With the accelerating aging of world population, the prevalence and disease burden of dementia such as Alzheimer's disease is increasing annually. As one of the major risk factors for dementia, air pollution is still an urgent global concern. Studies on the association between ambient particulate matter (PM), one of the major air pollutants, and dementia, such as Alzheimer's disease, are gaining attention. This paper reviewed the current evidence of relevant epidemiological and toxicological studies to illustrate the possible mechanisms underlying the effects of PM exposure on Alzheimer's disease through inflammatory responses, oxidative stress, endocrine disruption, excitatory neurotoxicity, glial cell activation, and intestinal flora disruption, which may provide clues for mitigating the health risks of air pollution and preventing Alzheimer's disease.

To evaluate the therapeutic effect of baicalein topical preparation on atopic dermatitis, we first constructed two atopic dermatitis-like mouse models induced by calcipotriol and 1-fluoro-2,4-dinitrobenzene to assess their therapeutic effect with skin tissue staining and other experiments. It was found that topical preparation of baicalein could alleviate epidermal thickening of diseased skin tissues, repair damaged skin barrier proteins, and inhibit T helper 2 cells (Th2) infiltration and mast cell infiltration and activation in lesional sites. Cyberpharmacology was utilized to analyze whether baicalein could treat atopic dermatitis by interfering with multiple pathogenesis-associated pathways. Results indicated that baicalein reduced the mRNA levels of inflammatory factors and inhibited the phosphorylation of NF-κB p65 and STAT1 proteins in keratinocyte cells. Together, the topical preparation of baicalein may be effective in alleviating atopic dermatitis-like symptoms in mice by down-regulating the phosphorylation level of NF-κB in keratinocytes, thereby decreasing the expression of inflammatory factors in keratinocytes, which provides an idea and a theoretical basis for the topical preparation of baicalein for the treatment of inflammatory skin diseases such as atopic dermatitis.

Objective: To develop and validate a health literacy assessment scale for junior high school students, providing an effective tool for evaluating and monitoring health literacy among Chinese adolescents. Methods: Based on school health education policy documents, a health literacy assessment framework was constructed, comprising five horizontal and four vertical dimensions. From May to June and August to September in 2024, the framework was refined through Delphi expert consultations and focus group discussions, leading to the development of the Health Literacy Assessment Scale for Junior High School Students. In September 2024, a convenience sample of 625 students from three junior high schools in Beijing and Tianjin completed the questionnaire. Item analysis, reliability, and validity tests were conducted to evaluate the scale. Results: The recovery rate for two rounds of expert consultation questionnaires was 100%. The expert authority coefficients ( Cr ) were 0.86 and 0.87 respectively (both >0.70), with Kendall W values of 0.34 and 0.27 ( P <0.05). The focus group discussions followed a rigorous structure, and after multiple rounds of item screening and revision, the version 3.0 of the junior high school students health literacy assessment scale was developed, comprising 57 items. Three items that failed to meet the comprehensive screening criteria were preliminarily removed, and the final scale contained 54 items. The scale demonstrated excellent reliability, with an overall Cronbach s α coefficient of 0.92 and split half reliability of 0.93. Confirmatory factor analysis [ χ 2/df =2.094, root mean square error of approximation ( RMSEA )=0.042, comparative fit index ( CFI )=0.911, Tucker Lewis index ( TLI )=0.907] indicated good model fit indices. Conclusions The preliminary development of the health literacy assessment scale for junior high school students follows a rigorous item screening process with well designed dimensions, demonstrating good reliability and validity, thus serving as an appropriate evaluation tool for adolescent health literacy.

Objective: To identify biomolecular markers closely related to the occurrence of kidney renal clear cell carcinoma (KIRC) and verify their expression levels in clinical samples. Methods: Stage Ⅰ KIRC mRNA sequencing data were obtained from The Cancer Genome Atlas (TCGA).Principal component analysis (PCA) was used for dimensionality reduction to screen differentially expressed genes (DEGs)，which then underwent GO and KEGG analyses.Weighted gene co-expression network analysis (WGCNA) was used to screen genes significantly related to KIRC，and a protein-protein interaction (PPI) network was constructed to screen hub genes.The diagnostic value of hub genes was evaluated with receiver operating characteristic (ROC) curve，and their prognostic value was analyzed using survival curve plots.The correlation between the mRNA expressions of hub genes and the pathological stages of KIRC was analyzed.Clinical samples of 20 patients with stage Ⅰ KIRC treated in our hospital were included，and the expressions of the hub genes in cancerous and adjacent tissues were detected with reverse transcription real-time quantitative polymerase chain reaction (RT-qPCR)，Western blotting，and enzyme-linked immunosorbent assay (ELISA). Results: A total of 8223 DEGs were screened out，including 4092 up-regulated ones and 4131 down-regulated ones.GO analysis showed that DEGs were related to bioadhesion，plasma membrane composition，and transporter activity.KEGG analysis showed that DEGs were related to pathways such as cell adhesion molecules，cytokine-cytokine receptor interactions，and interactions between viral proteins and cytokines and cytokine receptors.WGCNA analysis obtained 171 genes that were significantly related to stage Ⅰ KIRC.The hub gene，lymphocyte cytosolic protein 2 (LCP2)，screened out by the PPI network，was significantly related to stage Ⅰ KIRC.The area under the ROC curve was 0.96.The expression level was negatively correlated with the overall survival rate of patients.The expression of LCP2 was related to the stage and lymph node metastasis.Clinical verification showed that the mRNA and protein relative expressions of LCP2 in KIRC tissues were significantly higher than those in adjacent tissues (P<0.000 1). Conclusion: LCP2 is significantly up-regulated in stage Ⅰ KIRC tissues and can be used as a potential biomarker for the early diagnosis and treatment of KIRC.

To understand the progress of, summarize the lessons learned from and analyze the challenges in the national schistosomiasis elimination program of China in 2024, this article presented the endemic situation of schistosomiasis and national schistosomiasis surveillance results in the People’s Republic of China in 2024. By the end of 2024, Shanghai Municipality, Zhejiang Province, Fujian Province, Guangdong Province and Guangxi Zhuang Autonomous Region continued to consolidate schistosomiasis elimination achievements, and 7 provinces of Jiangsu, Sichuan, Yunnan, Hubei, Hunan, Anhui and Jiangxi maintained the criteria of schistosomiasis transmission interruption. A total of 450 counties (cites, districts) were found to be endemic for schistosomiasis in China in 2024, including 26 061 endemic villages covering 73 630 500 residents at risk of infections. Among the 450 counties (cities, districts) endemic for schistosomiasis, 388 (86.22%) achieved the criteria of schistosomiasis elimination and 62 (13.78%) achieved the criteria of transmission interruption. In 2024, a total of 4 102 624 individuals received immunological tests for schistosomiasis in China, with 44 823 sero-positives identified (1.09% seroprevalence), and a total of 169 722 individuals received parasitological examinations, with 1 egg-positives detected. A total of 27 321 cases with advanced schistosomiasis were documented in China by the end of 2024. In 2024, a total of 575 686 bovines were raised in schistosomiasis-endemic villages of China, and 113 842 bovines received immunological tests, with 235 sero-positives detected (0.21% seroprevalence), while no egg-positives were identified among the 167 475 bovines receiving parasitological examinations. In 2024, snail survey was performed covering an area of 680 498.27 hm² in China, and 190 778.66 hm² snail habitats were identified, including 59.09 hm² emerging snail habitats and 704.23 hm² reemerging snail habitats. In 2024, a total of 19 665 schistosomiasis patients receiving chemotherapy with praziquantel in China, and expanded chemotherapy was given to humans at 571 722 person-times and to bovines at 306 740 herd-times. In addition, snail control with chemical treatment covered 117 111.37 hm² snail habitats across China in 2024, and the actual area of chemical treatment was 66 562.95 hm², while environmental improvements were performed in snail habitats covering an area of 1 374.26 hm². The national schistosomiasis surveillance results showed that the mean prevalence rates of Schistosoma japonicum infections were both 0 among humans and bovines in China in 2024, and no S. japonicum infection was detected in snails. These data demonstrated that the prevalence of schistosomiasis remained at a low level in China in 2024; however, the areas of snail habitats remained high and the number of fenced cattle showed a slight increase. To address these risks, it is imperative to maintain the integrated strategy with an emphasis on management of the source of S. japonicum infection and intensified snail control in high-risk areas, and to reinforce schistosomiasis surveillance and forecast and snail control in high-risk areas.

Objective To study the relationship between serum insulin-like growth factor-1 (IGF-1) and resistin levels and osteoporosis in patients with type 2 diabetes mellitus (T2DM). Methods This study was conducted on 306 T2DM patients admitted to Baoding No.2 Central Hospital from January 2018 to January 2022. According to the detection results of bone mineral density, the patients were divided into osteoporosis group (T≤-2.5) and non-osteoporosis group (T>-2.5). The differences in IGF-1, resistin and bone mineral density were compared between the two groups. Pearson correlation analysis was used to analyze the correlation between serum IGF-1 and resistin levels and bone mineral density in patients with osteoporosis. Receiver operating characteristic (ROC) curve was applied to evaluate the application value of IGF-1 and resistin in predicting osteoporosis in patients with T2DM. Patients with T2DM complicated with osteoporosis were followed up for 2 years, and the occurrence of fractures was assessed. After univariate analysis, multivariate logistic regression analysis was applied to screen the risk factors for fractures in T2DM patients with osteoporosis. Results The incidence rate of osteoporosis in patients with T2DM was 53.59% (164/306). The IGF-1 level and bone mineral density level in the osteoporosis group were lower than those in the non-osteoporosis group, while the level of resistin was higher than that in the non-osteoporosis group (P<0.05). Serum IGF-1 in patients with osteoporosis was positively correlated with bone mineral density, and serum resistin was negatively correlated with bone mineral density (P<0.05). The AUC, sensitivity and specificity of combination of IGF-1 and resistin in predicting osteoporosis were 0.888, 82.93% and 62.68% respectively, which were all higher than those of single factor prediction (P<0.05). The 164 T2DM patients with osteoporosis were followed up for two years, and 15 patients developed fragility fractures, with the incidence of fracture of 9.15% (15/164). Multivariate analysis showed that hypoproteinemia, high-intensity exercise, lack of nutritional management, low IGF-1, and high resistin were risk factors for fractures in patients with T2DM complicated with osteoporosis (P<0.05). Conclusion For patients with T2DM, the incidence rates of osteoporosis and fractures are high. The levels of IGF-1 and resistin are closely related to bone mineral density, which can be combined to predict osteoporosis. Hypoproteinemia, high-intensity exercise, lack of nutritional management, low IGF-1 and high resistin are risk factors for fractures in T2DM patients with osteoporosis. It is necessary to carry out targeted preventive measures in clinical practice to reduce the incidence rate of fractures.

ObjectiveTo explore the effect and mechanism of Qigui Didang decoction， formulated based on the principle of Tonifying Deficiency and Unblocking Collaterals， on improving metabolic memory of db/db mice with diabetic nephropathy （DN） through silent information regulator 1 signal regulator 1 （Sirt1）/p53/nuclear factor kappa-B （NF-κB） p65 pathway. MethodsFifteen db/db mice were randomly divided into model group （10 mL·kg^-1·d^-1）， resveratrol group （20 mg·kg^-1·d^-1）， and Qigui Didang decoction group （3.34 g·kg^-1·d^-1） Another five db/m mice were selected as the normal group （10 mL·kg^-1·d^-1）. After the intervention， the kidney weight of each group was measured， and the kidney index （KI） was calculated. Fasting blood glucose （FBG）， creatinine （CRE）， β2-microglobulin （β2-MG）， blood urea nitrogen （BUN）， and cystatin C （CysC） were measured. Renal pathology was observed by hematoxylin-eosin （HE） staining and Masson staining. The mRNA and protein expression levels of Sirt1， NF-κB， tumor suppressor gene p53， interleukin-1β （IL-1β）， and cysteine aspartate protease-3 （Caspase-3） were detected using real-time quantitative polymerase chain reaction （Real-time PCR） and Western blot. ResultsCompared with the normal group， the model group showed disordered renal structure， obvious renal damage， and markedly elevated levels of renal function indexes （CRE， β2-MG， BUN， and CysC） （P<0.01）. The KI and blood glucose were significantly increased （P<0.01）， while Sirt1 expression was markedly decreased （P<0.01）. Expression levels of NF-κB p65， p53， IL-1β， and Caspase-3 were increased significantly （P<0.05）. Compared with those in the model group， DN mice treated with Qigui Didang decoction exhibited significantly decreased FBG， improved renal function， and markedly decreased KI （P<0.01）， along with reduced CRE， β2-MG， BUN， and CysC levels （P<0.05）. Protein expression of Sirt1 was significantly upregulated （P<0.05）， while that of NF-κB p65， p53， IL-1β， and Caspase-3 was markedly decreased （P<0.05）. The mRNA expression levels of NF-κB p65， p53， IL-1β， and Caspase-3 were significantly decreased （P<0.05）. The staining results indicate improved renal fibrosis， significantly decreased fiber deposition （P<0.05）， and less inflammatory infiltration in the Qigui Didang decoction group. ConclusionThe findings suggest that Qigui Didang decoction can alleviate the metabolic memory effect of DN， thereby inhibiting renal cell apoptosis and inflammatory response in mice， and improving renal function. The mechanism of action is closely related to the Sirt1/p53/NF-κB p65 signaling pathway.

Based on current national policies, regulations, standards, relevant literature, and departmental experience regarding the protection against radionuclides in China, this study provides a brief overview of key issues in the management of hospital wards for patients with internal radionuclide contamination. The discussion covers the detection of internal contamination, general requirements for internal radionuclide contamination wards, and inpatient management. In addition, the study explores in depth the daily responsibilities, protective measures, and management protocols for both healthcare staff and patients within such wards. This article summarizes a framework for the construction of internal radionuclide contamination wards, along with specific plans and detailed role-based guidelines. These results provide a reference for the management of hospital wards for patients with internal radionuclide contamination.

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.

Objective To understand the disease spectrum of a natural village in an area with high incidence of esophageal cancer to provide a reference for precise prevention and control. Methods From 2008 to 2024, 711 asymptomatic people over the age of 35 years in a natural village with high incidence of esophageal cancer in China were surveyed, and 171 of them were subjected to gastroscopy, biopsy, and pathological examination. All participants were followed up for a long time, and their disease history was recorded. Results A total of 16 years of follow-up were performed, and 703 people were effectively followed up. In 2008, 171 people underwent gastroscopy, and 160 people had biopsy and pathological results in endoscopic screening. By 2024, 76 people had been diagnosed with malignant tumors of 12 different types, and among these people, 45 had esophageal cancer. Conclusion Esophageal cancer remains a significant cause of morbidity and mortality from malignant tumors in this region. Biopsy and pathological examination should be strengthened during gastroscopy, and follow-ups and regular check-ups should be given high importance to reduce the incidence and mortality rates of esophageal cancer.