OBJECTIVE To investigate the application status of prescription pre-review systems in healthcare institutions of Yunnan province， evaluate their system functions and management capabilities， and provide a practical basis for promoting rational drug use. METHODS A questionnaire survey was conducted among public healthcare institutions at or above the secondary level in Yunnan province to investigate the deployment status of the systems. A capability maturity assessment framework was constructed， encompassing 6 dimensions and 39 indicators， including real-time prescription review， prescription correlation review， rule setting， evidence-based information support， prescription authority management， and system operation management. This framework was then used to evaluate the institutions that had implemented the pre-review systems. RESULTS A total of 100 valid questionnaires were collected， with 37 institutions having adopted prescription pre-review systems， mainly tertiary hospitals. The system predominantly adopted a modular architecture and was embedded into the hospital information system through application programming interfaces and middleware， providing certain capabilities for real-time prescription risk identification. Evaluation results indicated that basic functions such as reviewing indications， contraindications， and drug compatibility performed well， while deficiencies remained in functions related to parenteral nutrition prescription， review of drug dosage for specific diseases， individual patient characteristic recognition， and rule setting. Moreover， the construction of review centers and establishment of management systems were also not well-developed. CONCLUSIONS The overall application rate of prescription pre-review systems in Yunnan province remains low. System functions and management mechanisms require further improvement. It is recommended to enhance information infrastructure in lower-level institutions and explore regionally unified review models to promote standardized and intelligent development of prescription review practices.

Objective To explore the application of plasma 7 microRNA (miR7) testing in the differential diagnosis of very early-stage hepatocellular carcinoma (HCC). Methods This study is a multicenter real-world study. Patients with single hepatic lesion (maximum diameter≤2 cm) who underwent plasma miR7 testing at Zhongshan Hospital, Fudan University, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Anhui Provincial Hospital, and Peking University People’s Hospital between January 2019 and December 2024 were retrospectively enrolled. Patients were divided into very early-stage HCC group and non-HCC group, and the clinical pathological characteristics of the two groups were compared. The value of plasma miR7 levels, alpha-fetoprotein (AFP), and des-gamma-carboxy prothrombin (DCP) in the differential diagnosis of very early-stage HCC was evaluated using receiver operating characteristic (ROC) curves and area under the curve (AUC). In patients with both negative AFP and DCP (AFP＜20 ng/mL, DCP＜40 mAU/mL), the diagnostic value of plasma miR7 for very early-stage HCC was analyzed. Results A total of 64 528 patients from 4 hospitals underwent miR7 testing, and 1 682 were finally included, of which 1 073 were diagnosed with very early-stage HCC and 609 were diagnosed with non-HCC. The positive rate of miR7 in HCC patients was significantly higher than that in non-HCC patients (67.9% vs 24.3%, P＜0.001). ROC curves showed that the AUCs for miR7, AFP, and DCP in distinguishing HCC patients from the non-HCC individuals were 0.718, 0.682, and 0.642, respectively. The sensitivities were 67.85%, 43.71%, and 44.45%, and the specificities were 75.70%, 92.78%, and 83.91%, respectively. The pairwise comparison of AUCs showed that the diagnostic efficacy of plasma miR7 detection was significantly better than that of AFP or DCP (P＜0.05). Although its specificity was slightly lower than AFP and DCP, the sensitivity was significantly higher. Among patients negative for both AFP and DCP, miR7 maintained an AUC of 0.728 for diagnosing very early-stage HCC, with 67.82% sensitivity and 77.73% specificity. Conclusions Plasma miR7 testing is a potential molecular marker with high sensitivity and specificity for the differential diagnosis of small hepatic nodules. In patients with very early-stage HCC lacking effective molecular markers (negative for both AFP and DCP), miR7 can serve as a novel and effective molecular marker to assist diagnosis.

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 incidence risk and risk factors of tuberculosis (TB) among middle school students in Chongqing, so as to provide a basis for formulating TB prevention and control strategies. Methods: From September to December 2022, 32 181 middle school students were selected as the study cohort from 15 administrative districts in Chongqing by using the stratified cluster random sampling method. All cohort members were screened with the tuberculin skin test (TST), and relevant information was collected from January 1, 2023 to December 31, 2024. On the basis of active screening, the follow up data of the participants were compared with the National Tuberculosis Management Information System to obtain the incidence status of the study subjects. The Log rank test was used to compare the TB incidence rates among students with different characteristics, and a Cox proportional hazards model was established to analyze the incidence risk and risk factors of TB. Results: The TST screening rate of the cohort members was 93.0%. During the 2 year follow up period, a total of 36 TB cases occurred, with a cumulative incidence rate of 111.87/100 000 and an incidence density of 55.95/100 000. Among them, the cumulative incidence rate of students from public schools (170.44/ 100 000 ) was higher than that of students from private schools (41.16/100 000), the cumulative incidence rate of students in schools located in high epidemic areas (153.95/100 000) was higher than that in medium epidemic areas (69.00/100 000), and the difference was statistically significant ( χ 2=11.49, 4.73, both P <0.05). The Log-rank test for different TST results showed that the difference in TB comulative incidence rate between students with strongly positive TST results (216.55/ 100 000 ) and those with negative TST results (81.40/100 000) was statistically significant ( χ 2=5.85, P <0.05). Univariate analysis using the Cox proportional hazards model revealed that the risk of TB was lower in students from private schools ( HR=0.25, 95% CI = 0.10-0.59) and students in medium epidemic areas ( HR=0.46, 95%CI =0.23-0.94); whereas the risk of TB was increased in students with strongly positive TST results ( HR=1.39, 95%CI =1.05-1.84) (all P <0.05). Multivariate Cox regression analysis showed that the risk of TB in students from private schools was lower than that of students from public schools ( HR=0.23, 95%CI=0.08-0.62, P <0.05). Conclusions The annual average incidence rate of TB among middle school students in Chongqing is at a relatively high level. It is necessary to strengthen the management and intervention for student groups, including those in public schools, those in schools located in high epidemic areas, and those with strongly positive TST results, so as to reduce the incidence rate of TB.

Objective To analyze and compare the disease burden of high BMI in Kunshan City in different periods, and to provide a scientific basis for the prevention and control of overweight and obesity in Kunshan City. Methods Using the global burden of disease research method, the number of deaths attributable to high BMI and attributable YLL in Kunshan City were calculated using the survey data of chronic diseases and their risk factors and the data of the death registration system in Kunshan City. Results In 2023, R5.46% of deaths in Kunshan City were attributed to high BMI, with 345 attributable deaths, and attributable mortality rate and standardized attributable mortality rate were 39.16/100 000 and 33.82/100 000, Rrespectively. Attributable YLL rate and standardized attributable YLL rate were 692.35/100 000 and 604.46/100 000, respectively. High BMI caused a loss of 0.52 years of life expectancy per capita. Compared with 2012, PAF, standardized attributable mortality rate, standardized attributable YLL rate and life expectancy loss per capita of high BMI in 2023 increased by 121.95%, 100.71%, 57.05%, and 100%, respectively. Among different genders, PAF increased by 91.05% for males and 161.97% for females from 2012 to 2023. Among different diseases, cardiovascular and cerebrovascular diseases and cancers had the highest attributable disease burden, while diabetes, chronic kidney disease and Alzheimer's disease all had a significant increase. Conclusion The burden of disease attributable to high BMI has risen dramatically in Kunshan City, and the adverse health effects of overweight and obesity need to be reduced through scientific weight loss and comprehensive practical measures.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To analyze the change trends in the body shape indicators and proportions of students in Harbin from 2010 to 2024, and to investigate ergonomic compatibility of functional dimensions of school desks and chairs with current student shape indicators, so as to provide a reference for revising furniture standards of desks and chairs. Methods: Between September and November of both 2010 and 2024, a combination of convenience sampling and stratified cluster random sampling was conducted across three districts in Harbin, yielding samples of 6 590 and 6 252 students, respectively. Anthropometric shape indicators cluding height, sitting height, crus length, and thigh length-and their proportional changes were compared over the 15-year period. The 2024 data were compared with current standard functional dimensions of school furniture. The statistical analysis incorporated t-test and Mann-Whitney U- test. Results: From 2010 to 2024, average height increased by 1.8 cm for boys and 1.5 cm for girls; sitting height increased by 1.5 cm for both genders; crus length increased by 0.3 cm for boys and 0.4 cm for girls; and thigh length increased by 0.5 cm for both genders. The ratios of sitting height to height, and sitting height to leg length increased by less than 0.1 . The difference between desk chair height and 1/3 sitting height ranged from 0.4-0.8 cm. Among students matched with size 0 desks and chairs, 22.0% had a desk to chair height difference less than 0, indicating that the desk to chair height difference might be insufficient for taller students. The differences between seat height and fibular height ranged from -1.4 to 1.1 cm; and the differences between seat depth and buttock popliteal length ranged from -9.8 to 3.4 cm. Among obese students, the differences between seat width and 1/2 hip circumference ranged from -20.5 to -8.7 cm, while it ranged from -12.2 to -3.8 cm among non obese students. Conclusion Current furniture standards basically satisfy hygienic requirements; however, in the case of exceptionally tall and obese students, ergonomic accommodations such as adaptive seating allocation or personalized adjustments are recommended to meet hygienic requirements.

Circadian rhythm refers to the 24-hour periodic changes in behavior, physiology, and molecular processes in the human body. Disruptions to the circadian rhythm not only affect mental health but are also associated with various metabolic disorders, including the regulation of bone and muscle metabolism. Research has shown that work-related musculoskeletal disorders (WMSDs) are influenced not only by workload but also by circadian rhythm factors, such as shift work. This review examined the relationships between circadian rhythm-related antecedents, outcomes, and WMSDs, exploring their shared metabolic markers and mechanisms. It provided a systematic overview of the intrinsic connection between circadian rhythm disruptions and WMSDs. While current studies highlight the impact of circadian rhythm disturbances on musculoskeletal disorders, further investigation is required to address the confounding factors involved. Future research should integrate chronobiology with both subjective and objective data to explore the pathway from environmental factors to intermediate phenotypes to diseases, ultimately providing a more comprehensive understanding of the network mechanisms underlying WMSDs.

Objective To analyze the burden of disease of malignant tumors in Kunshan City from 2006 to 2021. Methods The global burden of disease research methodology was applied. The indicators of cancer incidence, mortality, and disability-adjusted life years (DALYs) in Kunshan were calculated using the data from the Tumor Registry System and Death Registry System in Kunshan. The changes in cancer were compared. Results In 2021, the number of incidences and deaths and the DALYs of cancer were 4724 cases, 1618 cases, and 20887.90 person-years, respectively. The incidence, mortality, and DALYs rates were 427.42/100000, 146.39/100000, and 18.90‰. Compared with those in 2006, the incidence rate increased by 53.40%, and the mortality and DALYs rates decreased by 24.23% and 25.73%, respectively. The DALYs rate of cancer was higher for males than for females at 22.12‰ and 15.91‰ in 2021, respectively. The DALYs rate increased with age, and it started to increase sharply after 45 years of age. The top 10 cancers in 2021 in terms of DALYs were lung cancer, stomach cancer, colorectal cancer, liver cancer, pancreatic cancer, breast cancer, leukemia, esophageal cancer, brain and nervous system cancer, and gallbladder and biliary tract cancer, accounting for 83.83% of all cancers. The proportion of years lived with disability (YLD) in DALYs increased continuously (27% in 2021), with females increasing faster than males. Conclusion The disease burden of cancer in Kunshan City remains high, and the incidence of cancer must be reduced by developing comprehensive measures and continuously strengthening the capacity of early screening and treatment of cancer.

ObjectiveTo investigate the chemical constituents of Chuanxiong Rhizoma-Paeoniae Radix Rubra（CRPRR） that cross the blood-brain barrier in rats with ischemic stroke， their brain-protective effects， and their impact on inflammatory factors including tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， and interleukin-18 （IL-18） based on ultra-high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry （UPLC-Q-TOF-MS） and pharmacodynamic experiments. MethodsA focal cerebral ischemia-reperfusion injury model was established in rats via the middle cerebral artery occlusion/reperfusion （MCAO/R） method using intraluminal suture. Neurological function was evaluated using behavioral scoring. UPLC-Q-TOF-MS was employed to identify the chemical constituents of CRPRR that crossed the blood-brain barrier and entered the cerebrospinal fluid in MCAO/R model rats. Male Sprague-Dawley rats were randomly divided into six groups： sham operation group， model group， low-， medium-， and high-dose CRPRR groups （1.35， 2.7， 5.4 g·kg^-1， respectively）， and an edaravone group （5 mg·kg^-1）， with 12 rats in each group. The sham and model groups received normal saline， while the treatment groups received the respective doses of CRPRR once daily by gavage for three consecutive weeks. The brain-protective effects of CRPRR were assessed using the Longa five-point scoring method， open field test， Morris water maze， 2，3，5-triphenyltetrazolium chloride （TTC） staining， hematoxylin and eosin （HE） staining， and transmission electron microscopy. ResultsNine chemical constituents were identified in the cerebrospinal fluid containing CRPRR， namely paeoniflorin， senkyunolide F， senkyunolide G， paeonimetabolin Ⅰ， paeoniflorin derivative， senkyunolide H， benzoylpaeoniflorin， senkyunolide A， and ligustilide. Animal experiment results showed that compared with the sham operation group， the model group exhibited disordered neuronal arrangement， severe vacuolation， nuclear pyknosis， and evident mitochondrial swelling. Chromatin aggregation and peripheralization were also observed. Neurological scores and the number of crossings in the central region were significantly increased （P<0.01）， while platform crossings were significantly decreased （P<0.01）， and clear infarct areas were present （P<0.01）. Serum levels and protein expression of TNF-α， IL-1β， and IL-18 were significantly elevated （P<0.01）. Compared with the model group， all dose groups of CRPRR showed marked improvement in neuronal morphology which was close to the normal level， with mitochondrial swelling alleviated and chromatin distribution more uniform. The medium- and high-dose groups significantly reduced neurological scores （P<0.01）， while the low-， medium-， and high-dose groups significantly reduced the number of central crossings （P<0.01） and infarct volume （P<0.01）， and decreased TNF-α， IL-1β， and IL-18 levels （P<0.05， P<0.01） compared with the model group. Furthermore， the medium- and high-dose groups significantly reduced TNF-α protein expression （P<0.05，P<0.01）， and the high-dose group significantly reduced IL-1β and IL-18 protein expression （P<0.01）. ConclusionThis study confirmed that CRPRR improves neurological function and alleviates brain tissue damage in MCAO/R rats. Its mechanism may be associated with the downregulation of inflammatory factors TNF-α， IL-1β， and IL-18， as well as the presence of nine active chemical constituents in cerebrospinal fluid， namely paeoniflorin， senkyunolide F， senkyunolide G， paeonimetabolin Ⅰ， paeoniflorin derivative， senkyunolide H， benzoylpaeoniflorin， senkyunolide A， and ligustilide， which are closely related to their brain-protective effects.