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Record W2165511696 · doi:10.1186/s13014-014-0266-7

Endothelial perturbations and therapeutic strategies in normal tissue radiation damage

2014· review· en· W2165511696 on OpenAlexaff
Elina Korpela, Stanley K. Liu

Bibliographic record

VenueRadiation Oncology · 2014
Typereview
Languageen
FieldMedicine
TopicEffects of Radiation Exposure
Canadian institutionsHealth Sciences CentreSunnybrook HospitalUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineRadiation therapyInflammationCancer researchMediatorToxicityCell damagePathologyInternal medicineBiology

Abstract

fetched live from OpenAlex

Most cancer patients are treated with radiotherapy, but the treatment can also damage the surrounding normal tissue. Radiotherapy side-effects diminish patients' quality of life, yet effective biological interventions for normal tissue damage are lacking. Protecting microvascular endothelial cells from the effects of irradiation is emerging as a targeted damage-reduction strategy. We illustrate the concept of the microvasculature as a mediator of overall normal tissue radiation toxicity through cell death, vascular inflammation (hemodynamic and molecular changes) and a change in functional capacity. Endothelial cell targeted therapies that protect against such endothelial cell perturbations and the development of acute normal tissue damage are mostly under preclinical development. Since acute radiation toxicity is a common clinical problem in cutaneous, gastrointestinal and mucosal tissues, we also focus on damage in these tissues.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.023
GPT teacher head0.377
Teacher spread0.354 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations71
Published2014
Admission routes1
Has abstractyes

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