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Record W2098282622 · doi:10.1126/science.1127592

Therapy-Induced Acute Recruitment of Circulating Endothelial Progenitor Cells to Tumors

2006· article· en· W2098282622 on OpenAlexaff
Yuval Shaked, Alessia Ciarrocchi, Marcela Franco, Christina R. Lee, Shan Man, Alison Cheung, Daniel J. Hicklin, David J. Chaplin, F. Stuart Foster, Robert Benezra, Robert S. Kerbel

Bibliographic record

VenueScience · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAngiogenesis and VEGF in Cancer
Canadian institutionsSunnybrook Health Science Centre
FundersNational Cancer Institute
KeywordsProgenitor cellAngiogenesisCancer researchBone marrowMedicineNeovascularizationProgenitorVasculogenesisPathologyImmunologyStem cellBiologyCell biology

Abstract

fetched live from OpenAlex

The contribution of bone marrow-derived circulating endothelial progenitor cells (CEPs) to tumor angiogenesis has been controversial, primarily because of their low numbers in blood vessels of untreated tumors. We show that treatment of tumor-bearing mice with vascular disrupting agents (VDAs) leads to an acute mobilization of CEPs, which home to the viable tumor rim that characteristically remains after such therapy. Disruption of this CEP spike by antiangiogenic drugs or by genetic manipulation resulted in marked reductions in tumor rim size and blood flow as well as enhanced VDA antitumor activity. These findings also provide a mechanistic rationale for the enhanced efficacy of VDAs when combined with antiangiogenic drugs.

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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.036
GPT teacher head0.310
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

Citations568
Published2006
Admission routes1
Has abstractyes

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