Objective:To analyze the epidemiological characteristics and infection sources of cholera in China from 2005 to 2024.Methods:A total of 2 066 cholera cases were included in the study, which were obtained from the China Disease Control and Prevention Information System (CDPCIS) of China CDC. The information on cholera clusters was downloaded from the National Public Health Emergency Event Surveillance System (PHEESS) of China CDC. A total of 128 cholera clusters were included and analyzed in this study. The epidemiological characteristics and infection sources of cholera were analyzed. The Jointpoint model was applied to analyze the incidence trend, and annual percentage change (APC) was also quantified.Results:From 2005 to 2024, a total of 2 066 cholera cases were reported, with an average of 103 cases reported annually. Specifically, the incidence showed a marked downward trend from 2004 to 2015 ( APC=-26.78%, P=0.006). During 2015-2024, the disease remained at low endemic levels, with an average of 18 reported cases annually ( APC=-2.68%, P=0.807). Cholera peak season was from May to October. A total of 24 provinces reported cholera cases, which were mainly distributed in Zhejiang, Fujian, Beijing, Jiangsu, Anhui, Guangdong, and Hainan provinces, accounting for 78.03% of the total cases. Pathogen surveillance indicated an alternating prevalence of Vibrio cholerae serogroups O1 and O139 among laboratory-confirmed cases between 2005 and 2024. There was a disparity in the dominant serogroup of Vibrio cholerae by region. The results from 128 cholera clusters indicated that cholera outbreaks frequently occurred in rural banquets (64.84%), followed by regular restaurants (13.28%). Among these, 63 clusters (49.22%) with identified infection sources indicated that foodborne transmission (95.24%) was the primary mode of cholera transmission, which mainly through seafood and aquatic products, such as soft-shelled turtles, shrimp and shellfish. The characteristics of cholera clusters caused by Vibrio cholerae serogroups O1 and O139 showed statistically significant differences in scale, attack rate, place of residence, setting, and infection source ( P<0.05). Conclusion:Cholera incidence has remained consistently low since 2015 in China, mainly in sporadic cases. Rural gatherings (e.g., wedding banquets) are the main settings for cholera clusters. The main infection sources are predominantly caused by cross-contamination due to improper processing practices of aquatic products, such as soft-shelled turtles.

Objective To investigate the clinical prognosis of untreated residual coronary artery dissection treated with drug coated balloon(DCB).Methods A retrospective analysis was conducted on the clinical and imaging data of patients with primary coronary artery lesions(2.5-4.0 mm)treated with DCB under angiography guidance at Xuzhou Cancer Hospital,Xuzhou New Health Geriatric Hospital,and Peixian Guotai Hospital from September 2017 to April 2023.According to the observation of coronary artery dissection through angiography,the patients were divided into a dissection group and a non dissection group.The main endpoint of this study was the major adverse cardiovascular event(MACE)during a 12-month follow-up.Results A total of 381 patients were enrolled in the three research centers,with 30 cases(30 lesions)in the dissection group and 351 cases(367 lesions)in the non dissection group.There was no significant difference between the two groups in terms of age,gender,hypertension,hyperlipidemia,diabetes,smoking,previous myocardial infarction,previous percutaneous coronary intervention,coronary artery bypass grafting and other baseline clinical characteristics(all P＞0.05).Except for the reference vessel diameter(P=0.049)and DCB pressure(P=0.032),there was no statistically significant difference in the characteristics of coronary angiography lesions between the two groups of patients(both P＞0.05).During a 12-month follow-up,there was no statistically significant difference(P＞0.05)in the incidence of MACE between the dissection group and the non dissection group after DCB treatment for primary coronary artery lesions in situ.Conclusions Untreated residual dissection after DCB treatment of de novo coronary lesions does not lead to an increase in clinical MACE.

To analyze the standard establishment approach and compilation rationale for metallic pharmaceutical packaging standard development in the 2025 edition of the Pharmacopeia of the People's Republic of China.This article systematically explained the background and process of establishing the guiding principles for metallic materials and containers used in pharmaceutical packaging in the Chinese Pharmacopoeia through basic information,relevant domestic and international standards,the establishment of key quality attributes of metallic pharmaceutical packaging materials,and the construction of metallic pharmaceutical packaging material standards.The newly established guidelines,the Pharmacopeia of the People's Republic of China 9625,prioritized product critical quality attributes(CQAs)and real-world applicability.This dual emphasis on rigidity and adaptability enhances drug safety,meets the regulatory requirements,and promotes the globalization and scientific advancement of China's pharmaceutical packaging industry.

To analyze the standard establishment approach and compilation rationale for metallic pharmaceutical packaging standard development in the 2025 edition of the Pharmacopeia of the People's Republic of China.This article systematically explained the background and process of establishing the guiding principles for metallic materials and containers used in pharmaceutical packaging in the Chinese Pharmacopoeia through basic information,relevant domestic and international standards,the establishment of key quality attributes of metallic pharmaceutical packaging materials,and the construction of metallic pharmaceutical packaging material standards.The newly established guidelines,the Pharmacopeia of the People's Republic of China 9625,prioritized product critical quality attributes(CQAs)and real-world applicability.This dual emphasis on rigidity and adaptability enhances drug safety,meets the regulatory requirements,and promotes the globalization and scientific advancement of China's pharmaceutical packaging industry.

Objective To investigate the clinical prognosis of untreated residual coronary artery dissection treated with drug coated balloon(DCB).Methods A retrospective analysis was conducted on the clinical and imaging data of patients with primary coronary artery lesions(2.5-4.0 mm)treated with DCB under angiography guidance at Xuzhou Cancer Hospital,Xuzhou New Health Geriatric Hospital,and Peixian Guotai Hospital from September 2017 to April 2023.According to the observation of coronary artery dissection through angiography,the patients were divided into a dissection group and a non dissection group.The main endpoint of this study was the major adverse cardiovascular event(MACE)during a 12-month follow-up.Results A total of 381 patients were enrolled in the three research centers,with 30 cases(30 lesions)in the dissection group and 351 cases(367 lesions)in the non dissection group.There was no significant difference between the two groups in terms of age,gender,hypertension,hyperlipidemia,diabetes,smoking,previous myocardial infarction,previous percutaneous coronary intervention,coronary artery bypass grafting and other baseline clinical characteristics(all P＞0.05).Except for the reference vessel diameter(P=0.049)and DCB pressure(P=0.032),there was no statistically significant difference in the characteristics of coronary angiography lesions between the two groups of patients(both P＞0.05).During a 12-month follow-up,there was no statistically significant difference(P＞0.05)in the incidence of MACE between the dissection group and the non dissection group after DCB treatment for primary coronary artery lesions in situ.Conclusions Untreated residual dissection after DCB treatment of de novo coronary lesions does not lead to an increase in clinical MACE.

Objective:To analyze the epidemiological characteristics and infection sources of cholera in China from 2005 to 2024.Methods:A total of 2 066 cholera cases were included in the study, which were obtained from the China Disease Control and Prevention Information System (CDPCIS) of China CDC. The information on cholera clusters was downloaded from the National Public Health Emergency Event Surveillance System (PHEESS) of China CDC. A total of 128 cholera clusters were included and analyzed in this study. The epidemiological characteristics and infection sources of cholera were analyzed. The Jointpoint model was applied to analyze the incidence trend, and annual percentage change (APC) was also quantified.Results:From 2005 to 2024, a total of 2 066 cholera cases were reported, with an average of 103 cases reported annually. Specifically, the incidence showed a marked downward trend from 2004 to 2015 ( APC=-26.78%, P=0.006). During 2015-2024, the disease remained at low endemic levels, with an average of 18 reported cases annually ( APC=-2.68%, P=0.807). Cholera peak season was from May to October. A total of 24 provinces reported cholera cases, which were mainly distributed in Zhejiang, Fujian, Beijing, Jiangsu, Anhui, Guangdong, and Hainan provinces, accounting for 78.03% of the total cases. Pathogen surveillance indicated an alternating prevalence of Vibrio cholerae serogroups O1 and O139 among laboratory-confirmed cases between 2005 and 2024. There was a disparity in the dominant serogroup of Vibrio cholerae by region. The results from 128 cholera clusters indicated that cholera outbreaks frequently occurred in rural banquets (64.84%), followed by regular restaurants (13.28%). Among these, 63 clusters (49.22%) with identified infection sources indicated that foodborne transmission (95.24%) was the primary mode of cholera transmission, which mainly through seafood and aquatic products, such as soft-shelled turtles, shrimp and shellfish. The characteristics of cholera clusters caused by Vibrio cholerae serogroups O1 and O139 showed statistically significant differences in scale, attack rate, place of residence, setting, and infection source ( P<0.05). Conclusion:Cholera incidence has remained consistently low since 2015 in China, mainly in sporadic cases. Rural gatherings (e.g., wedding banquets) are the main settings for cholera clusters. The main infection sources are predominantly caused by cross-contamination due to improper processing practices of aquatic products, such as soft-shelled turtles.

ObjectiveTo explore the current status and issues regarding the application of ancient books in clinical practice guidelines and expert consensus of traditional Chinese medicine （TCM） published in China， and to provide methodological recommendations for the incorporation of ancient books in the development of TCM guidelines. MethodsWe searched China National Knowledge Infrastructure （CNKI）， WanFang Data， VIP， SinoMed， PubMed， Embase， as well as six industry websites including China Association of Chinese Medicine， National Group Standards Information Platform， and Chinese Association of the Integration of Traditional and Western Medicine，etc. TCM clinical practice guidelines or expert consensus issued during January 1st， 2017， to November 26th， 2022 were searched. Clinical practice guidelines or expert consensus that explicitly referred to ancient books were included， and the content regarding the searching for ancient books， sources of access to ancient books， methods of evaluating the level of evidence， methods of evaluating the level of recommendation， and methods of evaluating the evidence for the ancient books were analysed. ResultsA total of 1,215 TCM clinical practice guidelines or expert consensus were retrieved， with 442 articles explicitly mentioning the application of ancient books， including 300 （67.87%） clinical practice guidelines and 142 （32.13%） expert consensus. Sixty of the 442 publications explicitly reported that ancient books searching had been conducted （13.57%）； among these 60 publications 27 （45.00%） explicitly reported ancient books searching strategies， and the most frequent method was manual searching with a total of 24 articles （40.00%）. The most popular search source was Chinese Medical Dictionary， a TCM classics database， with a total of 18 articles. 197 articles （44.57%） explicitly reported the evaluation criteria for the level of evidence， of which 141 articles （71.57%） involved the evaluation criteria for the ancient books； 413 articles （93.44%） mentioned ancient books in the recommendations， and only the source of formula name was mentioned in 409 （99.03%） of the publications. ConclusionThe current application of ancient books in TCM clinical practice guidelines and expert consensus is limited， with issues of non-standard searching and evaluation methods. Standar-dization and uniformity are needed in evidence grading and recommendation standards. Future research should clarify the scope and methods of applying ancient book， emphasize their integration with modern research evidence， and enhance their value and quality in the development of TCM clinical practice guidelines.

Objective To construct machine learning models that can be used to predict AUC fold change(FC)using a database of existing pharmacokinetic(PK)and drug-drug interaction(DDI)information,which can be used to explore the possibility of predicting existing drug interactions and to provide certain rational recommendations for clinical drug use.Methods PK data of DDIs and AUC fold change data were extracted from FDA-approved drug labels.Peptide and pharmacodynamic(PD)information related to drug interactions were retrieved through DrugBank,and PPDT identification of relevant peptide IDs was performed using Protein Resource(UniProt),and a matrix normalization code was used to generate multidimensional vector data that were easy to analysis.The effect of PPDT on the AUC,and the resulting multiplicity change was used as the dependent variable for machine learning model construction.The model with the smallest root mean square error(RMES)value was used for model construction to train a bagged decision tree(Bagged)prediction model.The models were tested using the trained models for some of the drug tests.The models were evaluated by reviewing the available literature findings on detection of drug interaction pairs and analyzing and comparing the predicted values.Results A total of 16 pairs of model drug pairs were tested for the effects of 16 drugs on tacrolimus,and it was found that the accuracy of the prediction of the presence or absence of drug interactions was 81.25％;the prediction results were classified according to the FDA standard classification of the strong and weak for the strength of drug interactions,and the results showed that the prediction of the strength of drug interactions,with a large deviation from the larger prediction was less.Conclusion The evaluation of the model to predict the presence or absence of drug interactions was general;however,after classifying the strengths and weaknesses of drug interactions,the prediction of drug interactions was better,and the prediction results indicated that the model prediction performance has a certain reference value for potential DDI assessment before clinical trials.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.