AIMC Topic: Polysaccharides

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GPMassSimulator: A Graphormer-Based Method for Glycopeptide MS/MS Spectra Prediction.

Analytical chemistry
Protein glycosylation is a critical post-translational modification involved in numerous biological processes and disease states. While mass spectrometry has emerged as the primary tool for glycoproteomics analysis, the structural complexity and hete...

Anthocyanins loaded bilayer films based on polysaccharides assisted by machine learning for fish freshness monitoring.

Food chemistry
Novel multifunctional packaging for monitoring and maintaining food freshness has been developed. Bilayer films based on polysaccharides incorporating red cabbage anthocyanins were prepared. Anthocyanins were encapsulated in the inner layer based on ...

GlyTrait: A Versatile Bioinformatics Tool for Glycomics Analysis.

Journal of proteome research
We developed GlyTrait, a Python-based framework designed to enhance Glycomics analysis through the innovative calculation and interpretation of derived traits from -glycome data. Glycomics research often grapples with the interpretability and biologi...

Bacterial polysaccharides in the food industry: Synthesis-structure-properties relationships, AI-driven innovations, regulatory challenges, and bioeconomy prospects.

Carbohydrate polymers
Bacterial polysaccharides have attracted considerable interest due to their rapid production, customizable properties, and suitability for large-scale manufacturing. Unlike plant or algal polysaccharides, they can be efficiently synthesized through f...

Classification of small blue round cell tumors by integrating peptide and N-glycan mass imaging spectrometric profiles.

Analytica chimica acta
BACKGROUND: Small blue round cell tumor (SBRCT) is an umbrella term for several tumor types of completely different cellular origin and differentiation. Members of this tumor group share a common morphological phenotype, which is characterized by sma...

Building simplified cancer subtyping and prediction models with glycan gene signatures.

Cell reports methods
We identified a gene panel comprising 71 glycosyltransferases (GTs) that alter glycan patterns on cancer cells as they become more virulent. When these cancer-pattern GTs (CPGTs) were run through an algorithm trained on The Cancer Genome Atlas, they ...

Integrating Deep Learning and Real-Time Imaging to Visualize In Situ Self-Assembly of Self-Healing Interpenetrating Polymer Networks Formed by Protein and Polysaccharide Fibers.

ACS applied materials & interfaces
Fibrillar protein hydrogels are promising sustainable biomaterials for biomedical applications, but their practical use is often limited by insufficient mechanical strength and stability. To address these challenges, we transformed native proteins in...

Library-based virtual match-between-runs quantification in GlyPep-Quant improves site-specific glycan identification.

Nature communications
Glycosylation changes are closely related to various diseases, including cancer. The quantitative analysis of site-specific glycans at proteomics scale remains challenging due to low glycopeptide spectra interpretation. Here, we present GlyPep-Quant,...

In-situ conversion of hemicellulose to furfural by Lewis acid-enhanced deep eutectic solvents to maintain stable pretreatment performance and trigger profitable biorefining processes.

International journal of biological macromolecules
Deep eutectic solvents (DESs) are gaining attention for lignocellulose pretreatment, yet screening methods and stable cyclic processes remain underexplored. This study compared solubility and machine learning to predict delignification, screening the...

Targeted conversion of cellulose and hemicellulose macromolecules in the phosphoric acid/acetone/water system: An exploration of machine learning evaluation and product prediction.

International journal of biological macromolecules
The simultaneous hydrolysis of cellulose and hemicellulose involves trade-offs, making precise control of hydrolysis products crucial for sustainable development. This study employed three machine learning (ML) models-Random Forest (RF), Extreme Grad...