PLoS ONE最新文献

Background: With the advancement of globalization, the prevalence of cognitive dysfunction in the elderly population has risen significantly. Early intervention may dramatically alleviate the disease burden and reduce economic costs associated with cognitive impairment. This study aims to construct a risk prediction model for cognitive dysfunction based on machine learning (ML) algorithms, providing healthcare professionals and patients with a more accurate and effective tool for risk assessment.

Methods: This study included 1,325 elderly participants who completed cognitive assessments and comprehensive laboratory blood tests. Risk factors for cognitive dysfunction were identified through univariate analysis, multivariate logistic regression, LASSO regression, and the Boruta algorithm. Nine ML methods-Random Forest (RF), Light Gradient Boosting Machine (LightGBM), Extreme Gradient Boosting (XGBoost), Logistic Regression, K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Artificial Neural Network (ANN), Decision Tree, and Elastic Net-were employed to construct the prediction models. The Shapley Additive Explanations (SHAP) algorithm was utilized to interpret the final model.

Results: The Random Forest model exhibited the highest predictive performance, with an AUC value exceeding those of other models. SHAP analysis identified age, race, education level, diabetes, and depression as the primary predictors of cognitive dysfunction in the elderly. The calibration curve indicated a strong alignment between the model's predictions and actual outcomes, while the decision curve confirmed the model's clinical applicability.

Conclusion: Age, race, education level, diabetes, and depression are significant influencing factors of cognitive dysfunction in the elderly. Among the ML algorithms evaluated, the Random Forest model exhibited the best predictive performance.

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.

Introduction: The transcription factor NK2 homeobox1 (NKX2-1), associated with brain lung thyroid syndrome, regulates the transcription of surfactant proteins, thyroglobulin (TG) and thyroid peroxidase (TPO). This study explored the pathogenicity of three NKX2-1 variants (p.(Tyr214Cys), p.(Arg165Trp) and p.(Gly147Ala)) that were identified in three infants with lethal forms of childhood interstitial lung disease.

Methods: HEK293T cells were co-transfected with expression plasmids of NKX2-1 (wild-type (WT) and variants) and PAX8, along with reporter plasmids containing the promoters of SFTPB, SFTPC, TG and TPO). Protein expression was analyzed by western blotting and immunofluorescence. Luciferase assays were performed to evaluate the activation of different promoters. Surfactant protein and NKX2-1 expression were also assessed on patient lung biopsies using immunohistochemistry.

Results: All three mutant proteins exhibited nuclear localization. Protein expression was altered in the p.(Tyr214Cys) and p.(Arg165Trp) variants located in NKX2.1 homeodomain. The p.(Tyr214Cys) variant failed to transactivate the tested promoters and was associated with a lack of pro-SP-C and SP-C expression in lung biopsy whereas the p.(Arg165Trp) variant induced both gain- or loss-of-function effects on the tested promoters. Finally, the p.(Gly147Ala) variant transactivated all the promoters tested, as for the WT. Conclusion: Our results demonstrated the pathogenicity of two variants, p.(Tyr214Cys) and p.(Arg165Trp), located within the homeodomain of NKX2-1. Conversely, the p.(Gly147Ala) variant showed no pathogenic effects. To date, the p.(Tyr214Cys) variant is associated with the most severe respiratory phenotype reported for NKX2-1-related disorders. Further studies are needed to understand the specific mechanisms underlying the pathogenicity of NKX2.1 variants located in the homeodomain.

Introduction: Children with severe eosinophilic asthma are at an increased risk of severe exacerbations, medication side effects, impaired lung function, and significantly reduced quality of life. The advent of biologic agents aimed at eosinophilic pathways has significantly improved management options for patients with severe asthma. Mepolizumab, an anti-interleukin-5 monoclonal antibody, was approved in 2018 as an add-on maintenance treatment for patients with severe eosinophilic asthma aged ≥6 years of age. Mepolizumab's efficacy and safety is well documented in adults, but paediatric data remain limited. This real-world observational study will evaluate the long-term safety and efficacy of mepolizumab in children and adolescents, including those with comorbidities and on concomitant medications to provide a clearer picture of its performance in everyday clinical practice.

Methods and analysis: Design: CASAM is an open label, multinational (Spain and United Kingdom), multicenter (15 Spanish and 6 UK public institutions) observational cohort study. Sample size: 150 paediatric patients on mepolizumab for SA between 6-17 years of age will be enrolled. Study Duration: Study will be conducted over 36 months (12 months pre mepolizumab initiation and 24 months after initiation). Data Collection: Pseudonymized data (prospective and retrospective) from medical charts will be collected and entered in the electronic case report forms (eCRFs) of the electronic data capture (EDC) system. Primary Outcome: To compare the rates of clinically significant asthma exacerbations in the pre-exposure and the 12-month post-exposure period with mepolizumab treatment. Protocol Version: CASAM Study_Protocol_V2.0_16th November 2023 KCH.

Registration details: The study is registered with ClinicalTrials.gov (NCT05139381), IRAS number 306475.

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.

Background: Cardiovascular dysfunction frequently accompanies aging and is often worsened by adverse lifestyle factors and genetic susceptibility. The apolipoprotein E (APOE) gene modulates susceptibility to cardiovascular disease, but how exercise and diet interact with APOE genotype remains insufficiently understood. We investigate the cardioprotective potential of exercise in humanized APOE-targeted replacement mice on control and high-fat diet, using photon-counting computed tomography (PCCT) and deep learning-based image segmentation.

Methods: This study included 251 male and female mice in mid-to-late life of APOE2, APOE3, and APOE4 genotypes with variation in humanized NOS2 (HN) mediated innate immune response, exercise status (exercised vs. sedentary) and diet (control vs. high-fat). Mice underwent in vivo cine cardiac PCCT imaging following contrast enhancement with liposomal iodine nanoparticles. Stroke volume, ejection fraction, and myocardial mass were derived from automated segmentation of cardiac structures using a 3D U-Net model. We assessed main and interaction effects of genotype, sex, HN status, age, exercise and diet using generalized linear models, while Mann-Whitney U tests assessed effects of exercise within stratified subgroups.

Results: Exercise was a significant predictor of improvement in several cardiac functional metrics with a large effect size. The interaction between exercise and diet was a significant predictor of reduced body mass and myocardial mass. Stratified analyses found that exercise improves cardiac functional metrics in APOE4 mice on both diets, and APOE3 mice primarily on control diet, while benefitting HN mice more than non-HN mice.

Conclusions: Voluntary exercise can partially rescue cardiac dysfunction induced by high-fat diet in adult APOE-targeted replacement mice, with benefits modulated by genotype, sex, and HN status. APOE4 and HN mice benefitted most from exercise. Contrast-enhanced PCCT combined with deep learning segmentation enables scalable, minimally invasive cardiac phenotyping and reveals interaction effects that are critical for designing precision lifestyle interventions in genetically at-risk populations.

Aim: Vascular smooth muscle cells (VSMCs) are characterized by a considerable plasticity. Their phenotypic switch (from contractile to synthetic) plays a crucial role in the atherosclerotic process, explaining that numerous studies focus on this phenotypic transition. Thus, it is essential to use VSMCs that have been finely phenotyped for experimental purposes. The use of MOVAS cell line is suitable because, unlike primary cells, it is believed that these cells retain their phenotype and avoid cell senescence in culture. This study aimed to assess the phenotype of MOVAS cells over culture passages to ensure that they retained a contractile phenotype, before using them for further investigations.

Methods: The phenotype of MOVAS cells at different culture passages (P3, P5 and P8) was analysed morphologically and by studying the expression of genes that indicate a contractile (Acta2, Myocd and Cnn1) and synthetic (Klf4 and Lgals3) VSMC phenotype by RT-qPCR. Cell stiffness was analysed by atomic force microscopy and cell adhesion and migration.

Results: Our results showed that MOVAS cells rapidly changed morphologically and that the gene expression of contractile markers was significantly reduced in favor of markers specific to the synthetic phenotype. These changes were associated with a reduction in cell stiffness and a significant increase in adhesion and migration properties.

Conclusion: MOVAS cells undergo a transition from contractile to synthetic phenotype with increasing number of passages in vitro, which means that these cells should be used with caution, at a low number of passages, while being regularly characterized.

Effective knowledge exchange is critical for innovation in knowledge-intensive sectors, yet the relationship between cognitive proximity and collaborative innovation remains underexplored in complex knowledge environments. While prior studies confirm a non-linear, inverted U-shaped relationship where moderate similarity balances absorptive capacity and novelty, how this relationship changes with increasing knowledge complexity is poorly understood. This study investigates how knowledge complexity moderates the cognitive proximity-innovation relationship in the U.S. biotechnology sector using a comprehensive dataset of over 650,000 patents from over 57,000 unique assignee organizations spanning 1976 to 2024. We distinguish between two dimensions of collaborative innovation: collaboration volume and collaboration quality. Cognitive proximity was measured through CPC-based Jaccard similarity, while knowledge complexity was operationalized using a structural complexity framework based on knowledge combination networks. Negative binomial regressions reveal that knowledge complexity moderates the proximity-innovation relationship differently across the two dimensions. For collaboration volume, higher complexity shifts the optimal proximity point rightward and flattens the curve while maintaining the inverted U-shape. For collaboration quality, complexity produces a leftward shift and, remarkably, leads to a complete breakdown of the curvilinear relationship at high complexity levels, where the relationship becomes nearly horizontal. These contrasting patterns indicate that cognitive proximity operates through fundamentally different mechanisms in partner selection versus innovation realization. While absorptive capacity considerations dominate partnership decisions even under high complexity, novelty-generating mechanisms become disconnected from proximity effects as complexity rises. The findings refine proximity theory by demonstrating that knowledge complexity serves as a structural moderator and offer actionable insights for partner selection strategies in advanced innovation ecosystems.

Background: Thoracolumbar fascia (TLF) is thought to be linked to low back pain (LBP). This cross-sectional study aimed to investigate the difference in TLF thickness and stiffness between elite weightlifters with and without chronic LBP.

Methods: Forty-six elite weightlifters (aged 16-26 years; 23 with chronic bilateral LBP) were recruited. TLF thickness was measured in all participants, while stiffness was assessed in 17 of them (aged 19-25 years; 9 with chronic bilateral LBP). Investigations were conducted at the L3 level, about 2 cm lateral to midline, using ultrasound. Bright mode and shear wave elastography (SWE) mode were employed to measure the thickness and Young's modulus (as an indicator of stiffness) of TLF, respectively. Analyses of covariates (ANCOVAs) were employed to compare the differences in TLF thickness and stiffness between LBP and non-LBP groups, controlling for pre-determined confounding factors. Repeated ANCOVAs were performed to investigate the side-to-side differences in TLF thickness and stiffness in weightlifters with and without LBP. The significance level was set as p ≤ 0.05.

Results: The mean thickness and stiffness of TLF were 1.63 ± 0.38 mm and 47.77 ± 13.26 kPa on the dominant, and 1.88 ± 0.60 mm and 48.09 ± 12.62 kPa on the non-dominant sides respectively. The stiffness of the TLF on the dominant side was 42.4% higher in the LBP group compared to the non-LBP control (mean difference (MD) =16.55 kPa > MDC95, p = 0.005, Cohen's d = 1.58). No significant differences were detected in TLF thickness (p > 0.05). Additionally, LBP was found to be a factor influencing the side-to-side differences in stiffness but not in thickness. Specifically, the thickness of the non-dominant side was 15.3% higher than the dominant side (MD = 0.25 mm > MDC95, p < 0.001, Cohen's d = 0.63), which was not detected in stiffness.

Conclusion: Chronic LBP in elite weightlifters was associated with significantly higher TLF stiffness but unchanged thickness, suggesting stiffness is a more informative indicator of TLF health than thickness. Addressing stiffness in prevention and rehabilitation programs may improve weightlifters' performance and career longevity.

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.