This study developed a novel classification scheme to assign chemicals to a verifiable mechanism of (eco-)toxicological action to allow for grouping, read-across, and model generation. The new classification scheme unifies and extends existing schemes and has, at its heart, direct reference to molecular initiating events (MIEs) promoting adverse outcomes. The scheme is based on three broad domains of toxic action representing nonspecific toxicity (e.g., narcosis), reactive mechanisms (e.g., electrophilicity and free radical action), and specific mechanisms (e.g., associated with enzyme inhibition). The scheme is organized at three further levels of detail beyond broad domains to separate out the mechanistic group, specific mechanism, and the MIEs responsible. The novelty of this approach comes from the reference to taxonomic diversity within the classification, transparency, quality of supporting evidence relating to MIEs, and that it can be updated readily.
BACKGROUND The configuration of the hepatic arteries is known to vary substantially between individuals. Here, we report a rare retroperitoneal configuration of an accessory hepatic artery existing alongside a left and right hepatic artery branching from the proper hepatic artery. During routine dissection, we discovered an anomalous configuration of the hepatic arteries that does not fit the commonly used categorizations for abnormal hepatic vasculature.
The is an independent lichenized lineage within the comprising . 390 species and 50 genera. Very few studies have dealt with family and genus classification using molecular data and many groups are in need of thorough revision.
Lung cancer is the dominant cause of worldwide cancer mortality. The relationship between pesticide exposure and lung cancer risk has shown mixed results epidemiologically. We hypothesized this discrepancy could arise from the varying effects of different pesticides and conducted this meta-analysis by using three pesticide classification schemes to examine the implications of diverse pesticide exposure types on lung cancer risk.
High-throughput sequencing has exponentially increased peptide sequences, necessitating a computational method to identify multi-functional therapeutic peptides (MFTP) from their sequences. However, existing computational methods are challenged by class imbalance, particularly in learning effective sequence representations. To address this, we propose PSCFA, a prototypical supervised contrastive learning with a feature augmentation method for MFTP prediction.
Background: Capecitabine, a prodrug of 5-fluorouracil, is extensively utilized for the treatment of metastatic breast cancer, colorectal cancer, and gastric cancer. Nevertheless, there exist limitations in comprehending adverse reactions (AEs) in clinical practice. In this study, we investigated the distribution of AEs associated with capecitabine and explored potential rare adverse reactions by mining the Food and Drug Administration Adverse Event Reporting System (FAERS).
