AIMC Topic: Hemolysis

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Automatic hemolysis identification on aligned dual-lighting images of cultured blood agar plates.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The recent introduction of Full Laboratory Automation systems in clinical microbiology opens to the availability of streams of high definition images representing bacteria culturing plates. This creates new opportunities to ...

HemoPred: a web server for predicting the hemolytic activity of peptides.

Future medicinal chemistry
AIM: Toxicity arising from hemolytic activity of peptides hinders its further progress as drug candidates.

Antihemolytic and antioxidant properties of pearl powder against 2,2'-azobis(2-amidinopropane) dihydrochloride-induced hemolysis and oxidative damage to erythrocyte membrane lipids and proteins.

Journal of food and drug analysis
Pearl powder, a well-known traditional mineral medicine, is reported to be used for well-being and to treat several diseases from centuries in Taiwan and China. We investigated the in vitro antihemolytic and antioxidant properties of pearl powder tha...

A Web Server and Mobile App for Computing Hemolytic Potency of Peptides.

Scientific reports
Numerous therapeutic peptides do not enter the clinical trials just because of their high hemolytic activity. Recently, we developed a database, Hemolytik, for maintaining experimentally validated hemolytic and non-hemolytic peptides. The present stu...

ConsAMPHemo: A computational framework for predicting hemolysis of antimicrobial peptides based on machine learning approaches.

Protein science : a publication of the Protein Society
Many antimicrobial peptides (AMPs) function by disrupting the cell membranes of microbes. While this ability is crucial for their efficacy, it also raises questions about their safety. Specifically, the membrane-disrupting ability could lead to hemol...

Deep-Learning-Based Approaches for Rational Design of Stapled Peptides With High Antimicrobial Activity and Stability.

Microbial biotechnology
Antimicrobial peptides (AMPs) face stability and toxicity challenges in clinical use. Stapled modification enhances their stability and effectiveness, but its application in peptide design is rarely reported. This study built ten prediction models fo...

[Study on lightweight plasma recognition algorithm based on depth image perception].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
In the clinical stage, suspected hemolytic plasma may cause hemolysis illness, manifesting as symptoms such as heart failure, severe anemia, etc. Applying a deep learning method to plasma images significantly improves recognition accuracy, so that th...

[Optimization of centrifugal artificial heart pump blade parameters based on back propagation neural network and grey wolf optimization algorithm].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
The impeller, as a key component of artificial heart pumps, experiences high shear stress due to its rapid rotation, which may lead to hemolysis. To enhance the hemolytic performance of artificial heart pumps and identify the optimal combination of b...

Structure-aware deep learning model for peptide toxicity prediction.

Protein science : a publication of the Protein Society
Antimicrobial resistance is a critical public health concern, necessitating the exploration of alternative treatments. While antimicrobial peptides (AMPs) show promise, assessing their toxicity using traditional wet lab methods is both time-consuming...