Evidence map›Paper›PMID 40868851›Full record

ArticleLife (Basel, Switzerland)2025

From Myofascial Chains to the Polyconnective Network: A Novel Approach to Biomechanics and Rehabilitation Based on Graph Theory.

Daniele Della Posta, Immacolata Belviso, Jacopo Junio Valerio Branca, Ferdinando Paternostro, Carla Stecco

Abstract read
In one paragraph

Article in Life (Basel, Switzerland), 2025. 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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. 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

5 authors.

Daniele Della PostaThe Anatomical Network APS, Via Fermo 2c, 00182 Rome, Italy.ORCID 0000-0002-2271-0324
Immacolata BelvisoDepartment of Psychology and Health Sciences, Telematic University Pegaso, 80143 Naples, Italy.
Jacopo Junio Valerio BrancaDepartment of Experimental and Clinical Medicine, University of Florence, 50134 Florence, Italy.ORCID 0000-0003-3179-0706
Ferdinando PaternostroDepartment of Experimental and Clinical Medicine, University of Florence, 50134 Florence, Italy.ORCID 0000-0003-3566-3499
Carla SteccoDepartment of Neuroscience, Institute of Human Anatomy, University of Padova, 35141 Padova, Italy.ORCID 0000-0002-8767-4555

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, the concept of the myofascial network has transformed biomechanical understanding by emphasizing the body as an integrated, multidirectional system. This study advances that paradigm by applying graph theory to model the osteo-myofascial system as an anatomical network, enabling the identification of topologically central nodes involved in force transmission, stability, and coordination. Using the aNETomy model and the BIOMECH 3.4 database, we constructed an undirected network of 2208 anatomical nodes and 7377 biomechanical relationships. Centrality analysis (degree, betweenness, and closeness) revealed that structures such as the sacrum and thoracolumbar fascia exhibit high connectivity and strategic importance within the network. These findings, while derived from a theoretical modeling approach, suggest that such key nodes may inform targeted treatment strategies, particularly in complex or compensatory musculoskeletal conditions. The proposed concept of a polyconnective skeleton (PCS) synthesizes the most influential anatomical hubs into a functional core of the system. This framework may support future clinical and technological applications, including integration with imaging modalities, real-time monitoring, and predictive modeling for personalized and preventive medicine.

Indexed as

anatomical networkbiomechanical modelingfunctional anatomymyofascial networkosteo-myofascial system

Identifiers

PMID40868851
PMCPMC12387315

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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.