Non-communicable diseases (NCDs), such as hypertension, are amongst the most fatal conditions afflicting people living in low- and middle-income countries (LMIC), including Bangladesh. This study addresses the lack of population-based studies in rural Bangladesh by examining the prevalence and distribution of hypertension and its associated risk factors. To this end, we surveyed adults aged ≥18 years (i.e., household heads and their spouses) from 7384 households across 149 villages in rural Bangladesh in 2017 using a semi-structured questionnaire to collect data on blood pressure, anthropometric, socioeconomic, lifestyle, and behavioral risk factors. Multivariate logistic regression analyses identified age, gender, and socioeconomic status as potential predictors of hypertension. The findings also showed that men and women from higher socioeconomic status (SES) groups had higher rates of overweight and obesity, risk factors for the development of hypertension (4.29% and 1.4% in adult men; 5.8% and 2.29% in adult women), as well as higher rates of fruit and vegetable consumption (10.29% and 7.25% in adult men; 9.95% and 6.84% in adult women). A significant association between tobacco consumption and age was observed for women (p=<0.0001), while higher levels of physical activity were found among men aged 45-54 years [OR:1.9, CI 95% (1.1-3.1)]. Furthermore, women in the highest SES brackets were 1.3 times as likely to engage in "moderate" physical activity as those in the lowest brackets. Age and overweight/obesity were found to be the strongest risk factors for hypertension in both genders, while education was not found to be significantly associated with hypertension in women. Notably, the findings revealed that 33.7% of men and 28.6% of women had elevated blood pressure, qualifying them as either prehypertensive or hypertensive. As such, we recommend that policy interventions aimed at stemming the growth of hypertension among Bangladesh's rural populations should take gender-specific risk factors, rural-urban disparities, and socioeconomic context into serious policy consideration.

Transitioning to university is a critical period marked by lifestyle changes, academic pressures, and increasing autonomy, which can influence students' overall well-being. Previous research suggests that unhealthy lifestyle behaviors-including poor diet, insufficient physical activity, inadequate sleep, and ineffective stress management-may negatively impact life satisfaction among young adults.

This cross-sectional study examined the relationship between lifestyle and life satisfaction among newly enrolled undergraduate students at Tehran University of Medical Sciences in 2024. Participants completed structured questionnaires assessing multiple lifestyle domains (diet, physical activity, sleep, smoking, alcohol use) and life satisfaction using validated Iranian questionnaires. Lifestyle scores were categorized as "healthy" or "unhealthy," and life satisfaction as "good" or "poor." Associations were analyzed using Pearson's chi-square test and multivariable logistic regression, adjusting for age, sex, socioeconomic status, and anxiety.

Overall, of the 419 students, 294 (70.2%) reported good life satisfaction. Socioeconomic status and anxiety levels differed significantly across life satisfaction groups (p < 0.001). Students with healthier dietary patterns reported higher life satisfaction (76.6% vs. 60.4%, p = 0.02). Multivariable analysis indicated that students with healthy lifestyles had significantly higher odds of good life satisfaction compared to those with unhealthy lifestyles (adjusted odds ratio [aOR = 1.91; 95% confidence interval [CI]: 1.10,3.35; p = 0.02). Each one-unit increase in lifestyle score was associated with a 28% increase in the odds of good life satisfaction (aOR = 1.28; 95% CI: 1.05,1.57; p = 0.02).

Unhealthy lifestyle behaviors are negatively associated with life satisfaction among new university students. Interventions promoting balanced nutrition, regular physical activity, adequate sleep, and overall health-conscious behaviors may enhance students' life satisfaction and well-being.

NK cells exhibit inherently short persistence in vivo. Allo-NK cells trigger host immune rejection in immune-competent patients. Lymphodepletion is a conventional approach for mitigating allogeneic rejection of therapeutic NK cells, which brings host immune suppression and infection risks. To address these problems, we test the concept of engrafting iNK progenitor (iNKP) cells derived from human induced pluripotent stem cells (iPSC) to achieve generating iNK cells in vivo in unconditioned host-immune humanised mice without the requirement for prior lymphodepleting chemotherapy or total body irradiation. Our results showed that a single low-dose infusion of iNKP cells successfully engrafted and continuously produced mature iNK cells in unconditioned B-NDG hIL15 mice. Furthermore, the iPSC-derived iNKP cells survived in the presence of autologous PBMC-humanised mice and generated mature iNK cells. This study provides evidence that autologous iPSC-derived iNKP cells have the application potential for treating the same individual without the preceding necessity of lymphodepletion.

Inappropriate empirical antimicrobial therapy (IEAT) significantly increases mortality in patients with resistant Gram-negative bacteremia. We developed a multitask machine learning framework to predict carbapenem resistance (CR), β-lactam/β-lactamase inhibitor combinations resistance (BL/BLI-R), and third-/fourth-generation cephalosporins resistance (3GC/4GC-R) in HM patients with monomicrobial BSIs caused specifically by Escherichia coli, Klebsiella pneumoniae, or Enterobacter cloacae.

Using retrospective data from 1,353 HM patients with three specific Enterobacterales BSIs (2017-2023), we trained support vector machines, eXtreme Gradient Boosting, and logistic regression models through 5-fold cross-validation with hyperparameter tuning and conducting internal validation via bootstrap. Model thresholds were optimized via Pareto front analysis to minimized IEAT and carbapenem use while maximizing sensitivity.

The models achieved AUCs of 0.81 (95% CI, 0.78-0.85) for CR model, 0.81 (95% CI, 0.77-0.84) for BL/BLI-R model, and 0.72 (95% CI, 0.68-0.76) for 3GC/4GC-R model before optimization. Threshold optimization improved sensitivity for CR prediction increased from 0.10 to 0.77, for BL/BLI-R prediction from 0.19 to 0.94, and for 3GC/4GC-R prediction from 0.54 to 0.98. SHAP analysis identified key predictors including prolonged neutropenia, prior carbapenem exposure, and tumor consolidation stage. Integrating pathogen species enhanced 3GC/4GC-R prediction (AUC 0.72 vs. 0.76). Clinically, by employing the threshold optimization strategy, the model successfully reduced empirical carbapenem use from 71.7% to 32.1% without increasing the rate of IEAT compared to clinical practice (4.0% vs. 6.11%).

This multitask framework supports resistance prediction in HM patients with monomicrobial BSIs due to three specific Enterobacterales species, mainly used to assist clinical decision-making after pathogen identification and strongly suspected infection with one of the three pathogens. Prospective validation is required before clinical application.

Radiotherapy remains a cornerstone in the clinical management of malignancies, leveraging DNA damage and oxidative stress to eradicate tumor cells. Nonetheless, the emergence of intrinsic and acquired radioresistance significantly compromises its therapeutic efficacy. While nanomedicine has substantially advanced radiosensitization strategies, the existing literature has largely focused on physical dose enhancement or conventional apoptosis, and the systematic reprogramming of diverse cell death modes beyond conventional apoptosis in the radiotherapy context has received less systematic attention. The present review provides a cross‑pathway synthesis of how engineered nanomaterials redirect tumor cell fate beyond apoptosis to achieve next‑generation radiosensitization, while also identifying the specific limitations and knowledge gaps that currently impede progress in this rapidly evolving field. We first delineate the hierarchical sensitization mechanisms, beginning with physical energy deposition via high-Z elements, followed by chemical amplification of reactive oxygen species through nanozyme catalysis, and biological intervention in the "6R" principles of radiobiology. Crucially, we evaluate the potential capacity of advanced nanomaterials to bypass conventional apoptotic resistance by triggering ferroptosis, pyroptosis, cuproptosis, disulfidptosis, and other emerging programmed death pathways, with a focus on the current evidence base and remaining preclinical and translational challenges. Beyond localized cytotoxicity, we highlight the mechanistic potential of nanomedicine to induce immunogenic cell death and activate the cGAS-STING pathway, suggesting a possible framework for transforming RT into an "in situ vaccine" that could reshape the immunosuppressive TME. Furthermore, we discuss the clinical translation of landmark nano-radiosensitizers, such as NBTXR3 and AGuIX, while critically addressing fundamental bottlenecks in targeting efficiency, biodistribution, and biosafety. By synthesizing current trends and future perspectives, this review contributes a strategic roadmap for advancing the design of next-generation, intelligent nanoplatforms toward more precise and systemic radiosensitization.

We aimed to examine the panoramic cellular composition and spatial structure of clinical samples from nonalcoholic fatty liver disease-associated hepatocellular carcinoma (NAFLD-HCC), assess the landscape of the tumor microenvironment (TME) and identify potential clinical biomarkers for prognosis.

Imaging mass cytometry (IMC) technology was used to analyze biomarker expression and spatial distribution in samples from 56 patients with NAFLD-HCC. Thirty-seven distinct metal-conjugated antibodies were designed to label the tumor, border and adjacent tissue regions, producing 367 highly multiplexed histological images at single-cell resolution. By combining biomarker expression levels with relative cell positional relationships, we defined functional units as tightly interacting cellular neighborhoods (CNs). Univariate and multivariate Cox regression models were employed to identify independent risk factors for prognosis assessment in patients with NAFLD-HCC on the basis of the proportion of CNs and other conventional clinical indicators.

Eighteen clusters of cells and 9 CNs were defined. Heterogeneity in the TME and CN composition was observed not only across various regions within the same individual but also among comparable regions in different patients. Overall survival data revealed that patients with high enrichment of GPC3⁺/YAP⁺ cancer cell-associated CNs had poor clinical prognoses.

Our study provides a landscape of NAFLD-HCC and its TME characteristics from a topological perspective. These findings indicate that targeting GPC3⁺/YAP⁺ cancer cells may improve the long-term prognosis of patients with NAFLD-HCC.

Acquired resistance to oxaliplatin limits the efficacy of first-line chemotherapy in colorectal cancer (CRC), yet the stress-responsive signaling mechanisms that enable tumor cells to adapt to platinum-induced DNA damage remain incompletely understood. CD55, a glycosylphosphatidylinositol-anchored complement regulator, has recently been implicated in non-canonical cellular stress signaling beyond its classical immune-modulatory role. Here, we investigated whether stress-induced CD55 signaling contributes to oxaliplatin resistance by modulating DNA damage response and repair capacity.

Oxaliplatin-resistant CRC cell lines were established through stepwise dose escalation. RNA sequencing with cross-validation against public datasets was used to identify candidate resistance genes. CD55 function was assessed using knockdown and overexpression approaches across seven CRC cell lines. Clinical correlations were evaluated using TCGA and GEO datasets. Homologous recombination (HR) capacity was measured using the DR-GFP reporter system, and DNA damage dynamics were assessed by γ-H2AX foci formation and comet assays. Drug interactions between oxaliplatin and PARP inhibitors were analyzed using the Chou-Talalay method. In vivo efficacy was evaluated in xenograft models.

CD55 was consistently upregulated in oxaliplatin-resistant CRC cells across three independent datasets and was induced by oxaliplatin treatment in a dose- and time-dependent manner, with stress-associated nuclear translocation observed following DNA damage. CD55 depletion sensitized all seven CRC cell lines to oxaliplatin (approximately 1.2- to 5.4-fold), with at least one siRNA reaching statistical significance in every line, irrespective of microsatellite instability or p53 status. In patient cohorts, elevated CD55 expression predicted poor response to FOLFOX therapy and independently correlated with reduced disease-free survival (hazard ratio = 3.47). Mechanistically, CD55 expression inversely correlated with genomic instability markers, and CD55 depletion significantly reduced HR efficiency in both parental and oxaliplatin-resistant CRC cells (~ 40-46% reduction), impaired BRCA1 induction, and prolonged γ-H2AX accumulation. In oxaliplatin-resistant cells, CD55 depletion converted the antagonistic oxaliplatin-olaparib interaction toward synergy in a dose-ratio-dependent manner (synergistic at 3:1 and 1:3, additive at 1:1; mean CI 0.58-0.95), reaching significance at the 3:1 ratio (P = 0.025). In xenograft models, CD55 depletion combined with dual-agent treatment reduced tumor burden by 62.8% in HCT116-OXR and consistently across all treatment arms in HT29-OXR.

CD55 acts as a stress-responsive signaling regulator that partially supports homologous recombination capacity under genotoxic stress and promotes oxaliplatin resistance in CRC. These findings identify CD55 as both a predictive biomarker and a therapeutic vulnerability, and demonstrate that CD55 depletion can induce a partial HR impairment - operationally described as a "BRCAness-like" state - that is sufficient to sensitize HR-proficient tumors to PARP inhibition, thereby expanding the potential utility of PARP inhibitor-based combination strategies.

Laparoscopic liver resection (LLR) is challenging due to the complex and variable intrahepatic vascular anatomy, limited surgical field of view, and lack of tactile feedback, which collectively increase the risk of intraoperative injury. Accurate identification of anatomical structures is therefore essential for safe LLR. This study explores Vivim, a video segmentation model based on the Mamba architecture-a state-space model that integrates the long-range dependency modeling of transformers with the efficiency of recurrent networks. Evaluated on a multicenter dataset of 15,865 annotated frames from 45 videos, Vivim outperformed several image-based and video-based baselines, including U-Net, DeepLab v3 + , nnU-Net, FPN + EfficientNetV2-L, SegFormer, ConvLSTM-U-Net, ViViT and SegFormer + T-Mamba, in segmenting the Glissonean pedicle (GP) and hepatic vein (HV). By leveraging Mamba's selective scanning and linear complexity, Vivim achieved Dice scores of 0.71 and 0.66 in single- and multi-target segmentation tasks, respectively, while maintaining real-time inference at 25 fps. The model demonstrated strong generalization on a cross-center external test set and robustness to typical surgical challenges. Clinically validated by 13 surgeons, Vivim improved recognition speed and accuracy, aiding intraoperative decision-making. Despite difficulties in differentiating similar vessels, this Mamba-based framework represents a promising step toward AI-assisted surgical navigation, bridging laboratory precision and clinical reliability.

Pathology vision-language models (VLMs) are promising for building the clinical decision support systems. However, a key barrier to real-world clinical deployment lies in the lack of rigorous and clinically meaningful model evaluation. Existing pathology visual question answering (VQA) benchmarks exhibit the weak alignment of vision-language information, insufficient support for knowledge-intensive reasoning, and a narrow disease spectrum, thereby undermining the ability to provide clinical-level evaluation of model performance. In this work, we introduce OmniPathoVQA, a new pathology VQA benchmark offering a broad disease coverage, spanning all human anatomical systems, and thousands of disease entities. To enhance well-organized visual-language alignment, we leverage pathology educational materials and design a fine-grained extraction pipeline for linking pathology images with the correct knowledge. To examine the knowledge depth for pathological reasoning, the hard-version questions are designed based on microanatomic features underlying similar diseases. A comprehensive evaluation of eighteen VLMs reveals that closed-source VLMs attain higher scores compared to open-source counterparts, yet their performance drops dramatically in difficult questions. We find that strong general reasoning ability is a crucial catalyst for the successful fine-tuning and pathology feature interpretation. Our study establishes a rigorous standard for assessing high-level reasoning and guiding the rapid development of clinical pathology VLMs.

Cancer-related fatigue (CRF) is a prevalent and distressing symptom that persist long after treatment, significantly diminishing the quality of life in cancer survivors-particularly those with gastrointestinal (GI) malignancies.

This study aimed to evaluate the prevalence and severity of CRF one year after treatment and to examine its associations with demographic and clinical characteristics in patients with non-metastatic GI cancers.

In this observational cross-sectional study, 103 patients with non-metastatic GI cancers who had completed treatment at least 12 months prior were recruited from Besat Hospital and Mahdieh Radiotherapy Center in Hamadan between 2020 and 2021 using a census sampling method. Fatigue was assessed with the Brief Fatigue Inventory (BFI-10), and associations with demographic variables, cancer stage, tumor site, and treatment type were analyzed using SPSS version 26.

The mean age of participants was 60.43 ± 10.52 years, and the average disease duration was 3.28 ± 0.45 years. The mean fatigue score was 5.63 ± 2.61 on a 0-10 scale. Most participants were male (51.5%), married (85.4%), had less than a high school education (49.5%), and were self-employed (57.5%). Rectal cancer was the most common diagnosis (53.4%), with the majority of patients diagnosed at stage III (68%). Fatigue severity was classified as mild in 26.2%, moderate in 34.0%, and severe in 39.8% of patients. Higher fatigue severity was significantly associated with female gender, advanced disease stage (stage III), and lower educational level (P < 0.05). No significant associations were found with age, disease duration, marital status, occupation, tumor location, or treatment type.

A considerable proportion of patients with non-metastatic GI cancers continue to experience moderate to severe CRF one year post-treatment. The greater fatigue burden among women and those with advanced-stage disease underscores the importance of routine fatigue assessment and targeted supportive care interventions for these at-risk populations.