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PubMed2026

Emergence of an optrA-positive Enterococcus faecalis ST699 lineage in animal-derived foods in Beijing, China.

Enterococci from animal-derived foods are key reservoirs for antimicrobial resistance (AMR) in the food chain. However, comparative genomic studies investigating the distribution of the oxazolidinone resistance gene optrA among food- and human-derived Enterococci remain limited. This study assessed linezolid-resistant Enterococci from retail meat and healthy humans in Beijing, China (2023-2024). Among 87 isolates, E. faecalis and E. faecium predominated. Food-derived isolates showed broader resistance profiles than human isolates. Fourteen optrA-positive strains were identified, accounting for 92.9% of food isolates. optrA frequently co-localized with erm(A), ant(9)-Ia, and fexA on Tn554-family transposons, suggesting a potentially transferable multidrug resistance module. Notably, an optrA-positive E. faecalis ST699 clone was identified for the first time in Chinese retail meat. This clone formed a distinct lineage and carried a complete Tn554-optrA island. A representative ST699 isolate exhibited enhanced fitness and virulence potential in the Galleria mellonella model. These findings highlight animal-derived foods as important reservoirs of linezolid-resistant Enterococci and provide genomic evidence consistent with their role as potential sources of optrA-mediated resistance. The emergence of a multidrug-resistant E. faecalis ST699 clone with enhanced fitness characteristics underscores the need for continued surveillance of foodborne antimicrobial resistance within the One Health framework.

Enterococcus faecalis↗

PubMed2026

Metagenome-scale modeling to assess microbiome metabolic complementarity for precision microbiota transplantation therapies.

Fecal microbiota transplantation (FMT) holds therapeutic promise beyond recurrent Clostridioides difficile infection, but clinical outcomes remain unpredictable and donor-selection strategies remain limited, in part because the role of donor‒recipient metabolic interactions in shaping the post-FMT community remains poorly understood. Here, we leverage metagenome-scale metabolic modeling to quantify metabolic niche complementarity between donor and recipient microbiomes and predict post-FMT community composition. Using MICOM-derived metabolic models, we show that donor genomes whose metabolic flux profiles are more dissimilar from the recipient community colonize at significantly higher rates in a murine FMT model. In a human IBS trial, the same metric predicted post-FMT community composition via leave-one-out cross-validation and captured known disease-associated alterations in short-chain fatty acid, sulfur, and gas metabolism. We then performed 2,548 in silico FMT simulations between IBS-D/M patients and donors from the OpenBiome biobank to evaluate personalized donor screening, identifying super-donors characterized by high taxonomic diversity, broad metabolic niche coverage, and community interaction networks dominated by cross-feeding rather than competition. Together, these results support metabolic niche complementarity as a potential determinant of post-FMT community composition and provide a mechanistic basis for evaluating donor-recipient metabolic compatibility. This framework offers a scalable approach for generating testable hypotheses for personalized donor selection.

Fecal Microbiota Transplantation↗

PubMed2026

Tigecycline-resistant Staphylococcus in waiting pens of a pig slaughterhouse: genomic insights into a food safety alert.

BACKGROUND: The waiting pens of slaughterhouses represent a critical control point in the 'farm-to-fork' continuum, yet their role in the emergence and dissemination of antimicrobial resistance remains understudied. This study investigated tigecycline-resistant Staphylococcus (TRS) in these high-risk zones to assess their prevalence, resistance mechanisms, and transmission dynamics. METHODS: 400 samples were collected from the waiting pens of a pig slaughterhouse in Guangzhou, China. Antimicrobial susceptibility testing, whole-genome sequencing, phylogenetic analysis, and molecular cloning were employed to characterize resistance mechanisms and transmission patterns. RESULTS: 78 TRS strains were isolated and classified into three species, including S. borealis, S. ureilyticus, and S. pasteuri. These isolates exhibited multidrug-resistant phenotypes and carried new mutations in rpsJ and tet(M), which were functionally confirmed to reduce tigecycline susceptibility. Phylogenetic evidence demonstrated clonal transmission between pig farms and the slaughterhouse. The tet(M) gene was located within Staphylococcal cassette chromosome mec elements mediated by IS257, while tet(L) was carried by plasmids formed through IS256/IS257-mediated recombination. CONCLUSIONS: Waiting pens serve as crucial reservoirs for the amplification and dissemination of antimicrobial resistance. Our findings underscore the urgent need for enhanced biosecurity measures, improved waste management, and routine molecular surveillance in these high-risk zones to mitigate the spread of resistance along the food production chain.

Animals↗

PubMed2026

Construction of circRNA-miRNA-mRNA regulatory networks in the intestine of turbot (Scophthalmus maximus) following Vibrio anguillarum infection.

Circular RNAs (circRNAs) play pivotal roles in post-transcriptional regulation by acting as molecular sponges for microRNAs (miRNAs) within the competitive endogenous RNA (ceRNA) network. However, the regulatory mechanisms in teleost immune responses remain poorly understood. In this study, circRNA-miRNA-mRNA networks were investigated in turbot (Scophthalmus maximus) following Vibrio anguillarum infection to elucidate host-pathogen interactions. Through high-throughput sequencing of intestinal tissues, a total of 50 differentially expressed circRNAs (DE-circRNAs) (18 at 2 hpi, 16 at 12 hpi, 16 at 48 hpi), 212 DE-miRNAs (11 at 2 hpi, 70 at 12 hpi, 15 at 48 hpi), and 1774 DE-mRNAs were identified. Functional enrichment analyses (GO/KEGG) revealed significant associations with immune pathways, including the MAPK signaling pathway and gap junction. An integrated circRNA-miRNA-mRNA regulatory network was constructed, highlighting key interactions including novel_circ_0002573/DE-miR-27a-3p/FGB and novel_circ_0002423/novel_347/GNE, which may regulate inflammatory and antibacterial responses. The expression patterns of selected circRNAs, miRNAs and mRNAs were validated using qRT-PCR, confirming the reliability of the sequencing results. Importantly, fibrinogen beta chain (FGB) and CXCR4/CXCL12 signaling were identified as critical immune modulators. These findings provide insights of the ceRNA regulatory networks involved in teleost intestinal immunity and provide potential molecular targets for selective breeding of disease resistance in this species.

Animals↗

PubMed2026

Genome-Wide Characterization of β-Glucosidase (TaBGLU) Genes in Bread Wheat and Their Expression Under Drought, Cold, and Combined Stress.

Glycoside hydrolase 1 (GH1) β-glucosidases were known to activate hormone conjugates and defense metabolites, yet their genomic organization and stress-response dynamics in wheat remained incompletely defined. We therefore performed an integrated characterization of TaBGLUs spanning phylogeny, gene structure and conserved motifs, subcellular localization, promoter cis-elements, Gene Ontology enrichment, protein-protein interaction networks, and targeted expression profiling. Wheat TaBGLUs partitioned into well-supported clades that shared canonical GH1 catalytic residues and a largely conserved motif scaffold. Subcellular localization predictions indicated predominant nuclear and chloroplast targeting, with a smaller cohort directed to secretory or endomembrane compartments. Promoters were enriched for light-responsive, hormone-related (ABA, JA/SA, auxin, GA) and stress-associated (MYB/WRKY, heat, low temperature) cis-elements, and functional annotations were consistent with roles in carbohydrate and cell-wall metabolism, hormone homeostasis, and defense. Network analysis revealed a densely connected TaBGLU submodule embedded within broader carbohydrate and defense interaction networks, suggesting coordinated or cooperative functions. Expression profiling under cold, drought, and combined drought and cold demonstrated broad stress inducibility, with early activation detected by 6 h, cold-responsive maxima typically at 12 h, drought-responsive peaks predominating at 24 h, and combined stress eliciting both earlier and more sustained expression maxima between 12-24 h. Representative strongly responsive genes included TaBGLU20, TaBGLU44, TaBGLU6, and TaBGLU23, which showed pronounced late induction under combined stress, TaBGLU30, which exhibited an earlier combined-stress peak, and TaBGLU12, which displayed a marked late drought-specific response. Taken together, this integrated genomic, regulatory, and expression atlas refined the wheat BGLU repertoire relative to previous gene model inventories, highlighted candidate TaBGLUs with central network positions and strong stress inducibility, and provided concrete entry points for functional validation and breeding for improved stress resilience.

Triticum↗

PubMed2026

Investigation of ACE gene polymorphism and serum ACE activity in relation to alopecia areata among Iraqi patients.

BACKGROUND: Alopecia areata (AA) is a multifactorial disorder with immune dysregulation and genetic susceptibility, affecting 0.5-2% globally. OBJECTIVE: This study investigated angiotensin converting enzyme (ACE) gene insertion /deletion (I/D) polymorphism and serum ACE activity in Iraqi AA patients and their association with inflammatory cytokines (interleukin [IL]-17) and nutritional markers to understand disease progression. METHODS: This case-control study included 50 AA patients (Male and Female) and 35 healthy controls. ACE gene polymorphism (rs1799752) was analyzed using real-time polymerase chain reaction (qPCR) with high-resolution melting (HRM) analysis. Serum IL-17 levels were determined by enzyme-linked immunosorbent assay (ELISA), and biochemical markers were measured using an automated analyzer. RESULTS: ACE gene polymorphism (rs1799752) showed non-significant genotype distribution between patient and control groups (p > 0.05), though a trend toward DD genotype enrichment was observed in patients. Serum ACE levels were significantly higher in patients versus controls (p < 0.0001) with high diagnostic performance. ACE correlated positively with IL-17 (P < 0.0001) and negatively with vitamin D3 and zinc (P < 0.0001). Female patients had significantly higher ACE levels than males (P < 0.01). CONCLUSIONS: ACE emerges as an immunometabolic hub in AA pathogenesis, integrating inflammation with nutritional deficits, suggesting its potential as a biomarker and therapeutic target.

Humans↗

PubMed2026

Hyperbaric oxygen for the treatment of traumatic incomplete spinal cord injury: a systematic review and meta-analysis of randomized controlled trials.

The therapeutic efficacy of hyperbaric oxygen therapy for traumatic incomplete spinal cord injury remains a subject of debate. To comprehensively evaluate the impact of hyperbaric oxygen on motor function, sensory function, and activities of daily living in patients with traumatic incomplete spinal cord injury, we conducted a systematic review and meta-analysis. We performed a comprehensive search across PubMed, Embase, the Cochrane Library, Web of Science, and major Chinese databases for randomized controlled trials published through June 2025. A total of 15 randomized controlled trials were included. The pooled results indicated that hyperbaric oxygen therapy significantly improved the American Spinal Injury Association motor score (mean difference = 10.30, 95% confidence interval: 7.70-12.90), the total American Spinal Injury Association sensory score (mean difference = 29.29, 95% confidence interval: 18.82-39.75), the American Spinal Injury Association light touch score (mean difference = 9.84, 95% confidence interval: 6.15-13.53), and the American Spinal Injury Association pinprick score (mean difference = 8.75, 95% confidence interval: 4.40-13.11). Furthermore, hyperbaric oxygen therapy was associated with significant enhancements in the Barthel Index (mean difference = 16.60, 95% confidence interval: 10.51-22.68) and the Functional Independence Measure (mean difference = 17.41, 95% confidence interval: 10.83-23.98). In conclusion, adjunctive hyperbaric oxygen therapy appears to improve motor function, sensory function, and activities of daily living in patients with traumatic incomplete spinal cord injury compared to conventional treatments alone. However, due to methodological limitations and potential publication bias in the included studies, these findings should be interpreted with caution, and further high-quality, multi-center randomized controlled trials are warranted.

Humans↗

PubMed2026

Metabolic and endocrine modulation of the gut-adipose tissue axis via pro-, pre-, and postbiotics in overweight dogs: A systematic review.

Canine obesity is a complex metabolic disorder driven by luminal dysbiosis, impaired gut barrier function, and metaflammation. Following PRISMA 2020 guidelines, this systematic review evaluated the efficacy of pro-, pre-, and postbiotics in modulating the gut-adipose tissue axis in overweight dogs (BCS ≥ 6/9) or diet-induced obesity models. Searches across PubMed and Dimensions (April 2026) identified seven eligible experimental trials. Results suggest that postbiotic Bifidobacterium animalis subsp. lactis CECT 8145 reduced postprandial glucose AUC by 6 % strictly during energy restriction. Pasteurized Akkermansia muciniphila postbiotics limited diet-induced weight gain, though glucoregulatory impacts were highly strain-specific (AKK2 reduced fasting glucose and insulin resistance indexes, whereas EB-AMDK19 exerted no significant effect). Specific probiotics (including Enterococcus faecium, Bifidobacterium lactis, Lactiplantibacillus plantarum and Bifidobacterium breve) attenuated fasting hyperinsulinemia and preserved circulating adiponectin, but lipid profile improvements (triglycerides and total cholesterol) were inconsistent across trials. In dogs, increased luminal short-chain fatty acids are not consistently mirrored by endocrine responses, so the coupling between microbial metabolites and incretin signaling remains incomplete. A critical lack of standardized reporting for species-validated insulin sensitivity metrics was identified. In conclusion, microbiome-targeted therapies, particularly inanimate postbiotics, may represent useful adjunctive strategies to mitigate metabolic dysregulation in obesogenic environments. However, clinical efficacy remains strictly strain-specific and dependent on host energy balance. Given the scarcity of high-certainty evidence, future trials must integrate dynamic physiological assessments with species-validated surrogate indexes alongside standardized dietary controls.

Animals↗

PubMed2026

Complexity in disguise: a systematic review of fractal analysis in psychiatric neuroimaging.

OBJECTIVES: Psychiatric diagnosis and fractal studies are complex processes that extend beyond clinical evaluation and require careful methodological considerations in neuroimaging. Over the years, fractals have helped reduce these complexities in research, but they still cannot grant clinical diagnoses. Thus, the main objective was a systematic review exploring the potential applications of fractal analysis in characterizing psychiatric conditions through neuroimaging techniques-including both functional and structural MRI. MATERIALS AND METHODS: A systematic literature review was conducted on PubMed, identifying thirty-nine original studies that met the inclusion criteria. Areas showing statistical significance (p < 0.05) were reported. These studies were categorized according to DSM-V classification and examined for the description of psychiatric conditions through the fractal analysis. RESULTS: The review primarily focuses on young adults with psychiatric conditions compared to control groups. Schizophrenia and Autism Spectrum Disorder are major areas of investigation, and fractal dimension (FD) is the primary analysis method used to reflect brain patterns. Studies that calculated whole-brain FD may have underestimated local abnormalities due to the inclusion of a high percentage of tissue, potentially resulting in overlooked findings. Notably, abnormalities in the frontal cortex represent a common neurobiological feature across several psychiatric conditions. CONCLUSIONS: The findings from this systematic review shed light on the use of fractal analysis to quantify complex brain patterns in both psychiatric patients and healthy individuals. However, it is essential to recognize the need for further research to elucidate a fractal analysis protocol that allows for optimal extraction of psychiatric insights. KEY POINTS: Question Fractal analysis applied to structural and functional MRI help characterize brain alterations across psychiatric conditions. Findings This review shows consistent fractal patterns across multiple psychiatric disorders, especially in frontal regions. Despite heterogeneous methodologies, results highlight shared structural and functional abnormalities. Clinical relevance Fractal analysis may offer complementary characterization of subtle brain organization across psychiatric disorders. Its potential clinical utility-such as improving diagnostic characterization, earlier detection, among others-remains limited by the current absence of a standardized protocol.

Humans↗

PubMed2026

Towards microplastic bioremediation: Fungal degradation of pristine and pretreated high-density polyethylene and polystyrene.

Microplastic (MP) contamination has become a significant ecological issue because of its enduring existence in the ecosystem and its possible negative impacts. Therefore, using degrading strategies to eliminate these stubborn polymers has been a subject of scientific research. However, the currently used degradation methods are relatively inefficient. Given the pervasiveness of High-Density Polyethylene (HDPE) and Polystyrene (PS) and their resistance to biodegradability, disposal strategies are critical and must be addressed. This manuscript examines the biodegradation of pristine and UV-treated HDPE and PS MPs by Aspergillus flavus species in minimal growth media over 70 days. The maximum weight loss observed at 70 days for pristine HDPE and PS in sole carbon source (SCS) media was (29.33 ± 0.28) % and (17.67 ± 0.35) %, respectively. Whereas, for UV-treated HDPE and PS MPs, the % weight reduction was (33 ± 0.21) % and (25 ± 0.19) %, respectively. UV-treated MPs exhibited greater weight reduction, as UV induced oxygenated functional groups enhance polymer susceptibility to enzymes, thereby promoting biodegradation. HDPE MPs typically show a higher proportion of particles in the lower size range compared to PS MPs. This assertion was based on the weight loss, particle size distribution, and SEM analysis. Furthermore, chemical changes were evaluated using Fourier transform Infrared Spectroscopy (FTIR) analysis, which also displayed chemical oxidation occurring during biodegradation. Liquid Chromatography-Mass Spectrometry (LC-MS) results indicate that UV pretreatment enhances biodegradability by promoting chain scission. These findings further suggest that this fungus's natural and ubiquitous occurrence in terrestrial and marine environments may actively contribute to MP biodegradation while requiring few nutrients.

Microplastics↗

PubMed2026

Premature closure underlies bias in medical diagnosis in students: A randomised controlled experiment.

OBJECTIVE: The purpose of the study reported in this article was to shed light on the cognitive mechanism mediating between biasing information and diagnostic error. The literature suggests at least two different hypotheses: premature closure leading biased participants to spend less time on diagnosis or increased competition between diagnostic hypotheses. The latter hypothesis predicts that biased participants would spend more time reaching a diagnosis. METHOD: Using the salient distracting findings (SDF) experimental paradigm, we biased 58 fourth-year medical students while diagnosing 12 clinical vignettes in a within-group incomplete block design under three conditions: cases presented without SDF, with SDF at the beginning and with SDF at the end. For each of these conditions, diagnostic accuracy, the number of SDF-related mistakes and time per word needed to process the case were recorded. The data were analysed using linear mixed modelling. Estimated marginal mean scores were reported. RESULTS: Participants confronted with salient distracting features (SDFs) at the beginning of a clinical case demonstrated significantly lower diagnostic accuracy (mean 0.11) compared with the No-SDF condition (0.27), representing a 61% reduction (F2,693 = 11.995, p < 0.001), and made more SDF-related mistakes (F2, 693 = 16.395, p < 0.001). When SDFs were presented at the end of the case, diagnostic accuracy was also reduced (mean 0.17; 36% reduction), but processing time did not differ from the No-SDF condition. Only early presentation of SDFs was associated with reduced processing time per word (F2,636 = 4.799, p < 0.01), consistent with premature closure. CONCLUSION: These findings demonstrate that biasing information increases diagnostic error in medical students and that only early bias is associated with reduced information processing. The data do not support the competition hypothesis for early bias, as processing time did not increase under biasing conditions. Premature closure can therefore be directly observed rather than inferred, inviting further research.

Humans↗

PubMed2026

Decoding the spatiotemporal patterns of food spoilage microbial communities: Integrating multi-omics and artificial intelligence to enable precision preservation.

In the global food supply chain, food wastage caused by spoilage has resulted in significant economic losses, food shortages, and environmental pressure. This process is fundamentally driven by the spatiotemporal dynamics of microbial communities. However, traditional research methods struggle to elucidate the complex mechanisms of spatial heterogeneity, interspecies interactions, and functional succession. This limits the development of effective preservation strategies. This review systematically reviews the cutting-edge progress of integrating multi-omics technologies and artificial intelligence (AI) to study food spoilage microbial communities, breaking through this bottleneck. We propose an intelligent theoretical framework that could potentially analyze microbial metabolic activities and predict dynamic shelf life if implemented. The conceptual framework integrates multidimensional data, including spatial metabolomics, temporal metatranscriptomics, single-cell transcriptomics, and longitudinal metagenomics. It can also be combined with AI models, such as graph neural networks. The article elaborates on the principles and applications of spatio-temporal monitoring technologies, such as nano secondary ion mass spectrometry, hyperspectral imaging, and the Internet of Things sensing. Through illustrative cases of typical perishable foods, it also explores how such a multi-omics - AI system might be applied to spoilage warning and precise intervention. Additionally, the article addresses the current challenges in data coverage, model generalization, and federated learning implementation. Then the research further explores emerging areas such as engineered probiotics, edge AI, and microfluidic sensing. These areas are targeted at transforming food preservation from an empirical control approach to a data-driven, precise regulatory framework. This transformation provides theoretical support and technical approaches for developing a smart, sustainable food preservation system.

Multiomics↗

PubMed2026

Diversification of yeast proteins as an approach for the development of sustainable food systems.

Despite growing trend in sustainable protein sources, yeast proteins have mainly been explored as a source of bioactive peptides using a monospecies and general protein approach. The contribution of highly abundant protein fractions in the yeast proteome to peptide formation remains insufficiently investigated, limiting a comprehensive understanding of yeast proteins as optimized peptide sources. The current review presents a systematic analysis of yeast proteins as emerging protein sources and evaluates the suitability of high-abundance proteins as bioactive peptide precursors by in silico techniques. Moreover, brewery by-product and single-cell yeast protein approaches are compared in terms of composition and techno-functionality whereas peptide formation mechanisms (in situ and ex situ) and regulatory aspects for food applications are also addressed. Cytoplasmic metabolic proteins, particularly glycolytic enzymes (GAPDH), are identified as highly abundant fractions of the yeast proteome. Proteins associated with cell and organelle membranes also contribute substantially based on cellular localization. These findings imply that such proteins may act as key precursors of yeast-derived bioactive peptides. In silico hydrolysis with Alcalase suggests a tendency toward the generation of short-chain peptides (3-11/14 aa), which may support biological activity. Moreover, peptide profiles appear to vary across yeast species, highlighting the role of species diversity in peptide generation. While single-cell yeast protein allows more controlled production than brewery by-products, nucleic acid content in both may limit applications. Overall, yeast proteins appear to be metabolically adaptable and species-diverse sources for various biological peptides.

Saccharomyces cerevisiae↗

PubMed2026

To Treat or Not to Treat: Navigating Early-Stage CLL in the Era of Targeted Therapy.

Chronic lymphocytic leukemia (CLL) is most frequently diagnosed at early, asymptomatic stages (Rai 0/Binet A), in which a watch-and-wait strategy remains the standard of care, based on historical trials demonstrating no overall survival benefit from early treatment. Over the past two decades, however, substantial advances in genomic profiling-including immunoglobulin heavy-chain variable region (IGHV) mutational status, TP53 disruption, recurrent gene mutations, and complex karyotype-have uncovered marked biological heterogeneity among early-stage patients and substantially improved prediction of disease progression. In parallel, targeted therapies such as Bruton tyrosine kinase (BTK) inhibitors and venetoclax-based combinations have transformed the management of symptomatic CLL, raising renewed interest in whether early intervention might favorably alter the natural history of biologically high-risk disease. In this review, we critically examine the evolution of prognostication in early-stage CLL, integrate contemporary molecular and clinical risk models, and summarize evidence from both historical chemotherapy-era studies and modern early-intervention trials. We discuss key unresolved controversies, including reliance on surrogate endpoints, the risks of overtreatment, and the persistent absence of an overall survival benefit across all early-treatment strategies. Finally, we outline future research priorities, including refined genomic stratification, minimal residual disease-driven (MRD)-driven approaches, and combination targeted therapies currently under investigation. Despite renewed interest in preemptive treatment, available evidence supports continued observation for asymptomatic patients outside clinical trials.

Humans↗

PubMed2026

Construction of precision clinical-proteomics risk model based on machine learning for predicting heart failure in type II diabetes mellitus.

BACKGROUND AND AIMS: Heart failure (HF) is a severe complication in type 2 diabetes mellitus (T2DM), but current risk stratification scores have limited predictive accuracy. We aimed to develop novel prediction tools integrating clinical variables with proteomics to improve risk stratification of hospitalization for HF in T2DM. METHODS AND RESULTS: In this study, we included 2111 UK Biobank participants with T2DM but no prior HF, and profiled 2920 proteins to predict 10-year incident HF hospitalization. Participants were randomly divided into training (70%), tuning (10%), and validation (20%) sets.Three prediction models were developed: a Clinical model based on demographic characteristics, comorbidities, medication use, and laboratory indices; a Protein model based on 40 proteins selected by the Light Gradient Boosting Machine (LGBM); and the Clinical OMics and Protein ASSessment for Heart Failure (COMPASS-HF) model, which integrated both clinical variables and the LGBM-selected proteins. Models were evaluated for area under the curve (AUC), sensitivity, and specificity. During follow-up, 168 participants (7.96%) developed incident HF. The COMPASS-HF model showed better discrimination than the Clinical model, with an AUC of 0.897 (95% CI: 0.850-0.945) versus 0.790 (95% CI: 0.723-0.856). It also demonstrated higher sensitivity (0.882; 95% CI: 0.725-0.967) and consistent performance in subgroups. COMPASS-HF effectively stratified risk of hospitalization for HF, with cumulative incidence rates of 31.9% in the high-risk group and 1.2% in the low-risk group. CONCLUSIONS: By combining clinical and proteomic variables, we developed a high-performance HF prediction model for T2DM, enabling precise risk stratification and informing early intervention strategies.

Humans↗

PubMed2026

Molecular Diagnostics for WHO Priority Bacterial Pathogens: A Bibliometric Mapping of Diagnostic Platforms, Resistance Markers, and Antimicrobial Resistance Research Trends.

Antimicrobial resistance (AMR) constrains effective treatment and carries implications for infection control, surveillance, and public health. The World Health Organization (WHO) priority bacterial pathogen framework has intensified the need for diagnostic innovation by redefining research priorities around organisms combining high disease burden with complex resistance profiles. Molecular diagnostics have accordingly moved beyond culture-based workflows, integrating rapid pathogen identification, resistance-marker detection, genomic surveillance, and clinical decision support. The present study conducted a bibliometric mapping of the literature on WHO priority pathogens. Rather than addressing resistance at a general level or a single pathogen or technology, it integrates priority pathogens, molecular platforms, and resistance markers within a single framework, tracing their joint thematic and temporal evolution along an explicit pathogen-platform-marker axis. Scopus-indexed articles and reviews (2000-2025) were retrieved, yielding 1746 publications after screening adapted from the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Analyses used Bibliometrix/Biblioshiny, R, and VOSviewer. The literature expanded markedly after 2018, led by China and the United States. Methicillin-resistant Staphylococcus aureus (MRSA), Mycobacterium tuberculosis, Enterococcus faecium, and the Enterobacterales-carbapenemase axis constituted the principal thematic cores, whereas conventional polymerase chain reaction (PCR)/nucleic acid amplification testing (NAAT) and whole-genome sequencing were the dominant platforms. Overall, the field has evolved from pathogen detection into an AMR-centered translational domain encompassing resistance prediction, genomic epidemiology, surveillance, and clinical decision support. Diagnostic development, stewardship, and surveillance depend on hybrid workflows coupling rapid marker-targeted assays with genome-based characterization, delivering actionable resistance within clinically meaningful timeframes, and extending coverage to underrepresented pathogens and platforms.

Humans↗

PubMed2026

Dynamic lysine acetylation and succinylation of platelet proteins regulates platelet storage lesion: mechanistic insights from multi-omics.

OBJECTIVES: Platelet storage lesion (PSL) severely impairs platelet function during storage, presenting a major hurdle in transfusion medicine; however, the dynamic interplay between global proteomic changes and post-translational modifications (PTMs) underlying these functional deteriorations remains insufficiently characterized. Here, we report the first comprehensive multi-omics analysis integrating global proteomics, acetylomics, and succinylomics to dissect the molecular dynamics during platelet storage. METHODS: We performed quantification of global proteomics, acetylome and succinylome based on TMT-labeled LC-MS/MS analysis, combined with antibody-affinity enrichment and purification. Dynamic molecular changes and functional transformation of platelet were also characterized under proper conditions stored for 1, 3, 5, 7 days, respectively. RESULTS: We systematically characterized 3,609 proteins, 1,308 acetylation sites, and 1,947 succinylation sites across multiple storage time points (D1, D3, D5, D7). We distinct temporal patterns of post-translational modifications, with succinylation showing more extensive coverage than acetylation in platelets. Pathway enrichment analysis revealed extensive metabolic reprogramming involving complement activation, energy metabolism, and cellular detoxification processes. The identification of specific motif patterns provided mechanistic insights into the functional specificity of these modifications. Random forest machine learning identified 20 core regulatory proteins representing critical nodes in PSL development. Furthermore, we employed real - time quantitative polymerase chain reaction (RT - QPCR) to measure the expression levels of key genes related to platelet function and PTM - associated pathways. CONCLUSION: By mapping the interplay between proteomic abundance shifts and PTM dynamics, this study provides a multidimensional understanding of PSL, establishing a foundational framework for optimizing storage protocols and enhancing transfusion safety.

Blood Platelets↗

PubMed2026

A horizontally acquired gene mediates insect cocoon pigmentation in the eri silkmoth, Samia ricini.

Holometabolous insects make cocoons during larval-pupal metamorphosis to protect the pupal phase. The materials used for cocoon construction vary widely. Lepidopteran insects typically secrete silk to form cocoons, which display diverse colors. The eri silkworm, Samia cynthia ricini, is an economically important domesticated species that mostly produces white cocoons, with some varieties producing red cocoons. The enzyme kynureninase (KYNU), acquired from bacteria by horizontal gene transfer, has previously been implicated in insect coloration, while the tryptophan metabolite 3-hydroxyanthranilic acid (3-HAA) has been identified as a red pigment. However, exactly how KYNU is involved in cocoon pigmentation remains unclear. Here, we report that a horizontally transferred bacterial gene encoding KYNU regulates red cocoon formation. Metabolomic analysis revealed a high accumulation of 3-HAA in red cocoons, confirming its role as the primary pigment and associating the coloration with tryptophan metabolism. Quantitative real-time polymerase chain reaction (qPCR) analysis indicated that SrKYNU is highly expressed in the silk glands and significantly downregulated in the red cocoon strain compared to the white cocoon strain. Genomic sequencing identified a 141 bp deletion in the upstream regulatory region of KYNU in the red cocoon strain compared to the white cocoon strain. Dual-luciferase assays confirmed that this deletion significantly reduced promoter activity. CRISPR/Cas9 knockout of SrKYNU in the white-cocoon strain resulted in mutants producing red cocoons with elevated 3-HAA content. These findings reveal that the horizontally transferred gene SrKYNU exhibits tissue-specific expression and regulates cocoon coloration in S. ricini, illustrating that horizontal gene transfer can play an important role in regulating an insect physiological process.

Animals↗