GNCnn: A QuPath extension for glomerulosclerosis and glomerulonephritis characterization based on deep learning.

The digitalization of traditional glass slide microscopy into whole slide images has opened up new opportunities for pathology, such as the application of artificial intelligence techniques. Specialized software is necessary to visualize and analyze these images. One of these applications is QuPath, a popular bioimage analysis tool.

Amalur EIS: a system for calculating the environmental impacts of industrial sites from E-PRTR records.

This article presents Amalur EIS ( https://www.amalur-eis.eus/ ), an Environmental Information System that estimates environmental impacts using data sourced from the European Pollutant Release and Transfer Register database (E-PRTR).

Data augmentation via warping transforms for modeling natural variability in the corneal endothelium enhances semi-supervised segmentation.

Image segmentation of the corneal endothelium with deep convolutional neural networks (CNN) is challenging due to the scarcity of expert-annotated data. This work proposes a data augmentation technique via warping to enhance the performance of semi-supervised training of CNNs for accurate segmentation. We use a unique augmentation process for images and masks involving keypoint extraction, Delaunay triangulation, local affine transformations, and mask refinement.

Multiomics and eXplainable artificial intelligence for decision support in insulin resistance early diagnosis: A pediatric population-based longitudinal study.

Pediatric obesity can drastically heighten the risk of cardiometabolic alterations later in life, with insulin resistance standing as the cornerstone linking adiposity to the increased cardiovascular risk. Puberty has been pointed out as a critical stage after which obesity-associated insulin resistance is more difficult to revert. Timely prediction of insulin resistance in pediatric obesity is therefore vital for mitigating the risk of its associated comorbidities.

Bee-Associated Beneficial Microbes-Importance for Bees and for Humans.

Bees are one of the best-known and, at the same time, perhaps the most enigmatic insects on our planet, known for their organization and social structure, being essential for the pollination of agricultural crops and several other plants, playing an essential role in food production and the balance of ecosystems, being associated with the production of high-value-added inputs, and a unique universe in relation to bees' microbiota. In this review, we summarize information regarding on different varieties of bees, with emphasis on their specificity related to microbial variations. Noteworthy are fructophilic bacteria, a lesser-known bacterial group, which use fructose fermentation as their main source of energy, with some strains being closely related to bees' health status.