MétaCan
Menu
Back to cohort
Record W4308581852

Defective bone repair in mast cell deficient mice with c-Kit loss of function

2014· article· en· W4308581852 on OpenAlexaff
DA Behrends, L Cheng, MB Sullivan, Michael H. Wang, GB Roby, N Zayed, Chenlu Gao, JE Henderson, PA Martineau

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2014
Typearticle
Languageen
FieldImmunology and Microbiology
TopicMast cells and histamine
Canadian institutionsMontreal General Hospital
Fundersnot available
KeywordsMast cellFunction (biology)Bone marrowCell biologyImmunologyChemistryBiology
DOInot available

Abstract

fetched live from OpenAlex

KitW-sh mice carry an inactivating mutation in the gene encoding the receptor for stem cell factor, which is expressed at high levels on the surface of haematopoietic precursor cells. The mutation results in mast cell deficiency, a variety of defects in innate immunity and poorly defined abnormalities in bone. The present study was designed to characterise healing of a cortical window defect in skeletally mature KitW-sh mice using high-resolution micro computed tomographic imaging and histological analyses. The cortical bone defect healed completely in all wild type mice but failed to heal in about half of the KitW-sh mice by 12 weeks post-operative. Defective healing was associated with premature and excessive expression of TRAP positive cells embedded in fibrous marrow but with little change in ALP activity. Immuno-histochemical analyses revealed reduced CD34 positive vascular endothelial cells and F4/80 positive macrophages at 1 and 2 weeks post-operative. Impaired bone healing in the KitW-sh mice was therefore attributed to altered catabolic activity, impaired re-vascularisation and compromised replacement of woven with compact bone.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.062
GPT teacher head0.400
Teacher spread0.338 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueDOAJ (DOAJ: Directory of Open Access Journals)Same topicMast cells and histamineFrench-language works237,207