BackgroundComparative analysis of tissue-specific transcriptomes is a powerful technique to uncover tissue functions. Our FlyAtlas.org provides authoritative gene expression levels for multiple tissues of Drosophila melanogaster (1). Although the main use of such resources is single gene lookup, there is the potential for powerful meta-analysis to address questions that could not easily be framed otherwise. Here, we illustrate the power of data-mining of FlyAtlas data by comparing epithelial transcriptomes to identify a core set of highly-expressed genes, across the four major epithelial tissues (salivary glands, Malpighian tubules, midgut and hindgut) of both adults and larvae.MethodParallel hypothesis-led and hypothesis-free approaches were adopted to identify core genes that underpin insect epithelial function. In the former, gene lists were created from transport processes identified in the literature, and their expression profiles mapped from the flyatlas.org online dataset. In the latter, gene enrichment lists were prepared for each epithelium, and genes (both transport related and unrelated) consistently enriched in transporting epithelia identified.ResultsA key set of transport genes, comprising V-ATPases, cation exchangers, aquaporins, potassium and chloride channels, and carbonic anhydrase, was found to be highly enriched across the epithelial tissues, compared with the whole fly. Additionally, a further set of genes that had not been predicted to have epithelial roles, were co-expressed with the core transporters, extending our view of what makes a transporting epithelium work. Further insights were obtained by studying the genes uniquely overexpressed in each epithelium; for example, the salivary gland expresses lipases, the midgut organic solute transporters, the tubules specialize for purine metabolism and the hindgut overexpresses still unknown genes.ConclusionTaken together, these data provide a unique insight into epithelial function in this key model insect, and a framework for comparison with other species. They also provide a methodology for function-led datamining of FlyAtlas.org and other multi-tissue expression datasets.

BackgroundThe triglyceride glucose (TyG) index, which is a new surrogate indicator of insulin resistance (IR), is thought to be associated with many diseases, such as cardiovascular disease, but its relationship with cerebrovascular disease is still controversial.MethodsThe PubMed, EMBASE, Cochrane Library, Web of Science and Medline databases were searched until March 2022 to evaluate the association between the TyG index and cerebrovascular disease risk. A random‒effects model was used to calculate the effect estimates and 95% confidence intervals (CIs).ResultsA total of 19 cohort studies and 10 case‒control/cross‒sectional studies were included in our study, which included 11,944,688 participants. Compared with a low TyG index, a higher TyG index increased the risk of cerebrovascular disease (RR/HR = 1.22, 95% CI [1.14, 1.30], P<  0.001; OR = 1.15, 95% CI [1.07, 1.23], P<  0.001). Furthermore, the results of the dose-response analysis of the cohort study demonstrated that the risk of cerebrovascular disease increased by 1.19 times per 1 mg/dl increment of the TyG index (relative risk = 1.19, 95% CI [1.13,1.25], P<  0.001).ConclusionTyG index is related to cerebrovascular disease. More data and basic research are needed to confirm the association.