AIMC Topic: Biomarkers

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PARP activity in peripheral blood lymphocytes as a predictive biomarker for PARP inhibition in tumor tissues - A population pharmacokinetic/pharmacodynamic analysis of rucaparib.

Clinical pharmacology in drug development
PURPOSE: Rucaparib is a potent Poly (ADP-ribose) Polymerase (PARP) inhibitor currently under clinical development. The objectives of this analysis were to establish population PK and PK/PD models for rucaparib, and to evaluate the predictability of P...

Prediction of Anti-inflammatory Plants and Discovery of Their Biomarkers by Machine Learning Algorithms and Metabolomic Studies.

Planta medica
Nonsteroidal anti-inflammatory drugs are the most used anti-inflammatory medicines in the world. Side effects still occur, however, and some inflammatory pathologies lack efficient treatment. Cyclooxygenase and lipoxygenase pathways are of utmost imp...

A machine learning heuristic to identify biologically relevant and minimal biomarker panels from omics data.

BMC genomics
BACKGROUND: Investigations into novel biomarkers using omics techniques generate large amounts of data. Due to their size and numbers of attributes, these data are suitable for analysis with machine learning methods. A key component of typical machin...

Machine learning framework for early MRI-based Alzheimer's conversion prediction in MCI subjects.

NeuroImage
Mild cognitive impairment (MCI) is a transitional stage between age-related cognitive decline and Alzheimer's disease (AD). For the effective treatment of AD, it would be important to identify MCI patients at high risk for conversion to AD. In this s...

Understanding migraine using dynamic network biomarkers.

Cephalalgia : an international journal of headache
BACKGROUND: Mathematical modeling approaches are becoming ever more established in clinical neuroscience. They provide insight that is key to understanding complex interactions of network phenomena, in general, and interactions within the migraine-ge...

A multi-technique approach to bridge electronic case report form design and data standard adoption.

Journal of biomedical informatics
BACKGROUND AND OBJECTIVE: The importance of data standards when integrating clinical research data has been recognized. The common data element (CDE) is a consensus-based data element for data harmonization and sharing between clinical researchers, i...

Identification of mitochondria metabolism-related biomarkers associated with the development of rheumatoid arthritis using bioinformatics: An observational study.

Medicine
Rheumatoid arthritis (RA) is a systemic inflammatory autoimmune disorder that has serious physical and mental health implications. It is evident that disruptions to mitochondrial function have a considerable impact on the survival, activation, and di...

Predictive markers for the efficacy of CAR T-cell therapy: the interplay between CAR T-cell fitness and systemic immunity.

Blood advances
Chimeric antigen receptor (CAR) T-cell therapy has revolutionized the therapeutic landscape for relapsed or refractory lymphoid malignancies, achieving remarkable rates of durable remission. Despite this success, significant variability among patient...

Identification and Validation of Phagocytosis-Regulating Factors as Potential Prognostic and Diagnostic Biomarkers for Intracerebral Hemorrhage Through Single-Cell and Bulk Transcriptomic.

FASEB journal : official publication of the Federation of American Societies for Experimental Biology
Intracerebral hemorrhage (ICH) is a major cause of death and disability worldwide. Despite treatment advances, reliable prognostic biomarkers are still lacking. While phagocytosis regulation is implicated in ICH pathogenesis, its potential for diagno...

An Interpretable Machine Learning Model Based on Metabolomics for Predicting Plaque Burden in Cryptogenic Stroke.

FASEB journal : official publication of the Federation of American Societies for Experimental Biology
Cryptogenic stroke represents 25%-40% of ischemic strokes, with many cases harboring unrecognized large artery atherosclerosis (LAA) requiring specific secondary prevention. In this multicenter pilot study, we developed a metabolomics-based machine l...