Abstract In order to understand and analyze the current standards and application of school desks and chairs for primary and secondary schools, and to promote the healthy growth of primary and secondary school students. The article conducts a comprehensive review of the functional and dimensional standards for school furniture both domestically and internationally, and objectively analyzes the current utilization and existing issues concerning desks and chairs in schools. It further explores the multifaceted factors that influence the allocation of desks and chairs, and proposes effective countermeasures, so as to provide a reference for the risk factors of common diseases related to desks and chairs, such as myopia and abnormal spinal curvature.

BACKGROUND:How to effectively promote bone regeneration and bone reconstruction after bone injury has always been a key issue in clinical bone repair research.The use of biological and degradable materials loaded with bioactive factors to treat bone defects has excellent application prospects in bone repair. OBJECTIVE:To investigate the effect of polylactic acid-glycolic acid copolymer(PLGA)composite scaffold modified by lysine-grafted graphene oxide nanoparticles(LGA-g-GO)on osteogenic differentiation and new bone formation. METHODS:PLGA was dissolved in dichloromethane and PLGA scaffold was prepared by solvent evaporation method.PLGA/GO composite scaffolds were prepared by dispersing graphene oxide uniformly in PLGA solution.LGA-g-GO nanoparticles were prepared by chemical grafting method,and the PLGA/LGA-g-GO composite scaffolds were constructed by blending LGA-g-GO nanoparticles at different mass ratios(1%,2%,and 3%)with PLGA.The micromorphology,hydrophilicity,and protein adsorption capacity of scaffolds of five groups were characterized.MC3T3 cells were inoculated on the surface of scaffolds of five groups to detect cell proliferation and osteogenic differentiation. RESULTS AND CONCLUSION:(1)The surface of PLGA scaffolds was smooth and flat under scanning electron microscope,while the surface of the other four scaffolds was rough.The surface roughness of the composite scaffolds increased with the increase of the addition of LGA-g-GO nanoparticles.The water contact angle of PLGA/LGA-g-GO(3%)composite scaffolds was lower than that of the other four groups(P<0.05).The protein adsorption capacity of PLGA/LGA-g-GO(1%,2%,and 3%)composite scaffolds was stronger than PLGA and PLGA/GO scaffolds(P<0.05).(2)CCK-8 assay showed that PLGA/LGA-g-GO(2%,3%)composite scaffold could promote the proliferation of MC3T3 cells.Alkaline phosphatase staining and alizarin red staining showed that the cell alkaline phosphatase activity in PLGA/LGA-g-GO(2%,3%)group was higher than that in the other three groups(P<0.05).The calcium deposition in the PLGA/GO and PLGA/LGA-g-GO(1%,2%,and 3%)groups was higher than that in the PLGA group(P<0.05).(3)In summary,PLGA/LGA-g-GO composite scaffold can promote the proliferation and osteogenic differentiation of osteoblasts,and is conducive to bone regeneration and bone reconstruction after bone injury.

Chronic heart failure is the terminal stage of various cardiovascular diseases， and cardiomyocyte apoptosis is the turning point of decompensation. Studies have shown that traditional Chinese medicine （TCM） could regulate apoptosis-related signaling pathways and factors and inhibit or up-regulate the expression of apoptosis-related proteins. Thus， TCM can reduce cardiomyocyte apoptosis， protect the myocardial tissue and improve the cardiac function， demonstrating remarkable clinical effects. In recent years， the research on the treatment of chronic heart failure based on the inhibition of cardiomyocyte apoptosis is increasing and becomes the current research hotspot. On the basis of literature review， this paper discovers that TCM regulates apoptosis factors and multiple signaling pathways to inhibit apoptosis and inflammation and delay the progression of chronic heart failure through classical pathways such as the death receptor pathway， the mitochondrial pathway， and the endoplasmic reticulum pathway. At the same time， the studies in this field have the following problems： Repeated studies with shallow， simple， and fragmented contents， treating animal models with TCM prescriptions without syndrome differentiation， treating diseases with drugs at only one concentration which is insufficient to indicate efficacy， and lacking comprehensive， holistic， and systematic studies on the relationships of apoptosis with inflammatory responses， pyroptosis， ferroptosis， and autophagy. In the future， more scientific， reasonable， comprehensive， and feasible experimental schemes should be designed on the basis of comprehensively mastering the research progress in this field， and the communication and cooperation between researchers in different disciplines should be strengthened. The specific pathological mechanism of cardiomyocyte apoptosis in chronic heart failure and the signaling pathways， active components， and action targets of TCM in inhibiting cardiomyocyte apoptosis in chronic heart failure should be elucidated. Such efforts are expected to provide sufficient reference for the clinical treatment of chronic heart failure.

Objective: To explore the isotemporal substitution effects among different intensities of physical activity within a 10 minute recess period on the mental health of junior high school students, aiming to provide evidence based references for targeted practical interventions. Methods: From May to November 2024, a total of 845 junior high school students from Tianjin,Taiyuan and L Liang in Shaanxi Province,Puyang in Henan Province,Xi an in Shaanxi Province,Quzhou in Zhejiang Province,and Chaoyang in Liaoning Province were selected by using a combination of stratified random sampling and convenience sampling. ActiGraph wGT3X-BT accelerometers was used to measure physical activity during a 10 minute recess period. Mental health status was assessed with the Depression Anxiety Stress Scale (DASS-21). An isotemporal substitution model was constructed in 1 minute increments to predict the effects of substituting different physical activity behaviors on students mental health. Results: During recess, sedentary behavior (SB) was predominant among junior high school students, with an average duration of [7.08(5.85,7.98)] minutes, while moderate to vigorous physical activity (MVPA) accounted for the shortest duration at [0.42(0.21,0.85)] minutes. There were statistically significant differences in MVPA,LPA and SB time between students of different genders and grades( Z/H =-9.08,-8.34,-9.51;84.87,126.82,135.27,all P <0.01). Isotemporal substitution analysis, adjusted for gender and age, showed that replacing 1 minute of SB with 1 minute of MVPA significantly improved anxiety levels ( β =-0.29, 95% CI =-0.53 to -0.04) and overall mental health ( β =-0.72, 95% CI =-1.39 to -0.04), with both results reaching statistical significance (both P <0.05). No significant effects were observed for other substitution patterns (both P >0.05). Conclusions Substituting SB with MVPA during a 10 minute recess period exerts a positive impact on the mental health of junior high school students. It is recommended to optimize the daily recess activity structure in schools to enhance students mental well being.

Objective To evaluate the predictive ability and clinical application value of artificial intelligence (AI) systems in the benign and malignant differentiation and pathological type of pulmonary nodules, and to summarize clinical application experience. Methods A retrospective analysis was conducted on the clinical data of patients with pulmonary nodules admitted to the Department of Thoracic Surgery, Second Hospital of Lanzhou University, from February 2016 to February 2025. Firstly, pulmonary nodules were divided into benign and non-benign groups, and the discriminative abilities of AI systems and clinicians were compared. Subsequently, lung nodules reported as precursor glandular lesions (PGL), microinvasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC) in postoperative pathological results were analyzed, comparing the efficacy of AI systems and clinicians in predicting the pathological type of pulmonary nodules. Results In the analysis of benign/non-benign pulmonary nodules, clinical data from a total of 638 patients with pulmonary nodules were included, of which there were 257 males (10 patients and 1 patient of double and triple primary lesions, respectively) and 381 females (18 patients and 1 patient of double and triple primary lesions, respectively), with a median age of 55.0 (47.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis of the two groups of variables showed that, except for nodule location, the differences in the remaining variables were statistically significant (P<0.05). Multivariate logistic regression analysis showed that age, nodule type (subsolid pulmonary nodule), average density, spicule sign, and vascular convergence sign were independent influencing factors for non-benign pulmonary nodules, among which age, nodule type (subsolid pulmonary nodule), spicule sign, and vascular convergence sign were positively correlated with non-benign pulmonary nodules, while average density was negatively correlated with the occurrence of non-benign pulmonary nodules. The area under the receiver operating characteristic curve (AUC) of the malignancy risk value given by the AI system in predicting non-benign pulmonary nodules was 0.811, slightly lower than the 0.898 predicted by clinicians. In the PGL/MIA/IAC analysis, clinical data from a total of 411 patients with pulmonary nodules were included, of which there were 149 males (8 patients of double primary lesions) and 262 females (17 patients of double primary lesions), with a median age of 56.0 (50.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis results showed that, except for gender, nodule location, and vascular convergence sign, the differences in the remaining variables among the three groups of PGL, MIA, and IAC patients were statistically significant (P<0.05). Multinomial multivariate logistic regression analysis showed that the differences between the parameters in the PGL group and the MIA group were not statistically significant (P>0.05), and the maximum diameter and average density of the nodules were statistically different between the PGL and IAC groups (P<0.05), and were positively correlated with the occurrence of IAC as independent risk factors. The average AUC value, accuracy, recall rate, and F1 score of the AI system in predicting lung nodule pathological type were 0.807, 74.3%, 73.2%, and 68.5%, respectively, all better than the clinical physicians’ prediction of lung nodule pathological type indicators (0.782, 70.9%, 66.2%, and 63.7% respectively). The AUC value of the AI system in predicting IAC was 0.853, and the sensitivity, specificity, and optimal cutoff value were 0.643, 0.943, and 50.0%, respectively. Conclusion This AI system has demonstrated high clinical value in predicting the benign and malignant nature and pathological type of lung nodules, especially in predicting lung nodule pathological type, its ability has surpassed that of clinical physicians. With the optimization of algorithms and the adequate integration of multimodal data, it can better assist clinical physicians in formulating individualized diagnostic and treatment plans for patients with lung nodules.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

BACKGROUND: Urolithiasis is a widespread disease with a high prevalence worldwide. This study aims to evaluate the disease burden of urolithiasis and its trends from 1990 to 2021 globally, based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 database. METHODS: The numbers and age-standardized rates (ASRs) of incidence, disability-adjusted life years (DALYs), and mortality of urolithiasis were extracted from GBD 2021 to represent the disease burden. Joinpoint regression analyses were conducted to assess the temporal trends in the burden of urolithiasis. The male-to-female ASR ratio indices were used to evaluate sex disparities. Additionally, we explored the relationship between the ASR ratio and the sociodemographic index (SDI). RESULTS: The total numbers of incidence, DALY, and mortality of urolithiasis were 105,983,780 cases (95% uncertainty interval [UI] = 88,349,356-128,645,155 cases), 693,444 cases (95% UI = 567,765-850,490 cases), and 17,672 cases (95% UI = 13,932-21,241 cases), respectively, in 2021. There is an increasing trend in the number of these measures globally, whereas the ASRs have decreased over the past 30 years. The age-standardized incidence rate (ASIR) and age-standardized mortality rate (ASMR) were significantly higher in males than in females in 2021. The sex disparities in the age-standardized DALY rate (ASDR) and ASMR of urolithiasis were negatively correlated with the SDI. In 2021, the ASIR of urolithiasis was 964.70 (95% UI = 801.26-1175.09) per 100,000 people in China, which is much lower than the global average (1242.84 [95% UI = 1034.94-1506.99] per 100,000 people). Compared with the global average, a more pronounced decline in ASIR was observed in China from 1793.16 (1446.0-2235.14) in 1990 to 964.70 (801.26-1175.09) per 100,000 people in 2021. CONCLUSIONS Urolithiasis poses a significant healthcare burden worldwide. More robust global and national strategies are warranted to address the prevention and treatment, especially in low SDI countries and regions.
Humans ; Urolithiasis/mortality* ; Male ; Female ; Incidence ; Global Burden of Disease ; Disability-Adjusted Life Years ; Adult ; Middle Aged ; Risk Factors ; Sex Factors