Effects of 2019 Novel Coronavirus on Male Reproductive System: A Retrospective Study (preprint)

A novel and highly pathogenic coronavirus (2019-nCoV)-induced pneumonia spread worldwide in a short time. However, studies on the effects of 2019-nCoV on the male reproductive system are limited. The aim of this study is to describe the clinical characteristics of the male reproductive system of COVID-19 patients and to explore the presence of 2019-nCoV in semen. Retrospective, single-center case series of 112 male patients with confirmed COVID-19 who were admitted to Renmin Hospital of Wuhan University from January 2 to March 7, 2020. Demographic data, symptoms and signs related to the male reproductive system, throat swabs and semen samples were collected and analyzed. 2019-nCoV RNA measured in throat swab and semen samples. The organ distribution of ACE2 mRNA and protein in human tissue on The Human Protein Atlas portal and investigated immunohistochemistry (IHC) images of the testis. The HPA dataset revealed relatively high levels of ACE2 protein and RNA expression in the testis. A total of 3 severe COVID-19 patients (2.7%) presented with orchidoptosis, while no patients experienced other symptoms or signs related to the male reproductive system. The analysis of 2019-nCoV RNA in semen included 17 patients with fertility needs. Among these patients, 9 (52.9%) remained positive for 2019-nCoV according to throat swab analysis, and 8 (47.1%) became negative. In the semen 2019-nCoV analysis, all 17 patients were negative for the N gene and ORF1ab gene. In view of the potential impairment, long-term follow-up for male COVID-19 patients with fertility needs is of great significance.

Immunodepletion with Hypoxemia: A Potential High Risk Subtype of Coronavirus Disease 2019 (preprint)

Background The outbreak of COVID-2019 is becoming a global public health emergency. Although its basic clinical features have been reported, the dynamic characteristics of immune system in COVID-2019 patients, especially those critical patients with refractory hypoxemia, are not yet well understood. We aim to describe the dynamic characteristics of immune system in 3 critical patients with refractory hypoxemia, and discuss the relationship between hypoxemia severity and immune cell levels, and the changes of gut microbes of COVID-2019 patient. Methods This is a retrospective study from 3 patients with 2019-nCoV infection admitted to Renmin Hospital of Wuhan University, a COVID-2019 designated hospital in Wuhan, from January 31 to February 6, 2020. All patients were diagnosed and classified based on the Diagnosis and Treatment of New Coronavirus Pneumonia (6th edition) published by the National Health Commission of China4. We recorded the epidemiological history, demographic features, clinical characteristics, symptoms and signs, treatment and clinical outcome in detail. Blood samples were collected and we determined the expression levels of immune cells (CD3+ T cells, CD4+ T cells, CD8+ T cells, CD19+ B cells, and CD16+56+ NK cells) in different time points. Nanopore Targeted Sequencing was used to determine the alterations of gut microbiota homeostasis. Results Apart from the clinical features described previously4, we found that four patients had decreased immune cells and refractory hypoxemia during the hospitalization, and the severity of hypoxemia was strongly correlated to the expression levels of immune cells. Additionally, we found that the proportion of probiotics was significantly reduced, such as Bifidobacterium, Lactobacillus, and Eubacterium, and the proportion of conditioned pathogenic bacteria was significantly increased, such as Corynebacterium of Actinobacteria and Ruthenibacterium of Firmicutes. Notably, all patients died. Conclusions We discussed the dynamic characteristics of host immune system and the imbalance of gut microbiota in 3 critical patients with COVID-2019. Hypoxemia severity was closely related with host immune cell levels, and the vicious circle between immune disorder and gut microbiota imbalance may be a high risk of fatal pneumonia. To the best of our knowledge, this is the first study which revealing that immunodepletion with refractory hypoxemia is a potential high risk subtype of COVID-2019 and the vicious circle between immune disorder and gut dysbiosis may be a high risk of fatal pneumonia.

Nanopore target sequencing for accurate and comprehensive detection of SARS-CoV-2 and other respiratory viruses (preprint)

The ongoing novel coronavirus pneumonia COVID-19 outbreak in Wuhan, China, has engendered numerous cases of infection and death. COVID-19 diagnosis relies upon nucleic acid detection; however, current recommended methods exhibit high false-negative rates, low sensitivity, and cannot identify other respiratory virus infections, thereby resulting patient misdiagnosis and impeding epidemic containment. Combining the advantages of target amplification and long-read, real-time nanopore sequencing, we developed nanopore target sequencing (NTS) to detect SARS-CoV-2 and other respiratory viruses simultaneously within 6-10 h. Parallel testing with approved qPCR kits of SARS-CoV-2 and NTS using 61 nucleic acid samples from suspected COVID-19 cases confirmed that NTS identified more infected patients as positive, and could also monitor for mutated nucleic acid sequence or other respiratory virus infection in the test sample. NTS is thus suitable for contemporary COVID-19 diagnosis; moreover, this platform can be further extended for diagnosing other viruses or pathogens.

Clinical characteristics of 82 death cases with COVID-19 (preprint)

Background A recently developing pneumonia caused by SARS-CoV-2 was originated in Wuhan, China, and has quickly spread across the world. We reported the clinical characteristics of 82 death cases with COVID-19 in a single center. Methods Clinical data on 82 death cases laboratory-confirmed as SARS-CoV-2 infection were obtained from a Wuhan local hospital's electronic medical records according to previously designed standardized data collection forms. Findings All patients were local residents of Wuhan, and the great proportion of them were diagnosed as severe illness when admitted. Most of the death cases were male (65.9%). More than half of dead patients were older than 60 years (80.5%) and the median age was 72.5 years. The bulk of death cases had comorbidity (76.8%), including hypertension (56.1%), heart disease (20.7%), diabetes (18.3%), cerebrovascular disease (12.2%), and cancer (7.3%). Respiratory failure remained the leading cause of death (69.5%), following by sepsis syndrome/MOF (28.0%), cardiac failure (14.6%), hemorrhage (6.1%), and renal failure (3.7%). Furthermore, respiratory, cardiac, hemorrhage, hepatic, and renal damage were found in 100%, 89%, 80.5%, 78.0%, and 31.7% of patients, respectively. On the admission, lymphopenia (89.2%), neutrophilia (74.3%), and thrombocytopenia (24.3%) were usually observed. Most patients had a high neutrophil-to-lymphocyte ratio of >5 (94.5%), high systemic immune-inflammation index of >500 (89.2%), increased C-reactive protein level (100%), lactate dehydrogenase (93.2%), and D-dimer (97.1%). A high level of IL-6 (>10 pg/ml) was observed in all detected patients. Median time from initial symptom to death was 15 days (IQR 11-20), and a significant association between aspartate aminotransferase (p=0.002), alanine aminotransferase (p=0.037) and time from initial symptom to death were interestingly observed. Conclusion Older males with comorbidities are more likely to develop severe disease, even die from SARS-CoV-2 infection. Respiratory failure is the main cause of COVID-19, but either virus itself or cytokine release storm mediated damage to other organ including cardiac, renal, hepatic, and hemorrhage should be taken seriously as well.

Deep learning-based model for detecting 2019 novel coronavirus pneumonia on high-resolution computed tomography: a prospective study in 27 patients (preprint)

Background: Computed tomography (CT) is the preferred imaging method for diagnosing 2019 novel coronavirus (COVID19) pneumonia. Our research aimed to construct a system based on deep learning for detecting COVID-19 pneumonia on high resolution CT, relieve working pressure of radiologists and contribute to the control of the epidemic. Methods: For model development and validation, 46,096 anonymous images from 106 admitted patients, including 51 patients of laboratory confirmed COVID-19 pneumonia and 55 control patients of other diseases in Renmin Hospital of Wuhan University (Wuhan, Hubei province, China) were retrospectively collected and processed. Twenty-seven consecutive patients undergoing CT scans in Feb, 5, 2020 in Renmin Hospital of Wuhan University were prospectively collected to evaluate and compare the efficiency of radiologists against 2019-CoV pneumonia with that of the model. Findings: The model achieved a per-patient sensitivity of 100%, specificity of 93.55%, accuracy of 95.24%, PPV of 84.62%, and NPV of 100%; a per-image sensitivity of 94.34%, specificity of 99.16%, accuracy of 98.85%, PPV of 88.37%, and NPV of 99.61% in retrospective dataset. For 27 prospective patients, the model achieved a comparable performance to that of expert radiologist. With the assistance of the model, the reading time of radiologists was greatly decreased by 65%. Conclusion: The deep learning model showed a comparable performance with expert radiologist, and greatly improve the efficiency of radiologists in clinical practice. It holds great potential to relieve the pressure of frontline radiologists, improve early diagnosis, isolation and treatment, and thus contribute to the control of the epidemic.