Objective To explore the value of deep learning(DL)model based on grayscale ultrasound for predicting asymptomatic advanced chronic liver disease(cACLD).Methods Totally 258 patients with asymptomatic compensatory chronic liver diseases were retrospectively included,among them 117 with F3 or F4 stage liver fibrosis were classified into cACLD group,while 141 with F1 or F2 stage liver fibrosis were taken as non-cACLD group.The patients were divided into training set(n=180,including 82 cases of cACLD and 98 cases of non-cACLD)and validation set(n=78,including 35 cases of cACLD and 43 cases of non-cACLD)at the ratio of 7∶3.Univariate and multivariate logistic regression were used to screen independent clinical predictors of cACLD and construct a clinical model.Based on liver grayscale ultrasound,optimal DL features were extracted and screened,and Resnet50 network was adopted as framework,na?ve Bayes classifier was used to construct DL model,and a combined model was constructed based on clinical model and DL model.The efficacy and clinical value of each model for predicting asymptomatic cACLD were evaluated.Results Age,gamma-glutamyl transferase and platelet count were all independent clinical predictors of cACLD,and a clinical model was constructed.Totally 38 optimal DL features were screened to build a DL model.The AUC of combined model in training set and validation set was 0.950 and 0.740,of DL model was 0.944 and 0.737,respectively,being not significantly different(both P＞0.05)but all higher than that of clinical model(0.667 and 0.573,all P＜0.05).Taken 0.59-0.90 as the threshold,the net benefits of combined model in both training and validation sets were higher than that of other models.Conclusion DL model based on grayscale ultrasound could be used to effectively predict asymptomatic cACLD.Combining with clinical characteristics might improve clinical net benefit of this model.

Objective:To explore the psychological acceptance mechanism of appropriate Traditional Chinese Medicine (TCM) techniques among patients with abnormal uterine bleeding (AUB) .Methods:Using purposive sampling, AUB patients experiencing menstruation but not yet menopausal were recruited from Zhumadian City, Henan Province, and Jiaxing City, Zhejiang Province, between November 2022 and January 2023. Semi-structured interviews were conducted, and the collected data were analyzed using content analysis.Results:A total of four main themes were identified: individualized disease perception and treatment experience; awareness and treatment experience of appropriate TCM techniques; cultural identity and influence of traditional beliefs; and the need for science communication and safety regarding TCM techniques.Conclusions:While AUB patients show a generally high level of acceptance toward appropriate TCM techniques, their understanding of both AUB and the relevant TCM therapies remains limited. Multiple factors influence patients' choices, and some concerns and doubts still persist during the decision-making process.

Purpose To develop an integrate model combining deep learning features from contrast-enhanced lung ultrasonography with clinical characteristics for predicting epidermal growth factor receptor mutation status in peripheral non-small cell lung cancer.Materials and Methods This retrospective study included 117 patients with pathologically confirmed non-small cell lung cancer from the First Affiliated Hospital of Guangxi Medical University(July 2021 to February 2024).Patients were randomly divided into training(n=93)and test(n=24)sets at an 8∶2 ratio.Regions of interest were delineated at the peak enhancement phase of contrast-enhanced lung ultrasonography.Various deep learning convolutional neural networks were pretrained,with ResNet18 selected as optimal for feature extraction.Deep learning,clinical,and integrated models were constructed using naive Bayesian algorithm.Performance was evaluated via receiver operating characteristic and calibration curves,while class activation mapping and Shapley additive explanation values provided model interpretability.Results In the training set,the deep learning,clinical and integrated models achieved area under the curve of 0.93(95%CI 0.88-0.98),0.86(95%CI 0.68-1.00),and 0.91(95%CI 0.85-0.97),respectively.Corresponding test set area under the curve were 0.81(95%CI 0.72-0.90),0.56(95%CI 0.33-0.80),and 0.87(95%CI 0.72-1.00).Both deep learning and integrated models significantly outperformed the clinical model in training(Z=2.380,P=0.017;Z=2.597,P=0.009)and test sets(Z=2.034,P=0.042;Z=2.577,P=0.010).The integrated model demonstrated excellent calibration and predictive performance.Conclusion The integrated model combining deep learning features from contrast-enhanced lung ultrasonography with clinical characteristics effectively predicts epidermal growth factor receptor mutation status in peripheral non-small cell lung cancer.

Purpose To develop an integrate model combining deep learning features from contrast-enhanced lung ultrasonography with clinical characteristics for predicting epidermal growth factor receptor mutation status in peripheral non-small cell lung cancer.Materials and Methods This retrospective study included 117 patients with pathologically confirmed non-small cell lung cancer from the First Affiliated Hospital of Guangxi Medical University(July 2021 to February 2024).Patients were randomly divided into training(n=93)and test(n=24)sets at an 8∶2 ratio.Regions of interest were delineated at the peak enhancement phase of contrast-enhanced lung ultrasonography.Various deep learning convolutional neural networks were pretrained,with ResNet18 selected as optimal for feature extraction.Deep learning,clinical,and integrated models were constructed using naive Bayesian algorithm.Performance was evaluated via receiver operating characteristic and calibration curves,while class activation mapping and Shapley additive explanation values provided model interpretability.Results In the training set,the deep learning,clinical and integrated models achieved area under the curve of 0.93(95%CI 0.88-0.98),0.86(95%CI 0.68-1.00),and 0.91(95%CI 0.85-0.97),respectively.Corresponding test set area under the curve were 0.81(95%CI 0.72-0.90),0.56(95%CI 0.33-0.80),and 0.87(95%CI 0.72-1.00).Both deep learning and integrated models significantly outperformed the clinical model in training(Z=2.380,P=0.017;Z=2.597,P=0.009)and test sets(Z=2.034,P=0.042;Z=2.577,P=0.010).The integrated model demonstrated excellent calibration and predictive performance.Conclusion The integrated model combining deep learning features from contrast-enhanced lung ultrasonography with clinical characteristics effectively predicts epidermal growth factor receptor mutation status in peripheral non-small cell lung cancer.

Objective To explore the value of deep learning(DL)model based on grayscale ultrasound for predicting asymptomatic advanced chronic liver disease(cACLD).Methods Totally 258 patients with asymptomatic compensatory chronic liver diseases were retrospectively included,among them 117 with F3 or F4 stage liver fibrosis were classified into cACLD group,while 141 with F1 or F2 stage liver fibrosis were taken as non-cACLD group.The patients were divided into training set(n=180,including 82 cases of cACLD and 98 cases of non-cACLD)and validation set(n=78,including 35 cases of cACLD and 43 cases of non-cACLD)at the ratio of 7∶3.Univariate and multivariate logistic regression were used to screen independent clinical predictors of cACLD and construct a clinical model.Based on liver grayscale ultrasound,optimal DL features were extracted and screened,and Resnet50 network was adopted as framework,na?ve Bayes classifier was used to construct DL model,and a combined model was constructed based on clinical model and DL model.The efficacy and clinical value of each model for predicting asymptomatic cACLD were evaluated.Results Age,gamma-glutamyl transferase and platelet count were all independent clinical predictors of cACLD,and a clinical model was constructed.Totally 38 optimal DL features were screened to build a DL model.The AUC of combined model in training set and validation set was 0.950 and 0.740,of DL model was 0.944 and 0.737,respectively,being not significantly different(both P＞0.05)but all higher than that of clinical model(0.667 and 0.573,all P＜0.05).Taken 0.59-0.90 as the threshold,the net benefits of combined model in both training and validation sets were higher than that of other models.Conclusion DL model based on grayscale ultrasound could be used to effectively predict asymptomatic cACLD.Combining with clinical characteristics might improve clinical net benefit of this model.

Objective:To explore the psychological acceptance mechanism of appropriate Traditional Chinese Medicine (TCM) techniques among patients with abnormal uterine bleeding (AUB) .Methods:Using purposive sampling, AUB patients experiencing menstruation but not yet menopausal were recruited from Zhumadian City, Henan Province, and Jiaxing City, Zhejiang Province, between November 2022 and January 2023. Semi-structured interviews were conducted, and the collected data were analyzed using content analysis.Results:A total of four main themes were identified: individualized disease perception and treatment experience; awareness and treatment experience of appropriate TCM techniques; cultural identity and influence of traditional beliefs; and the need for science communication and safety regarding TCM techniques.Conclusions:While AUB patients show a generally high level of acceptance toward appropriate TCM techniques, their understanding of both AUB and the relevant TCM therapies remains limited. Multiple factors influence patients' choices, and some concerns and doubts still persist during the decision-making process.

Objective To investigate the effect and mechanism of IL-17 on heart failure(HF)in hy-pertensive rats based on NF-κB/sarco-endoplasmic reticulum calcium ATPase 2(SERCA2)signa-ling pathway.Methods Thirty SPF male spontaneously hypertensive rats(SHR)aged 6-8 weeks were divided into control group,model group,phosphate buffer salt(PBS)solution injec-tion group(PBS group),IL-17 protein injection group(IL-17 group)and IL-17 and antibody injec-tion group(IL-17+IgG group),with 6 animals in each group.Hypertensive HF model was estab-lished,and corresponding agents were applied to the PBS group,IL-17 group and IL-17+IgG group intraperitoneally,respectively.The role of IL-17,NF-κB and SERCA2 in hypertensive HF was studied with HE staining,immunohistochemical assay,Western blotting,RT-qPCR and ELISA.Results Significantly higher serum levels of NT-proBNP and IL-17,enhanced myocardial expression of IL-17 mRNA and NF-κB protein,lower serum VEGF level,and down-regulated pro-tein level of SERCA2 in heart tissue were observed in the model group and the PBS group when compared with the control group(P＜0.01).The IL-17 group had obviously higher serum NT-proBNP and IL-17 levels and myocardial expression of IL-17 mRNA and NF-κB protein,and reduced serum VEGF level and SERCA2 protein level in heart tissue than the model group(P＜0.01).IL-17+IgG treatment resulted in notably lower serum IL-17 level and myocardial NF-κB protein level when compared with those of model group(8.98±1.20 vs 11.19±1.22,0.88±0.03 vs 0.93±0.03,P＜0.01),and also resulted in remarkably reduced serum levels of NT-proBNP and IL-17 and myocardial expression of IL-17 mRNA and NF-κB protein but increased serum VEGF level and SERCA2 protein level in heart tissue when compared with the IL-17 group(P＜0.01).The heart rate,SBP,IVSd,LVPWd,LVEDD and LVESD were significantly lower,while LVFS was notably higher in the IL-17+IgG group than the model group and IL-17 group(P＜0.01).The IL-17+IgG group had obviously higher LVEF than the IL-17 group[(70.81±6.50)％vs(62.77±5.43)％,P＜0.01].Conclusion IL-17/NF-κB/SERCA2 signaling pathway is involved in the regulation of inflammatory response after hypertensive HF,and inhibiting IL-17 can effective-ly improve the cardiac dysfunction caused by hypertensive HF.

ObjectiveTo determine the epidemic characteristics of anthrax in Chengde City， Hebei Province from 2005 to 2021， and to provide evidence for formulating prevention and control measures of anthrax and reducing incidence rate. MethodsThis study collected the data of anthrax epidemic in Chengde City and conducted descriptive analysis. ResultsFrom 2005 to 2021， a total of 11 anthrax cases were reported in Chengde City with no death. The average incidence rate was 0.08/10⁵， which remained low. Furthermore， 10 cases were cutaneous anthrax and 1 case was pulmonary anthrax. The cases were mainly reported in Weichang County， accounting for 90.91% of the total reported cases， followed by Pingquan City. In addition， the cases were mainly reported from July to August and mainly between 30 and 59 years old with a gender ratio of 2.67∶1. ConclusionThe anthrax epidemic in Chengde City is likely to increase. It mainly occurs in summer， rural areas， and male young and middle-aged farmers. It is necessary to improve epidemic monitoring， health education， disease prevention capacity， early identification of the epidemic， and active response.

Objective:To explore the application effects of the mode of "Multidisciplinary integration, Doctors & patients co-teaching, Simulated practice" in the teaching of spinal surgery.Methods:A total of 64 eight-year program clinical medical students who practiced in Peking Union Medical College Hospital in 2021 were taken as research objects and randomly divided into experimental group ( n=33) and control group ( n=31). The experimental group received the new teaching mode of "Multidisciplinary integration, Doctors & patients co-teaching, Simulated practice", and the control group received regular teaching mode. At the end of teaching, the teaching effects were evaluated from several aspects, including the scores of theoretical examinations, anatomical marks identification tests, and anonymous questionnaires. SPSS 22.0 software was used for paired t-test and two independent-samples t-test. Results:The theoretical test scores [(51.25±6.99) points] and anatomical structure identification scores [(37.56±1.83) points] of the experimental group were higher than those of the control group [(42.46±6.13) points and (30.37±3.46) points], and the differences were statistically significant ( P<0.001). The effective recovery rate of the questionnaire was 100%. The results of the questionnaire showed that the experimental group was significantly higher than the control group in terms of teaching attractiveness, attention, learning interest, learning efficiency, anatomical identification ability, problem-finding and problem-solving ability and overall teaching method satisfaction ( P<0.05). Conclusion:The teaching mode of "Multidisciplinary integration, Doctors & patients co-teaching, Simulated practice" can effectively improve students' theoretical knowledge, learning interest, learning efficiency, operation proficiency and problem-finding and problem-solving ability, which is worth promoting.

With the continuous advancement of health informatization and the wide application of medical big data, electronic health records came into being and spread rapidly. However, because electronic health records contain a large amount of private information, privacy protection is the primary consideration for the sustainable development of electronic health records. By analyzing the shortcomings of privacy protection of electronic health records in law, technology, management and protection consciousness, this paper put forward some countermeasures, such as perfecting the relevant laws and regulations of privacy protection of electronic health records, improving the technical level, improving the management defects of electronic health records, and cultivating the privacy protection consciousness of professionals and the public, so as to improve the overall privacy protection level of China’s health records information management system and provide effective protection for the privacy information of Chinese residents’ electronic health records.