AIMC Topic: Glucose

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Transfer learning for non-invasive glucose prediction under albumin interference in NIR spectroscopy.

Computers in biology and medicine
This study proposes a transfer learning framework for non-invasive glucose prediction using diffuse-reflectance near-infrared (NIR) spectroscopy, along with an in vitro phantom model that incorporates a pump-driven circulation system. Lipofundin and ...

AI-Assisted Microfluidic Paper-Based Analytical Device with Au-Pt Nanoparticles for Multiplex, Interference-Resistant Quantification of Urinary Biomarkers.

Analytical chemistry
Urinary glucose, creatinine, and uric acid are vital biomarkers for diabetes and kidney disease management. However, multiplex point-of-care detection faces challenges due to insufficient sensitivity in complex urine matrices and signal cross-talk fr...

Mechanism of triptolide in the treatment of gastric cancer with diabetes through JAK2/STAT3 pathway.

European journal of pharmacology
Univariate and multivariate Cox analyses revealed a correlation between diabetes and the prognosis of gastric cancer patients (p < 0.05). Using bioinformatics, Serine/threonine-protein kinase pim-1 (PIM1) was identified as the core target gene of tri...

Stable intracranial imaging of dura mater-engrafted pancreatic islet cells in awake mice.

Nature communications
By transplanting pancreatic islets onto the dura mater of the mouse brain, we establish a microscopy platform that enables longitudinal intravital imaging of otherwise optically inaccessible tissue. The system combines a cranial window with an air-cu...

Multi-omics unravel heterogeneity of glucose metabolism reprogramming in gastric cancer.

Clinical and experimental medicine
Gastric cancer (GC) presents striking survival disparities: 85-100% for early-stage versus only 5-20% for advanced disease. Glucose metabolic reprogramming (GMS)-a cancer hallmark linked to the Warburg effect-fuels tumor progression and immune evasio...

Ultraviolet-visible spectral characterization and ANN modeling of aqueous sugar solutions: Clinical and environmental perspectives.

PloS one
The characterization of aqueous sugar solutions using optical techniques offers a non-invasive, rapid, and reagent-free approach for concentration monitoring in both analytical and environmental contexts. In this study, aqueous D-glucose solutions at...

Characteristics of brain glucose metabolism in Parkinson's disease patients with freezing of gait: a study based on F-FDG PET imaging and deep learning.

BMC neurology
OBJECTIVE: Freezing of gait (FOG) is a common gait disorder in the advanced stages of Parkinson's disease (PD), closely associated with impaired balance and executive function. This study aimed to investigate specific changes in brain glucose metabol...

Estimated glucose disposal rate predicts frailty through diabetes: Evidence from machine learning and mediation models in NHANES.

PloS one
OBJECTIVE: As an emerging insulin resistance marker, the relationship between estimated glucose disposal rate (eGDR) and frailty needs further exploration. This study examines the eGDR-frailty link, develops a machine learning predictive model to add...

Glucostats: an efficient Python library for glucose time series feature extraction and visual analysis.

BMC bioinformatics
BACKGROUND: The advancement of technology and continuous glucose monitoring (CGM) systems has introduced several computational and technical challenges for clinicians and researchers. The growing volume of CGM data necessitates the development of eff...

Label-Free SERS Platform Assisted by Machine Learning for Multi-Target Detection and Physiological State Classification in Sweat.

Analytical chemistry
The detection of sweat metabolites is crucial for health monitoring, disease screening, and personalized medicine. Traditional methods encounter challenges like low metabolite concentrations, complex biological matrices, and difficulty in achieving m...