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Record W7019357830

Functional assessment of articular cartilage using injury-induced changes in solute transport and improved mechanical characterization

2014· dissertation· en· W7019357830 on OpenAlexfundno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2014
Typedissertation
Languageen
FieldComputer Science
TopicBayesian Methods and Mixture Models
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCartilageOsteoarthritisArticular cartilageArticular cartilage damageCartilage damageExtracellular matrixMatrix (chemical analysis)
DOInot available

Abstract

fetched live from OpenAlex

Articular cartilage is avascular and comprised mainly of a water-rich extracellular matrix (ECM); thus solute and fluid transport through cartilage ECM are crucial to cartilage physiology. Once injured, cartilage has a limited capacity for self-repair, often leading to long-term degeneration and osteoarthritis due to focal damage. Modern strategies for cartilage repair are promising, however they rely upon detection of tissue damage at an early stage following injury. This thesis explores relationships between cartilage injury, matrix damage, and associated changes in fluid and solute transport through cartilage. Results indicate avenues for improvement upon in vitro and in vivo methods for cartilage functional assessment, and early detection of focal lesions.First, an investigation was performed into the effects of a well-characterized in-vitro model for cartilage injury on the transport properties of a wide range of solutes, including fluorescent solutes and contrast agents. Mechanical injury was associated with a significant increase in effective diffusivity versus uninjured explants for all solutes studied. In contrast, mechanical injury had no effects on effective partition coefficients for most solutes tested. This distinction is important because measurement of equilibrium partitioning underlies many of the methods currently in use for clinical imaging of cartilage, but we found it to be much less sensitive to cartilage injury than non-equilibrium diffusive transport. Our results emphasized enhanced diffusive transport across the articular surface of injured cartilage, which may have important physiological implications for injury and repair situations. These support development of novel non-equilibrium methods for identification of focal cartilage lesions by contrast agent-based clinical imaging. Second, a new methodology for efficient in vitro mechanical characterization of soft tissue and gel samples was developed, which provides some important advantages over existing methods. Using a novel solution to the poroelastic governing equations for creep valid at early times combined with the classical solution for the stress relaxation problem, this method allows for measurement of gel elastic modulus and hydraulic permeability with some inherent redundancy that improves confidence in measured parameters.This thesis therefore emphasizes the development of new approaches for functional assessment of articular cartilage tissue in the laboratory and in the clinic. Improved observation and quantification of solute transport and poroelastic mechanics in cartilage will contribute to improved tissue functional assessment leading to a better understanding of cartilage physiology and more accurate identification of the stages of degenerative disease.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.094
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.024
GPT teacher head0.272
Teacher spread0.248 · 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.

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

Citations0
Published2014
Admission routes1
Has abstractyes

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