Machine learning application for the prediction of SARS-CoV-2 infection using blood tests and chest radiograph

Triaging and prioritising patients for RT-PCR test had been essential in the management of COVID-19 in resource-scarce countries. In this study, we applied machine learning (ML) to the task of detection of SARS-CoV-2 infection using basic laboratory markers. We performed the statistical analysis and trained an ML model on a retrospective cohort of 5148 patients from 24 hospitals in Hong Kong to classify COVID-19 and other aetiology of pneumonia. We validated the model on three temporal validation sets from different waves of infection in Hong Kong. For predicting SARS-CoV-2 infection, the ML model achieved high AUCs and specificity but low sensitivity in all three validation sets (AUC: 89.9-95.8%; Sensitivity: 55.5-77.8%; Specificity: 91.5-98.3%). When used in adjunction with radiologist interpretations of chest radiographs, the sensitivity was over 90% while keeping moderate specificity. Our study showed that machine learning model based on readily available laboratory markers could achieve high accuracy in predicting SARS-CoV-2 infection.

Polysaccharide peptide mediates apoptosis by up-regulating p21 gene and down-regulating cyclin D1 gene

The use of herbal medicine is a common practice among Chinese women with breast cancer. Yunzhi (Voriolus versicolor), a substance that is regarded as a biological response modifier, is frequently used. The aim of the present study is to evaluate the anti-proliferative action of, Yunzhi, polysaccharide peptide (PSP), on breast cancer cells. Breast cancer cells (MDA-MB-231) were cultured with and without PSP for 7 days. Cell growth at 24, 72, 120 and 168 hours was measured by Cell Proliferation Reagent (WST-1). Cells treated with PSP were found to have a significant reduction in cell proliferation as compared to controls after 72 hours of incubation. This lasted for 168 hours. When the effect of PSP on apoptosis was studied by the TdT-mediated X-dUTP nick end-labeling (TUNEL) assay, we found that PSP had a significant effect upon apoptosis from 24 hours onward. Immunostaining showed that PSP increased p21 expression and decreased cyclin D1 expression. In conclusion, PSP is effective in inhibiting cell proliferation through apoptosis. The mechanism for the apoptosis may be through up-regulation of p21 and down-regulation of cyclin D1.