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Tuberculosis (TB) is a chronic disease caused by Mycobacterium tuberculosis (M.tb) and responsible for millions of deaths worldwide each year. It has a complex pathogenesis that primarily affects the lungs but can also impact systemic organs. In recent years, single‐cell sequencing technology has been utilized to characterize the composition and proportion of immune cell subpopulations associated with the pathogenesis of TB disease since it has a high resolution that surpasses conventional techniques. This paper reviews the current use of single‐cell sequencing technologies in TB research and their application in analysing specimens from various sources of TB, primarily peripheral blood and lung specimens. The focus is on how these technologies can reveal dynamic changes in immune cell subpopulations, genes and proteins during disease progression after M.tb infection. Based on the current findings, single‐cell sequencing has significant potential clinical value in the field of TB research. Next, we will focus on the real‐world applications of the potential targets identified through single‐cell sequencing for diagnostics, therapeutics and the development of effective vaccines. [ABSTRACT FROM AUTHOR]

Age‐related chronic inflammatory lung diseases impose a threat on public health, including idiopathic pulmonary fibrosis (IPF) and chronic obstructive pulmonary disease (COPD). However, their etiology and potential targets have not been clarified. We performed genome‐wide meta‐analysis for IPF with the largest sample size (2883 cases and 741,929 controls) and leveraged the summary statistics of COPD (17,547 cases and 617,598 controls). Transcriptome‐wide and proteome‐wide Mendelian randomization (MR) designs, together with genetic colocalization, were implemented to find robust targets. The mediation effect was assessed using leukocyte telomere length (LTL). The single‐cell transcriptome analysis was performed to link targets with cell types. Individual‐level data from UK Biobank (UKB) were used to validate our findings. Sixteen genetically predicted plasma proteins were causally associated with the risk of IPF and 6 proteins were causally associated with COPD. Therein, genetically‐elevated plasma level of SCARF2 protein should reduce the risk of both IPF (odds ratio, OR = 0.9974 [0.9970, 0.9978]) and COPD (OR = 0.7431 [0.6253, 0.8831]) and such effects were not mediated by LTL. Genetic colocalization further corroborated these MR results of SCARF2. The transcriptome‐wide MR confirmed that higher expression level of SCARF2 was associated with a reduced risk of both. However, the single‐cell RNA analysis indicated that SCARF2 expression level was only relatively lower in epithelial cells of COPD lung tissue compared to normal lung tissue. UKB data implicated an inverse association of serum SCARF2 protein with COPD (hazard ratio, HR = 1.215 [1.106, 1.335]). The SCARF2 gene should be a novel target for COP. [ABSTRACT FROM AUTHOR]

The advent of high-throughput single-cell genomics technologies has fundamentally transformed biological sciences. Currently, millions of cells from complex biological tissues can be phenotypically profiled across multiple modalities. The scaling of computational methods to analyze and visualize such data is a constant challenge, and tools need to be regularly updated, if not redesigned, to cope with ever-growing numbers of cells. Over the last few years, metacells have been introduced to reduce the size and complexity of single-cell genomics data while preserving biologically relevant information and improving interpretability. Here, we review recent studies that capitalize on the concept of metacells—and the many variants in nomenclature that have been used. We further outline how and when metacells should (or should not) be used to analyze single-cell genomics data and what should be considered when analyzing such data at the metacell level. To facilitate the exploration of metacells, we provide a comprehensive tutorial on the construction and analysis of metacells from single-cell RNA-seq data (https://github.com/GfellerLab/MetacellAnalysisTutorial) as well as a fully integrated pipeline to rapidly build, visualize and evaluate metacells with different methods (https://github.com/GfellerLab/MetacellAnalysisToolkit). Several approaches have been designed to tackle the size and inherent noise of single-cell genomics data. This Review discusses the metacell concept, provides recommendations on when and how to use them and includes a tutorial and an integrated pipeline for building and analyzing metacells. [ABSTRACT FROM AUTHOR]

Several studies have shown that downregulation of GALNT2 (Polypeptide N‐Acetylgalactosaminyltransferase 2), encoding polypeptide N‐acetylgalactosaminyltransferase 2, decreases high‐density lipoprotein cholesterol (HDL‐C) and increases triglycerides levels by glycosylating key enzymes of lipid metabolism, such as angiopoietin like 3, apolipoprotein C‐III, and phospholipid transfer protein. GALNT2 is also a positive modulator of insulin signaling and action, associated with in vivo insulin sensitivity and during adipogenesis strongly upregulates adiponectin. Thus, the hypothesis that GALNT2 affects HDL‐C and triglycerides levels also through insulin sensitivity and/or circulating adiponectin, is tested. In 881 normoglycemic individuals the G allele of rs4846914 SNP at the GALNT2 locus, known to associate with GALNT2 downregulation, is associated with low HDL‐C and high values of triglycerides, triglycerides/HDL‐C ratio, and theHomeostatic Model Assessment of insulin resistance HOMAIR (p‐values = 0.01, 0.027, 0.002, and 0.016, respectively). Conversely, no association is observed with serum adiponectin levels (p = 0.091). Importantly, HOMAIR significantly mediates a proportion of the genetic association with HDL‐C (21%, 95% CI: 7–35%, p = 0.004) and triglyceride levels (32%, 95% CI: 4–59%, p = 0.023). The results are compatible with the hypothesis that, besides the effect on key lipid metabolism enzymes, GALNT2 alters HDL‐C and triglyceride levels also indirectly through a positive effect on insulin sensitivity. [ABSTRACT FROM AUTHOR]

The molecular mechanisms underlying posttraumatic stress disorder (PTSD) are yet to be fully elucidated, especially in underrepresented population groups. Expression quantitative trait loci (eQTLs) are DNA sequence variants that influence gene expression, in a local (cis‐) or distal (trans‐) manner, and subsequently impact cellular, tissue, and system physiology. This study aims to identify genetic loci associated with gene expression changes in a South African PTSD cohort. Genome‐wide genotype and RNA‐sequencing data were obtained from 32 trauma‐exposed controls and 35 PTSD cases of mixed‐ancestry, as part of the SHARED ROOTS project. The first approach utilised 108 937 single‐nucleotide polymorphisms (SNPs) (MAF > 10%) and 11 312 genes with Matrix eQTL to map potential eQTLs, while controlling for covariates as appropriate. The second analysis was focused on 5638 SNPs related to a previously calculated PTSD polygenic risk score for this cohort. SNP‐gene pairs were considered eQTLs if they surpassed Bonferroni correction and had a false discovery rate <0.05. We did not identify eQTLs that significantly influenced gene expression in a PTSD‐dependent manner. However, several known cis‐eQTLs, independent of PTSD diagnosis, were observed. rs8521 (C > T) was associated with TAGLN and SIDT2 expression, and rs11085906 (C > T) was associated with ZNF333 expression. This exploratory study provides insight into the molecular mechanisms associated with PTSD in a non‐European, admixed sample population. This study was limited by the cross‐sectional design and insufficient statistical power. Overall, this study should encourage further multi‐omics approaches towards investigating PTSD in diverse populations. [ABSTRACT FROM AUTHOR]

In this study, a portable Total Dissolved Solids (TDS) and Electrical Conductivity (EC) of water sensor using a disposable polymer strip and the readout circuit segments is presented. The strip consists of gold electrodes and a vent hole for water flow injection inside the measurement chamber. This strip reduces the cost of the measurement, decreases the measurement duration, and increases the repeatability of the system. Besides, there is no demand for electrodes cleaning and recalibration of the system. According to the electrical model of strip electrodes and their frequency responses, the EC value is in the range of 78.1–1230.8 (µs)/cm. The experimental tests are carried out based on the frequency method in the concentration range within 50–800 ppm. The results confirm the linear relation of TDS concentration on the EC voltage value which is 1.9 mV for 1 ppm resolution. Also, the effect of temperature variations on the EC value is investigated. Furthermore, the average amount of error for EC measurement exhibits an acceptable amount in comparison with other studies. Moreover, studying the drift variations for 20 days reveals the maximum drift of 1.6%. Finally, according to the present study, the sensor is a suitable candidate for practical applications. [ABSTRACT FROM AUTHOR]

When writing a research paper, the author has to select information to include in the paper to support various arguments. The information has to be organized and synthesized into a coherent whole through relationships and information structures. There is hardly any research on the information structure of research papers, and how information structure supports rhetorical and argument structures. Thus, this study is focused on information organization in the Abstract and Introduction sections of sociology research papers, analyzing the information structure of research objective, question, hypothesis, and result statements. The study is limited to research papers reporting research that investigated cause–effect relations between two concepts. Two semantic frames were developed to specify the types of information associated with cause–effect and comparison relations, and used as coding schemes to annotate the text for different information types. Six link patterns between the two frames were identified—showing how comparisons are used to support the claim that the cause‐effect relation is valid. This study demonstrated how semantic frames can be incorporated in discourse analysis to identify deep structures underlying the argument structure. The results carry implications for the knowledge representation of academic research in knowledge graphs, for semantic relation extraction, and teaching of academic writing. [ABSTRACT FROM AUTHOR]

Docosahexaenoic acid (DHA) is the predominant omega‐3 long‐chain polyunsaturated fatty acid found in human brain and eyes. There are a number of studies in the literature showing the health benefits of DHA. It is critical throughout all life stages from the need for fetal development, the prevention of preterm birth, and the prevention of cardiovascular disease to the improvements in the cognitive function and the eye health of adults and elderly. These benefits might be related to the modulation of gut microbiota by DHA. In addition, there are some discrepancies in the literature regarding certain health benefits of DHA, and this review is intended to explore and understand these discrepancies. Besides the variations in the DHA contents of different supplement sources, bioavailability is crucial for the efficacy of DHA supplements, which depends on several factors. For example, DHA in phospholipid and triglyceride forms are more readily to be absorbed by the body than that in ethyl ester form. In addition, dietary lipids in meals and emulsification of DHA oil can increase the bioavailability of DHA. Estrogens stimulated the biosynthesis of DHA, whereas testosterone stimulus induced a decrease in DHA. The roles of DHA through human lifespan, the sources, and its recommended daily intake in different countries are also discussed to provide a better understanding of the importance of this review. [ABSTRACT FROM AUTHOR]