Evidence map›Paper›PMID 38586151›Full record

ArticleCurrent opinion in biomedical engineering2024

Mechanome-Guided Strategies in Regenerative Rehabilitation.

Diego Jacho, Eda Yildirim-Ayan

Abstract read
In one paragraph

Article in Current opinion in biomedical engineering, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
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

2 authors.

Diego JachoDepartment of Bioengineering, University of Toledo, 2801 W. Bancroft Street, Toledo, OH, USA.
Eda Yildirim-AyanDepartment of Bioengineering, University of Toledo, 2801 W. Bancroft Street, Toledo, OH, USA.

Funding

Technology Development P2CHD086843 · NICHD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI AMBROSIO, FABRISIA · 2015 to 2024
$10.5M
NICHD NIH HHS P2C HD086843
6 · The paper itself

Abstract

Regenerative Rehabilitation represents a multifaceted approach that merges mechanobiology with therapeutic intervention to harness the body's intrinsic tissue repair and regeneration capacity. This review delves into the intricate interplay between mechanical loading and cellular responses in the context of musculoskeletal tissue healing. It emphasizes the importance of understanding the phases involved in translating mechanical forces into biochemical responses at the cellular level. The review paper also covers the mechanosensitivity of macrophages, fibroblasts, and mesenchymal stem cells, which play a crucial role during regenerative rehabilitation since these cells exhibit unique mechanoresponsiveness during different stages of the tissue healing process. Understanding how mechanical loading amplitude and frequency applied during regenerative rehabilitation influences macrophage polarization, fibroblast-to-myofibroblast transition (FMT), and mesenchymal stem cell differentiation is crucial for developing effective therapies for musculoskeletal tissues. In conclusion, this review underscores the significance of mechanome-guided strategies in regenerative rehabilitation. By exploring the mechanosensitivity of different cell types and their responses to mechanical loading, this field offers promising avenues for accelerating tissue healing and functional recovery, ultimately enhancing the quality of life for individuals with musculoskeletal injuries and degenerative diseases.

Indexed as

Cell-specificityFibroblastMacrophagesMechanical ForcesMechanical LoadingMechanomeMechanotherapyMechanotransductionMusculoskeletal tissuesMyofibroblastRegenerative RehabilitationStem Cells

Identifiers

PMID38586151
PMCPMC10993906

What OpenQuestion holds

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Registered trials

None linked

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.