Colonization of the intestinal tract by Candida albicans (C. albicans) can lead to invasive candidiasis. Therefore, a functional intestinal epithelial barrier is critical for protecting against invasive C. albicans infections. We collected fecal samples from patients with Candida albicans bloodstream infection and healthy people. Through intestinal flora 16sRNA sequencing and intestinal metabolomic analysis, we found that C. albicans infection resulted in a significant decrease in the expression of the metabolite kynurenic acid (KynA). We used a repeated C. albicans intestinal infection mouse model, established following intake of 3% dextran sulfate sodium salt (DSS) for 9 days, and found that KynA, a tryptophan metabolite, inhibited inflammation, promoted expression of intestinal tight junction proteins, and protected from intestinal barrier damage caused by invasive Candida infections. We also demonstrated that KynA activated aryl hydrocarbon receptor (AHR) repressor in vivo and in vitro. Using Caco-2 cells co-cultured with C. albicans, we showed that KynA activated AHR, inhibited the myosin light chain kinase-phospho-myosin light chain (MLCK-pMLC) signaling pathway, and promoted tristetraprolin (TTP) expression to alleviate intestinal inflammation. Our findings suggest that the metabolite KynA which is differently expressed in patients with C. albicans infection and has a protective effect on the intestinal epithelium, via activating AHR, could be explored to provide new potential therapeutic strategies for invasive C. albicans infections.
The present study aimed to explore the potential mechanism of the effect of hyperbaric oxygenation (HBO) preconditioning on cerebral ischemia and reperfusion injury (CIRI). GSE23160 dataset was used to identify differentially expressed genes (DEGs) from striatum between the middle cerebral artery occlusion (MCAO)/reperfusion and sham rats. The gene clusters with continuous increase and decrease were identified by soft clustering analysis in Mfuzz, and functional enrichment analysis of these genes was performed using clusterProfiler package. The intersection set of the genes with significantly altered expression at post-reperfusion 2, 8, and 24 h were screened in comparison to 0 h (sham group), and the expression of these genes was detected in the MCAO/reperfusion model and HBO preconditioning groups by real-time PCR (RT-PCR) and western blotting. A total of 41 upregulated DEGs, and 7 downregulated DEGs were detected, among which the expression of Gpr84 and Ggta1 was significantly upregulated at each reperfusion phase as compared to the sham group, while the expression of Kcnk3 was significantly downregulated except in the postreperfusion 8 h in the striatum group. RT-PCR and western blotting analyses showed that the expression of Ggta1, Gpr84, and Kcnk3 genes between the MCAO/reperfusion and sham rats were consistent with the bioinformatics analysis. In addition, the HBO preconditioning reduced the expression of Ggta1 and Gpr84 and increased the expression of Kcnk3 in MCAO/reperfusion rats. Kcnk3, Ggta1, and Gpr84 may play a major role in HBO-mediated protection of the brain against CIRI.
Soil shear strength is an important indicator of soil erosion sensitivity and the tillage performance of the cultivated layer. Measuring soil shear strength at a field scale is difficult, time-consuming, and costly. This study proposes a new method to predict soil shear strength parameters (cohesion and internal friction angle) by combining cone penetration test (CPT) data and soil properties. A portable CPT measuring device with two pressure sensors was designed to collect two CPT data in farmland, namely cone tip resistance, and cone side pressure. Direct shear tests were performed in the laboratory to determine the soil shear strength parameters for 83 CPT data collection points. Two easily available soil properties (water content and bulk density) were determined via the oven-drying method. Using the two CPT data and the two soil properties as predictors, three machine learning (ML) models were built for predicting soil cohesion and the internal friction angle, including backpropagation neural network (BPNN), partial least squares regression (PLSR), and support vector regression (SVR). The prediction performance of each model was evaluated using the coefficient of determination (R2), the root-mean-square error (RMSE), and the relative error (RE). The results suggested that among all the evaluated models, the BPNN model was the most suitable prediction model for soil cohesion, and the SVR model performed best in predicting soil internal friction angle. Thus, our findings provide a foundation for the convenient and low-cost measurement of soil shear strength parameters.
Heart diseases such as myocardial infarction and myocardial ischemia are paroxysmal and fatal in clinical practice. Cardiomyocytes (CMs) differentiated from human pluripotent stem cells provide a promising approach to myocardium regeneration therapy. Identifying the maturity level of human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs) is currently the main challenge for pathophysiology and therapeutics. In this review, we describe current maturity indicators for cardiac microtissue and microdevice cultivation technologies that accelerate cardiac maturation. It may provide insights into regenerative medicine, drug cardiotoxicity testing, and preclinical safety testing.
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