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Record W1937925273 · doi:10.1016/j.tranon.2015.03.009

Understanding Heterogeneity and Permeability of Brain Metastases in Murine Models of HER2-Positive Breast Cancer Through Magnetic Resonance Imaging: Implications for Detection and Therapy

2015· article· en· W1937925273 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueTranslational Oncology · 2015
Typearticle
Languageen
FieldMedicine
TopicBrain Metastases and Treatment
Canadian institutionsRobarts Clinical TrialsWestern University
FundersCanadian Institutes of Health ResearchGroupe de recherche interuniversitaire en limnologieCanadian HIV Trials Network, Canadian Institutes of Health ResearchBrain Tumour Foundation of Canada
KeywordsBreast cancerMagnetic resonance imagingMedicineCD31Brain metastasisPathologyHistologyImmunohistochemistryMetastasisCancerInternal medicineRadiology

Abstract

fetched live from OpenAlex

OBJECTIVES: Brain metastases due to breast cancer are increasing, and the prognosis is poor. Lack of effective therapy is attributed to heterogeneity of breast cancers and their resulting metastases, as well as impermeability of the blood-brain barrier (BBB), which hinders delivery of therapeutics to the brain. This work investigates three experimental models of HER2+ breast cancer brain metastasis to better understand the inherent heterogeneity of the disease. We use magnetic resonance imaging (MRI) to quantify brain metastatic growth and explore its relationship with BBB permeability. DESIGN: Brain metastases due to breast cancer cells (SUM190-BR3, JIMT-1-BR3, or MDA-MB-231-BR-HER2) were imaged at 3 T using balanced steady-state free precession and contrast-enhanced T1-weighted spin echo sequences. The histology and immunohistochemistry corresponding to MRI were also analyzed. RESULTS: There were differences in metastatic tumor appearance by MRI, histology, and immunohistochemistry (Ki67, CD31, CD105) across the three models. The mean volume of an MDA-MB-231-BR-HER2 tumor was significantly larger compared to other models (F2,12 = 5.845, P < .05); interestingly, this model also had a significantly higher proportion of Gd-impermeable tumors (F2,12 = 22.18, P < .0001). Ki67 staining indicated that Gd-impermeable tumors had significantly more proliferative nuclei compared to Gd-permeable tumors (t[24] = 2.389, P < .05) in the MDA-MB-231-BR-HER2 model. CD31 and CD105 staining suggested no difference in new vasculature patterns between permeable and impermeable tumors in any model. CONCLUSION: Significant heterogeneity is present in these models of brain metastases from HER2+ breast cancer. Understanding this heterogeneity, especially as it relates to BBB permeability, is important for improvement in brain metastasis detection and treatment delivery.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.428
Threshold uncertainty score0.293

Codex and Gemma teacher scores by category

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 head0.159
GPT teacher head0.382
Teacher spread0.223 · 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