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PubMed2026

Effects of rumen fluid transplantation on longissimus dorsi muscle development in Xizang sheep: An association analysis based on transcriptomic and serum metabolomic profiles.

This study aimed to investigate the effects of rumen fluid transplantation (RFT) on the growth and development of the longissimus dorsi muscle in female Xizang sheep. After RFT, muscle lightness differed significantly between the two groups, with the LDC group showing significantly higher lightness than the LDT group. In contrast, no significant differences were observed between groups in other muscle phenotypic traits, including drip loss, pH, cooking loss, shear force, redness, and yellowness. Antioxidant-related indices (SOD, GSH-PX, MDA, CAT, and T-AOC) also showed no significant differences between groups. Histological analysis revealed that muscle fiber length, width, and density were significantly greater in the experimental group than in the control group. Transcriptomic analysis identified 515 differentially expressed genes (DEGs), of which 419 were downregulated. KEGG analysis indicated that genes involved in muscle development-related pathways, such as cell adhesion and the PI3K-Akt signaling pathway, were predominantly downregulated. Key serum metabolites (L-kynurenine, IPA, allantoin, and propionylcarnitine) showed highly significant positive correlations with muscle fiber growth indices. In contrast, metabolites such as l-carnitine, acetylcarnitine, and citrulline were negatively correlated with muscle fiber growth, but positively correlated with the expression of muscle structure-related genes (COL11A1 and EFNA5) and with meat lightness. Overall, this study provides new insights into the potential molecular basis by which RFT influences muscle growth and development. However, the mechanisms by which RFT affects muscle development and meat quality-related traits remain unclear and warrant further investigation.

Animals↗

PubMed2025

Landscape genomics analysis reveals the genetic basis underlying cashmere goats and dairy goats adaptation to frigid environments.

Understanding the genetic mechanism of cold adaptation in cashmere goats and dairy goats is very important to improve their production performance. The purpose of this study was to comprehensively analyze the genetic basis of goat adaptation to cold environments, clarify the impact of environmental factors on genome diversity, and lay the foundation for breeding goat breeds to adapt to climate change. A total of 240 dairy goats were subjected to genome resequencing, and the whole genome sequencing data of 57 individuals from 6 published breeds were incorporated. By integrating multiple approaches such as phylogenetic analysis, population structure analysis, gene flow and population history exploration, selection signal analysis, and genome-environment association analysis, an in-depth investigation was carried out. Phylogenetic analysis unraveled the genetic relationships and differentiation patterns among dairy goats and other goat breeds. Through signal analysis (θπ, FST, XP-CLR), we identified numerous candidate genes associated with cold adaptation in dairy goats (STRIP1, ALX3, HTR4, NTRK2, MRPL11, PELI3, DPP3, BBS1) and cashmere goats (MED12L, MARC2, MARC1, DSG3, C6H4orf22, CHD7, MYPN, KIAA0825, MITF). Genome-environment association (GEA) analysis confirmed the link between these genes and environmental factors. Moreover, a detailed analysis of the critical genes C6H4orf22 and STRIP1 demonstrated their significant roles in the geographical variations of cold adaptation and allele frequency differences among different breeds. This study contributes to understanding the genetic basis of cold adaptation, providing crucial theoretical support for precision breeding programs aimed at improving production performance in cold regions by leveraging adaptive alleles, thereby ensuring sustainable animal husbandry.

Environmental adaptation↗

PubMed2025

Metagenomic analyses reveal E. coli-derived siderophores as potential signatures for breast cancer.

BACKGROUND: Breast cancer remains a leading cause of cancer-related mortality in women. Recent evidence implicates the gut microbiome and metabolites in breast cancer pathogenesis. This study explores associations between gut microbial species, their predicted metabolites, and breast cancer to uncover potential mechanistic insights. METHODS: Comprehensive metagenomic analyses were conducted on the gut microbiome of pre- and postmenopausal breast cancer patients, where microbial species were profiled through AMPHORA2 and metabolites were predicted through antiSMASH. Multivariate association analysis was used to identify significant associations between specific microbial species, predicted metabolites, and breast cancer status. A custom ensemble machine learning classifier was developed to classify pre- and postmenopausal breast cancer cases and controls based on microbial and predicted metabolite features. Additionally, a synthetic microbiome dataset was generated through MIDASim to validate the reproducibility of the ML results. Using our results, we explored the underlying dynamics of identified taxa and metabolite in breast cancer through literature and statistical support. RESULTS: Our analysis identified 471 microbial species and predicted 40 key metabolites in the metagenomic data. Multivariate analysis identified significant positive associations (p-value < 0.05) of E. coli, siderophore, and thiopeptide with breast cancer. The custom ensemble model achieved accuracy and AUC as high as 78% and 90%, respectively, in classifying pre- and postmenopausal cases and controls. The high-ranking features i.e., E. coli, siderophore, and thiopeptide were consistent with the results of the multivariate association analysis, thereby substantiating their biological significance. Using these findings, we propose a mechanistic model in which E. coli secretes siderophores under iron-limited conditions in breast cancer patients, for iron sequestration from the host, which can potentially promote angiogenesis and tumor progression. CONCLUSION: Our findings suggest that microbial iron acquisition mechanisms may play a critical role in breast cancer pathophysiology. Functional validation of these mechanisms is needed to assess therapeutic potential. This study highlights gut microbiota and their metabolites as promising targets for breast cancer research and intervention.

Breast Neoplasms↗

PubMed2025

Heterogeneity Analysis of Associations Involving the Large-Scale Online MindCrowd Survey Memory Test.

INTRODUCTION: Alzheimer's disease and related disorders (ADRDs), as well as general age-related cognitive decline, are known to be multifactorial with heterogeneous etiologies. Identifying and accommodating heterogeneity in any one ADRD-related data set can be pursued using different analytical techniques, each with different assumptions or purposes. For example, whereas a great deal of research has explored clustering individuals or variables that exhibit greater similarity in some way, little research has explored evidence for heterogeneity in the relationships between relevant outcomes, such as performance on a memory test, and risk factors such as environmental exposures, behaviors, or genetic factors among individuals. METHODS: We explored evidence of heterogeneity in the relationships between ability on a memory test, specifically the paired associate learning (PAL) test, and multiple social and demographic risk factors using the large MindCrowd study database (n > 90,000 individuals). We focused on mixtures of regression models but compared models assuming many interaction effects among independent variables as well as random effects. RESULTS: We ultimately find substantial evidence for heterogeneity and offer an intuitive explanation for it involving individual motivation for participating in the MindCrowd study. Basically, we argue that our mixture of regression model analysis results suggest that a smaller group of individuals (∼16%) likely participated in the MindCrowd study out of a concern for their cognitive abilities as they exhibit stronger and statistically significant negative associations between age, number of medications they are on, some ancestries, and the number correct on the PAL test. They also exhibit stronger positive associations between education and PAL test results in a dose-dependent manner suggesting that a "cognitive reserve" associated with greater education could benefit them. Analysis models assuming interaction terms and random effects suggested that other forms of heterogeneity in the relationships between variables exist in the data set, but their results do not carry with them the same intuitive explanation that the results of the mixture model analyses do. CONCLUSION: We find evidence for heterogeneity in the relationships between social and demographic variables and PAL test results in the large MindCrowd study database. This heterogeneity is likely due to individuals with and without concerns for their cognitive abilities participating in the study. We also find other types of evidence in the data set. Our results should motivate caution in the use of large epidemiological study or survey-oriented data sets to build predictive models of clinical or subclinical pathologies without exploring or accommodating heterogeneity. Our results also suggest that one should include questions about motivation to participate in large epidemiological studies since different motivations may impact important relationships between independent and dependent variables.

Humans↗

PubMed2026

miR-6388 regulates granulosa cell function in sheep by targeting GDF9 and modulating the TGF-β signaling pathway.

Litter size is an economically important trait in sheep and is closely associated with ovarian follicular development and granulosa cell (GC) function. This study investigated the association between GDF9 polymorphisms and litter size, and examined the post-transcriptional regulation of GDF9 by miR-6388 in ovine GCs. Variants were initially identified by Sanger sequencing in 20 ewes, and subsequently genotyped in 377 three-year-old ewes, including 231 Sonid (SN) sheep and 146 Ujimqin (UM) sheep for association analysis. Candidate miRNAs targeting litter size-associated variants in the GDF9 3'UTR were predicted, and the miR-6388-GDF9 interaction was evaluated using dual-luciferase reporter assays. RT-qPCR, Western blotting, EdU incorporation, and flow cytometry were used to assess endogenous GDF9 expression and GC function. Twelve single-nucleotide polymorphisms were identified, including the putatively novel variant g.42114076C > G. The linkage disequilibrium block comprising g.42116936C > T, g.42113821T > A, and g.42113962G > A polymorphisms of GDF9 was significantly associated with litter size in both SN and UM sheep, whereas the c.477G > A was associated with litter size only in UM sheep. Reporter assays showed that the GDF9 3'UTR region carrying the G allele of g.42113962G > A was more responsive to miR-6388-mediated repression than the region carrying the A allele. miR-6388 overexpression reduced GDF9 mRNA and GDF9 protein levels, inhibited GC proliferation, altered cell-cycle distribution, and promoted apoptosis, whereas miR-6388 knockdown increased GDF9 expression and GC proliferation and reduced apoptosis. These cellular changes were accompanied by altered expression of cell-cycle and apoptosis-related genes and TGF-β signaling-related components.

Animals↗

PubMed1978

Partial laryngectomy: analysis of associated swallowing disorders.

Evaluation of postoperative swallowing ability in thirty-eight patients having had partial laryngectomy indicates that there are marked differences in the degree of dysphagia among individuals with similar surgical defects. This variation in swallowing disability, however, appears to have definable limits. Rehabilitation is possible for many patients disabled by postoperative dysphagia. A transoral surgical technic for reconstruction of the obliterated pyriform sinus is described.

Deglutition Disorders↗

PubMed1978

Problems associated with analysis and interpretation of small molecule/macromolecule binding data.

In the analysis of binding data, arbitrary transformations such as the Scatchard plot, may give misleading estimates of the binding parameters. The statistically correct approach is to determine values of K and n by non-linear regression of the actual dependent variable against the actual independent variable. In the case of the spectrophotometric titration method the dependent variable is the absorbance and the independent variable is the composition of the drug/macromolecule mixture. The method relies on an accurate estimate of the extinction coefficient of the bound drug and this is best treated as a parameter to be estimated in the regression analysis. In testing models by data fits alone it is emphasized that whilst a model may be rejected if it does not fit the data, a good fit does not ensure uniquieness and confirmatory, independent evidence must be sought.

DNA↗

PubMed2026

Machine learning-driven spleen imaging and genomics uncover a splenic connection to coronary artery disease.

Despite advances in managing traditional risk factors, coronary artery disease (CAD) remains the leading cause of mortality. Circulating hematopoietic cells influence risk for CAD separately from traditional risk factors, but the role of a key regulating organ, the spleen, is unknown. The understudied spleen is a representation of the hematopoietic system optimally suited for unbiased radiologic investigations toward mechanistic insights. Here, we leveraged deep learning to extract 107 splenic radiomic features from abdominal magnetic resonance imaging (MRI) scans of 42,059 UK Biobank participants and of 2745 Mass General Brigham Biobank (MGBB) participants. Of these, 10 features from UK Biobank were associated with CAD. Genome-wide association analysis of CAD-associated features identified 219 loci, including 9p21. Variants at 9p21, the strongest yet mechanistically elusive CAD locus, were associated with splenic features such as run-length nonuniformity, reflecting heterogeneity of continuous texture regions. Research MRI findings were consistent internally, but external clinical validation highlighted challenges in translating analyses of abdominal MRI scans to routine clinical practice because of variability in imaging protocols and greater clinical heterogeneity among patients. Our study, combining deep learning with genomics, presents a framework to uncover potential splenic involvement in CAD and emphasizes translational gaps between research and clinical radiomics.

Humans↗

PubMed2025

Genome-to-genome analysis reveals associations between human and mycobacterial genetic variation in tuberculosis patients from Tanzania.

The risk and prognosis of tuberculosis (TB) are influenced by a complex interplay between human and bacterial genetic factors. While previous genomic studies have largely examined human and bacterial genomes separately, we adopted an integrated approach to uncover host-pathogen interactions. We leveraged paired human and Mycobacterium tuberculosis (M.tb) genomic data from 1000 adult TB patients from Tanzania and used a "genome-to-genome" approach to search for associations between human and M.tb genetic variants and to identify interacting genetic loci. Our analyses revealed two significant host-pathogen genetic associations. The first significant association (p = 4.7e-11) links a human intronic variant in PRDM15 (rs12151990), a gene involved in apoptosis regulation, with an M.tb variant in Rv2348c (I101M), which encodes a T cell-stimulating antigen. The second significant association (p = 6.3e-11) connects a human intergenic variant near TIMM21 and FBXO15 (rs75769176) - also associated with TB severity (p = 0.04) - with an M.tb variant in FixA (T67M). While FBXO15 is involved in the regulation of antigen processing and TIMM21 affects mitochondrial function, FixA's role remains undefined due to limited functional characterization. Additionally, we observed that a group of M.tb T cell epitope variants were significantly associated with HLA-DRB1 variation, suggesting that, despite their rarity, certain epitopes may still be subjected to immune selective pressure. Together, these findings identify previously unknown sites of genomic conflicts between humans and M.tb, advancing our understanding of how this pathogen evades selection pressure and persist in human populations.

Humans↗

PubMed1976

Canadian Hospital Association seeks analysis of health care cost escalation.

Explore the source record for details and available documents.

Canada↗

PubMed2026

AKR7A3 rs1738023 association with susceptibility to female hepatocellular carcinoma and its role in AFB1 metabolism and tumor.

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most common cancer worldwide. In this study, we performed a two-stage exome-chip association analysis and found that the aldo-keto reductase family7 member A3 (AKR7A3) rs1738023 may be a potential susceptibility locus for HCC in females. We aimed to explore its role and mechanism. METHODS: The association between genotype and phenotype was analyzed through GWAS method. The expression of AKR7A3 in cancer tissue and blood analysis by qRT-PCR. The relationship of AKR7A3 and aflatoxin B1 (AFB1) was also analyzed. The effect of AKR7A3 on the biological behavior of HCC cell line was investigated on proliferation and invasion. The potential mechanism was analyzed by transcriptome analysis and western blot. RESULTS: Through genome-wide association analysis (GWAS), AKR7A3 (rs1738023), KIF2C (rs4342887), and CYP3A5 (rs6977165 and rs4646450) were found to be associated with susceptibility to hepatocellular carcinoma (HCC) in women. Further expression quantitative trait loci (eQTL) analysis showed that only AKR7A3 (rs1738023) was significantly associated with gene expression. The expression of AKR7A3 was significantly lower in HCC than adjacent non-tumorous tissues (P < 0.001). The genotype of rs1738023 was significantly associated with AKR7A3 expression (P = 0.0085). Rs1738023[C] genotype had a low AKR7A3 expression level and limited detoxification ability of AFB1. Literature data showed that AKR7A3 is involved in the metabolism of aflatoxin B1 (AFB1). Functional experimental results showed that overexpression of AKR7A3 in the normal liver cell line HL-7702 could significantly reduce AFB1-induced ROS levels and DNA adduct formation, suggesting that it plays a protective role in AFB1 metabolic detoxification. Cell function test showed that overexpression of AKR7A3 inhibit the proliferation, migration and invasion of HCC cells, and block the cell cycle. Transcriptome sequencing and KEGG pathway enrichment analysis revealed that overexpression of AKR7A3 affected the PI3K signaling pathway and led to downregulation of HIF1A and its downstream VEGFA protein expression. The validation results were confirmed in HCC cell lines Huh-7 and SUN-387. CONCLUSION: Overexpression of AKR7A3 contributes to inhibition of HCC progression and reduction of aflatoxin toxicity. AKR7A3 may serve as a potential prognostic and therapeutic target for HCC patients, although further validation is needed.

AKR7A3↗

PubMed2026

Deletion of neurosecretory proteins GL and GM drives dual anti-obesity effects via appetite suppression and enhanced energy expenditure.

Obesity results from an imbalance between energy intake and expenditure and is regulated by hypothalamic neuropeptide systems. The neurosecretory proteins GL (NPGL) and GM (NPGM) are expressed in the hypothalamus and promote feeding in gain-of-function studies; however, their endogenous physiological roles remain unclear. Here, we show that mice lacking both NPGL and NPGM display a lean phenotype driven by reduced food intake and increased energy expenditure. This anti-obesity phenotype is associated with increased expression of anorexigenic pro-opiomelanocortin in the hypothalamus and enhanced thermogenic activity in brown adipose tissue, marked by elevated uncoupling protein 1. Consistent with these findings, suppression of NPGL/NPGM signaling reduces feeding and alters sympathetic nerve activity. In addition, genome-wide association analysis identifies an obesity-associated variant near the human NPGM locus, suggesting relevance to human energy balance. Together, these findings identify NPGL and NPGM as endogenous regulators of energy homeostasis with potential relevance to obesity.

Animals↗

PubMed2025

Interaction of host gene-gut microbiota in male grading of Macrobrachium rosenbergii.

UNLABELLED: The giant freshwater prawn (GFP; Macrobrachium rosenbergii), a crustacean of high nutritional and economic value, is crucial for aquaculture. During the same growth cycle, male GFPs develop into three distinct forms: small males, orange claw males, and blue claw males. These morphotypes display varying social behaviors, which severely constrain their industrial development. To address this, this study collected male GFP samples at critical developmental time points (100, 110, and 120 days post-hatching) for phenotypic trait measurement and analysis to obtain external morphological data. Through gut microbiota diversity analysis, we identified key gut bacteria (Lactococcus garvieae and Lactobacillus taiwanensis) influencing male morphotype differentiation. Transcriptomic analysis revealed host Kyoto Encyclopedia of Gene and Genome pathways and key genes (Wnt-6, CTSB, CTSL, PPAE, and TP53) associated with morphotype differentiation. The interactions among phenotypic traits, gut microbiota, and key genes were systematically studied through association analysis. Weighted gene co-expression network analysis was employed to construct co-expression modules, from which critical gene modules influencing phenotypic variation were identified. Through association network analysis, we established an "Achromobacter-CD-TRINITY_DN93139_c0_g2 (calpain clp-1)" interaction model. Our findings provide novel insights into the genetic enhancement of GFPs and offer guidelines for future research regarding gut symbiotic bacteria and breeding initiatives. IMPORTANCE: Male Macrobrachium rosenbergii (giant freshwater prawn [GFP]) in the same growth cycle will develop into small males, orange claw males, and blue claw males. This individual heterogeneity in growth significantly impacts the benefits of aquaculture. However, the factors influencing the differentiation of male GFP morphotype remain unclear. This study analyzed the phenotypic data of various GFP levels, the structure of the intestinal microbiota, and the differential genes within the gonadal transcriptome at critical time points of male GFP-level type differentiation. The aim was to explore the potential role of intestinal microbiota and differential genes in this phenomenon. This study offers new insights into the research on the phenomenon of male GFP-level type differentiation.

Animals↗

PubMed2026

A 2-step, 2-sample Mendelian randomization study of gut microbiota, blood metabolites and dry age-related macular degeneration.

Dry age-related macular degeneration (dAMD) is the leading cause of blindness among elderly people in developed countries. The main objective of this study is to investigate the causal relationship between gut microbiota (GM), blood metabolites, and dAMD among European participants. Based on the genome-wide association analysis database, double sample Mendelian randomization (MR) analysis was performed on GM, blood metabolites, and dAMD. The inverse-variance weighted method is used to estimate the causal relationship between GM, blood metabolites, and dAMD, while multiple methods are employed to eliminate pleiotropy and heterogeneity. A 2-step MR analysis quantitatively assessed the effect of metabolite-mediated GM on dAMD. In MR analysis, 15 GM were found to be associated with increased or decreased risk of dAMD, and 18 blood metabolites were found to be associated with increased or decreased risk of dAMD. Our research also found that the potential association between GM and dAMD may be mediated by blood metabolite levels, specifically, ADpSGEGDFXAEGGGVR levels accounted for 38.9% of the causal pathway from genus Parasutterella to dAMD. Our research findings indicate that certain GM and blood metabolites can affect the onset of dAMD, and increasing the abundance of genus Parasottella can increase the risk of dAMD through the mediation of ADpSGEGDFXAEGGGVR levels.

Humans↗

PubMed2026

Single-cell expression quantitative trait locus Mendelian randomization reveals immune cell-specific causal regulatory networks and actionable targets in polycystic ovary syndrome.

ObjectiveTo systematically investigate whether the pathogenesis of polycystic ovary syndrome (PCOS) is causally related to dysregulated gene expression in specific immune cell subsets, and to evaluate the potential of these causal genes as actionable drug targets.MethodsThis study employed a two-sample Mendelian randomization (MR) framework using publicly available genome-wide association study (GWAS) summary statistics. The participant data included 797 PCOS cases and 140,558 controls (no direct patient recruitment was involved). Instrumental variables were derived from high-resolution immune cell-specific single-cell expression quantitative trait locus (sc-eQTL) data (OneK1K project) across 14 immune cell types. Primary analyses utilized the inverse-variance weighted (IVW) method. Shared causal variants were validated using Bayesian colocalization. Phenome-wide association analysis (PheWAS), external transcriptomic dataset validation (GSE8157), and DrugBank database screening were conducted for pleiotropy assessment and drug repositioning.ResultsMR analysis revealed genome-wide significant causal associations for GLIPR1 in non-classical monocytes (Mono NC) and XBP1 in CD4+ effector memory T cells (CD4 ET) with PCOS risk. Higher GLIPR1 expression was associated with a decreased PCOS risk (OR = 0.669, P = 4.34×10-6), whereas higher XBP1 expression was associated with an increased risk (OR = 1.406, P = 9.53×10-8). Colocalization analysis confirmed that GLIPR1 shares a causal variant with PCOS (PP.H4 = 96.73%). PheWAS and external validation confirmed the safety profile and significant upregulation (P = 0.03) of GLIPR1. Drug repositioning identified SOT-107, a Phase III protein therapy drug, as a potential interacting agent for GLIPR1.ConclusionsThis sc-eQTL MR study reveals immune cell-specific causal regulatory networks in PCOS. GLIPR1 in non-classical monocytes represents a high-confidence protective target, while XBP1 provides suggestive evidence for immune-mediated pathogenesis. The candidate drug SOT-107 highlights theoretical repositioning opportunities, though rigorous preclinical validation remains required.

Female↗

PubMed2024

Contribution of copy number variations to education, socioeconomic status and cognition from a genome-wide study of 305,401 subjects.

Educational attainment (EA), socioeconomic status (SES) and cognition are phenotypically and genetically linked to health outcomes. However, the role of copy number variations (CNVs) in influencing EA/SES/cognition remains unclear. Using a large-scale (n = 305,401) genome-wide CNV-level association analysis, we discovered 33 CNV loci significantly associated with EA/SES/cognition, 20 of which were novel (deletions at 2p22.2, 2p16.2, 2p12, 3p25.3, 4p15.2, 5p15.33, 5q21.1, 8p21.3, 9p21.1, 11p14.3, 13q12.13, 17q21.31, and 20q13.33, as well as duplications at 3q12.2, 3q23, 7p22.3, 8p23.1, 8p23.2, 17q12 (105 kb), and 19q13.32). The genes identified in gene-level tests were enriched in biological pathways such as neurodegeneration, telomere maintenance and axon guidance. Phenome-wide association studies further identified novel associations of EA/SES/cognition-associated CNVs with mental and physical diseases, such as 6q27 duplication with upper respiratory disease and 17q12 (105 kb) duplication with mood disorders. Our findings provide a genome-wide CNV profile for EA/SES/cognition and bridge their connections to health. The expanded candidate CNVs database and the residing genes would be a valuable resource for future studies aimed at uncovering the biological mechanisms underlying cognitive function and related clinical phenotypes.

Humans↗

PubMed2026

Glutamate metabolic correlation analysis reveals CnP5CS1 contributes to 2-acetyl-1-pyrroline accumulation in aromatic coconut.

Flavor quality, a key sensory attribute of coconut, has consistently been a central breeding objective throughout long-term domestication and varietal improvement efforts. Developing high-aroma varieties requires a clear understanding of their underlying molecular genetic mechanisms. However, research on the metabolic regulatory enzymes involved remains limited, particularly those linked to 2-acetyl-1-pyrroline (2AP), a volatile compound that primarily contributes to the unique scent of aromatic coconuts. We developed contrasting populations and systematically evaluated the role of CnP5CS in 2AP accumulation by examining enzyme activity, metabolic flux, population-level genetic variation, and transcriptional regulatory networks. In the aromatic coconut population, the selected genomic regions were enriched in pathways associated with amino acid metabolism and stress responses. Conspicuously, glutamate (Glu) and its derivatives showed significant correlations within the differentiated populations. The Glu metabolic enzyme P5CS was subjected to strong purifying selection, and haplotype-phenotype association analysis further identified the dominant CnP5CS1 allele genotype. Moreover, we established metabolic marker indicators to assess relative 2AP levels, based on the metabolic profiles of CnP5CS and the substrates and products of its catalyzed reactions. The Y1H assay identified the key transcription factor CnYAB2, which exhibited a strongly correlated expression pattern with CnP5CS1 and major markers of 2AP metabolism. The identification of CnP5CS1 offers a novel perspective on the genetic regulation of 2AP metabolism in aromatic coconuts and establishes a theoretical foundation for developing molecular markers to support the breeding of high-aroma varieties.

Aroma↗

PubMed2026

Metagenomic next-generation sequencing for tuberculosis diagnosis: enhanced performance and cost-effectiveness.

UNLABELLED: Metagenomic next-generation sequencing (mNGS) is a promising tool for diagnosing challenging infections like tuberculosis (TB). However, previous studies largely focused on case-specific application of mNGS in TB diagnosis. Thus, we conducted a retrospective observational study to first systematically evaluate the diagnostic performance and cost-effectiveness of mNGS for TB diagnosis. We retrieved a total of 16,776 results of the seven TB diagnostic assays, including mNGS, tuberculosis IgG antibody, TB interferon-γ release assay (TB-IGRA), TB-DNA, Xpert MTB/RIF (Xpert), culture, and acid-fast bacilli staining (AFS) from 3,757 participants with suspected TB infection at Sichuan Provincial People's Hospital from September 2021 to July 2024. Diagnostic metrics were compared against a composite reference standard. Microbial composition and a cost-utility analysis were performed. Among seven TB assays studied, the World Health Organization (WHO)-recommended assays AFS, culture, and Xpert, as well as TB-IGRA, were requested most frequently for TB diagnosis, whereas mNGS ranked last. mNGS demonstrated the highest specificity (100%), accuracy (72.3%), and area under the curve (AUC) (0.795). Its sensitivity in bronchoalveolar lavage fluid and tissue was 71.0% and 72.7%, respectively. Sequential use of mNGS after initial WHO-recommended tests (Xpert/Culture/AFS) significantly improved diagnostic performance (sensitivity, 70.4%; AUC, 0.823). Microbial analysis associated Candida albicans with TB. Cost-utility analysis showed sequential mNGS became cost-effective at higher willingness-to-pay thresholds (>200,000 RMB per correct diagnosis). mNGS offers superior specificity for TB diagnosis. A sequential strategy applying mNGS to conventional-test-negative cases provides enhanced diagnostic performance and is cost-effective at higher healthcare investment values, supporting its utility for diagnostically challenging TB. IMPORTANCE: This study systematically assesses the diagnostic performance and cost utility of metagenomic next-generation sequencing (mNGS) for tuberculosis (TB) in a large real-world cohort of 3,757 suspected patients, comparing it against six conventional assays (tuberculosis IgG antibody, TB interferon-γ release assay, TB-DNA, Xpert, culture, and acid-fast bacilli staining). mNGS demonstrated the highest specificity (100%), accuracy (72.3%), and area under the curve (AUC) (0.795), with sensitivities of 71.0% in bronchoalveolar lavage fluid and 72.7% in tissue. Notably, sequential use of mNGS after the World Health Organization-recommended tests significantly improved sensitivity to 70.4% and AUC to 0.823. Candida albicans showed significant differences among the three groups. The sequential mNGS strategy was cost-effective compared with no mNGS, and its cost-effectiveness increased with a rising willingness-to-pay threshold. Overall, these results highlight mNGS as a valuable supplementary tool for challenging TB cases, especially when conventional tests are inconclusive, and provide strong evidence for integrating it into diagnostic algorithms to optimize clinical decision-making and resource allocation.

Adult↗