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Record W4283654560 · doi:10.3389/fbioe.2022.883268

Delamination of the Annulus Fibrosus of the Intervertebral Disc: Using a Bovine Tail Model to Examine Effect of Separation Rate

2022· article· en· W4283654560 on OpenAlexafffund
K. Josh Briar, John G. McMorran, Diane E. Gregory

Bibliographic record

VenueFrontiers in Bioengineering and Biotechnology · 2022
Typearticle
Languageen
FieldMedicine
TopicSpine and Intervertebral Disc Pathology
Canadian institutionsWilfrid Laurier University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsIntervertebral discAnnulus (botany)Delamination (geology)Separation (statistics)Materials scienceBiomedical engineeringAnatomyMedicineComposite materialBiologyComputer scienceMachine learning

Abstract

fetched live from OpenAlex

The intervertebral disc (IVD) is a complex structure, and recent evidence suggests that separations or delamination between layers of the annulus may contribute to degeneration development, a common cause of low back pain The purpose of the present experiment was to quantify the mechanical response of the layer-adjoining interlamellar matrix at different rates of separation. Understanding the rate-dependency of the interlamellar matrix, or the adhesion between adjacent layers of the disc, is important as the spine experiences various loading velocities during activities of daily living. Twelve discs were dissected from four bovine tails (three extracts per tail). Two multi-layered annulus samples were collected from each IVD (total = 24, mean bond width = 3.82 ± 0.96 mm) and randomly assigned to a 180° peel test at one of three delamination rates; 0.05 mm/s, 0.5 mm/s, or 5 mm/s. Annulus extracts were found to have similar maximal adhesion strengths ( p = 0.39) and stiffness ( p = 0.97) across all rate conditions. However, a significant difference in lamellar adhesion strength variability was observed between the 5 mm/s condition (0.96 N/mm ± 0.31) when compared to the 0.5 mm/s (0.50 N/mm ± 0.19) and 0.05 mm/s (0.37 N/mm ± 0.13) conditions ( p < 0.05). Increased variability may be indicative of non-uniform strength due to inconsistent adhesion throughout the interlamellar matrix, which is exacerbated by increased rates of loading. The observed non-uniform strength could possibly lead to a scenario more favourable to the development of microtrauma, and eventual delamination.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.496
Threshold uncertainty score0.265

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.009
GPT teacher head0.252
Teacher spread0.242 · 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

Citations6
Published2022
Admission routes2
Has abstractyes

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