AIMC Topic: Polysaccharides
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Building simplified cancer subtyping and prediction models with glycan gene signatures.
Cell reports methods
Aug 11, 2025
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
Aug 5, 2025
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
Jul 14, 2025
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
Apr 30, 2025
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
Mar 8, 2025
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...
Advanced machine learning-driven characterization of new natural cellulosic Lablab purpureus fibers through PCA and K-means clustering techniques.
International journal of biological macromolecules
Mar 2, 2025
The increasing demand for sustainable and eco-friendly materials has spurred significant interest in natural fibers as alternatives to synthetic reinforcements in composite applications. This study aims to explore the potential of Lablab purpureus fi...
Extraction of polysaccharides from Camellia oleifera leaves by dual enzymes combined with deep eutectic solvents screened by ANN and COSMO-RS.
International journal of biological macromolecules
Feb 16, 2025
Camellia oleifera leaves were byproduct of the C. oleifera industry which was rich in polysaccharides. Deep eutectic solvent-dual enzyme system (DES-dEAE) was established to achieve the simultaneous hydrolysis reaction of dual enzymes and DES extract...
GNOme, an ontology for glycan naming and subsumption.
Analytical and bioanalytical chemistry
Feb 8, 2025
While GlyTouCan provides stable identifiers for referencing glycan structures, they are not organized semantically. GNOme, a glycan naming and subsumption ontology and a member of the OBOFoundry, organizes GlyTouCan accessions for automated reasoning...
Design and optimization of tamarind seed polysaccharide-based scaffold for tissue engineering applications using statistical modeling and machine learning, and it's in-vitro validation.
International journal of biological macromolecules
Jan 30, 2025
This study explores the development and optimization of a novel biomaterial scaffold for tissue engineering, composed of Tamarind seed polysaccharide (TSP), Hydroxypropyl methylcellulose (HPMC), Chitosan (CS), and Sodium alginate (ALG). Scaffold prop...
Differentiation of Citri Reticulatae Pericarpium varieties via HPLC fingerprinting of polysaccharides combined with machine learning.
Food chemistry
Jan 27, 2025
To accurately and reliably distinguish different varieties of Citri Reticulatae Pericarpium (CRP), we propose a novel classification strategy combining polysaccharide fingerprinting and machine learning (ML). First, extraction conditions are optimize...
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