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Respiratory effects of recruitment maneuvers according to lung recruitability assessed by electrical impedance tomography in patients with acute respiratory distress syndrome.

Recruitment maneuvers (RM) can improve oxygenation in patients with acute respiratory distress syndrome (ARDS), but their physiological effects depend on lung recruitability. This secondary analysis of a randomized controlled trial (RCT) evaluated oxygenation, respiratory mechanics, regional ventilation, and cardiorespiratory adverse events responses to a RM followed by electrical impedance tomography (EIT)-guided PEEP titration, using EIT to assess lung recruitability. In this study, fifty patients with moderate-to-severe ARDS underwent a stepwise RM followed by individualized PEEP titration guided by EIT. Lung recruitability was determined using the collapse index at PEEP 6 cmH&#x2082;O (CLPEEP6), defined as the proportion of collapsed lung at this PEEP level. Patients were classified into high- and low-recruitability groups based on median CLPEEP6 values. Oxygenation (PaO&#x2082;/FiO&#x2082;), static compliance (Cstat), driving pressure (Pdriv), regional ventilation distribution, and cardiorespiratory adverse events were compared before and after RM, during subsequent individualized EIT-guided PEEP titration. In patients with high recruitability (CLPEEP6&#x2009;>&#x2009;12.5), the PaO&#x2082;/FiO&#x2082; ratio and Cstat increased significantly after RM (PaO&#x2082;/FiO&#x2082;: 100.8&#x2009;&#xb1;&#x2009;30.3 vs. 125.4&#x2009;&#xb1;&#x2009;38.3&#xa0;mmHg, p&#x2009;<&#x2009;0.05; Cstat: 21.5&#x2009;&#xb1;&#x2009;5.8 vs. 28.0&#x2009;&#xb1;&#x2009;7.0&#xa0;mL/cmH&#x2082;O, p&#x2009;<&#x2009;0.001), Pdriv decreased (19.1&#x2009;&#xb1;&#x2009;3.5 vs. 15.6&#x2009;&#xb1;&#x2009;3.2 cmH&#x2082;O, p&#x2009;<&#x2009;0.001). EIT demonstrated a posterior redistribution of ventilation after RM. In contrast, patients with low recruitability (CLPEEP6&#x2009;&#x2264;&#x2009;12.5) showed no significant mechanical or oxygenation improvement and transient hypotension, arrhythmia, and desaturation appeared numerically more common in this group. No barotrauma or cardiac arrest occurred, and ICU mortality was similar between groups. A strategy combining a RM with subsequent individualized EIT-guided PEEP titration was associated with improved oxygenation and lung mechanics in patients with high lung recruitability, whereas patients with low recruitability showed limited physiological benefit, with cardiorespiratory adverse events appearing numerically more frequent. The EIT-derived CLPEEP6 index represents a feasible and clinically applicable https://clinicaltrials.gov/study/NCT06733168.

Humans

PCa Detection in PI-RADS 4 and 5 Lesions: Comparison of [68Ga]Ga-PSMA-11 PET/CT-Guided Robot-Assisted Biopsy Versus mpMRI Cognitive-Fusion TRUS-Guided Prostate Biopsy.

Lesions with a Prostate Imaging-Reporting and Data System (PI-RADS) score of 4 or greater on multiparametric MRI (mpMRI) indicate a high likelihood of prostate cancer (PCa), and guidelines recommend a targeted biopsy. We aimed to compare the diagnostic performance of robotic arm-assisted [68Ga]Ga-PSMA-11 PET/CT-guided prostate biopsy (PGPB) with mpMRI-directed cognitive-fusion transrectal ultrasound-guided biopsy (MCFB) in biopsy-na&#xef;ve men with clinical findings suggestive of PCa. Methods: This prospective, single-center, randomized clinical trial (NCT05137561) enrolled biopsy-na&#xef;ve men age 50-90 y with elevated levels of prostate-specific antigen (&#x2265;4 ng/mL) and abnormal digital rectal examination findings. All participants underwent mpMRI, and those with a PI-RADS score of 4 or greater were randomized into 2 arms. In arm 1, participants underwent PGPB for a [68Ga]Ga-PSMA-avid lesion, and participants in arm 2 underwent MCFB. Participants in arm 1 with PET-negative findings subsequently underwent MCFB, and participants with negative biopsy results underwent PET and PGPB. The primary outcome was the detection of PCa. Secondary outcomes included complication rates and participant-reported pain. Result: Of the 267 participants enrolled, 81.3% (217) had lesions with a PI-RADS score of 4 or greater and were randomized to either PGPB (n = 112) or MCFB (n = 105). PCa was detected in 97.1% of participants (101/104) in arm 1 and 81.0% (85/105) in arm 2 (P < 0.05). PGPB showed higher diagnostic accuracy for PI-RADS 5 lesions (100% vs. 95.1%, P = 0.09). Major complications were observed in arm 2 only (n = 5). Arm 1 had significantly fewer complications (10.8% vs. 51.4%, P < 0.01), a lower median visual analog scale score for pain (3 vs. 5), and shorter procedure times. The core positivity rate was higher in arm 1 (60% &#xb1; 20%), despite obtaining fewer cores. Conclusion: [68Ga]Ga-PSMA-11 PGPB demonstrated higher diagnostic performance, fewer complications, and better tolerability compared with MCFB. This approach enables integrated diagnosis and staging, offering a promising alternative for efficient, safe, and accurate evaluation of prostate cancer.

Humans

Changes in hippocampal functional connectivity and volume associated with cognitive improvement and decline in amnestic mild cognitive impairment following computerized cognitive training.

BACKGROUND: The hippocampus influences the outcomes of amnestic mild cognitive impairment (aMCI) and undergoes different changes during the cognitive decline or recovery of aMCI compared to elderly individuals with normal cognition, which may reveal disease-dependent neurodegeneration or plasticity. We first aimed to investigate the hippocampal changes associated with cognitive changes in aMCI using a combined case-control study design. METHODS: In total, 50&#x202f;aMCI individuals and 50 healthy controls (HCs) were recruited in Shenyang, China, and separately randomized into training and control groups: aMCI training group, aMCI no training group, HC training group, and HC no training group. The aMCI and HC training groups received computerized cognitive training (CCT) thrice weekly for 12 weeks. Cognitive assessments and MRI data were collected at baseline and follow-up. RESULTS: The primary outcome was significant CCT&#xd7;diagnosis interaction effect on the change in cognitive performance as measured by clock drawing test (CDT) scores (F&#x202f;=&#x202f;4.322, P&#x202f;=&#x202f;0.041); this interaction was driven by CCT specifically in aMCI (F&#x202f;=&#x202f;4.465, P&#x202f;=&#x202f;0.038). Significant CCT&#xd7;diagnosis interaction effects of right-hippocampal FC changes were observed in the bilateral precuneus/cuneus (Pvoxel<0.05) driven by CCT in aMCI (F&#x202f;=&#x202f;5.429, P&#x202f;=&#x202f;0.023), and in the left superior temporal gyrus/middle temporal gyrus (STG/MTG, Pvoxel<0.05), driven by CCT of only in HCs (F&#x202f;=&#x202f;6.587, P&#x202f;=&#x202f;0.013). A significant interaction effect of left-hippocampal FC changes were observed in the right triangular part of the inferior frontal gyrus (IFGtriang, Pvoxel<0.05), driven by CCT in aMCI and HCs (F&#x202f;=&#x202f;6.550, P&#x202f;=&#x202f;0.013; F&#x202f;=&#x202f;7.097, P&#x202f;=&#x202f;0.010). No significant interaction effect on the change in hippocampal GMV was noted (P&#x202f;>&#x202f;0.05). CONCLUSION: CCT can improve the visuospatial ability of aMCI, which is reflected by the CDT scores. CCT can alter hippocampal FC in the bilateral precuneus/cuneus, the right IFGtriang, and the left STG/MTG. The hippocampal GMV is difficult to change in both HCs and aMCI during the cognitive decline. REGISTRATION NUMBER: ChiCTR1900026849. DATE OF REGISTRATION: 24 October 2019 NAME OF TRIAL REGISTRY: Chinese Clinical Trial Registry (ChiCTR).

Humans

Development of the zebrafish foveal analogue: a quantitative atlas of high-acuity zone growth and retinal regionalisation.

The vertebrate retina contains specialised regions for high-acuity vision, exemplified by the human fovea and its zebrafish analogue, the high-acuity zone (HAZ). Despite the widespread use of zebrafish to model retinal disease, a stage-resolved quantitative reference describing normal eye, photoreceptor layer (PRL) and lens growth has been lacking. Here, we apply contrast-enhanced micro-computed tomography (micro-CT) to construct the first three-dimensional micro-CT normative atlas of wild-type zebrafish eye development across five larval stages [3, 5, 7, 10 and 18&#x2005;days post-fertilisation (dpf)], mapping circumferential PRL thickness, eye and lens morphology, and compartment growth rates. Regional PRL thickening within the temporo-ventral region of the expected HAZ emerged by 5&#x2005;dpf and was sustained by a localised redistribution of growth, persisting and extending towards the optic nerve through 18&#x2005;dpf. The PRL, lens and eye grew through four phases, alternating between disproportionate PRL expansion and coordinated growth, while the eye remodelled from a nasal-dominant to a temporo-ventral-dominant form. This regional specialisation was protracted relative to gross ocular growth and could proceed independently of it, paralleling the extended postnatal maturation of the human fovea. This atlas provides a quantitative baseline for distinguishing disease-induced changes from normal variation, supporting zebrafish models of foveal hypoplasia and related disorders.

Animals

Mechanisms of Hematopoietic Stem Cell Aging and Emerging Rejuvenation Strategies.

Hematopoietic stem cell (HSCs) aging is a complex biological process driven by both cell-intrinsic alterations and extrinsic cues from the bone marrow niche. Understanding these mechanisms is critical for developing therapies against aging-related hematopoietic disorders. This review synthesizes recent advances in the molecular mechanisms underlying HSCs aging, including microenvironmental aging, genomic instability, epigenetic dysregulation, mitochondrial dysfunction, and aberrant nuclear mechanotransduction. We summarize that the functional decline of HSCs during aging drives a compensatory expansion of the phenotypically defined stem cell pool, leading to an aberrant increase in cell number. We also highlight aging-associated HSCs heterogeneity, including CD150high and P-selectin-positive subsets that enrich for myeloid-biased or functionally compromised HSCs states while emphasizing that surface phenotype alone may not fully indicate functional rejuvenation. Finally, we discuss emerging rejuvenation strategies-including targeting myeloid-biased HSCs, modulating inflammatory pathways, and implementing epigenetic or metabolic interventions-supported by cutting-edge technologies such as single-cell multi-omics, gene editing, and computational modeling. These approaches hold promise for counteracting age-related hematopoietic decline and restoring immune competence.

Humans

Machine learning-based prediction of unplanned readmission and construction of an online calculator for elderly patients with mild ischemic stroke.

OBJECTIVE: To screen for independent risk factors for unplanned readmission in elderly patients with mild ischemic stroke, and to construct and validate an online risk prediction calculator based on an interpretable machine learning model, thereby providing a promising practical tool for accurate clinical assessment of 30&#x2011;day all&#x2011;cause unplanned readmission risk in this population. METHODS: A prospective cohort study was conducted, including 1050 patients aged&#xa0;&#x2265;&#xa0;60&#xa0;years with mild ischemic stroke admitted between August 2023 and September 2024. Participants were randomly divided into a training set (840 cases) and a test set (210 cases) at a ratio of 8:2. Risk factors were screened by univariate analysis and multivariable Logistic regression. Four machine learning models, namely LightGBM, XGBoost, Random Forest, and K&#x2011;Nearest Neighbors (KNN), were developed and their performance was evaluated using AUC, accuracy, sensitivity, and specificity as metrics. The SHAP framework was used for interpretability analysis, and an online calculator was subsequently developed based on the optimal model. RESULTS: Univariate analysis showed significant differences (P&#xa0;<&#xa0;0.05) in 13 factors including age, smoking, AIP, TyG index, HALP score, etc. Multivariable Logistic regression identified age (OR&#xa0;=&#xa0;9.752), smoking (OR&#xa0;=&#xa0;5.171), AIP (OR&#xa0;=&#xa0;6.691), TyG index (OR&#xa0;=&#xa0;4.393), HALP score (OR&#xa0;=&#xa0;2.831), and&#xa0;&#x2265;&#xa0;2 comorbidities (OR&#xa0;=&#xa0;3.664) as independent risk factors. All four machine learning models demonstrated good predictive performance. Based on a comprehensive evaluation of multiple metrics and computational efficiency, the LightGBM model exhibited the best predictive performance (AUC&#xa0;=&#xa0;0.884, accuracy&#xa0;=&#xa0;0.829, sensitivity&#xa0;=&#xa0;0.812, specificity&#xa0;=&#xa0;0.875). SHAP analysis showed that age, AIP, TyG index, smoking, and HALP score were key predictors. An online calculator developed based on this model enables individualized risk predictions. CONCLUSION: Key risk factors associated with 30&#x2011;day unplanned readmission in elderly patients with mild ischemic stroke were identified. The LightGBM model demonstrated high predictive accuracy, and together with the interpretability analysis and online calculator, offers a practical tool to support clinical risk assessment. However, this tool requires future external validation.

Humans

Clinical applications of digital twin technology in In Vitro Fertilisation.

BACKGROUND: Digital twin technology, originating from aerospace and manufacturing industries, has emerged as a transformative tool in healthcare. In vitro fertilisation (IVF) faces persistent challenges including suboptimal embryo selection, unpredictable treatment outcomes, and limited personalisation of protocols. Despite advances in assisted reproductive technology, existing literature exhibits fragmentation: artificial intelligence applications in embryo selection, ovarian stimulation, and endometrial assessment have been developed independently without systematic integration into comprehensive treatment frameworks. Digital twin technology offers unprecedented opportunities to create virtual replicas of biological systems, enabling real-time monitoring, predictive modelling, and personalised treatment strategies. AIM: This narrative review aims to critically examine the current applications of digital twin technology in IVF, evaluate its potential benefits and limitations, synthesize existing evidence into an integrative conceptual model, and identify future directions for implementation in reproductive medicine. METHOD: A comprehensive narrative review was conducted using PubMed, Scopus, Web of Science, and IEEE Xplore databases. A narrative review approach was selected over systematic review to accommodate the heterogeneity of evidence types in this emerging field, including theoretical frameworks, simulation studies, and proof-of-concept implementations that would be excluded from systematic reviews. Search terms included "digital twin," "IVF," "in vitro fertilisation," "assisted reproductive technology," "embryo selection," and "predictive modelling." Studies published between 2015 and 2025 were included, focusing on original research articles, systematic reviews, and proof-of-concept studies describing digital twin applications in reproductive medicine. RESULTS: Digital twin technology in IVF demonstrates significant potential across multiple domains including embryo development simulation, ovarian response prediction, endometrial receptivity modelling, and personalised stimulation protocols. Current applications integrate artificial intelligence, machine learning algorithms, time-lapse imaging, and omics data to create comprehensive virtual models. Early evidence suggests improvements in embryo selection accuracy, ovarian response prediction, and treatment protocol optimization, though large-scale randomized controlled trials remain limited. Implementation challenges include data integration complexity, computational requirements, regulatory considerations, and validation requirements. CONCLUSION: Digital twin technology represents a paradigm shift in IVF practice, offering personalised, predictive, and precision medicine approaches. This review synthesizes existing evidence to propose an integrative conceptual model for digital twin implementation across the IVF treatment spectrum, identifies critical knowledge gaps, and establishes research priorities to advance clinical translation. Despite current limitations, continued advancement promises improved success rates and patient outcomes.

Humans

Plant cis-regulatory grammar: Decoding the multidimensional code of transcriptional regulation for programmable crop engineering.

Cis-regulatory elements (CREs) orchestrate the spatiotemporal precision of gene expression that underlies plant development, adaptation, and domestication. Decoding the cis-regulatory grammar of plant genomes remains a central challenge in modern biology, with profound implications for programmable crop engineering. Here, recent conceptual and technological advances are synthesized to reshape our understanding of plant CREs. This review first argues that CRE function is not only an intrinsic property of DNA sequence alone but also emerges from a multidimensional context, including chromatin accessibility, histone modifications, three-dimensional genome topology, and cell type-specific regulatory landscapes. Furthermore, the convergence of single-cell epigenomics, high-throughput functional assays, and CRISPR-based dissection has begun to unravel this contextual grammar, revealing the computational principles governing transcriptional regulation. Critically, we propose that artificial intelligence (AI) platforms are catalyzing an ongoing transition from descriptive discovery to predictive engineering, wherein these platforms outperform natural evolution in designing synthetic CREs. Finally, a roadmap is outlined toward a plant regulatory grammar foundation model, which will enable truly predictive engineering of gene expression when fine-tuned for specific tasks. Collectively, the integration of single-cell resolution maps, precise genome editing, AI-driven design, and regulatory-compliant delivery systems promises to transform our ability to reprogram plant gene regulation for next-generation agriculture, bridging the gap between foundational regulatory biology and tangible crop improvement.

artificial intelligence

Analyzing salinity tolerance in grass carp (Ctenopharyngodon idella): Insights from genome-wide association study and genomic selection.

Grass carp (Ctenopharyngodon idella) is one of the most widely cultured freshwater fish species globally. However, the expansion of its farming scale faces severe limitation owing to freshwater scarcity; therefore, the development of strains with greater salinity tolerance is key for expanding production using brackish water resources. To investigate the genetic basis of salinity tolerance in grass carp, a genome-wide association study (GWAS) was conducted using 200 individuals representing extreme phenotypes, namely salinity-tolerant and salinity-sensitive groups. In total, 17 single nucleotide polymorphisms (SNPs) related to salinity tolerance were detected, which were distributed across 11 chromosomes. Through gene annotation, 38 candidate genes were obtained from these loci. Enrichment analysis revealed these candidate genes are primarily implicated in key biological processes, including osmotic regulation, energy metabolism, and stress responses. Analyses of different SNP densities revealed that the 5&#xa0;K SNP density panel can balance prediction accuracy and computational efficiency. The BayesA model achieved the highest prediction accuracy under the GWAS_Evenly selection strategy, with substantial reductions in mean absolute error and mean square error. This study reveals the genetic mechanisms of salinity tolerance in grass carp, which might be optimized through genomic selection, and provides insights for selectively breeding new varieties with greater salinity tolerance.

Animals

The application of artificial intelligence in healthcare practice: A mapping review of systematic reviews.

Artificial intelligence (AI) is rapidly transforming healthcare practice, with growing evidence supporting its use in diagnosis, prognosis, treatment planning, and operational decision-making. The proliferation of systematic reviews in recent years underscores the need for an updated synthesis of the literature to inform research, policy, and practice. We searched PubMed, Web of Science, Scopus, IEEE Xplore, and CINAHL for systematic reviews and meta-analyses published between 2019 and February 2026. Eligible reviews focused on AI applications in healthcare practice, were peer-reviewed, and written in English. A total of 368 reviews met the inclusion criteria. Publication volume increased steadily, peaking in 2025. AI research was concentrated in high-density domains, such as radiology, oncology, and critical care. Across reviews, diagnostic imaging, electronic health record (EHR) data, and biomarkers/laboratory results accounted for 68% of training data sources, though newer data types, such as wearable device and sensor data, emerged from 2022 onward. Diagnosis, prognosis, and treatment comprised over 80% of AI applications, with novel uses emerging in recent years, such as AI-assisted clinical documentation (e.g., ambient documentation tools) and patient education. Ethical concerns were reported in 78.5% of reviews, with privacy, model accuracy, data and algorithmic bias, and explainability as recurrent themes. The proportion of reviews reporting ethical concerns increased from 2021 to 2025. AI applications in healthcare are expanding in scope, diversifying in data sources, and evolving toward novel clinical and operational uses. The human-centered AI or augmented intelligence paradigm, integrating computational precision with clinical expertise, holds significant promise but will require parallel advances in governance, regulatory frameworks, and ethical oversight to ensure safe adoption.

Artificial Intelligence

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

Discovery of NAT-6-321056 as a novel modulator of VEGFR2 signaling to suppress tumor angiogenesis.

Vascular endothelial growth factor receptor 2 (VEGFR2) is a master regulator of angiogenesis and cancer progression. However, current VEGFR2 modulators face significant challenges, including off-target toxicity and acquired resistance, underscoring the urgent need for novel therapeutic agents with improved efficacy and safety profiles. Here, we reported that virtual screening of 39,442 natural products from the ZINC natural products-derived library, coupled with molecular docking and molecular dynamics (MD) simulations to evaluate the binding stability of candidate compounds, identified NAT-6-321056 as a highly promising modulator of VEGFR2 signaling. Biological evaluations demonstrated that NAT-6-321056 exerted potent inhibition on the growth of a broad spectrum of cancer cells, including both solid tumors and hematological malignancies. In EA.hy 926 endothelial cells and SK-N-DZ neuroblast cells, the compound significantly suppressed proliferation, migration, and invasion. Microscale thermophoresis (MST) confirmed direct binding of NAT-6-321056 to VEGFR2 with favorable affinity. Kinase profiling against a panel of 33 kinases indicated that NAT-6-321056 exhibited a multi-kinase modulation profile. Mechanistic studies revealed that NAT-6-321056 suppressed the expression of hypoxia-inducible factor 1-alpha (HIF-1&#x3b1;) and was associated with reduced VEGFR2 phosphorylation and attenuation of the downstream ERK/JNK/AKT signaling pathways. Moreover, NAT-6-321056 exhibited robust in vivo anti-angiogenic effects in both the chick chorioallantoic membrane (CAM) assay and transgenic zebrafish vascular fluorescence imaging models. Computational absorption, distribution, metabolism, excretion, and toxicity (ADMET) prediction suggested acceptable drug-like properties. Collectively, these findings demonstrated that NAT-6-321056 is a promising modulator of VEGFR2 signaling with potent anti-angiogenic activity and represents a viable candidate for cancer therapy.

Vascular Endothelial Growth Factor Receptor-2

A reanalysis of the Hitachi cohort study evaluating the effectiveness of low-dose CT screening for lung cancer.

The effectiveness of low-dose thoracic computed tomography (CT) screening for lung cancer for non-smokers or light smokers has been unclear. The results of the Hitachi cohort study performed by the conventional multivariable analysis suggested the reduction of lung cancer mortality by thoracic CT screening, but also revealed the lower all-cause mortality in the CT group, which indicated the existence of self-selection bias. Because the background of the subjects in the CT screening group and that in the X-ray screening group were very different, it is critical to adjust appropriately the confounding factors. In this brief report, we describe a re-evaluation of the results of the Hitachi Cohort Study performed by using more flexible methods, propensity score matching and inverse probability weighting.

epidemiology/public health

Effect of Baseline ASPECTS on Tenecteplase Efficacy Before Thrombectomy in Acute Large-Vessel Occlusion Stroke: A Post Hoc Analysis of the BRIDGE-TNK Randomized Trial.

BACKGROUND AND OBJECTIVES: The impact of ischemic extent on the efficacy and safety of intravenous thrombolysis before thrombectomy remains uncertain. The aim of this study was to evaluate whether the baseline ischemic extent, measured by the Alberta Stroke Program Early Computed Tomography Score (ASPECTS), modifies outcomes of intravenous tenecteplase administered before endovascular thrombectomy. METHODS: This was a post hoc analysis of the BRIDGE-TNK (thrombectomy with vs without rhTNK-tPA in stroke) trial, conducted across China from May 2022 to September 2024. We compared the efficacy and safety of intravenous tenecteplase plus thrombectomy vs thrombectomy alone in acute large-vessel occlusion stroke patients within 4.5 hours of last known well, stratified by baseline ASPECTS (<8 vs 8-10). The outcomes included 90-day functional independence (modified Rankin Scale score of 0-2), 48-hour symptomatic intracranial hemorrhage (sICH), and 90-day mortality. Regression models incorporating a treatment-by-ASPECTS interaction term were used for analysis. RESULTS: Among 550 patients, 241 (43.8%) had ASPECTS <8 (median [interquartile range, IQR] age, 69 [61-77] years; 56.4% male) and 309 had ASPECTS 8-10 (median [IQR] age, 70 [61-77] years; 59.5% male). The rate of functional independence was significantly higher in the tenecteplase plus thrombectomy group than in the thrombectomy-alone group in the ASPECTS <8 subgroup (adjusted risk ratio [aRR], 1.67; 95% CI 1.18-2.35), but not in the ASPECTS 8-10 subgroup (aRR, 0.99; 95% CI 0.84-1.17; pinteraction = 0.007). Rates of sICH did not differ significantly between treatment groups in either ASPECTS subgroups (ASPECTS <8: 10.0% vs 11.2%; ASPECTS 8-10: 7.5% vs 2.8%; pinteraction = 0.11). Ninety-day mortality was comparable between treatment groups in the ASPECTS <8 subgroup, but numerically higher with tenecteplase plus thrombectomy in the ASPECTS 8-10 subgroup (aRR = 1.89, 95% CI 0.99-3.61, pinteraction = 0.04). DISCUSSION: In this exploratory post hoc analysis, a signal of benefit was observed in patients with ASPECTS <8 who received intravenous tenecteplase before thrombectomy, whereas no functional improvement and possible safety concerns were seen in those with ASPECTS 8-10. Prospective confirmation in randomized trials is required before practice change. TRIAL REGISTRATION INFORMATION: ClinicalTrials.gov; Unique identifier: NCT04733742.

Humans

SGLF-Net:Staged Global-to-Local Cross-Scale Fusion Network for Colonoscopic Polyp Segmentation.

Polyp segmentation in colonoscopy images plays a pivotal role in computer-aided medical diagnosis and the early prevention of colorectal cancer. However, existing methods often suffer from performance degradation when confronted with extreme polyp scale variation and polyp boundary ambiguity. To address these challenges, we propose the Staged Global-to-Local Cross-Scale Fusion Network (SGLF-Net), which adopts a novel staged global-to-local learning paradigm to progressively refine segmentation from coarse global semantics to fine-grained local details. Specifically, the Global Semantic Perception Stage integrates a Swin Transformer Encoder and a Dynamic Attentive Decoder (DAD) to construct comprehensive multi-scale contextual representations. The Local Detail Refinement Stage employs an Edge-aware Dynamic Attentive Decoder (E-DAD) to enhance structural fidelity and boundary precision through explicit edge-guided supervision. Furthermore, we introduce the Cross Spatial-Scale Feature Aggregation and Reconstitution (CSSAR) module, equipped with hybrid attention mechanisms, to facilitate efficient semantic structural interaction between the two cascaded stages. Extensive experiments on five public benchmark datasets demonstrate that SGLF-Net consistently outperforms state-of-the-art methods in both segmentation accuracy and boundary preservation.

Journal Article

Proteomics in environmental pollution research: Advances, challenges, and future directions.

Environmental proteomics has emerged as a powerful approach for elucidating the molecular mechanisms underlying pollutant-induced biological effects. Although this field has developed rapidly, the systematic review of recent proteomics applications in environmental pollution research remains limited. This review explored the emerging roles of toxicoproteomics in biomarker discovery and mechanistic elucidation, as well as ecotoxicoproteomics in ecological risk assessment and bioremediation strategies. Here, we review the field, highlighting recent trends such as the integration of proteomics with genomics, transcriptomics, and metabolomics to provide a comprehensive view of biological responses to environmental stressors. We further discuss the growing application of artificial intelligence in improving proteomics data interpretation and accelerating biomarker discovery. In addition, recent technological advances in environmental proteomics are highlighted, including next-generation tissue microarray proteomics, nanoscale proteomics, single-cell proteomics, and spatial proteomics. Despite its potential, proteomics faces challenges, such as high operational costs, computational complexity in analysis, and technical limitations in low-abundance protein detection. We propose that the convergence of proteomics with artificial intelligence and multi-omics approaches offers promising solutions to these challenges, enhancing the practical application of proteomics in environmental monitoring and risk assessment.

Proteomics

Effects of Cognitive Behavioral Couple Therapy With Integrated Mindfulness on Mindful Attention, Depressive Symptoms, and Dyadic Adjustment in Low-Income Couples: A Pilot Randomized Clinical Trial.

Psychosocial distress can exacerbate marital conflict, maladjustment, and mental health vulnerability. This pilot randomized clinical trial examined cognitive-behavioral couple therapy (CBCT) integrated with mindfulness in low-income Brazilian couples (per-capita household income up to one minimum wage). Thirty-four participants (17 heterosexual couples) were randomized (independent computer-generated sequence) to an experimental (n&#x2009;=&#x2009;16) or waitlist control group (n&#x2009;=&#x2009;18). We assessed dyadic adjustment, mindful attention, marital social skills, and depressive symptoms (R-DAS, MAAS, IHSC, BDI-II) at baseline, post-treatment, and 3-month follow-up. The intervention was eight 80-min conjoint sessions plus daily home exercises. Time&#x2009;&#xd7;&#x2009;group effects favored the experimental group for dyadic adjustment, mindful attention, and depressive symptoms (all p&#x2009;<&#x2009;0.001,&#x2009;=&#x2009;0.20-0.37), but not marital social skills (p&#x2009;=&#x2009;0.14). Because two outcomes differed at baseline, effects were confirmed with baseline- and dependence-adjusted sensitivity analyses. These findings provide preliminary evidence that CBCT with mindfulness may benefit disadvantaged couples.

Adult

Improving Patient Comfort of Vibratory Anesthetic Devices With a Dampener: A Pilot Study.

BACKGROUND: Vibratory anesthetic devices (VADs) reduce dermatologic injection pain, but their vibration can feel harsh at sensitive anatomical sites. Simple modifications improving patient comfort may enhance VAD adoption. OBJECTIVE: The authors evaluated whether dampening VAD vibration with a cotton buffer improves patient comfort and characterized tactile features influencing preferences. MATERIALS AND METHODS: In a single-site, participant-blinded pilot study (N = 53), adults received a dampened VAD (D-VAD) and standard VAD (S-VAD) at 5 sites-lateral nasal wall, submalar cheek, ear helix, lateral neck, and dorsal forearm-in randomized, contralateral application. Site-specific preference was analyzed with binomial and Cochran Q tests; demographic associations with univariate analyses. Word2vec and hierarchical clustering analyzed qualitative reasons behind patient preference. RESULTS: D-VAD was preferred at all sites across demographics-lateral nasal wall (88.7%), submalar cheek (84.9%), ear helix (88.7%), lateral neck (77.4%), and dorsal forearm (75.5%) (all p < .001), with strongest preference at face and head/neck (p = .018). Computational semantics analysis of qualitative responses identified 6 themes driving preference: Smoothness, Gentleness, Controlled, Low Frequency, Low Intensity, and Less Bothersome. CONCLUSION: Dampening VAD vibration with a cotton buffer enhances comfort across sensitive sites, with reduced harshness and smoother sensation underlying preference. This simple modification may improve patient experience, encouraging broader VAD adoption.

Humans