Abstract The prevention and control of myopia in Chinese children and adolescents has become a major public health issue. While maintaining increased outdoor activity as a cornerstone intervention, there is an urgent need to explore new complementary approaches that can be effectively implemented in both indoor and outdoor settings. In recent years, environmental spatial frequency has gained increasing attention as one of the key environmental factors influencing the development and progression of myopia. Both animal studies and human research have confirmed that indoor environments lacking mid to high spatial frequency components, often characterized as "visually impoverished", can promote axial elongation and myopia through mechanisms such as disruption of retinal neural signaling, impaired accommodative function, and altered expression of related molecules. Based on the scientific consensus, it is recommended that "enriching of environmental spatial frequency" should be integrated into the myopia prevention and control framework. Following the principles of schoolled organization, family cooperation, community involvement, and student participation, specific measures are put forward in three areas：optimizing school visual settings, improving home spatial environments, and promoting healthy visual behavior. The aim is to create "visually friendly" indoor environments as an important supplement to outdoor activity, thereby providing a novel perspective and strategy for comprehensively advancing myopia prevention and control among children and adolescents.

ObjectiveTo investigate the protective effects and mechanisms of Zhenzhu Tiaozhi capsules on the kidneys in the mouse model of diabetic kidney disease. MethodsThirty male C57BL/6J mice were selected as experimental objects. The model of diabetic kidney disease was induced by intraperitoneal injection of streptozotocin （STZ） at 40 mg·kg^-1 for 5 days combined with a high-fat diet （HFD）. Fasting blood glucose （FBG） ≥ 11.1 mmol·L^-1， increased urine volume， and continuous appearance of proteinuria indicated successful modeling. Mice were grouped as follows： Blank， model， low- and high-dose （0.98 and 1.96 g·kg^-1， respectively） Zhenzhu Tiaozhi capsules， and losartan potassium （30 mg·kg^-1）， with six mice in each group. After 12 weeks of continuous gavage， urine and kidney specimens were collected， and the 24-h urinary protein and the urinary albumin-to-creatinine ratio （UACR） in mice were measured. Hematoxylin-eosin （HE） staining， periodic acid-Schiff （PAS） staining， and Masson staining were performed for observation of histopathological changes in kidneys. Immunofluorescence assay was employed to detect the positive expression of the podocyte marker protein nephrin. Oil red O staining was used to detect renal lipid deposition. Enzyme linked immunosorbent assay was employed to measure the levels of interleukin-1β （IL-1β）， interleukin-6 （IL-6）， and tumor necrosis factor-α （TNF-α） in the renal tissue. Western blot was employed to determine the expression levels of sterol regulatory element-binding protein cleavage-activating protein （SCAP）， sterol regulatory element-binding protein-1c （SREBP-1c）， and NOD-like receptor protein 3 （NLRP3） in the renal tissue. ResultsCompared with the blank group， the model group showed increases in 24-h urinary protein and UACR （P<0.05）， glomeruli exhibiting capsule adhesion， collagen fiber deposition， mesangial proliferation， and inflammatory cell infiltration， elevated levels of IL-1β， IL-6， and TNF-α （P<0.05）， reduced positive expression of nephrin （P<0.05）， increased lipid deposition （P<0.05）， and up-regulated expression of SCAP， SREBP-1c， and NLRP3 （P<0.05） in the renal tissue. Compared with the model group， the treatment with losartan potassium or high-dose Zhenzhu Tiaozhi capsules for 12 weeks decreased 24-h urinary protein and UACR （P<0.05）， and the treatment with low-dose Zhenzhu Tiaozhi capsules for 12 weeks reduced the 24-h urinary protein （P<0.05）. Pathological staining results revealed that kidney damage in mice from all treatment groups was alleviated， with reduced inflammatory infiltration， collagen fiber deposition， and mesangial proliferation， and increased positive expression of nephrin in the renal tissue （P<0.05）. In addition， all the treatment groups showed reduced lipid droplets （P<0.05）， lowered levels of IL-1β， IL-6， and TNF-α （P<0.05）， and down-regulated expression of SCAP， SREBP-1c， and NLRP3 （P<0.05） in the renal tissue. ConclusionZhenzhu Tiaozhi capsules can ameliorate kidney damage in the mouse model of diabetic kidney disease by inhibiting the activation of the SCAP-SREBP-1c/NLRP3 signaling pathway， which reduces renal lipid deposition and inflammation.

ObjectiveTo investigate the protective effects and mechanisms of Zhenzhu Tiaozhi capsules on the kidneys in the mouse model of diabetic kidney disease. MethodsThirty male C57BL/6J mice were selected as experimental objects. The model of diabetic kidney disease was induced by intraperitoneal injection of streptozotocin （STZ） at 40 mg·kg^-1 for 5 days combined with a high-fat diet （HFD）. Fasting blood glucose （FBG） ≥ 11.1 mmol·L^-1， increased urine volume， and continuous appearance of proteinuria indicated successful modeling. Mice were grouped as follows： Blank， model， low- and high-dose （0.98 and 1.96 g·kg^-1， respectively） Zhenzhu Tiaozhi capsules， and losartan potassium （30 mg·kg^-1）， with six mice in each group. After 12 weeks of continuous gavage， urine and kidney specimens were collected， and the 24-h urinary protein and the urinary albumin-to-creatinine ratio （UACR） in mice were measured. Hematoxylin-eosin （HE） staining， periodic acid-Schiff （PAS） staining， and Masson staining were performed for observation of histopathological changes in kidneys. Immunofluorescence assay was employed to detect the positive expression of the podocyte marker protein nephrin. Oil red O staining was used to detect renal lipid deposition. Enzyme linked immunosorbent assay was employed to measure the levels of interleukin-1β （IL-1β）， interleukin-6 （IL-6）， and tumor necrosis factor-α （TNF-α） in the renal tissue. Western blot was employed to determine the expression levels of sterol regulatory element-binding protein cleavage-activating protein （SCAP）， sterol regulatory element-binding protein-1c （SREBP-1c）， and NOD-like receptor protein 3 （NLRP3） in the renal tissue. ResultsCompared with the blank group， the model group showed increases in 24-h urinary protein and UACR （P<0.05）， glomeruli exhibiting capsule adhesion， collagen fiber deposition， mesangial proliferation， and inflammatory cell infiltration， elevated levels of IL-1β， IL-6， and TNF-α （P<0.05）， reduced positive expression of nephrin （P<0.05）， increased lipid deposition （P<0.05）， and up-regulated expression of SCAP， SREBP-1c， and NLRP3 （P<0.05） in the renal tissue. Compared with the model group， the treatment with losartan potassium or high-dose Zhenzhu Tiaozhi capsules for 12 weeks decreased 24-h urinary protein and UACR （P<0.05）， and the treatment with low-dose Zhenzhu Tiaozhi capsules for 12 weeks reduced the 24-h urinary protein （P<0.05）. Pathological staining results revealed that kidney damage in mice from all treatment groups was alleviated， with reduced inflammatory infiltration， collagen fiber deposition， and mesangial proliferation， and increased positive expression of nephrin in the renal tissue （P<0.05）. In addition， all the treatment groups showed reduced lipid droplets （P<0.05）， lowered levels of IL-1β， IL-6， and TNF-α （P<0.05）， and down-regulated expression of SCAP， SREBP-1c， and NLRP3 （P<0.05） in the renal tissue. ConclusionZhenzhu Tiaozhi capsules can ameliorate kidney damage in the mouse model of diabetic kidney disease by inhibiting the activation of the SCAP-SREBP-1c/NLRP3 signaling pathway， which reduces renal lipid deposition and inflammation.

Kidney-Yang deficiency syndrome is a common geriatric disease that underlies chronic conditions such as diabetic nephropathy, chronic kidney disease, and osteoporosis. As age progresses, the kidney-Yang deficiency syndrome showcases increasingly pronounced manifestations, emerging as a key factor in the comorbidities experienced by elderly patients and affecting their quality of life and overall health status. Traditional Chinese medicine(TCM) has been extensively utilized in the treatment of kidney-Yang deficiency syndrome, with Epimedii Folium, Cinnamomi Cortex, and Lycii Fructus widely used in clinical settings. Despite the complexity of the molecular mechanisms involved in treating kidney-Yang deficiency syndrome, the potential therapeutic value of TCM remains compelling. Delving into the mechanisms of TCM treatment of kidney-Yang deficiency syndrome by regulating the neuro-endocrine-immune system can provide a scientific basis for targeted treatments of this syndrome and lay a foundation for the modernization of TCM. The pathophysiology of kidney-Yang deficiency syndrome involves multiple systems, including the interaction of the neuro-endocrine-immune system, the decline in renal function, the intensification of oxidative stress responses, and energy metabolism disorders. Understanding these mechanisms and their interrelationships can help untangle the etiology of kidney-Yang deficiency syndrome, aiding clinicians in making more precise diagnoses and treatments. Furthermore, the research on the specific applications of TCM in research on these pathological mechanisms can enhance the international recognition and status of TCM, enabling it to exert a greater global influence.
Humans ; Yang Deficiency/physiopathology* ; Drugs, Chinese Herbal/therapeutic use* ; Medicine, Chinese Traditional ; Kidney Diseases/physiopathology* ; Neurosecretory Systems/physiopathology* ; Animals ; Kidney/physiopathology* ; Endocrine System/physiopathology* ; Immune System/physiopathology*

In recent years, the application of artificial intelligence (AI) in the field of biology has witnessed remarkable advancements. Among these, the most notable achievements have emerged in the domain of protein structure prediction and design, with AlphaFold and related innovations earning the 2024 Nobel Prize in Chemistry. These breakthroughs have transformed our ability to understand protein folding and molecular interactions, marking a pivotal milestone in computational biology. Looking ahead, it is foreseeable that the accurate prediction of various physicochemical properties of proteins—beyond static structure—will become the next critical frontier in this rapidly evolving field. One of the most important protein properties is thermodynamic stability, which refers to a protein’s ability to maintain its native conformation under physiological or stress conditions. Accurate prediction of protein stability, especially upon single-point mutations, plays a vital role in numerous scientific and industrial domains. These include understanding the molecular basis of disease, rational drug design, development of therapeutic proteins, design of more robust industrial enzymes, and engineering of biosensors. Consequently, the ability to reliably forecast the stability changes caused by mutations has broad and transformative implications across biomedical and biotechnological applications. Historically, protein stability was assessed via experimental methods such as differential scanning calorimetry (DSC) and circular dichroism (CD), which, while precise, are time-consuming and resource-intensive. This prompted the development of computational approaches, including empirical energy functions and physics-based simulations. However, these traditional models often fall short in capturing the complex, high-dimensional nature of protein conformational landscapes and mutational effects. Recent advances in machine learning (ML) have significantly improved predictive performance in this area. Early ML models used handcrafted features derived from sequence and structure, whereas modern deep learning models leverage massive datasets and learn representations directly from data. Deep neural networks (DNNs), graph neural networks (GNNs), and attention-based architectures such as transformers have shown particular promise. GNNs, in particular, excel at modeling spatial and topological relationships in molecular structures, making them well-suited for protein modeling tasks. Furthermore, attention mechanisms enable models to dynamically weigh the contribution of specific residues or regions, capturing long-range interactions and allosteric effects. Nevertheless, several key challenges remain. These include the imbalance and scarcity of high-quality experimental datasets, particularly for rare or functionally significant mutations, which can lead to biased or overfitted models. Additionally, the inherently dynamic nature of proteins—their conformational flexibility and context-dependent behavior—is difficult to encode in static structural representations. Current models often rely on a single structure or average conformation, which may overlook important aspects of stability modulation. Efforts are ongoing to incorporate multi-conformational ensembles, molecular dynamics simulations, and physics-informed learning frameworks into predictive models. This paper presents a comprehensive review of the evolution of protein thermodynamic stability prediction techniques, with emphasis on the recent progress enabled by machine learning. It highlights representative datasets, modeling strategies, evaluation benchmarks, and the integration of structural and biochemical features. The aim is to provide researchers with a structured and up-to-date reference, guiding the development of more robust, generalizable, and interpretable models for predicting protein stability changes upon mutation. As the field moves forward, the synergy between data-driven AI methods and domain-specific biological knowledge will be key to unlocking deeper understanding and broader applications of protein engineering.

The connection between tendons and bones is called the tendon bone connection. With the continuous improvement of national sports awareness, excessive exercises and the related intensity are prone to damage the tendon bone connection. Tendon bone healing is a complex repair and healing process involving multiple factors, and good tendon bone healing is a prerequisite for its physiological function. The complexity of tendon bone structure also poses great challenges to the repair of tendon bone injuries. In recent years, researches have found that stem cells, growth factors, macrophages, and other factors are closely related to the healing process of tendon bone injuries, among which macrophages play an important role in the healing process. The authors reviewed relevant research literature in recent years and summarized the role of macrophages in tendon bone healing, in order to provide new ideas and directions for treatment strategies to promote tendon bone healing.
Humans ; Macrophages/metabolism* ; Wound Healing ; Animals ; Tendons/physiology* ; Bone and Bones/injuries* ; Tendon Injuries

In hypoxic-ischemic brain damage (HIBD), the programmed cell death known as ferroptosis is significantly activated. Microglial cells demonstrate a high level of sensitivity to iron accumulation. Understanding how to regulate the dual role of microglia and transforming the microglial ferroptosis to a moderate and controllable process has considerable implications for the targeted treatment in HIBD. This paper serves as an overview of microglia-mediated ferroptosis in HIBD as a disease model. We discuss various aspects centered around microglia, including pathophysiological mechanisms, polarization and functions of microglia, molecular mechanisms of ferroptosis, signaling pathways, and therapeutic strategies. The review aims to provide a reference for studies of ferroptosis in microglia.
Microglia/physiology* ; Ferroptosis/physiology* ; Humans ; Animals ; Hypoxia-Ischemia, Brain/pathology* ; Signal Transduction

This study investigated the impact of metabolic syndrome (MetS) and its components on prostate volume (PV) in the general Chinese population. In total, 43 455 participants in The First Medical Center of the Chinese PLA General Hospital (Beijing, China) from January 1, 2012, to December 31, 2022, undergoing health examinations were included in the study. Participants were categorized into four groups according to PV quartiles: Q1 (PV ≤24.94 ml), Q2 (PV >24.94 ml and ≤28.78 ml), Q3 (PV >28.78 ml and ≤34.07 ml), and Q4 (PV >34.07 ml), with Q1 serving as the reference group. Logistic regression analyses were used to examine the association between MetS and PV, with subgroup analyses conducted by age. Among the participants, 18 787 (43.2%) were diagnosed with MetS. In the multivariate analysis model, a significant correlation between MetS and PV was observed, with odds ratios (ORs) increasing as PV increased (Q2, OR = 1.203, 95% confidence interval [CI]: 1.139-1.271; Q3, OR = 1.300, 95% CI: 1.230-1.373; and Q4, OR = 1.556, 95% CI: 1.469-1.648). Analysis of MetS components revealed that all components were positively associated with PV, with abdominal obesity showing the most significant effect. The number of MetS components was identified as a dose-dependent risk factor for elevated PV. The impact of MetS, its components, and component count on PV exhibited a decreasing trend with advancing age. Overall, the influence of MetS, its components, and component count on PV was predominantly observed in the age groups of 40-49 years and 50-59 years. Early intervention targeting MetS can significantly alleviate the increase in PV, particularly benefiting individuals aged 40-59 years who have abdominal obesity.
Humans ; Male ; Metabolic Syndrome/complications* ; Middle Aged ; Cross-Sectional Studies ; Aged ; Prostate/diagnostic imaging* ; Adult ; Age Factors ; Organ Size ; China/epidemiology* ; Obesity, Abdominal ; Risk Factors

The relationship between hyperuricemia (HUA) and erectile dysfunction (ED) remains inadequately understood. Given that HUA is often associated with various metabolic disorders, this study aims to explore the multivariate linear impacts of metabolic parameters on erectile function in ED patients with HUA. A cross-sectional analysis was conducted involving 514 ED patients with HUA in the Department of Andrology, Jiangsu Province Hospital of Chinese Medicine (Nanjing, China), aged 18 to 60 years. General demographic information, medical history, and laboratory results were collected to assess metabolic disturbances. Sexual function was evaluated using the 5-item version of the International Index of Erectile Function (IIEF-5) questionnaire. Based on univariate analysis, variables associated with IIEF-5 scores were identified, and the correlations between them were evaluated. The effects of these variables on IIEF-5 scores were further explored by multiple linear regression models. Fasting plasma glucose ( β = -0.628, P < 0.001), uric acid ( β = -0.552, P < 0.001), triglycerides ( β = -0.088, P = 0.047), low-density lipoprotein cholesterol ( β = -0.164, P = 0.027), glycated hemoglobin (HbA1c; β = -0.562, P = 0.012), and smoking history ( β = -0.074, P = 0.037) exhibited significant negative impacts on erectile function. The coefficient of determination ( R ²) for the model was 0.239, and the adjusted R ² was 0.230, indicating overall statistical significance ( F -statistic = 26.52, P < 0.001). Metabolic parameters play a crucial role in the development of ED. Maintaining normal metabolic indices may aid in the prevention and improvement of erectile function in ED patients with HUA.
Humans ; Male ; Erectile Dysfunction/metabolism* ; Hyperuricemia/metabolism* ; Adult ; Middle Aged ; Cross-Sectional Studies ; Glycated Hemoglobin/metabolism* ; Blood Glucose/metabolism* ; Uric Acid/blood* ; Young Adult ; Triglycerides/blood* ; Adolescent ; Cholesterol, LDL/blood* ; Penile Erection/physiology* ; Surveys and Questionnaires

BACKGROUND: The incidence and mortality rates of lung cancer remain on the rise, creating an urgent need for screening among high-risk populations and early prevention. This study aims to explore the association and interaction between multidimensional lifestyle, socioeconomic status, and the incidence of lung cancer, and to provide scientific evidence for screening high-risk populations and preventing lung cancer. METHODS: Healthy lifestyle score was constructed using information on smoking, alcohol consumption, exercise, diet and sleep obtained through a questionnaire survey. Socioeconomic status was evaluated based on information on education, employment, and family income, and genetic testing data were used to assess the risk of genetic variation. A proportional hazards assumption test was conducted, and the Cox proportional hazards model was applied to analyze the associations between healthy lifestyle scores, socioeconomic status, and lung cancer, as well as the interactions among various factors, after adjusting for the risk of genetic variation, age, gender, diabetes, hypertension and the living environment score. RESULTS: A total of 245,538 samples that entered the cohort from March, 2006 to October, 2010 were included and followed up until December 31, 2022. The participants were divided into the case group (n=1472) and the control group (n=244,066). The analysis results showed that after adjusting for covariates, there was still an association between the healthy lifestyle score, socioeconomic status, and the incidence of lung cancer: compared with participants with a high healthy lifestyle score, the risk of lung cancer in participants with medium and low healthy lifestyle scores was significantly increased, with hazard ratios (HR) of 2.12 (95%CI: 1.86-2.41) and 3.36 (95%CI: 2.82-3.99) respectively; compared with participants with high socioeconomic status, the risk of lung cancer in participants with medium and low socioeconomic status was significantly increased, with HR of 1.29 (95%CI: 1.13-1.48) and 1.67 (95%CI: 1.46-1.90) respectively. Moreover, there were interactions between smoking status and socioeconomic status (Pfor interaction=0.05), as well as the other four lifestyle factors (Pfor interaction=0.02). CONCLUSIONS This study identified the association between multidimensional lifestyle factors and socioeconomic status with the incidence of lung cancer, as well as interactions between smoking and socioeconomic status and four other lifestyle factors, providing a scientific basis for screening and prevention in high-risk populations for lung cancer.
Humans ; Lung Neoplasms/epidemiology* ; Male ; Female ; Middle Aged ; Incidence ; Life Style ; Social Class ; Aged ; Adult ; Risk Factors