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Record W2153512461 · doi:10.1177/016173460102300203

High Frequency Acoustic Parameters of Human and Bovine Articular Cartilage following Experimentally-Induced Matrix Degradation

2001· article· en· W2153512461 on OpenAlexaff
G.A. Joiner, Earl R. Bogoch, Kenneth P. H. Pritzker, Michael D. Buschmann, Anik Chevrier, F. Stuart Foster

Bibliographic record

VenueUltrasonic Imaging · 2001
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsPolytechnique MontréalSt. Michael's HospitalMount Sinai HospitalHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsArticular cartilageDegradation (telecommunications)Materials scienceHigh frequency ultrasoundCartilageMatrix (chemical analysis)Composite materialAcousticsBiomedical engineeringAnatomyUltrasoundEngineeringPhysicsMedicineElectronic engineeringOsteoarthritisPathology

Abstract

fetched live from OpenAlex

Matrix degradation and proteoglycan loss in articular cartilag eare features of early osteoarthritis. To determine the effect of matrix degradation and proteoglycan loss on ultrasound propagation in cartilage, we used papain and interleukin-1alpha to degrade the matrix proteoglycans of human and bovine cartilage samples, respectively. There is also minor collagen alteration associated with these chemical degradation methods. We compared the speed of sound and frequency dependent attenuation (20-40 MHz) of control and experimental paired samples. We found that a loss of matrix proteoglycans and collagen disruption resulted in a 20-30% increase in the frequency dependent attenuation and a 2% decrease in the speed of sound in both human and bovine cartilage. We conclude that the frequency dependent attenuation and speed of sound in articular cartilage are sensitive to experimental modification of the matrix proteoglycans and collagen. These findings suggest that ultrasound can potentially be used to detect morphologic changes in articular cartilage associated with the progression of osteoarthritis.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.698

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.274
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations61
Published2001
Admission routes1
Has abstractyes

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