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Record W2154136969

Synergism in concomitant chemoradiotherapy of cisplatin and oxaliplatin and their liposomal formulation in the human colorectal cancer HCT116 model.

2012· article· en· W2154136969 on OpenAlexaff
Thititip Tippayamontri, Rami Kotb, Benoît Paquette, Léon Sanche

Bibliographic record

VenuePubMed · 2012
Typearticle
Languageen
FieldMedicine
TopicEffects of Radiation Exposure
Canadian institutionsCentre Hospitalier Universitaire de SherbrookeUniversité de Sherbrooke
Fundersnot available
KeywordsOxaliplatinCisplatinColorectal cancerPharmacologyChemoradiotherapyConcomitantChemistryRadiation therapyChemotherapyCancer researchCancerMedicineInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: We choose to test the effect of associating chemo-radiotherapy at 8 h (the highest level of DNA-platinum) and 48 h (the lower level of DNA-platinum) to clarify if irradiation at the maximum DNA-platinum concentration could improve the synergism. MATERIALS AND METHODS: Growth inhibition of the human colorectal cancer cell line HCT116 treated with cisplatin, oxaliplatin, Lipoplatin™ and Lipoxal™ plus gamma-radiation was determined by a colony formation assay. The synergism was evaluated using the combination index method. RESULTS: For 8 h and 48 h exposure to cisplatin or Lipoplatin™, followed by irradiation, drug concentrations higher than IC(50) were found to be synergistic, while a lower than IC(50) concentration was antagonistic. For oxaliplatin, exposure to a concentration above IC(50) for 8 h was synergistic, while the exposure to oxaliplatin (at any concentrations) for 48 h was antagonistic. Lipoxal™ significantly improved synergism compared to its parent drugs. All tested platinum drugs sensitize radiation-treated HCT116 cells by inducing G(2) phase. CONCLUSION: The difference of drug concentrations and the time interval between drug administration and radiotherapy could give different results in chemoradiation therapy.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.303

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 head0.019
GPT teacher head0.267
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 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

Citations25
Published2012
Admission routes1
Has abstractyes

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