OBJECTIVE To establish a whole-process quality management index system for traditional Chinese medicine （TCM） reserved in the department of medical institutions， providing a reference for standardized management. METHODS An initial indicator framework was determined by collecting and analyzing relevant laws， regulations， policy documents， group standards， and literature on TCM management. Two rounds of Delphi expert consultation involving 20 experts were conducted to refine and optimize the indicator system. The analytic hierarchy process was used to construct judgment matrices and convert the indicator weights into a percentage-based system； an assessment was conducted on 14 departments with reserved TCM among the affiliated units of the Quality Management and Control Center for Traditional Chinese Medicine in Hebei Province. RESULTS The response rate for both rounds of consultation was 100%， with an expert authority coefficient of 0.89. The final quality management system of TCM reserved in the department included four first-level indicators： management （composite weight： 0.366 3）， processing （composite weight： 0.119 7）， storage （composite weight： 0.291 7） and usage （composite weight： 0.222 3）， and twenty-four second-level indicators， such as establishing an organizational structure for hospital drug quality management and having dedicated regulations for backup drugs in clinical departments. Kendall’s coefficient of concordance confirmed consistency across all levels of indicators. Based on the application of the indicator system for evaluation， the average score for the standardized management of reserved TCM in the department of medical institutions increased from 67.01 points to 85.15 points over three months. CONCLUSIONS The constructed indicator system meets the standardized management requirements for reserved TCM， enabling closed-loop management across the entire process of management， processing， storage and usage. It provides a reference for medical institutions to enhance the precision and standardization of reserved TCM management.

Objective: To investigate the epidemiological characteristics and spatial-temporal clustering characteristics of scarlet fever in Jinhua City, Zhejiang Province from 2005 to 2023, so as to provide a reference for improving the prevention and control strategy of scarlet fever. Methods: The data of scarlet fever cases in Jinhua City from 2005 to 2023 were collected from the China Information System for Disease Control and Prevention, and descriptive epidemiological method was used to analyze the epidemiological characteristics of scarlet fever. The average annual percent change (AAPC) was calculated to analyze the trend of scarlet fever incidence from 2005 to 2023. The spatial-temporal clustering of scarlet fever was identified using spatial autocorrelation analysis and space-time scanning analysis. Results: A total of 1 494 scarlet fever cases were reported in Jinhua City from 2005 to 2023, and the average annual reported incidence rate was 1.41/100 000, with no significant change trend (AAPC=1.706%, P>0.05). There were two incidence peaks, from April to June and from November to January of the next year. There were 937 males and 557 females, with a male to female ratio of 1.68∶1. The age was mainly <10 years (1 391 cases, 93.11%), of which 3-<7 years was the high incidence age group (936 cases, 62.65%). There were 1 466 cases of preschool children, students, and scattered children, accounting for 98.13%. The average annual reported incidence of scarlet fever in Dongyang City, Pujiang County, and Yongkang City was 4.58/100 000, 3.04/100 000, and 1.99/100 000, respectively. The spatial autocorrelation analysis showed that there was a positive spatial correlation between the incidence of scarlet fever in Jinhua City from 2005 to 2023 (Moran's I=0.579, P<0.05), and the high-high clustering areas were mainly distributed in Dongyang City and Pujiang County. The spatial-temporal scanning analysis showed that there were 8 spatial-temporal clustering areas of scarlet fever in Jinhua City from 2005 to 2023. The class Ⅰ clustering area was 9 towns in Dongyang City, and the clustering period was from August 2013 to December 2022. There were 7 class Ⅱ clusters, covering some streets in Pujiang County, Dongyang City, Yongkang City, Yiwu City, and Pan'an County. Conclusions From 2005 to 2023, the incidence of scarlet fever in Jinhua City was relatively low, and children aged 3-<7 years had a high incidence, and there was a spatiotemporal clustering. The peak incidence was from April to June and from November to January of the next year. Dongyang City, Pujiang County, and Yongkang City had high incidence areas.

Objective: To analyze the epidemiological characteristics of leptospirosis in Jinhua City, Zhejiang Province, from 2007 to 2024, so as to provide a basis for improving the prevention and control strategies of leptospirosis. Methods: Data pertaining to leptospirosis cases in Jinhua City from 2007 to 2024 were collected through the Monitoring and Reporting Management System of the Chinese Disease Prevention and Control Information System. Descriptive epidemiological methods were used to analyze the distribution characteristics of leptospirosis in terms of time, region, population, interval from the onset of the disease to diagnosis and the outbreak of the epidemic. Results: A total of 81 cases of leptospirosis were reported in Jinhua City from 2007 to 2024, with an average annual reported incidence of 0.08/100 000. The peak incidence occurred from August to September, with 57 cases accounting for 70.37%. Leptospirosis cases were reported in 9 counties (cities, districts) in Jinhua City. Pan'an County reported the most cases, with 52 cases accounting for 64.20%. There were 54 male cases and 27 female cases, with a male-to-female ratio of 2∶1. The majority of cases were aged over 40 years, with 73 cases accounting for 90.12%. The average reported incidence of leptospirosis showed an upward trend with the increase of age (P<0.05), and the highest incidence of leptospirosis was at the 60-<80 age group (0.21/100 000). The majority of patients were farmers, with 77 cases accounting for 95.06%. The median interval from onset to diagnosis was 4.00 (interquartile range, 6.00) days. There were significant differences in the interval from onset to diagnosis among cases in Dongyang City compared with Pan'an County, Wuyi County, and Wucheng District, between Pan'an County and Jindong District, Wucheng District, and between Wuyi County and Wucheng District (all P<0.05). In 2007, one outbreak of leptospirosis was reported, which occurred in Jiuhe Township, Pan'an County, with 36 reported cases. Conclusions The reported incidence of leptospirosis in Jinhua City from 2007 to 2024 is generally low. The high-incidence period is from August to September, and Pan'an County is the high-incidence area. Males over 40 years and farmers are the key populations for prevention and control. It is recommended to strengthen epidemic surveillance and health education for high-risk populations.

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

ObjectiveTo analyze the epidemiological characteristics of patients with hepatitis C in Jinhua City, Zhejiang Province from 2005 to 2023, so as to provide a scientific basis for the prevention and control of hepatitis C. MethodsThe data on patients with hepatitis C, as well as whose current address is in Jinhua City, from 2005 to 2023 were collected from the infectious disease surveillance system of the China Disease Control and Prevention Information Management System. Descriptive epidemiological methods were used to analyze the temporal, spatial and demographic distribution characteristics of hepatitis C. ResultsA total of 2 326 cases of hepatitis C were reported in Jinhua from 2005 to 2023, including 2 death cases, with an average annual incidence rate of 2.19/100 000, showing a trend which rose first and then declined and then rose again. Hepatitis C was reported all the year round without significant seasonal pattern. In terms of the number of reported cases and the average annual incidence rate, Yiwu City ranked the first place. From 2005 to 2023, a total of 1 438 (61.82%) male cases and 888 (38.18%) female cases were reported, and the reported incidence rate was higher for males (2.62/100 000) than that for females (1.74/100 000), showing a statistically significant difference (χ²=92.937, P<0.001). Most cases aged between 30 to <50 years old (1 175, 50.52%), and the incidence rate of hepatitis C among the age group of 40‒<50, 50‒<60, 60‒<70 years old was showing an upward trend, with farmers (1 024, 44.02%) as the main occupation . ConclusionThe prevalence of hepatitis C in Jinhua City is generally at a low level, with an incidence rate of increasing and then decreasing, but rise up again after 2019. Therefore, epidemic surveillance and health education among the male, middle-aged and elderly people and farmers, as well as the key regions where the migrant workers flows in should be enhanced.

Objective:To observe the effect of combining robot-assisted gait training (RAGT) with task-oriented training (TOT) on the walking ability of children with dyskinetic cerebral palsy (DCP).Methods:Sixty DCP children were randomly divided into a conventional intervention group, an RAGT group, and a combined intervention group, each of 20. All of the children received conventional rehabilitation therapy, while the RAGT and combined intervention groups were additionally provided with RAGT, and RAGT combined with TOT, respectively. Before the experiment and after 12 and 24 weeks of treatment, the subjects′ walking ability was evaluated using the 10-metre walk test (10MWT), and the D energy zone (standing position) and the E energy zone (walking, running and jumping) of the Gross Motor Function Measurement-88 (GMFM-88) instrument.Results:After 12 and 24 weeks of treatment, the average 10MWT speed and D and E energy zone scores of all three groups had improved significantly. After 24 weeks the combined group′s averages on all three measures were significantly better than those of the other two groups.Conclusion:RAGT combined with TOT and conventional rehabilitation training significantly improves the walking ability of DCP children.

Outpatient humanistic care refered to providing a full process of caring medical services to outpatients. In order to standardize the human caring services for outpatients in medical institutions, promote the comprehensive service level of outpatient services, and improve the patient′s medical experience, Chinese Association for Life Care issued the group standard of Management Norms for Human caring of Outpatients in April 2023. This standard clarified the relevant terms and definitions of human caring for outpatients, specified the basic requirements for human caring, the humanistic quality and care responsibilities of outpatient staff, the outpatient care environment and facilities, the outpatient care process and measures, and quality management. It designed standardized and personalized full process care service norms, providing references for medical institutions at all levels to promote the development of human caring for outpatients.

Objective:To study the distribution of drug resistance genes and virulence genes in multidrug-resistant Salmonella typhimurium strains.Methods:A total of 96 strains of Salmonella typhimurium were collected，and drug sensitivity tests were performed to evaluate the drug resistance and multidrug-resistance of Salmonella typhimurium.Multidrug-resistant Salmonella typhimurium strains were selected to conducted whole genome sequencing，and the distribution of drug resistance genes and virulence genes in the strain were analyzed.Results:Salmonella typhimurium strains had the highest resistance rates to ampicillin and ampicillin/sulbactam，with 89.58% and 76.04%，respectively.Followed by trimethoprim/sulfamethoxazole，ceftriaxone，and aztreonam，with 47.92%，38.54% and 33.33%，respectively，and low resistance rates to ciprofloxacin and levofloxacin，with 8.33% and 4.17%，respectively.Ninety-six strains were all sensitive to carbapenem antibiotics and piperacillin/tazobactam.Fifty-seven strains（59.38%）of Salmonella typhimurium showed multidrug-resistance.Resistance genes were detected in all 57 multidrug-resistant Salmonella typhimurium strains,with higher carrier rates of 98.25%,77.19%,and 59.65% for aac(6')-Iaa,aadA22,and blaTEM-1B,respectively.The multidrug-resistant Salmonella typhimurium strains had the highest carrier rates for invA，sipA，sseL，and sopB.Conclusion:Multidrug-resistant Salmonella typhimurium strains have a high incidence and a high carrier rate for multiple drug resistance genes and virulence genes.The monitoring and prevention of Salmonella typhimurium should be strengthened in the clinic in order to reduce the spreading epidemic of multidrug-resistant strains.

Purpose/Significance To construct a Chinese medical knowledge Q&A corpus dataset as a standardized evaluation bench-mark for large language models(LLMs)in the medical domain,so as to improve the accuracy and efficiency of LLMs in handling Chinese medical questions.Method/Process Chinese medical paper knowledge,medical terminology explanations and supplementary questions are acquired from the Chinese medical licensing examination,and open-source Chinese medical Q&A datasets are encompassed in the developed Q&A datasets.Result/Conclusion The Chinese medical knowledge Q&A corpus datasets enrich the sources of existing datasets and promote the objective and comprehensive quantitative evaluation of large models in the medical field.In the near future,additional data such as electronic medical records and those from online health communities will be used to strengthen the support of artificial intelli-gence for the Healthy China strategy.