AIMC Topic: Biomarkers

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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...

Novel protocol for metabolomics data normalization and biomarker discovery in human tears.

Clinical chemistry and laboratory medicine
OBJECTIVES: Human tear analysis holds promise for biomarker discovery, but its clinical utility is hindered by the lack of standardized reference values, limiting interindividual comparisons. This study aimed at developing a protocol for normalizing ...

Embracing the changes and challenges with modern early drug discovery.

Expert opinion on drug discovery
INTRODUCTION: The landscape of early drug discovery is rapidly evolving, fueled by significant advancements in artificial intelligence (AI) and machine learning (ML), which are transforming the way drugs are discovered. As traditional drug discovery ...

Determining IFI44 as a key lupus nephritis's biomarker through bioinformatics and immunohistochemistry.

Renal failure
BACKGROUND: Lupus nephritis (LN) emerges as a severe complication of systemic lupus erythematosus (SLE), significantly affecting patient survival. Despite improvements in treatment reducing LN's morbidity and mortality, existing therapies remain subo...

Machine learning predicts spinal cord stimulation surgery outcomes and reveals novel neural markers for chronic pain.

Scientific reports
Spinal cord stimulation (SCS) is a well-accepted therapy for refractory chronic pain. However, predicting responders remain a challenge due to a lack of objective pain biomarkers. The present study applies machine learning to predict which patients w...

Identification and validation of endoplasmic reticulum stress-related diagnostic biomarkers for type 1 diabetic cardiomyopathy based on bioinformatics and machine learning.

Frontiers in endocrinology
BACKGROUND: Diabetic cardiomyopathy (DC) is a serious complication in patients with type 1 diabetes mellitus and has become a growing public health problem worldwide. There is evidence that endoplasmic reticulum stress (ERS) is involved in the pathog...

Development of a Disease Model for Predicting Postoperative Delirium Using Combined Blood Biomarkers.

Annals of clinical and translational neurology
OBJECTIVE: Postoperative delirium, a common neurocognitive complication after surgery and anesthesia, requires early detection for potential intervention. Herein, we constructed a multidimensional postoperative delirium risk-prediction model incorpor...

Tlalpan 2020 Case Study: Enhancing Uric Acid Level Prediction with Machine Learning Regression and Cross-Feature Selection.

Nutrients
Uric acid is a key metabolic byproduct of purine degradation and plays a dual role in human health. At physiological levels, it acts as an antioxidant, protecting against oxidative stress. However, excessive uric acid can lead to hyperuricemia, cont...