Anxiety in young people: Analysis from a machine learning model.

The study addresses the detection of anxiety symptoms in young people using artificial intelligence models. Questionnaires such as the Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder 7-item scale (GAD-7) are used to collect data, with a focus on early detection of anxiety. Three machine learning models are employed: Support Vector Machine (SVM), K Nearest Neighbors (KNN), and Random Forest (RF), with cross-validation to assess their effectiveness. Results show that the RF model is the most efficient, with an accuracy of 91 %, surpassing previous studies. Significant predictors of anxiety are identified, such as parental education level, alcohol consumption, and social security affiliation. A relationship is observed between anxiety and personal and family history of mental illness, as well as with characteristics external to the model, such as family and personal history of depression. The analysis of the results highlights the importance of considering not only clinical but also social and family aspects in mental health interventions. It is suggested that the sample size be expanded in future studies to improve the robustness of the model. In summary, the study demonstrates the usefulness of artificial intelligence in the early detection of anxiety in young people and highlights the relevance of addressing multidimensional factors in the assessment and treatment of this condition.

Eating behaviors associated with weight gain among university students worldwide and treatment interventions: A systematic review.

Introduction: Emerging adulthood has been described as a period of risk for body weight gain. Several studies have indicated that the positive or negative health behaviors established during this stage, tend to prevail the rest of life. However, there are discrepancies in published studies on weight change in freshmen and there are disagreements on weight gain predictors. The present study reviewed the literature with the aim of knowing the eating behaviors associated with weight gain in university students. Method: A systematic search was conducted in three databases according to the PRISMA method during the months of February to November 2020. Results: 20 articles were included in the review. The main behaviors associated with weight gain were the consumption of sugary drinks, alcohol consumption, low consumption of vegetables and fruits, frequent self-consumption, eating unhealthy and low levels of food regulation.

Screen use during food consumption: Does it cause increased food intake? A systematic review.

Nowadays people use screens, such as mobile phones, television, or tablets, more often during mealtimes, which may have an effect on intake. This review aims to analyze the effect of screen use, during food consumption, on intake. A systematic review was carried out, based on those protocols established by PRISMA. The Cochrane Library, PubMed, Web of Science and Scopus databases were consulted. Experimental studies, published between 2010 and 2021, that recorded individual intake while using screens such as television, cell phones, or tablets, were selected. A total of 7181 relevant articles were obtained, which were then assessed in accordance with predetermined inclusion and exclusion criteria. Finally, 35 studies were included in the complete review: 22 compared different kinds of television content (e.g., adverts), five which compared television versus the absence of screens, four which compared television versus video games, two which compared the use of simultaneous screens, and two studies which included cell phones. A total of 27 studies reported consumption increases related to the presence of advertisements and food signals on screens. No significant differences in intake were reported in the eight studies that reported design or sample size limitations, or lack of control of certain variables. It is thus concluded that screen use during food consumption may increase intake. Education is necessary to regulate the habit of consuming food in the presence of screens. Also, the creation of policies that regulate advertising and food cues on screens are justified and must be accompanied by strategies to monitor compliance. As a limitation, further evidence is necessary in order to determine the effect of mobile phone and tablet use while eating. This protocol was registered via PROSPERO, ID: CRD42020211797.

Cobalt Resistance via Detoxification and Mineralization in the Iron-Reducing Bacterium Geobacter sulfurreducens.

Bacteria in the genus Geobacter thrive in iron- and manganese-rich environments where the divalent cobalt cation (CoII) accumulates to potentially toxic concentrations. Consistent with selective pressure from environmental exposure, the model laboratory representative Geobacter sulfurreducens grew with CoCl2 concentrations (1 mM) typically used to enrich for metal-resistant bacteria from contaminated sites. We reconstructed from genomic data canonical pathways for CoII import and assimilation into cofactors (cobamides) that support the growth of numerous syntrophic partners. We also identified several metal efflux pumps, including one that was specifically upregulated by CoII. Cells acclimated to metal stress by downregulating non-essential proteins with metals and thiol groups that CoII preferentially targets. They also activated sensory and regulatory proteins involved in detoxification as well as pathways for protein and DNA repair. In addition, G. sulfurreducens upregulated respiratory chains that could have contributed to the reductive mineralization of the metal on the cell surface. Transcriptomic evidence also revealed pathways for cell envelope modification that increased metal resistance and promoted cell-cell aggregation and biofilm formation in stationary phase. These complex adaptive responses confer on Geobacter a competitive advantage for growth in metal-rich environments that are essential to the sustainability of cobamide-dependent microbiomes and the sequestration of the metal in hitherto unknown biomineralization reactions.

Behavioral responses of Rhodnius prolixus to volatile organic compounds released in vitro by bacteria isolated from human facial skin.

BACKGROUND: Previous studies have demonstrated the role of volatile organic compounds (VOCs) produced by skin microbiota in the attraction of mosquitoes to humans. Recently, behavioral experiments confirmed the importance of VOCs released by skin microbiota in the attraction of Rhodnius prolixus (Hemiptera: Triatominae), a vector of Chagas disease. METHODS/FINDINGS: In this study, we screened for VOCs released in vitro by bacteria isolated from human facial skin that were able to elicit behavioral responses in R. prolixus. The VOCs released in vitro by eight bacterial species during two growth phases were tested with adult Rhodnius prolixus insects using a dual-choice "T"-shaped olfactometer. In addition, the VOCs released by the bacteria were analyzed with headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC-MS). The VOCs produced by Staphylococcus capitis 11C, Staphylococcus warneri and Staphylococcus epidermidis 1 were attractive to R. prolixus, while the VOCs released by Citrobacter koseri 6P, Brevibacterium epidermidis and Micrococcus luteus 23 were non-attractive. CONCLUSIONS: The results shown here indicate that VOCs released by bacteria isolated from human facial skin have a potential for biotechnological uses as a strategy to prevent the vectorial transmission of Chagas disease mediated by Rhodnius prolixus.