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PubMed2026

Beyond multidimensionality: a systematic review of recurrent frailty archetypes in community-dwelling older adults.

BACKGROUND: Frailty is a clinically heterogeneous geriatric syndrome commonly summarised using physical or multidomain severity scores. Whether person-centred analyses identify recurring within-frailty configurations has not been systematically examined in community-dwelling older adults. METHODS: We searched PubMed, Embase, MEDLINE, and CINAHL (January 2000-November 2025) for cross-sectional studies using latent class, latent profile, or analogous clustering methods to derive frailty subgroups. Quality was assessed using the AHRQ checklist and a purpose-built appraisal of person-centred model reporting. Study-derived classes were mapped in duplicate to a structured archetype framework developed through comparison of class-defining features across studies. RESULTS: Fourteen reports representing 12 independent datasets from eight countries were included. Six configurations were identified: minimally impaired reference, mobility-physical, nutritional-metabolic, cognitive-predominant, combined cognitive-physical, and psychosocial/mood-predominant. Convergence was measurement-dependent. The reference and mobility-physical configurations recurred across physical-only and multidomain indicator sets, while the combined cognitive-physical configuration appeared across several multidomain frameworks but required cognition to be measured. The remaining configurations emerged only when their defining domains were included. Evidence of prognostic value beyond aggregate frailty severity came from one deficit-index study. Collapsing shared-provenance reports and excluding the boundary-eligible study did not alter recurrence; excluding the Croatian dataset left five configurations recurrent, with the cognitive-predominant configuration supported by one independent dataset. CONCLUSIONS: Person-centred analyses identify recurring within-frailty configurations, but their apparent stability is partly measurement-dependent. A five-configuration core persisted after exclusion of the Croatian dataset, whereas the cognitive-predominant configuration remained weakly replicated. Harmonised indicators and rigorous external validation are needed before clinical application.

Humans↗

PubMed2026

Coordinated use of three homocysteine methyltransferases supports l-methionine biosynthesis and environmental adaptation among plant-associated bacteria.

Plant pathogens colonize multiple plant-associated habitats throughout their life cycle, encountering distinct nutrient conditions and microbial communities. l-methionine is required for bacterial growth and environmental adaptation. However, how plant pathogens coordinate l-methionine biosynthetic pathways to adapt to different plant-associated environments remains poorly understood. Here, using the plant pathogen Xanthomonas campestris pv. campestris strain XC1 as a model, we show that three homocysteine methyltransferase pathways allow XC1 to catalyze the final step of l-methionine biosynthesis using different methyl donors and cofactors under different environmental conditions. Bioinformatic and transcriptional analyses identified three homocysteine methyltransferase-associated operons in XC1, mesMXD, mmuPM, and metHRHaHb, corresponding to the MesD-, MmuM-, and MetHaHb-dependent pathways, respectively. MesD uses an endogenously synthesized methyl donor and functions as the dominant homocysteine methyltransferase under l-methionine-limiting conditions, supporting bacterial growth, intracellular l-methionine accumulation, and full virulence. Furthermore, MmuM enables XC1 to use plant-derived S-methylmethionine for l-methionine biosynthesis, whereas MetHaHb enables XC1 to use vitamin B12 supplied by a neighboring bacterium for l-methionine biosynthesis in co-culture. Expression analyses showed that mesMXD was the only homocysteine methyltransferase-associated operon that responded to l-methionine availability, and its expression also decreased when S-methylmethionine- or vitamin B12-dependent pathways supported l-methionine biosynthesis. Comparative genomic analysis further showed that the three-homocysteine methyltransferase configuration is conserved in Xanthomonas and is also present in other plant-associated bacteria. Together, these findings show that a plant pathogen can coordinate endogenous, plant-derived, and microbially supported homocysteine methyltransferase pathways to maintain l-methionine biosynthesis, providing a metabolic strategy for adaptation to plant-associated environments.

Methionine↗

PubMed2026

An oxidative stress - and immunotherapy-related six-gene signature defines immune subtypes and predicts prognosis and immunotherapy response in hepatocellular carcinoma.

BACKGROUND: Oxidative stress and the tumor immune microenvironment jointly shape hepatocellular carcinoma (HCC) progression and response to immunotherapy, yet integrated biomarkers linking these processes are lacking. METHODS: Transcriptomic and clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets were used to identify oxidative stress- and immunotherapyrelated differentially expressed genes (OSIRDEGs). Functional enrichment, weighted gene co-expression network analysis (WGCNA) and LASSO-Cox regression were used to construct a prognostic signature. Consensus clustering, TIDE, CIBERSORT and ssGSEA characterized immune phenotypes. Somatic mutation, copy-number and drug-response data were integrated to assess genomic alterations and drug sensitivity. Expression of model genes was validated by qRT-PCR and western blotting in HCC cell lines. RESULTS: We identified 24 OSIRDEGs enriched in cell-cycle and mitotic pathways. WGCNA intersection yielded 18 module genes, from which a six-gene signature (BUB1B, CDKN2A, CENPE, HMMR, PTTG1, SPP1) was derived. The signature robustly stratified patients into high- and low-risk groups with significantly different progression-free and disease-free survival in both TCGA-LIHC and GSE14520. Based on signature expression, two molecular subtypes were defined, exhibiting distinct survival, immune landscapes and predicted immunotherapy responsiveness. Model genes harbored recurrent alterations and showed significant correlations with anticancer agents. All six genes were upregulated at mRNA and protein levels in metastatic HCC cell lines versus normal hepatocytes. CONCLUSIONS: We systematically explored the landscape of OSIRDEGs in HCC, and proposed a validated six-gene signature that refines prognostic stratification, delineates immunerelevant HCC subtypes and highlights candidate biomarkers for therapeutic selection and mechanistic investigation.

Humans↗

PubMed2026

Beyond antigen matching: compatibility intelligence theory for transfusion as an emergent biological system.

BACKGROUND: Despite major advances in serologic testing, extended phenotyping, and blood group genomics, clinically similar transfusion exposures may result in markedly different immune and clinical outcomes. Existing compatibility strategies do not fully explain this biological variability. OBJECTIVES: To examine transfusion compatibility as an emergent donor-recipient biological state and propose a systems-level conceptual framework that integrates established biological determinants into a testable model for future precision transfusion medicine. METHODS: This narrative review critically synthesizes current evidence from blood group genomics, recipient immunobiology, inflammation, disease-specific biology, transfusion medicine, and computational prediction. The proposed framework distinguishes Compatibility Intelligence Theory (CIT) as a biological interpretation from Precision Transfusion Intelligence (PTI) as its potential clinician-supervised translational application. RESULTS: The review argues that transfusion compatibility is shaped by interactions among donor genetics, recipient immune biology, inflammatory physiology, disease context, transfusion history, and longitudinal adaptation rather than by antigen matching alone. CIT provides an organizational framework for integrating these determinants, whereas PTI describes a possible clinician-supervised translation. To address current feasibility, the revised framework separates variables into routinely measurable, contextually available but incompletely standardized, and research-stage domains, and proposes a staged strategy for deriving rather than assuming their quantitative weights. Any clinical implementation would require comparative validation against current serologic, phenotypic, and genotype-based practice. CONCLUSIONS: Compatibility Intelligence Theory offers a testable systems-level framework for understanding transfusion compatibility without replacing established transfusion practices. The framework is not presented as a ready-to-use score: currently measurable variables can be organized for structured risk review, whereas inflammatory, immunogenetic, and multi-omic inputs require prospective standardization and validation. If future studies demonstrate incremental predictive and patient-centered benefit, CIT-informed PTI could support an adaptive, evidence-based extension of current precision transfusion practice.

Humans↗

PubMed2026

Effects of faba bean-based crisping culture on phenotypic characteristics, muscle quality, and serum metabolome in Nile tilapia: Screening biomarkers to assess the degree of crisping.

Feeding Nile tilapia (Oreochromis niloticus) a faba bean-based crisping diet enhances muscle hardness (crispness) and overall flesh quality. However, the underlying mechanisms and reliable biomarkers remain insufficiently defined. This study integrated phenotypic traits, muscle texture, collagen content, serum antioxidant enzyme activities (SOD, CAT, and GSH-Px), MDA levels, and serum metabolomics to understand the determinants of muscle crisping. Fish were assigned to a crisping diet or a control group for 90 days. Individuals in the crisping group were implanted with passive integrated transponder (PIT) tags to enable correlation analyses among phenotypic traits (body weight/length/frame changes), serum indicators (NAM, FAD, and GSH-Px) and muscle hardness. Compared with controls, the crisping diet significantly increased muscle hardness, gumminess, and chewiness, accompanied by elevated collagen content. Antioxidant profiles were altered, with higher activities of serum SOD and CAT, together with elevated MDA levels and reduced GSH-Px activity (P < 0.05). Metabolomic analysis identified 830 differential metabolites (682 upregulated and 148 downregulated), predominantly comprising carboxylic acids and derivatives, glycerophospholipids, and benzene derivatives. Enrichment analysis indicated significant involvement in general metabolic pathways, ATP-binding cassette (ABC) transporters, amino acid biosynthesis, and glycine, serine, and threonine metabolism (P < 0.05). Notably, acetylpyruvate was upregulated in glutathione metabolism, nicotinate and nicotinamide metabolism, and galactose metabolism; pantothenic acid was upregulated in glycine, serine, and threonine metabolism; whereas δ-tocotrienol was downregulated. Correlation analysis revealed weak negative associations between muscle hardness and phenotypic traits (body weight/length/frame changes D5-7, D5-10, D7-8) (P < 0.05). In contrast, serum NAM and FAD were weakly positively correlated with muscle hardness, whereas GSH-Px showed a weak negative correlation (P < 0.05). Collectively, these findings suggest that body weight, body length, frame measurements (D5-7, D5-10, and D7-8), and serum NAM, FAD, and GSH-Px are associated with the degree of muscle crispness in Nile tilapia fed a faba bean-based crisping diet and may serve as candidate biomarkers under these culture conditions.

Animals↗

PubMed2026

Evaluation of three Aspergillus antibody assays for screening of chronic pulmonary aspergillosis: prospective diagnostic accuracy study.

OBJECTIVES: Chronic pulmonary aspergillosis (CPA) is a frequent complication of pulmonary tuberculosis (PTB), particularly in high-burden settings where access to reliable serological diagnostics remains limited. We evaluated the diagnostic performance of two immunochromatographic technology (ICT) lateral flow assays (LFAs) and an ELISA for CPA screening among patients with active or previously treated PTB. METHODS: In this two-year prospective multicentre diagnostic evaluation, serum from adults with prior or active PTB was tested using the Era Biology Aspergillus IgG ICT LFA, LDBio Aspergillus IgG/IgM ICT LFA, and Bordier Aspergillus fumigatus IgG ELISA. CPA diagnosis was established using a consensus composite reference standard incorporating clinical, immunological, radiological, and microbiological criteria. The Bordier ELISA was used as part of the immunological component of the consensus CPA diagnosis, with a cutoff optical density of ≥1.0. Diagnostic accuracy, agreement statistics, receiver operating characteristic analysis, and latent class analysis (LCA) were performed. RESULTS: Among 340 participants, 24 (7.06%) had CPA. Proportion of participants with positive antibody tests among all tested individuals were 6.76% for LDBio ICT LFA, 20.0% for Era Biology ICT LFA, and 11.47% for Bordier ELISA. Against consensus CPA diagnosis, Bordier ELISA showed 87.50% sensitivity and 94.30% specificity, LDBio ICT LFA 58.33% sensitivity and 97.15% specificity, and Era Biology LFA 66.67% sensitivity and 83.54% specificity. LCA estimated CPA prevalence at 7.72%. LCA-derived sensitivities and specificities were 86.58% and 99.92% for LDBio ICT LFA, 83.39% and 85.31% for Era Biology LFA, and 79.10% and 94.19% for Bordier ELISA. CONCLUSIONS: The Bordier ELISA showed high sensitivity and specificity, while the LDBio ICT LFA demonstrated very high specificity with strong LCA-derived performance. These findings support the use of ELISA for laboratory diagnosis and ICT as a point-of-care screening tool for CPA in resource-limited settings. Era Biology Aspergillus IgG LFA demonstrated moderate sensitivity and acceptable diagnostic performance, indicating its potential utility as a supplementary screening assay for CPA in settings where rapid, point-of-care testing is required.

Humans↗

PubMed2026

Transverse Tibial Transport for Limb Salvage in Ischemic Lower Extremity Disease: Technique, Mechanisms, and Clinical Outcomes-A Systematic Review.

Transverse tibial transport (TTT) is a surgical technique derived from Ilizarov's distraction osteogenesis principles that stimulates angiogenesis and microcirculatory regeneration in the ischemic lower limb without directly manipulating macrovascular anatomy. By creating a proximal tibial cortical bone window and distracting it transversely using an external fixator, TTT triggers converging cascades of growth factor release, endothelial progenitor cell mobilization, and immunomodulation that translate into improved distal limb perfusion and wound healing. Combined TTT plus endovascular therapy improves amputation-free survival versus endovascular therapy alone. Prospective randomized trials and standardized international protocols are needed to consolidate TTT's role in multidisciplinary limb salvage pathways.

Humans↗

PubMed2026

Non-destructive prediction of lead content in oilseed rape leaves by fluorescence hyperspectral technology based on neural network.

Based on fluorescence hyperspectral imaging (FHSI), this study targeted rapid, non-destructive quantification of lead (Pb) content in oilseed rape leaves treated with varying silicon (Si) concentrations, acquiring fluorescence spectra over the 484.43-1001.61 nm wavelength range. To optimize spectral data quality, preprocessing methods (Savitzky-Golay smoothing, first derivative, detrending) were comprehensively compared. Characteristic wavelengths were then selected via interval variable iterative shrinkage, which effectively compressed data dimensionality and reduced computational load. A hybrid SE-CL1DA model, fusing a 1D convolutional neural network, a long short-term memory network and SE attention mechanism was constructed, with Bayesian optimization tuning hyperparameters to boost stability. The BO-SE-CL1DA outperformed both traditional machine learning and insufficiently optimized deep learning model (Rp2=0.9609, RMSE = 0.0377 mg/kg, RPD = 5.1736), thus enabling accurate Pb estimation, supporting Si-regulated heavy metal stress management and facilitating agricultural contamination monitoring.

Plant Leaves↗

PubMed2026

Artificial intelligence (AI) uses in stereotactic radiosurgery (SRS): diagnosis with brain metastasis (BM) - A systematic review.

BACKGROUND: Brain metastases (BM) are the most common intracranial tumors in adults, and stereotactic radiosurgery (SRS) has become a mainstay of management. However, several diagnostic challenges persist in the SRS pathway, particularly the differentiation of radiation necrosis (RN) from true tumor progression, which conventional MRI and even advanced imaging techniques often cannot reliably resolve. Recent advances in artificial intelligence (AI) offer the potential to address these diagnostic limitations. This systematic review synthesizes current literature on AI applications for MRI-based diagnostic decision support in BM patients undergoing SRS, with a focus on radiomics and deep learning tools for distinguishing RN from progression, classifying molecular and histologic subtypes, and predicting treatment response. METHODS: A systematic review was performed in accordance with PRISMA guidelines. PubMed, Web of Science, and Scopus were searched using a targeted query combining terms related to AI, brain metastasis, diagnosis or imaging, and SRS. After screening 483 records and applying strict inclusion and exclusion criteria, 18 studies published between 2015 and 2025 were included. Data were extracted on study design, cohort characteristics, imaging modality, AI methodology, validation strategy, and reported diagnostic performance. RESULTS: Among the 18 included studies, AI models demonstrated strong performance across diagnostic tasks in the BM-SRS pathway. The differentiation of RN from true tumor progression was the most extensively studied application, addressed by 14 of 18 studies, with reported AUCs ranging from 0.71 to 0.94. Support vector machines, random-forest ensembles, convolutional neural networks, and transformer-based multimodal architectures were widely used. The literature evolved from single-sequence radiomic classifiers in 2018 to multimodal deep learning frameworks fusing imaging with clinical and genomic data in 2025. Contrast-enhanced T1-weighted MRI was the dominant imaging input, and texture-based radiomic features (GLCM, GLSZM, GLDM, and wavelet-derived features) were the most consistently predictive. The highest-performing models reached AUCs of 0.85-0.91 through multimodal integration of imaging with clinical and genomic features, and consistently outperformed expert neuroradiologist read on matched cases. Remaining studies addressed longitudinal segmentation-based detection of local failure and adverse radiation effects, BRAF mutation status in melanoma BM, early Gamma Knife treatment response, and primary tumor histology classification, with more variable performance. CONCLUSION: AI models, particularly those integrating MRI-derived radiomic features with clinical and genomic data, show high accuracy in supporting diagnostic decisions for BM patients treated with SRS. The post-SRS differentiation of radiation necrosis from true tumor progression has reached the greatest level of maturity and is closest to clinical translation, with potential to reduce unnecessary biopsies, personalize surveillance intervals, and rationalize treatment-pathway decisions. Other diagnostic applications, including molecular subtyping and primary tumor histology classification, remain exploratory and require further multicenter validation. Integration of AI tools into multidisciplinary tumor-board workflows, combined with prospective validation and standardized reporting, will be essential to realize the full clinical benefits of AI in SRS for brain metastases.

Humans↗

PubMed2026

Algae-to-host horizontal gene transfer in Paramecium bursaria is associated with host adaptation during endosymbiosis.

Paramecium bursaria maintains a stable endosymbiosis with green algae, yet the evolutionary consequences of this association remain unclear. Here, we screened the host genome for algal-derived horizontally transferred genes (HTGs) using a lineage-aware workflow designed to detect horizontal gene transfer (HGT) between two defined lineages. We identified 16 candidate HTGs, including four putative newly transferred genes and 12 homologous transferred genes, most of which were functionally associated with redox homeostasis and metabolism. Five HTGs showed symbiosis-dependent expression. RNAi knockdown of GH32s and SATs reduced host proliferation, total cell area, and motility, while GH32s knockdown also reduced endosymbiont load. Duplication patterns suggest that most transfers may have occurred after the P. bursaria lineage diverged from the sampled Paramecium species but before its lineage-specific whole-genome duplication (WGD). The HTGs also showed host-associated shifts in GC content and gene length, while representative HTGs retained conserved domains and functional motifs. Together, our results support algae-to-host HGT in P. bursaria and suggest that some transferred genes may contribute to metabolic integration during endosymbiosis.

Gene Transfer, Horizontal↗

PubMed2026

Effects of semaglutide and empagliflozin on markers of endothelial function in persons with type 2 diabetes: A post hoc analysis of a randomized clinical trial.

AIMS: The endothelium maintains vascular health by regulating blood flow and protecting against inflammatory damage. In type 2 diabetes (T2DM), however, hyperglycemia, hypertension, and hyperlipidemia place a significant burden on the endothelium, potentially leading to atherosclerosis and cardiovascular disease (CVD). While semaglutide and empagliflozin have been shown to reduce CVD risk in T2DM, it remains unclear whether these benefits are mediated by improved endothelial function. This post-hoc analysis explores the effects of these agents on markers of endothelial function, i.e. the reactive hyperaemic index (RHI) and the endothelial-derived cell adhesion molecules (CAMs) E-Selectin, ICAM-1, P-Selectin, and VCAM-1. METHODS: This was a post-hoc analysis of a 32-week randomized trial evaluating the separate and combined effects of semaglutide and empagliflozin on cardio-renal organ damage. One hundred and twenty participants with type 2 diabetes, age ≥ 50 were randomized to four groups (semaglutide, empagliflozin, the combination or placebo). An increase in RHI and/or a decrease in CAMs were considered beneficial. RESULTS: RHI increased compared to baseline (0.11, 95%CI [0.008;0.21], p = 0.03) but not compared to placebo in the semaglutide group (0.11, 95%CI [-0.04;0.24], p = 0.16). There was no effect on RHI in the empagliflozin group. Compared to placebo, E-Selectin decreased significantly in the semaglutide and combination groups (-9, 95%CI [-14.1;-5.1] p < 0.01 and - 9, 95%CI [-14.3; -5.2] p < 0.01, respectively). VCAM-1 increased in the same groups, compared to placebo (12.3, 95%CI[2.8;20.8] p = 0.01 and 16.2, 95%CI [7.2;24.3], p < 0.01, respectively).P-Selectin and ICAM-1 was not significantly affected in any of the groups, compared to placebo (p ≥ 0.11 and p ≥ 0.09, respectively). CONCLUSION: Semaglutide improved endothelial function compared to baseline, but not significantly versus placebo, which likely is due to limited power. CAM responses were heterogeneous, suggesting distinct roles in endothelial dysfunction and atherosclerosis. ClinicalTrialsRegister.eu: EudraCT 2019-000781-38.

Aged↗

PubMed2026

From host response to genomic targets: electrochemical biosensing of tuberculosis biomarkers.

Tuberculosis (TB) remains one of the leading causes of death from a single infectious agent worldwide, with timely diagnosis continuing to be a major challenge, particularly in resource-limited settings. Conventional TB diagnostic methods are limited by low sensitivity, long turnaround times, and an inability to reliably differentiate latent from active disease. Biomarker-based diagnostic strategies have therefore gained increasing attention as they offer the potential to improve early detection, disease differentiation, and treatment monitoring. Herein, we examine electrochemical biosensing strategies for TB diagnostics using a biomarker-class-driven framework, covering host-response biomarkers (IFN-γ and TNF-α), pathogen-derived antigens (ESAT6, CFP10, CFP10-ESAT6, MPT64, Ag85, HspX and LpqH), cell-wall signatures and whole-cell markers (LAM and whole cell Mtb), and genomic markers (Mtb DNA and IS6110). Through structured comparison of recognition elements, biointerface designs, signal amplification strategies, electrochemical techniques, matrices, and validation levels, this review identifies the most promising technical approaches for different TB biomarker classes. It further highlights key translational bottlenecks, including limited clinical validation, buffer-based testing, complex multistep amplification, redox-probe dependence, matrix fouling, and insufficient evidence of manufacturability. This review therefore provides practical guidance for developing electrochemical TB biosensors that are analytically sensitive, clinically relevant, and suitable for decentralized diagnostic applications.

Biosensing Techniques↗

PubMed2026

Comparative genomics and full-length transcriptome profiling of wing morphs in Tetrix grossus (Orthoptera: Tetrigidae).

Wing polymorphism represents a paradigmatic dispersal-reproduction trade-off, yet its molecular basis remains uncharacterised in the phylogenetically distant pygmy grasshoppers (Tetrigidae). Here we integrate comparative genomics across ten orthopteran species with full-length transcriptomics of long-winged (FL) and short-winged (FS) Tetrix grossus. OrthoFinder recovered 118 orthogroups specific to T. grossus. Against a backdrop of pronounced gene-family contraction (36 expansions versus 222 contractions; net -186, mirrored at the ancestral Tetrix node, +37/-140), we identified an ancestral, Tetrix-specific expansion of hormone-regulation (12 genes; fold enrichment 7.93) and lipid/carbohydrate-metabolic families organised into syntenic clusters, alongside 513 positively selected genes enriched for integrin-mediated cell adhesion (6 genes), a process relevant to epithelial and appendage morphogenesis. Full-length transcriptomics of one long-winged (FL) and one short-winged (FS) adult female detected 7530 (FL) and 7515 (FS) expressed genes, with 794 FL- and 776 FS-restricted transcriptome-derived SNP-associated genes. The FL morph was enriched for an EGFR/Ras-Rho developmental-patterning axis and neuromuscular flight genes, whereas the FS morph was enriched for insulin/peptide-hormone response and growth-regulatory loci. Overall, we present genomic resources and testable hypotheses concerning the evolution and regulation of wing morphs in Tetrigidae rather than a validated genetic architecture of wing-morph determination.

Animals↗

PubMed2025

Application of causal discovery of factors driving dissolved oxygen in estuarine environments.

Dissolved oxygen (DO) concentrations in estuarine bottom waters are a manifestation of multiple, interacting physical and biogeochemical processes, yet identifying their independent contributions remains challenging. Here, we analyze monthly water quality monitoring data from eight stations across Long Island Sound from 1994 to 2022 using a causal discovery framework (PCMCI+) and transformation of forcing variables. Our goal is to identify and isolate variables that causally influence bottom DO and improve predictive models by minimizing overfitting and multicollinearity. PCMCI+ reveals surface-layer temperature as the most important and consistent negative driver of bottom DO, followed by stratification. Wind events exhibit only brief relief by advection and mixing, while river discharge shows no direct causal link to DO, making it less influential than previously thought. Biogeochemical variables, including chlorophyll-a (Chl-a), nitrate and nitrite, and particulate carbon, influence DO through both contemporaneous and time-lagged pathways, often with signs that shift depending on the process. The derived models were evaluated by comparing skill scores, mean squared error, and Akaike Information Criterion. Both model types perform well, with coefficient of determination values exceeding 0.90 at multiple stations using only 3-5 predictors. Our analysis reveals that the best causal predictors are surface-layer temperature, stratification, Chl-a, and particle carbon. This approach provides a scalable framework for improving prediction models and understanding the mechanistic links that control the seasonal variability of DO in estuarine systems.

Estuaries↗

PubMed2026

Glycerophospholipid remodeling under osmotic stress in grass carp gills.

Salinity fluctuations represent a pervasive environmental challenge for freshwater fishes, yet the cellular and metabolic programs governing early osmoregulatory responses remain understudied. Here, we investigated the time-dependent gill responses of juvenile grass carp (Ctenopharyngodon idella) subjected to an acute, sublethal salinity increase 9 parts per thousand (ppt). Histological and biochemical analyses revealed progressive gill lesions accompanied by elevated lactate dehydrogenase (LDH) activity and lipid peroxidation, indicating rapid tissue injury under osmotic stress. Integrative metabolomic and transcriptomic profiling uncovered pronounced temporal reprogramming, consistently highlighting glycerophospholipid metabolism as a central axis of response. In particular, phosphatidylcholine (PC) species exhibited dynamic remodeling, coupled with transcriptional enrichment of lipid turnover, membrane transport, and innate immune pathways. Network-based integration identified a PC-centered remodeling module characterized by accelerated PC headgroup turnover, disruption of the PLA2-LPCAT2 lyso-PC reacylation cycle, and enhanced ABC transporter-associated lipid and sterol export, reflected by cholesteryl sulfate accumulation and a shifted n-6 polyunsaturated fatty acid-derived oxylipin signature. Functional assays further demonstrated that PC and linoleic acid (LA) supplementation improved cell viability and alleviated oxidative stress and pro-inflammatory signaling in grass carp cells under salinity challenge. Collectively, these findings reveal phospholipid-centered membrane remodeling as an early, integrative mechanism linking osmotic stress to gill injury and immune activation in freshwater fish, providing insights into potential strategies of environmental stress adaptation.

Animals↗

PubMed2026

Glucocorticoids and placental 11βHSD2 - A systematic review of human studies and animal models.

CONTEXT: Elevated prenatal glucocorticoid (GC) exposure is linked to adverse offspring outcomes. The placental enzyme 11β-hydroxysteroid-dehydrogenase-type-2 (11βHSD2) protects the fetus by converting maternal derived cortisol to inactive cortisone. Although in vitro studies suggest GC mediated upregulation of 11βHSD2, in vivo evidence remains inconclusive. METHODS: PubMed, Embase, and PsycInfo were searched in October 2024 for human and mammalian animal studies on endogenous or exogenous GCs during pregnancy and associations with placental 11βHSD2 (mRNA, protein, activity, gene methylation). Narrative synthesis was conducted due to heterogeneity precluding meta-analysis. RESULTS: Eighteen studies (eight human, ten animal populations) met inclusion criteria. Exogenous GC exposure was associated with modifications in placental 11βHSD2 expression in animal models, with effects varying by substance, timing, and species. Dexamethasone trended towards increased expression in rodents, whereas betamethasone increased expression in non-human primates but not rodents. Human studies on endogenous GCs showed inconsistent associations with 11βHSD2 changes. In asthmatic pregnancies, moderate inhaled GC-use maintained enzyme activity compared to untreated patients. No convincing sex-specific trend emerged. CONCLUSIONS: GC exposure alters placental 11βHSD2 in a substance- and species-specific way; translational relevance remains limited based on current literature. Future studies should employ technological advances and include GC-sensitive biomarkers to clarify mechanisms of maternal-fetal stress transmission.

Female↗

PubMed2026

Lipid metabolism in hepatopancreas and ovaries of the mud crab Scylla paramamosain during vitellogenesis.

Ovarian lipids are essential nutrients that fundamentally determine oocyte and offspring quality, and ultimately affect the reproductive performance of decapod crustaceans. Lipids accumulated in the ovaries during vitellogenesis are mainly derived from the hepatopancreas. However, the molecular mechanisms underlying lipid metabolism in the hepatopancreas and ovaries during vitellogenesis remain largely unclear. In this study, comparative transcriptomic and lipidomic analyses were conducted on the hepatopancreas and ovaries of the mud crab Scylla paramamosain. From early to late vitellogenic stages, 454 lipid species were significantly increased and 17 decreased in abundance in the hepatopancreas, and 609 increased and 23 decreased in abundance in the ovaries. Meanwhile, there were 1481 upregulated and 963 downregulated transcripts in the hepatopancreas, and 3402 upregulated and 1478 downregulated transcripts in the ovaries. Subsequently, KEGG pathway co-enrichment analysis showed that the de novo biosynthesis of glycerophospholipids and glycerolipids was enhanced in the hepatopancreas, with upregulated ALDH, GPAT, plsC, PLPP, FASN, and HSD17B8 transcripts and elevated abundances of PC, PE, PS, PA, PG, DG, and TG species from the early to late vitellogenic stages in mud crabs. In contrast, glycerophospholipid catabolism and conversion were activated in the ovaries, with upregulated PLA2G, LYPLA1, NTE, GPCPD1, PLD_1, PGS1, and CRLS transcripts and elevated abundances of LPC, LPE, LPS species. These findings provide novel insights into the molecular mechanisms of lipid metabolism during vitellogenesis in decapod crustaceans.

Animals↗

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↗