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PubMed2026

Multi-omics panorama of glaucoma: Pathogenesis, biomarkers, and novel therapeutic strategies.

Glaucoma is a group of irreversible, blinding eye diseases characterized by progressive loss of retinal ganglion cells, leading to gradual visual field defects that severely impact patients' quality of life. Its complex pathophysiological mechanisms remain incompletely understood, limiting the development of early diagnostic and effective therapeutic strategies. Advances in omics technologies have provided new insights into elucidating the pathophysiology of glaucoma. We summarize specific alterations in genomics, transcriptomics, proteomics, metabolomics, epigenomics, and microbiomics associated with glaucoma. We emphasize the systematic analysis of disease mechanisms, identification of clinically applicable biomarkers, and discovery of novel therapeutic targets through the integration of these data. This approach paves new pathways for glaucoma subtype diagnosis and personalized treatment, while also outlining future research directions and challenges.

Humans↗
PubMed2026

Stage-specific ROMO1 in rheumatoid arthritis: predictive immune insights into the MIF pathway and HLA-DR/IL2RA axis via integrated GWAS, transcriptomic, single-cell, and spatial profiling.

Emerging evidence links reactive oxygen species modulator 1 (ROMO1), a key mitochondrial ROS regulator, to rheumatoid arthritis (RA) pathogenesis. However, its exact mechanism remains elusive given the conflicting evidence about its specific function. We used a four-level integrative framework combining multi-omics data and literature‑supported mechanistic inference. At the genetic level, Mendelian randomization (MR) was performed to explore potential causal relationships between ROMO1, IL2RA, HLA-DR, MIF, and RA risk, followed by differential expression analysis and machine learning-based feature selection to identify key mROS genes. The temporal expression dynamics of ROMO1 were assessed in RA progression. At the cellular and tissue levels, we integrated single-cell RNA sequencing and spatial transcriptomics to map cell-type-specific expression and synovial localization of ROMO1-related immune cells and pathways. Finally, our multi-omics findings were contextualized with literature-supported mechanistic inference. (1) MR results were consistent with a potential protective effect of ROMO1 on RA (OR = 0.52) and its potential regulation of risk factors IL2RA (OR = 0.46) and HLA-DR (OR = 0.40). Conversely, IL2RA (OR = 1.42), HLA-DR (OR = 1.88), and MIF (OR = 1.17) were positively associated with RA risk. Additionally, ROMO1 was identified as a top candidate diagnostic predictor with stage-specific dynamics: downregulated in the early but upregulated in the late/remission stages. (2) Single-cell RNA sequencing showed ROMO1's cell-specific expression in CD14+ HLA-DR+ CD74+ monocytes and CD4+ IL2RA+ T cells. Cell communication analysis further suggested that these cells may participate in MIF pathway regulation. Spatial transcriptomics subsequently identified that ROMO1-related cells localized to synovial pathological regions, with MIF pathway changes correlated with RA progression. (3) Finally, literature-supported mechanistic inference suggests that ROMO1 may modulate mROS levels to promote anti-inflammatory M2 macrophage polarization, which could theoretically contribute to reduced systemic inflammation and the alleviation of multi-organ decline in RA. This integrated multi-omics investigation, supported by literature-based mechanistic inference, suggests ROMO1 as a stage-dependent biomarker candidate and potential immune regulator in RA.

Humans↗
PubMed2026

Norgestrel drives mitochondrial collapse and plasma membrane impairment in Pacific oyster (Crassostrea gigas) sperm by triggering premature acrosome reaction.

The toxic mechanisms of norgestrel (NGT), an emerging marine pollutant, on the sperm from externally fertilized invertebrates remain elusive. This study employed an integrated physiological and multi-omics framework to elucidate how NGT (10 and 1000 ng/L) disrupts acrosome reaction (AR) signaling machinery, thereby impairing the functional integrity of Pacific oyster (Crassostrea gigas, also known as Magallana gigas) sperm. Exposure to NGT triggered a significant, dose-dependent premature AR, characterized by elevated acrosin activity and a loss of acrosomal integrity. Multi-omics integration supports a model in which this premature exocytosis is linked to signaling disturbances, including disruption of calcium signaling and reduced transcript abundance of calmodulin (CaM) and the primary recognition protein zonadhesin (Zan). This signaling interference induced an premature AR, subsequently driving a cascade of bioenergetic and structural failures. At the mitochondrial level, NGT induced abnormal mitochondrial permeability transition pore (mPTP) opening and elevated the transcript levels of antioxidant defense genes (e.g., peroxiredoxin-5, PRDX5). These alterations indicate the occurrence of mitochondrial collapse. Concurrently, scanning electron microscopy verified localized plasma membrane wrinkling and pore formation in sperm. In addition, NGT exposure decreased the transcript abundance of cytoskeleton-related genes, including solute carrier family 26 member 6 (SLC26A6), actin (ACT), and tubulin polymerization promoting protein family member 3 (TPPP3). These molecular changes further disrupted membrane phospholipid homeostasis, as represented by altered glycerophospholipid metabolism. At the same time, cumulative cellular stress was associated with decreased transcript abundance of cytoprotective factors (e.g., baculoviral IAP repeat-containing proteins, birc2) and changes in apoptosis-related genes consistent with activation of a caspase-8-mediated apoptotic programme. In conclusion, NGT, as a representative synthetic progestin, exerts reproductive toxicity by interfering with signaling mediators to induce premature AR, which subsequently exhausts metabolic energy and triggers plasma membrane impairment. These findings provide a critical mechanistic basis for the aquatic ecological risk assessment of synthetic progestins.

Animals↗
PubMed2026

Molecular Landscape and Advanced Diagnostic Technologies for BRAF Mutations in Cancer: From Quantitative PCR and ddPCR to CRISPR-Based Platforms.

BRAF mutations are key oncogenic alterations across multiple malignancies, including melanoma, thyroid carcinoma, colorectal cancer, non-small cell lung cancer, glioma, and hairy cell leukemia. The most prevalent variant, BRAF-V600E, induces constitutive activation of the MAPK signaling pathway, promoting tumor progression and influencing therapeutic responsiveness. Accurate detection of BRAF alterations is therefore essential for molecular classification, prognostic assessment, treatment selection, and resistance surveillance. This review summarizes the molecular heterogeneity of BRAF mutations and critically evaluates current diagnostic methodologies. Conventional approaches such as allele-specific PCR and Sanger sequencing are compared with advanced quantitative platforms, including high-resolution melting analysis, droplet digital PCR, and next-generation sequencing, with emphasis on analytical sensitivity, mutation coverage, and clinical applicability. Emerging technologies such as CRISPR-based assays, rolling circle amplification systems, and nanoparticle-based biosensors and point-of-care diagnostic platforms are also discussed for their potential to enhance ultra-sensitive detection, particularly in liquid biopsy settings. These emerging tools are highlighted for their potential to enable ultra-sensitive, rapid, and decentralized mutation detection, particularly in liquid biopsy settings. Key challenges, including intratumoral heterogeneity, low allele-frequency variants, FFPE-associated artifacts, and clonal evolution under therapeutic pressure, are examined within a translational framework. In addition, we examine critical barriers to clinical implementation, including standardization, cost, and global accessibility of molecular diagnostics, and outline potential solutions through scalable technologies and decentralized testing strategies. We propose that optimal BRAF testing requires a mutation subclass-informed and clinically integrated strategy combining comprehensive baseline profiling with longitudinal molecular monitoring. Future diagnostic paradigms will likely integrate multi-omics data and artificial intelligence (AI)-assisted interpretation to refine precision oncology implementation. Looking forward, we propose that optimal BRAF testing will require integration of multi-omics profiling with AI-assisted interpretation, enabling automated variant classification, real-time clinical decision support, and improved prediction of therapeutic response and resistance.

Humans↗
PubMed2026

BIOCARD framework: integrating fecal bile acids, lipids, and metabolites to assess response to a cardiovascular health intervention.

Cardiovascular disease (CVD) remains a leading cause of morbidity and mortality, particularly in under-resourced populations. Although nutritional interventions are important for CVD prevention, their outcomes are commonly evaluated using conventional clinical and behavioral indicators, which may not fully capture early molecular responses. In this study, we developed the BIOCARD framework, an exploratory fecal multi-omics platform integrating bile acids, lipids, and metabolites to evaluate intervention outcomes related to cardiovascular health. Fecal samples were collected from caregiver-child participants enrolled in a 10-week randomized controlled trial comparing a multicomponent garden-based intervention (SHA) with an education-only control group (MSP). Fecal polar metabolites, lipids, and bile acids were analyzed by UHPLC-HRMS-based approaches and integrated with conventional health indicators. Traditional clinical indicators in the present study showed limited sensitivity for detecting intervention-related differences. In contrast, fecal multi-omics analyzes revealed intervention-associated differences in metabolites, lipids, and bile acids, with children showing more apparent molecular variation than parents. Network analysis further revealed associations between selected molecular features and cardiovascular-related indicators, including blood pressure, body fat, skin carotenoids, and Healthy Eating Index scores. Together, these findings suggest that the BIOCARD framework may serve as an exploratory molecular approach to complement traditional outcome measures and improve the evaluation of nutritional interventions for cardiovascular health.

Humans↗
PubMed2026

ORBIT: Oncogenic Representation Learning via Bi-Prototype Contrastive Learning in Hyperbolic Space for cancer driver gene identification.

Accurate identification of cancer driver genes is crucial for precision oncology but remains challenging due to the complexity of integrating heterogeneous data and modeling dynamic biological systems. To address these limitations, we propose ORBIT (Oncogenic Representation Learning via Bi-Prototype Contrastive Learning in Hyperbolic Space). Our framework synergistically fuses multi-omics profiles with functional network data using a context-adaptive graph reweighting mechanism to capture cancer-specific dynamics. The model employs a bi-prototype contrastive learning strategy within hyperbolic space, which aligns gene representations around distinct driver and non-driver semantic anchors while preserving the intrinsic hierarchy of biological networks. Comprehensive evaluations demonstrate that ORBIT achieves highly competitive stability in pan-cancer analysis while consistently outperforming state-of-the-art methods in cancer-specific predictions. Furthermore, functional enrichment analysis confirms that the model effectively segregates core cancer pathways, and drug sensitivity profiling validates the clinical relevance of the identified drivers. By integrating hyperbolic geometry with context-adaptive learning, ORBIT offers a robust and interpretable paradigm for precision medicine. The source codes and datasets are publicly accessible at https://github.com/spcho-dev/ORBIT.

Humans↗
PubMed2026

3D epigenomic remodelling mediated by Foxa1 drives gemcitabine resistance in pancreatic cancer.

Gemcitabine remains a cornerstone treatment for pancreatic ductal adenocarcinoma (PDAC), yet the emergence of resistance constitutes a major clinical challenge with poorly understood epigenomic mechanisms. Here, we identified the pioneer transcription factor Foxa1 as a master regulator of gemcitabine resistance through multi-omics analysis. Mechanistically, Foxa1 drives widespread super-enhancer (SE) reprogramming and 3D genome remodelling in resistant cells, which coordinately activates the expression of key resistance genes, notably Rrm1 and Cdadc1. This is accompanied by increased chromatin accessibility, elevated H3K27ac enrichment at SEs, and enhanced Foxa1 binding at regulatory elements. Moreover, post-translational stabilization of Foxa1 via USP7-mediated deubiquitination sustains this epigenomic program. Genetic ablation of Foxa1 or specific SE regions near Rrm1 resensitizes resistant cells to gemcitabine. Building upon this mechanism, we demonstrate that bromodomain and extraterminal (BET) inhibitors, which disrupt SE function, potently reverse resistance. Notably, the clinical-stage BET inhibitor AZD5153, in combination with gemcitabine, achieves robust tumor suppression and overcomes resistance in cell-derived xenograft (CDX) models by dismantling the Foxa1-mediated resistant transcriptome and reinvigorating drug sensitivity. Our findings establish Foxa1-orchestrated enhancer reprogramming as a fundamental mechanism of gemcitabine resistance and unveil a promising epigenetic therapy to restore treatment efficacy in PDAC.

Hepatocyte Nuclear Factor 3-alpha↗
PubMed2026

Integrative genomic and transcriptomic analyses identify key regulators of skin pigmentation in Larimichthys crocea.

The yellow body coloration of large yellow croaker (Larimichthys crocea) constitutes a crucial economic trait, yet its underlying genetic regulatory mechanisms remain poorly understood. This study systematically elucidated the molecular basis of body color variation by integrating genome resequencing and skin transcriptome analyses, combined with the contextual analysis of key pigmentation-related genes and phenotypic histological validation. 200 phenotyped individuals (including yellow-selected lines, F1 progeny, and normal control groups, all derived from a well-characterized aquaculture stock) identified 39 significantly associated SNPs (-log₁₀(P) ≥ 6), mapping to multiple candidate genes. These genes were significantly enriched in pathways related to pigment deposition (GO:0033059), melanosome organization (GO:0032438), melanogenesis, and tyrosine metabolism. Cross-developmental stage transcriptome analysis revealed 2395 differentially expressed genes (DEGs). Multi-omics integration identified eight overlapping candidate genes, including tyrp1, slc45a2, oca2, and dgat2, among which tyrp1 was prioritized for in-depth validation based on its core regulatory role in eumelanin synthesis, significant SNP association signal, and consistent downregulation in transcriptomic data. Experimental validation demonstrated that the g.895C > T mutation in exon 2 of tyrp1b was strongly significantly associated with the yellow phenotype: the frequency of mutant genotypes (TT/CT) reached 92.86%in the yellow-selected group, whereas the control group exclusively exhibited the wild-type genotype (CC). qPCR confirmed significantly downregulated tyrp1b expression in the skin of yellow individuals, consistent with the transcriptome trend. Histological and stereomicroscopic observations of skin tissues further validated the physiological basis of the yellow phenotype, revealing a significant reduction in melanophore number and abnormal melanosome morphology in yellow-phenotype individuals, accompanied by increased xanthophore density. These results suggest that tyrp1b mutation is strongly associated with the yellow phenotype. However, the presence of a wild-type CC individual in the yellow group indicates that this mutation is not strictly required for yellow coloration, suggesting that other genetic or environmental factors may also contribute to the phenotype, Additionally, downregulation of the carotenoid metabolism gene bco2 coupled with upregulation of xdh, together with the functional changes of slc45a2 and oca2, may synergistically promote xanthophore pigment deposition, contributing to the yellow phenotype. As melanin synthesis in large yellow croaker relies on the conserved tyrosinase pathway and transporter proteins, mutations in associated genes (tyrp1b, slc45a2, oca2) represent a primary underlying cause for the loss of melanin-based coloration and transition to a yellow phenotype in L. crocea. These findings provide key molecular targets and a theoretical foundation for molecular breeding of body color in this species, and also enrich the understanding of xanthism regulatory mechanisms in teleosts.

Animals↗
PubMed2026

Integrated transcriptomic and metabolomic analysis of fluoride tolerance-related pathways and differentially expressed genes in silkworm strain XSKD.

XueSong KD (XSKD) silkworm strain exhibits prominent fluoride tolerance, yet the underlying molecular mechanisms of fluoride tolerance remains unclear. In the present study, fourth-instar pre-molting XSKD silkworms were used as experimental materials for integrated transcriptomic and untargeted metabolomic analyses. In total, 572 differentially expressed genes and 90 differential metabolites were screened. GO enrichment and KEGG enrichment based on the hypergeometric distribution model revealed that 13-Hydroxy-9Z,11E-octadecadienoic acid (13-(S)-HODE) acts as the core differential metabolite, which is significantly enriched in the linoleic acid metabolism pathway. Within this pathway, LOC101737302 and CYP338A1 display opposite expression trends and show correlations with pathway metabolites. Based on multi-omics data, this study preliminarily characterizes the lipid metabolic response under fluoride stress, providing omics dataset support for further in-depth exploration of the molecular mechanism of fluoride tolerance in silkworms.

Animals↗
PubMed2026

Clinicopathological response and survival outcomes of HER2-low versus HER2-zero early breast Cancer: A systematic review and Meta-analysis.

BACKGROUND: Breast cancer is the most common malignant tumor in women. Human epidermal growth factor receptor 2 (HER2) is a key biomarker for classification and treatment. A subgroup with HER2-low expression has been identified, but existing evidence is heterogeneous. This systematic review and meta-analysis compared pathological response and survival outcomes between HER2-low and HER2-zero early-stage breast cancer to clarify prognostic features. METHODS: This study followed PRISMA guidelines and was registered in PROSPERO (CRD420251120506). PubMed, Embase, Web of Science, ClinicalTrials.gov, and major oncology conferences were searched through September 2025. Cohort studies of early-stage breast cancer comparing HER2-low (IHC 1+/2+ and ISH-negative) vs. HER2-zero with extractable pCR, DFS, or OS data were included. Studies involving HER2-positive patients or inconsistent definitions were excluded. Meta-analyses were performed using RevMan 5.3. RESULTS: Twenty-eight studies involving 115,182 patients were included. HER2-low patients showed significantly lower pCR rates (OR = 0.58, 95% CI: 0.52-0.65). DFS favored HER2-low (multivariate HR = 0.75, 95% CI: 0.69-0.83), especially in HR+ tumors, with a weaker effect in HR- cases. OS also favored HER2-low (HR = 0.80, 95% CI: 0.72-0.89), mainly driven by the HR- subgroup; no OS difference was seen in HR+ tumors. Sensitivity analyses and funnel plots indicated robust results with no apparent publication bias. Overall study quality was high (17 high-quality, 11 moderate-quality). CONCLUSION: HER2-low early breast cancer shows lower pCR after neoadjuvant therapy but better long-term survival. These findings support the clinical relevance of HER2-low as a biologically meaningful subgroup within HER2-negative disease, while its status as a stable and independent subtype still requires further validation through prospective studies, standardized testing, and multi-omics investigation.

Humans↗
PubMed2026

Mechanistic insights into flavor deterioration in bitter sturgeon caviar: Evidence from lipidomics and metagenomics.

This study systematically compared the flavor and multi-omics differences between normal caviar and bitter caviar based on quantitative descriptive analysis (QDA), volatile compounds (VOCs) analysis, untargeted lipidomics, and metagenomics. The results showed that bitter caviar was characterized not only by increased bitterness, but also by decreased positive sensory attributes, including buttery, nutty, and marine fresh. VOCs analysis indicated that the volatile profile of bitter caviar was reorganized. Compounds such as 3-hydroxy-2-butanone, 1-octen-3-ol, and (E, Z)-2,6-nonadienal showed higher relative odor activity values (rOAVs); however, these changes did not improve its overall sensory experience. Untargeted lipidomics identified 492 differential lipids. These changes were mainly characterized by decreased PC and increased DG and LPC in bitter caviar. KEGG pathways analysis showed that these differential lipids were mainly associated with glycerophospholipid metabolism, choline metabolism in cancer, and retrograde endocannabinoid signaling. Metagenomic analysis showed that bacteria dominated the microbial community of caviar. Among them, Bacillus and Micromonospora showed relatively high abundance in the caviar microbiota. They were also closely associated with lipid metabolic changes involving PC, DG, and LPC, suggesting their potential as candidate targets for future microbiota-directed regulation of caviar quality. These findings provide new insights into the mechanisms underlying sensory deterioration and flavor formation in bitter caviar, and offer a theoretical basis for improving caviar quality in industrial production.

Animals↗
PubMed2026

Integrated salivary proteomic and metabolomic analyses reveal molecular characterization and novel biomarker panels of chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD) is a respiratory disorder characterized by chronic inflammation, oxidative stress, and metabolic dysregulation. The lack of convenient and easily-accessible non-invasive diagnostic approaches remains a major clinical challenge. This study applied an integrated saliva-based proteomic and untargeted metabolomic strategy to identify potential biomarkers for COPD classification. Comprehensive multi-omics analyses identified 225 differentially abundant proteins and 60 differentially abundant metabolites between patients with COPD and healthy controls, including 24 biologically relevant endogenous metabolites. Functional enrichment analyses revealed pronounced dysregulation of mitochondrial energy metabolism, redox homeostasis, lipid remodeling, and inflammatory-related pathways in COPD. By integrating salivary proteomic and metabolomic biomarkers, a stepwise feature selection combined with LASSO logistic regression was used to construct diagnostic models, yielding an optimized biomarker panel consisting of 11 proteins and 2 endogenous metabolites. This integrated model achieved excellent diagnostic performance, with an area under the ROC curve of 0.96. Collectively, these findings demonstrate that integrated salivary proteomic and metabolomic profiling provides a robust, non-invasive approach for COPD classification and offers a promising foundation for the development of biosensor-based diagnostic platforms and early disease detection. SIGNIFICANCE: Chronic obstructive pulmonary disease (COPD) remains a major global health burden. Current diagnostic approaches rely largely on spirometry and clinical assessment, which are limited in sensitivity for early-stage disease and unsuitable for large-scale screening. This study employs an integrated saliva-based proteomic and metabolomic strategy to identify non-invasive biomarkers for COPD classification. Our findings reveal coordinated dysregulation of mitochondrial energy metabolism, redox homeostasis, and lipid remodeling in COPD, highlighting the interconnected roles of metabolic reprogramming, oxidative stress, and inflammation in disease pathophysiology. Notably, a robust diagnostic panel comprising 11 proteins and 2 endogenous metabolites was established, achieving excellent classification performance (AUC of 0.96). To our knowledge, the integrated application of salivary proteomics and metabolomics for COPD diagnosis remains largely unexplored, underscoring the significance and translational potential of our findings.

Humans↗
PubMed2026

Single-organ proteomics in Drosophila melanogaster larva.

The combination of genetic accessibility, organ complexity, evolutionary conservation, and cost-efficiency makes Drosophila melanogaster (Dm) a well-known model system for biomedical and fundamental biological research. Proteomic analysis of single organs enables the identification and quantification of proteins expressed in specific organs. This will help to uncover specific biological functions and unique protein profiles that are not detectable in whole-organism analyses. In this study we have isolated single organs form Dm larvae, and we have performed a deep proteomics mapping by following a minimal manipulation preparation procedure. The combined dataset across all organs comprised 9132 identified proteins. As anticipated, principal component analysis (PCA) revealed clear separation between the proteomes of most organs, confirming distinct protein profiles. These findings demonstrate the applicability of the sample preparation strategy for high-resolution proteomic characterization of individual organs in Drosophila. Given the extensive genetic tools available for this model organism, our approach has the potential to open new avenues for proteomic studies in Drosophila melanogaster and any other biological systems where the sample amount is limiting. SIGNIFICANCE STATEMENT: Drosophila melanogaster is a well-known model system for biomedical and fundamental biological research that serves as a valuable in vivo model organism due to its high degree of evolutionary conservation with higher vertebrates, tractable genetics, and logistical efficiency. However, the proteome of Drosophila at single organ level has been elusive to date, due to several factors like low sensitivity of previous generation mass spectrometers and sample preparation procedures, difficult isolation of some organs. In this study we have applied a compilation of advanced methods including minimal sample manipulation together with simple, straightforward and efficient protein extraction and digestion methods. Obtained peptides were minimally handled to be analyzed by applying specific and sensitive nLC methods coupled on-line to state-of-the-art MS/MS system. Altogether, the applied strategy allowed us to get the first single organ study to date for this animal. These datasets represent a significative resource for future genomic, transcriptomic and proteomic studies in Drosophila, as multi-omic integration requires deep proteomics to translate data into functional biochemistry, and serves as a critical bridge and an indispensable standalone resource across the genomic, transcriptomic, and proteomic landscapes.

Animals↗
PubMed2026

Phytolacca acinosa Roxb. induces intestinal toxicity through the histamine-MLCK-tight junction axis: Integrated evidence from proteomics, metabolomics, intestinal organoids and epithelial barrier validation.

Phytolacca acinosa Roxb. (PR) is a saponin-rich medicinal plant associated with gastrointestinal toxicity, but the mechanisms underlying PR-induced intestinal barrier injury remain unclear. In this study, raw PR extract was analytically characterized by UPLC-ZenoTOF-MS/MS, confirming triterpenoid saponins as the predominant constituents. C57BL/6 J mice were orally exposed to characterized PR extract (1.20 or 12.0 g/kg for 5 h), and Caco-2 cells and mouse intestinal organoids were used to assess epithelial toxicity and barrier disruption. Histopathology, ELISA, FITC-dextran permeability assays, immunofluorescence, CCK-8, LDH release, western blotting, DIA-based proteomics and untargeted metabolomics were integrated to define toxicological mechanisms. PR induced dose-dependent intestinal inflammation and barrier dysfunction, with the ileum as the most sensitive target. PR increased serum DAO and D-lactate and intestinal TNF-α and IL-1β, disrupted organoid morphology, enhanced epithelial permeability, and reduced ZO-1 expression. Proteomics revealed changes in inflammatory, lipid-metabolic, cytoskeletal and tight-junction pathways, including upregulation of MLCK3 and phospholipase-related proteins and downregulation of ZO-1 and ZO-2. Metabolomics identified histidine metabolism disturbance and histamine accumulation. Integrated multi-omics and pharmacological validation indicated that histamine activated the PLC/IP₃/Ca²⁺/CaM/MLCK cascade, promoting MLC phosphorylation, tight-junction disassembly and epithelial leakiness. MLCK inhibition partially restored ZO-1/ZO-2 expression and attenuated PR-induced epithelial injury. These findings identify the histamine-MLCK-tight junction axis as a key mechanism of PR-induced intestinal toxicity and support hazard identification of saponin-rich PR exposure.

Animals↗
PubMed2026

Can host genetics transform the sustainable control of tropical theileriosis? Insights from the Tick-Theileria interface.

Tropical theileriosis, caused by the tick-transmitted apicomplexan parasite Theileria annulata, remains a major constraint on cattle production across North Africa, the Mediterranean basin, the Middle East and South Asia. Current control depends on acaricides, the theilericidal drug buparvaquone and live attenuated schizont vaccines, but acaricide resistance, buparvaquone-resistance mutations and the logistical demands of vaccination are eroding the sustainability of these tools. Host genetics offers a complementary and durable alternative. Indigenous Bos indicus breeds are consistently more resistant to ticks and tolerate T. annulata infection better than exotic Bos taurus cattle, and this advantage has a measurable heritable component. Unlike previous reviews, which treat tick resistance, T. annulata immunobiology and livestock genomic selection as separate subjects, we integrate all three and assess host genetics specifically against the failure modes of current control. We review the tick, parasite and host interface, the evidence for natural resistance, and the genetic and immunological mechanisms involved, including signal-regulatory protein, bovine major histocompatibility complex class II and inflammatory pathway genes. We then assess whether genomic selection, multi-omics, machine learning and gene editing can translate these mechanisms into resistant cattle, and we weigh the biological, economic and infrastructural barriers to implementation. The evidence indicates that host genetics will not replace existing control but could reduce reliance on acaricides and chemotherapy. That contribution remains prospective rather than demonstrated: no resistance marker for T. annulata has yet been validated, prediction accuracies are moderate and transfer poorly between breeds, and no endemic production system has implemented selection for resistance.

Animals↗
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

New Evidence in Heart Failure: 2026 Update.

Heart failure (HF) remains a major cause of morbidity, mortality, impaired quality of life and healthcare expenditure worldwide. The global burden of HF continues to increase due to population aging, improved survival, and the growing prevalence of cardiovascular, renal, and metabolic comorbidities. Simultaneously, the pace of scientific progress in HF has accelerated considerably. Recent advances have refined our understanding of HF epidemiology, prognosis, and disease trajectories, including emerging concepts of HF improvement, remission, and recovery. The Second Universal Definition of HF has also updated the classification framework, moving beyond the traditional ejection fraction-based categories. HF is now broadly classified into two major phenotypes: heart failure with reduced ejection fraction (HFrEF) and heart failure with preserved ejection fraction (HFpEF). Novel mechanistic insights highlight the role of inflammation, immune activation, metabolic dysfunction, mitochondrial biology, and multisystem interactions in HF progression. There has also been significant progress in the characterization and management of major comorbidities, including chronic kidney disease (CKD), diabetes, obesity, atrial fibrillation (AF), pulmonary hypertension, frailty, malnutrition, and cancer. Diagnostic innovations include novel biomarkers, multi-omics technologies, artificial intelligence-based approaches, advanced imaging techniques, congestion assessment tools, and emerging digital health solutions. Important advances have occurred in specific HF aetiologies, including cardiomyopathies, cardiac amyloidosis (CA), myocarditis, arrhythmia-induced cardiomyopathy (AiCM), and Chagas cardiomyopathy. Therapeutic developments continue to reshape HF management across the spectrum of left ventricular ejection fraction. Recent evidence has focused on optimization of guideline-directed medical therapy in HFrEF, expansion of evidence-based therapies in HFpEF, and growing roles for sodium-glucose cotransporter-2 inhibitors, finerenone, incretin-based therapies, and transcatheter valve interventions. Collectively, these advances support the transition from a predominantly phenotype-based approach towards a more personalized and biologically informed model of HF care, with the potential to further improve outcomes across the entire HF spectrum.

Journal Article↗
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↗