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Record W2115079680 · doi:10.1126/stke.3552006pe39

MAPping Out Arteries and Veins

2006· review· en· W2115079680 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueScience s STKE · 2006
Typereview
Languageen
FieldNeuroscience
TopicAxon Guidance and Neuronal Signaling
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMAPK/ERK pathwayTranscription factorBiologyCell biologyVascular endothelial growth factor AVascular endothelial growth factor BEndocrinologyVascular endothelial growth factor CSmoothenedSignal transductionHedgehog signaling pathwayVascular endothelial growth factorInternal medicineCancer researchMedicineGeneticsVEGF receptors

Abstract

fetched live from OpenAlex

Growing evidence suggests that a genetic program specifies the identity of arteries and veins before the onset of circulation. A signaling cascade involving sonic hedgehog (Shh), vascular endothelial growth factor (VEGF), the VEGF receptor 2 (VEGFR2), homeobox proteins Foxc1 and Foxc2, the Notch receptor, and the downstream transcription factor gridlock is required for expression of arterial markers, whereas only a single transcription factor, COUP-TFII (chicken ovalbumin upstream promoter-transcription factor II), has previously been implicated in maintaining venous fate. Recent work has now implicated two competing pathways downstream of VEGFR2 in arterial versus venous specification: Activation of the phospholipase C-gamma (PLC-gamma)-mitogen-activated protein kinase (MAPK) pathway acts in arterial specification, whereas the phosphoinositide 3-kinase (PI3K)-Akt pathway acts to allow a venous fate by inhibition of the PLC-gamma-MAPK pathway. Here, we review this work and discuss how activation of the MAPK signaling cascade could stimulate an arterial fate.

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.

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 score0.997
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.149
GPT teacher head0.364
Teacher spread0.215 · 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