Evidence map›Paper›PMID 34261061›Full record

ArticleCells, tissues, organs2022

A High-Throughput Mechanical Activator for Cartilage Engineering Enables Rapid Screening of in vitro Response of Tissue Models to Physiological and Supra-Physiological Loads.

Elisa Capuana, Davide Marino, Roberto Di Gesù, Vincenzo La Carrubba, Valerio Brucato, Rocky S Tuan, Riccardo Gottardi

Open access · hybridAbstract read
In one paragraph

Article in Cells, tissues, organs, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
1.7field-weighted citation impact, top 16% of its field
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

16 citing papers in PubMed, 23 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. [Effect of mechanical stimuli on physicochemical properties of joint fluid in osteoarthritis].Zhongguo xiu fu chong jian wai ke za zhi = Zhongguo xiufu chongjian waike zazhi = Chinese journal of reparative and reconstructive surgery · 2025
    Review
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Beginning of the era of Organ-on-Chip models in osteoarthritis research.Journal of clinical orthopaedics and trauma · 2024
    Article
  14. Article
  15. Review
  16. Mechanical environment forBiomaterials translational · 2023
    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

7 authors at 3 institutions in 3 countries.

Elisa CapuanaDepartment of Engineering, University of Palermo, Palermo, Italy.
Davide MarinoDepartment of Engineering, University of Palermo, Palermo, Italy.
Roberto Di GesùCenter for Cellular and Molecular Engineering, Department of Orthopedic Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.
Vincenzo La CarrubbaDepartment of Engineering, University of Palermo, Palermo, Italy.
Valerio BrucatoDepartment of Engineering, University of Palermo, Palermo, Italy.
Rocky S TuanCenter for Cellular and Molecular Engineering, Department of Orthopedic Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.
Riccardo GottardiCenter for Cellular and Molecular Engineering, Department of Orthopedic Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.
University of Pittsburgh · USChildren's Hospital of Philadelphia · USUniversity of Palermo · IT

Funding

3-D Osteochondral Micro-tissue to Model Pathogenesis of OsteoarthritisU18TR000532 · NCATS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI TUAN, ROCKY S · 2012 to 2013
$788k
NCATS NIH HHS U18 TR000532
6 · The paper itself

Abstract

Articular cartilage is crucially influenced by loading during development, health, and disease. However, our knowledge of the mechanical conditions that promote engineered cartilage maturation or tissue repair is still incomplete. Current in vitro models that allow precise control of the local mechanical environment have been dramatically limited by very low throughput, usually just a few specimens per experiment. To overcome this constraint, we have developed a new device for the high throughput compressive loading of tissue constructs: the High Throughput Mechanical Activator for Cartilage Engineering (HiT-MACE), which allows the mechanoactivation of 6 times more samples than current technologies. With HiT-MACE we were able to apply cyclic loads in the physiological (e.g., equivalent to walking and normal daily activity) and supra-physiological range (e.g., injurious impacts or extensive overloading) to up to 24 samples in one single run. In this report, we compared the early response of cartilage to physiological and supra-physiological mechanical loading to the response to IL-1β exposure, a common but rudimentary in vitro model of cartilage osteoarthritis. Physiological loading rapidly upregulated gene expression of anabolic markers along the TGF-β1 pathway. Notably, TGF-β1 or serum was not included in the medium. Supra-physiological loading caused a mild catabolic response while IL-1β exposure drove a rapid anabolic shift. This aligns well with recent findings suggesting that overloading is a more realistic and biomimetic model of cartilage degeneration. Taken together, these findings showed that the application of HiT-MACE allowed the use of larger number of samples to generate higher volume of data to effectively explore cartilage mechanobiology, which will enable the design of more effective repair and rehabilitation strategies for degenerative cartilage pathologies.

Indexed as

Cartilage, ArticularOsteoarthritisChondrocytesHumansTissue EngineeringTransforming Growth Factor beta1Transforming Growth Factor beta1CartilageIn vitro modelMechanical activationMechanobiologyPost-traumatic osteoarthritis

Identifiers

PMID34261061
PMCPMC9843549
OpenAlexW3182317831

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.