Evidence map›Paper›PMID 42115556›Full record

ArticleBiomechanics and modeling in mechanobiology2026

A mathematical model of osteocyte network control of bone mechanical adaptation.

Adel Mehrpooya, Vivien J Challis, Pascal R Buenzli

Abstract read
In one paragraph

Article in Biomechanics and modeling in mechanobiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Rethinking osteocyte modelsFrontiers in bioengineering and biotechnology · 2026
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Adel MehrpooyaSchool of Mathematical Sciences, Queensland University of Technology (QUT), Brisbane, Australia.ORCID http://orcid.org/0000-0002-5394-4262
Vivien J ChallisSchool of Mathematical Sciences, Queensland University of Technology (QUT), Brisbane, Australia.ORCID http://orcid.org/0000-0001-6240-5319
Pascal R BuenzliSchool of Mathematical Sciences, Queensland University of Technology (QUT), Brisbane, Australia. pascal.buenzli@qut.edu.au.ORCID http://orcid.org/0000-0003-3962-5393

Funding

Australian Research Council DP190102545Queensland University of Technology Postgraduate Research Award
6 · The paper itself

Abstract

The osteocyte network embedded in bone tissues plays a central role in the control of bone adaptation to mechanical loads and micro-damage repair. However, much remains to be understood about the precise mechanisms by which the osteocyte network regulates bone formation and bone resorption based on the propagation of biochemical signals emitted in response to mechanical stimulus. In this work, we propose a one-dimensional computational model of bone mechanical adaptation based on the propagation of signalling molecules through a dynamic osteocyte network. The osteocyte network is extended during bone formation and reduced during bone resorption, which affects the generation and propagation of the signalling molecules to the bone surface. We explore how this osteocyte-based model of bone mechanosensation and mechanoresponse gives rise to effective Wolff's laws, in which overloaded bone is consolidated and underloaded bone is removed. We find that the discrete addition and removal of osteocytes significantly affects signalling molecules propagating to the bone surface and leads to new bone adaptation behaviours compared to earlier models, including partial bone recovery following an unloading and reloading cycle and the emergence of a minimum threshold of mechanical stress below which all bone is resorbed. While many extensions of this mathematical model are possible, it provides a first illustration of how the osteocyte network could act as a dynamic embedded control network for bone adaptation to mechanical loads.

Indexed as

Adaptation, PhysiologicalBone and BonesOsteocytesStress, MechanicalBone RemodelingModels, BiologicalBone remodellingMechanobiologyMechanostatNetwork growthSignal propagationWolff’s law

Identifiers

PMID42115556
PMCPMC13160984

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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 OpenQuestion graph.