PubMed

Health Sci Rep. 2026 May 31;9(6):e72452. doi: 10.1002/hsr2.72452. eCollection 2026 Jun.ABSTRACTBACKGROUND/PURPOSE: Multi-omics integration linking genomic, transcriptomic, epigenomic, proteomic, metabolomic, single-cell, and spatial data has transformed the interpretation of human genetic variation by capturing molecular processes that extend beyond DNA sequence alone. Although these approaches substantially improve biomarker discovery and disease stratification, translation into clinical practice remains uneven due to methodological heterogeneity, limited validation, regulatory uncertainty, and structural inequities in data generation. This systematic review and meta-analysis aimed to evaluate scientific performance, clinical readiness, governance frameworks, and socio-technical constraints influencing multi-omics biomarker development, and to generate a roadmap for equitable global implementation.METHODS: Following PRISMA 2020 guidelines, we systematically searched PubMed, EMBASE, Web of Science, Scopus, medRxiv, and bioRxiv for studies published between January 2010 and December 2025. Eligible articles integrated ≥ 2 omics modalities, applied AI/ML to biomarker development or variant interpretation, assessed clinical utility or real-world implementation, or examined governance, ethics, consent, equity, or policy issues. Data extraction captured assay type, integration strategy, model performance, validation rigor, and regulatory or socio-technical insights. Random-effects meta-analyses estimated pooled improvements in AUC, sensitivity, specificity, and hazard ratio precision, and heterogeneity was assessed using I² statistics.RESULTS: From 9846 records, 528 studies met the inclusion criteria. Multi-omics integration improved predictive performance, yielding pooled gains of +0.16 in AUC (95% CI: 0.11-0.19), +13% in sensitivity, and +9% in specificity. Models combining ≥ 3 omics layers showed the largest improvements (+0.19 AUC). Single-cell and spatial assays enhanced risk stratification by 18% but demonstrated reproducibility limitations. AI/ML approaches added +0.12 AUC over traditional models, yet 67% exhibited ancestry bias, and only 22% implemented explainability tools. Only 19% of biomarkers underwent real-world evaluation due to limited validation, reimbursement gaps, interoperability challenges, and unclear data-rights governance.CONCLUSION: Multi-omics biomarkers offer substantial analytical advantages, but their translation requires standardized validation frameworks, accountable AI governance, interoperable infrastructure, and globally inclusive data sets to ensure equitable, trustworthy implementation.PMID:42255056 | PMC:PMC13239253 | DOI:10.1002/hsr2.72452

Front Vet Sci. 2026 May 21;13:1822882. doi: 10.3389/fvets.2026.1822882. eCollection 2026.ABSTRACTINTRODUCTION: This study evaluated the effects of Dendrobium devonianum Paxt stem residue (DPSR) and its fermented form (FDPSR) as dietary ingredients on broiler growth performance and roasted chicken quality.METHODS: A total of 63 white-feathered broilers were assigned to three dietary treatments for 45 days: CK (basal diet), DPSR (basal diet supplemented with 10% DPSR), and FDPSR (basal diet supplemented with 10% FDPSR), with three replicate pens per treatment and seven birds per pen. Roasted chicken breast was analyzed by texture profile analysis, oxidation-related assays, E-nose, E-tongue, LC-MS, HS-SPME-GC-MS, and molecular docking simulation analysis.RESULTS: During days 1-21, both DPSR and FDPSR reduced average daily gain to 24.70 and 26.60 g/bird/day, respectively, compared with 33.67 g/bird/day in the CK group (p < 0.05). Furthermore, feed conversion ratios increased feed to 1.66 and 1.54 for DPSR and FDPSR, respectively, compared with 1.27 in the CK group (p < 0.05). In contrast, no significant differences were observed among treatments during days 22-45 or over the entire 45-day feeding period. In roasted chicken, DPSR improved selected textural attributes, whereas FDPSR was more strongly associated with flavor-related variations. Both treatments significantly reduced malondialdehyde content after roasting (p < 0.05). Metabolomics identified 52 differential metabolites, with aldehydes being markedly higher in the FDPSR group (67.81%) than in the CK (43.56%) and DPSR (40.11%) groups. Molecular docking simulation suggested potentially favorable interactions between representative aroma compounds and selected olfactory receptors.DISCUSSION: Overall, DPSR and FDPSR altered the texture, oxidative stability, and flavor profiles of roasted chicken, with FDPSR demonstrating a more pronounced effect on flavor-related metabolites and volatile compounds. These findings provide preliminary support for the use of DPSR-based ingredients in poultry production, although further validation is required.PMID:42254895 | PMC:PMC13235580 | DOI:10.3389/fvets.2026.1822882

Front Vet Sci. 2026 May 21;13:1837846. doi: 10.3389/fvets.2026.1837846. eCollection 2026.ABSTRACTBACKGROUND: Biospecimen choice can substantially influence metabolite measurements, yet matched comparisons of serum, EDTA plasma, lithium-heparin plasma, and urine remain limited in canine targeted metabolomics.OBJECTIVES: To evaluate cross-matrix comparability of targeted small polar metabolite profiles in dogs and to assess how different biospecimens capture diet- and health-associated variation.ANIMALS: Client-owned dogs from a previously reported feeding trial.METHODS: Targeted ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) was performed on matched biospecimens from a baseline blood-matrix cohort (serum, EDTA plasma, lithium-heparin plasma) and an end-of-trial serum-urine cohort. Metabolites with >20% missing values within a matrix and samples with >20% missing metabolite values within a biofluid were excluded. Cross-matrix agreement was assessed using Pearson correlation and mean paired log10 concentration differences. PCA and PERMANOVA were used to compare global matrix effects and diet- and health-associated separation.RESULTS: After filtering, 88 metabolites remained for serum, 85 for EDTA plasma, and 88 for lithium-heparin plasma in the blood-matrix cohort. Globally, EDTA plasma separated clearly from both serum and lithium-heparin plasma, whereas serum and lithium-heparin plasma overlapped substantially. At the metabolite level, 10/84 (11.9%) serum-EDTA plasma, 16/88 (18.2%) serum-lithium-heparin plasma, 20/84 (23.8%) lithium-heparin plasma-EDTA plasma, and 4/75 (5.3%) serum-urine comparisons were comparable to varying degrees. Serum showed the clearest diet-associated separation at baseline (PERMANOVA pseudo-R 2 = 0.13, p = 0.013) and end-of-trial (pseudo-R 2 = 0.22, p = 0.021). Health-associated separation was weak and exploratory.CONCLUSIONS AND CLINICAL IMPORTANCE: Biospecimen choice materially affects targeted metabolite profiling in dogs. Serum and lithium-heparin plasma were globally more similar to each other than either was to EDTA plasma, whereas urine was a distinct complementary matrix rather than a blood surrogate. Serum was the most robust matrix for detecting diet-associated variation.PMID:42254893 | PMC:PMC13233384 | DOI:10.3389/fvets.2026.1837846

Front Psychiatry. 2026 May 21;17:1826019. doi: 10.3389/fpsyt.2026.1826019. eCollection 2026.ABSTRACTOBJECTIVE: This study aimed to construct a high-efficiency dual-modal diagnostic model for treatment-resistant depression (TRD) by integrating serum metabolomics and clinical risk factors, and explore its metabolic pathological mechanisms.METHODS: A total of 93 major depressive disorder (MDD) patients (53 TRD, 40 non-TRD) were enrolled for a single-center retrospective study. Serum untargeted metabolomics and clinical baseline data were collected, with differential metabolites and clinical risk factors screened by statistical analysis and multi-step machine learning to identify core features. Five machine learning algorithms were compared to build unimodal and random forest-based dual-modal diagnostic models, and KEGG pathway enrichment analysis was performed.RESULTS: 3 core clinical risk factors (medical history, HDL, FBG) and 8 core metabolic biomarkers were identified. The dual-modal model achieved AUC 0.996 (training) and 0.911 (validation), outperforming unimodal models. Differential metabolites were mainly enriched in lipid (44.8%) and amino acid (23.9%) metabolism. Fibrinopeptide A516, 12-HETE and the three clinical factors were core driving features.CONCLUSION: The dual-modal model has high diagnostic efficiency for TRD. TRD is associated with endocannabinoid system hypofunction and metabolic imbalance, which provides an objective diagnostic tool and new insights for TRD mechanism research and therapy development.PMID:42254727 | PMC:PMC13233471 | DOI:10.3389/fpsyt.2026.1826019

IMA Fungus. 2026 May 28;17:e192779. doi: 10.3897/imafungus.17.192779. eCollection 2026.ABSTRACTMembers of the genus Pestalotiopsis have been reported from symptomatic, asymptomatic, and dead plant tissues, and are therefore frequently described as phytopathogens, endophytes, or saprobes. This study focused on two closely related species, Pestalotiopsis formosana and P. neolitseae, which have been isolated from saprobic, endophytic, and pathogenic contexts in recent studies, raising questions regarding the basis for these diverse observed lifestyles. To clarify this ambiguity, we sequenced six new genomes representing strains of these species spanning these observed lifestyles and compared them with four publicly available, curated plant-associated genomes. Despite contrasting field observations, strains of P. formosana and P. neolitseae showed nearly identical genome features, sharing a core genome of 12,021 orthologous proteins with almost identical secretome content, effectors, CAZyme repertoires, and secondary metabolite gene clusters. Carbon-use assays (Biolog FF and minimal media) further showed broadly overlapping metabolic capabilities, although some strain-level differences were observed. CAZyme-based trophic prediction (CATAStrophy) also placed all analysed strains within the same broad trophic prediction space. Taken together, these results do not support clear genome-scale differentiation corresponding to the assigned lifestyle categories within the present sampling framework. Instead, the data are consistent with the interpretation that these fungi share a broadly conserved genomic toolkit, while ecological expression may depend on regulatory, physiological, host-related, and environmental factors. These findings provide a comparative framework for future studies integrating transcriptomics, metabolomics, and experimental infection assays to clarify how ecological behaviour is expressed in Pestalotiopsis.PMID:42254593 | PMC:PMC13237565 | DOI:10.3897/imafungus.17.192779

Bioinform Adv. 2026 May 15;6(1):vbag138. doi: 10.1093/bioadv/vbag138. eCollection 2026.ABSTRACTSUMMARY: Liquid chromatography-mass spectrometry (LC-MS/MS) data analysis requires adaptable software solutions to meet diverse analytical needs. We present eMZed 3, a modern Python framework for flexible and interactive analysis of LC-MS/MS data. eMZed 3 enables users to develop scalable workflows tailored to their specific requirements while leveraging Python's extensive ecosystem of libraries. Building on its predecessor, eMZed 3 is now Python 3-based and includes substantial enhancements, including support for chromatogram-based LC-MS data, a new SQLite-based backend supporting optional out-of-memory processing, and rich interactive visualization tools. Compared to the previous version, eMZed 3 is now split into three packages: emzed (core functionalities), emzed-gui (interactive data visualization), and emzed-spyder (an integrated development environment). This modular architecture allows straightforward integration of the emzed core library into headless Python environments, including computational notebooks (such as Jupyter) or high-performance computing clusters. eMZed 3 incorporates well-established libraries such as OpenMS, and is suited for both targeted and untargeted metabolomics. Overall, eMZed 3 supports the efficient development of scalable and reproducible LC-MS data analysis and is accessible to both novice and advanced programmers.AVAILABILITY AND IMPLEMENTATION: eMZed 3 and its documentation are freely available at https://emzed.ethz.ch, the source code is hosted at https://gitlab.com/groups/emzed3.An online-executable example workflow is available on Binder at: https://mybinder.org/v2/gl/emzed3%2Femzed-example-workflow/HEAD?_labpath=example.ipynb.PMID:42254591 | PMC:PMC13242181 | DOI:10.1093/bioadv/vbag138

Potato Res. 2026;69(4):131. doi: 10.1007/s11540-026-10083-2. Epub 2026 Jun 5.ABSTRACTTo obtain comprehensive insight into metabolic changes in potato seed tubers during storage and to identify patterns associated with physiological ageing, we analysed tuber metabolite composition using untargeted metabolomics based on gas and liquid chromatography-mass spectrometry (GC-MS and LC-MS). During two seasons, seed tubers of four contrasting cultivars (Agria, Festien, Innovator, and Lady Claire) were produced in a single field and after harvest, stored at different temperatures. During storage, the number of detected secondary metabolites increased progressively, particularly at higher temperatures (7-17 ˚C). Principal component analysis (PCA) revealed clear cultivar-specific metabolic profiles, with the starch cultivar Festien distinctly separated from the consumption cultivars, primarily caused by different amino acid composition. PCA further highlighted the impact of cold storage (4 ˚C) on primary metabolism, especially the accumulation of reducing sugars, as well as the combined effects of storage duration and elevated temperature on secondary metabolites, notably glycoalkaloids. Factor analysis (FA) supported these findings, with most metabolites strongly associated with the factor distinguishing cv. Festien from the other cultivars. Additionally, the leading factors captured cultivar-specific patterns and diverse trajectories reflecting the effects of storage duration and temperature. Together, these results provide a comprehensive overview of metabolic dynamics during storage and contribute to understanding the functional roles of metabolites in tuber physiological ageing.SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11540-026-10083-2.PMID:42254535 | PMC:PMC13241448 | DOI:10.1007/s11540-026-10083-2

Front Microbiol. 2026 May 21;17:1779143. doi: 10.3389/fmicb.2026.1779143. eCollection 2026.ABSTRACTBACKGROUND AND OBJECTIVE: Although infliximab (IFX) is endorsed for induction therapy in severe ulcerative colitis (SUC), its therapeutic response remains heterogeneous. We conducted a comprehensive analysis of fecal and mucosal microbiota, coupled with targeted metabolomics, to delineate microbial and metabolic signatures predictive of IFX induction efficacy and to explore mechanistic pathways underlying differential treatment responses.METHODS: This study was a prospective cohort study (clinical study registration number: ChiCTR2300071816). It enrolled adult patients aged ≥ 18 years who were first diagnosed with SUC at the First Affiliated Hospital of Nanjing Medical University and Northern Jiangsu People's Hospital between February 2022 and December 2023. None of these patients had received any medication for UC, including antibiotics. Clinical data, fecal samples, and rectal mucosal samples were collected for analysis. High-throughput sequencing of the 16S rRNA gene and non-targeted metabolomics analysis were performed on both fecal and rectal mucosal samples. All patients underwent IFX (5 mg/kg) induced remission therapy at weeks 0, 2, and 6. Based on their clinical response at week 14, they were categorized into two groups: response and unresponse. Significant differences in bacterial composition between the two groups were identified by screening fecal and mucosal samples. The gut microbiota of feces and intestinal mucosa were combined with clinical data to create four prediction models and conduct comparisons. Furthermore, different metabolites from fecal and mucosal samples of the two groups were screened and compared with KEGG and PubChem databases to identify metabolic pathways associated with the efficacy of IFX-induced therapy.RESULTS: Compared with non-responders, IFX responders harbor distinct gut microbiota. Clinical indices alone poorly forecast induction response (AUC 0.6429). Augmenting clinical variables with fecal or mucosal microbiota improves prediction to AUC 0.795 and 0.900, respectively; combining both compartments further elevates performance to AUC 0.964, indicating that integrated microbiome profiling is essential for optimal IFX response prediction. IFX responders and non-responders differ metabolically, with more discriminatory features in mucosa than feces. The most enriched differential pathways in feces included nicotinate and nicotinamide metabolism, butyrate metabolism, biosynthesis of valine, leucine, and isoleucine, pantothenate and coenzyme A biosynthesis, histidine metabolism, and alanine, aspartate, and glutamate metabolism. In mucosa, the most enriched differential pathways included alanine, aspartate, and glutamate metabolism, sphingolipid metabolism, ascorbate and aldarate metabolism, tryptophan metabolism, and D-glutamine and D-glutamate metabolism. The common pathway enriched in both feces and mucosa was alanine, aspartate, and glutamate metabolism.CONCLUSION: The intestinal microbiota may be a predictive factor for IFX induction outcome in patients with SUC. The metabolic pathway of alanine, aspartate, and glutamate may be associated with the 14-week clinical response to IFX treatment in SUC.PMID:42254525 | PMC:PMC13233438 | DOI:10.3389/fmicb.2026.1779143

Front Microbiol. 2026 May 22;17:1801806. doi: 10.3389/fmicb.2026.1801806. eCollection 2026.ABSTRACTBACKGROUND: Geographic variations in climate and lifestyle may be associated with hypertension (HTN) through alterations in the gut microbiota and its metabolites. This study aimed to comparatively analyze the gut microbiome and fecal metabolome of hypertensive patients from two Chinese cities characterized by distinct climatic conditions: Daqing (middle-temperate climate) and Haikou (tropical climate). The objective was to identify gut microbial and metabolic characteristics associated with geographic differences and to provide insights into HTN prevention and management.METHODS: A cross-sectional study was conducted between May and December 2024, involving hypertensive patients from Daqing and Haikou. Fecal samples were collected from 28 hypertensive patients in Daqing (DQ group) and 32 in Haikou (HK group), and analyzed using shotgun metagenomic sequencing and untargeted metabolomics.RESULTS: Differences in microbial composition and metabolite profiles were observed between the two groups. Using ALDEx2 analysis at the genus level, 34 genera were identified as differentially abundant between the DQ and HK groups. After adjusting for potential confounding variables, including age, body mass index, smoking, and drinking status, 6 genera remained significantly associated with geographic grouping. A logistic regression model based on these genera achieved an area under the curve (AUC) of 0.8069, with Pseudescherichia showing the highest individual discriminatory performance (AUC = 0.7925). Functional analysis suggested that pathways such as xylene degradation and biofilm formation were relatively reduced in the DQ group. Metabolomic analysis identified 38 differentially abundant metabolites, including 15-hydroxyeicosatetraenoic acid (15-HETE), 7α,25-dihydroxycholesterol, the putative metabolite (3-hydroxypentadecanoyl) lysine, and ginsenoside Rg3. Dysregulated pathways were mainly involved in glycerophospholipid metabolism, ABC transporters, and choline metabolism. Correlation analysis revealed potential associations between differential microbes and metabolites.CONCLUSION: Distinct gut microbiome and metabolome profiles were observed between hypertensive patients from the two geographic regions. These findings suggest potential associations between environmental factors and host-microbiome-metabolite interactions.PMID:42254517 | PMC:PMC13236899 | DOI:10.3389/fmicb.2026.1801806

Front Microbiol. 2026 May 22;17:1824965. doi: 10.3389/fmicb.2026.1824965. eCollection 2026.ABSTRACTSecondary bacterial pneumonia is a severe complication of influenza;howeve the biological determinants that distinguish progression from uncomplicated infection remain poorly understood. We investigated the oropharyngeal microbiome and plasma metabolome as potential discriminators of pneumonia development. In this study, we report a cross-sectional case-control study conducted during the 2022-2023 influenza season to identify and internally validate a microbiome-metabolite profile that characterizes pneumonia cases from uncomplicated influenza. We enrolled 236 consecutive influenza patients from Jiangsu Province, China (October 2023-December 2024): 59 with secondary pneumonia and 177 uncomplicated controls. Oropharyngeal swabs were subjected to 16S rRNA V3-V4 sequencing; plasma metabolomics was performed by UPLC-MS/MS in both ion modes. Seven machine-learning algorithms were compared; Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression was selected because it yielded the highest cross-validated discrimination. Microbial composition distinguished groups, not richness. Pneumonia cases showed enrichment of Synergistota and Bifidobacteriaceae with depletion of Bacillaceae (β-diversity p = 0.057). Controls exhibited enriched glycolysis and lipid metabolism pathways; pneumonia cases showed elevated degradation pathways (GLUCARDEG and GALLATE-DEGRADATION). Plasma metabolomics revealed a lipid depletion signature: phospholipids PC(O-16:0/0:0) and PS(14:0/18:3(9Z,12Z,15Z)) were significantly reduced (area under the (receiver operating characteristic) curves (AUCs) = 0.69-0.71). Small Molecule Pathway Database (SMPDB) pathway analysis demonstrated suppressed anabolic (tyrosine, steroid, and purine metabolism) and enhanced catabolic (beta-oxidation of very long-chain fatty acids) pathways. Machine learning identified Peptococcus as the top indicator (LASSO AUC = 0.65); Shapley Additive Explanation (SHAP) analysis revealed a monotonic risk increase with abundance. Oropharyngeal dysbiosis and systemic metabolic reprogramming characterize influenza cases that progress to secondary pneumonia. Peptococcus and four metabolites form an internally validated exploratory profile associated with secondary pneumonia; external validation and performance optimization are warranted.PMID:42254513 | PMC:PMC13236517 | DOI:10.3389/fmicb.2026.1824965

Front Microbiol. 2026 May 22;17:1810954. doi: 10.3389/fmicb.2026.1810954. eCollection 2026.ABSTRACTThis trial selected Turpan Black ewes at 100 days of gestation as test subjects to investigate the effects of supplemental feeding with Astragalus and fermented Astragalus on the ewes' rumen microbial community structure, plasma metabolites, antioxidant capacity, milk composition, as well as the immune parameters and growth performance of newborn lambs, in order to provide a theoretical basis for stress alleviation and the application of Astragalus and fermented Astragalus. The trial selected 60 Turpan Black ewes at 100 days of gestation and randomly divided them into three groups: Control group (CON group): basal diet; Astragalus group (AM group): basal diet + 2 g/day·head of Astragalus; Fermented Astragalus group (FAM group): basal diet + 2 g/day·head of fermented Astragalus. Each group consisted of 20 ewes, with a 5-day adaptation period and a 90-day experimental period. Dietary supplementation with Astragalus increased milk yield (p >0.05) and significantly enhanced antioxidant capacity, as evidenced by elevated catalase (CAT) activity and reduced nitric oxide (NO) levels (p < 0.01). Metabolomic analysis revealed that the treatment upregulated picolinic acid and related metabolites, thereby activating the tryptophan metabolic pathway (p < 0.01), which consequently improved rumen microbial community structure characterized by increased relative abundances of Bacteroidetes and Firmicutes. Additionally, membranaceus supplementation elevated birth weight of male lambs by 6.78%, and significantly increased serum concentrations of growth hormone (GH; p < 0.01), and immunoglobulins (IgA, IgG, and IgM; p < 0.01), accompanied by enhanced antioxidant capacity (p < 0.01). Fermented Astragalus membranaceus supplementation increased milk yield and enhanced ewe lactation performance, evidenced by elevated lactose content (p < 0.05). The intervention substantially improved systemic redox status, manifesting as increased T-AOC (p < 0.01) and augmented antioxidant enzyme activities (elevated CAT, reduced NO and MDA, p < 0.01). Rumen microbial profiling revealed significant enrichment of Bacillales, Methanobacteriales, and Spirochaetales (p < 0.05), coupled with metabolomic signatures indicating downregulation of medicarpin and concomitant activation of the α-linolenic acid metabolism pathway (p < 0.01). In offspring, the treatment increased male lamb birth weight (p < 0.01) and sustained elevation of GH secretion across all developmental stages (p < 0.01). Immunologically, neonatal lambs exhibited significantly higher circulating IgA, IgG, and IgM concentrations (p < 0.01), alongside enhanced neonatal antioxidant capacity characterized by elevated CAT and reduced NO levels (p < 0.01). In summary, fermented Astragalus demonstrated superior intervention effects compared to raw Astragalus in improving ewe milk quality, enhancing antioxidant capacity, optimizing rumen microbial flora structure, regulating lipid metabolism pathways, and promoting lamb growth, immunity, and antioxidant development.PMID:42254496 | PMC:PMC13236909 | DOI:10.3389/fmicb.2026.1810954

Res Pract Thromb Haemost. 2026 May 8;10(4):106635. doi: 10.1016/j.rpth.2026.106635. eCollection 2026 May.ABSTRACTBACKGROUND: To prolong the storage period of platelets, dimethyl sulfoxide (DMSO) has been used for platelet cryopreservation at -80 °C to prevent cold storage lesions. Nevertheless, it is important to note that DMSO is a toxic chemical agent that may cause adverse effects and potential safety concerns for clinical applications. Therefore, many studies have attempted to reduce the DMSO concentration used for platelet cryopreservation. Based on our previous findings regarding the stability of platelets in platelet-rich plasma stored at -80 °C for 1 month, it is imperative to explore the cryopreservation of platelets in plasma.OBJECTIVES: This study aimed to evaluate the feasibility of storing apheresis platelets in plasma at -80 °C as a supplemental solution in the absence of cryoprotectants, such as DMSO.METHODS: We used a comprehensive approach, analyzing platelet count, morphology, mitochondrial structure, and metabolomic and proteomic profiles to assess storage lesions.RESULTS: Our findings revealed that platelets stored at -80 °C in plasma maintained a stable cell count and procoagulant function, comparable with those stored with DMSO. Proteomic analysis showed that the fundamental protein composition essential for platelet clotting function was largely preserved, while metabolomic analysis suggested that metabolism had a minimal impact on platelet homeostasis. In vitro assessments showed no significant difference in platelet activation, and in vivo studies confirmed comparable bleeding times and platelet counts posttransfusion.CONCLUSION: These results demonstrate that storage in plasma at -80 °C effectively preserves platelet viability and functionality over a short period. This study highlights the potential for developing supplementary storage strategies as alternatives to conventional preservation methods, which could improve platelet availability in transfusion medicine.PMID:42254453 | PMC:PMC13241721 | DOI:10.1016/j.rpth.2026.106635

Food Sci Nutr. 2026 May 20;14(5):e71900. doi: 10.1002/fsn3.71900. eCollection 2026 May.ABSTRACTMiao Sour Soup (MSS) is a traditional fermented dish containing bioactive constituents such as lycopene, capsaicin, and short-chain fatty acids, which have been associated with anti-obesity, anti-inflammatory, and antioxidant effects. Excessively elevated hepatic gluconeogenesis is a critical element instigating energy metabolism dysregulation in the body. This research examined the extent to which MSS enhances energy metabolism abnormalities caused by a high-fat diet via hepatic gluconeogenesis and confirmed this route. The findings indicated that MSS intervention markedly decreased hepatic lipid accumulation, pro-inflammatory cytokine secretion, and blood lipid and glucose levels in rats subjected to a high-fat diet. Non-targeted metabolomics study revealed that MSS influences energy metabolism pathways, including glycolysis and gluconeogenesis. Subsequently, Western blot analysis was conducted to assess protein expression in the NF-κB inflammatory pathway and the PI3K/Akt/Foxo1 signaling pathway. The findings indicated that MSS decreased NF-κB expression in the livers of rats subjected to a high-fat diet, thereby activating the PI3K/Akt/Foxo1 signaling pathway and decreasing the expression of PEPCK and G6PC, essential proteins in gluconeogenesis. This study's results demonstrate that Foxo1 is a crucial protein in the dysregulation of glucose metabolism caused by lipid metabolism diseases. MSS may stimulate the PI3K/Akt/Foxo1 signaling pathway by mitigating chronic inflammation caused by a high-fat diet, therefore inhibiting excessive hepatic gluconeogenesis and ultimately improving insulin resistance.PMID:42254421 | PMC:PMC13238524 | DOI:10.1002/fsn3.71900

Ann Med Surg (Lond). 2026 Apr 27;88(6):3348-3359. doi: 10.1097/MS9.0000000000005027. eCollection 2026 Jun.ABSTRACTGastrointestinal (GI) disorders, affecting millions globally (approximately 1.5 billion people with IBS alone), impose a significant healthcare burden and remain challenging to diagnose and manage. Current approaches are often invasive or symptom based, highlighting an urgent need for more precise and personalized strategies. The gut microbiome may offer novel diagnostic biomarkers and therapeutic targets, potentially transforming patient care. It supports GI and systemic health via metabolism, immune modulation, and neurochemical signaling. The dysbiosis of the gut microbiota contributes significantly to the pathogenesis of various GI disorders, including inflammatory bowel disease (IBD), irritable bowel syndrome (IBS), colorectal cancer (CRC), and small intestinal bacterial overgrowth. This narrative review critically evaluates the diagnostic potential of microbiome profiling and its clinical applications in developing personalized therapeutic strategies. We examine cutting-edge techniques such as 16S rRNA sequencing, metagenomics, and metabolomics, and discuss how dietary modulation, precision probiotics, and fecal microbiota transplantation are being increasingly used to reshape gut microbial composition. However, it is critical to note that while microbiome alterations show consistent associations with GI diseases, current evidence remains largely observational and associative. To date, no microbiome-based test has achieved regulatory approval or clinical validation as a standalone diagnostic tool for IBD, IBS, or CRC, and therapeutic applications remain investigational with modest clinical benefits in select conditions. Additionally, we highlight the translational challenges of integrating microbiome-based diagnostics into mainstream clinical practice and propose future research imperatives. This review provides a balanced perspective on the promise and challenges of integrating microbiome-based approaches into clinical gastroenterology, while proposing actionable research priorities to guide future investigations toward clinically validated, patient-centered diagnostic, and therapeutic solutions.PMID:42254157 | PMC:PMC13236359 | DOI:10.1097/MS9.0000000000005027

Front Immunol. 2026 May 21;17:1776555. doi: 10.3389/fimmu.2026.1776555. eCollection 2026.ABSTRACTINTRODUCTION: Post-COVID Syndrome (PCS), or long-COVID, is a major public health burden, but its underlying mechanisms remain poorly understood. Because acute SARS-CoV-2 infection induces marked suppression of mitochondrial oxidative phosphorylation (OXPHOS), we investigated whether persistent immunometabolic remodeling is a recurring transcriptional, metabolic, and proteomic feature of PCS.METHODS: We performed an integrated multi-omics analysis of transcriptomic, proteomic, and metabolomic datasets across multiple tissues from Syrian hamster models and human cohorts spanning acute infection through post-acute and PCS stages extending up to 12 months post-infection.RESULTS: Across species and tissues, we observed overlapping signatures of mitochondrial dysfunction, including sustained suppression of OXPHOS, activation of mitochondrial stress responses, and enrichment of inflammatory pathways. Skeletal muscle exhibited the most pronounced and persistent mitochondrial repression in both hamsters and PCS patient biopsies, consistent with fatigue-associated phenotypes. Hamster heart and kidney tissues also showed persistent OXPHOS suppression, while lung tissue demonstrated prolonged inflammatory signaling despite partial metabolic recovery. In the nervous system, transcriptional profiles revealed region-specific patterns, including persistent cortical mitochondrial repression and partial recovery in sensory-associated regions. Peripheral blood mononuclear cells (PBMCs) transcriptomics and serum metabolic datasets suggested prolonged downregulation of OXPHOS-associated programs up to 12 months post-infection, potentially contributing to persistent immune dysregulation in susceptible individuals with underlying conditions. Longitudinal serum proteomics in PCS patients revealed sustained mitochondrial stress responses, increased oxidative stress signatures, and persistent immune activation at 1 and 6 months post-infection compared to recovered controls.DISCUSSION: Together, these multi-omics results identify persistent mitochondrial repression and immune dysregulation as recurring features across PCS-associated datasets, providing a framework linking bioenergetic dysfunction with chronic immune activation and supporting future mechanistic and therapeutic investigation.PMID:42253978 | PMC:PMC13234542 | DOI:10.3389/fimmu.2026.1776555

Front Immunol. 2026 May 22;17:1762013. doi: 10.3389/fimmu.2026.1762013. eCollection 2026.ABSTRACTEndometriosis (EMS) is a highly heterogeneous chronic gynecological disease characterized by pain, infertility, and relapse, with its etiology and pathogenesis not yet fully elucidated. Traditional theories, including "retrograde menstruation," "implantation theory," and "abnormalities in immune tolerance," struggle to adequately explain the complex lesion behavior, diverse phenotypic characteristics, and accompanying immune-metabolic disorders. In recent years, the key roles of imbalances in the gut and reproductive microbiomes, abnormal iron metabolism, and the newly proposed ferroptosis in the occurrence and development of EMS have gradually gained attention, suggesting that this disease may be a systemic condition involving the interplay of microbial ecology, iron metabolism, and cell death. Existing studies indicate that the gut-reproductive microbiome profoundly influences the body's iron homeostasis and iron load by regulating mucosal immunity, systemic inflammatory responses, and metabolic environments. This, in turn, activates the ferroptosis pathway through iron-dependent lipid peroxidation and cell membrane damage, participating in the formation, maintenance, and inflammatory microenvironment shaping of ectopic lesions. Based on these findings, this article systematically reviews the interactions between gut-reproductive microbiome imbalance and iron metabolism disorders, integrating multi-omics evidence such as microbiome analysis, metabolomics, and iron metabolism/ferroptosis-related molecular markers. It proposes a new pathological mechanism framework of "dysbiosis-iron overload-ferroptosis" incorporating microecological imbalance and ferroptosis into a unified picture of the pathogenesis of EMS. Furthermore, this article discusses potential therapeutic strategies and application prospects surrounding microbiome remodeling (such as probiotics, fecal microbiota transplantation, dietary and lifestyle interventions) and pharmacological targeting of key ferroptosis-related molecules. Through a comprehensive and critical analysis of existing evidence, this review aims to provide a more systematic theoretical framework for the mechanistic research of EMS and offer ideas and directions for future clinical translation of precise classification, individualized intervention, and novel treatment plans.PMID:42253950 | PMC:PMC13236934 | DOI:10.3389/fimmu.2026.1762013

MedComm (2020). 2026 May 31;7(6):e70795. doi: 10.1002/mco2.70795. eCollection 2026 Jun.ABSTRACTLiver failure remains a life-threatening syndrome where the available therapeutic options are extremely limited beyond transplantation. This study addresses critical cell source and mechanistic challenges by developing a novel bioartificial liver (BAL) system. We utilized CRISPR/Cas9 technology to knockout the GGTA1 gene in primary porcine hepatocytes to reduce immunogenicity. These hepatocytes were co-cultured with R-spondin1-overexpressing human umbilical vein endothelial cells (R-HUVECs) to form functionally stable liver organoids. In ex vivo study using plasma from patients with acute-on-chronic liver failure (ACLF), the BAL system demonstrated superior detoxification, significantly reducing ammonia and bilirubin levels compared to traditional non-bioartificial liver (NAL) support. Multi-omics analyses revealed that BAL treatment actively restored metabolic homeostasis by promoting branched-chain amino acid (BCAA) metabolism and upregulating lysophosphatidylcholine (LPC) species associated with membrane repair and anti-inflammatory signaling. Significantly, this research demonstrates that unlike the passive physical filtration of NAL, BAL serves as an active biological regulator of systemic metabolism. These findings provide a robust theoretical and practical foundation for the clinical translation of BAL technology, offering a promising strategy to improve outcomes for liver failure patients by modulating systemic metabolism.PMID:42253938 | PMC:PMC13239287 | DOI:10.1002/mco2.70795

Front Nutr. 2026 May 21;13:1769202. doi: 10.3389/fnut.2026.1769202. eCollection 2026.ABSTRACTThe management of pediatric pulmonary diseases is increasingly evolving from conventional respiratory and physical interventions toward integrated strategies that incorporate nutritional and immunomodulatory approaches. Childhood represents a critical window for immune system development and maturation, during which nutritional status profoundly influences immune responses, inflammatory processes, and tissue repair-largely mediated through the gut-lung axis and multiple molecular pathways. This review comprehensively reviews the immunomodulatory roles of key nutrients-including vitamin D, ω-3 polyunsaturated fatty acids, prebiotics/probiotics, and branched-chain amino acids-in supporting lung rehabilitation in children. It elaborates on how these nutrients modulate innate and adaptive immunity, influence key inflammatory markers such as TNF-α and IL-6, and optimize the microecological milieu, thereby facilitating pulmonary function recovery, enhancing exercise tolerance and respiratory muscle strength, and reducing the risk of recurrent infections. Although compelling mechanistic insights have been provided by preclinical studies and some adult clinical trials, high-quality randomized controlled trials in pediatric populations remain limited. Moreover, existing evidence exhibits considerable heterogeneity in terms of intervention dosage, formulation, and individual responsiveness. Future research should prioritize well-designed, multicenter trials on precision nutrition interventions for children, incorporating advanced tools such as nanotechnology, metabolomics, and digital health technologies to establish standardized and personalized immunonutritional frameworks for pediatric pulmonary rehabilitation.PMID:42253744 | PMC:PMC13233704 | DOI:10.3389/fnut.2026.1769202

Hum Mutat. 2026 May 31;2026:1645398. doi: 10.1155/humu/1645398. eCollection 2026.ABSTRACTPain is a heterogeneous clinical condition characterized by substantial interindividual variability in symptom severity and treatment response. Acupuncture has been widely used for the management of various pain disorders, including chronic musculoskeletal pain, migraine, and cancer-related pain. However, clinical outcomes remain highly variable across patients, suggesting that average treatment effects may not fully capture biologically and clinically meaningful response heterogeneity. Recent advances in human genetics and multiomics technologies have provided new opportunities to investigate the biological factors that may contribute to this variability. Current genetic evidence, derived mainly from candidate-gene studies, suggests that polymorphisms involved in pain perception and neuromodulatory pathways, including COMT and OPRM1, may influence individual sensitivity to acupuncture analgesia; however, these findings remain exploratory and require validation in larger and more diverse cohorts. In parallel, transcriptomic, epigenetic, proteomic, metabolomic, and inflammatory profiling studies have identified molecular changes associated with acupuncture treatment. These treatment-associated signals should be distinguished from predictive biomarkers: Baseline genetic or molecular features may help estimate the likelihood of response, whereas posttreatment molecular alterations more often reflect treatment engagement, biological adaptation, or downstream mechanistic effects. Although the available evidence remains fragmented and is often limited by small sample sizes, heterogeneous acupuncture protocols, variable analytical pipelines, and insufficient external validation, it provides a useful foundation for developing biomarker-informed approaches to acupuncture research. In this review, we summarize current evidence linking host genetic variability and omics-derived molecular signatures to acupuncture analgesia, clarify the conceptual distinction between predictive and treatment-associated biomarkers, and discuss the potential and limitations of response-stratified acupuncture. We further highlight key priorities for the field, including standardized treatment protocols, multicenter cohorts, prospective biospecimen collection, reproducible omics workflows, and external validation of prediction models. Together, these considerations support precision acupuncture as an emerging research framework for understanding and eventually improving individualized pain management, rather than as a currently established clinical strategy.PMID:42253505 | PMC:PMC13240497 | DOI:10.1155/humu/1645398

Aesthet Surg J Open Forum. 2026 May 14;8:ojag088. doi: 10.1093/asjof/ojag088. eCollection 2026.ABSTRACTThe prevailing paradigm in aesthetic medicine is the "antiaging" model, which focuses on correcting and/or reversing visible signs of aging. However, contemporary geroscience reconceptualizes aging as a malleable biological process driven by defined hallmarks, offering an opportunity to align aesthetic practice with the fundamental aging biology. This article explores the concept of "pro-aging" or "longevity aesthetics," a framework that prioritizes tissue function, resilience, and biological integrity alongside phenotypic improvement. The skin is presented as an accessible model organ that reflects key hallmarks of aging and their clinical manifestations. Although conventional aesthetic interventions effectively address structural changes, they often do not target upstream biological drivers of tissue aging. Within this framework, certain surgical and nonsurgical modalities may theoretically support tissue resilience through modulation of inflammation, collagen remodeling, and microvascular health. Importantly, some of these strategies, such as biostimulatory injectables including calcium hydroxylapatite and poly-L-lactic acid, as well as combination treatment approaches, are already integrated into clinical practice, whereas others remain in the translational or research domain. Emerging concepts such as multi-omics, defined as the integration of genomics, transcriptomics, proteomics, metabolomics, and epigenomics, may further enable personalized and predictive approaches in the future. Longevity aesthetics, therefore, represents a conceptual evolution from correction to functional preservation. However, direct clinical evidence supporting its biological impact remains limited, and these concepts should currently be interpreted as hypothesis driven. Advancing this framework will require prospective studies integrating biomarkers with long-term clinical outcomes. Ultimately, this approach positions aesthetic medicine to contribute to translational geroscience, provided innovation is guided by methodological rigor and ethical transparency. Level of Evidence: 5 (Therapeutic).PMID:42253424 | PMC:PMC13240679 | DOI:10.1093/asjof/ojag088