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Trends in Phytochemical Research ; 6(3):187-213, 2022.
Article in English | Scopus | ID: covidwho-2091561

ABSTRACT

Medicinal herbs, including the Asteraceae family (AF), have different antimicrobial and therapeutic effects. Therefore, they can be used as health factors in the food and medicinal industries. In this systematic review, the essential information was collected from the relevant databases, e.g., PubMed, Science Direct, and Google Scholar based on medicinal herbs, AF, essential oil, antimicrobial, antioxidant, therapeutic effect, and COVID-19 keywords. AF can be used as safe preservatives and food additives with a specific amount of consumption in the food industry thanks to their good flavor, antioxidant and antimicrobial effect. Due to their therapeutic effects, they can improve the health role of food. AF herbs contain important bioactive compounds, but not all of them can be used as medicine and food supplements since yarrow, chamomile, and artichoke exhibit toxic effects in high dosage, therefore, the consumption of these herbs should be considered to not endanger the health of the consumer. © 2022, Trends Phytochem. All rights reserved.

2.
Applied Sciences (Switzerland) ; 12(10), 2022.
Article in English | Scopus | ID: covidwho-1875463

ABSTRACT

Background: Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a global threat impacting the lives of millions of people worldwide. Automated detection of lung infections from Computed Tomography scans represents an excellent alternative;however, segmenting infected regions from CT slices encounters many challenges. Objective: Developing a diagnosis system based on deep learning techniques to detect and quantify COVID-19 infection and pneumonia screening using CT imaging. Method: Contrast Limited Adaptive Histogram Equalization pre-processing method was used to remove the noise and intensity in homogeneity. Black slices were also removed to crop only the region of interest containing the lungs. A U-net architecture, based on CNN encoder and CNN decoder approaches, is then introduced for a fast and precise image segmentation to obtain the lung and infection segmentation models. For better estimation of skill on unseen data, a fourfold cross-validation as a resampling procedure has been used. A three-layered CNN architecture, with additional fully connected layers followed by a Softmax layer, was used for classification. Lung and infection volumes have been reconstructed to allow volume ratio computing and obtain infection rate. Results: Starting with the 20 CT scan cases, data has been divided into 70% for the training dataset and 30% for the validation dataset. Experimental results demonstrated that the proposed system achieves a dice score of 0.98 and 0.91 for the lung and infection segmentation tasks, respectively, and an accuracy of 0.98 for the classification task. Conclusions: The proposed workflow aimed at obtaining good performances for the different system’s components, and at the same time, dealing with reduced datasets used for training. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

3.
Journal of Liver Transplantation ; : 100051, 2021.
Article in English | ScienceDirect | ID: covidwho-1474864

ABSTRACT

The COVID-19 pandemic strongly affected organ procurement and transplantation in France, despite the intense efforts of all participants in this domain. In 2020, the identification and procurement of deceased donors fell by 12% and 21% respectively, compared with the mean of the preceding 2 years. Similarly, the number of new registrations on the national waiting list declined by 12% and the number of transplants by 24%. The 3-month cumulative incidence of death or drop out for worsening condition of patients awaiting a liver transplant was significantly greater in 2020 compared to the previous 2 years. Continuous monitoring at the national level of early post-transplant outcomes showed no deterioration for any organ in 2020. At the end of 2020, less than 1% of transplant candidates and less than 1% of graft recipients — of any organ — had died of COVID-19.

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