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Record W2092063881 · doi:10.2174/1876388x01103010019

125I-Iododeoxyuridine for the Treatment of a Brain Tumor Model: Selection of Conditions for Optimal Effectiveness

2011· article· en· W2092063881 on OpenAlexafffund
Shirley Lehnert

Bibliographic record

VenueThe Open Nuclear Medicine Journal · 2011
Typearticle
Languageen
FieldMedicine
TopicRadiopharmaceutical Chemistry and Applications
Canadian institutionsMcGill University
FundersCanadian Institutes of Health ResearchCancer Research Society
KeywordsSelection (genetic algorithm)Computational biologyMedicineComputer scienceBiologyArtificial intelligence

Abstract

fetched live from OpenAlex

The intent of this study was to optimise conditions for the use of 125 IUdR in the treatment of cancer.The radiopharmaceutical plus a biomodulator, methotrexate (MTX) was delivered by intra-tumoral injection of a thermosensitive hydrogel forming a slow release depot of 125 IUdR and MTX in the tumor.Methods: The C6 rat glioblastoma was implanted intra-cranially.A chitosan polymer was used to formulate a biodegradable and biocompatible implant for controlled intra-tumoral delivery of 125 IUdR plus MTX.Results: Intratumoral implant of hydrogel loaded with 7.0 -7.4 MBq of 125 IUdR resulted in survival of 20% of treated animals to 180 days after tumor implant.Simultaneous delivery of MTX increased the number of rats that were effectively cured, to 40%.Conclusion: Using an injectable thermolabile hydrogel as vehicle for 125 IUdR delivery a higher level of tumor control was achieved in a rat glioma model than had been previously reported.

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 score0.003

Distilled classifier scores by category (both heads)

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 head0.115
GPT teacher head0.402
Teacher spread0.287 · 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

Citations2
Published2011
Admission routes2
Has abstractyes

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