Purpose: The SARS-CoV-2 pandemic has drastically disrupted radiology in-person education. The purpose of this study was to assess the implementation of a virtual teaching method using available technology and its role in the continuity of education of practicing radiologists and trainees during the pandemic. Methods: The authors created the Online Liver Imaging Course (OLIC) that comprised 28 online comprehensive lectures delivered in realtime and on-demand over six weeks. Radiologists and radiology trainees were asked to register to attend the live sessions. At the end of the course, we conducted a 46-question survey among registrants addressing their training level, perception of virtual conferencing, and evaluation of the course content. Results: One thousand four hundred and thirty four radiologists and trainees completed interest sign up forms before the start of the course with the first webinar having the highest number of live attendees (343 people). On average, there were 89 live participants per session and 750 YouTube views per recording (as of July 9, 2020). After the end of the course, 487 attendees from 37 countries responded to the postcourse survey for an overall response rate of (33%). Approximately (63%) of participants were practicing radiologists while (37%) were either fellows or residents and rarely medical students. The overwhelming majority (97%) found the OLIC webinar series to be beneficial. Essentially all attendees felt that the webinar sessions met (43%) or exceeded (57%) their expectations. When asked about their perception of virtual conferences after attending OLIC lectures, almost all attendees (99%) enjoyed the virtual conference with a majority (61%) of the respondents who enjoyed the virtual format more than in-person conferences, while (38%) enjoyed the webinar format but preferred in-person conferences. When asked about the willingness to attend virtual webinars in the future, (84%) said that they would attend future virtual conferences even if in-person conferences resume while (15%) were unsure. Conclusion: The success of the OLIC, attributed to many factors, indicates that videoconferencing technology provides an inexpensive alternative to in-person radiology conferences. The positive responses to our postcourse survey suggest that virtual education will remain to stay. Educational institutions and scientific societies should foster such models.

A library of novel regioselective 1,4-di and 1,4,5-trisubstituted-1,2,3-triazole based benzothiazole-piperazine conjugates were designed and synthesized using the click synthesis approach in the presence and absence of the Cu(I) catalyst. Some of these 1,2,3-triazole hybrids possess in their structures different heterocyclic scaffold including 1,2,4-triazole, benzothiazole, isatin and/or benzimidazole. The newly designed 1,2,3-triazole hybrids were assessed for their antiproliferative inhibition potency against four selected human cancer cell lines (MCF7, T47D, HCT116 and Caco2). The majority of the synthesized compounds demonstrated moderate to potent activity against all the cancer cell lines examined. Further, we have established a structure activity relationship with respect to the in silico analysis of ADME (adsorption, distribution, metabolism and excretion) analysis and found good agreement with in vitro activity.

PURPOSE Variability in computed tomography images intrinsic to individual scanners limits the application of radiomics in clinical and research settings. The development of reproducible and generalizable radiomics-based models to assess lesions requires harmonization of data. The purpose of this study was to develop, test, and analyze the efficacy of a radiomics data harmonization model. MATERIALS AND METHODS Radiomic features from biopsy-proven untreated hepatic metastasis (N = 380) acquired from 167 unique patients with pancreatic, colon, and breast cancers were analyzed. Radiomic features from volume-match 551 samples of normal liver tissue and 188 hepatic cysts were included as references. A novel linear mixed effect model was used to identify effects associated with lesion size, tissue type, and scanner model. Six separate machine learning models were then used to test the effectiveness of radiomic feature harmonization using multivariate analysis. RESULTS Proposed model identifies and removes scanner-associated effects while preserving cancer-specific functional dependence of radiomic features on the tumor size. Data harmonization improves the performance of classification models by reducing the scanner-associated variability. For example, the multiclass logistic regression model, LogitBoost, demonstrated the improvement in sensitivity in the range from 15% to 40% for each type of liver metastasis, whereas the overall model accuracy and the kappa coefficient increased by 5% and 8% accordingly. CONCLUSION The model removed scanner-associated effects while preserving cancer-specific functional dependence of radiomic features.

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Due to a great demand of new anticancer agents, novel series of phtalonitrile‐bis(1,2,3‐triazoles) appended with different functionalities were synthesized and characterized by FTIR, 1H NMR, 13C NMR and mass spectroscopy techniques. These were also screened for DNA binding, docking and anticancer activities. The DNA binding constants were in the range of 1.33×105 to 12.60×105 M−1; indicating strong binding affinity. The maximum anticancer activity was 79 % in A549 and H1299 lung cancer cell lines. The docking study suggested good interactions of the reported molecules with DNA through hydrogen bonding and hydrophobic interactions. All these results confirmed that the reported molecules have good anticancer activities. Therefore, these 1,2,3‐triazole scaffolds may be promising molecules as potential anticancer candidates in the future.