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Record W2793338763 · doi:10.1002/nbm.3907

Cranial irradiation increases tumor growth in experimental breast cancer brain metastasis

2018· article· en· W2793338763 on OpenAlexafffund
Amanda M. Hamilton, Suzanne M. Wong, Eugene Wong, Paula J. Foster

Bibliographic record

VenueNMR in Biomedicine · 2018
Typearticle
Languageen
FieldMedicine
TopicBrain Metastases and Treatment
Canadian institutionsRobarts Clinical TrialsWestern University
FundersCanadian Institutes of Health ResearchBrain Tumour Foundation of Canada
KeywordsBreast cancerBrain metastasisBreast tumorMetastasisIrradiationCancerPathologyCancer researchMedicineOncologyBiologyInternal medicinePhysics

Abstract

fetched live from OpenAlex

Whole-brain radiotherapy is the standard of care for patients with breast cancer with multiple brain metastases and, although this treatment has been essential in the management of existing brain tumors, there are many known negative consequences associated with the irradiation of normal brain tissue. In our study, we used in vivo magnetic resonance imaging analysis to investigate the influence of radiotherapy-induced damage of healthy brain on the arrest and growth of metastatic breast cancer cells in a mouse model of breast cancer brain metastasis. We observed that irradiated, but otherwise healthy, neural tissue had an increased propensity to support metastatic growth compared with never-irradiated controls. The elucidation of the impact of irradiation on normal neural tissue could have implications in clinical patient management, particularly in patients with residual systemic disease or with residual radio-resistant brain cancer.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.165
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.321
Teacher spread0.304 · 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.

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

Citations5
Published2018
Admission routes2
Has abstractyes

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