Juan Manuel

Facultad de Ingeniería Civil, Universidad de Colima, Carretera Colima-Coquimatlán km 9, Col. Jardines del Llano, Coquimatlán 28400, Mexico

Show more Journal of Antimicrobial Chemotherapy , dkae093, https://doi.org/10.1093/jac/dkae093

Background: Nowadays, pregnant women require more individualized attention in their assistance process during pregnancy. One of the aspects that requires the most focus is the suitability of carrying out physical activity. The objective of this meta-review is to find out the effects of physical activity during pregnancy on the incidence of GDM compared to women who do not perform physical activity. Methods: A search was conducted in Cochrane, CSIC, Ebscohost, Proquest, Pubmed, Scielo, and Scopus. The search focused on systematic reviews and meta-analyses published in the last five years. The AMSTAR-2 scale was used as a quality assessment tool for the final sample. Results: A total of 18 systematic reviews and meta-analyses were included. Sixteen of them found out that physical activity during pregnancy has preventive effects for GDM compared with women who lacked physical activity. Among the studies, we found a reduction in the risk of GDM of between 24% and 38% and odds ratios ranging between 0.39 and 0.83 calculated for a 95% CI. Only two studies did not find statistically significant effects. Other variables such as type and duration of physical activity, overweight and obesity, gestational age, etc., were also considered. Conclusions: Physical activity prevents the incidence of GDM. The main characteristics that enhance this preventive effect are starting at the initial stages of pregnancy and maintaining during the whole pregnancy as well as combining strength and aerobic exercise at a low to moderate intensity.

Abstract Kaposi's sarcoma (KS) is a cancer affecting skin and internal organs for which the Kaposi's sarcoma associated herpesvirus (KSHV) is a necessary cause.

This paper introduces a novel one-dimensional convolutional neural network that utilizes clinical data to accurately detect choledocholithiasis, where gallstones obstruct the common bile duct. Swift and precise detection of this condition is critical to preventing severe complications, such as biliary colic, jaundice, and pancreatitis. This cutting-edge model was rigorously compared with other machine learning methods commonly used in similar problems, such as logistic regression, linear discriminant analysis, and a state-of-the-art random forest, using a dataset derived from endoscopic retrograde cholangiopancreatography scans performed at Olive View–University of California, Los Angeles Medical Center. The one-dimensional convolutional neural network model demonstrated exceptional performance, achieving 90.77% accuracy and 92.86% specificity, with an area under the curve of 0.9270. While the paper acknowledges potential areas for improvement, it emphasizes the effectiveness of the one-dimensional convolutional neural network architecture. The results suggest that this one-dimensional convolutional neural network approach could serve as a plausible alternative to endoscopic retrograde cholangiopancreatography, considering its disadvantages, such as the need for specialized equipment and skilled personnel and the risk of postoperative complications. The potential of the one-dimensional convolutional neural network model to significantly advance the clinical diagnosis of this gallstone-related condition is notable, offering a less invasive, potentially safer, and more accessible alternative.

Laboratory of Food Chemistry and Toxicology, Faculty of Pharmacy, University of Valencia, Av. Vicent Andrés Estellés s/n, 46100 Burjassot, Spain

Research Group in Innovative Technologies for Sustainable Food (ALISOST), Food Chemistry and Toxicology Laboratory, Preventive Medicine

In the field of biology, the 'biomarkers' of the different animal species are of great relevance, as well as the relationships between them and the quality of the habitat. A study was proposed, analysing the antlers of the Iberian deer, to measure the bilateral asymmetry of its branches. The antlers are characterised in a 3D CAD model of their axial structure obtained via photogrammetric restitution from two photographs. This method quantifies the global and partial asymmetries of the antler's structural features. The research evaluated 48 deer antlers from hunting days and taxidermy workshops. To quantify asymmetries, the measurements required are the same as those considered to assess the hunting quality of antlers. Bilateral deviations are estimated for each structural trait and the whole antler. Preliminary results showed a convergence between the values of global asymmetry and hunting quality. The methodology proved to be fast, inexpensive, and easy to implement, which facilitates its use in future asymmetry studies of other biological elements of animal or plant origin. It is only necessary that the starting data, which is the bilateral axial structure of the analysed element, is characterised in a 3D model.

Departamento de Genética y Biología Molecular, Cinvestav, Av. Instituto Politécnico Nacional 2508, Mexico City 07360, Mexico

Loading [MathJax]/jax/output/HTML-CSS/fonts/Gyre-Pagella/Size6/Regular/Main.js Open Access Article by Philip C. Mack