Cross-Cultural Adaptation and Validation of the Fear of COVID-19 Scale for Chinese University Students: A Cross-Sectional Study.

BACKGROUND: fear of COVID-19 is widespread among the population, especially among college students because of their increased exposure to the media information overload of the COVID-19 outbreak. The Fear of COVID-19 scale (FCV-19 S) is a relatively short instrument used to evaluate fears surrounding the COVID-19 pandemic. However, the validity and reliability of the Fear of COVID-19 Scale have not been fully investigated in Chinese university student groups. OBJECTIVES: this study assessed the cross-cultural adaptability and reliability of the FCV-19S for Chinese university students. METHODS: a Chinese version of Fear of COVID-19 Scale (C-FCV-19S) was generated using the translation-backward translation method. Psychometric properties of the C-FCV-19S, including internal consistency, split-half reliability, construct reliability, convergent validity, and diagnostic accuracy, were evaluated. The Patient Health Questionnaire (PHQ) and Generalized Anxiety Disorder Questionnaire (GAD-7) scales were also used to evaluate participants for depression and anxiety. RESULTS: the C-FCV-19S has acceptable internal consistency (Cronbach's alpha: 0.872) and satisfactory split-half reliability (correlation coefficient: 0.799). Using the exploratory factor analysis (EFA), we examined the construct reliability (KMO = 0.920). The confirmatory factor analysis (CFA) confirmed that the bifactor model of scale (including general factor, factor1: the awareness of COVID-19 and physiological arousal, factor 2: fear-related thinking) had a good fit index (χ2/df =6.18, RMSEA= 0.067, SRMR = 0.028, GFI = 0.986, TLI = 0.970 and CFI= 0.988). Using depression-positive and anxiety-positive scores as reference criteria, we found that the areas under the curve were 0.70 and 0.68, respectively, and that the optimal cutoff scores of the C-FCV-19S was 17.5 (sensitivity: 66.3% and 58.7%, respectively). CONCLUSIONS: the validity and reliability of C-FCV-19S are satisfactory, and the optimal cutoff point was 17.5. The C-FCV-19S can be applied adopted in Chinese university students.

The Role of Imaging in the Detection and Management of COVID-19: A Review.

Coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is spreading rapidly around the world, resulting in a massive death toll. Lung infection or pneumonia is the common complication of COVID-19, and imaging techniques, especially computed tomography (CT), have played an important role in diagnosis and treatment assessment of the disease. Herein, we review the imaging characteristics and computing models that have been applied for the management of COVID-19. CT, positron emission tomography - CT (PET/CT), lung ultrasound, and magnetic resonance imaging (MRI) have been used for detection, treatment, and follow-up. The quantitative analysis of imaging data using artificial intelligence (AI) is also explored. Our findings indicate that typical imaging characteristics and their changes can play crucial roles in the detection and management of COVID-19. In addition, AI or other quantitative image analysis methods are urgently needed to maximize the value of imaging in the management of COVID-19.

Necrostatin-1 and necroptosis inhibition: Pathophysiology and therapeutic implications.

Necrostatin-1 (Nec-1) is a RIP1-targeted inhibitor of necroptosis, a form of programmed cell death discovered and investigated in recent years. There are already many studies demonstrating the essential role of necroptosis in various diseases, including inflammatory diseases, cardiovascular diseases and neurological diseases. However, the potential of Nec-1 in diseases has not received much attention. Nec-1 is able to inhibit necroptosis signaling pathway and thus ameliorate necroptotic cell death in disease development. Recent research findings indicate that Nec-1 could be applied in several types of diseases to alleviate disease development or improve prognosis. Moreover, we predict that Nec-1 has the potential to protect against the complications of coronavirus disease 2019 (COVID-19). This review summarized the effect of Nec-1 in disease models and the underlying molecular mechanism, providing research evidence for its future application.