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Record W4245861045 · doi:10.1007/s12079-014-0238-6

Abstracts Canadian Connective Tissue Meeting London, Ontario, Canada, June 8‐10, 2014

2014· article· en· W4245861045 on OpenAlexafffundabout
Dominique Behrends, Cheng Li, ME Sullivan, Menglin Wang, GB Roby, Nadia Zayed, Chan Gao, Janet E. Henderson, Paul A. Martineau, Christina Raykha, Bing Siang Gan, Gregory B. Gloor, David B. O’Gorman, Gurpreet S. Baht, Puviindran Nadesan, Qingxia Wei, Heather Whetstone, Benjamin A. Alman, Shabana Amanda Ali, Mushriq Al‐Jazrawe, Erik Holm, Jane E. Aubin, Graeme Hunter, Frank Beier, Harvey Goldberg, Erik Holm, L. Lacroix, Yeyin Hu, Charles B. Owen, Irina Voronov

Bibliographic record

VenueJournal of Cell Communication and Signaling · 2014
Typearticle
Languageen
FieldMedicine
TopicTissue Engineering and Regenerative Medicine
Canadian institutionsWestern UniversityLunenfeld-Tanenbaum Research InstituteMount Sinai HospitalUniversity of TorontoSickKids FoundationMcGill University Health CentreLawson Health Research InstituteUniversity of CalgaryMcGill UniversityHospital for Sick ChildrenUniversity of British Columbia
FundersCanadian Institutes of Health ResearchChildren's Health Research Institute
KeywordsConnective tissueMedicineData sciencePathologyComputer science

Abstract

fetched live from OpenAlex

Field of interest: Connective tissue remodelling An estimated 25 % of fractures in young Canadians fail to heal adequately as a consequence of infection or other underlying factors. The incidence of mal-union and failed joint replacements in the elderly is even higher, as a result of inadequate endogenous healing mechanisms. There is a pressing need for innovative approaches to promote bone repair in cases where healing is predicted to be compromised. This will reduce the number of failed procedures and significantly reduce the economic burden associated with musculoskeletal disease in Canada. Although the primary role ascribed to mast cells is that of protagonist in allergic reactions, there is growing evidence that they also play pivotal roles in normal physiology. A number of early studies noted accumulation of mast cells in and around fracture callus. We tested the hypothesis that mast cells are involved in all phases of fracture repair. We tested the hypothesis that mast cells are involved in fracture repair by comparing bone repair in uni-cortical femoral window defects in mast cell deficient C57BL/6-KitW-sh/Wshmice and their wild type littermates. Cohorts of mice were euthanized at timed intervals (2, 4, 6 and 12 weeks) after surgery and bone healing was quantified using micro CT and histological analyses. Bone mineral content was analyzed with von Kossa stain, and alkaline phosphatase and tartrate resistant acid phosphatase was used to assess osteoblasts and osteoclasts activity respectively. Acidic toluidine blue staining identified mast cells with a high degree of specificity and safranin O and alizarin red stain was used to assess their stage of maturity. Bone regeneration in the mast cell deficient mice is significantly delayed and associated with an abnormal spatial distribution of the new bone, which led to non-unions in half of the cases. Less bone was found at the level of the cortex and more bone inside the medullary cavity. The quality of the regenerating cortical bone was lower in the mast cell deficient mice, as indicated by higher porosity, less osteocytes, lower connectivity and impaired trabecular characteristics. The histological analyses confirmed the poor quality bone shown by micro CT and suggested it may be due to uncoupling of osteoblast from osteoclast activity. The changing maturity, number and distribution of mast cells throughout the process of healing indicate that the role of mast cells depends on the stage of bone regeneration.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.628
Threshold uncertainty score0.345

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.009
GPT teacher head0.222
Teacher spread0.213 · 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 designNot applicable
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 routes3
Has abstractyes

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