Objective:To investigate the diagnostic performance of a new artificial intelligence (AI) model incorporating SAM-YOLOV 5 deep learning network and image processing techniques for Breast Imaging Reporting and Data System (BI-RADS) 4 category breast masses in dynamic ultrasound classification.Methods:A total of 530 pathologically proven breast lesions of BI-RADS category 4 in 458 patients were retrospectively collected from May 2019 to June 2023 at the First Affiliated Hospital of Shantou University Medical College. The model was trained and tested at ratio of 7∶3, the area under the ROC curve (AUC), sensitivity, specificity, positive predictive value and negative predictive value of the model were determined. Firstly, the test results of the model were compared with a single static image, then, compared with the three conventional deep learning networks as well as senior and junior radiologists. The diagnostic efficiency of the new model in BI-RADS categories 4a, 4b, and 4c masses were analyzed.Results:The AUC, sensitivity, specificity, positive predictive value and negative predictive value of the new model based on dynamic ultrasound video were higher than those using a single ultrasound static imaging (all P<0.05). Based on dynamic ultrasound video, the AUC, sensitivity, specificity, positive predictive value and negative predictive value of the new model were significantly higher than those of YOLOV 5, VGG 16, Resnet 50 and the junior group (all P<0.05), lower than the senior group (just specificity and negative predictive value, P<0.05). The diagnostic efficiency of new model for BI-RADS category 4b masses was the lowest. Conclusions:Based on the SAM-YOLOV 5 deep learning network and image processing techniques, the new model has a high diagnostic value for breast mass dynamic ultrasound classification and is expected to be used in assisting clinical diagnosis.

Objective:To investigate the diagnostic accuracy of serological indicators and evaluate the diagnostic value of a new established combined serological model on identifying the minimal hepatic encephalopathy (MHE) in patients with compensated cirrhosis.Methods:This prospective multicenter study enrolled 263 compensated cirrhotic patients from 23 hospitals in 15 provinces, autonomous regions and municipalities of China between October 2021 and August 2022. Clinical data and laboratory test results were collected, and the model for end-stage liver disease (MELD) score was calculated. Ammonia level was corrected to the upper limit of normal (AMM-ULN) by the baseline blood ammonia measurements/upper limit of the normal reference value. MHE was diagnosed by combined abnormal number connection test-A and abnormal digit symbol test as suggested by Guidelines on the management of hepatic encephalopathy in cirrhosis. The patients were randomly divided (7∶3) into training set ( n=185) and validation set ( n=78) based on caret package of R language. Logistic regression was used to establish a combined model of MHE diagnosis. The diagnostic performance was evaluated by the area under the curve (AUC) of receiver operating characteristic curve, Hosmer-Lemeshow test and calibration curve. The internal verification was carried out by the Bootstrap method ( n=200). AUC comparisons were achieved using the Delong test. Results:In the training set, prevalence of MHE was 37.8% (70/185). There were statistically significant differences in AMM-ULN, albumin, platelet, alkaline phosphatase, international normalized ratio, MELD score and education between non-MHE group and MHE group (all P<0.05). Multivariate Logistic regression analysis showed that AMM-ULN [odds ratio ( OR)=1.78, 95% confidence interval ( CI) 1.05-3.14, P=0.038] and MELD score ( OR=1.11, 95% CI 1.04-1.20, P=0.002) were independent risk factors for MHE, and the AUC for predicting MHE were 0.663, 0.625, respectively. Compared with the use of blood AMM-ULN and MELD score alone, the AUC of the combined model of AMM-ULN, MELD score and education exhibited better predictive performance in determining the presence of MHE was 0.755, the specificity and sensitivity was 85.2% and 55.7%, respectively. Hosmer-Lemeshow test and calibration curve showed that the model had good calibration ( P=0.733). The AUC for internal validation of the combined model for diagnosing MHE was 0.752. In the validation set, the AUC of the combined model for diagnosing MHE was 0.794, and Hosmer-Lemeshow test showed good calibration ( P=0.841). Conclusion:Use of the combined model including AMM-ULN, MELD score and education could improve the predictive efficiency of MHE among patients with compensated cirrhosis.

Objective:To compare the differences in the prevalence of mild micro-hepatic encephalopathy (MHE) among patients with cirrhosis by using the psychometric hepatic encephalopathy score (PHES) and the Stroop smartphone application (Encephal App) test.Methods:This prospective, multi-center, real-world study was initiated by the National Clinical Medical Research Center for Infectious Diseases and the Portal Hypertension Alliance and registered with International ClinicalTrials.gov (NCT05140837). 354 cases of cirrhosis were enrolled in 19 hospitals across the country. PHES (including digital connection tests A and B, digital symbol tests, trajectory drawing tests, and serial management tests) and the Stroop test were conducted in all of them. PHES was differentiated using standard diagnostic criteria established by the two studies in China and South Korea. The Stroop test was evaluated based on the criteria of the research and development team. The impact of different diagnostic standards or methods on the incidence of MHE in patients with cirrhosis was analyzed. Data between groups were differentiated using the t-test, Mann-Whitney U test, and χ2 test. A kappa test was used to compare the consistency between groups. Results:After PHES, the prevalence of MHE among 354 cases of cirrhosis was 78.53% and 15.25%, respectively, based on Chinese research standards and Korean research normal value standards. However, the prevalence of MHE was 56.78% based on the Stroop test, and the differences in pairwise comparisons among the three groups were statistically significant (kappa = -0.064, P < 0.001). Stratified analysis revealed that the MHE prevalence in three groups of patients with Child-Pugh classes A, B, and C was 74.14%, 83.33%, and 88.24%, respectively, according to the normal value standards of Chinese researchers, while the MHE prevalence rates in three groups of patients with Child-Pugh classes A, B, and C were 8.29%, 23.53%, and 38.24%, respectively, according to the normal value standards of Korean researchers. Furthermore, the prevalence rates of MHE in the three groups of patients with Child-Pugh grades A, B, and C were 52.68%, 58.82%, and 73.53%, respectively, according to the Stroop test standard. However, among the results of each diagnostic standard, the prevalence of MHE showed an increasing trend with an increasing Child-Pugh grade. Further comparison demonstrated that the scores obtained by the number connection test A and the number symbol test were consistent according to the normal value standards of the two studies in China and South Korea ( Z = -0.982, -1.702; P = 0.326, 0.089), while the other three sub-tests had significant differences ( P < 0.001). Conclusion:The prevalence rate of MHE in the cirrhotic population is high, but the prevalence of MHE obtained by using different diagnostic criteria or methods varies greatly. Therefore, in line with the current changes in demographics and disease spectrum, it is necessary to enroll a larger sample size of a healthy population as a control. Moreover, the establishment of more reliable diagnostic scoring criteria will serve as a basis for obtaining accurate MHE incidence and formulating diagnosis and treatment strategies in cirrhotic populations.

Objective: To investigate risk factors and epidemiological characteristics of bacillary dysentery outbreaks in three schools, and to provide scientific basis for the prevention and control of the epidemic in the future. Methods: Case definition was established. All suspected, possible and confirmed cases of all students and faculty members from 3 schools (A, B, C) were selected for epidemiological investigation. Control group was used for case-control analysis, and relevant samples were collected for laboratory testing. Results: A total of 132 cases were found in 3 schools, all of which were from students, with the incidence rate of 17.74%. The morbidity in kindergarten A was 20.00%, in center primary school B it was 21.74%, and in junior middle school C it was 11.61%. Cohort studies and casecontrol studies suggested that schools are exposed places and that washing hands with raw water in schools was possible risk factor [OR(95%CI) =4.50(1.01-20.11)]. Nine stool samples were tested in laboratory, among which 8 were positive for Shigella(88.99%), and Shigella was detected in the end nodes of school s pipeline network, the water samples from canteen bucket, and the floor drains of sewer pipe. Conclusion The bacillary dysentery outbreaks in 3 schools was caused by Shigella, which may be due to fecal contamination of domestic water in 3 schools before the start of the school year. It is suggested to strengthen the management of centralized water supply and construction in rural areas, intensify the supervision at all levels, and sanitation and disinfection before school opens at all levels.

【Objective】 To assess the epidemiological characteristics and transmission risk of asymptomatic COVID-19 infection in Shaanxi Province. 【Methods】 A dense population database of COVID-19 cases in Shaanxi Province was constructed as of March 26, 2020, and 28 asymptomatic infected patients were selected through case epidemiological investigation report for descriptive analysis. 【Results】 In Shaanxi Province, the majority of asymptomatic COVID-19 infections were in the 20-59 years old group, and women took up a higher proportion than men. 82.14% of asymptomatic infections were found in the centralized isolation state. Nearly 80% of asymptomatic infections and confirmed cases were mainly exposed by living together in the family. The median number of days from last contact with the source of infection for all asymptomatic infected persons was 13, with 3 (10.71%) showing clinical symptoms. Epidemiological investigations showed that asymptomatic infections could spread as a result of shared family life. 【Conclusion】 At present, imported cases in Shaanxi Province continue to exist. Considering the concealed transmission of asymptomatic infections, prevention and control work is still facing challenges.

Objective:By analyzed the transmission patterns of 4 out of the 51 COVID-19 cluster cases in Shaanxi province to provide evidences for the COVID-19 control and prevention.Methods:The epidemiological data of RT-PCR test-confirmed COVID-19 cases were collected. Transmission chain was drawn and the transmission process was analyzed.Results:Cluster case 1 contained 13 cases and was caused by a family of 5 who traveled by car to Wuhan and returned to Shaanxi. Cluster case 2 had 5cases and caused by initial patient who participated family get-together right after back from Wuhan while under incubation period. Cluster case 3 contained 10 cases and could be defined as nosocomial infection. Cluster case 4 contained 4 cases and occurred in work place.Conclusion:Higher contact frequency and smaller places were more likely to cause a small-scale COVID-19 cluster outbreak, with potential longer incubation period. COVID-19 control strategies should turn the attention to infection prevention and control in crowded places, management of enterprise resumption and prevention of nosocomial infection.

Objective:To understand the incidence trend and epidemiological characteristics of COVID-19 in Shaanxi province.Methods:The incidence data of COVID-19 reported in Shaanxi as of 22 February, 2020 were collected for an epidemiological descriptive analysis.Results:A total of 245 confirmed cases of COVID-19 were reported in Shaanxi. Most cases were mild (87.76%). As time passed, the areas where confirmed cases were reported continued to increase. The case number in Xi’an was highest, accounting for nearly half of the total reported cases in the province. The epidemic pattern in Shaanxi had gradually shifted from imported case pattern to local case pattern, and the transmission of local cases was mainly based on family cluster transmission. The confirmed cases from different sources had caused the secondary transmission in Shaanxi. After February 7, the number of reported cases began to fluctuate and decrease stably, indicating a decrease-to-zero period.Conclusions:At present, the overall epidemic of COVID-19 in Shaanxi has gradually been mitigated. However, considering the approaching of return to work and study and the increasing of imported cases from other countries, the prevention and control of COVIS-19 in Shaanxi will face new challenges.

A total of 245 cases of COVID-19 in Shaanxi Province reported in the China information system for disease control and prevention as of February 24, 2020 were selected as the research objects, the cases are divided into imported cases (116 cases, 47.3%) and local cases (129 cases, 52.7%), their basic characteristics, time distribution, transmission mode, intergenerational interval and latent period transmission are analyzed. The age of local cases [(51.74±15.67) years old], female patients (69 cases, 53.5%), housework and retired staff (40 cases, 31.0%), and patients isolated at the time of onset (50 cases, 38.8%) were higher than imported cases, respectively[(40.66±15.41) years old, (45 cases, 38.8%), (21 cases, 18.1%), (17 cases, 14.6%)] ( P values were < 0.05); The infection rate was 0.8% (31/3 666) in close contacts with local cases, which was lower than imported cases 2.0% (69/3 435) ( P<0.001); The main source of infection in local cases was relatives (70 cases, 54.3%), and the main way of infection was living together and party (90 cases, 69.8%); the proportion of latent period transmission in our province was 15.5% (20 cases), and the interval between the second-generation case and the source of infection was about 4 days, and the interval between generations was about 6 days. In summary, the main way of infection of local cases in Shaanxi Province was living together and party, there were a certain proportion of latent period transmission cases at present, it's suggested that the investigation of close contacts should be started 4 days or earlier before the onset of the case.

A total of 245 cases of COVID-19 in Shaanxi Province reported in the China information system for disease control and prevention as of February 24, 2020 were selected as the research objects, the cases are divided into imported cases (116 cases, 47.3%) and local cases (129 cases, 52.7%), their basic characteristics, time distribution, transmission mode, intergenerational interval and latent period transmission are analyzed. The age of local cases [(51.74±15.67) years old], female patients (69 cases, 53.5%), housework and retired staff (40 cases, 31.0%), and patients isolated at the time of onset (50 cases, 38.8%) were higher than imported cases, respectively[(40.66±15.41) years old, (45 cases, 38.8%), (21 cases, 18.1%), (17 cases, 14.6%)] ( P values were < 0.05); The infection rate was 0.8% (31/3 666) in close contacts with local cases, which was lower than imported cases 2.0% (69/3 435) ( P<0.001); The main source of infection in local cases was relatives (70 cases, 54.3%), and the main way of infection was living together and party (90 cases, 69.8%); the proportion of latent period transmission in our province was 15.5% (20 cases), and the interval between the second-generation case and the source of infection was about 4 days, and the interval between generations was about 6 days. In summary, the main way of infection of local cases in Shaanxi Province was living together and party, there were a certain proportion of latent period transmission cases at present, it's suggested that the investigation of close contacts should be started 4 days or earlier before the onset of the case.

Objective: To understand the dynamics and epidemiological characteristics of hand, foot and mouth disease (HFMD) in Shaanxi province during 2009-2018 and provide evidence for prevention and control of HFMD. Methods: Information on HFMD was collected from the Chinese Disease Prevention and Control Information System in Shaanxi Province during 2009-2018 and was analyzed by descriptive, dynamic geometric series averaging and circular distribution methods. Results: The annual average incidence rate of HFMD was 140.04/100 000 in Shaanxi province during 2009-2018. The highest incidence rates were seen in age groups as 1-year olds (3 494.24/100 000), 2-year olds (2 734.79/100 000) and 3-year olds (2 608.58/100 000). The highest reported mortality rates appeared in: 1-year olds as 1.42/100 000, 2-year olds as 0.77/100 000) and 0-year olds (0.53/100 000). The incidence rate increased most rapidly in the 1-year olds and the 0-year olds groups. The top three incidence rates were reported in Xi’an (251.34/100 000), Weinan (161.21/100 000) and Xianyang (123.73/100 000) cities in Guanzhong area of Shaanxi province. In the whole province, incidence rate was on the rise, and the average increases of incidence rates were all greater than zero in these cities. The proportion of severe cases in most cities somehow declined. Results from the circular distribution method estimated that the peak incidence would appear in April 10-11 each year, and the high incidence season was from April to July. In 2018, the composition of enterviruses (EV) 71 was 26.47% (1 303/4 922). In 2014 to 2018, the proportion of Coxsackie virus A16 (Cox A16) was between 20.06%(753/3 753) and 23.08% (855/3 705). The proportions of other EVs increased from 6.09% (14/230) to 51.91% (2 555/4 922) during 2009-2018. Conclusions The overall incidence rate of HFMD was increasing, with high risk population appeared in children under 3 year olds, in Shaanxi province during 2009-2018. However, both mortality and fatality rates were declining, with severe cases also showing a downward trend in most of the areas. Composition of pathogens was changing over time.