Navigation auf zora.uzh.ch

Search ZORA

ZORA (Zurich Open Repository and Archive)

Hyperphysiological compression of articular cartilage induces an osteoarthritic phenotype in a cartilage-on-a-chip model

Occhetta, Paola; Mainardi, Andrea; Votta, Emiliano; Vallmajo-Martin, Queralt; Ehrbar, Martin; Martin, Ivan; Barbero, Andrea; Rasponi, Marco (2019). Hyperphysiological compression of articular cartilage induces an osteoarthritic phenotype in a cartilage-on-a-chip model. Nature Biomedical Engineering, 3(7):545-557.

Abstract

Owing to population aging, the social impact of osteoarthritis (OA)-the most common musculoskeletal disease-is expected to increase dramatically. Yet, therapy is still limited to palliative treatments or surgical intervention, and disease-modifying OA (DMOA) drugs are scarce, mainly because of the absence of relevant preclinical OA models. Therefore, in vitro models that can reliably predict the efficacy of DMOA drugs are needed. Here, we show, using a newly developed microphysiological cartilage-on-a-chip model that enables the application of strain-controlled compression to three-dimensional articular cartilage microtissue, that a 30% confined compression recapitulates the mechanical factors involved in OA pathogenesis and is sufficient to induce OA traits. Such hyperphysiological compression triggers a shift in cartilage homeostasis towards catabolism and inflammation, hypertrophy, and the acquisition of a gene expression profile akin to those seen in clinical osteoarthritic tissue. The cartilage on-a-chip model may enable the screening of DMOA candidates.

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Clinic for Obstetrics
Dewey Decimal Classification:610 Medicine & health
Scopus Subject Areas:Life Sciences > Biotechnology
Physical Sciences > Bioengineering
Health Sciences > Medicine (miscellaneous)
Physical Sciences > Biomedical Engineering
Physical Sciences > Computer Science Applications
Language:English
Date:July 2019
Deposited On:10 Jan 2020 13:57
Last Modified:22 Dec 2024 02:36
Publisher:Springer
ISSN:2157-846X
OA Status:Closed
Publisher DOI:https://doi.org/10.1038/s41551-019-0406-3
PubMed ID:31160722

Metadata Export

Statistics

Citations

Dimensions.ai Metrics
133 citations in Web of Science®
144 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

5 downloads since deposited on 10 Jan 2020
2 downloads since 12 months
Detailed statistics

Authors, Affiliations, Collaborations

Similar Publications