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PubMed2026

Target Capture of Ancient Shell DNA Enables Phylogenetic Reconstruction of Deep-Sea Molluscs.

Target capture is widely used to enrich endogenous DNA from calcium phosphate skeletal material in vertebrates, but its performance on calcium carbonate hard parts widely produced by invertebrates remains poorly understood. Here, we compared DNA recovery from four fresh and 12 ancient (eight radiocarbon-dated to 1671-1135 years old before present) deep-sea vesicomyid clam shells, including species Archivesica marissinica, A. nanshaensis and A. okutanii, using whole-genome sequencing (WGS) or target capture of ultraconserved elements (UCEs). WGS achieved 16.65% on-target read recovery of UCEs from fresh soft tissue, but < 1% from shell specimens. By contrast, UCE capture in the same specimen increased on-target reads by up to 155-fold, reaching 29.84% in fresh shells and up to 72-fold, reaching 19.89% in ancient shells. Target capture of UCEs recovered 142-1001 loci per sample compared to 0-230 with WGS alone. Ancient shells of A. marissinica and A. okutanii, based on reads mapped with bwa-mem2 and bbmap, exhibited characteristic post-mortem DNA damage signals, with average 5'-end C-to-T misincorporation rates of 3.46% and 15.97%, respectively, exceeding the levels observed in fresh A. marissinica shells (maximum 1.24%). UCE-based phylogenetic reconstructions incorporating shell ancient DNA recovered two major clades within Pliocardiinae, consistent with published phylogenomic trees. Together, these findings demonstrate that target-capture enrichment enables effective recovery of highly degraded DNA from ancient mollusc shells and supports robust phylogenetic inference at the intrageneric scale, expanding the utility of shells-one of the most abundant invertebrate remains-for evolutionary, biogeographic and conservation studies.

Animals↗

PubMed2026

Ceftriaxone for methicillin-susceptible Staphylococcus aureus bloodstream infections is associated with increased short-term mortality: a systematic review and meta-analysis.

BACKGROUND: Bloodstream infections (BSIs) by methicillin-susceptible Staphylococcus aureus (MSSA) are a significant cause of morbidity and mortality, traditionally treated with antistaphylococcal penicillins (ASPs) or cefazolin. Ceftriaxone has emerged as an alternative due to its once-daily dosing regimen and favourable safety profile; however, its efficacy compared to the standard of care (SoC) remains controversial. This evidence synthesis aimed to assess the role of ceftriaxone in treating MSSA-BSIs. METHODS: A systematic literature search was conducted in PubMed, Embase, and Scopus up to December 31, 2025 (PROSPERO protocol CRD42024595748). Studies comparing ceftriaxone to ASPs or cefazolin for MSSA-BSIs were included. Primary outcomes were 30-day and 90-day all-cause mortality . Pooled effect sizes with their 95% confidence intervals (CIs), were calculated using random-effects models, odds ratios (ORs) and mean differences (MDs) according to the type of outcome. RESULTS: Eleven studies totalling 2,568 patients were included. Ceftriaxone was associated with significantly increased 30-day mortality (OR 3.33; 95% CI: 2.17-5.10), although differences at 90 days were not significant (OR 1.71; 95% CI: 0.75-3.90). No significant differences were noted for clinical success (OR 0.49; 95% CI: 0.19-1.26), microbiological clearance (OR 1.66; 95% CI: 0.73-3.82). Adverse event rates were similar between groups. CONCLUSION: Given the availability of various alternatives and the consistent short-term mortality signal observed, routine use of ceftriaxone for MSSA-BSIs, especially as initial therapy, is not supported by current evidence. Only novel findings from randomized studies may change the place in therapy of the drug in this context.

Humans↗

PubMed2026

Getting to the Core of the Matter-Assessing the Role of Replication in Metabarcoding-Based sedaDNA.

Replication is central to most experimental and sampling designs, increasing inferential power and capturing fine-scale data heterogeneity. However, its importance remains poorly evaluated in some ecological and evolutionary settings. This is the case of metabarcoding studies using DNA recovered from sedimentary archives, in which biological signals integrate ecological information through depositional and burial processes, yet are commonly inferred from a single sediment core per site. Here, we evaluated the effect of different types of replication using sedimentary DNA metabarcoding data from two genetic markers (mitochondrial COI and nuclear 18S) using a nested sampling design. The design included three intertidal sites, three spatially separated sediment cores per site (biological replicates), two sediment horizons per core, and eight PCR (technical) replicates per sediment sample. Variance partitioning showed that site identity and sediment age group together explained > 70% of the variation in beta diversity, indicating that among-site spatial and stratigraphic differences were the dominant drivers of community composition. PERMANOVA likewise identified non-significant effects of biological replication. Among PCR replicates from the same sediment sample, richness varied substantially, whereas Shannon diversity was more consistent. Despite this variability, differences in community composition among technical replicates remained smaller than those associated with biological replication or site identity, indicating a limited influence on broader ecological patterns. Community composition was highly similar among replicate cores within sites, consistent with stratigraphic coherence. These results indicate limited within-site heterogeneity and suggest that, under stratigraphically coherent conditions, increasing biological replication may provide little additional information, whereas enhancing technical replication and stratigraphic resolution can improve ecological inference from sedimentary DNA metabarcoding datasets.

DNA Barcoding, Taxonomic↗

PubMed2026

Genome-wide insights into the evolutionary and demographic history of the red alga Mazzaella laminarioides: Evidence for speciation with ancient migration along the southeast Pacific coast.

The mechanisms driving lineage divergence in red algae remain unexplored, despite the group's remarkable diversity and ancient evolutionary history. The red alga Mazzaella laminarioides, a Chilean intertidal species complex composed of three parapatric cryptic lineages (North, Center, South), offers a valuable system to evaluate these processes, as its life history combines severe dispersal limitation with a haploid-diploid cycle that may influence the emergence of reproductive barriers. We reconstructed its evolutionary history using whole-genome sequencing and nuclear genome assembly of representative individuals from each lineage. Phylogenomic analyses based on 1,507 single-copy orthologs recovered three deeply divergent lineages with limited nuclear discordance consistent with incomplete lineage sorting. For both splits, demographic modelling was most consistent with an Ancient Migration scenario, although support over strict isolation was moderate, suggesting that divergence may have begun with low asymmetric ancestral gene flow followed by subsequent loss of connectivity, demographic bottlenecks, and later population expansion. Coding sequence analyses revealed lineage-specific dN/dS heterogeneity; only one South-lineage locus passed FDR correction (metaxin-1, mitochondrial protein import), with two further South-lineage candidates in chlorophyll and heme biosynthesis falling below the FDR threshold. Together, these signals suggest that divergent selective pressures on energy acquisition may have contributed to divergence at the southern end of the distribution. These results add to the small but growing body of whole-genome data for red algae and, alongside recent macroalgal studies, suggest that ancestral connectivity could be a recurrent feature of lineage divergence even in marine organisms with extremely restricted dispersal.

Rhodophyta↗

PubMed2026

Genetic evidence for a causal relationship between melatonin metabolism and depression.

To investigate the causal relevance of melatonin metabolism, which provides the biological basis for circulating melatonin levels, to specific depression symptom subtypes, we performed a targeted systematic review of melatonin metabolism pathways in the human brain and liver. Using two-sample Mendelian randomization (MR), we assessed the causal effects of metabolism pathways and/or individual genes on major depressive disorder (MDD) and nine symptom subtypes derived from Patient Health Questionnaire-9 (PHQ-9). Instrumental variables (IVs) were expression quantitative trait loci (eQTL) for eight individual genes, one synthesis route, and three degradation routes. Results were assessed using Bayesian colocalization and phenome-wide association analyses. At the pathway-level, the genetically proxied synthesis-route signal was associated with PHQ-9 Assessment 5 (PHQ9A5, OR: 0.89, 95% CI: 0.85-0.93), but sensitivity analyses suggested this association was primarily driven by TPH1 and may reflect serotonin-related biology. In contrast, higher brain melatonin degradation raised the risk of both PHQ9A1 (OR: 1.03, 95% CI: 1.02-1.04) and PHQ9A7 (OR: 1.03, 95% CI: 1.02-1.03). Within degradation, up-regulation of the kynurenine sub-pathway increased the odds of PHQ9A3 (OR: 1.05, 95% CI: 1.02-1.07), PHQ9A4 (OR = 1.04, 95% CI: 1.02-1.06) and PHQ9A7 (OR: 1.05, 95% CI: 1.02-1.07). Gene-level analyses were largely concordant, except for SULT1A1, whose higher expression was genetically protective for PHQ9A3 but risk-increased for PHQ9A1 and PHQ9A4. Overall, these results demonstrate that melatonin metabolism exerts symptom-specific and pathway-specific causal effects on depression. A stratified view of melatonin's role may help optimize the application of exogenous melatonin supplementation.

Melatonin↗

PubMed2026

ScRNA-seq analysis reveals the effects of nitrite stress on the endocrine system of the eyestalk in Litopenaeus vannamei.

Nitrite is a harmful substance generated in Litopenaeus vannamei farming systems, largely originating from the inadequate breakdown of surplus feed and shrimp feces. Its accumulation in the water can affect the growth and physiological functions of shrimp, damage the immune system, and even cause mass mortality, thus becoming a key environmental factor restricting the green development of the industry. Under nitrite stress, the eyestalk, as an important neuroendocrine regulatory center in crustaceans, participates in the stress adaptation of the organism and exerts a protective effect by regulating energy metabolism and immune function. However, the molecular regulatory mechanism of the eyestalk in response to nitrite stress remains unclear. In this study, single-cell RNA sequencing (scRNA-seq) technology was used to analyze the heterogeneity of eyestalk cells in L. vannamei under nitrite stress. A total of 18, 394 high-quality cells were obtained, and six major cell subpopulations, including Neurosecretory cell, Motor neuron, Sensory neuron, Interneuron, Neurogliocyte, and Support cell, were identified. Differential expression analysis identified 839 differentially expressed genes, and different cell types showed distinct specific responses to nitrite stress. Functional enrichment analysis indicated that pathways such as glycolysis, oxidative phosphorylation, ribosome function, and endoplasmic reticulum protein processing were significantly activated, while signal transduction and DNA repair-related pathways were inhibited. Further analysis revealed that nitrite stress could induce mitochondrial function changes and trigger oxidative stress, thereby affecting the neuroendocrine system function of the eyestalk. This study provided insights into transcriptomic responses of the eyestalk to nitrite stress at the single-cell level, laying a theoretical foundation for the management of aquaculture environments.

Animals↗

PubMed2026

Polygenic risk scores in major depressive disorder: A systematic review across diagnostic, treatment, course/severity, and subtype domains.

BACKGROUND: Major depressive disorder (MDD) is heterogeneous across diagnostic, treatment-related, course/severity, and subtype domains. Polygenic risk score (PRS) studies have examined these domains, but differences in PRS sources, samples, methods, and endpoint definitions have fragmented the evidence. We synthesised findings and examined potential contributors to heterogeneity. METHODS: PubMed/MEDLINE, Embase, PsycINFO, and Web of Science were searched for studies published from January 2016 through 25 November 2025. Result records were synthesised using SWiM, and certainty was assessed with an adapted GRADE framework. RESULTS: Sixty studies contributed 493 retained records; 450 were descriptively classified as positive, null, or reverse, although records were not independent. Positive findings accounted for 44/56 diagnostic, 61/273 treatment-related, 64/100 course/severity, and 14/21 subtype records. For MDD/depression-derived PRSs and case-control MDD status, all 10 contributing studies showed higher liability in cases (exploratory exact sign test p = 0.002; FDR q = 0.004). The same PRS group showed positive findings for overall depressive symptom severity (14/18), although the study-level test was imprecise (5/5 studies; p = 0.063). Pharmacological response/remission findings for these PRSs were mostly null or directionally mixed (10 positive, 18 null, and 9 reverse). Treatment-resistant depression (TRD) findings differed by operational definition. Atypical and psychotic subtype signals arose mainly from single-study PRS and endpoint contrasts. CONCLUSIONS: PRS evidence was clearest for MDD diagnostic status and showed a tentative pattern for overall symptom burden. Treatment and subtype findings were less consistent or less replicated. Larger, ancestrally diverse studies with standardised endpoints and transparent PRS methods are needed.

Humans↗

PubMed2026

Natural products alleviate exercise-induced fatigue by modulating gut microbiota: a systematic review.

BACKGROUND: Exercise-induced fatigue critically impairs athletic performance and training quality. The gut microbiota, as a key regulator of the "gut-muscle axis," has emerged as a promising anti-fatigue target. Natural products - owing to their diverse sources, structural complexity, and favorable safety profiles - have attracted growing research interest. However, a systematic synthesis comparing their anti-fatigue effects via gut microbiota modulation across different sources is lacking. SCOPE AND APPROACH: We systematically searched PubMed, Web of Science, the Cochrane Library, and CNKI for original studies that administered natural products and concurrently assessed gut microbiota changes and anti-fatigue outcomes. Twenty-six studies (25 animal experiments and 1 human trial) were included and categorized into seven groups by source and chemical characteristics. A descriptive systematic review was conducted to identify common mechanisms and source-specific differentiations. KEY FINDINGS AND CONCLUSIONS: The enrichment of short-chain fatty acid (SCFA)-producing bacteria and the activation of the SCFA-AMPK/PGC-1α axis were shared core events across all product categories. However, source-dependent mechanistic divergences emerged: polysaccharides acted primarily as fermentable substrates with an optimal dose window; polyphenols and saponins exerted dual modulation on both microbiota and host signaling pathways; compound extracts achieved systemic synergy through functional complementation; marine- and animal-derived products exhibited unique targeting profiles and rapid action. Intestinal barrier maintenance and brain-gut axis regulation further extended the anti-fatigue repertoire. Collectively, natural products possess a solid mechanistic basis for alleviating exercise-induced fatigue via gut microbiota remodeling. The differentiated characteristics of these methods in targeting precision and pathway engagement provide a theoretical foundation for designing precision intervention strategies tailored to specific fatigue contexts.

Humans↗

PubMed2026

Lipid metabolism is a key central, systemic and gut microbial feature of the decline in rat hippocampal function during middle age.

Middle age is emerging as a turning point in brain ageing, prognostic of future cognitive health and amenable to intervention. Metabolic and proteomic differences during this period are not yet fully understood and may potentially influence functions of the hippocampus, a brain area that regulates memory and anxiety. While the gut microbiota is implicated in brain ageing, the relationship between the gut microbiota, the metabolic state, and hippocampal proteome in middle age has not been investigated. We hypothesise that peripheral metabolic or protein features are associated with hippocampal vulnerability in middle age. Therefore, young adult and middle-aged rats were assessed for behavioural, proteomic, metabolic, and gut microbiota differences. Proteomic profiling of the hippocampus revealed differential expression of proteins indicative of altered synaptic signalling. Concurrently, adult hippocampal neurogenesis was decreased in middle age. Hippocampal microglia exhibited a lipid rich, inflammatory phenotype in middle age which correlated with poorer memory performance. CSF and serum proteomic and metabolomic analyses identified dysregulated lipid-related pathways potentially contributing to hippocampal vulnerability in middle age. Furthermore, 16S rRNA sequencing revealed reduced abundance of bacteria involved in lipid metabolism regulation. However, faecal microbiota transfer from young to middle aged rats was not sufficient to robustly improve hippocampus-dependent spatial memory. Together, these findings highlight dysfunctional lipid metabolism as a key feature of middle age that may contribute to decline in hippocampal function. Given that the scope for intervention is limited during older age, targeting biomarkers involved in metabolic and lipid homeostasis may be pivotal for the development of pharmacological or lifestyle-based interventions during middle age which could ultimately delay future cognitive ageing.

Animals↗

PubMed2026

Prioritizing Parkinson's disease risk-associated mitochondrial candidate genes via multi-omics integrative analysis.

BACKGROUND: Mitochondrial dysfunction has been implicated in Parkinson's disease (PD), but the genetically regulated mitochondrial genes associated with PD risk remain incompletely defined. METHODS: We conducted a summary-data-based genetic epidemiology study integrating summary-based Mendelian randomization (SMR), Heterogeneity in dependent instruments (HEIDI) filtering, and Bayesian colocalization to prioritize mitochondrial-related molecular features associated with PD risk. Mitochondrial-related genes were defined using MitoCarta3.0. Genetically predicted gene expression and plasma protein abundance were evaluated using expression quantitative trait loci (eQTL) data from eQTLGen and GTEx v8, and protein quantitative trait loci (pQTL) data was assessed using International Parkinson's Disease Genomics Consortium (IPDGC) as the discovery genome-wide association study (GWAS) and FinnGen as the replication dataset. Prespecified QTL analyses were interpreted using FDR correction, HEIDI filtering, and colocalization support. DNA methylation QTL analysis, mitochondrial phenotype MR, and single-nucleus RNA-seq analysis were performed as complementary analyses. RESULTS: In the primary eQTL analysis, higher genetically predicted TTC19 expression was associated with lower PD risk (OR = 0.80, 95% CI: 0.74-0.87, PPH4 = 0.80), whereas higher MALSU1 expression was associated with increased PD risk (OR = 2.21, 95% CI: 1.59-3.06, PPH4 = 0.96). Both associations survived FDR correction, passed HEIDI filtering, and showed colocalization support. GTEx whole-blood data supported the direction of the TTC19 association. No mitochondrial protein reached significance after FDR correction and colocalization filtering in the primary pQTL analysis. Complementary methylation analysis highlighted cg06270993 as an exploratory regulatory signal for MALSU1. CONCLUSIONS: This MR-colocalization study prioritizes TTC19 and MALSU1 as genetically supported mitochondrial-related candidate genes associated with PD risk. Further validation is required to define their functional roles in PD pathogenesis.

Humans↗

PubMed2026

Privacy, security, and reliability risks of artificial intelligence in healthcare: a systematic review of empirical evidence.

BACKGROUND: Artificial intelligence (AI) is increasingly integrated into healthcare information systems, supporting clinical decision-making, imaging analysis, and predictive modeling. While these applications offer operational and clinical benefits, they also introduce emerging risks to patient privacy, data security, and system reliability. OBJECTIVE: To systematically review empirical evidence on privacy breaches, security vulnerabilities, and misuse associated with AI applications in healthcare settings. METHODS: PubMed, Embase, Web of Science, Scopus, IEEE Xplore, and ACM Digital Library were searched for empirical studies published between January 2015 and November 2025 that evaluated AI use or misuse in clinical diagnosis, treatment, or decision-making. Two reviewers independently screened studies and extracted data using a standardized form. Findings were synthesized narratively due to heterogeneity in study designs, AI methods, and reported outcomes. RESULTS: Of 7,285 records identified through database searches and 205 through citation screening, 22 empirical studies met the inclusion criteria, spanning multiple clinical domains and data modalities, predominantly medical imaging applications. Five recurring threat categories were identified: patient re-identification, membership inference, unauthorized access and adversarial exploitation, input manipulation, and misuse or overinterpretation of AI outputs. Across studies, AI models were shown to encode latent biometric signals across diverse data types, limiting the effectiveness of traditional anonymization and synthetic data approaches. Adversarial attacks and input manipulation were also shown to compromise diagnostic performance and system integrity. CONCLUSION: This systematic review provides empirical evidence suggesting that contemporary AI systems in healthcare introduce privacy and security risks that may challenge traditional assumptions about data protection. These findings underscore the need for privacy- and security-by-design approaches and governance frameworks that address risks across the AI lifecycle.

Humans↗

PubMed2026

Introgression shapes the genomic conflict landscape of Malus, providing evidence for a reticulate backbone in a woody crop lineage.

Phylogenomic discordance is widespread across plants, but its evolutionary significance is often obscured when conflict is treated primarily as analytical noise rather than as evidence of underlying processes. In woody lineages in particular, incomplete lineage sorting, introgression, and genome duplication can interact over long timescales to produce complex genomic histories that are not adequately summarized by a strictly bifurcating tree. Here, we use Malus as a model woody genus to investigate how these processes structure conflict across a genus-scale, accession-based phylogenomic framework. Using broad taxon sampling, hundreds of nuclear loci, plastid genomes, and genome-wide SNP summaries, we reconstruct a robust nuclear backbone for sampled Malus lineages and evaluate where discordance is concentrated and which processes best explain it. Nuclear analyses resolve eight major clades, whereas conflict is non-random and localized to recurrent hotspots rather than evenly distributed across the tree. Cytonuclear discordance is similarly concentrated, especially around Clade H, represented by sampled accessions of M. tschonoskii, where localized plastid-nuclear disagreement is consistent with candidate plastid capture or organellar introgression. Multiple complementary analyses further indicate that the strongest conflict is not explained by ILS alone, but instead reflects lineage-structured introgression, while polyploid complexes represent additional localized sources of evolutionary complexity. Together, these results provide evidence for a reticulate genomic backbone in Malus and show how integrating nuclear, plastid, and genome-wide conflict analyses can help distinguish background discordance from process-specific signals in woody plant radiations. Several lineage-level reticulation hypotheses identified here should now be tested with broader population-level sampling and curated reference accessions.

Malus↗

PubMed2026

Genome mining of alkaliphilic cyanobacterial consortia: identification of biosynthetic gene clusters in Sodalinema and associated heterotrophs.

Alkaline soda lakes are high-pH environments that host specialized microbial communities with potential for biotechnology and natural product discovery. We characterized three Sodalinema-dominated cyanobacterial consortia enriched from Canadian soda lakes over 510 days. Using hybrid metagenomic sequencing and metatranscriptomics across pH, alkalinity, and temperature gradients, we reconstructed high-quality metagenome-assembled genomes and assessed functional activity. All consortia converged toward cyanobacteria dominance and exhibited temperature optima between 21°C and 30°C. Phylogenetic analysis placed Sodalinema genomes within a distinct clade affiliated with Candidatus Sodalinema alkaliphilum. Genomic analysis indicated complete biosynthetic pathways for vitamin B5, vitamin B7, and the molybdenum cofactor, but incomplete pathways for vitamins B1, B9, and B12, consistent with patterns observed in Sodalinema yuhuli. Metatranscriptomic profiles showed increased expression of genes involved in phycocyanin and carotenoid biosynthesis at pH 10.2 relative to pH 8.5. Biosynthetic gene cluster analysis revealed that most secondary metabolic potential resided in heterotrophic community members. Roseinatronobacter encoded pathways for N-acyl homoserine lactones, osmoprotectants, betalactones, and prodigiosin, while Alkalimonas, Wenzhouxiangella, and members of the Kiloniellales encoded clusters for lanthipeptides, cyclodipeptides, hydrogen cyanide, and pyrroloquinoline quinone. These findings indicate functional partitioning within the consortia and highlight the contribution of heterotrophs to secondary metabolism.IMPORTANCEAlkaline soda lakes contain microbial communities adapted to high pH that remain underexplored for biotechnology. This study focuses on Sodalinema, a filamentous cyanobacterium that dominates enriched consortia from Canadian soda lakes, and its associated heterotrophic partners. We show that while Sodalinema drives primary productivity, heterotrophic bacteria encode most of the pathways for antimicrobial and signaling compounds. These interactions may support community stability and defense against competing microorganisms. By linking genomic potential with gene expression, this work identifies alkaline cyanobacterial consortia as a source of bioactive compounds and provides a framework for exploring extremophilic microbial communities for natural product discovery.

Sodalinema↗

PubMed2026

Genome-Wide Impact of Human DBR1 Depletion on RNA Processing Networks Reveal a Connection Between Pre-mRNA Splicing, mRNA Surveillance and Stress Granule Dynamics.

The RNA lariat debranching enzyme DBR1 is essential for intron turnover and RNA metabolism, yet its broader impact on transcriptome regulation remains incompletely defined. To elucidate the consequences of DBR1 depletion, we performed transcriptome-wide RNA sequencing of DBR1-knockdown and wild-type HEK293 cells. Differential expression analysis revealed widespread perturbations in pathways linked to RNA splicing, mRNA surveillance, translational control, and stress-granule biology. Many of the most significantly altered transcripts encode splicing factors and RNA quality-control components, underscoring DBR1's influence on post-transcriptional regulation. Alternative splicing analysis showed changes across multiple event types, with exon skipping accounting for >50% of events, followed by mutually exclusive exons, alternative 5' and 3' splice sites, and retained introns, indicating that DBR1 depletion induces pervasive splicing defects. Direct spliceosome inhibition using isoginkgetin (blocks tri-snRNP recruitment) and pladienolide B (targets SF3B1) reproduced the DBR1-KD mis-splicing patterns of cell signaling genes and factors involved in RNA metabolism, supporting a functional link between DBR1 activity and alternative splicing. Notably, DBR1 knockdown revealed a subset of transcripts that are both NMD-sensitive and enriched within stress granules. Consistent with this observation, G3BP1 immunopurification and confocal microscopy further support a role for DBR1 and UPF1 in stress-granule dynamics, suggesting that these factors may participate at distinct stages to influence mRNA fate under stress conditions. Together, these findings indicate that DBR1 functions beyond lariat RNA turnover as a common regulator of RNA processing, transcriptome stability, and stress granule homeostasis, revealing intricate crosstalk between RNA splicing and RNA quality control pathways in human cells.

Humans↗

PubMed2026

Metabolomic Responses to Oral Glucose Tolerance Test and Hyperinsulinemic-euglycemic Clamp in CKD.

BACKGROUND: The oral glucose tolerance test (OGTT) captures integrated physiological responses involving intestinal glucose absorption, incretin signaling, and endogenous insulin secretion, whereas the hyperinsulinemic-euglycemic clamp (clamp) isolates insulin-mediated glucose uptake. Comparing plasma metabolomic responses to these two challenges may identify processes specific to intestinal nutrient delivery and how they vary in CKD. METHODS: Targeted plasma metabolomics was performed in 59 adults without diabetes (39 with CKD [eGFR <60 mL/min/1.73 m2] and 20 controls) from the Study of Glucose and Insulin in Renal Disease (SUGAR). Each participant underwent a 75-g OGTT and clamp approximately one week apart. Eighty-eight plasma metabolites were quantified at fasting and during each challenge. Metabolite levels were log-transformed and normalized using Systematic Error Removal Using Random Forest (SERRF). Metabolites were classified using adjusted regression slopes relating OGTT and clamp responses. RESULTS: The mean (SD) age and eGFR were 64 (13) years and 54 (26) mL/min/1.73 m2, respectively, and 41% were female. In the overall cohort, OGTT and clamp induced broad plasma metabolic changes, with 63 (72%) and 76 (86%) metabolites significantly altered from fasting, respectively. Seventy-three metabolites (83%) demonstrated a significant relationship between OGTT and clamp responses. Of these, 22 (25%) exhibited true concordance and 51 (58%) demonstrated similar directional changes but differed in magnitude. A total of 15 (17%) metabolites were discordant or non-corresponding, of which only three were discordant. The non-corresponding metabolites were enriched in amino acid metabolism. Eleven metabolites (13%) demonstrated differential responses between OGTT and clamp by CKD status, involving amino acid and glucose metabolism pathways. CONCLUSIONS: Metabolomic responses to OGTT and clamp were largely directionally concordant but differed in magnitude, with attenuation during OGTT. Discordant metabolites were rare, while non-corresponding metabolites were confined to amino acid pathways. CKD modified OGTT-clamp correspondence for metabolites involved in amino acid and glycolytic metabolism.

Journal Article↗

PubMed2026

Challenges and future directions in AI-driven biomaterials for microbiome-associated oral infectious diseases: A systematic review.

Oral biofilm-induced antimicrobial resistance is the core pathogenic mechanism of microbiome-associated oral infectious diseases (dental caries, periodontitis, peri-implantitis, and endodontic infection). Traditional therapies and biomaterials are limited by poor biofilm penetration, drug resistance induction, single functionality, and inadequate adaptation to dynamic oral microenvironmental changes (e.g., pH fluctuations, salivary rinsing, masticatory stimulation). Artificial intelligence (AI) has transformed the field by integrating materials science, microbiology, and stomatology data. Via machine learning, deep learning, and multi-physics simulation, AI optimizes biomaterial physicochemical properties, decodes microenvironmental signals, constructs precise sensing-response loops, and supports the full chain of material design, performance prediction, and action simulation, advancing treatment from empirical intervention to precision regulation. This systematic review retrieved literature from PubMed, Embase, and Web of Science (January 2016-January 2026) using keywords across three dimensions: AI, biomaterials, and oral microbiome. Following inclusion/exclusion criteria, 99 articles were included. It elaborates on five core mechanisms of AI-driven oral biomaterials (precise oral microbiome analysis, targeted material design/optimization, performance prediction/simulation, targeted delivery/intervention, effect evaluation/dynamic regulation), analyzes their applications in microbiome-targeted biomaterial research and development (R&D) and clinical practice for the four major oral infectious diseases, addresses technical bottlenecks (insufficient targeting specificity and precision of biomaterials, poor stability and durability in complex oral microenvironments, inadequate biofilm disruption capacity, and clinical translation obstacles), and proposes future directions (multimodal design to enhance targeting specificity, structural and component optimization to improve stability/durability, development of multi-mechanism synergistic biofilm disruption strategies, strengthening translational research for clinical application, and deep integration of AI in the full chain of biomaterial R&D). This work provides comprehensive theoretical and practical support for the R&D, optimization, and clinical translation of AI-driven microbiome-targeted oral biomaterials.

Humans↗

PubMed2026

Storm and Stress 2.0? A Dual-Factor, Person-Centered Analysis of Adolescent Well-being Across Two Year 7 Cohorts and Gender.

PURPOSE: Concerns about the mental health and well-being of younger generations is a recurring theme across countries and time. Adolescence is debated as a period of volatility ("storm and stress") or growth. Recent trends have reignited worries about youth mental health and well-being, particularly for females, and revived a deficit-based view of adolescence. To advance understanding, this study adopts a dual-factor approach that incorporates both negative and positive well-being domains. Mental health trends were compared across two grade-matched Australian adolescent cohorts assessed 5 years apart. METHODS: Data were drawn from cross-sectional cohorts of year 7 students (12-13 years) in one Australian jurisdiction: 2,085 in 2018 and 2,378 in 2023. Positive affect, happiness, resilience, depression, and anxiety were assessed using latent profile analysis to identify mental health profiles, which were then compared between cohorts and gender. RESULTS: Four profiles were identified: complete mental health, symptomatic but positive, resilient but disaffected, and troubled. Approximately 80% of students were classified in profiles reflecting some positive mental health. Between 2018 and 2023, the proportion with complete mental health declined by 7.93%, while those categorized as troubled increased by 4.76%. Declines were most pronounced among female students. DISCUSSION: Findings highlight both resilience and vulnerability in adolescent mental health. While most students continue to show positive well-being, the decline among females signals an urgent need for gender-sensitive approaches. At the same time, the results add nuance to accounts of a youth mental health 'crisis' to some degree, by highlighting positive domains of well-being which are often overlooked.

Humans↗

PubMed2026

Tissue origins of the plasma proteomic response to glucose ingestion in humans.

AIMS/HYPOTHESIS: Circulating proteins act as important hormonal signals of nutrient intake. We aimed to systematically characterise the time-resolved proteomic response to glucose ingestion in humans, and to assess its robustness following prolonged complete caloric restriction. METHODS: We conducted oral glucose tolerance tests (OGTTs) in 11 healthy volunteers before and after 7 days of complete caloric restriction and measured the response of >2900 targets through high-resolution plasma protein profiling. RESULTS: We identified a signature of 44 proteins that changed significantly following glucose ingestion, which was reproducible after 7 days without food, and was strongly (20-fold) enriched for 'stomach-specific' proteins. We report that annexin A10 (ANXA10) shows the most significant post-glucose change observed, similar to the trajectories of secreted hormones. We present observational human evidence from multiple sources suggesting that ANXA10 is secreted upon sensing an increase in gastric pH, with the stomach as the major contributing tissue. Despite a profound metabolic shift after 7 days of complete caloric restriction, characterised by delayed insulin secretion and postprandial hyperglycaemia, only four proteins showed robust evidence for a differential trajectory during both OGTTs. This included plasma levels of tryptophanyl-tRNA synthetase 1 (WARS), for which we found a genetic association with glucose homeostasis and coronary artery disease. CONCLUSIONS/INTERPRETATION: Our exploratory study identifies the proteomic response to glucose ingestion and demonstrates its reproducibility despite major shifts in glucose homeostasis. We characterise the gastrointestinal origin of these changes, and hypothesise a hitherto under-recognised role for sensing of changes in gastric pH on the plasma proteome.

Humans↗