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Record W2125770816 · doi:10.1586/14737140.6.9.1271

Breast cancer metastasis progression as revealed by intravital videomicroscopy

2006· review· en· W2125770816 on OpenAlexafffund
Ian C. MacDonald, Ann F. Chambers

Bibliographic record

VenueExpert Review of Anticancer Therapy · 2006
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Research and Treatments
Canadian institutionsWestern University
FundersCanada Research Chairs
KeywordsMetastasisMedicinePrimary tumorIntravital microscopyPathologyFlow cytometryCancer researchMetastatic breast cancerCancerBreast cancerImmunologyInternal medicineMicrocirculation

Abstract

fetched live from OpenAlex

Metastasis is the spread of cells from a primary tumor to a distant site, where they arrest and grow to form a secondary tumor. Conventional metastasis models have focused primarily on analysis of end point tumor formation following inoculation with tumor cells. This approach can be used to measure the metastatic potential of cell lines, the morphology of metastases and their vasculature and the overall effectiveness of treatment strategies. However, it cannot, reveal the dynamics of metastatic progression, tumor cell interactions with host tissues or the characteristics of blood flow within the tumor microvasculature. Intravital videomicroscopy has been developed to visualize and quantify the movement of tumor cells and their interactions with host tissues as they travel through metastatic pathways within the body and arrest at secondary sites. Intravital videomicroscopy can also be used to quantify the morphology and functional capacity of tumor microvasculature, as well as the timing and dynamic effects of drugs targeted to disrupt tumor vasculaturization. With the development of new fluorescent probes and reporter genes, intravital videomicroscopy has the potential to provide evidence of the timing and location of metabolic processes within the metastatic cascade that may serve as specific targets for the treatment of breast 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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.883
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.021
GPT teacher head0.442
Teacher spread0.421 · 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 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

Citations12
Published2006
Admission routes2
Has abstractyes

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