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PubMed2026

Integrated multi-omics analyses identify an RAS-SLC11A2-associated molecular framework linking iron metabolism with PCOS-related cardiometabolic risk.

INTRODUCTION: PCOS is a common endocrine disorder with elevated cardiometabolic risk, yet the role of the renin-angiotensin system (RAS)-iron metabolism axis in this comorbidity remains unclear. We explored its underlying mechanisms and evaluated the therapeutic potential of gentiopicroside. METHODS: Integrated multi-omics analyses combining transcriptomics, single-cell RNA sequencing, Mendelian randomization, machine learning, molecular docking, and in vitro functional assays were performed to identify shared molecular pathways and therapeutic targets across PCOS, hypertension, NAFLD, and T2DM. RESULTS: SLC11A2 was consistently dysregulated in PCOS transcriptomic datasets, and associated with iron metabolism, inflammatory response and oxidative stress pathways. Genetic analyses validated RAS-related regulation in hypertension susceptibility and revealed shared genetic architecture between PCOS and cardiometabolic traits. Network and single-cell analyses characterized SLC11A2-associated molecular patterns in disease-relevant cell types; machine learning identified disease-classifying molecular signatures. Gentiopicroside alleviated inflammatory and oxidative stress phenotypes, including reduced IL-6 expression and reactive oxygen species accumulation. CONCLUSION: This study defines an RAS-SLC11A2 molecular framework linking iron metabolism dysregulation to PCOS-related cardiometabolic risk, elucidating the mechanisms connecting ovarian dysfunction, inflammation, oxidative stress and hypertension, and supports gentiopicroside as a promising therapeutic candidate.

Humans↗

PubMed2026

Preparation and study of non-thrombotic and biostable sulfobetaine-modified small-diameter polyurethane vascular grafts.

A novel sulfobetaine-modified polysiloxane-polycarbonate polyurethane (ZSiPCU) was synthesized. In vitro characterizations revealed that polysiloxane surface enrichment endowed the material with excellent biostability. Importantly, sulfobetaine zwitterions formed a robust hydration layer, effectively suppressing protein adsorption and platelet adhesion to ensure outstanding hemocompatibility. Furthermore, the material supported the adhesion and proliferation of vascular endothelial cells, confirming its cytocompatibility, while its elastomeric matrix provided rapid mechanical self-sealing capabilities. Electrospun ZSiPCU grafts were evaluated in a 3-month rat abdominal aorta model, maintaining high patency rates and facilitating in situ luminal endothelialization and smooth muscle cell remodeling. Additionally, superior puncture resistance of the grafts was demonstrated by puncture tests, with complete hemostasis achieved within 2 mins through mechanical self-sealing.

Polyurethanes↗

PubMed2026

Tripled-Stranded Antisense Oligonucleotide for Biomarker-Activated Suppression of Essential Genes.

Conditional activation of antisense oligonucleotides (ASOs) is a promising strategy for selective suppression of cancer cells without affecting normal cells. In this study, we developed a tripled-stranded ASO (tsASO) that is rendered inactive through complexation with two additional oligonucleotides. The key innovation is the use of partial overlap between the parent ASO and the biomarker sequence, combined with toehold-mediated strand displacement, enabling precise conditional activation. The tsASO effectively triggered RNase H-mediated degradation of DYNC1I2 and DARS1 RNAs exclusively in the presence of the ERBB2 sequence. In cell-free systems, the tsASO demonstrated high cleavage efficiency (up to 81%), comparable to the parent ASO efficiency, with minimal background activity in the absence of the biomarker sequence, validating the concept at the molecular level. However, in cells using lipid-based transfection, the tsASO exhibited nonspecific cytotoxicity that did not correlate with biomarker presence or target gene expression. Detailed analysis showed no clear support for known sequence-driven toxicity mechanisms (CpG/TLR9, G-quadruplexes) in the nonimmune cell lines, suggesting that the primary limitation is intracellular delivery rather than the tsASO design. Future work should focus on optimizing delivery platforms to achieve controlled cellular uptake and biomarker-dependent release, unlocking the therapeutic potential of this conditional gene silencing approach.

Oligonucleotides, Antisense↗

PubMed2026

Astigmatic vector outcomes after FS-LASIK versus SMILE for high myopic astigmatism: a single-center retrospective comparative cohort study without cyclotorsion compensation.

PURPOSE: To compare astigmatic correction vector outcomes between femtosecond laser-assisted in situ keratomileusis (FS-LASIK) and small-incision lenticule extraction (SMILE, also termed Keratorefractive Lenticule Extraction, KLEx) without intraoperative cyclotorsion compensation in patients with high myopic astigmatism (- 2.00 to - 3.75 D), and to clarify procedure-specific correction tendencies under this non-standardized alignment protocol. METHODS: This single-center retrospective comparative cohort study enrolled 155 eyes (one eye randomly selected per patient) that underwent FS-LASIK (80 eyes) or SMILE/KLEx (75 eyes) for high myopic astigmatism correction from January 2023 to July 2024 in Beijing Fenglian Jiayue Lige Clinic. Intraoperative cyclotorsion compensation was intentionally disabled to isolate inherent procedural astigmatism correction characteristics. Standardized Alpins vectorial analysis was performed at 3 months and 12 months postoperatively. PRIMARY ENDPOINT: 12-month Alpins correction index (CI). Multivariable propensity score adjustment was applied to mitigate confounding by clinical treatment selection bias. Statistical multiplicity control was implemented for secondary vector and visual outcomes. RESULTS: Baseline demographic, refractive, corneal and ocular biometric parameters were balanced between groups after propensity matching. No statistically significant intergroup differences were detected in uncorrected distance visual acuity (UDVA), corrected distance visual acuity (CDVA), residual cylinder, safety index or efficacy index at 3 and 12 months (all P > 0.05). Under the non-cyclotorsion-compensated protocol, significant intergroup differences were identified in the magnitude of surgically induced astigmatism (SIA), correction index (CI), and magnitude error (ME) at both follow-up timepoints (all P < 0.0001). Target induced astigmatism (TIA), difference vector (DV), index of success (IOS), and angle error (AE) magnitudes were comparable between groups (all P > 0.05). The vector mean axis of DV differed significantly between groups at 3 and 12 months (Watson-Williams circular test, all P < 0.0001). No reoperations were documented in clinic medical records for either cohort. No standardized dry eye questionnaires, tear film testing or corneal nerve density metrics were collected to quantify dry eye adverse events; only unstructured clinical notes were reviewed for complication screening. CONCLUSIONS: Under surgical alignment without cyclotorsion compensation, FS-LASIK and SMILE/KLEx both yielded acceptable visual and refractive safety/efficacy for high myopic astigmatism (- 2.00 to - 3.75 D) at 1-year follow-up, but demonstrated divergent astigmatism correction tendencies: FS-LASIK exhibited relative astigmatism overcorrection (vector mean DV: - 0.35 ± 0.43 D × 91°, CI > 1), while SMILE/KLEx showed relative undercorrection (vector mean DV: - 0.21 ± 0.53 D × 12°, CI < 1). These correction biases are specific to the study's manual limbal alignment protocol without cyclotorsion tracking and cannot be generalized to modern optimized surgical platforms equipped with automated cyclotorsion compensation. Residual refractive errors across both groups are likely multifactorial, including differential corneal stromal healing responses, divergent femtosecond/excimer laser tissue modification mechanisms, and uncorrected intraoperative ocular cyclotorsion.

Humans↗

PubMed2026

Effectiveness of Mobile-Delivered Exercise and Yoga Programs on Depressive Symptom Reduction in Employees: Randomized Controlled Trial.

BACKGROUND: Mental health challenges such as stress and depression are prevalent among employees. Mobile health platforms that deliver exercise or yoga interventions offer a promising approach to improve mental health outcomes in this population. OBJECTIVE: This study aimed to assess the effectiveness of 12-session adaptive moderate-intensity exercise and yoga programs delivered via a motion-detecting digital platform in reducing stress and depressive symptoms among employees. METHODS: This was an unblinded, 3-arm, parallel-group, randomized controlled trial conducted at Seoul National University Bundang Hospital and Boramae Medical Center between November 2023 and January 2024. Eligible participants were full-time employees. Seventy-five participants were randomly assigned to an exercise, a yoga, or a cognitive behavioral therapy-based self-care control group using computer-generated randomization. The exercise and yoga groups engaged in motion-detecting, adaptive physical activity training, whereas the control group accessed mobile-based, self-directed stress management educational materials. The intervention was largely automated, with no individualized therapeutic guidance provided. Allocation was concealed until trial entry. All recruitment and outcome assessments were conducted in person at the hospitals. The primary outcomes were perceived stress and depressive symptoms, whereas the secondary outcomes included posttraumatic stress, insomnia severity, cognitive stress response, occupational stress, and burnout. Physiological outcomes were assessed using heart rate variability and electroencephalography. Measurements were collected at baseline, immediately after the intervention, and at 4-week follow-up. Data were analyzed using a multivariate linear model to evaluate the main effects of time, group, and time×group interactions. RESULTS: Of the 75 randomized participants (exercise: n=24, 32%; yoga: n=25, 33.3%; and control: n=26, 34.7%), 71 (94.7%) who completed at least 9 of the 12 sessions (≥40 min each) were included in the outcome analysis (exercise: n=21, 29.5%; yoga: n=24, 33.8%; and control: n=26, 36.6%). For the coprimary outcomes, the group×time interaction for depressive symptoms (Patient Health Questionnaire-9) approached but did not reach the Bonferroni-corrected threshold (F4,136=2.71; P=.03; adjusted α=.025); however, planned pairwise comparisons revealed significantly greater improvement in the yoga group compared to the control group at 4-week follow-up (β=-3.67; adjusted P<.001). For the Perceived Stress Scale, the interaction was not significant (P=.29), although a significant main effect of time (P<.001) indicated overall stress reduction across all groups. For secondary outcomes, a significant group×time interaction was found for the Cognitive Stress Responses Scale (P=.003), indicating differential trajectories of improvement. The yoga group showed a consistent linear decrease, whereas the exercise group showed immediate but less sustained gains. CONCLUSIONS: Digitally delivered adaptive yoga programs demonstrated superior and sustained improvements in depressive symptoms and Cognitive Stress Responses Scale scores compared with the active cognitive behavioral therapy-based self-care control group. However, the exercise program showed more modest and less sustained effects, warranting further investigation using larger samples.

Adult↗

PubMed2026

Chemical Complementarities of Neuroblastoma Tumor-Resident TCR CDR3s and CMV Antigens are Associated with a Better Outcome.

A likely immune response to a virus can be detected via the presence of TCR CDR3s that (a) exactly match CDR3s known to bind viral antigens or (b) represent chemical complementarity to viral antigens. Previous studies, based on genomics approaches to characterizing anti-CMV TCR CDR3s in patient blood samples, have indicated the possibility that a systemic CMV infection is associated with worse outcomes for NBL, as well as for breast cancer. Thus, the association of NBL tumor-resident anti-CMV TCR CDR3s and patient outcomes was evaluated here, with results indicating that high levels of chemical complementarity between tumor-resident TCR CDR3s and CMV antigens represented a better outcome. This is in apparent contrast to results obtained via the previous study of blood sourced, anti-CMV TCR CDR3s representing a worse outcome. This study identified gene expression values associated with the tumor-specific anti-CMV TCR CDR3s, representing exact matches to known anti-CMV TCR CDR3s, which may assist in identifying a potential underlying mechanism effecting the better outcomes associated with the tumor-resident, anti-CMV TCR CDR3s. Overall, results here raise the question of whether an anti-CMV response directly against the tumor, or within the tumor microenvironment, is involved in reductions in tumor progression or responsiveness to treatment?

Humans↗

PubMed2026

Multimodal alignment improves generalizability of genomic biomarker prediction in computational pathology.

Computational pathology models that use digitized histopathology whole-slide images have the potential to become a cost-effective and scalable alternative to molecular assays for the prediction of genomic biomarkers, a key task in precision oncology. However, as new genomic biomarkers are discovered or quantified, large, labeled datasets must be prospectively collected to train new models. To address this challenge, we developed multimodal alignment for biomarker learning and generalization (MARBLE), a multimodal contrastive pretraining strategy that integrates structured biomarker knowledge into representation learning of histopathology images. MARBLE aligns histopathology-derived representations with representations of genomic biomarkers generated by a large language model (LLM) and a protein language model (PLM). This biologically informed alignment enables data-efficient generalization to novel, out-of-distribution biomarkers. Using the MSK-IMPACT cohort of over 40,000 patients across multiple biomarker panel versions, we design experiments grounded in real-world data to demonstrate the value of our proposed approach.

CP: computational biology↗

PubMed2026

Endocrine-disrupting chemical-induced gene networks confer coronary heart disease risk revealed by causal inference and single-cell analyses.

BACKGROUND: Endocrine-disrupting chemicals (EDCs) are linked to coronary heart disease (CHD), but underlying mechanisms remain unclear. We aimed to identify EDC-related genes and evaluate their causal roles in CHD. METHODS: We curated EDC-related genes from a compound-gene interaction database and integrated them with CHD genome-wide association study (GWAS) summary statistics and tissue-specific expression quantitative trait loci (eQTL) data. Two-sample Mendelian randomization (MR) and Bayesian colocalization were applied to infer causality. Functional enrichment, single-cell RNA sequencing of human coronary arteries, and EDC-gene networks were further analyzed. RESULTS: After FDR correction, 39 genes were significantly associated with CHD risk via MR. Four genes-ZNF827, FCHO1, IPO9 (protective), and RPL13 (risk-increasing)-showed strong colocalization (PPH4 > 0.9). Pathway and single-cell analyses of coronary artery tissue indicated that vascular and immune pathways mediate these effects. An interaction network highlighted associations between specific EDCs and candidate genes implicated in CHD susceptibility. CONCLUSION: This integrative genomic study provides evidence that EDCs influence CHD susceptibility through distinct gene networks, revealing potential mechanisms and molecular targets for prevention and therapy.

Humans↗

PubMed2026

From pathobiology to prescribing in obesity-driven HFpEF: A systematic review and practical therapeutic framework.

Heart failure with preserved ejection fraction (HFpEF) is increasingly driven by obesity and cardiometabolic dysfunction. In this phenotype, the dominant biology extends beyond congestion alone and includes visceral and epicardial adiposity, systemic inflammation, impaired myocardial energetics, endothelial dysfunction, and exertional elevation in filling pressures. We performed a PRISMA-compliant systematic review with structured narrative evidence synthesis to evaluate pharmacological therapy in obesity-driven HFpEF, searching PubMed/MEDLINE, Scopus, Web of Science Core Collection, ClinicalTrials.gov, and WHO ICTRP through December 2025. Eighteen reports were included in the final qualitative synthesis. The available evidence supports sodium-glucose cotransporter 2 inhibitors as the pharmacological foundation because they provide the most mature outcome data across the preserved ejection fraction spectrum. Semaglutide improves symptoms, physical limitations, exercise capacity, and body weight in dedicated obesity-related HFpEF trials, whereas tirzepatide extends this signal by improving clinical status and reducing worsening heart failure events. Finerenone broadens the therapeutic platform in HF with mildly reduced or preserved ejection fraction, although obesity-specific data remain indirect. Conventional neurohormonal therapies retain a selective role, but they are not the principal biological match for this phenotype. Obesity-driven HFpEF should therefore be managed as a cardiometabolic syndrome with heart failure expression, using a phenotype-based sequence that links diagnosis, decongestion, SGLT2 inhibition, obesity-directed therapy, and selective adjunctive intensification.

Humans↗

PubMed2026

Revealing potential biomarkers and metabolic mechanisms of ovarian aging in hens during late laying period based on machine learning and metabolomics.

Ovarian function decline during the late laying period represents a major bottleneck for the economic efficiency of the global poultry industry. However, the underlying metabolic mechanisms and reliable early-warning biomarkers for ovarian aging remain poorly understood. In this study, we performed the first untargeted LC-MS/MS metabolomics analysis of ovarian tissues from Taihe silky fowls at peak laying (30 weeks) and late laying (50 weeks) stages, and employed an ensemble machine learning strategy integrating LASSO, random forest, and support vector machine (SVM) algorithms to identify high-confidence core biomarkers of ovarian aging. Gene expression analysis was further conducted to validate the potential molecular mechanisms. Our results showed that the metabolic profiles of ovarian tissues differed significantly between the two groups. A total of 6 core biomarkers were identified, 4 of which were long-chain acylcarnitines. Mechanistic analysis revealed that downregulation of key genes in the carnitine shuttle system led to impaired mitochondrial fatty acid β-oxidation, which in turn triggered excessive oxidative stress and compromised ovarian endocrine function. In conclusion, this study identifies long-chain acylcarnitines as potential metabolic biomarkers for ovarian aging in Taihe silky fowls. These findings provide novel insights into the metabolic basis of poultry ovarian aging and lay a theoretical foundation for the precise regulation of reproductive performance in indigenous poultry breeds.

Animals↗

PubMed2026

Alternative genetic codes in bacteria and archaea identified with a fast k-mer-based algorithm.

The genetic code is conserved across all domains of life and is often described as universal. Nevertheless, many exceptions to the "universal" code have now been documented, most of these through manual or semiautomated inspection of highly conserved genes. Modern bioinformatics tools improved our ability to find alternative genetic codes but remain computationally expensive, preventing widespread use on thousands of new species identified by sequencing environmental samples. Here, I report a >100-fold accelerated method for inferring the genetic code directly from assembled genomes and apply it to thousands of previously uncharacterized assemblies from archaea and bacteria. I describe three candidate genetic code variations, one of which, an alternative genetic code used by a family of Asgard archaea, is a unique example of sense codon reassignments for this domain. Identifying genetic code variations is important for understanding evolution of the standard code and improving accuracy of protein databases and open reading frame identification.

Genetic Code↗

PubMed2026

Multi-omic biomarkers in cardiovascular disease: Discovery to clinical translation.

Cardiovascular disease (CVD) remains the leading cause of mortality worldwide, necessitating improved risk stratification and early detection strategies. Multiomics approaches that integrate genomics, transcriptomics, proteomics, metabolomics, and epigenomics offer unprecedented opportunities for biomarker discovery and precision medicine in cardiovascular care. This narrative review examines the current landscape of multiomics biomarkers for CVD, tracing their evolution from discovery to clinical translation. We synthesize evidence from recent studies evaluating the clinical utility of integrated omics approaches across diverse cardiovascular conditions, including atherosclerotic cardiovascular disease, heart failure, and atrial fibrillation. High-throughput proteomics has identified novel protein signatures that enhance cardiovascular risk prediction beyond traditional risk factors. Metabolomics has revealed pathway-specific biomarkers, including trimethylamine N-oxide and lipid species, associated with atherogenesis. Polygenic risk scores derived from genomic data demonstrate incremental value when combined with clinical risk scores. Multiomics biomarkers represent a transformative approach to cardiovascular risk assessment and disease management.

Humans↗

PubMed2026

Triacylglycerol metabolism is a novel target to combat West Nile virus infection.

West Nile virus (WNV) is a zoonotic Orthoflavivirus transmitted by mosquitoes that is responsible for outbreaks of meningitis and encephalitis worldwide. Driven by climate change, WNV has expanded as a global public health concern, particularly in temperate regions. However, there are still no specific approved therapies, reinforcing the need for antiviral development. Previous works have documented that WNV multiplication strictly depends on certain cellular lipids. To identify novel lipid-related therapeutic targets, we analyzed the infection driven alterations in the CNS lipidome, the primary tissue supporting WNV replication. Our results indicated that the major alterations in the brain lipid content of WNV-infected mice corresponded to triacylglycerols (TAGs). Moreover, transcriptomic analysis showed that infected brains underwent changes in the expression of TAG metabolism. Supplementation with exogenous fatty acids increased lipid droplets (LD) content and promoted viral replication in cell culture models. On the contrary, pharmacological intervention in TAG metabolism using diacylglycerol acyltransferase inhibitors (DGATi) suppressed WNV multiplication in cell culture models. As a proof-of-concept of the therapeutic potential of DGATi, treatment of mice with A922500 reduced viral burden in the brain and proinflammatory cytokine production. Overall, our results unveil the importance of LDs and glycerolipid metabolism for WNV and highlight the potential of therapeutic interventions targeting this pathway to control viral replication and neuroinflammation.

West Nile virus; lipid↗

PubMed2026

Transcranial Magnetic Stimulation for Patients with Exposure Therapy Resistant Obsessive-Compulsive Disorder (TETRO): Study Protocol for a Multicenter Randomized Controlled Trial.

BACKGROUND: Obsessive-compulsive disorder (OCD) is a disabling mental disorder, characterized by obsessions, compulsions, and substantial morbidity. Approximately 50% of adults with OCD fail to achieve satisfactory outcomes from first-line treatments, such as exposure therapy with response prevention (ERP), with or without medication. This leads to chronic social, educational, and occupational impairment. While invasive procedures such as deep brain stimulation are available for severe, treatment-refractory cases, a need remains for less invasive alternatives. Repetitive transcranial magnetic stimulation (rTMS), a noninvasive intervention, shows promise in reducing OCD symptoms. Unlike in depression, rTMS is not yet reimbursed for OCD in the Dutch healthcare system. OBJECTIVE: This study examines the efficacy and cost-effectiveness of low-frequency (1Hz) rTMS targeting the presupplementary motor area (pre-SMA) compared to sham rTMS as an adjuvant treatment to ERP in adults with OCD with inadequate response to first-line treatment. METHODS: A total of 250 adults with OCD will be enrolled in this multicenter randomized controlled trial. Participants will be randomly assigned to ERP combined with either active or sham 1Hz rTMS over the pre-SMA. Treatment is administered 4 times weekly for at least 5 weeks (20 rTMS-ERP sessions), with optional extension of 1 to 2 weeks, up to 28 rTMS-ERP sessions. Clinical assessments occur at baseline, weekly during treatment, posttreatment, and at 3, 6, and 12 months follow-up. Participants undergo pre- and posttreatment (functional) (MRI) scans, including a symptom provocation task. Blood sampling takes place pre- and posttreatment and at 3-month follow-up. The primary outcome is OCD severity at posttreatment, as measured by the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS). Secondary outcomes include functional improvement, quality of life, and societal costs. Pretreatment symptom profiles, genotype, and brain network topology will be analyzed as predictors of response and relapse risk. Pre-to-post treatment change in blood-based and magnetic resonance (MR)-based neuroplasticity markers will help explore differential mechanisms between ERP alone and combined rTMS-ERP. We expect that the verum rTMS protocol will be cost-effective compared to sham-rTMS. RESULTS: Recruitment started in April 2022, and as of February 2026, 201 participants have been enrolled. Posttreatment assessments are projected to be completed in December 2026, with final one-year follow-up evaluations anticipated by the end of 2027. CONCLUSIONS: To our knowledge, this study is the first adequately powered randomized controlled trial examining efficacy, cost-effectiveness, and mechanism of action of rTMS for OCD as adjuvant therapy to ERP. In case of efficacy and/or cost-effectiveness, it will pave the way for rTMS as insured health care for adults with OCD in the Netherlands, and possibly other European countries. Furthermore, this trial will provide insight into the mechanisms of treatment response to intensive ERP, with and without adjunctive rTMS, as well as potential side effects, individual variability, and long-term outcomes in adults with OCD.

Humans↗

PubMed2026

Genome-wide association study of estimated glomerular filtration rate using repeated measurements in the Taiwan Biobank.

BACKGROUND: Chronic kidney disease (CKD) is a major global public health issue, with genetic factors playing a significant role in kidney function. Although genome-wide association studies (GWAS) have identified numerous loci associated with estimated glomerular filtration rate (eGFR), most studies relied on a single time-point measurement, which limits the capacity to account for within-individual measurement variability. METHODS: We performed a repeated-measurement GWAS in the prospective Taiwan Biobank (Taiwanese ancestry; n = 25,004) using two repeated creatinine-based eGFR measurements. Repeated eGFR values were analyzed using a linear mixed-effects model with a subject-specific random intercept and time-varying covariates, providing a more precise estimate of eGFR level. Identified loci underwent functional annotation (expression quantitative trait locus, deleteriousness prediction, and epigenetic markers) and were compared with results from a single-measurement GWAS. RESULTS: Six loci associated with eGFR were identified, including four previously reported regions (1q22, 4q21.1, 11p14.1, and 17q21.2) and two additional loci (6p21.32 and 15q24.2). Functional annotation implicated several candidate genes-such as MUC1/EFNA1, SHROOM3, HLA-DQB1, MPPED2, NRG4, and PGAP3/FBXL20-in the regulation of kidney function. CONCLUSION: Incorporating repeated eGFR measurements into GWAS may improve phenotypic precision for identifying genetic associations with kidney function. This study identified eGFR-associated loci and biologically plausible candidate genes in a Taiwanese population, which require further replication and functional validation.

Chronic kidney disease↗

PubMed2026

Decoding tumor immune microenvironment heterogeneity by single-cell and spatial multi-omics: From immunotherapy resistance to translational biomarkers.

Immune checkpoint blockade has transformed cancer therapy, yet primary and acquired resistance remain major clinical challenges. Increasing evidence indicates that immunotherapy resistance cannot be fully explained by tumor-intrinsic alterations or conventional biomarkers such as PD-L1 expression, tumor mutational burden, or microsatellite instability. Instead, therapeutic response is shaped by the tumor immune microenvironment (TIME) as a heterogeneous, spatially organized, and dynamically evolving ecosystem. Single-cell omics has revealed diverse immune and stromal cell states, including progenitor and terminally exhausted T cells, suppressive myeloid programs, B-cell/TLS-associated immune-reactive states, and CAF-mediated exclusion phenotypes. Spatial transcriptomics, spatial proteomics, and imaging-based approaches further demonstrate that these cell states assemble into distinct immune niches, including immune-inflamed, T-cell-excluded, myeloid-suppressive, metabolic/hypoxic, and TLS-associated niches. These spatial ecosystems determine whether antitumor immune cells can access malignant cells, receive antigen-presenting support, or become restrained by stromal, vascular, metabolic, and myeloid barriers. In this review, we summarize how single-cell and spatial multi-omics redefine TIME heterogeneity in immunotherapy resistance, highlight ligand-receptor communication networks linking cell states to spatial immune dysfunction, and discuss emerging translational biomarkers for patient stratification. We further propose that future immunotherapy biomarkers should evolve from static single-marker assays toward longitudinal, spatially resolved, and interpretable multi-omics models that guide precision combination immunotherapy.

Humans↗

PubMed2026

AI-enabled viral genomics: from virus discovery to host prediction and emerging variant forecasting.

The rapid expansion of metagenomic sequencing has generated vast repositories of viral sequence data that far outpace our capacity to interpret them using conventional approaches. Highly divergent sequences, sparse functional annotation, and taxonomically uneven sampling present fundamental challenges for reference-dependent methods, which lose sensitivity precisely for novel and understudied viruses with high public health relevance. Artificial intelligence (AI) provides a new avenue to address these challenges by enabling predictive inference from viral genomes and proteins while reducing dependence on sequence similarity. In this Review, we discuss representative advances in AI for virus discovery, taxonomic classification and functional annotation, prediction of host range and zoonotic potential, and efforts toward forecasting emerging variants. These advances are transforming viral genomics from a largely descriptive discipline into one with increasing predictive capability. We also critically assess the major challenges that constrain current approaches, including the availability of high-quality and representative datasets, rigorous model evaluation, biological interpretability and responsible governance for increasingly capable AI models.

Artificial Intelligence↗

PubMed2026

Penalized Cumulative Probability Model for a Continuous Outcome Subject to Detection Limits.

Mixed-type outcome data occur when the outcome variable's distribution is a mixture of both continuous and discrete ordinal variables. Such mixed-type outcomes are common in biomedical, psychological, and the health sciences, particularly for variables having either a detection or quantitation limit. When interest lies in identifying a combination of genomic features associated with a mixed-type outcome, any method used would require a variable selection strategy for high-dimensional data. Unfortunately, few variable selection methods exist for modeling a mixed-type outcome when the covariate space is high dimensional. This study develops a high-dimensional penalized cumulative probability model (CPM), to allow for the identification of genomic features associated with mixed-type outcome of interest. We demonstrated how such model may be estimated using the iterative penalization procedure-the generalized monotone incremental forward stagewise (GMIFS) algorithm. The Model-X knockoffs procedure was combined with the estimation algorithm to control the false discovery rates (FDR) when performing variable selection. Through extensive simulation studies, our penalized CPM was shown to outperform alternative methods in terms of controlled variable selection performance by achieving high statistical power with the FDR being controlled at the target level. We demonstrate the utility of our method by applying it to predict estimated glomeruli filtration rate (eGFR) in kidney transplant recipients at 24 months post-transplant using baseline gene expression data as predictors. Our CPM model identified five genes associated with this mixed-type outcome which have important links to renal disease, which may provide prognostic guidance for kidney transplantation recipients.

Models, Statistical↗