Artificial Intelligence in Toxicological Pathology: Quantitative Evaluation of Compound-Induced Follicular Cell Hypertrophy in Rat Thyroid Gland Using Deep Learning Models.

Digital pathology has recently been more broadly deployed, fueling artificial intelligence (AI) application development and more systematic use of image analysis. Here, two different AI models were developed to evaluate follicular cell hypertrophy in hematoxylin and eosin-stained whole-slide-images of rat thyroid gland, using commercial AI-based-software. In the first, mean cytoplasmic area measuring approach (MCA approach), mean cytoplasmic area was calculated via several sequential deep learning (DL)-based algorithms including segmentation in microanatomical structures (separation of colloid and stroma from thyroid follicular epithelium), nuclear detection, and area measurements. With our additional second, hypertrophy area fraction predicting approach (HAF approach), we present for the first time DL-based direct detection of the histopathological change follicular cell hypertrophy in the thyroid gland with similar results. For multiple studies, increased output parameters (mean cytoplasmic area and hypertrophic area fraction) were shown in groups given different hypertrophy-inducing reference compounds in comparison to control groups. Quantitative results correlated with the gold standard of board-certified veterinary pathologists' diagnoses and gradings as well as thyroid hormone dependent gene expressions. Accuracy and repeatability of diagnoses and grading by pathologists are expected to be improved by additional evaluation of mean cytoplasmic area or direct detection of hypertrophy, combined with standard histopathological observations.

Artificial Intelligence in Toxicologic Pathology: Quantitative Evaluation of Compound-Induced Hepatocellular Hypertrophy in Rats.

Digital pathology evolved rapidly, enabling more systematic usage of image analysis and development of artificial intelligence (AI) applications. Here, combined AI models were developed to evaluate hepatocellular hypertrophy in rat liver, using commercial AI-based software on hematoxylin and eosin-stained whole slide images. In a first approach, deep learning-based identification of critical tissue zones (centrilobular, midzonal, and periportal) enabled evaluation of region-specific cell size. Mean cytoplasmic area of hepatocytes was calculated via several sequential algorithms including segmentation in microanatomical structures (separation of sinusoids and vessels from hepatocytes), nuclear detection, and area measurements. An increase in mean cytoplasmic area could be shown in groups given phenobarbital, known to induce hepatocellular hypertrophy when compared to control groups, in multiple studies. Quantitative results correlated with the gold standard: observation and grading performed by board-certified veterinary pathologists, liver weights, and gene expression. Furthermore, as a second approach, we introduce for the first time deep learning-based direct detection of hepatocellular hypertrophy with similar results. Cell hypertrophy is challenging to pick up, particularly in milder cases. Additional evaluation of mean cytoplasmic area or direct detection of hypertrophy, combined with histopathological observations and liver weights, is expected to increase accuracy and repeatability of diagnoses and grading by pathologists.

Report from the BfR expert hearing on practicability of hormonal measurements: recommendations for experimental design of toxicological studies with integrated hormonal end points.

This publication summarizes discussions that were held during an international expert hearing organized by the German Federal Institute for Risk Assessment (BfR) in Berlin, Germany, in October 2017. The expert hearing was dedicated to providing practical guidance for the measurement of circulating hormones in regulatory toxicology studies. Adequate measurements of circulating hormones have become more important given the regulatory requirement to assess the potential for endocrine disrupting properties for all substances covered by the plant protection products and biocidal products regulations in the European Union (EU). The main focus was the hypothalamus-pituitary-thyroid axis (HPT) and the hypothalamus-pituitary-gonadal axis (HPG). Insulin, insulin-like growth factor 1 (IGF-1), parathyroid hormone (PTH) and vitamins A and D were also discussed. During the hearing, the experts agreed on specific recommendations for design, conduct and evaluation of acceptability of studies measuring thyroid hormones, thyroid stimulating hormone and reproductive hormones as well as provided some recommendations for insulin and IGF-1. Experts concluded that hormonal measurements as part of the test guidelines (TGs) of the Organisation for Economic Co-operation and Development (OECD) were necessary on the condition that quality criteria to guarantee reliability and reproducibility of measurements are adhered to. Inclusion of the female reproductive hormones in OECD TGs was not recommended unless the design of the study was modified to appropriately measure hormone concentrations. The current report aims at promoting standardization of the experimental designs of hormonal assays to allow their integration in OECD TGs and highlights research needs for better identification of endocrine disruptors using hormone measurements.

Liverbeads: a practical and relevant in vitro model for gene induction investigations.

Cryopreserved rat hepatocytes entrapped within an alginate matrix, commercially available as Liverbeads, were evaluated for their relevance as a screening tool for gene induction in vitro, using quantitative real-time reverse transcriptase-polymerase chain reaction. They were treated with the reference compounds beta-naphthoflavone (BNF), phenobarbital (PB), pregnenolone 16alpha-carbonitrile (PCN), and clofibric acid (CLO) and analyzed for mRNA levels of Cyp1a1, Cyp2b1, Cyp3a1, Cyp4a1, Ugt1a6, and Ugt2b1. In addition, for PB and PCN, the results were compared with those obtained in rat liver in vivo. For each inducer, the gene induction profiles obtained with the Liverbeads in vitro model were time- and dose-dependent. The in vitro gene expression profiles confirmed the corresponding known P450 and UGT induction by each reference compound. In particular, the most strongly induced genes were Cyp1a1 by BNF, Cyp2b1 by PB, Cyp3a1 and Ugt2b1 by PCN, and Cyp4a1 and Cyp2b1 by CLO. Other genes investigated were also induced by the reference compounds, but the expression levels were lower, and increases were seen only after prolonged treatment. In particular, Ugt1a6 and Cyp2b1 were increased by BNF, Cyp1a1, Cyp3a1, and Ugt2b1 by PB, and Cyp3a1 and Ugt2b1 by CLO. All of these results correlated well with published in vitro data and our in vivo data. In conclusion, our results suggest that Liverbeads is a relevant and useful in vitro screening tool for determining gene induction profiles of new molecules. In addition, because Liverbeads from different species are available, this tool offers the possibility to conduct interspecies comparisons.

MicroRNA-375/SEC23A as biomarkers of the in vitro efficacy of vandetanib.

In this study, we performed microRNA (miRNA) expression profiling on a large series of sporadic and hereditary forms of medullary thyroid carcinomas (MTC). More than 60 miRNAs were significantly deregulated in tumor vs adjacent non-tumor tissues, partially overlapping with results of previous studies. We focused our attention on the strongest up-regulated miRNA in MTC samples, miR-375, the deregulation of which has been previously observed in a variety of human malignancies including MTC. We identified miR-375 targets by combining gene expression signatures from human MTC (TT) and normal follicular (Nthy-ori 3-1) cell lines transfected with an antagomiR-375 inhibitor or a miR-375 mimic, respectively, and from an in silico analysis of thyroid cell lines of Cancer Cell Line Encyclopedia datasets. This approach identified SEC23A as a bona fide miR-375 target, which we validated by immunoblotting and immunohistochemistry of non-tumor and pathological thyroid tissue. Furthermore, we observed that miR-375 overexpression was associated with decreased cell proliferation and synergistically increased sensitivity to vandetanib, the clinically relevant treatment of metastatic MTC. We found that miR-375 increased PARP cleavage and decreased AKT phosphorylation, affecting both cell proliferation and viability. We confirmed these results through SEC23A direct silencing in combination with vandetanib, highlighting the importance of SEC23A in the miR-375-associated increased sensitivity to vandetanib.Since the combination of increased expression of miR-375 and decreased expression of SEC23A point to sensitivity to vandetanib, we question if the expression levels of miR-375 and SEC23A should be evaluated as an indicator of eligibility for treatment of MTC patients with vandetanib.