Unveiling insights from the Joint FAO/WHO Expert Committee on Food Additives (JECFA) portal.

This study presents a method for automating the retrieval of key identifies and links to toxicological data from the Joint FAO/WHO Expert Committee on Food Additives (JECFA) database using web scraping techniques. Although the method primarily serves as an automated indexing tool, facilitating organization and access to relevant reports, monographs, and specifications, it significantly enhances the efficiency of navigating the extensive JECFA database. Researchers can then perform more targeted and efficient searches, although additional manual steps are required to extract and structure the detailed toxicological data.

Species in Small Mammals in Turkey: sp. nov. Isolated from a Ural Field Mouse ().

The genus is composed of Gram-negative, fastidious, facultative intracellular bacteria that can cause bacteremia in mammals and various disorders in humans. Rodents have been reported as reservoirs of more than 30 species, seven of which cause zoonotic infections. In the present study, the isolation of sp.

Determination of volatile impurities and ethanol content in ethanol-based hand sanitizers: Compliance and toxicity.

This study aimed to assess volatile impurities and ethanol content in ethanol-based hand sanitizers. A total of 31 different brands of hand sanitizers were analyzed using headspace gas chromatography-mass spectrometry to detect impurities and determine alcohol content for compliance. Volatile impurities were identified through Mass Spectrometry database analysis, and regression analysis was employed to ascertain ethanol percentage.

sp. nov., isolated from infected rodents () in Senegal.

species are involved in various human diseases, causing a range of clinical manifestations; animals are considered as the main reservoirs, transmitting diverse species of through direct contact and haematophagous insects. Here, we characterize a new species, sp. nov.

Towards an ML-based semantic IoT for pandemic management: A survey of enabling technologies for COVID-19.

The connection between humans and digital technologies has been documented extensively in the past decades but needs to be evaluated through the current global pandemic. Artificial Intelligence(AI), with its two strands, Machine Learning (ML) and Semantic Reasoning, has proven to be a great solution to provide efficient ways to prevent, diagnose and limit the spread of COVID-19. IoT solutions have been widely proposed for COVID-19 disease monitoring, infection geolocation, and social applications.