.5% v/v) were nominated to the National Toxicology Program and evaluated for skin sensitization. The test compound was applied to the ears of female BALB/c mice daily for 3 days in a primary irritancy (IRR)/local lymph node assay (LLNA). Sensitization was assessed in vitro in the direct peptide reactivity assay (DPRA), KeratinoSens™ assay, and human cell line activation test (h-CLAT). In the LLNA, the butylated ILs, BMIM, and BMPY were more potent than NBuPY (butylated) or EMIM (ethylated), which was neither an irritant nor a sensitizer. NBuPY induced skin irritation in vivo at ≥3.12% (p ≤ 0.01), and sensitization in vitro in the KeratinoSens™ assay and h-CLAT, but was negative for sensitization in vivo and in the DPRA. Although SI3 was not achieved, dermal treatment with 12.5% BMIM or 6.25% BMPY increased (p ≤ 0.01) lymph node cell proliferation in the LLNA. In vitro, BMIM was positive for sensitization in the h-CLAT, and BMPY was positive in the h-CLAT and KeratinoSens™ assay; both were negative in the DPRA. Integrated data analyses, weighted toward in vivo data, suggested that BMIM and BMPY may induce weak to mild sensitization.
Subject(s)
Chlorides/adverse effects , Dermatitis, Allergic Contact/etiology , Ionic Liquids/adverse effects , Skin/drug effects , Animals , Female , Mice , Mice, Inbred BALB CABSTRACT
The National Toxicology Program (NTP) now uses an extended longitudinal sectioning protocol for the uterus to better evaluate female rodent reproductive tract toxicity for all developmental and reproductive toxicology and 2-year toxicity and carcinogenicity bioassays. The previous protocol for toxicity/carcinogenicity studies involved 1 cross section midway through each uterine horn and collection of uterine cervix and vagina only if gross lesions were present. Here we compare the histological findings of the original cross sections with the additional longitudinal sections of residual uterine tissues of 7 chronic NTP rat bioassays. The goal of this study was to determine whether there might be any advantages to examining additional uterine tissue. The longitudinal protocol allowed for 10 to 20 times more uterine tissue for evaluation. Results indicate that the potential advantages of a more complete evaluation of female reproductive tract tissue include increased detection of reproductive targets, increased detection of neoplastic and nonneoplastic lesions, improved detection of tissue origin of neoplasms, less reliance on gross identification of lesions, improved accuracy in the application of severity grades, and increased detection of preneoplastic or subtle lesions.
Subject(s)
Neoplasms , Reproduction , Animals , Biological Assay , Carcinogenicity Tests , Female , Histological Techniques , Rats , UterusABSTRACT
Quantitative high throughput screening (qHTS) experiments can generate 1000s of concentration-response profiles to screen compounds for potentially adverse effects. However, potency estimates for a single compound can vary considerably in study designs incorporating multiple concentration-response profiles for each compound. We introduce an automated quality control procedure based on analysis of variance (ANOVA) to identify and filter out compounds with multiple cluster response patterns and improve potency estimation in qHTS assays. Our approach, called Cluster Analysis by Subgroups using ANOVA (CASANOVA), clusters compound-specific response patterns into statistically supported subgroups. Applying CASANOVA to 43 publicly available qHTS data sets, we found that only about 20% of compounds with response values outside of the noise band have single cluster responses. The error rates for incorrectly separating true clusters and incorrectly clumping disparate clusters were both less than 5% in extensive simulation studies. Simulation studies also showed that the bias and variance of concentration at half-maximal response (AC50 ) estimates were usually within 10-fold when using a weighted average approach for potency estimation. In short, CASANOVA effectively sorts out compounds with "inconsistent" response patterns and produces trustworthy AC50 values.
ABSTRACT
BACKGROUND: Dust mite allergens can induce allergic sensitization and exacerbate asthma symptoms. Although dust mite reduction and control strategies exist, few asthmatics employ them. OBJECTIVES: We examined whether an in-home test kit, which quantifies dust mite allergen levels, resulted in behavioral changes in implementation and maintenance of mite reduction strategies and helped reduce allergen levels in homes of dust mite-sensitive children. METHODS: We enrolled 60 households of children aged 5-15 with parent-reported dust mite allergy into a randomized controlled trial. Intervention homes (N = 30) received educational material about reducing dust mites and test kits at 1, 2, 5 and 8 months. Control homes (N = 30) received only educational material. At baseline, 6 and 12 months, study staff visited all homes, collected dust samples from three locations and obtained information about parents' mite reduction behaviors by questionnaire. Allergen concentrations (Der f 2/Der p2) in dust were assessed by immunoassays. After adjusting for visit and location, allergen concentrations in intervention and control homes were compared using mixed effects model analysis. RESULTS: In the intervention homes, allergen concentrations in the child's bedroom and living room floors were significantly reduced over time compared to control homes. Although not all location-specific differences in allergen concentrations were statistically significant, combining data across locations, there was a differential reduction in allergen concentrations in the intervention group versus the control group (p = 0.02). CONCLUSION: The use of in-home test kits along with education may beneficially influence behaviors and attitudes toward dust mite reduction strategies and help reduce residential dust mite allergen levels.
Subject(s)
Air Pollution, Indoor/prevention & control , Allergens/analysis , Antigens, Dermatophagoides/analysis , Arthropod Proteins/analysis , Cysteine Endopeptidases/analysis , Dust/analysis , Environmental Monitoring/instrumentation , Adolescent , Air Pollution, Indoor/analysis , Child , Child, Preschool , Health Education , Housing , Humans , Pilot ProjectsABSTRACT
The National Toxicology Program (NTP) has historically used Fischer 344/N (F344/N) rats for the majority of its bioassays. Recently the NTP began using the Harlan Sprague Dawley (SD) as the primary rat model for NTP studies. The NTP had previously used female SD rats in nine bioassays. This article compares historical control (HC) tumor incidence rates from these nine SD rat studies with HC tumor rates from matched NTP F344/N rat bioassays to identify similarities and differences. Matching on sex, laboratory, diet, and route led to nine comparable F344/N rat studies. Our analyses revealed statistically significant strain differences, with female SD rats having lower incidence rates for clitoral gland adenoma (0.2% vs. 5.8%) and mononuclear cell leukemia (0.9% vs. 16.7%) and higher incidence rates for mammary gland fibroadenoma (67.4% vs. 48.4%), mammary gland carcinoma (10.2% vs. 2.4%), and thyroid gland C cell adenoma (25.4% vs. 13.6%) relative to female F344/N rats. These represent five of the seven most common tumor types among female SD and F344/N rats in the NTP HC database. When vehicle was included as an additional matching criterion, the number of comparable F344/N rat studies dropped to four, but similar results were obtained.
Subject(s)
Carcinogenicity Tests/methods , Neoplasms/epidemiology , Neoplasms/veterinary , Rats, Inbred F344 , Rats, Sprague-Dawley , Animals , Carcinogenicity Tests/standards , Female , Incidence , Neoplasms/genetics , RatsABSTRACT
A bootstrap based methodology is introduced for analyzing repeated measures/longitudinal microarray gene expression data over ordered categories. The proposed non-parametric procedure uses order-restricted inference to compare gene expressions among ordered experimental conditions. The null distribution for determining significance is derived by suitably bootstrapping the residuals. The procedure addresses two potential sources of correlation in the data, namely, (a) correlations among genes within a chip ("intra-chip" correlation), and (b) correlation within subject due to repeated/longitudinal measurements ("temporal" correlation). To make the procedure computationally efficient, the adaptive bootstrap methodology of Guo and Peddada (2008) is implemented such that the resulting procedure controls the false discovery rate (FDR) at the desired nominal level.
ABSTRACT
BACKGROUND: For gene expression data obtained from a time-course microarray experiment, Liu et al. developed a new algorithm for clustering genes with similar expression profiles over time. Performance of their proposal was compared with three other methods including the order-restricted inference based methodology of Peddada et al. In this note we point out several inaccuracies in Liu et al. and conclude that the order-restricted inference based methodology of Peddada et al. (programmed in the software ORIOGEN) indeed operates at the desired nominal Type 1 error level, an important feature of a statistical decision rule, while being computationally substantially faster than indicated by Liu et al. RESULTS: Application of ORIOGEN to the well-known breast cancer cell line data of Lobenhofer et al. revealed that ORIOGEN software took only 21 minutes to run (using 100,000 bootstraps with p = 0.0025), substantially faster than the 72 hours found by Liu et al. using Matlab. Also, based on a data simulated according to the model and parameters of simulation 1 (sigma2 = 1, M = 5) in [1] we found that ORIOGEN took less than 30 seconds to run in stark contrast to Liu et al. who reported that their implementation of the same algorithm in R took 2979.29 seconds. Furthermore, for the simulation studies reported in [1], unlike the claims made by Liu et al., ORIOGEN always maintained the desired false positive rate. According to Figure three in Liu et al. their algorithm had a false positive rate ranging approximately from 0.20 to 0.70 for the scenarios that they simulated. CONCLUSIONS: Our comparisons of run times indicate that the implementations of ORIOGEN's algorithm in Matlab and R by Liu et al. is inefficient compared to the publicly available JAVA implementation. Our results on the false positive rate of ORIOGEN suggest some error in Figure three of Liu et al., perhaps due to a programming error.