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The current knowledge of Staphylococcus warneri phages is limited, with few genomes sequenced and characterized. In this study, a prophage, vB_G30_01, isolated from Staphylococcus warneri G30 was characterized and evaluated for its lysogenic host range. The phage was studied using transmission electron microscopy and a host range. The phage genome was sequenced and characterized in depth, including phylogenetic and taxonomic analyses. The linear dsDNA genome of vB_G30_01 contains 67 predicted open reading frames (ORFs), classifying it within Bronfenbrennervirinae. With a total of 10 ORFs involved in DNA replication-related and transcriptional regulator functions, vB_G30_01 may play a role in the genetics and transcription of a host. Additionally, vB_G30_01 possesses a complete set of genes related to host lysogeny and lysis, implying that vB_G30_01 may influence the survival and adaptation of its host. Furthermore, a comparative genomic analysis reveals that vB_G30_01 shares high genomic similarity with other Staphylococcus phages and is relatively closely related to those of Exiguobacterium and Bacillus, which, in combination with the cross-infection assay, suggests possible cross-species infection capabilities. This study enhances the understanding of Staphylococcus warneri prophages, providing insights into phage–host interactions and potential horizontal gene transfer. [ABSTRACT FROM AUTHOR]

Tuberculosis (TB) is a global infectious threat, and the emergence of multidrug-resistant TB has become a major challenge in eradicating the disease that requires the discovery of new treatment strategies. This study aimed to elucidate the immune infiltration and molecular regulatory network of T cell-interacting activating receptors on myeloid cell 1 (TARM1)-related genes based on a bioinformatics analysis. The GSE114911 dataset was obtained from the Gene Expression Omnibus (GEO) and screened to identify 17 TARM1-related differentially expressed genes (TRDEGs). Genes interacting with the TRDEGs were analyzed using a Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. A gene set enrichment analysis (GSEA) was used to identify the biological pathways significantly associated with a Mycobacterium tuberculosis (Mtb) infection. The key genes were obtained based on Cytoscape's cytoHubba plug-in. Furthermore, protein–protein interaction (PPI) networks were analyzed through STRING, while mRNA–RNA-binding protein (RBP) and mRNA–transcription factor (TF) interaction networks were developed utilizing the StarBase v3.0 and ChIPBase databases. In addition, the diagnostic significance of key genes was evaluated via receiver operating characteristic (ROC) curves, and the immune infiltration was analyzed using an ssGSEA and MCPCounter. The key genes identified in the GSE114911 dataset were confirmed in an independent GSE139825 dataset. A total of seventeen TRDEGs and eight key genes were obtained in a differential expression analysis using the cytoHubba plug-in. Through the GO and KEGG analysis, it was found that these were involved in the NF-κB, PI3K/Akt, MAPK, and other pathways related to inflammation and energy metabolism. Furthermore, the ssGSEA and MCPCounter analysis revealed a significant rise in activated T cells and T helper cells within the Mtb infection group, which were markedly associated with these key genes. This implies their potential significance in the anti-Mtb response. In summary, our results show that TRDEGs are linked to inflammation, energy metabolism, and immune cells, offering fresh insights into the mechanisms underlying TB pathogenesis and supporting further investigation into the possible molecular roles of TARM1 in TB, as well as assisting in the identification of prospective diagnostic biomarkers. [ABSTRACT FROM AUTHOR]

Observational studies indicate that variations in peripheral blood mononuclear cell (PBMC) subsets are associated with an increased risk of pulmonary tuberculosis (PTB) and coronavirus disease 2019 (COVID-19), but causal validation is lacking. Here, we combined single-cell expression quantitative trait locus (sc-eQTL) and two-sample mendelian randomization (MR) analyses to elucidate the causal relationship between PBMC subsets and the occurrence of PTB and COVID-19 and verified by RT-qPCR. We observed an increase in the CD4+ Effective Memory T Cell (CD4+ TEM) cluster in both PTB and COVID-19 patients according to the single-cell transcriptional landscape of PBMC. Through MR analysis using an inverse variance weighted (IVW) method, we found strong evidence of positive correlations between CD4+ TEM cell markers (GBP2, TRAV1-2, and ODF2L) and PTB, and between markers (LAG3 and SLFN5) and COVID-19, especially highlighted by lead eQTL-SNPs of GBP2 (rs2256752, p = 4.76321 × 10−15) and LAG3 (rs67706382, p = 6.16× 10−16). Similar results were observed in validation sets, and no pleiotropy was detected in sensitivity analyses including weighted median (WM), MR-Egger, MR-pleiotropy residual sum and outlier, and leave-one-out analyses (all p > 0.05). We visualized the colocalization of marker-eQTLs and markers of PTB and COVID-19 genome-wide association study (GWAS) associations. Based on CellChat analyses, monocytes communicated predominantly with CD4+ TEM cells positively expressing PTB markers (GBP2, TRAV1-2, and ODF2L) and COVID-19 markers (LAG3 and SLFN5) in both PTB and COVID-19. Our data suggest a causal effect between two key CD4+ TEM cell markers (GBP2 and LAG3) and the risk for PTB and COVID-19 infection. Our findings provide novel insights into the biological mechanism for PTB and COVID-19 infection, but future single-cell studies are necessary to further enhance understanding of this find. [ABSTRACT FROM AUTHOR]

A dual NIR fluorescent probe Cy-ND is developed for viscosity sensing with λex/em = 766/806 nm, making it apt for biological analysis, whose response is validated through DFT and TDDFT computations. Cy-ND successfully detected viscosity changes amidst acute alcohol-induced liver injury and liver ischemia-reperfusion injury. [ABSTRACT FROM AUTHOR]

Lung cancer is a kind of malignant tumor with high morbidity and poor prognosis, and non-small cell lung cancer is in the majority. Some indications other than anatomical changes, can be helpful for monitoring disease progress. Inflammation is closely related to non-small cell lung cancer. Inflammatory indexes based on common peripheral blood cells and C-reactive protein are of great prognostic value. In this paper, we review the articles about the prognostic value of inflammation indexes in peripheral blood, to understand related research status scientifically, comprehensively and objectively.

To improve the simulation performance of the RegCM4 model in climate simulations over the Yangtze River Basin (YRB), it is essential to determine the optimal cumulus convection and land surface process schemes from the numerous physical parameterization options within RegCM4. In this study, we selected five cumulus convection schemes (Kuo, Grell, Emanuel, Tiedtke, and Kain–Fritsch) and three land surface process schemes (BATS, CLM3.5, and CLM4.5) to configure 72 mixed schemes. Four years of short-term simulations (1990–1993) with a horizontal resolution of 50 km were conducted using ERA-Interim as the initial and boundary conditions for the 72 schemes. The climate simulation performance of all schemes in the YRB was comprehensively evaluated using a multi-criteria scoring approach. The results indicate that among the selected cumulus convection schemes, the Kain–Fritsch scheme, applied to both ocean and land, demonstrates optimal performance in simulating precipitation over the YRB, with spatial correlation coefficients between simulated and observed annual precipitation around 0.3. Compared to the Community Land Models (CLM3.5 and CLM4.5), BATS exhibits superior capabilities in reproducing the temperature features of the region, with spatial correlation coefficients between simulated and observed values typically exceeding 0.99 and standard deviations within 1.25 °C. Under the optimal KF scheme, the simulated soil moisture in the YRB using CLMs is notably drier, ranging from −7.79 to −8.39 kg/m2, compared to that achieved with BATS. The findings provide a localized reference for the parameterization schemes of RegCM4 in the YRB. [ABSTRACT FROM AUTHOR]