Objective To construct large medical model named by "Huaxi HongYi"and explore its application effectiveness in assisting medical record generation. Methods By the way of a full-chain medical large model construction paradigm of "data annotation - model training - scenario incubation", through strategies such as multimodal data fusion, domain adaptation training, and localization of hardware adaptation, "Huaxi HongYi" with 72 billion parameters was constructed. Combined with technologies such as speech recognition, knowledge graphs, and reinforcement learning, an application system for assisting in the generation of medical records was developed. Results Taking the assisted generation of discharge records as an example, in the pilot department, after using the application system, the average completion times of writing a medical records shortened (21 min vs. 5 min) with efficiency increased by 3.2 time, the accuracy rate of the model output reached 92.4%. Conclusion It is feasible for medical institutions to build independently controllable medical large models and incubate various applications based on these models, providing a reference pathway for artificial intelligence development in similar institutions.

[This corrects the article DOI: 10.1016/j.jpha.2023.08.006.].

OBJECTIVE: Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health. Analysis of these mixture exposures presents several key challenges for environmental epidemiology and risk assessment, including high dimensionality, correlated exposure, and subtle individual effects. METHODS: We proposed a novel statistical approach, the generalized functional linear model (GFLM), to analyze the health effects of exposure mixtures. GFLM treats the effect of mixture exposures as a smooth function by reordering exposures based on specific mechanisms and capturing internal correlations to provide a meaningful estimation and interpretation. The robustness and efficiency was evaluated under various scenarios through extensive simulation studies. RESULTS: We applied the GFLM to two datasets from the National Health and Nutrition Examination Survey (NHANES). In the first application, we examined the effects of 37 nutrients on BMI (2011-2016 cycles). The GFLM identified a significant mixture effect, with fiber and fat emerging as the nutrients with the greatest negative and positive effects on BMI, respectively. For the second application, we investigated the association between four pre- and perfluoroalkyl substances (PFAS) and gout risk (2007-2018 cycles). Unlike traditional methods, the GFLM indicated no significant association, demonstrating its robustness to multicollinearity. CONCLUSION GFLM framework is a powerful tool for mixture exposure analysis, offering improved handling of correlated exposures and interpretable results. It demonstrates robust performance across various scenarios and real-world applications, advancing our understanding of complex environmental exposures and their health impacts on environmental epidemiology and toxicology.
Humans ; Environmental Exposure/analysis* ; Linear Models ; Nutrition Surveys ; Environmental Pollutants ; Body Mass Index

ObjectiveTo elucidate the pharmacodynamic substances responsible for the anti-inflammatory and analgesic effects of Cyperi Rhizoma by structure-activity omics. MethodOn the basis of the previous in vitro efficacy study by our research group， this study explored the in vivo efficacy of the flavonoids in Cyperi Rhizoma. The flavonoids in Cyperi Rhizoma and their targets were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform （TCMSP）， PharmMapper， Swiss TargetPrediction， and available articles. The targets of the anti-inflammatory and analgesic effects were collected from DisGeNET and Online Mendelian Inheritance in Man （OMIM）. The common targets shared by flavonoids and the effects were selected as the direct targets of flavonoids endowing Cyperi Rhizoma with anti-inflammatory and analgesic effects， and protein-protein interaction （PPI） network of the core targets was constructed. The method of structure-activity omics was employed to correlate the structure and efficacy of one or more classes of chemical components in Cyperi Rhizoma with the targets as a bridge. The components were classified according to structure. Molecular docking of components to core targets was carried out via SYBYL-X 2.1.1， PyMol， and Discovery Studio 4.5 visualizer. Two targets with the highest binding affinity were selected to explore the relationship between compound structures and targets. ResultThe flavonoids in Cyperi Rhizoma exerted anti-inflammatory and analgesic effects on the mouse model of pain induced by formaldehyde. Eighteen components and 115 direct targets were screened out， and the core targets with high activities were protein kinase B1 （Akt1）， interleukin-1β （IL-1β）， cellular tumor antigen p53 （TP53）， prostaglandin-endoperoxide synthase 2 （PTGS2）， and matrix metalloproteinase-9 （MMP-9）. According to the structures， the flavonoids in Cyperi Rhizoma were classified into bioflavonoids， flavonols， flavones， and flavanes. The molecular docking results showed that flavonoids of Cyperi Rhizoma had the highest binding affinity to TP53 and PTGS2. The results of structure-activity omics showed that bioflavonoids represented the best binding structure to the targets， while their polyhydroxyl etherification resulted in a significant decrease in the binding affinity to PTGS2. Glycosides had higher binding affinity to PTGS2. The introduction of the long-chain hydrocarbon group to the A ring of flavonols facilitated the binding to TP53， while the change of B ring substituents was not the main factor affecting the binding affinity. The 3，4-dihydroxyl flavane outperformed 3-hydroxyl flavane in the binding to TP53， while the two compounds showed similar binding affinity to PTGS2. ConclusionThe method of structure-activity omics was used to analyze the material basis for the anti-inflammatory and analgesic effects of flavonoids in Cyperi Rhizoma. Structure-activity omics provides new ideas for revealing the pharmacodynamic substances of traditional Chinese medicine.

ObjectiveTo elucidate the active compounds for the anti-inflammatory and analgesic effects of Paeoniae Radix Alba from structure-activity omics. MethodOn the basis of the previous in vitro efficacy study by our research group， a mouse model of foot swelling was induced by methyl aldehyde and used to study the anti-inflammatory and analgesic effects of total glycosides of Paeoniae Radix Alba in vivo. The core targets of the active compounds for the anti-inflammatory and analgesic effects of Paeoniae Radix Alba were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform （TCMSP）， Online Mendelian Inheritance in Man （OMIM）， and Search Tool for Recurring Instances of Neighbouring Genes （STRING）. Molecular docking was conducted for the total glucosides of Paeoniae Radix Alba with the core targets， and the key core targets with high binding affinity were screened out according to the comprehensive score of each target and active structure. The structure-activity relationship was analyzed with targets as a bridge through the combination of compound structures and pharmacological effects. ResultThe total glucosides of Paeoniae Radix Alba had good anti-inflammatory and analgesic effects in vivo. The core targets of 23 active components of Paeoniae Radix Alba were epidermal growth factor receptor （EGFR）， signal transducer and activator of transcription 3 （STAT3）， vascular endothelial growth factor A （VEGFA）， cellular tumor antigen p53 （TP53）， and proto-oncogene transcription factor （JUN）. According to the structure of the parent nucleus， there were 16 pinane monoterpene glycosides， 4 pinene monoterpene glycosides， 2 monoterpene lactone glycosides， and 1 monoterpene ketone. The key core targets screened out by molecular docking were EGFR and STAT3. The structure-activity analysis of the active compound structures and the key core targets showed that the introduction of ketone group and benzene ring group on the parent nucleus affected the binding activity. ConclusionThis study analyzed the material basis for the anti-inflammatory and analgesic effects of total glycosides of Paeoniae Radix Alba from structure-activity omics， providing new ideas and methods for revealing the pharmacodynamic substances in traditional Chinese medicine.

The breakage pattern of unit particles during the production of oral solid dosage forms (OSD) is closely related to the quality of intermediate or final products. To accurately characterize the particles and study the evolution law of particle breakage, the Bonding model of the discrete element method (DEM) was used to investigate the breakage patterns of model parameters, particle shape and process conditions (loading mode and loading rate) on the dynamic breakage, force-time curve, breakage rate, maximum breakage size ratio and fracture strength of particles. The results showed that the particle breakage force was positively correlated with normal strength and bonded disk scale, negatively correlated with normal stiffness per unit area and tangential stiffness per unit area, and weakly correlated with tangential strength. The particle breakage rate was negatively correlated with the aspect ratio of the particles, and the maximum breakage size ratio was positively correlated with the aspect ratio of the particles; among the three loading modes, the breakage rate of compression breakage model was the largest, the breakage rate of shear breakage model was the second largest, and the breakage rate of wear breakage model was the smallest; the maximum breakage size ratio was positively correlated with the loading rate, the loading mode and the loading rate had no mutual influence on particle breakage rate, but had mutual influence on the maximum breakage size ratio. The research results will provide a theoretical basis for the shift of OSD from batch manufacturing to advanced manufacturing.

Objective:To explore the impact of sleep duration, physical exercise, and their interactions on the risk of dyslipidemia in older adults aged ≥80 (the oldest old) in China.Methods:The study subjects were the oldest old from four rounds of Healthy Aging and Biomarkers Cohort Study (2008-2009, 2011-2012, 2014 and 2017-2018). The information about their demographic characteristics, lifestyles, physical examination results and others were collected, and fasting venous blood samples were collected from them for blood lipid testing. Competing risk model was used to analyze the causal associations of sleep duration and physical exercise with the risk for dyslipidemia. Restricted cubic spline (RCS) function was used to explore the dose-response relationship between sleep duration and the risk for dyslipidemia. Additive and multiplicative interaction model were used to explore the interaction of sleep duration and physical exercise on the risk for dyslipidemia.Results:The average age of 1 809 subjects was (93.1±7.7) years, 65.1% of them were women. The average sleep duration of the subjects was (8.0±2.5) hours/day, 28.1% of them had sleep duration for less than 7 hours/day, and 27.2% had sleep for duration more than 9 hours/day at baseline survey. During the 9-year cumulative follow-up of 6 150.6 person years (follow-up of average 3.4 years for one person), there were 304 new cases of dyslipidemia, with an incidence density of 4 942.6/100 000 person years. The results of competitive risk model analysis showed that compared with those who slept for 7-9 hours/day, the risk for dyslipidemia in oldest old with sleep duration >9 hours/day increased by 22% ( HR=1.22, 95% CI: 1.07-1.39). Compared with the oldest old having no physical exercise, the risk for dyslipidemia in the oldest old having physical exercise decreased by 33% ( HR=0.67, 95% CI: 0.57-0.78). The RCS function showed a linear positive dose-response relationship between sleep duration and the risk for hyperlipidemia. The interaction analysis showed that physical exercise and sleep duration had an antagonistic effect on the risk for hyperlipidemia. Conclusion:Physical exercise could reduce the adverse effects of prolonged sleep on blood lipids in the oldest old.

Objective:To investigate the association of urinary cadmium level with body mass index (BMI) and body circumferences among the older adults over 65 years old in 9 longevity areas of China.Methods:Subjects were older adults over 65 years old from the Healthy Aging and Biomarkers Cohort Study (HABCS) between 2017 and 2018 conducted in 9 longevity areas in China. A total of 1 968 older adults were included in this study. Information including socio-demographic characteristics, lifestyles, diet intake, and health status was collected by using questionnaires and physical examinations. Urine samples were collected to detect urinary cadmium and creatinine levels. Body circumferences included waist circumference, hip circumference and calf circumference. Subjects were divided into three groups (low:<0.77 μg/g·creatinine, middle:0.77-1.69 μg/g·creatinine, high:≥1.69 μg/g·creatinine) by tertiles of creatinine-adjusted urinary cadmium concentration. Multiple linear regression models were used to analyze the association of creatinine-adjusted urinary cadmium level with BMI and body circumferences. The dose-response relationship of creatinine-adjusted urinary cadmium concentration with BMI and body circumferences was analyzed by using restrictive cubic splines fitting multiple linear regression model.Results:The mean age of subjects was (83.34±11.14) years old. The median (Q1, Q3) concentration of creatinine-adjusted urinary cadmium was 1.13 (0.63, 2.09) μg/g·creatinine, and the BMI was (22.70±3.82) kg/m 2. The mean values of waist circumference, hip circumference, and calf circumference were (85.42±10.68) cm, (92.67±8.90) cm, and (31.08±4.76) cm, respectively. After controlling confounding factors, the results of the multiple linear regression model showed that for each increment of 1 μg/g·creatinine in creatinine-adjusted urinary cadmium, the change of BMI, waist circumference, hip circumference, and calf circumference in the high-level group was -0.28 (-0.37, -0.19) kg/m 2, -0.74 (-0.96, -0.52) cm, -0.78 (-0.96, -0.61) cm, and -0.20 (-0.30, -0.11) cm, respectively. The restrictive cubic splines curve showed a negative nonlinear association of creatinine-adjusted urinary cadmium with BMI ( Pnonlinear<0.001) and negative linear associations of creatinine-adjusted urinary cadmium with waist circumference ( Plinear<0.001), hip circumference ( Plinear<0.001), and calf circumference ( Plinear<0.001). Conclusion:Urinary cadmium level is significantly associated with decreased BMI, waist circumference, hip circumference and calf circumference among older adults over 65 years old in 9 longevity areas of China.

The complex chemical composition and limited research ideas of traditional Chinese medicine （TCM） have led to the unclear material basis and mechanism of the medicinal effects， which is a common problem hindering the modernization of TCM in China. The introduction of computer virtual technology has provided a new perspective for TCM research. In this study， we established the research method of structure-activity omics to study the relationships between the structures and effects of different compounds in TCM based on the chemical structures of TCM components and to analyze and predict the material basis and multitarget synergistic mechanism of TCM. Furthermore， a structure-activity omics study was carried out with the anti-inflammatory and analgesic effects of Qizhi Weitong granules as an example. This study provides support for screening the pharmacodynamic components and analyzing the active ingredients of TCM and gives insights into the research on the material basis and mechanism of compound efficacy and the development of lead compounds of TCM， thus promoting the modern research and the innovative development of TCM.