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Effect of cyclooxygenase inhibitors in a xenograft model of canine mammary tumours

2010· article· en· W1975266651 on OpenAlexafffund
Karine Sonzogni-Desautels, Deborah W. Knapp, Eva A. Sartin, Monique Doré

Bibliographic record

VenueVeterinary and Comparative Oncology · 2010
Typearticle
Languageen
FieldMedicine
TopicInflammatory mediators and NSAID effects
Canadian institutionsUniversité de MontréalCegep de Saint Hyacinthe
FundersHealth Canada
KeywordsCyclooxygenaseCancer researchMedicineMammary tumorPharmacologyInternal medicineChemistryEnzymeCancerBiochemistry

Abstract

fetched live from OpenAlex

Inhibition of cyclooxygenase-2 (COX-2) represents a possible avenue for the prevention and/or treatment of some cancers. Our goal was to compare the effect of a selective inhibitor of COX-2, deracoxib, and a COX-1 and -2 inhibitor, piroxicam, on the growth of canine mammary tumours in a murine model. CMT-9 was used to induce xenografts in nude mice. Mice were treated with piroxicam (0.6 mg kg(-1)), deracoxib (6 mg kg(-1)) or a control solution. Tumour volumes between 0 and 24 days post-treatment showed no significant difference between all groups. A second series of experiments was performed with a higher dose of piroxicam (0.9 mg kg(-1)). Tumour volumes between 14 and 21 days post-treatment were significantly smaller in piroxicam-treated mice compared with controls. These results demonstrate that COX inhibition reduced the growth of canine mammary cancer xenografts in mice, suggesting that COX inhibitors could have a positive effect in dogs.

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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.031
GPT teacher head0.336
Teacher spread0.305 · 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

Citations13
Published2010
Admission routes2
Has abstractyes

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