OBJECTIVE: To investigate the relationship between physical activity and genetic risk and their combined effects on the risk of developing chronic obstructive pulmonary disease. METHODS: This prospective cohort study included 318,085 biobank participants from the UK. Physical activity was assessed using the short form of the International Physical Activity Questionnaire. The participants were stratified into low-, intermediate-, and high-genetic-risk groups based on their polygenic risk scores. Multivariate Cox regression models and multiplicative interaction analyses were used. RESULTS: During a median follow-up period of 13 years, 9,209 participants were diagnosed with chronic obstructive pulmonary disease. For low genetic risk, compared to low physical activity, the hazard ratios ( HRs) for moderate and high physical activity were 0.853 (95% confidence interval [ CI]: 0.748-0.972) and 0.831 (95% CI: 0.727-0.950), respectively. For intermediate genetic risk, the HRs were 0.829 (95% CI: 0.758-0.905) and 0.835 (95% CI: 0.764-0.914), respectively. For participants with high genetic risk, the HRs were 0.809 (95% CI: 0.746-0.877) and 0.818 (95% CI: 0.754-0.888), respectively. A significant interaction was observed between genetic risk and physical activity. CONCLUSION Moderate or high levels of physical activity were associated with a lower risk of developing chronic obstructive pulmonary disease across all genetic risk groups, highlighting the need to tailor activity interventions for genetically susceptible individuals.
Humans ; Pulmonary Disease, Chronic Obstructive/epidemiology* ; Exercise ; Male ; Female ; Middle Aged ; Prospective Studies ; Aged ; Genetic Predisposition to Disease ; Risk Factors ; United Kingdom/epidemiology* ; Incidence ; Adult

ObjectiveTo analyze the reported cases of infectious diseases across different tiers of public medical and healthcare institutions in Minhang District, Shanghai from 2013 to 2023, to investigate the status and changes in reported infectious diseases in this district from a temporal, etiological, and demographic perspectives, so as to provide a scientific basis for the construction of a hierarchica early-warning surveillance system under the grading diagnosis and treatment model in medical institutions, as well as for optimizing sentinel surveillance at facilities of different levels. MethodsA retrospective analysis was performed using surveillance data from the China Disease Prevention and Control Information System in Minhang District from 2013 to 2023. Reported infectious diseases were categorized into three categories based on transmission routes: respiratory infectious diseases, intestinal infectious diseases, and sexually transmitted and blood borne infectious diseases. According to the implementation phase of the grading diagnosis and treatment policy, the research time was divided into four time periods: 2013‒2016, 2017‒2019, 2020‒2022, and 2023. The distribution and temporal changes of reported cases of infectious diseases were compared across community health service centers (CHCs), secondary hospitals, tertiary grade-A hospitals and tertiary grade-B hospitals. Chi-square test was used for univariate analysis of differences in the number of reported cases. Quantitative data with normal distribution were analyzed using parametric tests, otherwise, Kruskal⁃Wallis H tests were used. ResultsThe proportions of total reported cases of infectious diseases in medical institutions at all levels in Minhang District, Shanghai from 2013 to 2023 were 10.66% in CHCs, 9.10% in secondary hospitals, 64.95% in tertiary grade-B hospitals, and 15.29% in tertiary grade-A hospitals, with an overall decline and then rebound trend in the reported cases. After the implementation of grading diagnosis and treatment policy, the number of reported cases in CHCs and secondary hospitals showed a trend of first decreasing and then increasing, while that in tertiary grade-B hospitals showed a steady decreasing trend and that in tertiary grade-A hospitals showed an increasing trend. In terms of the research periods divided above, a total of 10 392 cases were reported in 2013‒2016 (70.34% from tertiary grade-B hospitals and 12.59% from CHCs), including 2 922 cases of respiratory infectious diseases, 1 241 cases of intestinal infectious diseases, and 6 229 cases of sexually transmitted and blood-borne infectious diseases. Between 2017 and 2019, a total of 6 967 cases were reported (73.49% from tertiary grade-B hospitals and 11.84% from tertiary grade-A hospitals), including 2 983 cases of respiratory infectious diseases, 279 cases of intestinal infectious diseases, and 3 705 cases of sexually transmitted and blood-borne infectious diseases. Between 2020 and 2022, a total of 4 599 cases were reported (69.92% from tertiary grade-B hospitals and 24.57% from tertiary grade-A hospitals), including 1 627 cases of respiratory infectious diseases, 123 cases of intestinal infectious diseases, and 2 849 cases of sexually transmitted and blood-borne infectious diseases. In 2023, a total of 4 648 cases were reported (35.20% from tertiary grade-B hospitals and 27.50% from tertiary grade-A hospitals), including 3 165 cases of respiratory infectious diseases, 69 cases of intestinal infectious diseases, and 1 414 cases of sexually transmitted and blood-borne infectious diseases. The proportion of reported cases from tertiary grade-B hospitals was the highest in all the four research periods, but exhibited an obvious decrease in 2023. The differences in the reported cases of infectious diseases with different transmission routes among medical institutions at all levels were statistically significant (χ²=3 225.628, P<0.05). The differences in the mean age of patients among medical institutions at all levels were statistically significant (H=1 325.927, P<0.05). ConclusionThere are significant differences in the number of reported cases of infectious disease in the medical institutions at different levels. Tertiary grade-B hospitals have historically dominated the number of reported cases, but its share has declined recently. Whereas, CHCs and tertiary grade-A hospitals have played an increasingly important role in the surveillance and early warning of respiratory and intestinal infectious diseases. Therefore, it is recommended to leverage the strengths of grading diagnosis and treatment to establish targeted sentinel sites and deploy specialized teams tailored to the epidemiological characteristics of specific disease categories.

Medical institutions, with their clinical practice foundation and abundant human use experience data, have become important carriers for the inheritance and innovation of traditional Chinese medicine(TCM) and the "cradles" of the preparation of new TCM. To effectively promote the transformation of new TCM originating from the TCM clinical practice in medical institutions and establish an effective evaluation index system for the transformation of new TCM conforming to the characteristics of TCM, consensus experts adopted the literature research, questionnaire survey, Delphi method, etc. By focusing on the policy and technical evaluation of new TCM originating from the TCM clinical practice in medical institutions, a comprehensive evaluation from the dimensions of drug safety, efficacy, feasibility, and characteristic advantages was conducted, thus forming a comprehensive evaluation system with four primary indicators and 37 secondary indicators. The expert consensus reached aims to encourage medical institutions at all levels to continuously improve the high-quality research and development and transformation of new TCM originating from the TCM clinical practice in medical institutions and targeted at clinical needs, so as to provide a decision-making basis for the preparation, selection, cultivation, and transformation of new TCM for medical institutions, improve the development efficiency of new TCM, and precisely respond to the public medication needs.
Medicine, Chinese Traditional/standards* ; Humans ; Consensus ; Drugs, Chinese Herbal/therapeutic use* ; Surveys and Questionnaires

The quality of traditional Chinese medicine(TCM) is a critical foundation for ensuring the stability of its efficacy, as well as the safety and effectiveness of its clinical use. The identification of critical quality attributes(CQAs) is one of the core components of TCM preparation quality control. This study focuses on Jianwei Xiaoshi Tablets and explores their CQAs related to property and flavor from the perspective of taste receptor proteins. Three taste receptor proteins, T1R2, T1R3, and TRPV1, were selected, and a biosensor based on high-electron-mobility transistor(HEMT) was constructed to detect the interactions between Jianwei Xiaoshi Tablets and taste receptor proteins. Simultaneously, liquid chromatography-mass spectrometry(LC-MS) technology was used to analyze the chemical composition of Jianwei Xiaoshi Tablets. In examining the interaction strength, the results indicated that the interaction between Jianwei Xiaoshi Tablets and TRPV1 protein was the strongest, followed by T1R3, with the interaction with T1R2 being relatively weaker. By combining biosensing technology with LC-MS, 16 chemical components were identified from Jianwei Xiaoshi Tablets, among which six were selected as CQAs for sweetness and seven for pungency. Further validation experiments demonstrated that CQAs such as hesperidin and hesperetin had strong interactions with their corresponding taste receptor proteins. Through the combined use of multiple technological approaches, this study successfully determined the property and flavor-related CQAs of Jianwei Xiaoshi Tablets. It provides novel ideas and approach for the identification of CQAs in TCM preparations and offers comprehensive theoretical support for TCM quality control, contributing to the improvement and development of TCM preparation quality control systems.
Drugs, Chinese Herbal/chemistry* ; Biosensing Techniques/methods* ; TRPV Cation Channels/chemistry* ; Tablets/chemistry* ; Receptors, G-Protein-Coupled/genetics* ; Quality Control ; Taste ; Humans ; Mass Spectrometry

OBJECTIVE: To explore the accuracy of human-computer interaction software in identifying and locating type C1 distal radius fractures. METHODS: Based on relevant inclusion and exclusion criteria, 14 cases of type C1 distal radius fractures between September 2023 and March 2024 were retrospectively analyzed, comprising 3 males and 11 females(aged from 27 to 82 years). The data were assigned randomized identifiers. A senior orthopedic physician reviewed the films and measured the ulnar deviation angle, radial height, palmar inclination angle, intra-articular step, and intra-articular gap for each case on the hospital's imaging system. Based on the reduction standard for distal radius fractures, cases were divided into reduction group and non-reduction group. Then, the data were sequentially imported into a human-computer interaction intelligent software, where a junior orthopedic physician analyzed the same radiological parameters, categorized cases, and measured fracture details. The categorization results from the software were consistent with manual classifications (6 reduction cases and 8 non-reduction cases). For non-reduction cases, the software performed further analyses, including bone segmentation and fracture recognition, generating 8 diagnostic reports containing fracture recognition information. For the 6 reduction cases, the senior and junior orthopedic physicians independently analyzed the data on the hospital's imaging system and the AI software, respectively. Bone segments requiring reduction were identified, verified by two senior physicians, and measured for displacement and rotation along the X (inward and outward), Z (front and back), and Y (up and down) axes. The AI software generated comprehensive diagnostic reports for these cases, which included all measurements and fracture recognition details. RESULTS: Both the manual and AI software methods consistently categorized the 14 cases into 6 reduction and 8 non-reduction groups, with identical data distributions. A paired sample t-test revealed no statistically significant differences (P>0.05) between the manual and software-based measurements for ulnar deviation angle, radial ulnar bone height, palmar inclination angle, intra-articular step, and joint space. In fracture recognition, the AI software correctly identified 10 C-type fractures and 4 B-type fractures. For the 6 reduction cases, a total of 24 bone fragments were analyzed across both methods. After verification, it was found that the bone fragments identified by the two methods were consistent. A paired sample t-tests revealed that the identified bone fragments and measured displacement and rotation angles along the X, Y, and Z axes were consistent between the two methods. No statistically significant differences(P>0.05) were found between manual and software measurements for these parameters. CONCLUSION Human-computer interaction software employing AI technology demonstrated comparable accuracy to manual measurement in identifying and locating type C1 distal radius fractures on CT imaging.
Humans ; Male ; Female ; Radius Fractures/surgery* ; Middle Aged ; Adult ; Aged ; Aged, 80 and over ; Tomography, X-Ray Computed/methods* ; Retrospective Studies ; Software ; Wrist Fractures

Benign prostatic hyperplasia (BPH) is one of the most common diseases in elderly men, the incidence of which gradually increases with age and leads to lower urinary tract symptoms (LUTS), which seriously affects the quality of life of patients. Chinese herbal medicines (CHMs) are widely used for the treatment of BPH in China and some other countries. To explore the molecular mechanisms of CHMs for BPH, we conducted a review based on peer-reviewed English-language publications in PubMed and Web of Science databases from inception to December 31, 2023. This article primarily reviewed 32 papers on the use of CHMs and its active compounds in the treatment of BPH, covering animal and cell experiments, and identified relevant mechanisms of action. The results suggest that the mechanisms of action of CHMs in treating BPH may involve the regulation of sex hormones, downregulation of cell growth factors, anti-inflammatory and antioxidative effects, inhibition of cell proliferation, and promotion of apoptosis. CHMs also exhibit α-blocker-like effects, with the potential to relax urethral smooth muscle and alleviate LUTS. Additionally, we also reviewed 4 clinical trials and meta-analyses of CHMs for the treatment of BPH patients, which provided initial evidence of the safety and effectiveness of CHMs treatment. CHMs treatment for BPH shows advantages as a multi-component, multi-target, and multi-pathway therapy, which can mitigate the severity of the disease, improve LUTS, and may become a reliable treatment option in the future.
Prostatic Hyperplasia/drug therapy* ; Humans ; Drugs, Chinese Herbal/pharmacology* ; Male ; Animals

Approximately 30%-40% of epilepsy patients do not respond well to adequate anti-seizure medications (ASMs), a condition known as pharmacoresistant epilepsy. The management of pharmacoresistant epilepsy remains an intractable issue in the clinic. Its early prediction is important for prevention and diagnosis. However, it still lacks effective predictors and approaches. Here, a classical model of pharmacoresistant temporal lobe epilepsy (TLE) was established to screen pharmacoresistant and pharmaco-responsive individuals by applying phenytoin to amygdaloid-kindled rats. Ictal electroencephalograms (EEGs) recorded before phenytoin treatment were analyzed. Based on ictal EEGs from pharmacoresistant and pharmaco-responsive rats, a convolutional neural network predictive model was constructed to predict pharmacoresistance, and achieved 78% prediction accuracy. We further found the ictal EEGs from pharmacoresistant rats have a lower gamma-band power, which was verified in seizure EEGs from pharmacoresistant TLE patients. Prospectively, therapies targeting the subiculum in those predicted as "pharmacoresistant" individual rats significantly reduced the subsequent occurrence of pharmacoresistance. These results demonstrate a new methodology to predict whether TLE individuals become resistant to ASMs in a classic pharmacoresistant TLE model. This may be of translational importance for the precise management of pharmacoresistant TLE.
Epilepsy, Temporal Lobe/diagnosis* ; Animals ; Drug Resistant Epilepsy/drug therapy* ; Electroencephalography/methods* ; Rats ; Anticonvulsants/pharmacology* ; Neural Networks, Computer ; Male ; Humans ; Phenytoin/pharmacology* ; Adult ; Disease Models, Animal ; Female ; Rats, Sprague-Dawley ; Young Adult ; Convolutional Neural Networks