Browse Articles

The role of chest X-ray in tuberculosis detection for high school students in China: a cross-sectional study

A novel prognostic model for lung squamous cell carcinoma based on multi-omics analysis and machine learning

Lung squamous-cell carcinoma (LUSC) is a highly aggressive malignancy with a poor prognosis. Tertiary lymphoid structures (TLS) play a crucial role in the immune response and significantly influence the efficacy of immunotherapy. However, the prognostic and immunological implications of TLS-associated molecular subtypes in LUSC remain unclear. In this study, we applied 10 multi-omics integration strategies to perform a multi-omics analysis of the mRNA expression profiles, DNA methylation, and genomic mutation data of 39 TLSs-related genes, along with long non-coding RNA (lncRNA) expression profiles, to generate integrated consensus subtypes of LUSC. Four molecular subtypes were identified: cancer subtype 1 (CS1), CS2, CS3, and CS4. We observed a significant difference in overall survival between cancer subtype 1 (CS1) and CS3. Subsequently, we identified 33 prognosis-related genes based on differential expression between CS1 and CS3, which were further refined to 20 genes using the least absolute shrinkage and selection operator (LASSO) regression algorithm, and constructed a prognostic signature termed the LUSC-Survival Prediction Index (LUSCSPI). The high-LUSCSPI group demonstrated a poor prognosis and was more likely to benefit from treatment with nine chemotherapeutic agents (shikonin, doxorubicin, CMK, S-Trityl-L-cysteine, paclitaxel, DMOG, gemcitabine, erlotinib, and crizotinib). In contrast, the low-LUSCSPI group exhibited a more favorable prognosis, with thapsigargin and cisplatin identified as promising treatment options. In conclusion, our results highlight the potential of LUSCSPI as an independent prognostic factor for LUSC. Further, the multi-omics consensus approach provides a robust foundation for prognostic stratification in LUSC patients, facilitating personalized treatment and disease management.

Nanoarray-fortified ultra-durable nanofiber membrane via sequential crystallization

Dengue virus infection amongst malaria and typhoid fever suspected acute febrile patients in the Niger river basin of Nigeria

Elucidating the isorhamnetin-3-O-glucoside-iNOS interaction via molecular dynamics and Hirshfeld surface analyses

Inducible nitric oxide synthase (iNOS) remains a demanding metallo-enzyme target because the catalytic heme shapes both geometry and electrostatics at the binding site. We evaluated the dietary flavonol glycoside isorhamnetin-3-O-glucoside (I3OG) against mouse (3E6T) and human (3E7G) iNOS oxygenase domains using a heme-aware, auditably validated docking workflow. we centered the docking grids at the crystallographic Fe position and validated the protocol by re-docking the native co-crystallized inhibitors (3E6T: AR-C118901/1A2; 3E7G: AR-C95791/AT2), reproducing the crystal poses with heavy-atom RMSD = 1.093 Å and 0.327 Å, respectively (≤ 2.0 Å criterion). Explicit-solvent 100-ns MD confirmed stable complexes for both systems; 3E6T showed tighter ligand RMSD, lower pocket Cα-RMSF, and a more persistent H-bond network. MM/GBSA over equilibrated frames (60−100 ns) yielded ΔG_bind ≈ −44.9 ± 3.9 kcal·mol −1 (3E6T) vs −36.1 ± 3.7 kcal·mol −1 (3E7G), with per-residue hot spots matching docking contacts. Principal-component free-energy maps indicated more focused minima for 3E6T and a broader low-energy valley for 3E7G, consistent with the MD metrics. we performed an apo-form heme-cavity test (heme removed, grid kept at Fe; proximal Cys re-protonated) to probe pocket occupancy/flexibility without claiming a catalytic model. Collectively, the heme-centred, co-crystal-validated protocol plus the apo-cavity readout support I3OG as a plausible scaffold for iNOS engagement and provide a transparent template for future metallo-enzyme docking studies.

Development of a portable avian influenza virus characterisation system: bringing the inside-out

ACEF score as a predictor of new-onset atrial fibrillation in patients with ST-elevation myocardial infarction: A retrospective cohort study

Background New-onset atrial fibrillation (NOAF) during acute ST-elevation myocardial infarction (STEMI) is common and linked to adverse outcomes. This study aimed to assess the predictive value of the age–creatinine–ejection fraction (ACEF) score for NOAF in STEMI patients. Methods We retrospectively analyzed 951 STEMI patients who underwent primary percutaneous coronary intervention (PCI) at out tertiary center between 2020 and 2023. Patients with prior atrial fibrillation (AF), AF on admission, cardiogenic shock, heart failure, significant valvular disease, or failed PCI were excluded. Clinical, laboratory, and echocardiographic data were collected, and ACEF scores were calculated. NOAF was defined as any AF episode during hospitalization in patients without prior AF. The optimal ACEF cutoff was determined using receiver operating characteristic (ROC) curve analysis (Youden’s index), and multivariate logistic regression identified independent predictors of NOAF. Results NOAF occurred in 63 patients (6.6%). These patients were older, more often female, and had lower systolic blood pressure, lower left ventricular ejection fraction, and higher C-reactive protein and creatinine levels (all p < 0.05). In-hospital major adverse cardiac events (MACE) and mortality were significantly higher in the NOAF group than patients in without NOAF group (22.2% vs. 6.2%, and 15.9% vs. 4.3%, respectively; p < 0.001). The ACEF score was significantly higher in patients with NOAF (1.73 ± 0.74 vs. 1.42 ± 0.64, p < 0.001). ROC analysis showed an area under curve (AUC) of 0.643 (95% CI: 0.571–0.715; p < 0.001). An ACEF score ≥1.32 predicted NOAF with 73% sensitivity and 55.6% specificity. In multivariate analysis, ACEF remained an independent predictor of NOAF (OR ~1.5, p = 0.02), but among its components, only age was independently associated with NOAF (OR ~1.03 per year, p = 0.01). Conclusions The ACEF score modestly predicts NOAF in STEMI patients, but its predictive power only incremental to age alone. Further studies are warranted for this field.

ACO-tuned randomized decision tree for detecting cyber threats in mobile web applications

The impact of COVID-19 on walking practices in Korea: Policy implications for Urban health and physical activity resilience

Background This study adopts a socio-ecological model to evaluate the individual- and community-level factors influencing walking practices among urban adults before (2018−2019) and after (2020−2021) the COVID-19 pandemic. Busan, South Korea, characterized by dense urban environments and structured health promotion systems, offers a relevant context to examine pandemic-related changes in physical activity behaviors. Methods The 2018–2021 Korea Community Health Survey was used, targeting adults aged 19 and older living in Busan Metropolitan City. Multilevel logistic regression models were constructed using data from 58,028 individuals (Level 1) and 16 administrative districts (Level 2). The binary dependent variable was walking. The independent variables included individual-level and community-level factors. Model fit was evaluated using the intraclass correlation coefficient, likelihood ratio, and −2 log likelihood. Results Individual-level variables such as sex, age, household income, subjective health status, and depression significantly correlated with walking before and after the COVID-19 pandemic. Females who perceived their health as poor or experienced depression were less likely to walk. However, the associations between age, household income, and walking practices were inconsistent. Before the pandemic, individuals who reported high trust in their neighbors were more likely to engage in walking practices. After the pandemic, those classified as obese were less likely to engage in walking practice, while individuals who engaged in alcohol consumption showed higher odds of walking practice. Moreover, participants who perceived access to public transportation as good had increased odds of walking. At the community level, pedestrian paths and social network difficulty were negatively associated with walking practice. In contrast, the availability of public sports facilities was positively associated with walking. Conclusion The COVID-19 pandemic significantly affected urban adults’ walking habits. Factors such as pedestrian paths, sports facilities, and reduced social relationship challenges helped maintain walking practices. These results highlight the need for multilevel interventions that target environmental, social, and individual determinants to promote and sustain walking during and after public health emergencies. In Korea and other high-density Asian cities, these findings provide policy-relevant evidence to guide walkability-oriented urban planning and health promotion strategies that strengthen physical activity resilience in future public health crises.

Virus-derived serpin reduces immuno-coagulopathic damage in murine colitis by targeting the urokinase-type plasminogen activator receptor (uPAR) and complement

Dry eye disease seasonal pattern and climatic association in Saudi Arabia using Google Trends

Purpose The study aims to investigate the dry eye search term pattern in Saudi Arabia using Google Trends, and to explore the association of weather changes on dry eye disease (DED) search interests. Methods Time series analysis for data that were collected from Google Trends (GTs) on period from January 2011 to October 2024 using Arabic term for Dry Eye with setting allocated in Saudi Arabia. Seasonality was evaluated using Fourier terms in ARIMA regression model. Monthly variation was further evaluated. Climate factors, mean surface air temperature, relative humidity and accumulated precipitate were incorporated into ARIMAX model to find environmental relationship with DED. Kruskal-Wallis test was performed to confirm significant finding in monthly variation. Results Dry eye disease (DED) related search term demonstrates significant monthly differences ( p  = 0.008). Monthly effect ARIMA model (R² = 0.93) identified sustained high season from February through August higher than January. June represents maximum annual peak. A significant upward trend of 0.48 per month in RSV is also noted over the 13-year period ( p  < 0.001). In ARIMAX model, relative humidity is most important associated factor with dry eye search activity (β = −0.26, p  = 0.002). Conclusion This study is the first evidence of seasonality of DED using Google Trends (GTs) in Saudi Arabia and highlighting the growing public health concern of DED. Understanding the disease pattern can aid public health implications to decrease risk of DED. This finding can serve as valuable reference to supplement traditional methods.

Quantitative analysis of the influence of faults on deep in situ stress under different stress types

Correction: LPS responsiveness and neutrophil chemotaxis in vivo require PMN MMP-8 activity

Clinical and simulated impact of intraocular lens tilt and decentration based on real-world data and optical simulation

Advance directives prior to COVID-19 diagnosis in a United States national healthcare system

Background An advance directive (AD) document allows a patient to indicate their health care preferences and identify an agent to make decisions on their behalf if they lose their ability to communicate. Due to the substantially elevated risk of acute respiratory failure and death during the COVID-19 pandemic, ADs were especially relevant. The objective of this study was to describe AD completed prior to COVID-19 infection (COVID-19) among patients receiving care in a national healthcare system. Methods We conducted a cohort study of United States Veterans Health Administration (VA) patients with COVID-19 between March 2020 and December 2022. AD completion before COVID-19 was ascertained by progress note titles in the electronic health record. Covariates included age, sex, race/ethnicity, marital status, geographic region, health care utilization, calendar quarter of COVID-19, and VA COVID-19 (VACO) 30-day mortality index score. Results Among 422,028 COVID-19 patients (median age = 62 years; 88.5% male; 58.6% non-Hispanic White (NH-White), 23.3% non-Hispanic Black (NH-Black), 9.2% Hispanic), 67,970 (16.1%) had AD documentation which varied substantially across all covariates. AD completion increased with VACO Index quintiles ranging from 8.2 to 31.0%. In a model adjusted for covariates, relative to NH-White, NH-Black and Hispanic groups had decreased odds for AD (NH-Black odds ratio (OR)=0.77 (95% confidence interval 0.76–0.79); Hispanic OR=0.85 (0.82–0.87)). VACO index includes age, and both were strongly associated with AD completion. Women compared to men, and those who were widowed, separated/divorced and never married relative to people who were married, had increased AD completion. Conclusions AD completion was overall low, including among patients at high risk of mortality due to COVID-19. When controlling for age, risk for mortality and other covariates, men and people who identify as Black or Hispanic were less likely to have completed an AD. Investment in interventions to facilitate AD completion are needed, particularly among historically underrepresented populations.

Assessing readiness of health facilities for hypertension and integration with diabetes care in Bangladesh: Evidence from the National Service Provision Assessment Survey

Background Hypertension (HT) and diabetes mellitus (DM) are two major noncommunicable diseases (NCDs) with a high rate of comorbidity that utilize similar health system resources. Limited evidence exists, however, on the level of readiness of health facilities in Bangladesh to manage HT and integrated HT–DM care. The objective of this study was an assessment of facility readiness for HT and integrated HT–DM management and to identify key factors influencing levels of readiness. Methods The study involved the analysis of data from 382 health facilities at or above sub-district level from the most recent nationally representative dataset, the 2017 Bangladesh Health Facility Survey (BHFS). Readiness for HT and integrated HT–DM services was assessed based on composite scores as constructed from the WHO–Service Availability and Readiness Assessment (SARA) indicators. Negative binomial regression models were applied to determine the factors associated with facility readiness. Results Facilities showed low readiness scores for both HT and integrated HT–DM care, with mean scores of 3.72 (out of 8) and 6.71 (out of 16), respectively. Although most facilities have basic equipment like BP apparatuses (98.7%) and stethoscopes (98.8%), a huge gap is observed in the training of staff (20.5%) and availability of guidelines for management (16.6%) of HT, diagnostic tools for DM, and essential medicines including ACE inhibitors (7.3%), thiazide diuretics (12.0%), and metformin (49.4%). Significant determinants of HT readiness included type of facility, client feedback system, and the number of HT care providers, while for integrated HT-DM readiness, important predictors were a type of facility, treatment-only service provision, client feedback mechanism, and structure of user-fees. Conclusions In Bangladesh, health facilities are still not adequately ready to deliver integrated HT-DM services, illustrating deficits in human resources, clinical protocols, diagnostics, and availability of medicines at an overall system level. There are several areas that need improvement-the need for strengthening integrated training, free availability of medicines, client feedback systems, and collaboration between the public-private-NGO sectors. The results, though based on 2017 data, remain important in capturing system readiness prior to the reform and serve as a nationally representative baseline to assess the upspring of HT and NCD program improvements in Bangladesh.

Retraction: Beyond emotional and spatial processes: Cognitive dysfunction in a depressive phenotype produced by long photoperiod exposure

Does local government tax competition promote industrial transformation and upgrading?

Promoting industrial transformation and upgrading (ITU) is the vital driving force for achieving high-quality economic development. This paper systematically interprets the theoretical mechanism of the impact of local government tax competition on ITU from a theoretical perspective. On this basis, a two-way fixed effects model is used to examine the impact of local government tax competition on ITU, the transmission mechanism, and the moderating effect of technological innovation. The study finds an inverted “U-shaped” relationship between local government tax competition and ITU, with tax structure, income distribution, and industrial agglomeration playing a non-linear mediating role. Improvements in technological innovation will reinforce the inverted “U-shaped” relationship between local government tax competition and ITU. The inverted “U-shaped” impact of local government tax competition on ITU is more pronounced in cities without economic growth targets, cities in eastern China, economically developed cities, and cities with weak tax enforcement capabilities. The research findings provide theoretical support and decision-making references for optimizing local tax policies and promoting high-quality economic development.

A lightweight network for phone surface defect detection with industrial deployment on RK3568 edge devices

In smartphone production, detecting small defects on screens remains challenging due to low detection accuracy, high missed detection rates, and slow processing speeds. To address these issues, this paper presents a Lightweight Network Based on YOLOv8 (LNB-YOLO) for defect detection, with several key enhancements. First, a Feature Pyramid Network based on Context-Guided Spatial Feature Reconstruction (CGRFPN) is integrated to improve the perception of multi-level features and enhance small target recognition in complex backgrounds. Second, the Efficient Local Attention (ELA) module is incorporated into the Backbone’s C2F module to improve localization precision, while the Minimum Point Distance based IoU (MPDIoU) loss function is employed to prevent gradient explosion. Third, a lightweight Detail-Enhanced Convolution and Shared Convolutional Detection Head (LSDECD) is designed to capture fine details while reducing parameters and computational complexity. Finally, model pruning and knowledge distillation techniques are applied to further optimize efficiency. Experimental results on the PKU-Market-Phone dataset show that LNB-YOLO achieves a mAP@0.5 of 97.5% and a mAP@.5:.95 of 68.8%, surpassing the original YOLOv8 by 6.1% and 9.3%, respectively. The model also reduces parameters by 80% and computational cost by 63%, effectively meeting precision requirements for smartphone production lines.

Dual niche modeling with GEE and SHAP for predicting habitat shifts of Haloxylon ammodendron and Cistanche deserticola under climate change

Haloxylon ammodendron , a keystone woody species, and its parasitic plant, Cistanche deserticola , play critical roles in sustaining arid ecosystems and supporting regional economies. However, their distribution is increasingly threatened by global climate change. Here, we propose a dual niche modeling framework that integrates climate and soil suitability layers using a multi-model ensemble approach combined with interpretable machine-learning techniques, specifically SHapley Additive exPlanations (SHAP). Using CMIP6 scenarios (SSP126, SSP245, and SSP585), we predicted the current and future potential habitats for both species. The results demonstrated that the ensemble models delivered robust performance, surpassing the accuracy of single-model predictions. Currently, suitable habitats are concentrated in northwestern China as well as parts of Mongolia and Kazakhstan. Under SSP585 (2081–2100), H. ammodendron habitats are projected to shrink by 56.2%, whereas C. deserticola is expected to lose more than 97% of its habitat, nearly disappearing from Central Asia. Key climatic drivers include temperature seasonality and precipitation patterns, whereas the soil water-holding capacity and gravel content significantly affect local suitability. Niche overlap analysis revealed a strong host dependency for C. deserticola. However, the climate–soil niche congruence is projected to decrease under future scenarios, indicating the potential risks of ecological decoupling. This integrative and interpretable approach offers a scalable tool for biodiversity assessment and provides actionable insights for conservation planning in climate-sensitive, arid ecosystems.