PubMed COVID-19 Clinical Care

The coronavirus disease 2019 (COVID-19) pandemic is an ongoing global health concern, and effective antiviral reagents are urgently needed. Traditional Chinese medicine theory-driven natural drug research and development (TCMT-NDRD) is a feasible

CONCLUSIONS AND RELEVANCE: The findings of this nested case-control study show a direct association of MVPA with risk of SARS-CoV-2 infection, which was mitigated after completion of the COVID-19 vaccination primary series. In addition, higher levels

A generation of microplastics caused by improper disposal of disposable masks has become a non-negligible environmental concern. In order to investigate the degradation mechanisms of masks and the release of microplastics under different

Community Mental Health Centers (CMHCs) and Federally Qualified Health Centers (FQHCs) are critical access points for families with adolescents needing mental health care, especially those enrolled in Medicaid. However, barriers exist which may

In a convenience sample of 93 patients treated with monoclonal antibodies (moAbs) against SARS-CoV-2, the interleukin-6²/lymphocyte count ratio (IL-6²/LC) was able to predict clinical worsening both in early stages of COVID-19 and in oxygen-requiring

Appropriate interpretation of various diagnostic tests for COVID-19 is critical, yet the association among rapid antigen tests, reverse transcription (RT)-PCR, and viral culture has not been fully defined. To determine whether rapid antigen testing

Symptoms of anxiety and depressive disorders have been increasing substantially among adults in the United States (US) during the COVID-19 pandemic, particularly for low-income populations. Under-resourced communities have difficulties accessing

CONCLUSIONS: Having the most significant correlations, IL-6 high levels in mechanically ventilated patients were shown to affect laboratory results, and, therefore, is suggested as a severity biomarker of COVID-19.

CONCLUSIONS: Perceived susceptibility, perceived seriousness, perceived benefits, perceived barriers and cues to action were found to affect a person's adherence with coronavirus disease-2019 protocols.

While research into drug-target interaction (DTI) prediction is fairly mature, generalizability and interpretability are not always addressed in the existing works in this field. In this paper, we propose a deep learning (DL)-based framework, called