Systematic Mining of Bioactive Compounds for Wound Healing From <i>Cayratia Japonica</i> Exosome-Like Nanovesicles: A Workflow Combining LC-MS and DeepSeek Models.

ABSTRACT:

Background

Plant-derived exosome-like nanovesicles (P-ELNs) effectively deliver bioactive compounds due to their high biocompatibility and low immunogenicity. While liquid chromatography-mass spectrometry (LC-MS) profiles compounds in complex samples, its analysis of large datasets remains limited by traditional methods. Recent advances in large language models (LLMs) and domain-specific systems have enhanced Chinese biomedical data processing and cross-modal pharmaceutical research.

Objective

This study aimed to create a multimodal framework of LC-MS combined with DeepSeek models for data mining of compounds with wound-healing properties from exosome-like nanovesicles derived from Cayratia japonica (CJ-ELNs).

Methods

LC-MS identified compounds enriched in CJ (n=3) an

SUBMITTER: Fu Q 

PROVIDER: S-EPMC12784863 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature