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Record W2019456960 · doi:10.1139/o04-109

Angiostatin and plasminogen share binding to endothelial cell surface actin

2005· article· en· W2019456960 on OpenAlexaffvenue
Anil K. Dudani, M Ben-Tchavtchavadze, Sharon Porter, E. Tackaberry

Bibliographic record

VenueBiochemistry and Cell Biology · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAngiogenesis and VEGF in Cancer
Canadian institutionsHealth Canada
Fundersnot available
KeywordsAngiostatinPlasminKringle domainEndothelial stem cellMolecular biologyBinding siteChemistryWestern blotCell biologyCellBiochemistryBiologyAngiogenesisIn vitroEnzymeCancer research

Abstract

fetched live from OpenAlex

Previous studies from this laboratory have demonstrated that plasminogen binds to endothelial cell surface-associated actin via its kringles in a dose-dependent and specific manner. The purpose of this study was to determine whether angiostatin, a proteolytic fragment of plasminogen, shares binding properties with plasminogen. Our results indicated that like plasminogen, angiostatin bound to actin in a time-, concentration-, and kringle-dependent manner. Furthermore, this binding was significantly inhibited by excess plasminogen, suggesting that both proteins shared binding motifs on the actin molecule. Fluorescence studies demonstrated that angiostatin bound to intact endothelial cells through its kringles, and this binding was also inhibited by plasminogen but not by unrelated proteins. Ligand blot analyses on endothelial cell lysates indicated that angiostatin interacted with a 42 kDa protein, which was identified as actin. Furthermore, an anti-actin antibody inhibited binding of angiostatin to endothelial cells by approximately 25%. These results suggest that angiostatin and plasminogen share binding to endothelial cell surface actin and, therefore, that angiostatin has the potential to inhibit plasmin-dependent processes such as cell migration-movement.

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 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 score0.156
Threshold uncertainty score0.830

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 head0.010
GPT teacher head0.242
Teacher spread0.232 · 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.

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

Citations21
Published2005
Admission routes2
Has abstractyes

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