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PubMed2026

A mechanism-guided framework for prioritizing membrane-interaction anti-Vibrio peptides from peptidomics data.

A mechanism-guided framework for prioritizing membrane-interaction antimicrobial peptide candidates from proteomics-derived peptide mixtures is presented. The framework integrates conservative machine-learning-based antimicrobial peptide (AMP) screening with a literature-derived membrane-interaction plausibility (MAP) assessment and a data-driven membrane-interaction ranking function (AIPx), followed by structural visualization for interpretability. MAP encodes physicochemical characteristics commonly associated with peptide-membrane interaction and provides a graded plausibility assessment. Building upon this physicochemically interpretable framework, AIPx ranks peptides using feature weights calibrated from experimentally characterized anti-Vibrio peptides, where minimum inhibitory concentration (MIC) values are used as a coarse-grained ranking reference rather than a direct prediction target. In a peptidomics-based peptide fractionation study targeting Vibrio spp., AIPx exhibited a consistent relationship with experimentally observed antibacterial activity. Distributional analysis revealed that peptide fractions exhibiting high anti-Vibrio activity are characterized by enrichment of high-ranking peptides rather than by AMP abundance alone. By structuring AMP identification and prioritization as sequential stages, the MAP + AIPx framework enables interpretable and experimentally actionable candidate selection by reducing biologically implausible candidates. The framework facilitates species-oriented prioritization of AMP candidates, addressing a key challenge in antimicrobial peptide discovery where activity may depend on target-specific membrane characteristics. Moreover, the approach is extensible through species-specific calibration and supports interpretable, mechanism-informed prioritization in antimicrobial peptide discovery.

Proteomics↗
PubMed2026

Forensic taphonomy in fluvial water: A systematic review.

Human remains are frequently recovered from fluvial (lotic) water environments. Rivers, streams, canals and other flowing water bodies pose distinct challenges in forensic practice, particularly due to their current. Compared to other aquatic contexts, fluviatile taphonomy is underrepresented in the forensic literature and the last comprehensive summary was written over a decade ago. Therefore, a systematic review was performed to collect and summarise the current knowledge in forensics about fluvial taphonomy, including decomposition of remains, transport characteristics, search, postmortem submersion interval (PMSI) estimation, taphonomic alterations, and differences to other water bodies. 92 reports met the inclusion criteria for this review, most of them showed a moderate risk of bias. Their main findings were summarised and two major challenges identified. First, predictions about fluvial transport of human bodies pose a tremendous issue in forensic practice, leading to later detection and lower recovery rate of remains, complicating various subsequent analyses. Second, PMSI estimations are difficult particularly due to variable environmental conditions in fluviatile systems. Recommendations for future research in the area of fluvial forensic taphonomy include that case-related data such as the detailed decomposition state and river characteristics need to be made available. More standardised research protocols are required for a facilitated comparison between studies, environments and regions. This review provides forensic practitioners with a comprehensive, updated resource for the investigation of fluvial remains. It also guides future research towards a more efficient practice to build the basis for a broader, more robust and comprehensive synthesis, subsequently supporting analyses in forensic casework.

Humans↗
PubMed2026

Cross-tissue multi-omics integration highlights BPHL and mitochondrial targets in Alzheimer's disease.

BACKGROUND: Mitochondrial dysfunction is a hallmark of Alzheimer's disease (AD), yet specific molecular targets remain to be fully characterized. METHODS: A summary-data-based Mendelian randomization (SMR) framework integrated AD genome-wide association study (GWAS) statistics (39,918 cases) with blood DNA methylation quantitative trait loci (mQTL), gene expression (eQTL), and protein (pQTL) data for 1136 mitochondria-related genes. Associations were assessed using Bayesian colocalization and HEIDI testing. Tissue relevance was evaluated in four brain regions (hippocampus, amygdala, cortex, frontal cortex) using GTEx and external transcriptomic datasets. RESULTS: Screening identified eight candidates supported across blood mQTL and eQTL layers. Stepwise central nervous system (CNS) evaluation singled out biphenyl hydrolase-like (BPHL) as the consistent candidate. Higher genetically predicted BPHL expression was associated with reduced AD risk across the hippocampus (OR=0.920, 95% CI 0.873-0.970), amygdala (OR=0.925, 95%CI 0.880-0.973), cortex (OR=0.943, 95% CI 0.908-0.978), and frontal cortex (OR=0.938, 95%CI 0.901-0.976). These findings aligned with protein-protein interactions connecting BPHL to respiratory complexes and lower BPHL expression in independent AD brains. Functional enrichment converged on oxidative phosphorylation pathways. CONCLUSIONS: By integrating multi-omics data with tissue-specific validation, this study nominates BPHL as a consistent protective candidate in the brain. These findings provide genetic support for mitochondrial molecular perturbations in AD, offering insights for future validation.

Alzheimer Disease↗
PubMed2026

Effects of exercise snacking on neuromuscular performance in insufficiently active adults: A systematic review and meta-analysis.

OBJECTIVE: To examine the effects of exercise snacking (ES) on neuromuscular performance in insufficiently active adults. METHODS: Six databases were searched from inception to July 17, 2026. Randomized controlled trials and non-randomized studies of interventions involving insufficiently active adults undertaking ES interventions were included. Outcomes were functional performance, muscular strength, and muscular power. A three-level random-effects meta-analysis was performed. Risk of bias was assessed with RoB 2 or ROBINS-I, and certainty of evidence was evaluated using GRADE. RESULTS: Nine studies (13 reports) involving 313 participants were included. In the primary three-level model, ES showed a small positive overall effect on neuromuscular performance (g = 0.37, 95% CI 0.16-0.58, p = 0.001), which remained supported under trial-clustered robust inference with small-sample adjustment. Domain-specific estimates for muscular power/velocity, functional performance, and muscular strength were positive but imprecise and were not statistically supported after small-sample robust adjustment. Robust moderator tests provided no evidence of between-subgroup differences, and the certainty of evidence was low for all outcomes. CONCLUSION: Current low-certainty evidence suggests that ES may produce a small improvement in overall neuromuscular performance. However, domain-specific effects remain uncertain because of the limited number of independent trials, and the overall prediction interval crossed zero, indicating uncertainty across future populations and settings. Larger, preregistered randomized controlled trials are needed to confirm these preliminary findings.

Adult↗
PubMed2026

Microbial diversity, functional activities, and safety risks in fermented tea: a comprehensive review.

Microbial fermented teas are gaining global popularity due to their unique sensory profiles and health benefits. The quality and safety of these products are governed by complex microbial ecosystems that orchestrate the biotransformation of tea leaf components. This review addresses a critical paradox in the field: the same microbial activities that generate desirable bioactive metabolites, such as theabrownins and organic acids, also create ecological niches for mycotoxigenic fungi, posing significant health risks from contaminants like ochratoxin A, citrinin, and aflatoxins. While extensive research has cataloged the microbial diversity in these systems, a comprehensive framework linking processing environments to microbial community assembly, functional outcomes, and quantifiable safety risks remains elusive. This review systematically bridges this gap by synthesizing current knowledge on the microbial consortia-dominated by Aspergillus, Penicillium, Bacillus, and Lactiplantibacillus species-that drive tea fermentation. We critically analyze their functional roles in enhancing flavor, bioactivity, and potential probiotic activity while simultaneously evaluating the mechanisms of mycotoxin production and accumulation. By integrating microbial ecology, biochemistry, and food safety, we propose a forward-looking perspective focused on transitioning the industry from traditional, spontaneous fermentation to modern, controlled biotechnological processes. This approach, centered on the use of defined starter cultures, predictive modeling, and active biocontrol strategies, provides a roadmap for ensuring the consistent quality and safety of fermented tea products, ultimately unlocking their full potential as high-quality functional foods.

Tea↗
PubMed2026

Bioactive peptides for meat quality and preservation: Integrating peptidomics and computational screening.

Bioactive peptides generated from meat proteins, fermented meat products, and slaughter by-products have attracted increasing attention as functional molecules for improving meat quality and preservation. In meat systems, peptides can be produced through endogenous postmortem proteolysis, microbial fermentation, gastrointestinal digestion, or controlled enzymatic hydrolysis of underutilized animal by-products. These peptides are closely associated with key meat science endpoints, including postmortem tenderization, oxidative stability, color retention, flavor development, microbial inhibition, and the valorization of processing by-products. However, although high-resolution peptidomics has greatly expanded the identification of meat-derived peptide sequences, their translation into practical meat applications remains limited by matrix interactions, processing stability, sensory constraints, safety concerns, and insufficient validation in real meat systems. This review synthesizes recent advances in meat-related peptidomics and computational screening, including sequence-based prediction, machine learning, molecular docking, molecular dynamics, stability assessment, and safety-oriented filtering. Particular attention is given to how these approaches can prioritize peptides with antioxidant, antimicrobial, flavor-modulating, and preservation-related functions under meat-specific technological constraints. By integrating peptide generation pathways, mass spectrometry-based identification, in silico prioritization, and meat quality endpoints, this review proposes a stage-gated framework for translating meat-derived bioactive peptides from discovery to application. Future research should strengthen matrix-specific validation, standardized peptidomic reporting, and safety assessment to support the use of bioactive peptides in meat quality improvement, clean-label preservation, and circular utilization of meat industry by-products.

Animals↗
PubMed2026

PPRC1 is a prognostic biomarker and key regulator of mitochondrial oxidative phosphorylation in multiple myeloma.

BACKGROUND: Multiple myeloma (MM) remains an incurable haematological malignancy, underscoring the need for novel prognostic biomarkers and therapeutic targets. This study aimed to investigate the clinical and biological significance of peroxisome proliferator-activated receptor gamma coactivator-related protein 1 (PPRC1) in MM. METHODS: Expression and clinical data were obtained from public databases and an independent local cohort. Kaplan-Meier and Cox regression analyses were performed to evaluate prognostic value. Differential expression analysis, pathway enrichment analysis and single-cell RNA-seq data analysis were used to explore biological functions. PPRC1 was silenced in MM cell lines using siRNA to assess its effects on cell survival and oxidative phosphorylation. RESULTS: PPRC1 was significantly upregulated in MM and was associated with advanced disease stage and poor overall survival. Multivariate Cox analysis identified PPRC1 as an independent prognostic factor. A nomogram incorporating PPRC1 and revised-ISS improved survival prediction. Functional analyses revealed that PPRC1 was positively correlated with oxidative phosphorylation and oncogenic signalling pathways. A potential connection between PPRC1 expression and immune cell infiltration was observed. PPRC1 knockdown inhibited cell proliferation, induced cell cycle arrest and apoptosis and impaired oxidative phosphorylation in MM. CONCLUSIONS: PPRC1 acts as a prognostic biomarker and metabolic regulator in MM by sustaining mitochondrial oxidative phosphorylation. These findings highlight PPRC1 as a potential therapeutic target in MM.

Humans↗
PubMed2026

Genome-wide identification and expression profiling of CSP and OBP genes in Stictocephala bisonia reveals candidate genes potentially associated with insecticide response.

Stictocephala bisonia is an important invasive agricultural pest. Due to the frequent application of insecticides in its habitat, this species is under intense selection pressure. Chemosensory proteins (CSPs) and odorant-binding proteins (OBPs) are known to play key roles in insecticide resistance, but their specific functions in S. bisonia remain unclear. In this study, we identified a total of 22 SbisCSPs and 16 SbisOBPs based on the S. bisonia genome. To screen for candidate genes potentially linked to insecticide resistance, we adopted a multi-criteria screening strategy that integrated phylogenetic analysis, molecular docking with three insecticides, and tissue-specific expression profiling. Phylogenetic analysis identified several SbisCSPs and SbisOBPs clustering with genes known to be involved in insecticide resistance, serving as an initial evolutionary filter. Molecular docking results indicated that λ-Cyhalothrin exhibited the strong predicted binding affinity with most of SbisCSPs and SbisOBPs. Subsequent qPCR validation of seven prioritized candidates revealed distinct expression patterns: SbisCSP22 was highly expressed in adults and demonstrated strong binding affinity to all three insecticides tested, suggesting a potential role in mediating multi-insecticide response. Conversely, SbisCSP17 was significantly upregulated in larvae, clustered with genes known to mediate imidacloprid resistance, and exhibited strong binding affinity to imidacloprid. Given its larval-specific expression and the soil-dwelling behavior of larvae, we hypothesize that SbisCSP17 is a key candidate gene for larvae coping with soil-treated insecticides.

Animals↗
PubMed2026

Genome-wide characterization of heat shock protein genes reveals thermal stress-responsive candidates in Litopenaeus vannamei.

Heat shock proteins (HSPs) are conserved molecular chaperones involved in protein folding, refolding, aggregation prevention, and degradation of damaged proteins. However, the genomic organization and thermal responsiveness of HSP genes in the Pacific white shrimp (Litopenaeus vannamei) remain incompletely understood. Here, we performed a genome-wide analysis of the HSP gene family and examined its phylogenetic relationships, structural features, duplication patterns, sequence variation, interaction networks, and transcriptional responses to acute heat stress. A total of 34 HSP genes were identified and classified into the HSP90, HSP70, HSP40/DNAJ, HSP60, and small HSP families. Phylogenetic, motif, gene structure, synteny, and subcellular localization analyses revealed evolutionary conservation and structural diversification among family members. Three duplicated gene pairs were identified, comprising two segmental duplications and one tandem duplication. All pairs exhibited Ka/Ks ratios below 1, consistent with purifying selection of varying strength. Sequence analysis identified 295 nonsynonymous single-nucleotide polymorphisms, of which 12 were consistently predicted to be deleterious by multiple algorithms. Protein-protein interaction analysis indicated enrichment of protein-folding and cellular stress-response functions. RT-qPCR analysis showed significant induction of HSPA4, HSP90AA1, TRAP1, BiP, and DNAJA1 after 6, 12, and 24 h of exposure to 34 °C, whereas DNAJC3 was significantly induced only at 12 h. All six genes reached their highest transcript abundance at 12 h. These findings may provide a genomic framework for HSP genes in L. vannamei and identify candidate genes and variants associated with thermal stress responses.

Animals↗
PubMed2026

Diagnostic criteria and severity assessment for syndesmosis injury using magnetic resonance imaging: A systematic review.

High ankle sprains involving syndesmosis injury present challenges in both diagnosis and severity assessment. Magnetic resonance imaging is widely regarded as the preferred modality for evaluating syndesmosis injury and related structural damage. This systematic review primarily examined the diagnostic utility of magnetic resonance imaging. Secondarily, it explores grading and prognostics of syndesmosis injuries with magnetic resonance imaging and identified possible imaging parameters predictive of injury severity. A comprehensive search of MEDLINE, Embase, CINAHL Complete, and Scopus was performed through February 12, 2025, following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Peer-reviewed human studies in English that used magnetic resonance imaging to assess syndesmosis injury were included. Excluded were review articles, case reports, abstract-only studies, and biomechanical or cadaveric investigations. Twenty-seven studies comprising 1931 ankles met inclusion criteria. Magnetic resonance imaging demonstrated high diagnostic accuracy for complete tears of the anterior and posterior inferior tibiofibular ligaments. Ancillary signs such as the ring-of-fire edema pattern, distal tibiofibular joint effusion, and widening of the distal joint space exhibited high specificity with variable sensitivity and may assist in grading injury severity. Magnetic resonance imaging in chronic syndesmosis injury primarily detects fibrotic scarring and post-injury changes. Evidence gaps remain regarding the parameters that best determine injury severity and indicate early surgical intervention in competitive athletes. Consolidating multiple magnetic resonance imaging findings into standardized diagnostic criteria may improve reliability and clinical decision-making.

Humans↗
PubMed2026

A systematic review of macaque brain stimulation: Trends and future directions.

Neurostimulation techniques can powerfully modulate neural circuit activity and provide causal insights into the relationship between brain function and behavior. Macaque monkeys have long been a key animal model for brain stimulation studies. While stimulating the macaque brain with one or a few electrodes has already taught us much about brain function and dysfunction, recent technological advances promise a future with more precise stimulation using many more electrodes. However, such possibilities also increase the number of choices an experimenter has when designing their study. We can learn from a rich past, but a comprehensive overview of which brain regions have been studied and with what stimulation parameters is lacking. Here, we present a PRISMA-compliant systematic review of 734 macaque brain stimulation studies using electrical and/or optogenetic stimulation. We find a striking bias in which brain areas have traditionally been stimulated: a mere 10 brain regions account for half of all studies, with the remainder of studies investigating approximately 150 other areas. Across studies, stimulation frequency robustly predicted direct behavioral effects independent of brain region, while amplitude did not. Future studies could more systematically explore less studied regions through lower stimulation frequencies (e.g., 20-50 Hz) alongside established ranges (∼200 Hz). Tools such as fMRI or optical imaging can capture neural circuit engagement evoked by these frequencies, even when behavioral effects are absent or remain subtle. Our synthesis offers a guide towards the next steps in high-channel-count, high-precision stimulation approaches.

Animals↗
PubMed2026

Complement component C4 and neuroimaging in psychiatry: A systematic review.

INTRODUCTION: Genomic, transcriptomic, and proteomic studies suggest that the complement system contributes to the pathophysiology of various psychiatric disorders partly through neurodevelopmental effects linked to C4A protein levels variations. We conducted a systematic review to characterize how brain micro- and macrostructure and connectivity vary with proxies of in vivo brain C4A protein levels in both psychiatric and general-population cohorts. METHODS: We used Medline, Web of Science, and Embase, and included all studies published before April 14, 2025. Inclusion criteria were: (1) inclusion of healthy controls and/or individuals with psychiatric disorders assessed according to recognized diagnostic manuals (DSM or ICD); (2) use of MRI-based neuroimaging; and (3) use of genomic, transcriptomic and/or proteomic approaches as proxies of in vivo brain C4A proteins levels. RESULTS: From 317 identified articles, 11 were included. Associations between C4A levels and brain structure were heterogeneous across regions. Only the mOFC, dlPFC, and entorhinal cortex were implicated in more than one study. Findings for the mOFC and dlPFC varied by the type of metrics and clinical status, whereas higher C4A levels were more consistently associated with smaller entorhinal cortex surface area and cortical thickness in pediatric, middle-aged, and older general-population cohorts. In addition, one study found higher genetically predicted C4A expression to be associated with higher TSPO levels. CONCLUSION: The limited number of available studies and their methodological heterogeneity make synthesis challenging. However, biological hypotheses such as excessive synaptic pruning or broader inflammatory effects on the brain may provide plausible explanatory frameworks for the reported associations.

Humans↗
PubMed2026

The global potential of freshwater microbes for plastic degradation.

Plastic pollution is becoming increasingly severe on a global scale, and the potential for biodegradation as a treatment method that is environmentally friendly merits greater attention. A significant number of genes that associated the degradation of plastic (PDAGs) have been identified, however, the distribution of these genes among microorganisms in global inland waters remains to be elucidated. A global-scale meta-analysis was conducted, incorporating approximately 1000 metagenome datasets of inland waters across seven continents. A total of 13,109 metagenome-assembled genomes (MAGs) were obtained by means of metagenomics binning, and 22,621 PDAGs were identified from these. Among these recognized PDAGs, phenylacetaldehyde dehydrogenase (PAD) was the most dominant (n = 16,664), followed by catalase (n = 5931). The predominant hosts for PAD and catalase were identified as Gamma-proteobacteria and Bacteroidia, respectively. The largest number of both PAD and catalase was found in MAGs from North America, while the average gene number in single MAG was highest in MAGs from Oceania. In accordance with the prediction of traits, PDAG-carrying MAGs from Europe demonstrated the fastest growth rate and the lowest optimal growth rate. Furthermore, 25 styrene monooxygenase (StyA) enzymes were identified, which were found to cluster into two distinct groups hosted by Alpha-proteobacteria and Gamma-proteobacteria, respectively. Moreover, 11 MAGs were observed to possess the complete pathway of polystyrene degradation. These results explored the potential of inland water microorganisms as a biological resource for plastic degradation and provided valuable microbial reference information that can be used to develop biological treatment technologies for mitigating plastics.

Plastics↗
PubMed2026

Prevalence and cardiometabolic impact of mild autonomous cortisol secretion in primary aldosteronism: a systematic review and meta-analysis.

Many primary aldosteronism (PA) patients harbor concomitant mild autonomous cortisol secretion (MACS), termed "Connshing syndrome." The prevalence and cardiometabolic impact of this co-secretion have not been quantitatively synthesized. To determine the pooled prevalence of MACS in PA and evaluate its association with cardiovascular (CV) events, type 2 diabetes mellitus (T2DM), and obesity. PubMed, Embase, Cochrane, Web of Science, and Scopus through January 2026. Following PRISMA 2020 and MOOSE guidelines (PROSPERO: CRD420261334965), studies reporting MACS prevalence [post-1 mg dexamethasone suppression test (DST) cortisol ≥1.8 μg/dl] in PA were included. Prevalence was pooled using random-effects models. Odds ratios (ORs) were calculated for cardiometabolic outcomes. Certainty was evaluated using GRADE. Fourteen studies (2356 patients) were included. Pooled MACS prevalence was 26.2% [95% confidence interval (CI): 24.1-28.4; I2 = 24.2%; prediction interval: 21.6-31.4%], consistent across European (27.0%) and East Asian (25.2%) cohorts ( P = 0.62). MACS + PA patients had higher odds of CV events (OR 1.60; 95% CI: 1.07-2.38; P = 0.021) and T2DM (OR 1.37; 95% CI: 1.00-1.86; P = 0.048), but not obesity (OR 1.10; P = 0.411). Sensitivity analyses confirmed robustness. GRADE certainty was moderate for prevalence and low for CV events. Approximately one in four PA patients has MACS, associated with a 60% higher CV event risk. These findings support routine DST screening in PA and have implications for perioperative management and cardiometabolic risk stratification.

Humans↗
PubMed2026

Improving insurance deduction identification: a hybrid artificial intelligence model using machine learning and expert systems.

PURPOSE: Financial challenges in healthcare systems worldwide, especially in low- and middle-income countries like Iran, have increased hospitals' reliance on insurance reimbursements. Unrecognized insurance deductions often cause severe financial shortages, making efficient deduction management crucial. This study aimed to design a hybrid intelligent system for identifying and predicting insurance deductions by combining machine learning and expert system frameworks. DESIGN/METHODOLOGY/APPROACH: A mixed-methods design was applied in four stages. First, a scoping review identified the causes and patterns of insurance deductions. Second, interviews with 15 insurance experts produced a validated checklist and a dataset from inpatient billing records. Third, using the CRISP-DM methodology, machine learning algorithms were developed and tested in SPSS Modeler alongside a fuzzy expert system developed in MATLAB. Finally, the model was validated using the holdout method. FINDINGS: Four categories of deduction drivers were identified: service provision, registration errors, document submission issues, and revenue conversion processes. The CHAID decision tree outperformed other algorithms with a 99% precision rate and the lowest Mean Absolute Error (9.43). A brief assessment of potential overfitting was conducted to ensure that the CHAID model's high accuracy was interpreted cautiously and supported by the validation results. The fuzzy expert system with validated rules was adaptable for deduction classification, especially for cases unsuitable for quantitative modeling. ORIGINALITY/VALUE: The hybrid model improves detection and prevention of deductions, offering actionable insights for hospital administrators, insurers, and policymakers. Its implementation can enhance hospital information systems, streamline claims processing, and optimize revenue management amid financial constraints.

Machine Learning↗
PubMed2026

Longitudinal whole-genome analysis of bluetongue virus identifies conserved serotype-specific genomes and distinct genomic constellations within a Colorado sheep flock (2021-2023).

Bluetongue virus (BTV) is a segmented double-stranded RNA virus of ruminants transmitted by Culicoides spp. biting midges. Although the genome consists of ten segments, classification into serotypes is primarily based on genome segment 2. However, reassortment among genomic segments is a major driver of BTV evolution and diversity. This study used longitudinal whole-genome sequencing to characterize BTV genomes collected from 2021 to 2023 within a single sheep flock in Colorado, where multiple serotypes co-circulate. Whole-genome sequences were generated from fourteen blood samples representing four serotypes: BTV-6, -11, -13, and -17. Longitudinal sampling identified multiple BTV serotypes within individual sheep across consecutive years. Tanglegram analysis comparing segment phylogenies to the segment 2 tree demonstrated incongruent topologies across all genomic segments, suggestive of reassortment or the circulation of distinct genomic constellations. Nucleotide-level comparisons revealed high sequence homology among same-serotype samples from the same year, while the greatest genetic divergence was observed among BTV-17 genomes collected in different years. Additionally, all BTV-13 genomes contained a previously undescribed nonsynonymous substitution in segment 10 predicted to extend the encoded protein by three amino acids. Together, these findings demonstrate that highly conserved BTV genomes and distinct genomic constellations can be detected at the flock level across multiple years. This longitudinal whole-genome approach reveals the genetic complexity of endemic BTV populations, including novel variants and genomic patterns consistent with reassortment that are lost with conventional serotyped-based approaches, highlighting the need to integrate whole-genome characterization into endemic BTV monitoring programs.

Animals↗
PubMed2026

GSTT1 promotes stemness and FGFR inhibitor sensitivity in pancreatic cancer through regulation of CD133 (PROM1).

Pancreatic ductal adenocarcinoma (PDA) is among the deadliest malignancies, driven by metastatic progression and profound cellular heterogeneity. We previously identified glutathione S-transferase theta 1 (GSTT1) as a regulator of a slow-cycling, highly metastatic tumor cell population, suggesting that GSTT1High cells may possess stem-like properties. Here, we define the functional and molecular features of this subpopulation in metastatic PDA. Using a mCherry-tagged Gstt1 reporter system in metastatic murine PDAC cells, we enriched for Gstt1High cells and observed increased tumor sphere formation, accompanied by upregulation of stemness-associated genes including PROM1 (CD133) and activation of Wnt and FGF signaling pathways. In human PDA models, CD133HighGSTT1High cells exhibited enhanced tumor sphere initiation and expansion compared to other populations, defining a maximal stem-like state. Notably, sensitivity to FGFR inhibitors was observed only under tumor sphere conditions, highlighting a context-dependent therapeutic vulnerability. Mechanistically, FGFR3 expression correlated with GSTT1 and CD133 levels, and FGF signaling was required to sustain this state. GSTT1 knockdown reduced CD133 protein levels, impaired tumor sphere formation, and altered sensitivity to FGFR inhibition. These findings were largely recapitulated in patient-derived PDA organoids, where GSTT1 and PROM1 co-expression predicted increased tumor sphere formation and enhanced response to the multi-kinase inhibitor Nintedanib. Together, these results identify a GSTT1HighCD133High stem-like subpopulation in metastatic PDA and identify an FGFR-dependent signaling axis that sustains this state, representing a potential therapeutic vulnerability.

AC133 Antigen↗
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↗