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Studies have suggested that serum testosterone levels may be strongly correlated with the pathogenesis of arthritis. Therefore, the aim of this study was to assess the relationship between serum testosterone levels and arthritis in US adults using the National Health and Nutrition Examination Survey (NHANES). We used the database from NHANES, 2013–2016 to perform a cross-sectional study. This study investigated the relationship between serum testosterone and arthritis using multivariate logistic regression models and also used smoothed curve fitting and generalized additivity models. A total of 10,439 adults were included in this analysis. A significant negative association between serum testosterone and arthritis was found in a linear regression analysis. The study showed that the arthritis group had lower testosterone levels than the non-arthritis group. The univariate multivariate analyses of Q4, using Q1 as a reference, all showed a significantly lower risk of developing arthritis. In subgroup analyses, the negative correlation between serum testosterone levels and arthritis was more significant in women and those with a body mass index (BMI) ≥ 30 kg/m 2 . After controlling for various variables, we found a significant association between serum testosterone and arthritis in this analysis. Further study of the relationship between testosterone and arthritis is necessary to clarify the specific mechanism of serum testosterone action on arthritis.

Introduction In the aging process of the body, in addition to changes in fat and muscle content, there is also bone loss, implying the possibility of a strong muscle–bone–lipid link. In this study, we initially investigated the relationship between lumbar BMD and low muscle mass and the relationship between “muscle–bone–lipid.” Methods The datasets from the National Health and Nutrition Examination Survey (NHANES) 2011–2018 were used in a cross-sectional investigation. BMD and appendicular skeletal muscle (ASM) were measured by dual-energy X-ray absorptiometry (DXA), and appendicular skeletal muscle was adjusted by body mass index (BMI) as a marker of sarcopenia. Weighted multivariate regression and logistic regression analysis were used to explore the independent relationship between lumbar BMD and sarcopenia. Fitted smoothing curves and threshold effect analysis were used to describe the nonlinear relationship. Result In 8386 participants with ages 20–59 years, there was a negative association between lumbar BMD and sarcopenia. In the fully adjusted model, the risk of developing sarcopenia decreased by 93% for each 1-unit increase in lumbar BMD (OR = 0.07, 95%CI 0.03–0.20). The risk of sarcopenia was 58% lower in participants in the highest quartile of lumbar BMD than in those in the lowest quartile (OR = 0.42, 95%CI 0.27–0.64). This negative association was more pronounced in the population of women with BMI ≥ 25. Conclusion Our findings suggest that lumbar BMD is negatively associated with sarcopenia in US adults. The dynamic balance between “muscle–bone–lipid” is likely to be related to the pathogenesis of bone loss.

Consideration for patients with visual impairment, from low vision to blindness, is an important part of building a barrier-free society. Some authors have elaborated that visual impairment can indeed lead to delayed development in theory of mind, thereby causing pragmatic knowledge deficiency. Verifying whether those with eye conditions have pragmatic impairment is an essential way for their clinical evaluation, intervention and rehabilitation. We primarily carry out a meta-analysis of visual impairment from low vision to blindness and pragmatic impairment in people with low vision or blindness to verify visual impairment may cause pragmatic impairment. Electronic databases Pubmed, Medline, MesH, Psychinfo, Ovid, EBSCO and CNKI and the reference sections of previous reviews. Studies were included when they built on primary data from clinical questionnaire surveys or field trials anywhere in the world, and when they reported impacts of visual impairment on social cognition, communication, skills, behavior and intelligence. In total, 25 original studies were included, in which 25735 people were evaluated. Statistically, visual impairments and pragmatic impairment exist correlation due to the significant p value(p = 0.0005 < 0.05) in group and the subgroup sorted in the light of 18 years old (p < 0.0001 and p = 0.003 < 0.05). Psychologically, because people with visual impairment can not normally get non-verbal information, they can not get a complete pragmatic knowledge system. Pragmatic knowledge deficiency leads to abnormal in executive functions and development delay from the perspective of theory of mind, inducing pragmatic impairment. Therefore, visual impairment has an impact on pragmatic impairment. The meta-analysis reveals robust evidence on the relationship of vision impairment and pragmatic impairment in children or adults. Such evidence may help to gradually improve the clinical evaluation, intervention and rehabilitation of these people.

This paper studies the scheduling of autonomous mobile robots (AMRs) at hospitals where the stochastic travel times and service times of AMRs are affected by the surrounding environment. The routes of AMRs are planned to minimize the daily cost of the hospital (including the AMR fixed cost, penalty cost of violating the time window, and transportation cost). To efficiently generate high-quality solutions, some properties are identified and incorporated into an improved tabu search (I-TS) algorithm for problem-solving. Experimental evaluations demonstrate that the I-TS algorithm outperforms existing methods by producing high-quality solutions. Based on the characteristics of healthcare requests and the AMR working environment, scheduling AMRs reasonably can effectively provide medical services, improve the utilization of medical resources, and reduce hospital costs.

Anoikis and immune cell infiltration are pivotal factors in the pathophysiological mechanism of diabetic nephropathy (DN), yet a comprehensive understanding of the mechanism is lacking. This work aimed to pinpoint distinctive anoikis-related genes (ARGs) in DN and delve into their impact on the immune landscape. Three datasets (GSE30528, GSE47184, and GSE96804) were downloaded from the gene expression omnibus (GEO) dataset. Differentially expressed genes (DEGs) were identified using the “limma” package, while ARGs were obtained from GSEA, GeneCard, and Harmonizome datasets. The intersection of DEGs and ARGs was analyzed for Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. The CIBERSORT algorithm was employed to estimate the infiltration percentage of 22 immune cell types in DN renal tissue. Subsequently, the least absolute shrinkage and selection operator (LASSO), support vector machine recursive feature elimination (SVM-RFE), and random forest (RF) algorithms were adopted to screen key ARGs related to DN. After that, receiver operating characteristic (ROC) analysis was employed to assess the diagnostic accuracy of each gene and the real-time quantitative polymerase chain reaction (RT-qPCR) was adopted to quantitatively detect the expression of biomarkers in DN cell models. Finally, correlations between key genes and immune cell infiltration were analyzed, and a competitive endogenous ribonucleic acid (RNA) (ceRNA) network based on key genes was constructed. A total of 59 DEARGs were identified. GO functional annotation enrichment analysis revealed their involvement in kidney development, extracellular matrix (ECM), cytoplasmic vesicle cavity, immunoinflammatory response, and cytokine effect. KEGG pathway analysis indicated that MAPK, PI3K -Akt, IL -17, TNF, and HIF- 1 signaling pathways are critical for DN. In addition, seven key genes, including PDK4, S100A8, HTRA1, CHI3L1, WT1, CDKN1B, and EGF, were screened by machine learning algorithm. Most of these genes exhibited low expression in renal tissue of DN patients and positive correlation with neutrophils, and their expressions were verified in an external dataset cell model. The ceRNA analysis suggested potential regulatory pathways (H19/miR-15b-5p/PDK4 and KCNQ1T1/miR-1207-3p/WT1) influencing early DN progression. This work provided a comprehensive analysis of the role of DEARGs in DN for the first time, offering valuable insights for further understanding the disease mechanism and guiding clinical diagnosis, treatment, and research of DN.

Background Type 2 diabetes mellitus (DM2) and osteoporosis (OP) are currently the two most significant causes of mortality and morbidity in older adults, according to clinical evidence. The intrinsic link between them is yet unknown, despite reports of their coexistence. By utilizing the two-sample Mendelian randomization (MR) approach, we sought to evaluate the causal impact of DM2 on OP. Methods The aggregate data of the whole gene-wide association study (GWAS) were analyzed. A two-sample MR analysis was performed using single-nucleotide polymorphisms (SNPs), which are strongly associated with DM2, as instrumental variables (IVs) to evaluate the causal analysis of DM2 on OP risk with OR values, using inverse variance weighting, MR-egger regression, and weighted median methods, respectively. Result A total of 38 single nucleotide polymorphisms were included as tool variables. According to the results of inverse variance-weighted (IVW), we found that there was a causal relationship between DM2 and OP, in which DM2 had a protective effect on OP. For each additional case of DM2, there is a 0.15% decrease in the odds of developing OP (OR = 0.9985;95%confidence interval:0.9974,0.9995; P value = 0.0056). There was no evidence that the observed causal effect between DM2 and the risk of OP was affected by genetic pleiotropy ( P  = 0.299). Using Cochran Q statistics and MR-Egger regression in the IVW approach, the heterogeneity was calculated; P  > 0.05 shows that there is a significant amount of heterogeneity. Conclusion A causal link between DM2 and OP was established by MR analysis, which also revealed that DM2 decreased the occurrence of OP.

Network analysis, an interdisciplinary method rooted in graph theory and complex systems, is a promising approach for advancing our understanding of the brain's complex architecture and its implications for behavior, cognition, and mental health. Despite the potential of this method, the application of network analysis in brain science is underutilized, highlighting the need for increased awareness and the development of network-based studies to fully realize its transformative potential for behavior and brain research. [...]we introduce an insightful behavioral exemplar to increase awareness of the potential application of network analysis in brain science. [...]network analysis can contribute to the enhancement of BCIs by improving precision, response time, and overall usability.

In order to develop nutritious and healthy fermented fig juice, foure samples fermented were made using natural fermentation and fermentation by lactobacillus. Then the total acidity, total sugar, reducing sugar, total phenols, total flavones and characteristic organic acids, antioxidant activity, and inhibition of enzyme activity in fermented fig juice were compared. The results showed that natural fermentation could produce more reducing sugar, lactic acid, flavonoids, and exhibit stronger DPPH radical scavenging capacity and total reducing power. Inhibition of tyrosinase and pancreatic lipase was detected in fermented fig juice, of which the inhibition rate of tyrosinase by natural fermentation was 81.80%, and the inhibition rate of pancreatic lipase by mixed cultures was 38.72%, which was higher than that of other groups. The results indicated the functional activity of fermented fig juice could be improved by fermentation, and the natural fermentation method was found superior.

Background Although spatial organization of compartments and topologically associating domains at large scale is relatively well studied, the spatial organization of regulatory elements at fine scale is poorly understood in plants. Results Here we perform high-resolution chromatin interaction analysis using paired-end tag sequencing approach. We map chromatin interactions tethered with RNA polymerase II and associated with heterochromatic, transcriptionally active, and Polycomb-repressive histone modifications in Arabidopsis . Analysis of the regulatory repertoire shows that distal active cis -regulatory elements are linked to their target genes through long-range chromatin interactions with increased expression of the target genes, while poised cis -regulatory elements are linked to their target genes through long-range chromatin interactions with depressed expression of the target genes. Furthermore, we demonstrate that transcription factor MYC2 is critical for chromatin spatial organization, and propose that MYC2 occupancy and MYC2-mediated chromatin interactions coordinately facilitate transcription within the framework of 3D chromatin architecture. Analysis of functionally related gene-defined chromatin connectivity networks reveals that genes implicated in flowering-time control are functionally compartmentalized into separate subdomains via their spatial activity in the leaf or shoot apical meristem, linking active mark- or Polycomb-repressive mark-associated chromatin conformation to coordinated gene expression. Conclusion The results reveal that the regulation of gene transcription in Arabidopsis is not only by linear juxtaposition, but also by long-range chromatin interactions. Our study uncovers the fine scale genome organization of Arabidopsis and the potential roles of such organization in orchestrating transcription and development.