Evidence map›Paper›PMID 34904305›Full record

ArticleNMR in biomedicine2022

Evaluation of enzymatic proteoglycan loss and collagen degradation in human articular cartilage using ultrashort echo time-based biomarkers: A feasibility study.

Lidi Wan, Xin Cheng, Adam C Searleman, Ya-Jun Ma, Jonathan H Wong, R Scott Meyer, Jiang Du, Guangyu Tang, Eric Y Chang

Open access · greenAbstract read
In one paragraph

Article in NMR in biomedicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.2field-weighted citation impact, top 20% 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

7 citing papers in PubMed, 10 citations in OpenAlex.

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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

9 authors at 4 institutions in 2 countries.

Lidi WanDepartment of Radiology, University of California, San Diego, California, USA.ORCID 0000-0001-6851-4583
Xin ChengDepartment of Radiology, University of California, San Diego, California, USA.
Adam C SearlemanDepartment of Radiology, University of California, San Diego, California, USA.
Ya-Jun MaDepartment of Radiology, University of California, San Diego, California, USA.ORCID 0000-0003-0830-9232
Jonathan H WongDepartment of Radiology, University of California, San Diego, California, USA.
R Scott MeyerOrthopaedic Surgery Service, VA San Diego Healthcare System, San Diego, California, USA.
Jiang DuDepartment of Radiology, University of California, San Diego, California, USA.ORCID 0000-0002-9203-2450
Guangyu TangDepartment of Radiology, Tenth People's Hospital of Tongji University, Shanghai, China.
Eric Y ChangDepartment of Radiology, University of California, San Diego, California, USA.
University of California San Diego · USTongji University · CNJinan University · CNVA San Diego Healthcare System · US

Funding

Quantitative UTE MR Imaging: Sensitive Biomarkers for OsteoarthritisR01AR062581 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI DU, JIANG · 2013 to 2022
$4.1M
Traning Clinical Scientists in Radiological ImagingT32EB005970 · NIBIB · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Eric Y Chang, Rebecca Ann Rakow-Penner · 2007 to 2026
$3.2M
UTE Magnetic Resonance Imaging: New Biomarkers for Multiple SclerosisR01NS092650 · NINDS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI DU, JIANG · 2015 to 2019
$1.9M
Three-dimensional Ultrashort Echo Time Magnetic Resonance Imaging of EnthesesR01AR075825 · NIAMS · VETERANS MEDICAL RESEARCH FDN/SAN DIEGO · PI CHANG, ERIC Y · 2019 to 2023
$1.8M
Three-Dimensional UTE Magnetic Resonance Imaging of the Osteochondral JunctionR21AR075851 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI MA, YAJUN · 2020 to 2021
$376k
Quantitative Magnetic Resonance Imaging of Human Rotator Cuff TendonI01CX001388 · VA · VA SAN DIEGO HEALTHCARE SYSTEM · PI CHANG, ERIC Y · 2016 to 2024
–
Quantitative Measurement of Joint pH with Magnetic Resonance ImagingI01RX002604 · VA · VA SAN DIEGO HEALTHCARE SYSTEM · PI CHANG, ERIC Y · 2018 to 2022
–
CSRD VA I01 CX001388NIAMS NIH HHS R01 AR062581NIAMS NIH HHS R01 AR075825NIAMS NIH HHS R21 AR075851NIBIB NIH HHS T32 EB005970NINDS NIH HHS R01 NS092650RRD VA I01 RX002604
6 · The paper itself

Abstract

The objective of the current study was to investigate the feasibility of quantitative 3D ultrashort echo time (UTE)-based biomarkers in detecting proteoglycan (PG) loss and collagen degradation in human cartilage. A total of 104 cartilage samples were harvested for a trypsin digestion study (n = 44), and a sequential trypsin and collagenase digestion study (n = 60), respectively. Forty-four cartilage samples were randomly divided into a trypsin digestion group (tryp group) and a control group (phosphate-buffered saline [PBS] group) (n = 22 for each group) for the trypsin digestion experiment. The remaining 60 cartilage samples were divided equally into four groups (n = 15 for each group) for sequential trypsin and collagenase digestion, including PBS + Tris (incubated in PBS, then Tris buffer solution), PBS + 30 U col (incubated in PBS, then 30 U/ml collagenase [30 U col] with Tris buffer solution), tryp + 30 U col (incubated in trypsin solution, then 30 U/ml collagenase with Tris buffer solution), and tryp + Tris (incubated in trypsin solution, then Tris buffer solution). The 3D UTE-based MRI biomarkers included T

Indexed as

Cartilage, ArticularBiomarkersCollagenCollagenasesFeasibility StudiesHumansImaging, Three-DimensionalMacromolecular SubstancesMagnetic Resonance ImagingProteoglycansTromethamineTrypsinBiomarkersCollagenCollagenasesMacromolecular SubstancesProteoglycansTromethamineTrypsincartilagemagnetic resonance imagingosteoarthritis

Identifiers

PMID34904305
PMCPMC9042587
OpenAlexW4200122703

What OpenQuestion holds

Textmetadata
LicenceTDM
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.