Occupational carpal tunnel syndrome (OCTS) has been included in the official list of occupational diseases in China. Imaging techniques have been widely applied in the diagnosis of carpal tunnel syndrome (CTS), including OCTS, owing to their advantages of visualization, non-invasiveness, and high patient compliance. Computed tomography (CT) can be used to visualize bony structures of the wrist, however, it has limited resolution for nerve compression caused by non-osseous factors. Magnetic resonance imaging (MRI) provides high-resolution visualization of the microstructure of muscles, nerves, and surrounding tissues, particularly diffusion-weighted magnetic resonance neuroimaging for assessment of the median nerve. However, MRI is costly and time-consuming. Therefore, both CT and MRI are limited in CTS diagnosis. Ultrasonography has its advantages, such as real-time dynamic assessment, low cost, non-invasiveness, and non-ionizing radiation effect. High-frequency ultrasound has shown correlations with nerve conduction and electromyography findings in the progression and diagnosis of CTS. Real-time shear wave elastography enables quantitative assessment of tissue elasticity and stiffness, while superb microvascular imaging allows quantitative evaluation of intraneural microvascular flow, compensating for the subjectivity of conventional high-frequency ultrasound. According to GBZ 336-2025 Diagnostic Standard for Occupational Carpal Tunnel Syndrome, high-frequency ultrasound examination of the wrist has been listed as an important diagnostic basis for OCTS. Future studies should explore the combined use of multimodal ultrasound techniques (high-frequency ultrasound, SMI, and SWE) to construct a comprehensive diagnostic model for OCTS that integrates multi-dimensional imaging features with neurophysiological parameters and occupational exposure history, thereby enhancing diagnostic accuracy and objectivity.

Objective To investigate the relationship between sleep disorders and coronary heart disease through big data combined with Mendelian randomization analysis.Methods Data from 2005 to 2018 National Health and Nutrition Examination Survey in the United States were utilized.Logistic regression analysis was employed to evaluate the association between sleep disorders and coronary heart disease,while analyzing relevant influencing factors.A two-sample Mendelian randomization approach was implemented using Genome-Wide Association Studies to establish causal relationships.Results Logistic regression analysis demonstrated a significant association between sleep disorders and coronary heart disease(P＜0.001),with the neutrophil-to-lymphocyte ratio serving as a mediating factor in this relationship(P＜0.001).Mendelian randomization analysis revealed a positive correlation between sleep disorders and coronary heart disease(OR=1.030,95％CI:1.01-1.04).Conclusion Sleep disorders can increase the risk of coronary heart disease by activating inflammatory factors.

Objective To construct a risk prediction model for post-stroke dysphagia(PSD)based on clinical and laboratory indicators of elderly stroke patients with explainable machine learning.Methods A retrospective analysis was conducted on 3994 stroke patients hospitalized in Depart-ment of Neurology of First Medical Center of Chinese PLA General Hospital from October 2010 to December 2021.Among them,the 1390 cases admitted during January 2019 and December 2021 were assigned into an external validation set,and the 2604 cases admitted during October 2010 to January 2019 were into a training group.Those from the training group were further divided into a training set(1823 cases)and an internal validation set(781 cases)in a 7∶3 ratio,and also grouped into a PSD subgroup(773 cases)and a non-PSD group(1831 cases).With occurrence of swallowing difficulties as an endpoint,risk prediction models were constructed using random for-est(RF),eXtreme Gradient Boosting(XGBoost),Support Vector Machine(SVM),and logistic regression.ROC curve analysis was employed to evaluate the performance of our models.After the optimal model was selected,SHAP was employed to interpret feature contributions.Results There were significant differences in muscle strength,right/left-sided stroke,and area of brain in-jury between the PSD and the non-PSD groups(P＜0.01).The PSD group had obviously larger proportions of hypertension,diabetes,and drinking history,increased neutrophil counts,and de-creased levels of potassium and albumin when compared with the non-PSD group(P＜0.05,P＜0.01).Multivariate logistic regression analysis showed that age,drinking history,diabetes,hyper-tension,muscle strength grade,area of brain injury,hemispheric stroke,neutrophil count,and al-bumin and potassium levels were risk factors for PSD(P＜0.05,P＜0.01).The external validation results showed that the area under curve value of the RF model,XGBoost model,SVM model,and our logistic model was 0.883,0.902,0.877,and 0.868,respectively.The distribution of SHAP value showed that drinking history,hypertension and diabetes were positively correlated with PSD risk;Muscle strength was negatively correlated with the risk;Age growth was positively correlated with the risk;Subtentorial lesions showed stronger predictive efficacy than supratentorial lesions and entire lesions;The bilateral and right-sided stroke had higher risk for PSD than the left-sided stroke.Conclusion The model based on the XGBoost model shows best performance in predicting the risk for swallowing disorders in elderly patients after stroke.

Objective This study aimed to investigate the antimicrobial resistance profiles of bacterial strains isolated from pediatric intensive care units(PICU)in China for better antimicrobial therapy.Methods Clinical isolates were collected from 17 institutions,including tertiary care children's hospitals and pediatric department of tertiary general hospitals in China from January 1,2020 to December 31,2022.Antimicrobial susceptibility testing was carried out according to a unified protocol using Kirby-Bauer method or automated systems.Results were interpreted according to the breakpoints released by the Clinical and Laboratory Standards Institute(CLSI)in 2020.Results A total of 10 688 isolates were collected,including gram-positive organisms(39.2％)and gram-negative organisms(60.8％).The top three organisms were S.aureus(13.6％,1 453/10 688),A.baumannii(10.0％,1 067/10 688),and coagulase-negative Staphylococcus(9.9％,1 058/10 688).Multi-drug resistant organisms(MDROs)were very common in children.The prevalence of methicillin-resistant Staphylococcus aureus(MRSA),carbapenem-resistant Enterobacterales(CRE),carbapenem-resistant E.coli,carbapenem-resistant K.pneumoniae(CRKP),carbapenem-resistant A.baumannii(CRAB),and carbapenem-resistant P.aeruginosa(CRPA)was 41.1％,19.4％,8.8％,30.9％,67.4％,and 28.8％,respectively.Overall,more than 50％of Enterobacteriales isolates were resistant to cephalosporins,while nearly 25％of Enterobacteriales isolates were resistant to carbapenems.MDROs were highly resistant to commonly used antibiotics.More than 80％of CRE and CRAB strains were resistant to all beta-lactam antibiotics.CRE and CRAB showed low resistance rates to tigecycline and polymyxin.CRPA showed lower resistance rates to piperacillin,beta-lactamase inhibitor combinations than the resistance rates to third and fourth generation cephalosporins.All of the Staphylococcus and Enterococcus isolates were susceptible to vancomycin and tigecycline.None of PRSP strains isolated from meningitis and nonmeningitis samples were resistant to rifampicin,vancomycin,or linezolid.The prevalence of β-lactamase-negative ampicillin-resistant(BLNAR)strains was 43.3％in Haemophilus influenzae.Conclusions MDROs were prevalent in PICU.It is necessary to establish an effective multidisciplinary team(MDT)to control the antimicrobial resistance.

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 relationship between prolactin and mild cognitive impairment(MCI)in postmenopausal women with type 2 diabetes mellitus(T2DM).Methods A total of 319 postmenopausal women with T2DM who were hospitalized in the Department of Endocrinology,Drum Tower Hospital,Affiliated Hospital of Medical School,Nanjing University were enrolled in this study from August 2016 to October 2023.All the patients were divided into two groups according whether they had MCI:T2DM group(n=161)and MCI group(n=158).Differences in clinical characteristics were compared between the two groups.Pearson correlation was used to analyze the correlation between sex hormones and cognitive domains,and Logistic regression analysis was used to evaluate the influencing factors for MCI development.Results Serum prolactin levels were significantly lower in the MCI group than in the T2DM group[(5.5±2.1)vs(7.2±2.9)μg/L,P<0.05].Serum prolactin level was positively correlated with mini-mental state examination score,Montreal cognitive assessment score,immediate memory score,visuopatial constructional score,attention score and hippocampal volume(P<0.05),and negatively correlated with processing speed test(time)and executive function test(time)(P<0.05).Logistic regression analysis demonstrated that serum prolactin level was an influencing factor for the risk of MCI in postmenopausal women with T2DM(OR 0.715,95%CI 0.605～0.845,P<0.01).Conclusions The decrease of serum prolactin level is associated with an increased risk of MCI in postmenopausal women with T2DM.

Adenoid cystic carcinoma(ACC)of the cervix is a rare and highly aggressive subtype of cervical cancer,accounting for less than 1%of all cervical cancer cases.ACC predominantly affects postmenopausal women over the age of 60,with postmenopausal vaginal bleeding being the most common symptom.Diagnosis of ACC primarily relies on histopathological examination and immunohistochemical analysis.Although there is currently no standard treatment protocol,surgical resection combined with radiotherapy or concurrent chemoradiotherapy is considered to be an effective approach.However,the effectiveness is limited,particularly in advanced cases,which generally have a poor prognosis.The treatment and prognosis of ACC are closely related to tumor staging,perineural invasion,and margin status.This paper discusses the clinical data and follow-up of six ACC patients treated at our institution,and goes through a literature review,examines its clinical features and treatment outcomes,underscores the critical importance of early diagnosis and individualized treatment.

Objective To construct a risk prediction model for post-stroke dysphagia(PSD)based on clinical and laboratory indicators of elderly stroke patients with explainable machine learning.Methods A retrospective analysis was conducted on 3994 stroke patients hospitalized in Depart-ment of Neurology of First Medical Center of Chinese PLA General Hospital from October 2010 to December 2021.Among them,the 1390 cases admitted during January 2019 and December 2021 were assigned into an external validation set,and the 2604 cases admitted during October 2010 to January 2019 were into a training group.Those from the training group were further divided into a training set(1823 cases)and an internal validation set(781 cases)in a 7∶3 ratio,and also grouped into a PSD subgroup(773 cases)and a non-PSD group(1831 cases).With occurrence of swallowing difficulties as an endpoint,risk prediction models were constructed using random for-est(RF),eXtreme Gradient Boosting(XGBoost),Support Vector Machine(SVM),and logistic regression.ROC curve analysis was employed to evaluate the performance of our models.After the optimal model was selected,SHAP was employed to interpret feature contributions.Results There were significant differences in muscle strength,right/left-sided stroke,and area of brain in-jury between the PSD and the non-PSD groups(P＜0.01).The PSD group had obviously larger proportions of hypertension,diabetes,and drinking history,increased neutrophil counts,and de-creased levels of potassium and albumin when compared with the non-PSD group(P＜0.05,P＜0.01).Multivariate logistic regression analysis showed that age,drinking history,diabetes,hyper-tension,muscle strength grade,area of brain injury,hemispheric stroke,neutrophil count,and al-bumin and potassium levels were risk factors for PSD(P＜0.05,P＜0.01).The external validation results showed that the area under curve value of the RF model,XGBoost model,SVM model,and our logistic model was 0.883,0.902,0.877,and 0.868,respectively.The distribution of SHAP value showed that drinking history,hypertension and diabetes were positively correlated with PSD risk;Muscle strength was negatively correlated with the risk;Age growth was positively correlated with the risk;Subtentorial lesions showed stronger predictive efficacy than supratentorial lesions and entire lesions;The bilateral and right-sided stroke had higher risk for PSD than the left-sided stroke.Conclusion The model based on the XGBoost model shows best performance in predicting the risk for swallowing disorders in elderly patients after stroke.

Obesity, as a chronic recurrent disease, has become a major public health challenge in China. To implement the requirements of the Healthy China Initiative (2019—2030), under domestic guidelines or consensus statements on overweight and obesity, and in alignment with the latest scientific advances globally, the Quality control protocol for adult overweight and obesity screening in health management (examination) institutions (2025 edition) was developed. This protocol was drafted by the Health Management Center of Shanghai Changzheng Hospital and formulated through multiple rounds of deliberation by experts in China’s health examination quality control field. The protocol establishes unified standards for screening facilities, personnel qualifications, and measurement or testing procedures. It defines specific screening items, outlines a standardized screening pathway, and sets requirements for the final medical review, ensuring the scientific validity, effectiveness, and safety of the screening process. The implementation of this protocol will enhance the consistency of weight management practices for adults across health examination institutions and strengthen the quality control of overweight and obesity screening programs.