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Record W2148307534 · doi:10.1183/09031936.05.00017305

Aerosol delivery of chemotherapy in an orthotopic model of lung cancer

2005· article· en· W2148307534 on OpenAlexaff
Frédéric Gagnadoux, Alain Le Pape, É. Lemarié, Stéphanie Lerondel, Isabelle Valo, Valérie Leblond, J.-L. Racineux, T. Urban

Bibliographic record

VenueEuropean Respiratory Journal · 2005
Typearticle
Languageen
FieldMedicine
TopicInhalation and Respiratory Drug Delivery
Canadian institutionsInstitut universitaire de cardiologie et de pneumologie de Québec
FundersLigue Contre le Cancer
KeywordsGemcitabineLung cancerChemotherapyMedicineCarcinomaAnimal modelLungPathologyNuclear medicineUrologyInternal medicine

Abstract

fetched live from OpenAlex

The aim of this study was to evaluate the effect on tumour growth of gemcitabine delivered by aerosol in an orthotopic model of lung carcinoma. Large cell carcinoma (NCI-H460) cells were implanted intrabronchially in 24 male BALB/c nude mice on day (d) 0. Aerosols were delivered once a week from d1 to d29 using an endotracheal sprayer. Altogether, 16 animals received gemcitabine at 8 (n=8) and 12 mg.kg-1 (n=8), and eight received a vehicle aerosol. Animals were sacrificed on d36 for histological examination. All animals in the vehicle group developed a large infiltrating carcinoma. Comparatively, four of 13 (31%) animals treated with gemcitabine had no visible tumour and nine of 13 (69%) had a smaller carcinoma with a mean+/-sem largest tumour diameter of 2.05+/-0.7 versus 5+/-0.3 mm in the vehicle group. Gemcitabine was well tolerated at 8 mg.kg-1. At 12 mg.kg-1, three cases of fatal pulmonary oedema were observed, prompting a dose reduction to 8 mg.kg-1 in the remaining animals. A dose effect was observed, with more marked tumour growth inhibition in the animals treated at 12 mg.kg-1 on d1 and d8. In conclusion, in this study, an animal model of aerosolised chemotherapy in lung cancer was developed and demonstrated inhibition of orthotopic tumour growth by aerosol delivery of gemcitabine.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.177
Threshold uncertainty score0.497

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 head0.034
GPT teacher head0.310
Teacher spread0.276 · 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 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

Citations58
Published2005
Admission routes1
Has abstractyes

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