Iron-related gene mutations driving global Mycobacterium tuberculosis transmission revealed by whole-genome sequencing.

BACKGROUND: Iron plays a crucial role in the growth of Mycobacterium tuberculosis (M. tuberculosis). However, the precise regulatory mechanism governing this system requires further elucidation. Additionally, limited studies have examined the impact of gene mutations related to iron on the transmission of M. tuberculosis globally. This research aims to investigate the correlation between mutations in iron-related genes and the worldwide transmission of M. tuberculosis. RESULTS: A total of 13,532 isolates of M. tuberculosis were included in this study. Among them, 6,104 (45.11%) were identified as genomic clustered isolates, while 8,395 (62.04%) were classified as genomic clade isolates. Our results showed that a total of 12 single nucleotide polymorphisms (SNPs) showed a positive correlation with clustering, such as Rv1469 (ctpD, C758T), Rv3703c (etgB, G1122T), and Rv3743c (ctpJ, G676C). Additionally, seven SNPs, including Rv0104 (T167G, T478G), Rv0211 (pckA, A302C), Rv0283 (eccB3, C423T), Rv1436 (gap, G654T), ctpD C758T, and etgB C578A, demonstrated a positive correlation with transmission clades across different countries. Notably, our findings highlighted the positive association of Rv0104 T167G, pckA A302C, eccB3 C423T, ctpD C758T, and etgB C578A with transmission clades across diverse regions. Furthermore, our analysis identified 78 SNPs that exhibited significant associations with clade size. CONCLUSIONS: Our study reveals the link between iron-related gene SNPs and M. tuberculosis transmission, offering insights into crucial factors influencing the pathogenicity of the disease. This research holds promise for targeted strategies in prevention and treatment, advancing research and interventions in this field.

Blood metabolites and chronic kidney disease: a Mendelian randomization study.

BACKGROUND: Human blood metabolites have demonstrated close associations with chronic kidney disease (CKD) in observational studies. Nonetheless, the causal relationship between metabolites and CKD is still unclear. This study aimed to assess the associations between metabolites and CKD risk. METHODS: We applied a two-sample Mendelian randomization (MR) analysis to evaluate relationships between 1400 blood metabolites and eight phenotypes (outcomes) (CKD, estimated glomerular filtration rate(eGFR), urine albumin to creatinine ratio, rapid progress to CKD, rapid decline of eGFR, membranous nephropathy, immunoglobulin A nephropathy, and diabetic nephropathy). The inverse variance weighted (IVW), MR-Egger, and weighted median were used to investigate the causal relationship. Sensitivity analyses were performed with Cochran's Q, MR-Egger intercept, MR-PRESSO Global test, and leave-one-out analysis. Bonferroni correction was used to test the strength of the causal relationship. RESULTS: Through the MR analysis of 1400 metabolites and eight clinical phenotypes, a total of 48 metabolites were found to be associated with various outcomes. Among them, N-acetylleucine (OR = 0.923, 95%CI: 0.89-0.957, PIVW = 1.450 × 10-5) has a strong causal relationship with lower risk of CKD after the Bonferroni-corrected test, whereas Glycine to alanine ratio has a strong causal relationship with higher risk of CKD (OR = 1.106, 95%CI: 1.063-1.151, PIVW = 5.850 × 10-7). No horizontal pleiotropy and heterogeneity were detected. CONCLUSION: Our study offers groundbreaking insights into the integration of metabolomics and genomics to reveal the pathogenesis of and therapeutic strategies for CKD. It underscores 48 metabolites as potential causal candidates, meriting further investigation.

Association between chronic kidney disease and age-related macular degeneration: a Mendelian randomization study.

Purpose: Observational studies have reported inconsistent results on the relationship between chronic kidney disease (CKD) and age-related macular degeneration (AMD). The primary objective of this study was to investigate the causal relationships between estimated glomerular filtration rate (eGFR), CKD, its common causes, and AMD among participants of European descent. Methods: Genetic variants associated with eGFR, CKD and its common causes, encompassing diabetic nephropathy (DN), immunoglobulin A nephropathy (IgAN), and membranous nephropathy (MN) were obtained from previously published genome-wide association studies (GWAS) and FinnGen database. Summary statistics for early AMD, AMD, dry AMD, and wet AMD were acquired from the GWAS and FinnGen database. Inverse-variance-weighted (IVW) method was the main MR analysis. Sensitivity analyses were performed with Cochran's Q, MR-Egger intercept, and leave-one-out analysis. In addition, RadialMR was utilized to identify and remove outliers. Results: IVW results showed that CKD, eGFR were not associated with any type of AMD (p > 0.05). DN (OR: 1.042, 95% CI: 1.002-1.083, p = 0.037) and MN (OR: 1.023, 95% CI: 1.007-1.040, p = 0.005) were associated with an increased risk of earl AMD. DN (OR: 1.111, 95% CI: 1.07-1.154, p = 4.87 × 10-8), IgAN (OR: 1.373, 95% CI: 1.097-1.719, p = 0.006), and MN (OR: 1.036, 95% CI: 1.008-1.064, p = 0.012) were associated with an increased risk of AMD. DN (OR: 1.090, 95% CI: 1.042-1.140, p = 1.57 × 10-4) and IgAN (OR: 1.480, 95% CI: 1.178-1.858, p = 7.55 × 10-4) were associated with an increased risk of dry AMD. The risk of wet AMD was associated with DN (OR: 1.107, 95% CI: 1.043-1.174, p = 7.56 × 10-4) and MN (OR: 1.071, 95% CI: 1.040-1.103, p = 5.48 × 10-6). Conclusion: This MR study found no evidence of causal relationship between CKD and AMD. DN, IgAN, and MN may increase risk of AMD. This findings underscore the importance of ocular examinations in patients with DN, MN, and IgAN. More studies are needed to support the findings of our current study.

Grasshopper platform-assisted design optimization of fujian rural earthen buildings considering low-carbon emissions reduction.

This work aims to explore optimization methods for the design of earthen buildings in rural Fujian to achieve low-carbon emissions and improve the structural stability of earthen buildings. First, parametric modeling and optimization algorithms are employed through the Grasshopper platform. An intelligent earthen building design is created by combining the optimization of factors such as the structure of earthen buildings, building materials, and orientation. Then, a comparison is made with the unoptimized, energy-efficient, and carbon emission reduction designs. Finally, the work concludes that the proposed design significantly optimizes the total carbon emissions, energy consumption, structural stability, and economic aspects. The proposed design scheme achieves the highest carbon emission reduction effect, with a reduction rate of 34.64%. The proposed design exhibits lower maximum stress and higher minimum safety factor in terms of structural stability compared to other scenarios, along with smaller structural displacement. It also performs well in terms of initial investment, annual operating costs, and construction period. The significance of this work lies in providing scientific guidance for the design and construction of rural earthen buildings, promoting the organic integration of rural development with low-carbon initiatives. This indicates that the use of intelligent optimization methods for earthen building design is feasible and can yield positive results in practice.

Toxin-antitoxin system gene mutations driving Mycobacterium tuberculosis transmission revealed by whole genome sequencing.

Background: The toxin-antitoxin (TA) system plays a vital role in the virulence and pathogenicity of Mycobacterium tuberculosis (M. tuberculosis). However, the regulatory mechanisms and the impact of gene mutations on M. tuberculosis transmission remain poorly understood. Objective: To investigate the influence of gene mutations in the toxin-antitoxin system on M. tuberculosis transmission dynamics. Method: We performed whole-genome sequencing on the analyzed strains of M. tuberculosis. The genes associated with the toxin-antitoxin system were obtained from the National Center for Biotechnology Information (NCBI) Gene database. Mutations correlating with enhanced transmission within the genes were identified by using random forest, gradient boosting decision tree, and generalized linear mixed models. Results: A total of 13,518 M. tuberculosis isolates were analyzed, with 42.29% (n = 5,717) found to be part of genomic clusters. Lineage 4 accounted for the majority of isolates (n = 6488, 48%), followed by lineage 2 (n = 5133, 37.97%). 23 single nucleotide polymorphisms (SNPs) showed a positive correlation with clustering, including vapB1 G34A, vapB24 A76C, vapB2 T171C, mazF2 C85T, mazE2 G104A, vapB31 T112C, relB T226A, vapB11 C54T, mazE5 T344C, vapB14 A29G, parE1 (C103T, C88T), and parD1 C134T. Six SNPs, including vapB6 A29C, vapB31 T112C, parD1 C134T, vapB37 G205C, Rv2653c A80C, and vapB22 C167T, were associated with transmission clades across different countries. Notably, our findings highlighted the positive association of vapB6 A29C, vapB31 T112C, parD1 C134T, vapB37 G205C, vapB19 C188T, and Rv2653c A80C with transmission clades across diverse regions. Furthermore, our analysis identified 32 SNPs that exhibited significant associations with clade size. Conclusion: Our study presents potential associations between mutations in genes related to the toxin-antitoxin system and the transmission dynamics of M. tuberculosis. However, it is important to acknowledge the presence of confounding factors and limitations in our study. Further research is required to establish causation and assess the functional significance of these mutations. These findings provide a foundation for future investigations and the formulation of strategies aimed at controlling TB transmission.

Exploring the therapeutic effect of core components in Xuanshen Yishen mixture on hypertension through network pharmacology.

OBJECTIVE: This study aims to elucidate the mechanism of action and impact of the "Xuanshen Yishen Mixture" (XYM) on hypertension. METHODS: Active components were identified and potential targets were predicted using the Traditional Chinese Medicine Systems Pharmacology database. Hypertension-related targets were collected from GeneCards, DRUGBANK, OMIM, TTD, and PharmaGKB databases. Intersections of disease and drug targets were visualized using the R package "VennDiagram". A protein-protein interaction network was established via the STRING database. GO function enrichment and KEGG pathway analyses were conducted using "clusterProfiler", while "Cytoscape" was used to construct a "drug-component-target" network. Additionally, data from 60 patients with essential hypertension from the Affiliated Hospital of Shandong University of Traditional Chinese Medicine were retrospectively analyzed. Patients were divided into a control group (n = 30) and an XYM group (n = 30) based on treatment regimen. RESULTS: Sixty active ingredients and 98 related targets were identified from Uncaria, Radix Scrophulariae, and Epimedium in hypertension treatment. Key active components such as quercetin, kaempferol, yohimbine, and beta-sitosterol were pinpointed, with PTGS2, PTGS1, AR, DPP4, and F2 as crucial targets. KEGG pathway analysis highlighted significant pathways including IL-17 signaling, TNF signaling, Relaxin signaling, and HIF-1 signaling. Clinical data indicated that XYM's therapeutic effects are comparable to those of valsartan, which significantly reduced diastolic and systolic blood pressure and demonstrated good biosafety. CONCLUSIONS: Uncaria, Radix Scrophulariae, and Epimedium effectively mitigate hypertension through multiple components, targets, and pathways. Additionally, DPP4, IL-17, and TNF-α are identified as potential therapeutic targets for traditional Chinese medicine preparations in hypertension treatment. This study provides a foundation for further investigation into XYM's mechanisms in hypertension management.