Huazhong University of Science and Technology

About: Huazhong University of Science and Technology is a education organization based out in Wuhan, China. It is known for research contribution in the topics: Population & Computer science. The organization has 120339 authors who have published 122521 publications receiving 2168040 citations. The organization is also known as: Central China University of Science and Technology.

Neurologic Manifestations of Hospitalized Patients With Coronavirus Disease 2019 in Wuhan, China.

Abstract: Importance The outbreak of coronavirus disease 2019 (COVID-19) in Wuhan, China, is serious and has the potential to become an epidemic worldwide. Several studies have described typical clinical manifestations including fever, cough, diarrhea, and fatigue. However, to our knowledge, it has not been reported that patients with COVID-19 had any neurologic manifestations. Objective To study the neurologic manifestations of patients with COVID-19. Design, Setting, and Participants This is a retrospective, observational case series. Data were collected from January 16, 2020, to February 19, 2020, at 3 designated special care centers for COVID-19 (Main District, West Branch, and Tumor Center) of the Union Hospital of Huazhong University of Science and Technology in Wuhan, China. The study included 214 consecutive hospitalized patients with laboratory-confirmed diagnosis of severe acute respiratory syndrome coronavirus 2 infection. Main Outcomes and Measures Clinical data were extracted from electronic medical records, and data of all neurologic symptoms were checked by 2 trained neurologists. Neurologic manifestations fell into 3 categories: central nervous system manifestations (dizziness, headache, impaired consciousness, acute cerebrovascular disease, ataxia, and seizure), peripheral nervous system manifestations (taste impairment, smell impairment, vision impairment, and nerve pain), and skeletal muscular injury manifestations. Results Of 214 patients (mean [SD] age, 52.7 [15.5] years; 87 men [40.7%]) with COVID-19, 126 patients (58.9%) had nonsevere infection and 88 patients (41.1%) had severe infection according to their respiratory status. Overall, 78 patients (36.4%) had neurologic manifestations. Compared with patients with nonsevere infection, patients with severe infection were older, had more underlying disorders, especially hypertension, and showed fewer typical symptoms of COVID-19, such as fever and cough. Patients with more severe infection had neurologic manifestations, such as acute cerebrovascular diseases (5 [5.7%] vs 1 [0.8%]), impaired consciousness (13 [14.8%] vs 3 [2.4%]), and skeletal muscle injury (17 [19.3%] vs 6 [4.8%]). Conclusions and Relevance Patients with COVID-19 commonly have neurologic manifestations. During the epidemic period of COVID-19, when seeing patients with neurologic manifestations, clinicians should suspect severe acute respiratory syndrome coronavirus 2 infection as a differential diagnosis to avoid delayed diagnosis or misdiagnosis and lose the chance to treat and prevent further transmission.

Correlation of Chest CT and RT-PCR Testing for Coronavirus Disease 2019 (COVID-19) in China: A Report of 1014 Cases.

Abstract: Chest CT had higher sensitivity for diagnosis of COVID-19 as compared with initial reverse-transcription polymerase chain reaction from swab samples in the epidemic area of China.

Guidelines for the use and interpretation of assays for monitoring autophagy

Abstract: In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. A key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process vs. those that measure flux through the autophagy pathway (i.e., the complete process); thus, a block in macroautophagy that results in autophagosome accumulation needs to be differentiated from stimuli that result in increased autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field.

Clinical predictors of mortality due to COVID-19 based on an analysis of data of 150 patients from Wuhan, China.

Abstract: Dear Editor, The rapid emergence of COVID-19 in Wuhan city, Hubei Province, China, has resulted in thousands of deaths [1]. Many infected patients, however, presented mild flu-like symptoms and quickly recover [2]. To effectively prioritize resources for patients with the highest risk, we identified clinical predictors of mild and severe patient outcomes. Using the database of Jin Yin-tan Hospital and Tongji Hospital, we conducted a retrospective multicenter study of 68 death cases (68/150, 45%) and 82 discharged cases (82/150, 55%) with laboratory-confirmed infection of SARS-CoV-2. Patients met the discharge criteria if they had no fever for at least 3 days, significantly improved respiratory function, and had negative SARS-CoV-2 laboratory test results twice in succession. Case data included demographics, clinical characteristics, laboratory results, treatment options and outcomes. For statistical analysis, we represented continuous measurements as means (SDs) or as medians (IQRs) which compared with Student’s t test or the Mann–Whitney–Wilcoxon test. Categorical variables were expressed as numbers (%) and compared by the χ2 test or Fisher’s exact test. The distribution of the enrolled patients’ age is shown in Fig. 1a. There was a significant difference in age between the death group and the discharge group (p < 0.001) but no difference in the sex ratio (p = 0.43). A total of 63% (43/68) of patients in the death group and 41% (34/82) in the discharge group had underlying diseases (p = 0.0069). It should be noted that patients with cardiovascular diseases have a significantly increased risk of death when they are infected with SARS-CoV-2 (p < 0.001). A total of 16% (11/68) of the patients in the death group had secondary infections, and 1% (1/82) of the patients in the discharge group had secondary infections (p = 0.0018). Laboratory results showed that there were significant differences in white blood cell counts, absolute values of lymphocytes, platelets, albumin, total bilirubin, blood urea nitrogen, blood creatinine, myoglobin, cardiac troponin, C-reactive protein (CRP) and interleukin-6 (IL-6) between the two groups (Fig. 1b and Supplementary Table 1). The survival times of the enrolled patients in the death group were analyzed. The distribution of survival time from disease onset to death showed two peaks, with the first one at approximately 14 days (22 cases) and the second one at approximately 22 days (17 cases) (Fig. 1c). An analysis of the cause of death was performed. Among the 68 fatal cases, 36 patients (53%) died of respiratory failure, five patients (7%) with myocardial damage died of circulatory failure, 22 patients (33%) died of both, and five remaining died of an unknown cause (Fig. 1d). Based on the analysis of the clinical data, we confirmed that some patients died of fulminant myocarditis. In this study, we first reported that the infection of SARS-CoV-2 may cause fulminant myocarditis. Given that fulminant myocarditis is characterized by a rapid progress and a severe state of illness [3], our results should alert physicians to pay attention not only to the symptoms of respiratory dysfunction but also the symptoms of cardiac injury. *Correspondence: songsingsjx@sina.com 4 Department of Infectious Diseases, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan 430030, Hubei, China Full author information is available at the end of the article