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PubMed2026

Maternal vaccination with RSVpreF and risk of hypertensive disorders of pregnancy: a systematic review and meta-analysis.

BACKGROUND: A bivalent respiratory syncytial virus (RSV) prefusion F protein-based vaccine (RSVpreF) was approved in the United States in August 2023 for use during pregnancy to prevent infant RSV-associated lower respiratory tract disease. The pivotal phase 3 trial identified a numerical imbalance in hypertensive disorders of pregnancy (HDP) that did not reach statistical significance; postmarketing observational studies have since reported inconsistent findings. We conducted a systematic review and meta-analysis to assess this association. METHODS: We searched MEDLINE, Embase, CENTRAL, Scopus, ClinicalTrials.gov, and WHO ICTRP from inception to Jan 26, 2026, for randomized controlled trials (RCTs) and observational studies comparing HDP outcomes in RSVpreF-vaccinated versus unvaccinated or placebo-receiving pregnant individuals. Unadjusted risk ratios (RRs) were pooled using a random-effects model; adjusted estimates from observational studies were pooled separately by inverse variance methods. This study is registered with PROSPERO (CRD420251026835). RESULTS: Nine studies were included (3 RCTs, 6 retrospective cohort studies; n = 148,267). RSVpreF vaccination was associated with a small but statistically significant increase in overall HDP risk (RR 1·08, 95% CI 1·02-1·13; p = 0·004; I2 = 44%), driven by the observational studies group (1·08, 1·02-1·14; I2 = 61%); RCTs showed a directionally consistent but non-significant RR (1·12, 0·87-1·43; I2 = 0%). The association was attributable to gestational hypertension, with no significant association for preeclampsia/eclampsia. CONCLUSION: Maternal RSVpreF vaccination was associated with a small increase in HDP attributable to gestational hypertension and driven primarily by observational studies, in which residual confounding remains possible. The benefits of infant RSV prevention remain substantial, and these findings support continued postmarketing surveillance and informed shared decision-making.

Humans↗

PubMed2026

Glaucoma filtering surgery combined with phacoemulsification in the era of new aqueous humor filtration devices: A systematic review.

We evaluate the efficacy and safety of filtering glaucoma surgeries combined with phacoemulsification (PCE)-including new aqueous humor drainage devices-compared to standalone procedures. We performed a systematic search up to March 23, 2025, including all comparative studies assessing trabeculectomy (TRAB), non-penetrating deep sclerectomy (NPDS), Xen® Gel Stent (XEN), or Preserflo® MicroShunt (PMS) combined with PCE, versus the same surgery alone. Key exclusion criteria include inadequate follow-up (less than 12-month), absence of a defined success criterion, more than 50% of loss to follow-up at 12-month, and lens extraction performed without PCE. Main outcome was surgical success at ≥ 12 months. Secondary outcomes included intraocular pressure (IOP) reduction, decrease in hypotensive medications, and rates of complications. A total of 27 studies were included for analysis. Among studies comparing TRAB/PCE with standalone TRAB, half reported similar success rates, while others favored standalone TRAB, particularly using strict IOP thresholds. Safety profiles were comparable. For NPDS/PCE, data mostly showed equivalent outcomes versus standalone NPDS, with comparable safety. In studies on XEN/PCE and PMS/PCE, results suggested similar rates of surgical success, efficacy in IOP and medication reduction, and safety compared to their stand-alone procedures. Small differences occasionally favored standalone procedures under stricter success definitions. Current evidence suggests that combined filtering glaucoma surgery provides long-term efficacy and safety comparable to standalone, though some subgroups and outcome thresholds may slightly favor standalone approaches. The limited availability of high-quality prospective trials underscores the need for further large-scale robust studies.

Humans↗

PubMed2026

Cytonuclear conflict and reticulate evolution in the Morelloid clade (Solanum, Solanaceae): Insights from genome skimming and network Phylogenomics.

The Morelloid clade (black nightshades) is one of the most strongly supported clades within the megadiverse Solanum genus. It comprises 76 globally distributed, non-spiny herbaceous and suffrutescent species. While often erroneously considered poisonous weeds, several species are economically important as orphan crops. The clade is closely related to tomato and potato but, due to a lack of focused breeding efforts, remains a putative reservoir of genetic diversity for crop improvement. Despite this potential, we lack fundamental knowledge on the evolution of the Morelloid clade. The group includes polyploid species with unknown parental origins-likely reflecting reticulate processes such as hybridization, introgression, and associated backcrossing events. Prior analyses have been unable to disentangle these processes, leaving the mechanisms underlying reticulate evolution in the Morelloid clade poorly understood. Here, we use genome skimming to produce a well-supported maximum likelihood plastid phylogeny from complete circularized plastomes and a coalescent-based species tree from combined Angiosperms353 and conserved ortholog set nuclear markers. Our dataset, composed of previously published data and deep genome skimming from herbarium samples, spans 26 Morelloid species. To investigate phylogenetic discordance, we used a nuclear phylogenetic network, multispecies coalescent simulations, a fused rooted nuclear chloroplast tree, and quantification of nuclear gene tree concordance. We show that incongruence between nuclear and plastid trees is pervasive and cannot be explained by incomplete lineage sorting alone. Instead, our results demonstrate that events consistent with repeated chloroplast capture have shaped the reticulate evolutionary history of the clade, especially among African polyploid and Pan-American diploid lineages.

Phylogeny↗

PubMed2026

Systematic review of machine learning approaches for predicting sickle cell crisis and mortality risk at the climate-health nexus.

BACKGROUND: Sickle cell anemia (SCA) is a severe genetic blood disorder characterized by recurrent vaso-occlusive crises and increased mortality, with the greatest burden occurring in low- and middle-income countries. Climatic and environmental conditions, including temperature variability, humidity, rainfall, air pollution, and seasonal changes, have been associated with disease exacerbation. However, the extent to which these factors have been incorporated into predictive models remains unclear. This study systematically reviews the application of machine learning (ML) models for predicting SCA crises and mortality in relation to climate and environmental factors. METHODOLOGY: The PRISMA guidelines were used, and 34 peer-reviewed studies published between 2005 and 2026 were analyzed to identify the climate variables, ML approaches employed, and predictive performance. The reviewed studies applied a range of ML techniques, including artificial neural networks, random forests, support vector machines, decision trees, logistic regression, and deep learning models. Temperature, humidity, rainfall, wind speed, air quality indicators, and seasonal patterns were the most frequently examined environmental variables. RESULTS: The findings indicate that most existing models rely predominantly on clinical and demographic data, with limited integration of climate information and inadequate representation of high-burden regions, especially Sub-Saharan Africa. Studies incorporating environmental variables reported improved predictive performance and highlighted the potential of climate-informed early warning systems for SCA management. CONCLUSION: The review recommends development of interdisciplinary, climate-aware ML frameworks, expansion of longitudinal environmental datasets, and increased research in underrepresented regions to support climate-resilient and patient-centered SCA care.

Humans↗

PubMed2026

Depth-dependent microbial succession and interspecies hydrogen transfer drive pit mud maturation in Chinese strong-flavor baijiu fermentation.

Microbial communities in fermentation pit mud play a key role in determining the quality of Chinese strong-flavor baijiu (CSFB). However, the ecological processes underlying pit mud maturation across spatial and temporal scales remain unclear. In this study, amplicon sequencing and metagenomic analyses were employed to investigate the taxonomic succession, community assembly, and metabolic functions of bacterial and archaeal communities during the transition from fresh pit mud (FPM) to new pit mud (NPM) and old pit mud (OPM). A pronounced depth-dependent succession pattern was observed, with 4 cm representing a critical ecological boundary separating distinct community structures and maturation trajectories. During surface-layer maturation, community assembly shifted from stochastic to deterministic processes, accompanied by homogeneous selection and increasing network complexity. In contrast, stochastic processes remained dominant throughout deep-layer maturation. Metagenomic analyses revealed a functional transition from lactate and acetate production, primarily associated with Lactobacillus in FPM and NPM, to butyrate and caproate production associated with Clostridium and Caproiciproducens in OPM. This functional transition was accompanied by enhanced amino acid metabolism, which was associated with the enrichment of Proteiniphilum and Aminobacterium. Notably, methanogen-mediated interspecies hydrogen transfer (IHT) emerged as a key ecological feature during pit mud maturation. In OPM, IHT networks primarily involving Methanobacterium and Methanosarcina linked methanogenesis with reverse β-oxidation through diverse hydrogen-transfer pathways, reinforcing metabolic interactions underlying caproate production. These findings provide new insights into the ecological mechanisms underlying pit mud maturation and offer a theoretical basis for the directed cultivation of high-quality pit mud in CSFB production.

Hydrogen↗

PubMed2026

How the microbiome shapes epigenetic trained memory in neuroinflammation: Implications for neurodegenerative diseases.

Neurodegenerative diseases are increasingly recognized as disorders involving immune dysregulation. However, the mechanisms underlying this dysfunction remain poorly characterized. Trained immunity has recently emerged as a potential contributor to immune dysregulation, particularly in neuroinflammation and neurodegenerative diseases, where trained immunity is the epigenetic reprogramming of innate immune responses following an initial inflammatory stimulus, which increases responses to subsequent exposures. In parallel, although the brain has traditionally been viewed as an immune-privileged organ, growing evidence indicates that peripheral immune activity exerts significant influence on neuroinflammation in the brain. A major driver of peripheral immunity is the microbiome. Therefore, this perspective aims to present a conceptual framework for a relationship between the microbiome, trained immunity, and neurodegenerative diseases. We first summarize evidence of trained immunity in the brain and its role in neurodegeneration. Next, we highlight the role of the microbiome in peripheral immune modulation and in trained immunity. Finally, we propose potential mechanisms through which the microbiome may induce or modulate trained immunity in the brain. These include: 1) immunogenic microbial metabolites that cross the blood-brain barrier and alter host cell epigenetics; 2) migration of peripherally trained myeloid cells into the brain; 3) viral infection-induced trained immunity that may predispose to neurodegeneration. Together, this perspective suggests that microbiome-induced trained immunity offers a novel mechanism linking peripheral immune regulation with neuroinflammation and neurodegeneration with implications for therapeutic targeting of epigenetic modification as a molecular prevention strategy for progression of neurodegeneration.

Humans↗

PubMed2026

How do women with a history of childhood sexual abuse experience the preconception and perinatal period? A qualitative systematic review.

CONTEXT: Child sexual abuse (CSA) is a public health issue that predominantly affects women and has both short- and long-term consequences. The perinatal period can represent a challenge, but also an opportunity to identify a history of CSA and to provide sensitive care that may help prevent the intergenerational transmission of trauma. AIM: To describe and understand the experiences and coping strategies of women who are survivors of child sexual abuse and are transitioning to motherhood. METHOD: We conducted a systematic review of qualitative studies according to a protocol registered in PROSPERO, following methodological standards and reporting the results according to the ENTREQ guideline. A search was conducted on five databases up to July 2025. Two authors independently selected the articles and assessed their methodological quality. Data were analysed using thematic synthesis and the confidence in the findings was evaluated according to GRADE-CERQual. RESULTS: We included 21 qualitative studies that resulted in six themes. The findings reveal how women who experienced child sexual abuse and are transitioning to motherhood may experience this stage with ambivalence-ranging from revictimisation to identity reconstruction-where perinatal care emerges as a potential healing vehicle throughout this process. CONCLUSIONS: The perinatal period becomes a window of opportunity to heal deep wounds, with perinatal care playing a key role. The findings support trauma-informed perinatal care, underpinned by reflective practice and a holistic approach. Further work is needed to improve the identification of child sexual abuse, enhance professional training and review current practices to ensure sensitive care.

Humans↗

PubMed2026

The Role of Artificial Intelligence Combined With Digital Cholangioscopy for Indeterminant and Malignant Biliary Strictures: A Systematic Review and Meta-analysis.

BACKGROUND: Current endoscopic retrograde cholangiopancreatography (ERCP) and cholangioscopic-based diagnostic sampling for indeterminant biliary strictures remain suboptimal. Artificial intelligence (AI)-based algorithms by means of computer vision in machine learning have been applied to cholangioscopy in an effort to improve diagnostic yield. The aim of this study was to perform a systematic review and meta-analysis to evaluate the diagnostic performance of AI-based diagnostic performance of AI-associated cholangioscopic diagnosis of indeterminant or malignant biliary strictures. METHODS: Individualized searches were developed in accordance with PRISMA and MOOSE guidelines, and meta-analysis according to Cochrane Diagnostic Test Accuracy working group methodology. A bivariate model was used to compute pooled sensitivity and specificity, likelihood ratio, diagnostic odds ratio, and summary receiver operating characteristics curve (SROC). RESULTS: Five studies (n=675 lesions; a total of 2,685,674 cholangioscopic images) were included. All but one study analyzed a deep learning AI-based system using a convoluted neural network (CNN) with an average image processing speed of 30 to 60 frames per second. The pooled sensitivity and specificity were 95% (95% CI: 85-98) and 88% (95% CI: 76-94), with a diagnostic accuracy (SROC) of 97% (95% CI: 95-98). Sensitivity analysis of CNN studies (4 studies, 538 patients) demonstrated a pooled sensitivity, specificity, and accuracy (SROC) of 95% (95% CI: 82-99), 88% (95% CI: 72-95), and 97% (95% CI: 95-98), respectively. CONCLUSIONS: Artificial intelligence-based machine learning of cholangioscopy images appears to be a promising modality for the diagnosis of indeterminant and malignant biliary strictures.

Humans↗

PubMed2026

Quantitative susceptibility mapping in neurodegenerative diseases: An umbrella review of iron-related biomarkers and mechanisms.

Pathological iron accumulation is a common pathophysiological hallmark across multiple neurodegenerative diseases (NDDs), motivating the need for accurate, non-invasive quantification methods. Quantitative susceptibility mapping (QSM) is an advanced magnetic resonance imaging (MRI) technique that enables in vivo measurement of tissue magnetic susceptibility (χ), providing a sensitive proxy for iron content. This umbrella review systematically evaluates the diagnostic accuracy, clinical correlations, and distinct iron distribution patterns of QSM in major NDDs, such as Parkinson's disease (PD), Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), and atypical Parkinsonism. We included 15 (13/15 were rated Low or Critically Low on AMSTAR 2) systematic reviews and meta-analyses (through July 15, 2026); however, the findings should be interpreted cautiously because of heterogeneity and the low methodological quality. A Corrected Covered Area (CCA) analysis demonstrated only slight overlap of primary studies across the included reviews (CCA = 5.42%). Collectively, the evidence indicates that QSM provides comparable or higher diagnostic sensitivity and reliability than conventional R2* and SWI techniques, particularly for deep gray matter structures. The findings support significant iron overload in the substantia nigra, particularly in the pars compacta, as a robust biomarker for PD that correlates with motor severity and disease duration. Furthermore, regional iron profiling in the basal ganglia is critical for differential diagnosis; specifically, elevated χ in the putamen and globus pallidus effectively distinguishes multiple system atrophy and progressive supranuclear palsy from idiopathic PD. Distinctively, AD and ALS exhibit specific χ alterations in the thalamus, motor cortex, and hippocampus, reflecting divergent iron-related pathophysiological mechanisms, which correlate with cognitive impairment and upper motor neuron signs. Overall, QSM shows diagnostic promise and offers mechanistic insights into iron-related neurodegenerative processes.

Humans↗

PubMed2026

Artificial Intelligence for Diagnosing Meibomian Gland Dysfunction: A Systematic Review and Meta-Analysis of Diagnostic Test Accuracy Studies.

PURPOSE: To identify, appraise, and synthesize the performance of artificial intelligence-based meibography reading as compared with human graders in diagnosing meibomian gland dysfunction. METHODS: We followed Cochrane methodology and reporting guidelines for diagnostic test accuracy reviews. To assess potential risk of bias and applicability, we used a modified Quality Assessment of Diagnostic Accuracy Studies-2 checklist. We applied bivariate logistic models to estimate summary sensitivity and specificity when appropriate and used the GRADE framework to rate the certainty of the evidence. RESULTS: We identified 14 eligible studies involving 5511 predominantly middle-aged participants (average age: 27-55 years) who were primarily female (≥54.5%). A total of 18,926 meibography images were obtained through noncontact infrared (11 studies) or in vivo confocal microscopy (three studies). Two studies reported external validation of deep learning models, 12 reported internally validated models, and one reported both. All but one study had high risk of bias in at least one domain; 12 studies raised high or intermediate concern about applicability. Based on three external evaluations, the summary sensitivity and specificity for diagnosing meibomian gland dysfunction from normal glands were 97.5% (95% confidence interval: 77.5%-99.8%) and 85.5% (95% confidence interval: 47.3%-97.5%). Sources of heterogeneity in internally validated models included study population, case mix, and others. The overall evidence was very low to low certainty because of imprecision, high risk of bias, and concerns about applicability. CONCLUSIONS: Artificial intelligence-based meibography grading appears less accurate than human graders. Future studies should adopt rigorous designs, including a more diverse participant pool (or image set), and external validation.

Humans↗

PubMed2026

A multi-scale fusion model based on multi-phase contrast-enhanced CT for predicting pancreatic cancer resectability.

Purpose.Develop a multi-scale fusion model (MSFM) based on multi-phase contrast-enhanced computed tomography (CECT) to predict pancreatic cancer (PC) resectability, thereby assisting expert decision-making.Methods.This retrospective study enrolled 280 patients with PC from four institutions, which were randomly divided into a training cohort (202 patients) and an independent test cohort (78 patients). Three-phase CECT images (arterial, venous, and delayed phases) were used for modeling. The MSFM comprises two sub-networks: (1) a multi-phase fusion network for extracting cross-phase shared fusion features, (2) a phase-specific branch network for capturing phase-specific features; and a post-fusion strategy to generate the final predictive score by integrating the shared fusion features and three groups of phase-specific features. Additionally, a human-machine fusion deep learning model (HMfDL) was constructed by fusing the predictive score of the MSFM with expert assessments.Results.In the independent test, the MSFM achieved an AUC (area under the receiver operating characteristic curve) of 0.8385 (95% CI: 0.7521-0.9249), accuracy of 84.62%, sensitivity of 72.00%, and specificity of 90.57%. This performance outperformed single-phase models (AUC range: 0.7638-0.7781), two-phase models (AUC range: 0.7826-0.7864), and ten states-of-the-art classifiers (AUC range: 0.7404-0.7796). The HMfDL further improved the performance, reaching an AUC of 0.8626 (95% CI: 0.7853-0.9400), accuracy of 91.03%, sensitivity of 80.00%, and specificity of 96.23%. Notably, the HMfDL corrected 58.82% of misdiagnosis made by experts.Conclusions. The MSFM effectively fuses multi-phase CECT to enable highly accurate predictions of PC resectability, and provides valuable support for expert decision-making through HMfDL.

Humans↗

PubMed2026

Targeting Both Oncogenic Signaling and Dependence Receptor Function is Required to Fully Suppress MET Exon 14 Skipping-Driven tumorigenesis.

Receptor tyrosine kinases (RTKs) classically function as oncogenic drivers that promote survival and proliferation upon ligand binding. A subset of RTKs can also function as dependence receptors, inducing apoptosis in the absence of their ligands. Genetic alterations that enhance RTK signaling are well characterized in cancer and can be targeted with kinase inhibitors, which show limited efficacy in some clinical settings. Elucidation of whether oncogenic mutations can promote tumorigenesis by directly abolishing the pro-apoptotic activity of dependence receptors could help improve strategies to target RTKs. Here, we identified MET exon 14 skipping (METex14Del) as a paradigmatic example of an oncogenic alteration that drives tumorigenesis through genetic inactivation of the dependence receptor function of an RTK. METex14Del removed both the caspase cleavage site and adjacent CBL-binding motif, preventing generation of the pro-apoptotic p40MET fragment while sustaining oncogenic MET signaling. Uncoupling regulatory functions of MET using genome editing showed that loss of apoptosis capacity is a critical determinant of METex14Del-driven tumorigenesis. Combined-but not individual-mutation of the caspase and CBL sites was sufficient to recapitulate resistance to apoptosis and tumor growth induced by METex14Del in HGF-humanized mouse models. Importantly, inducible re-expression of p40MET in METex14Del-expressing cells restored apoptotic sensitivity, decreased tumor formation in vivo, and resensitized tumors to capmatinib. Together, these findings redefine RTKs as receptors with dual oncogenic and tumor-suppressive functions and show that disruption of dependence receptor-mediated apoptosis is an oncogenic mechanism. These results provide a conceptual framework explaining why therapies targeting only RTK signaling may fail and support strategies restoring dependence receptor function to achieve durable tumor suppression.

Journal Article↗

PubMed2026

Development and Crossover Evaluation of an Artificial Intelligence-Assisted System for Solid Pancreatic Lesion Detection and Pancreatic Parenchyma Recognition in Endoscopic Ultrasonography (With Video).

BACKGROUND AND STUDY AIMS: Pancreatobiliary endoscopic ultrasonography (EUS) is technically demanding, and supervised training opportunities are limited. We developed an artificial intelligence (AI) overlay system for detecting solid pancreatic lesions (SPL) and recognizing pancreatic parenchyma (PP) and evaluated its effect on reader performance. PATIENTS AND METHODS: Across six centers, two deep learning-based models were trained using expert-annotated EUS frames. We then conducted a randomized, two-sequence, two-period crossover reader study in which eight endosonographers (five novices and three experts) interpreted image sets with and without AI assistance. The primary endpoint was superiority of sensitivity for SPL detection among novices; key secondary endpoints included specificity and PP recognition. RESULTS: From 118 patients, 120 SPL-positive/negative image sets and 160 PP-positive/negative image sets were constructed. Among novices, AI assistance improved SPL detection sensitivity (88.7% vs. 76.8%, p < 0.001) and accuracy (86.4% vs. 78.7%), while specificity met the predefined noninferiority criterion (84.2% vs. 80.5%, p < 0.001). For PP recognition, sensitivity increased numerically (86.3% vs. 83.3%) but did not meet the predefined superiority criterion (p = 0.095); specificity met the noninferiority criterion (87.8% vs. 81.0%), and accuracy increased from 82.1% to 87.0%. Among experts, sensitivity was maintained for both tasks, whereas specificity increased with AI assistance. CONCLUSIONS: AI assistance improved SPL detection among novice endosonographers. For PP recognition, sensitivity increased without reaching statistical superiority, whereas specificity met the predefined noninferiority criterion. These findings support a potential adjunctive role for AI in EUS interpretation.

Humans↗

PubMed2026

Form and function of actin impacts actin health and aging.

The actin cytoskeleton is a fundamental and highly conserved structure that functions in diverse cellular processes, yet its direct contribution to organismal aging remains unclear. Here, we systematically interrogated how genetic and pharmacologic perturbations of actin structure and function influence lifespan and various hallmarks of aging in Caenorhabditis elegans. Whole-animal and tissue-specific knockdown of actin and key actin-binding proteins (ABPs)-arx-2 (Arp2/3), unc-60 (cofilin), and lev-11 (tropomyosin)-led to premature disruption of filament organization, reduced lifespan, and tissue-specific physiological defects. Actin dysfunction also displayed a more "aged" transcriptome using previously validated transcriptomics clocks, and broadly exacerbated many age-associated phenotypes, including mitochondrial dysfunction, lipid dysregulation, loss of proteostasis, impaired autophagy, and intestinal barrier failure. Pharmacological destabilization with Latrunculin A mirrored genetic knockdowns, while mild stabilization with Jasplakinolide modestly extended lifespan, emphasizing that optimal and finely tuned actin function is critical for healthy aging. Finally, analysis of human genome-wide association data revealed that common ACTB polymorphisms correlate with differences in age-related decline in gait speed, suggesting some links between aging and actin across organisms. Taken together, our results provide a comprehensive and publicly accessible resource that maps, for the first time, how changes in actin integrity correlate with diverse aging phenotypes across tissues. This descriptive framework is intended to enable future mechanistic discovery by offering a deep, unbiased dataset that can be integrated with emerging studies to define how actin dynamics can potentially influence aging.

actin↗

PubMed2026

Single-cell transcriptome revealed the aberrant keratinocytes activation in antigen presentation in atopic dermatitis.

BACKGROUND: Atopic dermatitis (AD), a common chronic inflammatory skin disease, has been extensively studied using single-cell genomics. However, keratinocytes, as key effector cells in AD, have underlying mechanisms remain incompletely understood and require further investigation. METHODS: We integrated single-cell transcriptomic data from skin tissues of healthy controls, chronic active AD patients, spontaneously healed AD (SHAD) patients, and an ovalbumin-induced AD mouse model. The study particularly emphasized the gene expression and cellular dynamics of keratinocytes across the different groups, as well as their interactions with immune cells. RESULTS: Compared to healthy controls, we observed significant changes in the keratinocyte transcriptome, cellular state, and keratinocyte-immune cell ligand-receptor interactions in AD skin, particularly the marked activation of genes involved in antigen processing and presentation. Interestingly, such gene activation was not observed in keratinocytes from the ovalbumin-induced AD mouse model, despite its phenotype closely resembling human AD. Furthermore, in SHAD, we identified a recovery of both the ligand-receptor interaction patterns and antigen processing and presentation genes, accompanied by a notable shift in the transcriptome. This involved a significant downregulation of genes related to cytoplasmic transcription and oxidative phosphorylation. Notably, this pattern was not observed in the self-healing mouse model following the removal of ovalbumin stimulation. CONCLUSION: Our results suggest that the persistent activation of antigen processing and presentation pathways in keratinocytes may be a key driver of chronic inflammation in AD. Therefore, redirecting anti-allergic therapeutic strategies from solely targeting immune cells to targeting of keratinocyte-mediated antigen presentation may offer a more effective approach. Furthermore, we raise concerns about the use of ovalbumin-induced mouse models to recapitulate human chronic AD, as the underlying mechanisms may differ significantly.

Dermatitis, Atopic↗

PubMed2026

Impact of renal dysfunction on immediate versus staged revascularization of non-culprit lesions in patients with ST segment elevation myocardial infarction: a pre-specified subgroup analysis of the randomized MULTISTARS AMI trial.

BACKGROUND: Renal dysfunction might affect outcomes in patients with ST-segment elevation myocardial infarction (STEMI) and multivessel coronary artery disease (MVD) undergoing percutaneous coronary intervention (PCI). METHODS: In MULTISTARS AMI, patients with STEMI and MVD were randomized to immediate or staged PCI of non-culprit lesions. In this pre-specified analysis, patients were stratified according to the presence of renal dysfunction at baseline, defined at an estimated glomerular filtration rate (eGFR) of 60 ml/min/1.73 m2. Patients with an eGFR < 30 ml/min/1.73 m2 were excluded from the trial. The primary endpoint was a composite of death, non-fatal myocardial infarction, stroke, unplanned revascularization, or hospitalization for heart failure at 1 year. RESULTS: In MULTISTARS AMI, 108 (13%) of 832 patients had renal dysfunction. The primary endpoint occurred more frequently in patients with renal dysfunction (19.4% vs. 11.2%, unadjusted HR 1.82, 95% CI 1.13-2.94), primarily driven by higher rates of death. Among patients with renal dysfunction, the rates of the primary end point were 14.5% and 24.5% in the immediate and staged PCI groups (unadjusted HR 0.55, 95% CI 0.23-1.33). There was no interaction between renal dysfunction and the randomized treatment assignment with respect to the primary end point (adjusted HR 1.30, 95% CI 0.8-2.20, pint 0.82). The occurrence of acute renal insufficiency was statistically similar in patients with renal dysfunction who underwent immediate and staged PCI (10.9% vs. 18.9%, unadjusted HR 0.61, 95% CI 0.22-1.72, pint 0.09). Renal dysfunction at baseline emerged as a strong risk factor for the development of acute renal insufficiency (adjusted HR 5.0, 95% CI 2.30-10.70, p < 0.01). CONCLUSIONS: Outcomes with immediate compared to staged multivessel PCI did not appear significantly altered by the presence of renal dysfunction at baseline. (Supported by Boston Scientific; MULTISTARS AMI ClinicalTrials.gov number, NCT03135275).

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

Environmentally relevant concentrations of DCOIT impaired lifespan and healthspan in Caenorhabditis elegans.

DCOIT (4,5-dichloro-2-n-octyl-4-isothiazolin-3-one) is an antifouling biocide widely used as an alternative to organotin compounds. While previous studies had focused on its effects on energy production, endocrine disruption, and lipid metabolism, its impact on aging and underlying mechanisms remained unclear. Here, we demonstrated that environmentally relevant concentrations of DCOIT (37, 370 and 3700 ng/L) significantly impaired both lifespan and healthspan in Caenorhabditis elegans. RNA-seq and validation assays revealed that DCOIT upregulated comt-4, a key gene in dopamine metabolism, leading to dopamine depletion and subsequent induction of oxidative stress. This redox imbalance critically contributed to accelerated aging phenotypes. Importantly, both genetic (comt-4 RNAi) and pharmacological (opicapone) interventions restored dopamine levels, alleviated oxidative stress, and reversed DCOIT-induced aging deficits. Our study established the comt-4/dopamine/oxidative stress axis as a central mechanism in DCOIT toxicity, suggesting dopamine modulation as a potential countermeasure against environmental toxicant-induced aging.

Animals↗