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Record W2156123937 · doi:10.3415/vcot-11-01-0006

Effects of a novel hydrogel on equine bone healing: A pilot study

2012· article· en· W2156123937 on OpenAlexfundno aff
Jennifer M. Cohen, Julie B. Engiles, Midge Leitch, David M. Nunamaker, Louise L. Southwood

Bibliographic record

VenueVeterinary and Comparative Orthopaedics and Traumatology · 2012
Typearticle
Languageen
FieldMedicine
TopicPeriodontal Regeneration and Treatments
Canadian institutionsnot available
FundersCanadian Mental Health Association
KeywordsMedicineBone healingGelatin spongeBiocompatibilityImplantDentistrySurgery

Abstract

fetched live from OpenAlex

OBJECTIVE: To examine the efficacy and biocompatibility of a thiolated gelatin-thiolated carboxymethyl hyaluronan (CMHA-SGX) sponge as an osteoconductive device in an equine second and fourth metacarpal bone defect model. METHODS: Seven millimetre segmental ostectomies were created bilaterally in the second and fourth metacarpal bones of four horses. The left and right metacarpal defects were randomly assigned to (1) be filled with a CMHA-SGX sponge (treated) or (2) were left unfilled (control). The duration of the study was nine weeks. Bone healing was evaluated using serial radiology, as well as histologically and histomorphometrically. Data were analyzed using an analysis of variance (ANOVA). The level of significance was p<0.05. RESULTS: Serial radiographic evaluation revealed improved healing in the treated compared to the control defects at weeks eight and nine (p = 0.02). This finding was not corroborated histologically. Histomorphometry did not reveal any significant differences in healing between experimental groups. The CMHA-SGX sponge did not inhibit bone formation, induce local inflammation or lead to surgical site infection. CLINICAL SIGNIFICANCE: While further optimization to improve osteoconductive properties should be considered, the CMHA-SGX sponge appears to be a biocompatible orthopaedic implant and its use as a carrier for osteogenic proteins warrants further investigation.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.126
Threshold uncertainty score0.527

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.149
GPT teacher head0.357
Teacher spread0.207 · 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 designObservational
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

Citations10
Published2012
Admission routes1
Has abstractyes

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