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.

Porcine circovirus type 3 (PCV3) was detected in Shandong, China. One hundred and thirty-two of 222 (59.46%) samples were PCV3 positive, while 52 of 132 (39.39%) samples were co-infected with PCV2. There were no clinical signs of infection in either multiparous sows or live-born infants. Two strains of PCV3 were indentified from natural stillborn foetuses. Phylogenetic analysis showed the two strains of PCV3 are 96% identical to the known PCV3/Pig/USA (KX778720.1, KX966193.1 and KX898030.1) and closely related to Barbel Circovirus. Further studies of the epidemiology of PCV3 and the co-infection with PCV2 are needed.

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Foot-and-mouth disease virus (FMDV) causes a highly contagious, debilitating disease in cloven-Further mechanistic studies demonstrated that 3C pro induced proteasome-and caspase-independent protein degradation of karyopherin ␣1 (KPNA1), the nuclear localization signal receptor for tyrosine-phosphorylated STAT1, but not karyopherin ␣2, ␣3, or ␣4. Finally, we showed that the protease activity of 3C pro contributed to the degradation of KPNA1 and thus blocked STAT1/STAT2 nuclear translocation. Taken together, results of our experiments describe for the first time a novel mechanism by which FMDV evolves to inhibit IFN signaling and counteract host innate antiviral responses. IMPORTANCE We show that 3Cpro of FMDV antagonizes the JAK-STAT signaling pathway by blocking STAT1/STAT2 nuclear translocation. Furthermore, 3C pro induces KPNA1 degradation, which is independent of proteasome and caspase pathways. The protease activity of 3C pro contributes to the degradation of KPNA1 and governs the ability of 3C pro to inhibit the JAK-STAT signaling pathway. This study uncovers a novel mechanism evolved by FMDV to antagonize host innate immune responses.

Background SARS-CoV-2 has spread worldwide and has the ability to damage multiple organs. However, information on serum SARS-CoV-2 nucleic acid(RNAemia) in patients affected by COVID-19 is limited. Methods Patients who admitted to Zhongnan Hospital of Wuhan University with laboratory-confirmed COVID-19, were tested SARS-COV-2 RNA in serum from January 28, 2020, to February 9, 2020. Demographic data, laboratory findings, radiological, comorbidities and outcomes data were collected and analyzed. Results 85 patients were included in the analysis. The viral load of throat swabs was significantly higher than serum samples. The highest detection of SARS-CoV-2 RNA in serum samples was between 11 to 15 days after the symptom onset. Analysis to compare with and without RNAemia provided evidence that CT and some laboratory biomarkers(total protein, BUN, LDH, hypersensitive troponin I and D-dimer) were abnormal, and that the extent of these abnormalities was generally higher in RNAemia than in non-RNAemia. Organ damages(respiratory failure, cardiac damage, renal damage and coagulopathy) were more common in RNAemia than non-RNAemia. Patients with vs without RNAemia had shorter durations from serum testing SARS-CoV-2 RNA. The mortality rate was higher among patients with vs without RNAemia. Conclusions This study provides evidence to support that SARS-CoV-2 may have an important role in multiple organ damage, such as respiratory failure, cardiac damage, renal damage and coagulopathy. We did not find strong evidence that SARS-CoV-2 plays a role in damage of liver and the central nervous system. And our evidence suggests that RNAemia has a significant association with a higher risk of in-hospital mortality.