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hERGAT: predicting hERG blockers using graph attention mechanism through atom- and molecule-level interaction analyses.
J Cheminform
January 2025
Department of Intelligent Electronics and Computer Engineering, Chonnam National University, Gwangju, Republic of Korea.
The human ether-a-go-go-related gene (hERG) channel plays a critical role in the electrical activity of the heart, and its blockers can cause serious cardiotoxic effects. Thus, screening for hERG channel blockers is a crucial step in the drug development process. Many in silico models have been developed to predict hERG blockers, which can efficiently save time and resources.
View Article and Find Full Text PDF[The many ways flowers send signals to pollinators].
Biol Aujourdhui
January 2025
Institut d'Écologie et des Sciences de l'Environnement de Paris (iEES Paris), Paris, France - Sorbonne Université, 4 place Jussieu, 75005 Paris, France.
The evolutionary success of angiosperms, which make up more than 95 percent of the world's terrestrial flora, is largely based on their interactions with animal pollinators. Indeed, it is estimated that, on average, 87.5 percent of flowering plants are pollinated by animals.
View Article and Find Full Text PDFYour Brain's "Save" Button: The Amygdala.
Front Young Minds
January 2024
Immersive Neuromodulation and Neuroimaging Laboratory, Department of Psychology, University of Utah, Salt Lake City, UT, USA.
Do you ever wonder why you remember some experiences better than others? Why you remember that funny joke your friend told at lunch a few months ago or the scary snake you saw in your backyard, but not that time you went to the post office with your parents? Just like a computer has a save button, our brains do, too! When something scary, exciting, or strange happens, a small part of the brain, the amygdala, helps us click save on that event so we can remember it later. Decades of research have helped scientists understand what parts of the brain are important for memory and how the amygdala works with other brain regions to tag experiences as worth remembering. This research is important for understanding how memories are formed and can help us create new therapies for people with memory problems, who have trouble forming new memories and remembering past experiences.
View Article and Find Full Text PDFAutomated spinopelvic measurements on radiographs with artificial intelligence: a multi-reader study.
Radiol Med
January 2025
Department of Radiology, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.
Purpose: To develop an artificial intelligence (AI) algorithm for automated measurements of spinopelvic parameters on lateral radiographs and compare its performance to multiple experienced radiologists and surgeons.
Methods: On lateral full-spine radiographs of 295 consecutive patients, a two-staged region-based convolutional neural network (R-CNN) was trained to detect anatomical landmarks and calculate thoracic kyphosis (TK), lumbar lordosis (LL), sacral slope (SS), and sagittal vertical axis (SVA). Performance was evaluated on 65 radiographs not used for training, which were measured independently by 6 readers (3 radiologists, 3 surgeons), and the median per measurement was set as the reference standard.
Efficient diagnosis of diabetes mellitus using an improved ensemble method.
Sci Rep
January 2025
Faculty of Engineering, Université de Moncton, Moncton, NB, E1A3E9, Canada.
Diabetes is a growing health concern in developing countries, causing considerable mortality rates. While machine learning (ML) approaches have been widely used to improve early detection and treatment, several studies have shown low classification accuracies due to overfitting, underfitting, and data noise. This research employs parallel and sequential ensemble ML approaches paired with feature selection techniques to boost classification accuracy.
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