Evidence map›Paper›PMID 41104104›Full record

ArticleFrontiers in bioengineering and biotechnology2025

Computational simulations of endocrine bone diseases related to pathological glandular PTH secretion using a multi-scale bone cell population model.

Corinna Modiz, Natalia M Castoldi, Stefan Scheiner, Javier Martínez-Reina, Jose L Calvo-Gallego, Vittorio Sansalone, Saulo Martelli, Peter Pivonka

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Article in Frontiers in bioengineering and biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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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

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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.

2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. 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

8 authors.

Corinna ModizSchool of Mechanical, Medical and Process Engineering, Queensland University of Technology, Brisbane, QLD, Australia.
Natalia M CastoldiSchool of Mechanical, Medical and Process Engineering, Queensland University of Technology, Brisbane, QLD, Australia.
Stefan ScheinerInstitute for Mechanics of Materials and Structures, TU Wien, Vienna, Austria.
Javier Martínez-ReinaDepartamento de Ingeniería Mecánica y Fabricación, Universidad de Sevilla, Sevilla, Spain.
Jose L Calvo-GallegoDepartamento de Ingeniería Mecánica y Fabricación, Universidad de Sevilla, Sevilla, Spain.
Vittorio SansaloneUniv Paris Est Creteil, Univ Gustave Eiffel, CNRS, UMR 8208, MSME, F-94010, Créteil, France.
Saulo MartelliSchool of Mechanical, Medical and Process Engineering, Queensland University of Technology, Brisbane, QLD, Australia.
Peter PivonkaSchool of Mechanical, Medical and Process Engineering, Queensland University of Technology, Brisbane, QLD, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Bone diseases significantly impact global health by compromising skeletal integrity and quality of life. In disease states linked to parathyroid hormone (PTH) glandular secretion, disrupted PTH patterns typically promote osteoclast proliferation, leading to increased bone resorption. Methods: While mathematical modeling has proven valuable in analyzing bone remodeling, current bone cell population models oversimplify PTH secretion by assuming constant levels, limiting their ability to represent disorders characterized by variations in PTH pulse characteristics. To address this, we present a novel semi-coupled approach integrating a two-state PTH receptor model with an established bone cell population model. Instead of conventional Hill-type functions, we implement a cellular activity function derived from the receptor model, incorporating pulsatile PTH patterns, cell dynamics, and intracellular communication pathways. Results: Our numerical simulations demonstrate the model's capability to reproduce various catabolic bone diseases, providing realistic changes in bone volume fraction over a 1-year period. Notably, while direct implementation of PTH disease progression in the bone cell population model fails to capture diseases only characterized by altered pulse duration and baseline, such as glucocorticoid-induced osteoporosis, our semi-coupled approach successfully models these conditions. Discussion: This physiologically more realistic approach to endocrine disease modeling offers potential implications for optimizing therapeutic interventions and understanding disease progression mechanisms.

Indexed as

bone cell dynamicsdisease modelingparathyroid hormoneparathyroid hormone/parathyroid hormone-related protein receptorpulsatile signal characteristics

Identifiers

PMID41104104
PMCPMC12521151

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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 Socratic graph.