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Record W2053886536 · doi:10.1155/2012/923914

DNA-Platinum Thin Films for Use in Chemoradiation Therapy Studies

2011· article· en· W2053886536 on OpenAlexafffund
Mohammad Rezaee, Elahe Alizadeh, Darel J. Hunting, Léon Sanche

Bibliographic record

VenueBioinorganic Chemistry and Applications · 2011
Typearticle
Languageen
FieldMedicine
TopicMetal complexes synthesis and properties
Canadian institutionsUniversité de Sherbrooke
FundersCanadian Institutes of Health Research
KeywordsDNAChemistryPlatinumDNA damageAnalytical Chemistry (journal)BiochemistryChromatographyCatalysis

Abstract

fetched live from OpenAlex

Dry films of platinum chemotherapeutic drugs covalently bound to plasmid DNA (Pt-DNA) represent a useful experimental model to investigate direct effects of radiation on DNA in close proximity to platinum chemotherapeutic agents, a situation of considerable relevance to understand the mechanisms underlying concomitant chemoradiation therapy. In the present paper we determine the optimum conditions for preparation of Pt-DNA films for use in irradiation experiments. Incubation conditions for DNA platination reactions have a substantial effect on the structure of Pt-DNA in the films. The quantity of Pt bound to DNA as a function of incubation time and temperature is measured by inductively coupled plasma mass spectroscopy. Our experiments indicate that chemical instability and damage to DNA in Pt-DNA samples increase when DNA platination occurs at 37(°)C for 24 hours, the condition which has been extensively used for in vitro studies. Platination of DNA for the formation of Pt-DNA films is optimal at room temperature for reaction times less than 2 hours. By increasing the concentration of Pt compounds relative to DNA and thus accelerating the rate of their mutual binding, it is possible to prepare Pt-DNA samples containing known concentrations of Pt while reducing DNA degradation caused by more lengthy procedures.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.135
GPT teacher head0.292
Teacher spread0.157 · 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

Citations17
Published2011
Admission routes2
Has abstractyes

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