Objective : To study the epidemiological characteristics of coronavirus disease 2019 （COVID-19） in Zhoushan, so as to provide reference for improving the prevention and control capability of COVID-19. Methods : All the confirmed cases of COVID-19 in Zhoushan, diagnosed according to China’s “COVID-19 diagnosis and treatment plan （fifth version） ” and reported from January 19 to February 17, 2020, were extracted from the infectious disease surveillance system. Data of general information, clinical characteristics, laboratory Results, transmission and detection routes were collected and analyzed. Results : By February 17, Ten confirmed cases of COVID-19 in Zhoushan had been reported, including 7 males and 3 females. They were all adults, with an average age of （50.90±15.00） years. Five cases were discharged. The incubation period ranged from 2 to 12 days, with a median of 5 days. The first symptoms were fever （8 cases）, cough （7 cases） and muscle pain （2 cases）. Chest computed tomographic （CT） scans showed ground glass opacities in the lungs of all the cases. Six cases had Wuhan related exposure. SARS-CoV-2 was tested positive in the sputum specimens or throat swabs of all the cases and the faeces of 4 cases. The last suspicious exposure of 5 cases occurred before, and that of another 5 cases occurred after the onset of clinical symptoms in the confirmed maternal cases. Three cases were found in active consultation after clinical symptoms, and another 7 cases were found in the monitoring of close contacts. Conclusions The 10 confirmed cases of COVID-19 reported in Zhoushan are all adults, and most have Wuhan related exposure. SARS-CoV-2 can be detected in the fecal samples, but the existence of fecal-oral transmission needs more research. SARS-CoV-2 has strong infectivity, and may also have infectivity before the onset of symptoms （at the end of incubation period）. Isolation and early detection of close contacts are conducive for early case-finding.

Through the reform and practice of the "four-in-one" cultivation model of clinical medical talents, the training mode of applied high-quality medical and health talents with different orientations is established, and the curriculum teaching system suitable for the development of modern medical education is constructed to promote the reform of education and teaching. It solves the problems of single medical talents training mode, fragmentation of curriculum system, single teaching and training in teaching, and insufficient support for talent training. This reform established a set of curriculum system, teaching methods and evaluation methods to strengthen the cultivation of medical students' post competency, and achieved the goal of improving the quality of clinical medical personnel training in local medical colleges.

Objective:To investigate the value of intratumoral and peritumoral radiomics features of multi-parameter MRI in evaluation of the status of human epithelial growth factor receptor 2 in breast cancer.Methods:The clinical, pathological and imaging data of 340 patients with pathologically confirmed breast cancer in Henan Provincial People′s Hospital from September 2019 to December 2020 were retrospectively collected. All patients were female, 48 (42, 55) years old. All patients underwent multi-parameter breast MRI before surgery, including dynamic contrast-enhanced T 1WI (DCE-T 1WI), fat-suppressed T 2WI (T 2WI) and diffusion-weighted imaging (DWI). The region of interest (ROI) for lesions were manually delineated and the segmented ROIs were zoomed in ring shape by 4 mm to acquire ROI intra and ROI prei, respectively. Then six sets of radiomics features were extracted from ROI intra and ROI prei of DCE-T 1WI, T 2WI and DWI. The cases were divided into a training set (272 cases) and a test set (68 cases) by stratified sampling at a ratio of 4∶1. The Mann-Whitney U test, Select K Best and minimum absolute contraction and selection operator were used for feature selection of the 6 sets of radiomics features. The feature subsets after reduction were used to construct independent and combined radiomics signatures with support vector machine algorithm to predict the HER2 status of breast cancer. Receiver operating characteristic curve was generated and area under curve (AUC) was calculated to compare the prediction performance of different models. Results:Of the 340 patients, 80 were HER2-positive and 260 were HER2-negative. Among the radiomics signatures based on single sequence, the DWI peri showed the best performance in predicting HER2 status of breast cancer, with an AUC of 0.678 for the test set. Among the combination of intratumoral and peritumoral radiomics signatures based on same sequence, the DWI intra+DWI peri had the highest prediction value, achieving an AUC of 0.774 for the testing set. Among the intratumoral or peritumoral radiomics signatures derived from two different sequences, the DCE-T 1WI intra+DWI intra and T 2WI peri+DWI peri showed the best predictive performance, yielding AUC of 0.766 and 0.769 in the testing set, respectively. Among the combination of intratumoral or peritumoral radiomics signatures derived from all 3 sequences or combinations of all features, the DCE-T 1WI intra+T 2WI intra+DWI intra+DCE-T 1WI peri+T 2WI peri+DWI peri obtained the highest prediction efficiency, with an AUC of 0.913 for the testing set. Conclusion:The radiomics features of intratumoral and peritumoral regions based on multi-parameter MRI have a certain value in non-invasive evaluation of HER2 status of breast cancer, which can help clinicians to provide scientific basis for decision-making of targeted therapy in patients with breast cancer.