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Record W2088283720 · doi:10.1139/y09-017

Modulation of the sensitivity in Chinese hamster cells to photons and fast neutrons by cisplatin, vinblastine, and bleomycin

2009· article· en· W2088283720 on OpenAlexvenueno aff
B.B. Mokaleng, John Akudugu

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2009
Typearticle
Languageen
FieldMedicine
TopicRadiation Therapy and Dosimetry
Canadian institutionsnot available
Fundersnot available
KeywordsVinblastineBleomycinCisplatinChinese hamsterHamsterPhysicsPhotonChemistryBiologyBiophysicsIn vitroMedicineMolecular biologyInternal medicineOpticsChemotherapyBiochemistry

Abstract

fetched live from OpenAlex

Normal tissue toxicity resulting from chemoradiotherapy is of significant clinical concern. This study used normal Chinese hamster fibroblasts from lung (V79) and ovary (CHO-K1) to assess the modulation of cellular response to photons and neutrons by cisplatin, vinblastine, and bleomycin. Based on the colony formation assay, the drug concentration corresponding to 50% cell survival (EC50) of V79 cells was 1.50 +/- 0.21 micromol/L for cisplatin, 0.97 +/- 0.06 nmol/L for vinblastine, and 1.68 +/- 0.11 micromol/L for bleomycin. The corresponding values for CHO-K1 cells were significantly lower for vinblastine (0.54 +/- 0.02 nmol/L) and bleomycin (0.49 +/- 0.13 micromol/L), but not for cisplatin (1.57 +/- 0.20 micromol/L). No radiosensitivity enhancement was apparent when cells were exposed to p(66)/Be neutrons or photons (60Co gamma-rays) in the presence of these drugs at EC50 concentrations. These data suggest that concurrent use of these drugs with radiation for the treatment of lung and ovarian diseases radiation does not exacerbate radiation-induced normal tissue toxicity, regardless of the quality of radiation. The relatively higher sensitivity of the ovarian cells to vinblastine and bleomycin might constitute a limitation in the use of these drugs for the treatment of lung lesions.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.869
Threshold uncertainty score0.230

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.005
GPT teacher head0.252
Teacher spread0.247 · 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

Citations4
Published2009
Admission routes1
Has abstractyes

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