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Record W2021043007 · doi:10.1097/mnh.0b013e32836235f4

Slit2–Robo signaling

2013· review· en· W2021043007 on OpenAlexafffund
Darren A. Yuen, Lisa A. Robinson

Bibliographic record

VenueCurrent Opinion in Nephrology & Hypertension · 2013
Typereview
Languageen
FieldNeuroscience
TopicAxon Guidance and Neuronal Signaling
Canadian institutionsSt. Michael's HospitalHospital for Sick Children
FundersCanadian Institutes of Health Research
KeywordsCell biologySignal transductionAngiogenesisBiologyActin cytoskeletonVascular smooth muscleVascular permeabilityReceptorNeuroscienceCytoskeletonCancer researchCellEndocrinology

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Vascular injury is a common contributor to, and complication of, kidney disease. Given the prevalence and importance of vascular injury in renal disease, interest has grown in a novel signaling pathway first identified in developing neurons that also has widespread effects on vascular structure and function, comprising the secreted ligand Slit2 and its cognate Roundabout (Robo) receptors. RECENT FINDINGS: Although initially discovered as a modulator of neuronal migration during development, the Slit2-Robo signaling pathway has recently been found to regulate the structure and function of various subsets of vascular cells and circulating hematopoietic cells that interact with the vessel wall. Through the regulation of intermediate signaling enzymes that control the organization of the actin cytoskeleton, Slit2 and its Robo receptors regulate such diverse processes as angiogenesis, endothelial permeability, vascular smooth muscle cell migration, and thrombosis. SUMMARY: Recent advances in our understanding of Slit2-Robo signaling have provided novel insights into the pathophysiology of vascular injury that is commonly associated with renal disease. These insights have created potential opportunities for the development of new therapies targeting vascular injury associated with renal disease.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.980
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.002

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 head0.289
GPT teacher head0.396
Teacher spread0.107 · 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

Citations41
Published2013
Admission routes2
Has abstractyes

Explore more

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