AIMC Topic: Hemolysis
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Optimization of hemocompatibility metrics in ventricular assist device design using machine learning and CFD-based response surface analysis.
The International journal of artificial organs
Jun 6, 2025
Ventricular assist devices (VADs) are essential for end-stage heart failure patients, but their design must balance hydraulic efficiency and hemocompatibility to minimize blood damage. This study presents a multi-objective optimization framework inte...
Addressing Hemolysis-Induced Loss of Sensitivity in Lateral Flow Assays of Blood Samples with Platinum-Coated Gold Nanoparticles and Machine Learning.
Analytical chemistry
Mar 27, 2025
Gold nanoparticles (GNPs), which appear red, are widely used as labels in lateral flow assays (LFAs) for visual detection. However, in blood-derived samples, hemolysis─caused by the rupture of red blood cells and the release of hemoglobin─creates a r...
Multi-Peptide: Multimodality Leveraged Language-Graph Learning of Peptide Properties.
Journal of chemical information and modeling
Dec 19, 2024
Peptides are crucial in biological processes and therapeutic applications. Given their importance, advancing our ability to predict peptide properties is essential. In this study, we introduce Multi-Peptide, an innovative approach that combines trans...
Novel active Trp- and Arg-rich antimicrobial peptides with high solubility and low red blood cell toxicity designed using machine learning tools.
International journal of antimicrobial agents
Dec 5, 2024
BACKGROUND: Given the rising number of multidrug-resistant (MDR) bacteria, there is a need to design synthetic antimicrobial peptides (AMPs) that are highly active, non-hemolytic, and highly soluble. Machine learning tools allow the straightforward i...
Enhanced prediction of hemolytic activity in antimicrobial peptides using deep learning-based sequence analysis.
BMC bioinformatics
Nov 27, 2024
Antimicrobial peptides (AMPs) are a promising class of antimicrobial drugs due to their broad-spectrum activity against microorganisms. However, their clinical application is limited by their potential to cause hemolysis, the destruction of red blood...
Discovery of AMPs from random peptides via deep learning-based model and biological activity validation.
European journal of medicinal chemistry
Aug 26, 2024
The ample peptide field is the best source for discovering clinically available novel antimicrobial peptides (AMPs) to address emerging drug resistance. However, discovering novel AMPs is complex and expensive, representing a major challenge. Recent ...
Machine Learning-Driven Discovery and Evaluation of Antimicrobial Peptides from Mucus Proteome.
Marine drugs
Aug 26, 2024
Marine antimicrobial peptides (AMPs) represent a promising source for combating infections, especially against antibiotic-resistant pathogens and traditionally challenging infections. However, traditional drug discovery methods face challenges such a...
Hybrid transformer-CNN model for accurate prediction of peptide hemolytic potential.
Scientific reports
Jun 20, 2024
Hemolysis is a crucial factor in various biomedical and pharmaceutical contexts, driving our interest in developing advanced computational techniques for precise prediction. Our proposed approach takes advantage of the unique capabilities of convolut...
Measuring haemolysis in cattle serum by direct UV-VIS and RGB digital image-based methods.
Scientific reports
Aug 8, 2022
A simple, rapid procedure is required for the routine detection and quantification of haemolysis, one of the main sources of unreliable results in serum analysis. In this study, we compared two different approaches for the rapid determination of haem...
A deep learning-based system for assessment of serum quality using sample images.
Clinica chimica acta; international journal of clinical chemistry
Apr 12, 2022
BACKGROUND: Serum quality is an important factor in the pre-analytical phase of laboratory analysis. Visual inspection of serum quality (including recognition of hemolysis, icterus, and lipemia) is widely used in clinical laboratories but is time-con...
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