MétaCan
Menu
Back to cohort
Record W2090261930 · doi:10.4161/cc.5.13.2928

Control of Murine Kidney Development by Sonic Hedgehog and its GLI Effectors

2006· review· en· W2090261930 on OpenAlexafffund
Paul Gill, Norman D. Rosenblum

Bibliographic record

VenueCell Cycle · 2006
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRenal and related cancers
Canadian institutionsHospital for Sick Children
FundersHospital for Sick ChildrenCanada Research Chairs
KeywordsSonic hedgehogBiologyKidney developmentWnt signaling pathwayMorphogenesisCell biologyHedgehogHedgehog signaling pathwayKidneyGeneticsSignal transductionGeneEmbryonic stem cell

Abstract

fetched live from OpenAlex

Sonic hedgehog (SHH) controls cell differentiation and morphogenesis in many tissues and species. The mammalian kidney is a paradigm for studying epithelial-mesenchymal interactions and growth factor signaling during embryogenesis. Here, we review our recent findings demonstrating that SHH is required for normal murine kidney development. During renal morphogenesis, SHH controls a hierarchy of genes including renal patterning genes, cell cycle modulators, and GLI family members. Our investigation of GLI protein processing and binding of GLI activators and repressor to SHH target genes provide insight into the molecular mechanisms by which SHH and its GLI family of effectors control renal embryogenesis. Further, we highlight the roles of BMP, WNT and FGF signaling during renal development and discuss possible interactions of these pathways with SHH signaling.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.003

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 head0.005
GPT teacher head0.232
Teacher spread0.227 · 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 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

Citations69
Published2006
Admission routes2
Has abstractyes

Explore more

Same venueCell CycleSame topicRenal and related cancersFrench-language works237,207