Purpose: The study is to describe the clinical characteristics, outcomes and follow-up of cancer patients with COVID-19. Methods: Clinical records, demographic data, signs and symptoms, laboratory results, cytokine pro les, chest CT scans, comorbidities, treatments, clinical outcomes, and RT-PCR of SARS-CoV-2 after discharge were retrospectively collected for fty-six cancer patients with laboratory-con rmed COVID-19 pneumonia who were admitted to

Objective: To identify predictors of pulmonary fibrosis development by combining follow-up thin-section CT findings and clinical features in patients discharged after treatment for COVID-19. Materials and Methods: This retrospective study involved 32 confirmed COVID-19 patients who were divided into two groups according to the evidence of fibrosis on their latest follow-up CT imaging. Clinical data and CT imaging features of all the patients in different stages were collected and analyzed for comparison. Results: The latest follow-up CT imaging showed fibrosis in 14 patients (male, 12; female, 2) and no fibrosis in 18 patients (male, 10; female, 8). Compared with the non-fibrosis group, the fibrosis group was older (median age: 54.0 years vs. 37.0 years, p = 0.008), and the median levels of C-reactive protein (53.4 mg/L vs. 10.0 mg/L, p = 0.002) and interleukin-6 (79.7 pg/L vs. 11.2 pg/L, p = 0.04) were also higher. The fibrosis group had a longer-term of hospitalization (19.5 days vs. 10.0 days, p = 0.001), pulsed steroid therapy (11.0 days vs. 5.0 days, p < 0.001), and antiviral therapy (12.0 days vs. 6.5 days, p = 0.012). More patients on the worst-state CT scan had an irregular interface (59.4% vs. 34.4%, p = 0.045) and a parenchymal band (71.9% vs. 28.1%, p < 0.001). On initial CT imaging, the irregular interface (57.1%) and parenchymal band (50.0%) were more common in the fibrosis group. On the worst-state CT imaging, interstitial thickening (78.6%), air bronchogram (57.1%), irregular interface (85.7%), coarse reticular pattern (28.6%), parenchymal band (92.9%), and pleural effusion (42.9%) were more common in the fibrosis group. Conclusion: Fibrosis was more likely to develop in patients with severe clinical conditions, especially in patients with high inflammatory indicators. Interstitial thickening, irregular interface, coarse reticular pattern, and parenchymal band manifested in the process of the disease may be predictors of pulmonary fibrosis. Irregular interface and parenchymal band could predict the formation of pulmonary fibrosis early.

These authors contributed equally to this work. ⇤ Corresponding authors.The sudden outbreak of novel coronavirus 2019 (COVID-19) increased the diagnostic burden of radiologists. In the time of an epidemic crisis, we hoped artificial intelligence (AI) to help reduce physician workload in regions with the outbreak, and improve the diagnosis accuracy for physicians before they could acquire enough experience with the new disease. Here, we present our experience in building and deploying an AI system that automatically analyzes CT images to detect COVID-19 pneumonia features. Different from conventional medical AI, we were dealing with an epidemic crisis. Working in an interdisciplinary team of over 30 people with medical and / or AI background, geographically distributed in Beijing and Wuhan, we were able to overcome a series of challenges in this particular situation and deploy the system in four weeks. Using 1,136 training cases (723 positives for COVID-19) from five hospitals, we were able to achieve a sensitivity of 0.974 and specificity of 0.922 on the test dataset, which included a variety of pulmonary diseases. Besides, the system automatically highlighted all lesion regions for faster examination. As of today, we have deployed the system 2 All rights reserved. No reuse allowed without permission.

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Fusion of the outer mitochondrial membrane is mediated by the dynamin-like GTPase mitofusin (MFN). Here, we determined the structure of the minimal GTPase domain (MGD) of human MFN1 in complex with GDP-BeF. The MGD folds into a canonical GTPase fold with an associating four-helix bundle, HB1, and forms a dimer. A potassium ion in the catalytic core engages GDP and BeF (GDP-BeF). Enzymatic analysis has confirmed that efficient GTP hydrolysis by MFN1 requires potassium. Compared to previously reported MGD structures, the HB1 structure undergoes a major conformational change relative to the GTPase domains, as they move from pointing in opposite directions to point in the same direction, suggesting that a swing of the four-helix bundle can pull tethered membranes closer to achieve fusion. The proposed model is supported by results from in vitro biochemical assays and mitochondria morphology rescue assays in MFN1-deleted cells. These findings offer an explanation for how Charcot-Marie-Tooth neuropathy type 2 A (CMT2A)-causing mutations compromise MFN-mediated fusion.