Attitudes towards the mixing of COVID-19 vaccinated and unvaccinated patients in multi-bed hospital rooms.

Aim: To explore patient and staff views about the mixing of COVID-19 vaccinated and unvaccinated patients in multi-bed hospital rooms.

Methods: We conducted a mixed methods study with paper surveys and structured interviews. Self-administered surveys were undertaken with inpatients on the general medicine, general surgery, orthopaedic and respiratory wards in Dunedin Public Hospital.

Amelioration of SARS-CoV-2 infection by ANO6 phospholipid scramblase inhibition.

As an enveloped virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) delivers its viral genome into host cells via fusion of the viral and cell membranes. Here, we show that ANO6/TMEM16F-mediated cell surface exposure of phosphatidylserine is critical for SARS-CoV-2 entry and that ANO6-selective inhibitors are effective against SARS-CoV-2 infections. Application of the SARS-CoV-2 Spike pseudotyped virus (SARS2-PsV) evokes a cytosolic Ca elevation and ANO6-dependent phosphatidylserine externalization in ACE2/TMPRSS2-positive mammalian cells.

COVID-19 doesn't need lockdowns to destroy jobs: The effect of local outbreaks in Korea.

Unlike most countries, Korea did not implement a lockdown in its battle against COVID-19, instead successfully relying on testing and contact tracing. Until the summer of 2020, only one region, Daegu-Gyeongbuk, had a significant number of infections, traced to a religious sect. This allows us to estimate the causal effect of the outbreak on the labor market using difference-in-differences.

srBERT: automatic article classification model for systematic review using BERT.

Background: Systematic reviews (SRs) are recognized as reliable evidence, which enables evidence-based medicine to be applied to clinical practice. However, owing to the significant efforts required for an SR, its creation is time-consuming, which often leads to out-of-date results. To support SR tasks, tools for automating these SR tasks have been considered; however, applying a general natural language processing model to domain-specific articles and insufficient text data for training poses challenges.