Hiring in life sciences? Share your open positions with our professional community. Read more Close

Advertisement

Exploratory bone-brain transcriptomic associations and an ODE-based digital-twin framework for fracture healing.

Created on 12 Oct 2026

Authors

Chao Ma, Wei Lu, Ruipeng Guo

Published in

Brain research. Pages 150597. Oct 11, 2026. Epub Oct 11, 2026.

Abstract

Fracture healing is generally viewed as a local tissue-regeneration process, although skeletal injury can also elicit systemic immune, vascular, and neural responses. We used a stratified analytical strategy combining reanalysis of public transcriptomic datasets, descriptive single-nucleus profiling, and an ordinary differential equation (ODE)-based simulation of fracture healing to examine possible associations between adverse bone phenotypes and Alzheimer disease. In the primary random-effects meta-analysis of three retained human bone-related binary cohorts, 72 prespecified panel genes were measured in all three cohorts; BMP10 and ANGPT1 had the smallest adjusted P values. In the separate GSE48350 whole-brain dataset, 6 of 84 mapped target genes had nominal P < 0.05. Descriptive single-nucleus RNA-sequencing analysis of GSE138852 showed within-dataset, cell-type-specific expression patterns across annotated neural cell populations. The eight-state ODE prototype, built on prespecified assumptions, generated fracture-healing trajectories and scenario-dependent model outputs. Tissue-expression and genetic analyses provided additional exploratory context for the selected genes. These analyses define a hypothesis-generating framework for studying skeletal-neural associations after fracture.

PMID:
42860235
Bibliographic data and abstract were imported from PubMed on 12 Oct 2026.

Read full publication at:
Please sign in to see all details.

Advertisement

Stats

  • Community rating n/a 0 votes
  • Reviewers' rating n/a 0 votes
  • Your rating

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

  • Recommendations n/a n/a positive of 0 vote(s)
  • Views 8
  • Comments 0

Recommended by

  • No recommendations yet.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.

Advertisement