Repeated COVID-19 infection in recipients of post-living donor liver transplantation: Two real-life cases

COVID-19 is an emerging pandemic. The course and management of the disease in the liver transplant setting may be difficult due to a long-standing immunosuppressive state. In Egypt, the only available option is living donor liver transplantation (LDLT). In our centre, we have transplanted 440 livers since 2008. In this study, we report a single-centre experience with COVID-19 infection in long-term liver transplant recipients. A total of 25 recipients (5.7 %) had COVID-19 infections since March 2020. Among these recipients, two developed COVID-19 infections twice, approximately three and two months apart, respectively.Copyright © 2021 The Author(s)

Antiviral Activity of Vitamin D and COVID 19: Current Understanding

Innate and adaptive immune responses, which are intimately related to the evolution of many infectious diseases, are influenced by the biologically active form of vitamin D. From a mechanical perspective, there are several rationales to assume that vitamin D positively modifies host responses to SARS-CoV-2, either in the early infection or subsequent hyper-inflammatory stages of COVID-19. It has been long known that vitamin D metabolites induce antiviral effects through indirect and direct mechanisms via antimicrobial peptides, immune modulation, the interaction between major viral and cellular particles, initiation of apoptosis and autophagy, and diversity of hereditary and epigenetic aspects. The remarkable overlap between the deficiency of vitamin D and risk factors for severe COVID-19, including obesity, aging, and Black or Asian ethnicity, has motivated researchers to assume that supplementation of vitamin D can be promising as a preventive or treatment agent for COVID-19. Since the outset of the pandemic, researchers have integrated literature searches and cross-sectional statistical studies to appraise the vitamin D level impact of COVID-19, whereby nearly 30 observational studies have confirmed that the incidence, severity, and mortality of COVID-19 are inversely related to the serum 25OHD concentrations. Also, some recently announced clinical trials indicated that vitamin D supplementation has a positive effect on the severity of COVID-19;however, other studies, including clinical trials, have not supported that, especially if we take into account what was revealed in a recent clinical trial, i.e., airway diseases are related to the irregular metabolism of vitamin D increasing the potential of developing vitamin D deficiency due to pulmonary inflammation. Therefore, more dedicated studies are required without critical limitations to ascertain the actual effect of vitamin D in preventing and treating COVID-19, and if its effectiveness is proven, the effective dose must be determined. © 2021 Bentham Science Publishers. All rights reserved.

Deep Learning Enabling Analysis of Exhaled Breath Using Fourier Transform Spectroscopy in the Mid-Infrared

Exhaled breath analysis is a promising noninvasive method for rapid diagnosis of diseases by detecting different types of volatile organic compounds (VOCs) that are used as biomarkers for early detection of various diseases such as lung cancer, diabetes, anemias, etc... and more recently COVID-19. Infrared spectroscopy seems to be a promising method for VOCs detection due to its ease of use, selectivity, and existence of compact low-cost devices. In this work, the use of Fourier transforms infrared (FTIR) spectrometer to analyze breath samples contained in a gas cell is investigated using deep learning and taking into account the practical performance limits of the spectrometer. Synthetic spectra are generated using infrared gas spectra databases to emulate real spectra resulted from a breath sample and train the neural network model (NNM). The dataset is generated in the spectral range of 2000 cm-1 to 6500 cm-1 and assuming a light-gas interaction length of 5 meters. The FTIR device performance is assumed with a signal-to-noise ratio (SNR) of 20,000:1 and a spectral resolution of 40 cm-1. The proposed NNM contains a locally connected and 4 fully connected layers. The concentrations of 9 biomarker gases in the exhaled breath are predicted with r2 score higher than 0.93, including carbon dioxide, water vapor, acetone, ethene, ammonia, methane, carbonyl sulfide, carbon monoxide and acetaldehyde demonstrating the possibility of detection. © 2021 IEEE.