Evidence map›Paper›PMID 37052844›Full record

ReviewAdvances in experimental medicine and biology2023

Understanding the Influence of Local Physical Stimuli on Chondrocyte Behavior.

Byumsu Kim, Lawrence J Bonassar

Abstract readReview
PubMed Publisher
In one paragraph

Review in Advances in experimental medicine and biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. 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

2 authors.

Byumsu KimSibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, NY, USA.
Lawrence J BonassarSibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, NY, USA. lb244@cornell.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Investigating the mechanobiology of chondrocytes is challenging due to the complex micromechanical environment of cartilage tissue. The innate zonal differences and poroelastic properties of the tissue combined with its heterogeneous composition create spatial- and temporal-dependent cell behavior, which further complicates the investigation. Despite the numerous challenges, understanding the mechanobiology of chondrocytes is crucial for developing strategies for treating cartilage related diseases as chondrocytes are the only cell type within the tissue. The effort to understand chondrocyte behavior under various mechanical stimuli has been ongoing over the last 50 years. Early studies examined global biosynthetic behavior under unidirectional mechanical stimulus. With the technological development in high-speed confocal imaging techniques, recent studies have focused on investigating real-time individual and collective cell responses to multiple / combined modes of mechanical stimuli. Such efforts have led to tremendous advances in understanding the influence of local physical stimuli on chondrocyte behavior. In addition, we highlight the wide variety of experimental techniques, spanning from static to impact loading, and analysis techniques, from biochemical assays to machine learning, that have been utilized to study chondrocyte behavior. Finally, we review the progression of hypotheses about chondrocyte mechanobiology and provide a perspective on the future outlook of chondrocyte mechanobiology.

Indexed as

Cartilage, ArticularChondrocytesCartilageChondrocyteMechanobiology

Identifiers

PMID37052844

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.