AIMC Topic: Blood Proteins

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Identification of plasma proteins associated with seizures in epilepsy: A consensus machine learning approach.

PloS one
Blood-based biomarkers in epilepsy could constitute important research tools advancing neurobiological understanding and valuable clinical tools for better diagnosis and follow-up. An interesting question is whether biomarker patterns could contribut...

A correlational study of plasma galectin-3 as a potential predictive marker of postoperative delirium in patients with acute aortic dissection.

Scientific reports
This study aimed to demonstrate whether plasma galectin-3 could predict the development of postoperative delirium (POD) in patients with acute aortic dissection (AAD). Prospective, observational study. Cardiac surgery intensive care unit. Consecutive...

Quantitative detection of serum biochemical indexes via UV-Vis-NIRS combined with deep neural networks.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
To achieve rapid, cost-efficient, convenient and accurate detection of five clinical serum biochemical indexes, namely glucose (GLU), triglycerides (TG), total cholesterol (TC), total protein (TP) and albumin (ALB), ultraviolet-visible-near infrared ...

Plasma Proteomic Profiles Predict Individual Future Osteoarthritis Risk.

Arthritis & rheumatology (Hoboken, N.J.)
OBJECTIVE: Osteoarthritis (OA) is a widespread degenerative joint disease that causes a considerable socioeconomic burden. Despite progress in genetic and environmental insights, early diagnosis is still limited by the lack of evident symptoms during...

Machine learning approach on plasma proteomics identifies signatures associated with obesity in the KORA FF4 cohort.

Diabetes, obesity & metabolism
AIMS: This study investigated the role of plasma proteins in obesity to identify predictive biomarkers and explore underlying biological mechanisms.

Machine learning models for predicting interaction affinity energy between human serum proteins and hemodialysis membrane materials.

Scientific reports
Membrane incompatibility poses significant health risks, including severe complications and potential fatality. Surface modification of membranes has emerged as a pivotal technology in the membrane industry, aiming to improve the hemocompatibility an...

Performance and efficiency of machine learning models in analyzing capillary serum protein electrophoresis.

Clinica chimica acta; international journal of clinical chemistry
BACKGROUND AND OBJECTIVE: Serum protein electrophoresis (SPEP) plays a critical role in diagnosing diseases associated with M-proteins. However, its clinical application is limited by a heavy reliance on experienced experts.

MAGPIE: A Machine Learning Approach to Decipher Protein-Protein Interactions in Human Plasma.

Journal of proteome research
Immunoprecipitation coupled to tandem mass spectrometry (IP-MS/MS) methods are often used to identify protein-protein interactions (PPIs). While these approaches are prone to false positive identifications through contamination and antibody nonspecif...

A Plasma Proteomics-Based Model for Identifying the Risk of Postpartum Depression Using Machine Learning.

Journal of proteome research
Postpartum depression (PPD) poses significant risks to maternal and infant health, yet proteomic analyses of PPD-risk women remain limited. This study analyzed plasma samples from 30 healthy postpartum women and 30 PPD-risk women using mass spectrome...