To summarize the applications of data-intelligence technology in diagnosing lysosomal storage disease(LSD), analyze their opportunities and challenges in clinical practice as well as their development trends, and provide insights and recommendations for advancing digitally driven auxiliary diagnostic technologies.

Objective To develop an integrated intelligent management information platform for venous thromboembolism(VTE)prevention and treatment,enabling comprehensive data statistics,in-depth analysis,and intelligent retrieval across all staff,processes,timeframes,and domains.Methods Utilizing artificial intelligence technologies such as machine learning,natural language processing,and knowledge graphs,the platform was designed by integrating national VTE guidelines and author-itative medical literature with the hospital's clinical needs.Customized reasoning algorithms and backend open clinical rule set-tings were implemented to deploy an AI-assisted diagnosis and treatment system specifically for VTE.Results After implemen-ting the platform,the VTE assessment rate for inpatients(excluding pediatrics)reached 99.8％,and lifelong identification of high-risk patient records was achieved.□ Conclusion This intelligent management platform has established an effective AI-as-sisted mechanism for VTE prevention,diagnosis,and management in our hospital,significantly enhancing VTE prevention and treatment capabilities.

This study established the HPLC fingerprints, characteristic chromatograms, and a multi-component content determination method for Bidens bipinnata and B. biternata. The chemical pattern recognition analysis was then employed to clarify the characteristic indexes of quality differences between the two original plants of Bidentis Herba, providing a reference for establishing the quality standards of Bidentis Herba. HPLC was launched on an Agilent Poroshell 120 EC-C_(18) chromatographic column(4.6 mm×250 mm, 4 μm) by gradient elution with a mobile phase of 0.1% aqueous phosphoric acid-acetonitrile at a flow rate of 0.7 mL·min~(-1), detection wavelength of 270 nm, column temperature of 25 ℃, and an injection volume of 5 μL. The similarity between the fingerprints of 18 batches of Bidentis Herba samples and the common pattern(R) ranged from 0.572 to 0.933. A total of 23 chromatographic peaks were calibrated. Through comparison with the reference substances, six components(neochlorogenic acid, chlorogenic acid, isochlorogenic acid A, isochlorogenic acid B, rutin, and hyperoside) were identified and subjected to quantitative analysis. The characteristic fingerprints of B. bipinnata and B. biternata were calibrated with 20 and 17 characteristic peaks, respectively. Among them, peaks 8, 9, 22, and 23 were the characteristic peaks of B. bipinnata, and peak 7 was the characteristic peak of B. biternata, which can be used to distinguish the two original plants of Bidentis Herba. The relative standard deviation of the content of the above-mentioned six components ranged from 36% to 123%. The cluster analysis, principal component analysis, and orthogonal partial least squares-discriminant analysis(OPLS-DA) classified the 18 batches of Bidentis Herba samples into two categories. Additionally, through the analysis of variable importance in projection(VIP) under OPLS-DA, three characteristic indexes, rutin, isochlorogenic acid A, and isochlorogenic acid B, were identified. The analytical method established in this study can comprehensively evaluate the consistency of Bidentis Herba samples derived from different original plants, specifically identify the differential components between them, and effectively distinguish the two original plants of Bidentis Herba, providing a basis for the differentiation between different original plants and the quality control of Bidentis Herba.
Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Quality Control ; Bidens/chemistry*

The therapeutic effects of Yueju Pills on depression and cardiovascular diseases have been widely recognized. Previous studies have shown that the drug can significantly improve depressive-like behaviors induced by chronic unpredictable mild stress(CUMS) combined with atherosclerosis(AS). Given the complex pathogenesis of psychocardiac diseases, this study integrated metabolomics and network pharmacology to systematically elucidate the mechanism of Yueju Pills in alleviating depressive symptoms in psychocardiac diseases. The results demonstrate that, after Yueju Pill intervention, the levels of 9 abnormal metabolites in the hippocampus restore to normal ranges, primarily involving key pathways or signaling pathways, including the cyclic adenosine monophosphate(cAMP), mammalian target of rapamycin(mTOR), glycine/serine/threonine metabolism, and aminoacyl-tRNA biosynthesis. In a high-fat diet-induced CUMS ApoE~(-/-) mouse model, Yueju Pills significantly increases adenosine monophosphate(AMP) levels and decreases L-alanine and D-glyceric acid levels in the hippocampus. In conclusion, Yueju Pills exert antidepressant effects by regulating multiple metabolic axes, including glycine/serine/threonine metabolism and the cAMP, mTOR signaling pathways. Network pharmacology predictions reveal that the treatment of CUMS combined with AS by its core active components may be realized through modulating pathways concerning neuroinflammation and synaptic plasticity, including serine/threonine-protein kinase 1(AKT1), mitogen-activated protein kinase 1(MAPK1), and prostaglandin-endoperoxide synthase 2(PTGS2). This study provides a theoretical reference for the clinical application of Yueju Pills in alleviating the depressive symptoms of psychocardiac diseases.
Animals ; Network Pharmacology ; Mice ; Drugs, Chinese Herbal/administration & dosage* ; Metabolomics ; Male ; Depression/genetics* ; Humans ; Hippocampus/drug effects* ; Mice, Inbred C57BL ; Signal Transduction/drug effects*

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

OBJECTIVE: To investigate the distribution of traditional Chinese medicine (TCM) syndrome types of and influencing factors on ED with hyperuricemia. METHODS: Based on the clinical data on 271 cases of ED with hyperuricemia admitted to our Department of Andrology, we studied the characteristics of syndrome elements, summarized the TCM syndrome types, and investigated the influencing factors on the distribution of the syndrome types by factor analysis and cluster analysis. RESULTS: By factor analysis of the data collected on TCM symptoms, 12 common factors and 15 syndrome type elements were identified, including disease type syndrome elements dampness, phlegm, heat, qi stagnation, blood stasis, qi deficiency, blood deficiency, yin deficiency, yang deficiency and essence deficiency, and disease-location syndrome elements kidney, liver, spleen, limbs and joints. Common factor cluster analysis revealed the main TCM syndrome types kidney deficiency damp-heat syndrome, spleen and kidney deficiency syndrome, liver depression and kidney deficiency syndrome, kidney deficiency and blood stasis syndrome, and the main influencing factors on the distribution of syndrome types including uric acid, systolic blood pressure, urea, obesity and so on. CONCLUSION The main TCM syndrome types of ED with hyperuricemia include kidney deficiency damp-heat syndrome, spleen and kidney deficiency syndrome, liver depression and kidney deficiency syndrome, kidney deficiency and blood stasis syndrome, and the related influencing factors can be used as an objective basis for the differentiation of TCM syndromes.
Humans ; Medicine, Chinese Traditional ; Hyperuricemia/complications* ; Male ; Cluster Analysis

Objective To develop an integrated intelligent management information platform for venous thromboembolism(VTE)prevention and treatment,enabling comprehensive data statistics,in-depth analysis,and intelligent retrieval across all staff,processes,timeframes,and domains.Methods Utilizing artificial intelligence technologies such as machine learning,natural language processing,and knowledge graphs,the platform was designed by integrating national VTE guidelines and author-itative medical literature with the hospital's clinical needs.Customized reasoning algorithms and backend open clinical rule set-tings were implemented to deploy an AI-assisted diagnosis and treatment system specifically for VTE.Results After implemen-ting the platform,the VTE assessment rate for inpatients(excluding pediatrics)reached 99.8％,and lifelong identification of high-risk patient records was achieved.□ Conclusion This intelligent management platform has established an effective AI-as-sisted mechanism for VTE prevention,diagnosis,and management in our hospital,significantly enhancing VTE prevention and treatment capabilities.

Objective:To evaluate the training efficacy of the autonomic nervous system stability assessing and enhancing capsule (hereinafter referred to as the EC), and to study the difference in physiological indicators for autonomic nervous system stability training between the EC and a non-capsule environment.Methods:A total of 1 478 male military pilots under autonomic nervous system stability training between February 2022 and February 2024 were selected before they completed training sessions in both the EC and a non-capsule environment. The pre-training time-domain and frequency-domain indices of heart rate variability (HRV) and the 0.1 Hz index were compared with the post-training ones, and across difficulty levels (low, moderate, and high). The difference that the EC made in relaxation training was analyzed.Results:①Time-domain indices of HRV were of statistical significance in the main effects of training difficulty, those of training environments, and their interactions ( F=4.40-160.80, all P<0.05 or 0.01). Simple effect analysis revealed that in the same phase of training the standard deviation of all NN intervals (SDNN) at the low level of difficulty in the EC was lower than in the non-capsule environment. However, all time-domain indices after training were higher in the EC than in the non-capsule environment. The differences were statistically significant (all P<0.05 or 0.01).②For frequency-domain HRV indices, significant differences were observed in both the main effect of training difficulty and the interactions ( F=4.40-1 524.33, all P<0.01). Very low frequency power (VLF), high frequency (HF), the ratio of low frequency to high frequency (LF/HF), normalized low frequency (LFnorm), and normalized high frequency (HFnorm) were significantly different in the main effect of training environments ( F=4.24, 12.00, 6.91, 23.39, 23.39, P=0.040, <0.001, =0.009, <0.001, <0.001). Simple effect analysis revealed that at the same level of training difficulty, the EC delivered significantly lower values of LF and LFnorm but higher values of HF and HFnorm than the non-capsule environment before training (all P<0.05). VLF across levels of training difficulty and LF/HF at the high level of difficulty level were significantly lower in the EC than in the non-capsule environment. After training, total power, VLF, LF, HF, and HFnorm were significantly higher in the EC than in the non-capsule environment, but LF/HF and LFnorm were significantly lower (all P<0.05). ③For the 0.1 Hz index, significant differences were observed in both the main effect of training difficulty and the interactions ( F=2 147.75, 6.63, both P<0.001). Subsequent simple effect analysis revealed that at the same level of training difficulty, 0.1 Hz indices of pilots in the EC were lower than in the non-capsule environment before and after training (all P<0.01). Conclusions:During the autonomic nervous system stability training, the EC can effectively and quickly regulate and alleviate pilots′ fatigue and stress. Furthermore, it provides sustained autonomic nervous system training, thereby stabilizing pilots′ autonomic nervous system.

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*