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Toxoplasmosis is a disease caused by a protozoan called Toxoplasma gondii, it manifests itself with great morbidity and mortality in fetuses, newborns and immunocompromised patients, however, toxoplasmosis can also manifest itself in immunocompetent patients suffering from: chorioretinitis, lymphadenopathy, pneumonia, brain abscess, myositis, myocarditis and hepatitis. The objective of this investigation was to identify the clinical manifestations of toxoplasmosis in pork meat and the possible risks to human health. A literature review was performed in the Scopus, Cochrane, Web of Science, PubMed, Library, and Embase databases up to October 2022. Reference lists of all major articles found electronically were also hand searched, which allowed obtaining 85 records, of which 19 were selected. Toxoplasmosis is a common infectious disease in developing, tropical, and subtropical countries around the world. The incidence has increased in rural areas and in lower socioeconomic groups. [ABSTRACT FROM AUTHOR]

The regulation of the circadian cycle, an essential process for the functioning of living organisms, including humans, is highly dependent on exposure to external light, directly influencing the sleep cycle. However, increasing exposure to artificial light from digital devices such as televisions, cell phones and computers, especially during nighttime hours, has raised concerns about its impact on the circadian cycle. This prolonged exposure alters external stimuli and, in turn, affects the production of internal chemical messengers, which can lead to metabolic, hormonal, immunological, mental and physical disorders in individuals. These findings underscore the importance of understanding the negative effects of blue light and developing strategies to counteract its impacts on human health and well-being. [ABSTRACT FROM AUTHOR]

Copyright of Revista de Ciencias Médicas de Pinar del Río is the property of Editorial Ciencias Medicas and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Neutrosophic Computing & Machine Learning is the property of Multimedia Larga and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In-depth interviews are a method widely used by researchers, which are processed once transcribed. Currently, with the development of computer programming, the use of a natural language processing method to analyze such interviews has spread. There are dissimilar programs of various kinds, where lexicons offer highly useful benefits for researchers as they save time and increase efficiency. In essence, these expose how positive or negative a text related to a topic can be. Taking into consideration the usefulness of Neutrosophy for social phenomena and the treatment of indeterminacies, vagueness, and neutralities, it is convenient to establish as an objective of this paper: to develop a method for the sentiment analysis of the transcripts of in-depth interviews in Action Research based on natural language processing and Single Value Neutrosophic Numbers (SVNN). The most important characteristics to take into account in the in-depth interviews will be determined. Then the lexicon will be selected for the natural language processing of the research to fulfill its main objective. [ABSTRACT FROM AUTHOR]