AIMC Topic: Energy Metabolism

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Optimizing intervertebral disc cell metabolic phenotyping with machine learning and artificial neural networks.

Scientific reports
Biological phenotyping of cellular metabolism is essential for deciphering health and disease states. The Seahorse XF analyzer enables direct measurement of oxygen consumption rate (OCR) and extracellular acidification rate (ECAR), providing insight ...

Plasma metabolomics disentangles T2DM- and CAD-specific dysmetabolism and identifies potential biomarkers for CAD risk escalation in diabetic patients.

Cardiovascular diabetology
BACKGROUND: Type 2 diabetes mellitus (T2DM) is a major driver of coronary artery disease (CAD). Prior studies often conflate T2DM- and CAD-specific metabolic alterations, limiting insights into CAD pathogenesis in T2DM. This study aimed to distinguis...

Estimation of daily energy requirements using a hybrid artificial intelligence model.

Scientific reports
Accurately estimating energy requirements is critical for individuals to maintain a healthy life. Traditional methods may be time-consuming, complex, low in accuracy, and costly, thus creating a need for new approaches. This study explores the applic...

From past to future: a review of methods for assessing physical activity energy expenditure.

Journal of health, population, and nutrition
BACKGROUND: Physical activity energy expenditure (PAEE) assessment is important for helping individuals maintain energy balance. This study adopts a technological evolution perspective to systematically examine the historical evolution and current pr...

Interpretable deep learning for personalized energy expenditure prediction using ECG and acceleration signals in incremental exercise.

Scientific reports
Energy expenditure (EE) assessment is crucial in both sports science and health management. However, current EE prediction models often overlook individual differences and lack dynamic correlation analysis between multi-modal data and EE. Building up...

Characterization of SPTLC2 as a key driver promoting microglial activation and energy metabolism reprogramming after ischemic stroke through bulk and single-cell analyses combined with experimental validation.

Cell biology and toxicology
BACKGROUND: Ischemic stroke (IS) stands as a principal contributor to high rates of sickness and death. The condition's pathological development is complicated, featuring mechanisms like mitochondrial impairment and the activation of microglial cells...

Energy constraints and neural strategy transitions in Alzheimer's: A game-theoretic model.

Journal of theoretical biology
While many mechanisms have been proposed to drive Alzheimer's disease, particularly the accumulation of amyloid plaques and hyperphosphorylation of tau proteins, emerging evidence suggests that they may be the byproducts of earlier damage rather than...

Cuproptosis induced by curcumin interfering with proliferation and energy metabolism in colorectal cancer: 3D tumor model and computational simulations reveal curcumin inhibition of HSPD1 and CALCOCO2.

European journal of pharmacology
PURPOSE: Colorectal cancer is a highly aggressive malignancy characterized by complex tumor micro-environments and significant drug resistance. We highlighted the critical role of curcumin in inhibiting tumor growth and migration, inducing cuproptosi...

Energy consumption analysis and prediction in exercise training based on accelerometer sensors and deep learning.

Scientific reports
This study aims to enhance the accuracy and efficiency of energy consumption prediction during exercise training and address the limitations of existing methods in terms of data feature extraction, model complexity, and adaptability to practical appl...

Calibration and Validation of Machine Learning Models for Physical Behavior Characterization: Protocol and Methods for the Free-Living Physical Activity in Youth (FLPAY) Study.

JMIR research protocols
BACKGROUND: Wearable activity monitors are increasingly used to characterize physical behavior. The development and validation of these characterization methods require criterion-labeled data typically collected in a laboratory or simulated free-livi...