ArticlebioRxiv : the preprint server for biology2025
Integration of localized microbiome, metabolome, and clinical datasets predicts healing in chronic wounds among veterans.
Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
8 authors.
Funding
Abstract
The chronic wound microenvironment consists of a complex milieu of host cells, microbial species, and metabolites. While much is known about wound microbiomes, our knowledge of metabolic landscapes influencing wound healing is limited. Furthermore, integrating complex datasets into predictive models of wound healing is almost non-existent. Microbial rRNA and total metabolites were extracted from 45 diabetic foot ulcers (DFU) debridement samples from 13 patients, with 25 from non-healing wounds and 20 from healing wounds that remained closed for over 30 days. 16S rRNA sequencing and global metabolomics were performed and clinical metadata collected. Healing outcome was modeled as a function of three blocks of features (N = 21 clinical, 634 microbiome, and 865 metabolome) using DIABLO (
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.