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Record W2006502967 · doi:10.1242/jcs.091066

The novel formin FMNL3 is a cytoskeletal regulator of angiogenesis.

2012· article· en· W2006502967 on OpenAlexaff
Clare Hetheridge, Alice Scott, R Swain, John W. Copeland, Henry N. Higgs, Roy Bicknell

Bibliographic record

VenueJournal of Cell Science · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAngiogenesis and VEGF in Cancer
Canadian institutionsUniversity of Ottawa
FundersNational Institute of General Medical SciencesBritish Heart FoundationCancer Research UK
KeywordsBiologyForminsRegulatorCytoskeletonCell biologyAngiogenesisActin cytoskeletonGeneticsCellGene

Abstract

fetched live from OpenAlex

The process of angiogenesis requires endothelial cells (ECs) to undergo profound changes in shape and polarity. Although this must involve remodelling of the EC cytoskeleton, little is known about this process or the proteins that control it. We used a co-culture assay of angiogenesis to examine the cytoskeleton of ECs actively undergoing angiogenic morphogenesis. We found that elongation of ECs during angiogenesis is accompanied by stabilisation of microtubules and their alignment into parallel arrays directed at the growing tip. In other systems, similar microtubule alignments are mediated by the formin family of cytoskeletal regulators. We screened a library of human formins and indentified formin-like 3 (FMNL3; also known as FRL2) as a crucial regulator of EC elongation during angiogenesis. We showed that activated FMNL3 triggers microtubule alignment and that FMNL3 is required for this alignment during angiogenic morphogenesis. FMNL3 was highly expressed in the ECs of zebrafish during development and embryos that were depleted for FMNL3 showed profound defects in developmental angiogenesis that were rescued by expression of the human gene. We conclude that FMNL3 is a new regulator of endothelial microtubules during angiogenesis and is required for the conversion of quiescent ECs into their elongated angiogenic forms.

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)0.001
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 score0.066
Threshold uncertainty score0.180

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.011
GPT teacher head0.263
Teacher spread0.252 · 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

Citations42
Published2012
Admission routes1
Has abstractyes

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