AIMC Topic: Biomarkers

Clear Filters Showing 81 to 90 of 2219 articles

Deep Learning-Decoded Raman Spectroscopy for Hour-Scale iPSC Pluripotency Assessment via Lipid-Protein Biomarkers.

Analytical chemistry
Rapid and label-free evaluation of induced pluripotent stem cell (iPSC) pluripotency is critical for advancing regenerative medicine and clinical applications. Although traditional genomics- and proteomics-based pluripotency assessment methods are re...

Ultrasensitive SERS-LFA for the detection of neurofilament light chain and machine learning-assisted Alzheimer's disease classification.

Nanoscale
Neurofilament light chain (NfL), a cytoskeletal protein released during neuronal injury, is a promising biomarker, with elevated levels consistently associated with disease severity and progression in multiple neurological conditions, including Alzhe...

HMGCR-driven cholesterol metabolism dysregulation and its role in osteoarthritis diagnosis and immune regulation.

Biochemical and biophysical research communications
Osteoarthritis (OA) is the most common degenerative joint disease, and the complexity of its molecular mechanisms has hindered the development of effective diagnostic and therapeutic strategies. In this study, we integrated five independent OA RNA-se...

Tb(III)-Functionalized Hydrogen-Bonded Organic Framework with Dual-Emission for Liver Health Biomarker Detection and a Smartphone-Integrated Bionic Visual Diagnostic Platform.

Analytical chemistry
Developing a sensitive analytical platform for monitoring tiopronin (MPG), its metabolite 2-mercaptopropionic acid (MPA), and the key liver biomarker glutathione (GSH) is crucial for liver health assessment. Here, an artificial intelligence-assisted ...

Artificial Intelligence-Coupled Self-Calibrating SERS Spectroscopy for Robust Clinical Diagnosis of Diabetes and Associated Complications.

Analytical chemistry
Diabetes mellitus (DM), a prevalent metabolic disorder, poses significant diagnostic and therapeutic challenges, especially, in the early stage diagnosis of diabetes related complications. Accurate early stage diagnosis of diabetes and its complicati...

Multi-omics-based decoding of circulating biomarkers in amyotrophic lateral sclerosis and risks in environmental toxins.

BMC pharmacology & toxicology
BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by the interplay of genetic and environmental factors, and currently, there there is a lack of effective diagnostic or therapeutic strategies available...

Web based AI-driven framework combining multi-modal data with CNN and LLM for Parkinson's disease diagnosis.

Scientific reports
Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by a wide spectrum of motor and non-motor symptoms, often leading to delayed or inaccurate diagnosis. Conventional diagnostic methods frequently suffer from limited se...

Label-free estimation of regulatory T cell activation markers using Raman spectroscopy with machine learning.

Scientific reports
Regulatory T cells are a class of T lymphocytes which respond to activation signals by expanding their cell numbers, and whose culturing and expansion are of significant clinical interest. Cellular activation states are used to inform process control...

Prediction of clinical outcomes of ST-elevated myocardial infarction patients using atmospheric solids analysis probe mass spectrometry and machine learning.

The Analyst
: Analysis of small molecule metabolites found in blood plasma of patients undergoing treatment for STEMI has the potential to be used as a clinical diagnostic and prognostic tool, capable of predicting disease progression, risk of negative outcomes,...