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Illicium verum polysaccharide targets fimbriae and flagella to disrupt biofilm and inhibit multidrug-resistant Escherichia coli proliferation.

The widespread dissemination of multidrug-resistant (MDR) E. coli has led to a decrease in the efficacy of antibiotics, posing severe challenges to clinical anti-infective therapy. Owing to their safety, multitarget activities, and low risk of inducing drug resistance, plant polysaccharides represent a promising alternative strategy. In this study, an acidic polysaccharide (IVP-3) was isolated and purified from the medicinal and edible plant Illicium verum, and it was found to inhibit MDR E. coli colonization by disrupting its biofilm. The Mw of IVP-3 was determined to be 35.566 kDa. Its backbone consists of →4)-α-D-GalpA-6-OMe-(1→, →4)-α-D-GalpA-(1→, →4)-β-D-Galp-(1→, and →3,4)-α-D-GalpA-(1 → residues, whereas the branched chain is composed of α-L-Araf-(1 → 5)-α-L-Araf-(1 → attached to the O-5 position of →2,5)-α-L-Araf-(1→, which is further linked to the O-3 position of the backbone. Mechanistically, IVP-3 disrupts the structure of fimbriae and flagella, inhibits bacterial motility, effectively prevents initial biofilm adhesion, and eradicates preformed mature biofilms. Additionally, IVP-3 damages cell membrane integrity, disrupts the proton motive force, and induces energy metabolism disorder, efflux pump inhibition, and oxidative stress, ultimately leading to bacterial lysis. This study provides a theoretical basis for the development of natural antibacterial agents targeting MDR E. coli biofilms and for the high-value utilization of Illicium verum.

Biofilms

Spinal meningiomas: histopathological grading using a benchmark radiomics model with notes on disease control.

OBJECTIVE: Spinal meningiomas (SMs) are common primary spinal tumors for which surgery is considered the first-line treatment when safe and feasible. The ability to extrapolate the tumor grade from preoperative imaging may significantly inform early patient expectation-setting regarding recurrence. Building on radiomics studies in cranial meningiomas, the authors aimed to construct a benchmark radiomics model to preoperatively identify the histological grade of SMs. METHODS: Institutional surgical records from May 2012 to November 2025 were queried for pathology-confirmed meningiomas below the foramen magnum, with preoperative contrast-enhanced imaging available for segmentation. SMs were classified as low-grade (WHO grade 1) and high-grade (WHO grade 2 tumors and grade 1 tumors with atypia). Tumors were manually segmented, and features were extracted using the PyRadiomics software package. An ensemble model of k-nearest neighbors, random forest, and support vector machine classifiers was trained using nested cross-validation on a subset of 10 features to differentiate tumor grades. Clinical data for the cohort were also extracted, and disease control in an adjunctive clinical series was assessed. RESULTS: Seventy-four patients were included in radiomics analysis, with an area under the receiver operating characteristic curve of 0.879 and a mean F1 score of 0.748. The model's top 5 features were all texture features that differed significantly (p < 0.05) across low- and high-grade SMs. These included measures of tumor textural and contrast-enhancement heterogeneity, with overlap with features reported in radiomics models for histological grading of intracranial meningiomas. Fifty-five patients with a median radiographic follow-up of 22.2 (range 1.9-86.4) months remained for clinical analysis after exclusion of patients with less than 1 month of follow-up and syndromic meningiomas. Four recurrences occurred at a median of 20.8 (range 1.8-41.8) months. High-grade tumor pathology did not significantly impact progression-free survival (p = 0.682, log-rank test; Cox regression high vs low grade hazard ratio [HR] 0.62, 95% CI 0.06-6.11, p = 0.685). Subtotal resection was associated with poorer progression-free survival than gross-total resection (p = 0.004, log-rank test; Cox regression subtotal vs gross-total resection HR 10.62, 95% CI 1.46-77.05, p = 0.019). These findings remain contextualized within a relatively limited follow-up window and small recurrence event count, suggesting a need to characterize the interplay between tumor grade and extent of resection as drivers of local disease control in SMs. CONCLUSIONS: A preoperative radiomics model can stratify high-grade SMs using open-source tools applied to single-institution data.

Humans

Systematic evaluation of one-dimensional-to-two-dimensional near-infrared spectroscopy transformations with deep learning for quantifying coconut sap adulteration.

Near-infrared (NIR) spectroscopy have limitations when combined with deep learning (DL) algorithms because they rely on low-dimensional datasets. Therefore, we investigated the potential of transforming one-dimensional (1D) NIR spectra into two-dimensional (2D) spectrograms using synchronous and asynchronous techniques and the continuous wavelet transform (CWT) and their effectiveness by integrating with DL for detecting adulteration in coconut sap. NIR spectra (12,500-4000&#xa0;cm-1) were collected from binary mixtures (0%-100%;w/w). The performance of all DL (convolutional neural networks-CNN, AlexNet and ResNet) models was compared with that of partial least squares (PLS). The models were ranked in the mentioned order based on their performances: 2D-CWT&#xa0;>&#xa0;2D-asynchronous > 2D-synchronous > 1D/2D-PLS. The important features of the best model can be explained and visualized using gradient-weighted-class-activation-mapping. The findings highlight that the 1D-to-2D NIR data transformation combined with DL is a highly robust approach because it addresses the feature representation gap in NIR data and effectively captures the spatial-spectral correlations.

Spectroscopy, Near-Infrared

Differential contributions of mt-Tr and Cs variants to developmental cochlear defects and mitochondrial dysfunction in A/J mice.

A/J mice exhibit early-onset hearing loss linked to Cdh23, mitochondrial tRNA-Arg (mt-Tr), and citrate synthase (Cs) variants. Although developmental cochlear defects have been identified in juvenile A/J mice, the hierarchical contributions of mt-Tr versus Cs remain unclear. Using reciprocal intercross-derived strains to decouple mitochondrial haplotypes from nuclear factors, we demonstrate that the mitochondrial background is the primary determinant of auditory dysfunction. Mice with A/J mtDNA (AXB strains) displayed significantly higher ABR thresholds, accelerated hair cell attrition, and severe stereocilia dysmorphology compared to those with B6 mtDNA (BXA strains), occurring largely independently of the Cs genotype. While the Cs mutation exacerbated hearing loss, its impact was secondary to that of the dominant mitochondrial background. Systemic behavioral assessments and mitochondrial assays confirmed that A/J mitochondria exert a more profound metabolic impact than the Cs mutation. Our findings establish that the mitochondrial genomic background, with the mt-Tr locus as a prominent candidate variant, serves as the principal driver of developmental cochlear defects and early-onset hearing loss in A/J mice, while the nuclear Cs mutation acts as a synergistic modifier. This study underscores the critical role of mitonuclear crosstalk in inner ear maturation and provides new insights into the etiology of hereditary hearing loss.

Animals

Molecular mechanisms of neuroendocrine regulation of molting in the Chinese mitten crab (Eriocheir sinensis): A transcriptomic analysis based on eyestalk ablation model.

Molting disability severely restricts the sustainable aquaculture of the Chinese mitten crab, yet the neuroendocrine mechanisms coordinating physiological responses remain poorly understood. Using unilateral eyestalk ablation to remove the primary source of molt-inhibiting hormone (MIH), we performed time-resolved transcriptomic profiling of the thoracic ganglion at 24&#xa0;h (early premolt) and 48&#xa0;h (ecdysis) post-ablation. We identified 2825 differentially expressed genes and uncovered a biphasic molecular response. At 24&#xa0;h, the thoracic ganglion activates pathways associated with neuromuscular adaptation, oxidative stress, and cardiac muscle contraction. Notably, the arachidonic acid metabolism pathway is selectively rewired: cytochrome P450 &#x3c9;-hydroxylases (CYP2J2, CYP4V2) are upregulated, while competing branches (epoxide hydrolase, cyclooxygenase) are suppressed, promoting local synthesis of the potent vasoconstrictor 20-HETE within the thoracic ganglion. This enzymatic switch provides a mechanistic link between MIH withdrawal and the local generation of elevated hemolymph pressure required for molting. By 48&#xa0;h, the transcriptional program shifts toward chitin-based extracellular matrix remodeling, glycosphingolipid biosynthesis, and synaptic reorganization. Collectively, our findings redefine the thoracic ganglion as an active neuroendocrine integrator that translates reduced MIH signaling into phased physiological outputs, revealing a "neuro-endocrine-hemolymph pressure" regulatory axis. This study provides novel molecular targets (e.g., CYP2J2, CHS1, UGCG) for mitigating molting disability in E. sinensis aquaculture.

Animals

Genome-wide insights into the evolutionary and demographic history of the red alga Mazzaella laminarioides: Evidence for speciation with ancient migration along the southeast Pacific coast.

The mechanisms driving lineage divergence in red algae remain unexplored, despite the group's remarkable diversity and ancient evolutionary history. The red alga Mazzaella laminarioides, a Chilean intertidal species complex composed of three parapatric cryptic lineages (North, Center, South), offers a valuable system to evaluate these processes, as its life history combines severe dispersal limitation with a haploid-diploid cycle that may influence the emergence of reproductive barriers. We reconstructed its evolutionary history using whole-genome sequencing and nuclear genome assembly of representative individuals from each lineage. Phylogenomic analyses based on 1,507 single-copy orthologs recovered three deeply divergent lineages with limited nuclear discordance consistent with incomplete lineage sorting. For both splits, demographic modelling was most consistent with an Ancient Migration scenario, although support over strict isolation was moderate, suggesting that divergence may have begun with low asymmetric ancestral gene flow followed by subsequent loss of connectivity, demographic bottlenecks, and later population expansion. Coding sequence analyses revealed lineage-specific dN/dS heterogeneity; only one South-lineage locus passed FDR correction (metaxin-1, mitochondrial protein import), with two further South-lineage candidates in chlorophyll and heme biosynthesis falling below the FDR threshold. Together, these signals suggest that divergent selective pressures on energy acquisition may have contributed to divergence at the southern end of the distribution. These results add to the small but growing body of whole-genome data for red algae and, alongside recent macroalgal studies, suggest that ancestral connectivity could be a recurrent feature of lineage divergence even in marine organisms with extremely restricted dispersal.

Rhodophyta

Occupationally relevant vibrations and the brain: frequency-dependent proteomics signatures in a rat model.

INTRODUCTION: Occupational exposure to whole-body vibration (WBV), particularly in agricultural environments, has been associated with adverse cognitive and physiological effects. This study examined the neurophysiological impact of WBV in a rat model at 4&#x202f;Hz and 30&#x202f;Hz, frequencies representative of off-road and on-road vehicle operation. METHODOLOGY: Forty-four Sprague-Dawley rats were assigned to control (0&#x202f;Hz), low-frequency (4&#x202f;Hz), or high-frequency (30&#x202f;Hz) vibration conditions. After three days of exposure, brain tissues were collected and analyzed using mass spectrometry-based proteomics to identify differentially expressed proteins. RESULTS: Proteomic profiling revealed distinct, frequency-dependent alterations in brain protein expression. Compared with controls, 32 cognition-related proteins were differentially regulated at 4&#x202f;Hz and 29 at 30&#x202f;Hz, with 13 differing between the two vibration conditions. Principal component analysis showed clear separation among groups, indicating unique proteomic signatures for each exposure frequency. Functional enrichment and protein-protein interaction analyses demonstrated involvement of synaptic plasticity, cytoskeletal organization, calcium regulation, and neurotransmitter release. Exposure to 4 Hz was associated with the upregulation of proteins involved in calcium homeostasis and synaptic integrity, suggesting potential disruption of cognitive processes. In contrast, 30 Hz increased the expression of proteins related to axonal guidance and neuroprotection, indicating a less clearly adverse response that may reflect adaptive or potentially beneficial effects. DISCUSSION: These findings provide new insight into biological mechanisms underlying WBV-induced cognitive changes and underscore the importance of vibration frequency in shaping neurophysiological outcomes. They also establish a foundation for future studies integrating proteomics with behavioural assessments in animals and humans.

Animals

Muscle mechanical and architectural adaptations in response to different endurance training modalities in older adults.

INTRODUCTION: This study examined the effects of various cycling endurance training modalities, matched for total workload, on muscle mechanical and architectural characteristics in older adults. METHODS: Fifty healthy participants (25 females, 59-79&#xa0;yrs) were randomly assigned to five age and sex matched groups: one control and four workload-matched training groups (moderate-intensity continuous, heavy-intensity continuous, high-intensity interval, and heavy-intensity continuous in eccentric cycling). Training consisted of three weekly sessions over 8&#xa0;weeks, with evaluations conducted at the beginning and end of the intervention with maximal voluntary isometric contractions at five different knee angles (90, 75, 60, 45, 30&#xb0;) and maximal concentric and eccentric isokinetic contractions at five different knee angular velocities (45, 90, 150, 210, 250&#xb0;/s). Maximum voluntary isometric torque (Tmax) and optimal knee angle (KAopt) were obtained from the isometric contractions; eccentric torque (Tecc) and maximum concentric knee angular velocity (Vmax) were obtained from the isokinetic contractions. The muscle architecture of vastus lateralis (VL) at rest (muscle thickness, pennation angle, and fascicle length) was investigated as well. RESULTS: No statistical differences were detected between groups or time points in VL architecture, in KAopt and in Vmax. A main effect of time was observed for Tmax (p&#xa0;<&#xa0;0.001, &#x3b7;2p&#xa0;=&#xa0;0.458) and Tecc (p&#xa0;=&#xa0;0.002, &#x3b7;2p&#xa0;=&#xa0;0.191) in all the investigated training groups. The within-group comparisons indicate significant increases in Tmax in the training groups, but not in the control group. CONCLUSIONS: Commonly applied endurance exercises improve muscle mechanical capacity (Tmax and Tecc) in older adults, with no structural (architectural) muscle remodelling, when matched for workload.

Humans

TNF-NF-&#x3ba;B signaling mediates immune-biomineralization crosstalk during shell repair under ocean acidification in Mytilus edulis.

Ocean acidification (OA) impairs biomineralization in bivalves, but its effects on immune-biomineralization crosstalk during shell repair remain unknown. Here, we exposed adult Mytilus edulis bearing standardized shell perforations to three pH levels (8.1, 7.9, and 7.7) for up to 40 days. OA slowed early repair and caused microstructural disorganization and an approximately 87% reduction of compressive strength at pH 7.7, yet the damaged area appeared largely closed by day 15, suggesting a decoupling between morphological closure and functional recovery. In addition, transcriptomic profiling of hemocytes and mantle tissue, based on an average of 6.5&#x202f;Gb of clean reads per sample mapped to the M. edulis reference genome (NCBI Assembly GCF_000511035.1), revealed that these shell-level defects were accompanied by coordinated immune and metabolic reprogramming. Hemocytes, the primary immune effector cells of bivalves, exhibited pH- and time-dependent shifts with moderate acidification (pH 7.9) promoting inflammatory transcripts, whereas severe acidification (pH 7.7) suppressed these signals while upregulating stress-associated pathways; both treatments consistently downregulated lysosomal proteases and NF-&#x3ba;B negative regulators. The mantle, a primarily mineralizing organ, paradoxically upregulated immune-related genes while suppressing oxidative phosphorylation and extracellular matrix pathways. This tissue-level imbalance, with hemocytes recruited but functionally constrained and mantle metabolically suppressed yet immunologically activated, points to TNF-NF-&#x3ba;B pathway modulation as a key mediator of shell repair under acidification. Our findings demonstrate that visible shell closure masks underlying structural and mechanical failure, and that immune regulation, rather than simple suppression or activation, critically shapes the repair outcome. These results advocate for multifunctional indicators beyond closure area to assess shell integrity in acidified marine environments.

Animals

Can ChatGPT Replace Human Clinical Coders? A Comparative Study in Otology Billing.

OBJECTIVE: Evaluate the utility of the large language model (LLM), ChatGPT, for the analysis of operative notes and the generation of Current Procedural Terminology (CPT) codes in comparison to human clinical coders. STUDY DESIGN: CPT billing codes assigned by ChatGPT were compared to existing billing data. Otology practice within a tertiary academic center. METHODS: About 191 operative notes from a single surgeon (9/2022-10/2023) were analyzed. ChatGPT-3.5 and 4 models were prompted for CPT codes based on operative notes. Assessment included determining exact and partial match rates, sensitivity and specificity for targeted procedures, and work Relative Value Units (wRVU) differences between ChatGPT-generated and human-assigned codes. RESULTS: ChatGPT-3.5 achieved exact matches in 22% of cases and partial matches in 32%, while ChatGPT-4 achieved 14% exact and 33% partial matches. When cochlear implantation (CI) was excluded, performance dropped significantly. For CI, ChatGPT-3.5 demonstrated a sensitivity of 94% and specificity of 90%, while ChatGPT-4 showed a sensitivity of 96% and specificity of 92%. In contrast, performance on cartilage grafting was poor, with sensitivities of 4.2% for ChatGPT-3.5 and 0% for ChatGPT-4. ChatGPT-3.5 and 4 showed moderate CPT code matching accuracy among themselves, with slight agreement to human coders. Both models tended to underbill for wRVUs compared to human coders, with significant differences in the values generated. CONCLUSION: This study assessed ChatGPT's effectiveness in automating CPT code assignment for otologic surgeries. While the models achieved high sensitivity values for assigning codes related to cochlear implantation, both models struggled with complex cases, failed to apply modifiers, and often assigned fewer wRVUs. The findings highlight ChatGPT's potential in medical billing but indicate a need for further refinement.

Humans

Interface-dependent V. parahaemolyticus biofilm under varying temperatures, media, and oxygen conditions: implications for seafood safety.

Vibrio parahaemolyticus biofilms play a critical role in pathogen persistence in marine and seafood-processing environments, where oxygen availability, temperature, and surface interfaces vary widely. This study investigated biofilm development by three strains on partially submerged stainless-steel coupons under gas-liquid-wall (GLW) and fully submerged (SM) interfaces. Viable cell counts (log&#x2081;&#x2080;CFU/cm2) along with normalized protein concentration per viable cell (nProt) and normalized polysaccharide concentration per viable cell (nPol) were measured, under aerobic and anaerobic conditions across a temperature range of 15-30&#xa0;&#xb0;C, using tryptic soy broth with 3% NaCl (TSB) and seawater-based medium (SW). GLW biofilms consistently exhibited higher cell counts (6.4-7.3 log&#x2081;&#x2080;CFU/cm2) compared to SM biofilms (5.9-6.3 log&#x2081;&#x2080;CFU/cm2), suggesting that enhanced oxygen diffusion promotes bacterial proliferation. Conversely, SM biofilms exhibited significantly higher nProt and nPol levels (p&#xa0;<&#xa0;0.001), indicating increased production of the extracellular polymeric substance (EPS) matrix under low-oxygen, high-nutrient conditions. Microscopy and three-dimensional surface plot analyses revealed relatively uniform biofilm layers at the GLW interface, whereas SM biofilms formed heterogeneous, tower-like structures. EPS production was further influenced by medium composition, oxygen, and temperature. SM biofilms grown in SW exhibited significantly higher nProt and nPol than those in TSB under aerobic conditions (p&#xa0;<&#xa0;0.001), indicating enhanced matrix stabilization. Under anaerobic conditions at 15&#xa0;&#xb0;C, nProt and nPol were higher, whereas under aerobic conditions, peak nProt and nPol occurred at elevated temperatures. These findings highlight a trade-off between bacterial growth and matrix production and provide insight into biofilm adaptation and persistence in seafood-processing environments. These insights may help develop improved biofilm control and seafood safety management.

Biofilms

Challenges and future directions in AI-driven biomaterials for microbiome-associated oral infectious diseases: A systematic review.

Oral biofilm-induced antimicrobial resistance is the core pathogenic mechanism of microbiome-associated oral infectious diseases (dental caries, periodontitis, peri-implantitis, and endodontic infection). Traditional therapies and biomaterials are limited by poor biofilm penetration, drug resistance induction, single functionality, and inadequate adaptation to dynamic oral microenvironmental changes (e.g., pH fluctuations, salivary rinsing, masticatory stimulation). Artificial intelligence (AI) has transformed the field by integrating materials science, microbiology, and stomatology data. Via machine learning, deep learning, and multi-physics simulation, AI optimizes biomaterial physicochemical properties, decodes microenvironmental signals, constructs precise sensing-response loops, and supports the full chain of material design, performance prediction, and action simulation, advancing treatment from empirical intervention to precision regulation. This systematic review retrieved literature from PubMed, Embase, and Web of Science (January 2016-January 2026) using keywords across three dimensions: AI, biomaterials, and oral microbiome. Following inclusion/exclusion criteria, 99 articles were included. It elaborates on five core mechanisms of AI-driven oral biomaterials (precise oral microbiome analysis, targeted material design/optimization, performance prediction/simulation, targeted delivery/intervention, effect evaluation/dynamic regulation), analyzes their applications in microbiome-targeted biomaterial research and development (R&D) and clinical practice for the four major oral infectious diseases, addresses technical bottlenecks (insufficient targeting specificity and precision of biomaterials, poor stability and durability in complex oral microenvironments, inadequate biofilm disruption capacity, and clinical translation obstacles), and proposes future directions (multimodal design to enhance targeting specificity, structural and component optimization to improve stability/durability, development of multi-mechanism synergistic biofilm disruption strategies, strengthening translational research for clinical application, and deep integration of AI in the full chain of biomaterial R&D). This work provides comprehensive theoretical and practical support for the R&D, optimization, and clinical translation of AI-driven microbiome-targeted oral biomaterials.

Humans

A Qualitative Analysis of Cancer Survivors' Experience in a Time-Restricted Eating vs Control Clinical Trial to Address Cancer-Related Fatigue.

PURPOSE: To describe cancer survivors' lived experiences in a clinical trial that tested an individualized nutrition counseling with or without time-restricted eating to address cancer-related fatigue. METHODS: The Fatigue REDuction After cancer study was a two-arm, randomized controlled trial. Participants were adult cancer survivors who were 2 months to 2 years post-treatment. All participants received individualized nutrition counseling; those in the time-restricted eating group self-selected a consistent 10-hour eating window for 12 weeks. After the study, semi-structured exit interviews were conducted to gauge participants' experiences in the trial. Interviews were transcribed and two independent coders thematically analyzed the interviews using inductive and deductive coding. NVivo software was used for data organization and analysis. RESULTS: Participants (n&#x202f;=&#x202f;24; TRE&#x202f;=&#x202f;11; Control&#x202f;=&#x202f;13) were 55 &#xb1; 13 years old, 75% were female, and they had a variety of cancer types. The majority of participants found that being in the study helped them to set and achieve lifestyle goals and would therefore recommend the study to others. Participants in the time-restricted eating group noted that time-restricted eating helped them set a better routine, providing a positive sense of control. However, some noted difficulty switching to a 14-hour fasting schedule, as it can interfere with their regular routine or employment schedules. Many participants noted they were happy that cancer-related fatigue was gaining more attention, hoping to find solutions for persistent cancer-related fatigue. CONCLUSION: The majority of participants found the study useful and, regardless of their group assignment or the intervention's impact on their fatigue, found the study helped them to gain better control of their dietary habits.

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

ESC quality indicators for post-myocardial infarction care: transition and chronic coronary syndrome phases.

AIMS: We aimed to develop the European Society of Cardiology (ESC) quality indicators (QIs) for myocardial infarction (MI), from 1 year after hospital discharge, corresponding to transition to the chronic coronary syndrome phases. METHODS AND RESULTS: We collaborated with the European Association of Preventive Cardiology (EAPC) and developed QIs for the long-term management of patients following MI. We applied the ESC methodology for QI development by (i) determining key domains of post-MI care; (ii) developing candidate QIs by performing a systematic review of the literature, and (iii) selecting the final set of QIs using a modified Delphi approach. In total, 18 QIs were identified across seven domains of care including (i) structural framework, (ii) risk assessment and follow-up, (iii) pharmacological management, (iv) rehabilitation, behavioural, and preventive interventions, (v) coronary revascularization, (vi) clinical outcomes, and (vii) patient-reported outcomes. CONCLUSION: We present the ESC QIs from 1 year after hospitalization for MI, to standardize and address gaps in care for this high-risk group. These QIs are supported by evidence from contemporary literature, endorsed by expert consensus, and aligned with the 2024 ESC guidelines on the management of chronic coronary syndromes. LAY SUMMARY: Measures to evaluate and improve the long-term management of patients following a heart attack are needed. In this paper, we identified key aspects of care that can help clinicians, decision-makers and patients improve the quality of care, from one year after a heart attack onwards, and help address inequalities and variations in clinical practice.

Humans

Putting Globus Into Context: Prevalence, Characteristics, and Overlap With Other Disorders of Gut-Brain Interaction.

OBJECTIVE: Globus is characterized by the sensation of a lump in the throat without dysphagia or underlying structural abnormality or major motility disorder. Reported prevalences vary considerably across studies. Globus has been linked to both heartburn and affective disorders. This study aims to determine the global prevalence of globus, its association with heartburn, overlap with disorders of gut-brain interaction (DGBI) and psychosocial disorders, and its impact on health-related quality of life (HRQOL). METHODS: Internet surveys from the Rome Foundation Global Epidemiology study were used (N&#xa0;=&#xa0;54,127). Rome IV criteria were used to identify globus and concurrent DGBI. Heartburn was defined as symptoms &#x2265; 2-3&#xa0;days/week. Psychosocial co-morbidity and somatic symptom severity were assessed with PHQ-4 and PHQ-15, and HRQOL by PROMIS-10. RESULTS: The global prevalence of globus according to Rome IV criteria was 0.75%, representing 12.8% of esophageal DGBI and 1.86% of all DGBI. Prevalence was highest in Western Europe (0.94%) and Asia (0.90%), and lowest in the Middle East (0.31%). Globus was slightly more common in females (55.4%), and most affected individuals were aged between 40 and 64&#xa0;years (46.6%). Coexisting heartburn was reported in 17.4% of cases, esophageal DGBI in 9.1%, and non-esophageal DGBI in 49.0%. Anxiety and/or depression was present in 60.5%. CONCLUSION: Global prevalence of globus is 0.75%, with a slight female predominance, and is most prevalent below 65&#xa0;years. Overlap with non-esophageal DGBI was greater than with heartburn symptoms or esophageal DGBI, and most patients had anxiety and/or depressive symptoms.

Humans

Nurse-led attribution remodeling training based on the Neuman systems model to enhance resilience, adaptive coping, and attributional style in women newly diagnosed with breast cancer: A randomized controlled trial.

BACKGROUND: Psychological interventions for patients with breast cancer often overlook the critical role of maladaptive attributional style in shaping their adjustment. Therefore, the need for theory-driven, scalable interventions that target cognitive restructuring, particularly during the vulnerable post-diagnosis period, is clear. OBJECTIVE: To evaluate the effectiveness of a nurse-led attribution remodeling training intervention grounded in the Neuman systems model for improving resilience, adaptive coping, and attributional style among women newly diagnosed with breast cancer. DESIGN: A randomized controlled trial. SETTING: A tertiary general hospital. PARTICIPANTS: A total of 130 eligible women newly diagnosed with breast cancer were recruited between March and November 2024. METHODS: A two-arm parallel-group randomized controlled trial was conducted. Participants were randomly assigned to receive either attribution remodeling training plus routine nursing (n&#xa0;=&#xa0;65) or routine nursing only (n&#xa0;=&#xa0;65). The nurse-led attribution remodeling training intervention, delivered via a blended model of in-person sessions and continued support through the WeChat mobile platform, was designed to systematically reshape maladaptive attributions into more adaptive ones. Resilience (primary indicator), coping strategy (i.e., confrontation, avoidance, resignation), and attributional style (secondary indicators) were assessed at baseline and at 1, 3, and 6&#xa0;months post-baseline. A linear mixed model was used to analyze the effects of group, time, and group-by-time interactions. Effect sizes (Cohen's D) were calculated based on the means and standard deviations. RESULTS: At the 6-month follow-up, the intervention group had better outcomes than the control group in terms of resilience (mean difference: 1.49, 95% confidence interval: 0.37, 2.61), confrontation coping (3.35 [2.33, 4.37]), and adaptive attributional style (4.16 [3.87, 4.45]). Avoidance coping showed a small increase (0.82 [0.22, 1.42]), whereas resignation coping decreased (-1.66 [-2.49, -0.83]). Group effects and group-by-time interactions were statistically significant for all outcomes. Effect sizes at 6&#xa0;months ranged from small for resilience (D&#xa0;=&#xa0;0.28) and avoidance coping (D&#xa0;=&#xa0;0.26) to moderate for confrontation coping (D&#xa0;=&#xa0;0.60) and resignation coping reduction (D&#xa0;=&#xa0;-0.51), and large for attributional style (D&#xa0;=&#xa0;0.94). CONCLUSIONS: Attribution remodeling training is a promising and effective theory-based intervention that can enhance psychological adaptation in women newly diagnosed with breast cancer. By strengthening key defense mechanisms, as conceptualized by the Neuman systems model, the program is effective, scalable, and nurse-deliverable for psycho-oncology care, bridging a critical gap in supportive cancer care and empowering nurses as primary psychological support providers. REGISTRATION: ChiCTR2000031827, registered prospectively on April 11, 2020, www.Chictr.or.cn.

Humans

A systematic review and network meta-analysis of single nucleotide polymorphisms associated with oral submucous fibrosis risk.

BACKGROUND: Oral submucous fibrosis (OSF) is a chronic and insidious oral disease characterized by hyalinization of the subepithelial connective tissue and progressive fibrosis of the oral submucosa. It is a precancerous condition of oral squamous cell carcinoma. Studies have demonstrated that single nucleotide polymorphisms (SNPs) are closely associated with susceptibility to OSF. This study aims to comprehensively evaluate the association between SNPs and OSF risk and to rank the strength of the association between different genetic models and OSF susceptibility. METHODS: Literature related to OSF was comprehensively searched from PubMed, Web of Science, Embase, Cochrane Library, CNKI, and Wangfang databases up to July 2025. Full-text case-control studies with patients diagnosed with OSF were included. Quality assessment was performed to evaluate the risk of bias. RevMan 5.4, GeMTC 0.14.3, and STATA 17.0 were used for the pairwise and Bayesian network meta-analysis. RESULTS: A total of 24 studies with 2545 cases and 3772 controls, covering 13 SNPs in 11 genes, were included in our meta-analysis. We found that CYP1A1 rs4646903:T>C, CYP1A1 rs1048943:A>G, GSTT1 null genotype, GSTM1 null genotype, and XRCC3 rs861539:C>T were associated with an increased risk of OSF, while MMP2 rs243865:C>T and MMP3 rs3025058: 5A>6A were associated with a decreased risk of OSF. Further Bayesian network meta-analysis indicated the top 5 genetic models with the highest association with OSF risk in network group 1 were the dominant model, homozygous model, allelic model, and recessive model of CYP1A1 rs1048943:A>G (ranked 1-4), and the heterozygous/dominant model of CYP1A1 rs4646903:T>C (both ranked 5). While the allelic models of XRCC3 rs861539:C>T and MMP3 rs3025058: 5A>6A ranked first for predicting OSF in group 2 and group 3, respectively. CONCLUSION: Some specific SNPs are significantly related to the risk of OSF. Among them, the dominant model of CYP1A1 rs1048943:A>G may be the most strongly associated genetic model with OSF risk. Future large-sample, well-designed studies with detailed genotype data are needed to validate the roles of these SNPs in OSF risk.

Humans