In recent years,significant breakthroughs have been achieved in the immunotherapy for Alzheimer's disease.In line with global advancements,two anti-amyloid-β monoclonal antibodies have been approved and successfully launched in China for clinical use.Lecanemab and Donanemab were officially used in June 2024 and April 2025 in China,respectively.In order to standardize the rational and safe application of anti-amyloid-β monoclonal antibodies for Alzheimer's disease in China,this article integrates recom-mendations from the clinical trials and real-world experience from the author's team and domestic peers to further update the recom-mendations for the clinical use of anti-amyloid-β monoclonal antibody based on the 2024 version.It includes indications for therapy,pre-treatment evaluation and preparation,administration protocols and safety measures during treatment,and post-treatment monitor-ing strategies.

Purpose To investigate the immunohistochemical HER2 expression in a large group of patients with urothelial carcinoma and to compare the results with the pathologic features and survival rate.Methods A total of 519 urothelial carcinoma specimens were collected from two centers.HER2 expression was measured by EnVision immuno-histochemistry.HER2 expression was compared with clinicopathological parameters,and further analyzed in relation to patient prognosis.Results The median age of the 519 patients was 66 years with a male to female ratio of 1.93∶1.Among them,160 cases were radical specimens,and 359 were transurethral resection specimens.The overall HER2 positivity rate was 61.7％(320/519),of which 148 cases(28.5％)were HER2 1+,238(45.9％)were HER2 2+,and 82(15.8％)were HER2 3+.In addition,51 cases(9.8％)were HER2-negative.HER2-positive ex-pression was associated with age,tumor location,histological grade,histological type,surgical approach,lymphovas-cular invasion,and neural invasion(all P＜0.05),but there was no significant correlation with gender,pT stage,muscular invasion,or lymph node metastasis.Univariate and multivariate logistic regression analysis showed that age≥ 66 years,higher tumor grade,and lymphovascular invasion were risk factors for positive HER2 expression,and high histological grade and lymphovascular invasion were independent risk factors affecting HER2 expression after controlling for confounders.Survival analysis showed no significant difference in recurrence-free survival between patients with HER2-positive and HER2-negative non-muscle-invasive urothelial carcinoma(P=0.274).Conclusion High histologic grade,tumor lymphovascular invasion,and neural invasion were associated with positive HER2 expression in patients with urothelial carcinoma,and higher histologic grade and lymphovascular invasion are important factors affect-ing HER2 expression.However,HER2-positive expression may not affect the prognosis of patients with non-muscle-invasive bladder urothelial carcinoma.

Objective:To analyze the reasons of misdiagnosed cases in the intraoperative frozen pathological diagnosis of breast disease and explore effective measures and practices for targeted and standardized quality control.Methods:A retrospective analysis was conducted on 2 421 cases of breast intraoperative frozen pathological examination performed at Renmin Hospital of Wuhan University from Apr. 2020 to Dec. 2021. The results of intraoperative frozen pathological examination were compared with postoperative pathological results to calculate the overall concordance rate and misdiagnosis rate. Pathological classification and causative analysis were performed for misdiagnosed cases. Standardized management was implemented to address the identified issues, and an analysis was conducted on 2248 cases from Feb. 2022 to Nov. 2023 to compare the overall concordance rate and misdiagnosis rate before and after management.Results:The comparison between intraoperative rapid frozen pathology diagnosis and postoperative paraffin pathology diagnosis showed that among the 2 421 breast specimens, there were 2 377 cases (98.18%) with concordant results and 44 cases of misdiagnosis, resulting in a misdiagnosis rate of 1.82%. The pathological types of 44 misdiagnosed cases were analyzed, among which 10 cases were lymph node metastatic carcinoma, 5 were lobar tumors, 3 were intraductal papillary tumors, 7 were carcinoma in situ and common hyperplasia each, and 4 were carcinoma in situ, sclerosing adenopathy, and other invasive carcinoma each. Through the analysis of causes, it was found that poor slide quality, the need for immunohistochemistry assistance, careless slide reading, missed critical lesions, and other factors contributed to misdiagnosis, with variations in the causes of misdiagnosis among different pathological types. After implementing standardized management, the overall concordance rate significantly improved (98.93%) and the misdiagnosis rate significantly decreased (1.07%) .Conclusions:Intraoperative frozen pathological diagnosis is of great significance in the treatment of breast diseases. The targeted standardized quality control can help early detection and solve problems, reduce the differences between different doctors and technicians, and improve the accuracy of intraoperative frozen pathological diagnosis.

Objective To understand the current situation of healthcare-associated infection(HAI)in China,pro-vide data support and decision-making basis for formulating scientific and effective strategies for HAI prevention and control.Methods A nationwide cross-sectional survey on HAI was conducted among various types and levels of medical institutions in China according to a unified protocol of bedside surveys and case investigations.Results In 2024,a total of 5 736 medical institutions and 2 751 765 patients were surveyed.Among them,34 889 HAI cases were identified,with a prevalence rate of 1.27％.The number of HAI episodes was 38 032,and case prevalence rate was 1.38％.The prevalence rate of HAI in medical institutions in different regions of China ranged from 0.66％to 2.35％.Among medical institutions of different scales,those with a bed capacity of ≥900 had the high-est incidence of HAI,reaching 1.65％.The most common infection site was the lower respiratory tract(44.66％),followed by the urinary tract(12.94％),surgical site(9.32％),upper respiratory tract(7.02％),and bloodstream infection(5.78％).The top 3 departments with the highest HAI rates were the general intensive care unit(10.02％),department of neurosurgery(5.51％),and department(group)of hematology(5.34％).A total of 23 238 strains of HAI pathogens were detected,with 10 714 strains(46.10％)from lower respiratory tract speci-mens.The top 5 detected strains were Klebsiella pneumoniae(14.76％),Pseudomonas aeruginosa(13.33％),Escherichia coli(12.79％),Acinetobacter baumannii(9.23％),and Staphylococcus aureus(7.88％).231 944 pa-tients underwent class Ⅰ incision surgery were monitored,with 1 647 cases experienced surgical site infection,and the prevalence rate of surgical site infection was 0.71％.The number of patients who should undergo pathogen de-tection(patients receiving therapeutic and therapeutic combined prophylactic antimicrobial agents)was 715 179,while the actual number was 480 492,with a pathogen detection rate of 67.18％.425 225 patients received patho-genic detection before treatment,with a detection rate of 59.46％.Conclusion The overall HAI prevalence in Chi-na is lower,showing disparities among medical institutions of different regions and scales.Therefore,precise imple-mentation of measures is necessary for HAI prevention and control,with a focus on high-risk institutions and high-risk departments,key areas,and critical procedures.All levels of medical institutions should continuously reduce the incidence of HAI by strengthening monitoring,standardizing the use of antimicrobial agents,and reinforcing basic HAI prevention and control measures.

Objective:To analyze the reasons of misdiagnosed cases in the intraoperative frozen pathological diagnosis of breast disease and explore effective measures and practices for targeted and standardized quality control.Methods:A retrospective analysis was conducted on 2 421 cases of breast intraoperative frozen pathological examination performed at Renmin Hospital of Wuhan University from Apr. 2020 to Dec. 2021. The results of intraoperative frozen pathological examination were compared with postoperative pathological results to calculate the overall concordance rate and misdiagnosis rate. Pathological classification and causative analysis were performed for misdiagnosed cases. Standardized management was implemented to address the identified issues, and an analysis was conducted on 2248 cases from Feb. 2022 to Nov. 2023 to compare the overall concordance rate and misdiagnosis rate before and after management.Results:The comparison between intraoperative rapid frozen pathology diagnosis and postoperative paraffin pathology diagnosis showed that among the 2 421 breast specimens, there were 2 377 cases (98.18%) with concordant results and 44 cases of misdiagnosis, resulting in a misdiagnosis rate of 1.82%. The pathological types of 44 misdiagnosed cases were analyzed, among which 10 cases were lymph node metastatic carcinoma, 5 were lobar tumors, 3 were intraductal papillary tumors, 7 were carcinoma in situ and common hyperplasia each, and 4 were carcinoma in situ, sclerosing adenopathy, and other invasive carcinoma each. Through the analysis of causes, it was found that poor slide quality, the need for immunohistochemistry assistance, careless slide reading, missed critical lesions, and other factors contributed to misdiagnosis, with variations in the causes of misdiagnosis among different pathological types. After implementing standardized management, the overall concordance rate significantly improved (98.93%) and the misdiagnosis rate significantly decreased (1.07%) .Conclusions:Intraoperative frozen pathological diagnosis is of great significance in the treatment of breast diseases. The targeted standardized quality control can help early detection and solve problems, reduce the differences between different doctors and technicians, and improve the accuracy of intraoperative frozen pathological diagnosis.

Objective:To investigate the prognostic value of deep learning-based automated quantification of tumor-stroma ratio (TSR) in patients undergoing neoadjuvant therapy (NAT) for breast cancer.Methods:Specimens were collected from 209 breast cancer patients who received NAT at Renmin Hospital of Wuhan University from October 2019 to June 2023. TSR levels in pre-NAT biopsy specimens were automatically computed using a deep learning algorithm and categorized into low stroma (TSR≤30%), intermediate stroma (TSR 30% to ≤60%), and high stroma (TSR>60%) groups. Residual cancer burden (RCB) grading of post-NAT surgical specimens was determined to compare the relationship between TSR expression levels and RCB grades. The correlation of TSR with NAT efficacy was analyzed, and the association between TSR expression and patient prognosis was further investigated.Results:There were 85 cases with low stroma (TSR≤30%), 93 cases with intermediate stroma (TSR 30% to ≤60%), and 31 cases with high stroma (TSR>60%). Different TSR expression levels showed significant differences between various RCB grades ( P<0.05). Logistic univariate and multivariate analyses showed that TSR was a risk factor for obtaining a complete pathological remission from neoadjuvant therapy for breast cancer when it was used as a continuous variable ( P<0.05); COX regression and survival analyses showed that the lower the percentage of tumorigenic mesenchyme was, the better the prognosis of the patient was ( P<0.05). Conclusions:The deep learning-based model enables automatic and accurate quantification of TSR. A lower pre-treatment tumoral stroma is associated with a lower RCB score and a higher rate of pathologic complete response, indicating that TSR can predict the efficacy of neoadjuvant therapy in breast cancer and thus holds prognostic significance. Therefore, TSR may serve as a biomarker for predicting therapeutic outcomes in breast cancer neoadjuvant therapy.

Purpose To investigate the immunohistochemical HER2 expression in a large group of patients with urothelial carcinoma and to compare the results with the pathologic features and survival rate.Methods A total of 519 urothelial carcinoma specimens were collected from two centers.HER2 expression was measured by EnVision immuno-histochemistry.HER2 expression was compared with clinicopathological parameters,and further analyzed in relation to patient prognosis.Results The median age of the 519 patients was 66 years with a male to female ratio of 1.93∶1.Among them,160 cases were radical specimens,and 359 were transurethral resection specimens.The overall HER2 positivity rate was 61.7％(320/519),of which 148 cases(28.5％)were HER2 1+,238(45.9％)were HER2 2+,and 82(15.8％)were HER2 3+.In addition,51 cases(9.8％)were HER2-negative.HER2-positive ex-pression was associated with age,tumor location,histological grade,histological type,surgical approach,lymphovas-cular invasion,and neural invasion(all P＜0.05),but there was no significant correlation with gender,pT stage,muscular invasion,or lymph node metastasis.Univariate and multivariate logistic regression analysis showed that age≥ 66 years,higher tumor grade,and lymphovascular invasion were risk factors for positive HER2 expression,and high histological grade and lymphovascular invasion were independent risk factors affecting HER2 expression after controlling for confounders.Survival analysis showed no significant difference in recurrence-free survival between patients with HER2-positive and HER2-negative non-muscle-invasive urothelial carcinoma(P=0.274).Conclusion High histologic grade,tumor lymphovascular invasion,and neural invasion were associated with positive HER2 expression in patients with urothelial carcinoma,and higher histologic grade and lymphovascular invasion are important factors affect-ing HER2 expression.However,HER2-positive expression may not affect the prognosis of patients with non-muscle-invasive bladder urothelial carcinoma.

Objective:To investigate the prognostic value of deep learning-based automated quantification of tumor-stroma ratio (TSR) in patients undergoing neoadjuvant therapy (NAT) for breast cancer.Methods:Specimens were collected from 209 breast cancer patients who received NAT at Renmin Hospital of Wuhan University from October 2019 to June 2023. TSR levels in pre-NAT biopsy specimens were automatically computed using a deep learning algorithm and categorized into low stroma (TSR≤30%), intermediate stroma (TSR 30% to ≤60%), and high stroma (TSR>60%) groups. Residual cancer burden (RCB) grading of post-NAT surgical specimens was determined to compare the relationship between TSR expression levels and RCB grades. The correlation of TSR with NAT efficacy was analyzed, and the association between TSR expression and patient prognosis was further investigated.Results:There were 85 cases with low stroma (TSR≤30%), 93 cases with intermediate stroma (TSR 30% to ≤60%), and 31 cases with high stroma (TSR>60%). Different TSR expression levels showed significant differences between various RCB grades ( P<0.05). Logistic univariate and multivariate analyses showed that TSR was a risk factor for obtaining a complete pathological remission from neoadjuvant therapy for breast cancer when it was used as a continuous variable ( P<0.05); COX regression and survival analyses showed that the lower the percentage of tumorigenic mesenchyme was, the better the prognosis of the patient was ( P<0.05). Conclusions:The deep learning-based model enables automatic and accurate quantification of TSR. A lower pre-treatment tumoral stroma is associated with a lower RCB score and a higher rate of pathologic complete response, indicating that TSR can predict the efficacy of neoadjuvant therapy in breast cancer and thus holds prognostic significance. Therefore, TSR may serve as a biomarker for predicting therapeutic outcomes in breast cancer neoadjuvant therapy.

Objective To understand the current situation of healthcare-associated infection(HAI)in China,pro-vide data support and decision-making basis for formulating scientific and effective strategies for HAI prevention and control.Methods A nationwide cross-sectional survey on HAI was conducted among various types and levels of medical institutions in China according to a unified protocol of bedside surveys and case investigations.Results In 2024,a total of 5 736 medical institutions and 2 751 765 patients were surveyed.Among them,34 889 HAI cases were identified,with a prevalence rate of 1.27％.The number of HAI episodes was 38 032,and case prevalence rate was 1.38％.The prevalence rate of HAI in medical institutions in different regions of China ranged from 0.66％to 2.35％.Among medical institutions of different scales,those with a bed capacity of ≥900 had the high-est incidence of HAI,reaching 1.65％.The most common infection site was the lower respiratory tract(44.66％),followed by the urinary tract(12.94％),surgical site(9.32％),upper respiratory tract(7.02％),and bloodstream infection(5.78％).The top 3 departments with the highest HAI rates were the general intensive care unit(10.02％),department of neurosurgery(5.51％),and department(group)of hematology(5.34％).A total of 23 238 strains of HAI pathogens were detected,with 10 714 strains(46.10％)from lower respiratory tract speci-mens.The top 5 detected strains were Klebsiella pneumoniae(14.76％),Pseudomonas aeruginosa(13.33％),Escherichia coli(12.79％),Acinetobacter baumannii(9.23％),and Staphylococcus aureus(7.88％).231 944 pa-tients underwent class Ⅰ incision surgery were monitored,with 1 647 cases experienced surgical site infection,and the prevalence rate of surgical site infection was 0.71％.The number of patients who should undergo pathogen de-tection(patients receiving therapeutic and therapeutic combined prophylactic antimicrobial agents)was 715 179,while the actual number was 480 492,with a pathogen detection rate of 67.18％.425 225 patients received patho-genic detection before treatment,with a detection rate of 59.46％.Conclusion The overall HAI prevalence in Chi-na is lower,showing disparities among medical institutions of different regions and scales.Therefore,precise imple-mentation of measures is necessary for HAI prevention and control,with a focus on high-risk institutions and high-risk departments,key areas,and critical procedures.All levels of medical institutions should continuously reduce the incidence of HAI by strengthening monitoring,standardizing the use of antimicrobial agents,and reinforcing basic HAI prevention and control measures.

Objective:To aid in the detection of thyroid cancer by using deep learning to differentiate the unique bioimpedance parameter patterns of different thyroid tissues.Methods:An electrical impedance system was designed to measure 331 ex-vivo thyroid specimens from 321 patients during surgery. The impedance data was then analyzed with one dimensional convolution neural (1D-CNN) combining with long short-term memory (LSTM) network models of deep learning. In the process of analysis, we assigned 80% of the data to training set (1072/1340) and the remaining 20% data to the test set (268/1340). The performance of final model was assessed using receiver operating characteristic (ROC) curves. In addition, sensitivity, specificity, positive predictive value, negative predictive value, Youden index were applied to compare impedance model with ultrasound results.Results:The ROC curve of the two-classification (malignant /non-malignant tissue) model showed a good performance (area-under-the-curve AUC=0.94), with an overall accuracy of 91.4%. To better fit clinical practice, we further performed a three-classification (malignant/ benign/ normal tissue) model, of which the areas under ROC curve were 0.91, 0.85, 0.92 for normal, benign, and malignant group, respectively. The results indicated that the area under micro-average ROC curve and the macro-average ROC curve were 0.91 and 0.90, respectively. Moreover, compared with ultrasound, the impedance model exhibited higher specificity.Conclusions:A deep learning model (CNN-LSTM) trained by thyroid electrical impedance spectroscopy (EIS) parameters shows an excellent performance in distinguishing among different in-vitro thyroid tissues, which is promising for applications. In future clinical utility, our study does not replace existing tests, but rather complements others, thus contributing to therapeutic decision-making and management of thyroid disease.