Search

Background Since December 2019, coronavirus disease 2019 (COVID-19), caused by severe adult respiratory syndrome coronavirus 2, occurred in Wuhan, and rapidly spread throughout China. This study aimed to clarify the characteristics of patients with refractory COVID-19. Methods In this retrospective single-center study, we included 155 consecutive patients with confirmed COVID-19 in Zhongnan Hospital of Wuhan University from 1 January to 5 February. The cases were divided into general and refractory COVID-19 groups according to the clinical efficacy of treatment after hospitalization, and the differences between groups were compared. Results Compared with patients with general COVID-19 (45.2%), those with refractory disease were older, were more likely to be male, and had more underlying comorbid conditions, a lower incidence of fever, higher maximum temperatures among patients with fever, higher incidences of shortness of breath and anorexia, more severe disease assessment at admission, higher neutrophil, aspartate aminotransferase, lactate dehydrogenase, and C-reactive protein levels, lower platelet counts and albumin levels, and higher incidences of bilateral pneumonia and pleural effusion (P <.05). Patients with refractory COVID-19 were more likely to receive oxygen, mechanical ventilation, expectorant, and adjunctive treatment, including corticosteroids, antiviral drugs, and immune enhancers (P <.05). Considering the factors of disease severity at admission, mechanical ventilation, and intensive care unit transfer, patients with refractory COVID-19 were also more likely to be male, have manifestations of anorexia on admission, and receive oxygen, expectorant, and adjunctive agents (P <.05). Conclusion In nearly 50% of patients with COVID-19 obvious clinical and radiological remission was not achieved within 10 days after hospitalization. Male, anorexia, and no fever at admission was predictive of poor treatment efficacy. [ABSTRACT FROM AUTHOR]

The poor outcomes in advanced non‐small‐cell lung cancer (NSCLC) necessitate new treatments. Recent studies emphasize anisomycin as a promising anti‐cancer drug candidate. In this work, we systematically investigated the efficacy of anisomycin alone and its combination with the standard‐of‐care drugs in NSCLC. We showed that anisomycin inhibited growth, migration, and survival in NSCLC cells regardless of genetic mutation status, and to a greater extent than in normal lung epithelial cells. Isobologram analysis showed that the combination of anisomycin with cisplatin, paclitaxel, or gefitinib was synergistic in NSCLC but not normal lung cells. We further demonstrated that anisomycin inhibited NSCLC growth in mice. The combination of anisomycin with cisplatin was more effective than cisplatin alone and completely arrested NSCLC growth throughout the whole duration of treatment. JNK and p38 MAPK were not required for anisomycin's action. In contrast, anisomycin inhibits PI3K/Akt/mTOR pathway. Overexpression of constitutively active Akt reversed the pro‐apoptotic effect of anisomycin. Our work demonstrates the selective anti‐NSCLC activity of anisomycin via suppressing PI3K/Akt/mTOR. Our findings provide preclinical evidence to initialize the clinical trial of using anisomycin to sensitize NSCLC to current therapy. [ABSTRACT FROM AUTHOR]

To describe the radiological features of coronavirus disease 19 (COVID-19) and to explore the significant signs that indicate severity of disease. We collected data retrospectively of 180 cases of COVID-19, from 15 January 2020 to 31 March 2020, from both the Wuhan Zhongnan and Beijing Ditan Hospitals, including 103 cases of mild and 77 cases of severe pneumonia. All patients had their first chest computed tomography scan within five days of symptom onset. The dandelion sign was defined by a focal ground glass opacity (GGO) with a central thickening of the airway wall, and the focal crazy paving sign was defined by a focal GGO with thickening of the interlobular septa. Consolidation presented in only 4.9% (5/103) of the mild pneumonia cases, which was significantly lower than that in severe pneumonia cases (70.1% 54/77), p <.001). Multifocal distribution and pure GGOs were observed more frequently in severe cases of pneumonia (p <.05). The dandelion sign was present in 86.4% (89/103) of the mild pneumonia cases, significantly more frequent than those with severe pneumonia (13.0% [10/77], p <.001). The focal crazy paving sign presented in 65.0% (67/103) of the mild pneumonia cases and was significantly more frequent than in severe cases (23.4% [18/77], p <.001). The hospital stay duration of the mild pneumonia group (13.6 ± 7.2 days) was significantly shorter than the severe pneumonia group (26.6 ± 11.7 days, p <.001) Consolidation, pure GGO and multifocal distribution on a CT scan were associated with severe COVID-19. The dandelion and focal crazy paving signs indicate mild COVID-19. [ABSTRACT FROM AUTHOR]

Background: Globally, there have been many cases of coronavirus disease 2019 (COVID-19) among medical staff; however, the main factors associated with the infection are not well understood.Aim: To identify the super-factors causing COVID-19 infection in medical staff in China.Methods: A cross-sectional study was conducted between January 1st and February 30th, 2020, in which front-line members of medical staff who took part in the care and treatment of patients with COVID-19 were enrolled. Epidemiological and demographic data between infected and uninfected groups were collected and compared. Social network analysis (SNA) was used to establish socio-metric social links between influencing factors.Findings: A total of 92 medical staff were enrolled. In all participant groups, the super-factor identified by the network was wearing a medical protective mask or surgical mask correctly (degree: 572; closeness: 25; betweenness centrality: 3.23). Touching the cheek, nose, and mouth while working was the super-factor in the infected group. This was the biggest node in the network and had the strongest influence (degree: 370; closeness: 29; betweenness centrality: 0.37). Self-protection score was the super-factor in the uninfected group but was the isolated factor in the infected group (degree: 201; closeness: 28; betweenness centrality: 5.64). For family members, the exposure history to Huanan Seafood Wholesale Market and the contact history to wild animals were two isolated nodes.Conclusion: High self-protection score was the main factor that prevented medical staff from contracting COVID-19 infection. The main factor contributing to COVID-19 infections among medical staff was touching the cheek, nose, and mouth while working. [ABSTRACT FROM AUTHOR]

Purpose: The aim of the study was to describe the use of masks among health care personnel (HCP) exposed to index cases of coronavirus disease 2019 (COVID-19), and to evaluate any association with infection rate.Methods: We did a retrospective, observational study of HCP at Zhongnan Hospital of Wuhan University for the management of COVID-19 (before person-to-person transmission was official confirmed, no additional protection was provided). A questionnaire was given to all staff listed on the roster in the clinical regions providing care for index patients with COVID-19. All participants were surveyed regarding hand-washing and use of surgical masks and gloves and were tested for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Data were analysed (Student's t test and Pearson χ2 test) for an association between infection and use of personal protective equipment.Results: Exposure of a total of 299 non-infected and 30 infected staff was confirmed. None of the 149 staff who reported use of all three preventative measures (hand-washing and use of gloves and masks) became infect-ed. In contrast, all 30 of the staff who became infected had omitted at least one of the measures. Fewer staff who wore surgical masks (P=0.000003) became infected compared with those who did not. Infections rates were significantly lower in HCP from the internal medicine departments, as these personnel generally wore masks.Conclusion: An association was found between SARS-CoV-2 infection of HCP and the non-use of masks when working with index cases in clinical settings. We recommend that all HCP follow the strict instructions for prevention and treatment of nosocomial infection during intimate contact with COVID-19, especially staff from surgical departments. [ABSTRACT FROM AUTHOR]

Background: Smoking participates in pathogenesis of lung cancer. Long non-coding RNAs (lncRNAs) play some specific roles during development of lung cancers., Objective: To investigate effects of smoking on lncRNA alterations in lung cancer., Methods: There are 522 lung adenocarcinoma (LUAD) and 504 lung squamous cell carcinoma (LUSC) participants. Clinical and lncRNA genetic data were downloaded from The Cancer Genome Atlas (TCGA) database. LncRNA alterations were analyzed in lung cancer patients. Smoking category and packs were evaluated. Correlations between smoking and LncRNA alterations were analyzed. Kaplan-Meier analysis was performed to determine overall survival and disease free survival., Results: There are more non-smokers in LUSC than in LUAD. In both LUAD and LUSC, smoking could increase total mutation counts and fraction of copy number alterations. Smoking index positively correlated with total mutations in LUAD, but not in LUSC. Smoking could trigger lncRNA alterations both in LUAD and LUSC. Smoking regulated different lncRNA between male and female. EXOC3-AS1 and LINC00603 alterations were positively correlated with smoking index in male LUAD smokers. In female LUAD smokers, smoking index was positively correlated with SNHG15, TP53TG1 and LINC01600 and negatively with LINC00609 and PTCSC3. In both male and female LUSC patients, smoking increased or decreased several lncRNA alterations. DGCR5 alteration increased in male LUSC than in female LUSC patients. In female LUSC patients, LOH12CR2 alteration was positively correlated with smoking index., Conclusion: Smoking promoted LUAD and LUSC development by affecting different lncRNA alterations in different genders., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

BACKGROUND. Chest CT findings have the potential to guide treatment of hospitalized patients with coronavirus disease (COVID-19). OBJECTIVE. The purpose of this study was to assess a CT visual severity score in hospitalized patients with COVID-19, with attention to temporal changes in the score and the role of the score in a model for predicting in-hospital complications. METHODS. This retrospective study included 161 inpatients with COVID-19 from three hospitals in China who underwent serial chest CT scans during hospitalization. CT examinations were evaluated using a visual severity scoring system. The temporal pattern of the CT visual severity score across serial CT examinations during hospitalization was characterized using a generalized spline regression model. A prognostic model to predict major complications, including in-hospital mortality, was created using the CT visual severity score and clinical variables. External model validation was evaluated by two independent radiologists in a cohort of 135 patients from a different hospital. RESULTS. The cohort included 91 survivors with nonsevere disease, 55 survivors with severe disease, and 15 patients who died during hospitalization. Median CT visual lung severity score in the first week of hospitalization was 2.0 in survivors with non-severe disease, 4.0 in survivors with severe disease, and 11.0 in nonsurvivors. CT visual severity score peaked approximately 9 and 12 days after symptom onset in survivors with nonsevere and severe disease, respectively, and progressively decreased in subsequent hospitalization weeks in both groups. In the prognostic model, in-hospital complications were independently associated with a severe CT score (odds ratio [OR], 31.28), moderate CT score (OR, 5.86), age (OR, 1.09 per 1-year increase), and lymphocyte count (OR, 0.03 per 1 × 10 9 /L increase). In the validation cohort, the two readers achieved C-index values of 0.92-0.95, accuracy of 85.2-86.7%, sensitivity of 70.7-75.6%, and specificity of 91.4-91.5% for predicting in-hospital complications. CONCLUSION. A CT visual severity score is associated with clinical disease severity and evolves in a characteristic fashion during hospitalization for COVID-19. A prognostic model based on the CT visual severity score and clinical variables shows strong performance in predicting in-hospital complications. CLINICAL IMPACT. The prognostic model using the CT visual severity score may help identify patients at highest risk of poor outcomes and guide early intervention.