Robust Institutional Support and Collaboration Between Summer Training Programs in Cancer and Biomedicine Drive the Pivot to a Virtual Format in Response to the COVID Pandemic.

Summer internships serve important roles in training the next generation of biomedical researchers and healthcare providers through laboratory and clinical experiences that excite trainees about these fields and help them make informed decisions about career paths. The SARS-CoV-2 (COVID) pandemic and associated physical distancing restrictions precluded implementation of traditional in-person summer curricula and led to the cancellation of many internships across the USA. COVID-related disruptions also created opportunities for trainees to engage in remote research, become proficient in online learning platforms, and explore multidisciplinary topics. These skills are highly relevant to trainees as virtual interfaces occupy an increasingly mainstream role in their professional paths. The response to the COVID pandemic required real-time adaptations at all levels for major biomedical institutions including the University of Maryland Baltimore (UMB). Pivoting summer programs to a virtual format as part of this response provided a "teachable moment" to expose trainees to the innovation and resilience that are essential components of the biomedical profession. UMB summer programs, which span diverse biomedical disciplines from cancer research to diabetes, consolidated resources and identified mentors with online research projects to develop a robust virtual curriculum. Herein, data from a cancer-focused internship illustrate the collaborative adaptations to established components and creation of new learning modules in the transition to, and implementation of, online training. Outcomes are presented in the context of the COVID pandemic and significant societal issues that arose in the summer of 2020. The utility of virtual components and their impact on future programs is discussed.

[CT imaging analysis of 33 cases with the 2019 novel coronavirus infection].

Objective: To explore the CT imaging features of the 2019 novel coronavirus (2019-nCoV) infection in order to summarize the imaging characteristics of the disease and improve the ability of imaging diagnosis and early diagnosis of the disease. Methods: From January 13, 2020 to January 31, 2020, a total of 33 patients with 2019-nCoV infection diagnosed and treated by Suzhou Fifth People's Hospital were analyzed retrospectively, including 20 males and 13 females, with an average age of (50±12) years, ranging from 20 to 70 years old. There were 3 cases of mild type, 27 cases of common type and 3 cases of severe type.There were 2 cases with hypertension, 1 case with postoperative lung,1 case with diabetes, 1 case with chronic bronchitis, and 1 case with bronchiectasis.SPSS25.0 Chi-square test was used to analyze the distribution of lesions in each lung lobe; SPSS25.0 Spearman correlation coefficient was used to analyze the image score and clinical classification. Results: There were 3 cases (9.1%) with normal lung and 30 cases (90.9%) with Novel Coronavirus Pneumonia(COVID-19) of the 2019-nCoV infected patients. In the distribution of COVID-19, 29 cases (87.9%) were involved in bilateral lung and 1 case (3.0%) in unilateral lung. There was no statistically significant difference in the distribution of lesions in each lobe. The correlation coefficient between the degree of lesion distribution and clinical classification was 0.819, and the two were highly correlated.There were 30 cases (90.9%) with subpleural lesions, 17 cases (51.5%) with central lesions. There were many kinds of lesions, 25 cases (75.8%) had ground glass density shadow, 16 cases (48.5%) had consolidation, 12 cases (36.4%) had interstitial change, and 18 cases (54.5%) had interlobular septal thickening. Among the 22 cases, 10 cases had more lesions, 6 cases had no changes and 6 cases had less lesions. Conclusion: Most of the patients with 2019-nCoV infection have pulmonary inflammation.CT manifestations include multiple parts, subpleural area or middle and lateral field of lung, ground glass shadow and consolidation, or coexistence. Some cases have pleural thickening or interlobular septal thickening. CT images can indicate the diagnosis of COVID-19 and provide important basis for early detection and disease monitoring.