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Record W2136114658 · doi:10.3109/09553002.2015.1068458

Assessing patient characteristics and radiation-induced non-targeted effects in vivo for high dose-rate (HDR) brachytherapy

2015· article· en· W2136114658 on OpenAlexaff
Christine Pinho, Emilia Timotin, Raimond Wong, Ranjan Sur, Joseph E. Hayward, Thomas J. Farrell, Colin Seymour, Carmel Mothersill

Bibliographic record

VenueInternational Journal of Radiation Biology · 2015
Typearticle
Languageen
FieldMedicine
TopicEffects of Radiation Exposure
Canadian institutionsMcMaster UniversityMcMaster University Medical Centre
Fundersnot available
KeywordsBrachytherapyIn vivoMedicineRadiobiologyRadioresistanceUrineNuclear medicineRadiation therapyUrologyPathologyInternal medicineBiology

Abstract

fetched live from OpenAlex

PURPOSE: To test whether blood, urine, and tissue based colony-forming assays are a useful clinical detection tool for assessing fractionated treatment responses and non-targeted radiation effects in bystander cells. MATERIALS AND METHODS: To assess patients' responses to radiation treatments, blood serum, urine, and an esophagus explant-based in vivo colony-forming assay were used from oesophageal carcinoma patients. These patients underwent three fractions of high dose rate (HDR) intraluminal brachytherapy (ILBT). RESULTS: Human keratinocyte reporters exposed to blood sera taken after the third fraction of brachytherapy had a significant increase in cloning efficiency compared to baseline samples (p < 0.001). Such results may suggest an induced radioresistance response in bystander cells. The data also revealed a clear inverse dose-rate effect during late treatment fractions for the blood sera data only. Patient characteristics such as gender had no statistically significant effect (p > 0.05). Large variability was observed among the patients' tissue samples, these colony-forming assays showed no significant changes throughout fractionated brachytherapy (p > 0.05). CONCLUSION: Large inter-patient variability was found in the urine and tissue based assays, so these techniques were discontinued. However, the simple blood-based assay had much less variability. This technique may have future applications as a biological dosimeter to predict treatment outcome and assess non-targeted radiation effects.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.581
Threshold uncertainty score0.605

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.015
GPT teacher head0.322
Teacher spread0.307 · 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

Citations7
Published2015
Admission routes1
Has abstractyes

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