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Record W7133019527

Radiation-induced craniofacial bone growth inhibition: Investigation of the mechanisms and radioprotection in vitro

2007· dissertation· W7133019527 on OpenAlexfundno aff
Artur Gevorgyan

Bibliographic record

VenueTSpace · 2007
Typedissertation
Language
FieldMedicine
TopicOral health in cancer treatment
Canadian institutionsnot available
FundersNational Cancer InstituteCanadian Institutes of Health ResearchHospital for Sick Children
KeywordsAmifostineCraniofacialOsteoblastHead and neckIn vitroCalvariaOsteoradionecrosisBone growth
DOInot available

Abstract

fetched live from OpenAlex

Radiation resulted in a dose-dependent inhibition of survival and two-fold changes in osteoblast-like phenotype. Pre-treatment with Amifostine or WR-1065 (in primary and clonal cells, respectively) resulted in a significantly improved survival at clinically relevant radiation doses and drug concentrations. In this work, the cellular and functional mechanisms of radiation effects with and without radioprotection were investigated in cultured craniofacial osteoblast-like cells in order to understand the pathophysiology of radiation-induced craniofacial bone growth inhibition. Primary periosteal osteoblast-like cells were obtained from the infant rabbit orbitozygomatic complex following radiation with or without intravenous Amifostine. MC3T3-E1 mouse calvarial osteoblastic cells underwent gamma-radiation with and without WR-2721 or WR-1065 (10-3-10-7 M, 30 minutes before radiation). Survival, viability and osteoblast phenotype were assessed. This work establishes that Amifostine affords significant radioprotection of craniofacial osteoblast-like cells. This is important in devising pharmacological strategies for preventing impaired cramofacial bone growth in the survivors of head and neck cancer.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0020.000

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 head0.026
GPT teacher head0.348
Teacher spread0.322 · 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 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
Published2007
Admission routes1
Has abstractyes

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