AIMC Topic: L-Lactate Dehydrogenase
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Machine-Learning-Driven Discovery of -Phenylbenzenesulfonamides as a Novel Chemotype for Lactate Dehydrogenase A Inhibition with Anti-Pancreatic Cancer Activity.
Journal of medicinal chemistry
Jul 11, 2025
Lactate dehydrogenase A (LDHA) is a promising target for cancer therapy due to its crucial role in aerobic glycolysis. Despite extensive efforts, the structural diversity of LDHA inhibitors remains limited. Here, we utilized machine learning techniqu...
Metabolic alterations driven by LDHA in CD8 + T cells promote immune evasion and therapy resistance in NSCLC.
Scientific reports
Jul 8, 2025
Non-small cell lung cancer (NSCLC) is a leading cause of cancer-related deaths worldwide. Despite advancements in treatment, prognosis for patients with advanced stages remains poor. Metabolic reprogramming in the tumor microenvironment, particularly...
Role of Artificial Intelligence in Identifying Vital Biomarkers with Greater Precision in Emergency Departments During Emerging Pandemics.
International journal of molecular sciences
Jan 16, 2025
The COVID-19 pandemic has accelerated advances in molecular biology and virology, enabling the identification of key biomarkers to differentiate between severe and mild cases. Furthermore, the use of artificial intelligence (AI) and machine learning ...
Novel molecular inhibitor design for Plasmodium falciparum Lactate dehydrogenase enzyme using machine learning generated library of diverse compounds.
Molecular diversity
Aug 20, 2024
Generative machine learning models offer a novel strategy for chemogenomics and de novo drug design, allowing researchers to streamline their exploration of the chemical space and concentrate on specific regions of interest. In cases with limited inh...
Prognosis of COVID-19 severity using DERGA, a novel machine learning algorithm.
European journal of internal medicine
Mar 8, 2024
It is important to determine the risk for admission to the intensive care unit (ICU) in patients with COVID-19 presenting at the emergency department. Using artificial neural networks, we propose a new Data Ensemble Refinement Greedy Algorithm (DERGA...
Residual facial erythema in atopic dermatitis patients treated with dupilumab stratified by machine learning.
Journal of the European Academy of Dermatology and Venereology : JEADV
Feb 26, 2024
BACKGROUND: Persistent facial erythema represents a significant complication in atopic dermatitis (AD) patients undergoing treatment with dupilumab. Stratifying patients based on the erythema course is crucial for elucidating heterogeneous phenotypes...
Machine Learning Models for the Diagnosis and Prognosis Prediction of High-Grade B-Cell Lymphoma.
Frontiers in immunology
May 24, 2022
High-grade B-cell lymphoma (HGBL) is a newly introduced category of rare and heterogeneous invasive B-cell lymphoma (BCL), which is diagnosed depending on fluorescence hybridization (FISH), an expensive and laborious analysis. In order to identify H...
A photonic crystal fiber-based fluorescence sensor for simultaneous and sensitive detection of lactic acid enantiomers.
Analytical and bioanalytical chemistry
Jan 13, 2022
A photonic crystal fiber (PCF)-based fluorescence sensor is developed for rapid and sensitive detection of lactic acid (LA) enantiomers in serum samples. The sensor is fabricated by chemical binding dual enzymes on the inner surface of the PCF with n...
Artificial Intelligence Predicts Severity of COVID-19 Based on Correlation of Exaggerated Monocyte Activation, Excessive Organ Damage and Hyperinflammatory Syndrome: A Prospective Clinical Study.
Frontiers in immunology
Aug 27, 2021
BACKGROUND: Prediction of the severity of COVID-19 at its onset is important for providing adequate and timely management to reduce mortality.
Using Unsupervised Machine Learning to Identify Age- and Sex-Independent Severity Subgroups Among Patients with COVID-19: Observational Longitudinal Study.
Journal of medical Internet research
May 27, 2021
BACKGROUND: Early detection and intervention are the key factors for improving outcomes in patients with COVID-19.
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