The Human Phospholipase B-II Precursor (HPLBII-P) in Urine as a Novel Biomarker of Glomerular Activity in COVID-19 and Diabetes Mellitus (preprint)

The human phospholipase B-II precursor (HPLBII-P) was originally purified from white blood cells but is also found in other cellular structures such as kidney glomeruli and tubuli. The objective of this report was to investigate the relationship of HPLBII-P in urine to acute kidney injury in patients with COVID-19 Methods Urine was collected at admission from 132 COVID-19 patients admitted to the intensive care units (ICU) because of respiratory failure. HPLBII-P was measured by a sensitive ELISA. For comparison, HNL was measured in urine, by the ELISA configured with mabs 763/8F, as a sign of tubular affection in addition to routine biomarkers of kidney disease Results Overall, the concentrations of urinary HPLBII-P were almost 3-fold higher in COVID-19 patients as compared to healthy controls (p

Modeling and Forecast of COVID-19 Vaccinations Population Size in China: A Non-Clinical Study (preprint)

BACKGROUND Since its outbreak in December 2019, severe acute respiratory syndrome coronavirus-2, the virus responsible for the COVID-19 pandemic, has considerably affected the worldwide population. Health authorities and the medical community identify vaccines as an effective tool for managing public health. METHODS In this study, the autoregressive integrated moving average (ARIMA) model built-in Python was adopted to establish the COVID-19 vaccination forecast model. In this study, the sample data were selected from the Our World in Data website. COVID-19 vaccinations administered daily in China from December 16, 2020 to March 21, 2021 were analyzed to establish an autoregressive integrated moving average (ARIMA) model. RESULTS The built-in ARIMA module function of Python was used, and the optimum model was ARIMA (3, 2, 3) according to the established time series analysis. The analysis showed that the predicted COVID-19 vaccination uptake supplemented well with the actual values with a small relative error. CONCLUSIONS This indicated that the ARIMA(3, 2, 3) model could be used to forecast the number of COVID-19 vaccinations in China.