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The Open Anatomy Explorer - a journey towards accessible open-source 3D learning environments.
J Vis Commun Med
January 2025
Department of Human Structure and Repair, Ghent University, Ghent, Belgium.
Anatomy learning has traditionally relied on drawings, plastic models, and cadaver dissections/prosections to help students understand the three-dimensional (3D) relationships within the human body. However, the landscape of anatomy education has been transformed with the introduction of digital media. In this light, the Open Anatomy Explorer (OPANEX) was developed.
View Article and Find Full Text PDFAISMPred: A Machine Learning Approach for Predicting Anti-Inflammatory Small Molecules.
Pharmaceuticals (Basel)
December 2024
Computational Biology Laboratory, Department of Genetic Engineering, School of Bioengineering, SRM Institute of Science and Technology, Kattankulathur, Chengalpattu 603203, Tamil Nadu, India.
Inflammation serves as a vital response to diverse harmful stimuli like infections, toxins, or tissue injuries, aiding in the elimination of pathogens and tissue repair. However, persistent inflammation can lead to chronic diseases. Peptide therapeutics have gained attention for their specificity in targeting cells, yet their development remains costly and time-consuming.
View Article and Find Full Text PDFHepatic stellate cell single cell atlas reveals a highly similar activation process across liver disease aetiologies.
JHEP Rep
January 2025
Vrije Universiteit Brussel, Liver Cell Biology research group, Laarbeeklaan 103, 1090 Brussel, Belgium.
Article Synopsis
- This research explores the activation of hepatic stellate cells (HSCs) across different types of chronic liver disease (CLD), finding that their activation follows similar mechanisms regardless of the injury type.
- A single-cell RNA-sequencing atlas was created to categorize HSCs into three profiles: quiescent, initiatory, and myofibroblasts, indicating consistent activation patterns in both mice and humans.
- The study highlights key transcription factors and novel ligands involved in HSC activation, paving the way for new insights and potential treatments for liver fibrosis.
Automating radiological measurements of the hip in children with cerebral palsy.
Bone Joint J
January 2025
Division of Informatics, Imaging & Data Sciences, The University of Manchester, Manchester, UK.
Aims: The aims of this study were to develop an automatic system capable of calculating four radiological measurements used in the diagnosis and monitoring of cerebral palsy (CP)-related hip disease, and to demonstrate that these measurements are sufficiently accurate to be used in clinical practice.
Methods: We developed a machine-learning system to automatically measure Reimer's migration percentage (RMP), acetabular index (ACI), head shaft angle (HSA), and neck shaft angle (NSA). The system automatically locates points around the femoral head and acetabulum on pelvic radiographs, and uses these to calculate measurements.
- a large-scale dataset of 3D medical shapes for computer vision.
Biomed Tech (Berl)
December 2024
Institute for Artificial Intelligence in Medicine (IKIM), University Hospital Essen (AöR), Essen, Germany.
Objectives: The shape is commonly used to describe the objects. State-of-the-art algorithms in medical imaging are predominantly diverging from computer vision, where voxel grids, meshes, point clouds, and implicit surface models are used. This is seen from the growing popularity of ShapeNet (51,300 models) and Princeton ModelNet (127,915 models).
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