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Record W2090409255 · doi:10.1158/1538-7445.am2014-1220

Abstract 1220: Investigation of the biological properties of human breast cancer in a nude rat model

2014· article· en· W2090409255 on OpenAlexaff
Reza Bayat Mokhtari, Joris Nofiele, Syed S. Islam, Herman Yeger, Hai‐Ling Margaret Cheng

Bibliographic record

VenueCancer Research · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Research and Treatments
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsBreast cancerNude mouseCancerMagnetic resonance imagingMetastasisCancer researchImmunohistochemistryHuman breastMedicinePathologyAnimal modelPreclinical imagingIn vivoBiologyInternal medicineRadiology

Abstract

fetched live from OpenAlex

Abstract Developing imaging technology for cancer diagnosis and treatment monitoring is best performed on larger pre-clinical animal models recapitulating tumor growth and metastasis more similar to that found in humans. Such models are amenable to morphological and functional imaging techniques at spatial resolutions appropriate for animal imaging and, translatable to human imaging. In comparison to mouse xenografts, rat models offer the advantages of clinical imaging capabilities, development of xenograft and metastatic models, in orthotopic sites. Human breast cancer cell lines MDA-MB-231 and MCF-7 show a variable take rate in mice, ∼ 68% incurring considerable cost and time. Having a more reproducible method is needed for breast cancer studies. Here we present evidence for development of a novel method in the immune-compromised nude rats. Spheroids grown under stem cell conditions were derived from human breast adenocarcinoma estrogen dependent (MCF-7, ZR-75-1) and independent (MDA-MB-231) lines, and xenografted in both subcutaneous and orthotopic (fat pad) sites in the nude rat. To verify that rat tumors could be studied in detail at spatial resolutions achievable on a clinical 3 Tesla scanner, high-resolution magnetic resonance imaging was performed to identify vascular, viable, and necrotic tumor regions. The breast cancer phenotype and was confirmed by immunohistochemistry for ER and HER2. Tumors were characterized with proliferation marker Ki67, vascularization by CD34 and VEGF, and presence of hypoxic regions by HIF1α. Our results indicated that spheroids from all three lines readily generated tumors independent of exogenous estrogen. MRI is an effective and sensitive method for investigating the biological behavior and vascularization of breast cancer. These findings offer a potential novel method for pre-clinical study and investigation of human breast cancer. Citation Format: Reza Bayat Mokhtari, Joris Tchouala Nofiele, Syed S. Islam, Herman Yeger, Hai-Ling Margaret Cheng. Investigation of the biological properties of human breast cancer in a nude rat model. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1220. doi:10.1158/1538-7445.AM2014-1220

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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.118
GPT teacher head0.392
Teacher spread0.274 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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