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Background Salinity-alkalinity stress is one of the major abiotic stresses affecting plant growth and development. γ-Aminobutyrate (GABA) is a non-protein amino acid that functions in stress tolerance. However, the interactions between cellular redox signaling and chlorophyll (Chl) metabolism involved in GABA-induced salinity-alkalinity stress tolerance in plants remains largely unknown. Here, we investigated the role of GABA in perceiving and regulating chlorophyll biosynthesis and oxidative stress induced by salinity-alkalinity stress in muskmelon leaves. We also evaluated the effects of hydrogen peroxide (H 2 O 2 ), glutathione (GSH), and ascorbate (AsA) on GABA-induced salinity-alkalinity stress tolerance. Results Salinity-alkalinity stress increased malondialdehyde (MDA) content, relative electrical conductivity (REC), and the activities of superoxide dismutase (SOD), ascorbate peroxidase (APX) and dehydroascorbate reductase (DHAR). Salinity-alkalinity stress decreased shoot dry and fresh weight and leaf area, reduced glutathione and ascorbate (GSH and AsA) contents, activities of glutathione reductase (GR) and monodehydroascorbate reductase (MDAR). By contrast, pretreatment with GABA, H 2 O 2 , GSH, or AsA significantly inhibited these salinity-alkalinity stress-induced effects. The ability of GABA to relieve salinity-alkalinity stress was significantly reduced when the production of endogenous H 2 O 2 was inhibited, but was not affected by inhibiting endogenous AsA and GSH production. Exogenous GABA induced respiratory burst oxidase homologue D ( RBOHD ) genes expression and H 2 O 2 accumulation under normal conditions but reduced the H 2 O 2 content under salinity-alkalinity stress. Salinity-alkalinity stress increased the accumulation of the chlorophyll synthesis precursors glutamate (Glu), δ-aminolevulinic acid (ALA), porphobilinogen (PBG), uroporphyrinogen III (URO III), Mg-protoporphyrin IX (Mg-proto IX), protoporphyrin IX (Proto IX), protochlorophyll (Pchl), thereby increasing the Chl content. Under salinity-alkalinity stress, exogenous GABA increased ALA content, but reduced the contents of Glu, PBG, URO III, Mg-proto IX, Proto IX, Pchl, and Chl. However, salinity-alkalinity stress or GABA treated plant genes expression involved in Chl synthesis had no consistent trends with Chl precursor contents. Conclusions Exogenous GABA elevated H 2 O 2 may act as a signal molecule, while AsA and GSH function as antioxidants, in GABA-induced salinity-alkalinity tolerance. These factors maintain membrane integrity which was essential for the ordered chlorophyll biosynthesis. Pretreatment with exogenous GABA mitigated salinity-alkalinity stress caused excessive accumulation of Chl and its precursors, to avoid photooxidation injury.

Cardiovascular disease (CVD) is the leading cause of death worldwide and a major public health concern. CVD prediction is one of the most effective measures for CVD control. In this study, 29930 subjects with high-risk of CVD were selected from 101056 people in 2014, regular follow-up was conducted using electronic health record system. Logistic regression analysis showed that nearly 30 indicators were related to CVD, including male, old age, family income, smoking, drinking, obesity, excessive waist circumference, abnormal cholesterol, abnormal low-density lipoprotein, abnormal fasting blood glucose and else. Several methods were used to build prediction model including multivariate regression model, classification and regression tree (CART), Naïve Bayes, Bagged trees, Ada Boost and Random Forest. We used the multivariate regression model as a benchmark for performance evaluation (Area under the curve, AUC = 0.7143). The results showed that the Random Forest was superior to other methods with an AUC of 0.787 and achieved a significant improvement over the benchmark. We provided a CVD prediction model for 3-year risk assessment of CVD. It was based on a large population with high risk of CVD in eastern China using Random Forest algorithm, which would provide reference for the work of CVD prediction and treatment in China.

Introduction Neurological diseases are a significant contributor to premature mortality and temporary or long-term disability among survivors. Asia serves as an essential region for assessing the shifting burden of these disorders. This study aims to calculate and evaluate the changes in burden of neurological diseases across Asia. Methods The Global Burden of Disease database provided data on deaths, disability-adjusted life-years (DALYs), incidence, and prevalence from 1990 to 2021 across Asian subregions and countries. Twelve common neurological diseases were analyzed. Estimated Annual Percent Change were calculated to reveal trends in all the metrics. The Nordpred age-period-cohort model was employed to project the neurological disease burden. Results In 2021, the leading neurological disorders in DALYs were stroke (109,144.87, 95% uncertainty intervals (UI) 95,992.89–123,089.90), headache disorders (25,713.91, 95%UI 4,693.65–54,853.47), and Alzheimer’s disease and other dementias (19,156.46, 95% UI 9,137.72–41,421.18). Stroke and degenerative neurological disorder presented the most severe burden in East Asia, while headache disorders were prominent in South Asia. Between 1990 and 2021, Asia’s regions showed varying reductions in age-standardized DALYs and age-standardized death rates for neurological diseases, with the steepest decline observed in high-income Asia Pacific (DALYs -2.27, 95% confidence interval (CI) -2.4 to -2.13; ASDR -3.85, 95% CI -4.02 to -3.69). Neurological disease burden was higher in males, peaking at ages 65–74. Projections to 2045 indicate a decline in DALYs for stroke, infectious neurological diseases, Parkinson’s disease, and idiopathic epilepsy across most regions of Asia. In contrast, trends for other neurological diseases will vary regionally. Conclusion Neurological diseases were the primary cause of DALYs in 2021, ranking second only to cardiovascular diseases as a leading cause of death. As the aging trend in Asia’s population continues to intensify, it is crucial to focus more on the prevention and management of neurological disorders.

Introduction Structural MRI has long been used to characterize local morphological features of the human brain. Coordination patterns of the local morphological features among regions, however, are not well understood. Here, we constructed individual‐level morphological brain networks and systematically examined their topological organization and long‐term test–retest reliability under different analytical schemes of spatial smoothing, brain parcellation, and network type. Methods This study included 57 healthy participants and all participants completed two MRI scan sessions. Individual morphological brain networks were constructed by estimating interregional similarity in the distribution of regional gray matter volume in terms of the Kullback–Leibler divergence measure. Graph‐based global and nodal network measures were then calculated, followed by the statistical comparison and intra‐class correlation analysis. Results The morphological brain networks were highly reproducible between sessions with significantly larger similarities for interhemispheric connections linking bilaterally homotopic regions. Further graph‐based analyses revealed that the morphological brain networks exhibited nonrandom topological organization of small‐worldness, high parallel efficiency and modular architecture regardless of the analytical choices of spatial smoothing, brain parcellation and network type. Moreover, several paralimbic and association regions were consistently revealed to be potential hubs. Nonetheless, the three studied factors particularly spatial smoothing significantly affected quantitative characterization of morphological brain networks. Further examination of long‐term reliability revealed that all the examined network topological properties showed fair to excellent reliability irrespective of the analytical strategies, but performing spatial smoothing significantly improved reliability. Interestingly, nodal centralities were positively correlated with their reliabilities, and nodal degree and efficiency outperformed nodal betweenness with respect to reliability. Conclusions Our findings support single‐subject morphological network analysis as a meaningful and reliable method to characterize structural organization of the human brain; this method thus opens a new avenue toward understanding the substrate of intersubject variability in behavior and function and establishing morphological network biomarkers in brain disorders. We proposed a method to construct individual‐level morphological brain networks from structural MRI data. We demonstrated that morphological brain networks derived from this method were specifically organized, test–retest reliable and dependent on different analytic strategies of data preprocessing and network construction methods.

We conducted a comprehensive intensive intervention for hypertension patients working in universities or colleges. From July 2015 to March in 2016, 220 hypertension subjects were recruited, with 165 cases in intensive intervention group and 55 in standard intervention group. After 24 months of intervention, 208 ones including of 157 in intensive intervention group and 51 in standard intervention group were included in the final analysis. The patients in standard intervention group were given routine intervention, which mainly including of drug treatment and health education. The patients in intervention group were given comprehensive intensive intervention in addition to routine intervention, including follow-up management of hypertension, emotional, lifestyle intervention and else. The study and experimental protocols were approved by institutional review board of Zhejiang Hospital and Fu Wai Hospital and registered (ChiCTR-ECS-14004641, date of registration: May 8, 2014). After 2 years, compared with the standard intervention group, SBP/DBP in the intensive intervention group decreased by 3.7/4 mmHg and BP control rate increased by 8.9%, and the unhealthy behaviors and life quality including tension and pressure were also improved in the intensive intervention group. We used mixed effect model to analyze the intervention effect which could solve the problems of missing values and correlation. The intensive intervention of hypertension control including follow-up management, emotional and lifestyle intervention in occupational places could promote the development of the prevention, treatment and control of hypertension among staff in colleges and universities.

Background Various risk factors influence obesity differently, and environmental endocrine disruption may increase the occurrence of obesity. However, most of the previous studies have considered only a unitary exposure or a set of similar exposures instead of mixed exposures, which entail complicated interactions. We utilized three statistical models to evaluate the correlations between mixed chemicals to analyze the association between 9 different chemical exposures and obesity in children and adolescents. Methods We fitted the generalized linear regression, weighted quantile sum (WQS) regression, and Bayesian kernel machine regression (BKMR) to analyze the association between the mixed exposures and obesity in the participants aged 6–19 in the National Health and Nutrition Examination Survey (NHANES) 2005–2010. Results In the multivariable logistic regression model, 2,5-dichlorophenol (2,5-DCP) (OR (95% CI): 1.25 (1.11, 1.40)), monoethyl phthalate (MEP) (OR (95% CI): 1.28 (1.04, 1.58)), and mono-isobutyl phthalate (MiBP) (OR (95% CI): 1.42 (1.07, 1.89)) were found to be positively associated with obesity, while methylparaben (MeP) (OR (95% CI): 0.80 (0.68, 0.94)) was negatively associated with obesity. In the multivariable linear regression, MEP was found to be positively associated with the body mass index (BMI) z-score ( β (95% CI): 0.12 (0.02, 0.21)). In the WQS regression model, the WQS index had a significant association (OR (95% CI): 1.48 (1.16, 1.89)) with the outcome in the obesity model, in which 2,5-DCP (weighted 0.41), bisphenol A (BPA) (weighted 0.17) and MEP (weighted 0.14) all had relatively high weights. In the BKMR model, despite no statistically significant difference in the overall association between the chemical mixtures and the outcome (obesity or BMI z-score), there was nonetheless an increasing trend. 2,5-DCP and MEP were found to be positively associated with the outcome (obesity or BMI z-score), while fixing other chemicals at their median concentrations. Conclusion Comparing the three statistical models, we found that 2,5-DCP and MEP may play an important role in obesity. Considering the advantages and disadvantages of the three statistical models, our study confirms the necessity to combine different statistical models on obesity when dealing with mixed exposures.

Objective Cardiopulmonary resuscitation (CPR) is vital for saving patients experiencing cardiac arrest. Teaching CPR skills through short videos offers numerous advantages. However, potential inaccuracies or misinformation could mislead the public and impact the effectiveness of CPR education. This study aims to evaluate the quality and accuracy of CPR instructional videos shared on three major short video platforms in China (TikTok, Bilibili, and REDnote), analyze common irregular or erroneous practices, and provide valuable suggestions for content optimization. Methods The collected videos were evaluated using a five-point scoring criterion based on 2020 American Heart Association (AHA) Guidelines for Cardiopulmonary Resuscitation (CPR) and Emergency Cardiovascular Care (ECC). The videos were categorized into three levels: excellent, moderate, and poor, based on their video quality scores for CPR procedures and non-procedural content. Further categorization was made by video duration (≤5 min as short; >5 min as long). Additionally, the most critical and prevalent irregularities or errors were documented, and a detailed analysis of the most popular video from each platform was carried out. The relationship between video quality and popularity, and video duration and popularity were examined separately. Results A total of 100 CPR instructional videos were analyzed. While 86% of the videos were produced by healthcare professionals, substantial errors were identified in critical areas such as the extra time spent removing foreign body airway obstruction (67%), and incorrect hand position during compression (62%). Other issues with non-procedural content were identified, including video acceleration (13%), lack of step-by-step explanations (61%), etc. Statistical analysis revealed no significant differences in popularity across videos of different quality or duration ( p  = 0.876 among video quality groups for CPR procedures, p  = 0.988 among video quality groups for non-procedural content, p  = 0.260 between video duration groups). Conclusions This study identified the necessity for improvements in CPR procedures and non-procedural content of CPR instructional videos. To enhance video quality, measures such as rigorous review mechanisms, public feedback and promotion of certified high-quality videos are recommended.

Background Post-traumatic brain edema is a critical factor influencing the prognosis of traumatic brain injury (TBI). However, current imaging scoring systems, such as the Marshall and Rotterdam scores, lack specific quantitative criteria for assessing brain edema. This study aims to develop a prognostic prediction model for TBI by integrating the novel A5(+ 1) CT brain edema grading system with advanced machine learning methodologies. Methods A total of 216 patients with traumatic brain injury (TBI) were retrospectively enrolled in this study. CT imaging characteristics and clinical parameters within 72 h post-injury were extracted. Variable selection was performed using least absolute shrinkage and selection operator (LASSO) regression analysis. Subsequently, nine machine learning models were developed and their performances were compared. The evaluation metrics included the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and decision curve analysis (DCA). Results Seven key predictors were identified: age, contusion type, midline shift, CT edema grade, Glasgow Coma Scale score, pulmonary infection, and perilesional CT value. The naive Bayes (NB) model demonstrated superior performance, achieving an AUC of 0.944 in the test set, with 84.6% sensitivity and 94.1% specificity. The CT edema grade was the most significant predictor. A grade of ≥ 3 (indicating bilateral or diffuse edema) was strongly associated with poor Glasgow Outcome Scale scores ( p  < 0.001), elevated intracranial pressure ( p <  0.001), and reduced perilesional CT values ( p <  0.001). DCA indicated substantial clinical net benefit when the intervention threshold probability exceeded 40%. Conclusion The ML model incorporating the novel A5(+ 1) CT edema grading system enables precise prognostic prediction for TBI patients. This integrated approach provides a quantitative and dynamic assessment of edema severity, outperforming traditional scoring systems and offering a valuable tool for risk stratification and clinical decision-making.

N95 mask is essential for healthcare workers dealing with the coronavirus disease 2019 (COVID-19). However, N95 mask causes discomfort breathing with marked reduction in air exchange. This study was designed to investigate whether the use of N95 mask affects rescuer's fatigue and chest compression quality during cardiopulmonary resuscitation (CPR). After a brief review of CPR, each participant performed a 2-minute continuous chest compression on a manikin wearing N95 (N95 group, n = 40) or surgical mask (SM group, n = 40). Compression rate and depth, the proportions of correct compression rate, depth, complete chest recoil and hand position were documented. Participants' fatigue was assessed using Borg score. Significantly lower mean chest compression rate and depth were both achieved in the N95 group than in the SM group (p < 0.05, respectively). In addition, the proportion of correct compression rate (61 ± 19 vs. 75 ± 195, p = 0.0067), depth (67 ± 16 vs. 90 ± 14, p < 0.0001) and complete recoil (91 ± 16 vs. 98 ± 5%, p = 0.0248) were significantly decreased in the N95 group as compared to the SM group. At the end of compression, the Borg score in the N95 group was significantly higher than that in the SM group (p = 0.027). Wearing a N95 mask increases rescuer's fatigue and decreases chest compression quality during CPR. Therefore, the exchange of rescuers during CPR should be more frequent than that recommended in current guidelines when N95 masks are applied.

A detailed review of various fractal models used in tribology is presented. The analysis of the models is based on the use of the Cantor–Borodich (CB) profile and its modifications. This profile and related models may be studied analytically and, therefore, they provide us with tools for rigorous analysis of fractal approaches to description of surface roughness and corresponding contact problems. In turn, this allows us to present a critical review of current fractal approaches to tribology. It will be demonstrated that fractal dimension alone cannot give a full description of surface roughness, however, some of these models may reflect the multilevel hierarchical structure of real surface roughness. This review helps to avoid the repetition of common erroneous statements about the use of fractal concepts in tribology.