Insects use taste to evaluate food, hosts, and mates. Drosophila has many “orphan” taste neurons that express no known taste receptors. The Ionotropic Receptor (IR) superfamily is best known for its role in olfaction, but virtually nothing is known about a clade of ~35 members, the IR20a clade. Here, a comprehensive analysis of this clade reveals expression in all taste organs of the fly. Some members are expressed in orphan taste neurons, whereas others are coexpressed with bitter- or sugar-sensing Gustatory receptor (Gr) genes. Analysis of the closely related IR52c and IR52d genes reveals signatures of adaptive evolution, roles in male mating behavior, and sexually dimorphic expression in neurons of the male foreleg, which contacts females during courtship. These neurons are activated by conspecific females and contact a neural circuit for sexual behavior. Together, these results greatly expand the repertoire of candidate taste and pheromone receptors in the fly.

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Abstract Objective To conduct a systematic scoping review of explainable artificial intelligence (XAI) models that use real-world electronic health record data, categorize these techniques according to different biomedical applications, identify gaps of current studies, and suggest future research directions. Materials and Methods We searched MEDLINE, IEEE Xplore, and the Association for Computing Machinery (ACM) Digital Library to identify relevant papers published between January 1, 2009 and May 1, 2019. We summarized these studies based on the year of publication, prediction tasks, machine learning algorithm, dataset(s) used to build the models, the scope, category, and evaluation of the XAI methods. We further assessed the reproducibility of the studies in terms of the availability of data and code and discussed open issues and challenges. Results Forty-two articles were included in this review. We reported the research trend and most-studied diseases. We grouped XAI methods into 5 categories: knowledge distillation and rule extraction (N = 13), intrinsically interpretable models (N = 9), data dimensionality reduction (N = 8), attention mechanism (N = 7), and feature interaction and importance (N = 5). Discussion XAI evaluation is an open issue that requires a deeper focus in the case of medical applications. We also discuss the importance of reproducibility of research work in this field, as well as the challenges and opportunities of XAI from 2 medical professionals’ point of view. Conclusion Based on our review, we found that XAI evaluation in medicine has not been adequately and formally practiced. Reproducibility remains a critical concern. Ample opportunities exist to advance XAI research in medicine.

LncRNAs were a group of RNAs, which can be a regulator or master in biological activities of cancer cells. HIF1A-AS2 belongs to this group, and it has been verified to be able to affect cell activities in several kinds of cancers. In this study, we tried to study the functions of HIF1A-AS2 exerted in colorectal cancer. In order to clearly know about the expression of HIF1A-AS2, miR-129-5p and DNMT3A in CRC tissues and cells, we employed qRT-PCR. The relevance among those three genes was examined by the use of Pearson correlation analysis. With the aid of bioinformatics analysis and dual luciferase reporter assays, the combinations between them were verified one by one MTT, colony formation trans-well and western blotting, immunofluorescence, all those assays reflected a fact that as a ceRNA, HIF1A-AS2 could directly bind with miR-129-5p, and could positively affect cell proliferation, invasion and EMT formation by regulation of the expression of miR-129-5p and DNMT3A. Therefore, we obtained a conclusion that HIF1A-AS2 exerted the oncogenic functions in CRC through regulating miR-129-5p/DNMT3A axis, which indicates that HIF1A-AS2 might be a useful therapeutic target in CRC.