The DOI matches its Crossref record.
Analysis of cartilage matrix fixed charge density and three-dimensional morphology via contrast-enhanced microcomputed tomography
Open accessAbstract
Small animal models of osteoarthritis are often used for evaluating the efficacy of pharmacologic treatments and cartilage repair strategies, but noninvasive techniques capable of monitoring matrix-level changes are limited by the joint size and the low radiopacity of soft tissues. Here we present a technique for the noninvasive imaging of cartilage at micrometer-level resolution based on detecting the equilibrium partitioning of an ionic contrast agent via microcomputed tomography. The approach exploits electrochemical interactions between the molecular charges present in the cartilage matrix and an ionic contrast agent, resulting in a nonuniform equilibrium partitioning of the ionic contrast agent reflecting the proteoglycan distribution. In an in vitro model of cartilage degeneration we observed changes in x-ray attenuation magnitude and distribution consistent with biochemical and histological analyses of sulfated glycosaminoglycans, and x-ray attenuation was found to be a strong predictor of sulfated glycosaminoglycan density. Equilibration with the contrast agent also permits direct in situ visualization and quantification of cartilage surface morphology. Equilibrium partitioning of an ionic contrast agent via microcomputed tomography thus provides a powerful approach to quantitatively assess 3D cartilage composition and morphology for studies of cartilage degradation and repair.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
HANDSCHUH, S., BEISSER, C. J., RUTHENSTEINER, B., & METSCHER, B. D. (2017) · Journal of Microscopy · doi:10.1111/jmi.12543 · Cited by 48
Metadata
- Authors
- Palmer, A. W., Guldberg, R. E., & Levenston, M. E.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2006-12-19
- Volume
- 103
- Issue
- 51
- Pages
- 19255-19260
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2131907878
- Cited by
- 291
- References
- 0
- FWCI
- 5.58
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.