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Glutathione

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Machine Learning-Enabled Time-Resolved Nanozyme-Encoded Recognition of Endogenous Mercaptans for Disease Diagnosis.

Analytical chemistry
With their important role in regulating intracellular redox balance and maintaining cell homeostasis, endogenous mercaptans are recognized as biomarkers of many diseases in clinical practice, and thus establishing efficient yet simple methods to dist...

Machine learning-assisted surface-enhanced raman spectroscopy for the rapid determination of the glutathione redox ratio.

The Analyst
Rapid and accurate detection of glutathione in its reduced (GSH) and oxidized (GSSG) forms is essential for monitoring oxidative stress in biological systems. Oxidative stress is a key indicator of various diseases, and glutathione plays a vital role...

Deep learning based prediction of species-specific protein S-glutathionylation sites.

Biochimica et biophysica acta. Proteins and proteomics
As a widespread and reversible post-translational modification of proteins, S-glutathionylation specifically generates the mixed disulfides between cysteine residues and glutathione, which regulates various biological processes including oxidative st...

Discovery of Small-Molecule Activators for Glucose-6-Phosphate Dehydrogenase (G6PD) Using Machine Learning Approaches.

International journal of molecular sciences
Glucose-6-Phosphate Dehydrogenase (G6PD) is a ubiquitous cytoplasmic enzyme converting glucose-6-phosphate into 6-phosphogluconate in the pentose phosphate pathway (PPP). The G6PD deficiency renders the inability to regenerate glutathione due to lack...

Deep learning algorithm reveals two prognostic subtypes in patients with gliomas.

BMC bioinformatics
BACKGROUND: Gliomas are highly complex and heterogeneous tumors, rendering prognosis prediction challenging. The advent of deep learning algorithms and the accessibility of multi-omic data represent a new approach for the identification of survival-s...

Predicting lifespan-extending chemical compounds for with machine learning and biologically interpretable features.

Aging
Recently, there has been a growing interest in the development of pharmacological interventions targeting ageing, as well as in the use of machine learning for analysing ageing-related data. In this work, we use machine learning methods to analyse da...

Bioinspired Iron Porphyrin Covalent Organic Frameworks-Based Nanozymes Sensor Array: Machine Learning-Assisted Identification and Detection of Thiols.

ACS applied materials & interfaces
Given the crucial role of thiols in maintaining normal physiological functions, it is essential to establish a high-throughput and sensitive analytical method to identify and quantify various thiols accurately. Inspired by the iron porphyrin active c...

A hybrid machine learning framework for functional annotation of mitochondrial glutathione transport and metabolism proteins in cancers.

BMC bioinformatics
BACKGROUND: Alterations of metabolism, including changes in mitochondrial metabolism as well as glutathione (GSH) metabolism are a well appreciated hallmark of many cancers. Mitochondrial GSH (mGSH) transport is a poorly characterized aspect of GSH m...

Deep machine learning-assisted MOF@COF fluorescence/colorimetric dual-mode intelligent ratiometric sensing platform for sensitive glutathione detection.

Talanta
Glutathione (GSH) levels have been linked to aging and the pathogenesis of various diseases, highlighting the necessity for the development of sensitive analytical methods for GSH to facilitate disease diagnosis and treatment. In this study, we synth...