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Record W2527801845 · doi:10.1242/dev.131466

Activation of Smad2 but not Smad3 is required to mediate TGF-β signaling during axolotl limb regeneration

2016· article· en· W2527801845 on OpenAlexafffund
Jean-François Denis, Fadi Sader, Samuel Gatien, Éric Villiard, Anie Philip, Stéphane Roy

Bibliographic record

VenueDevelopment · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicTGF-β signaling in diseases
Canadian institutionsMcGill UniversityUniversité de Montréal
FundersInstitute of Musculoskeletal Health and ArthritisCanadian Institutes of Health ResearchRéseau de Recherche en Santé Buccodentaire et Osseuse
KeywordsAxolotlBiologyRegeneration (biology)Cell biologyTransforming growth factorSignal transduction

Abstract

fetched live from OpenAlex

Axolotls are unique among vertebrates in their ability to regenerate tissues, such as limbs, tail and skin. The axolotl limb is the most studied regenerating structure. The process is well characterized morphologically; however, it is not well understood at the molecular level. We demonstrate that TGF-β1 is highly upregulated during regeneration and that TGF-β signaling is necessary for the regenerative process. We show that the basement membrane is not prematurely formed in animals treated with the TGF-β antagonist SB-431542. More importantly, Smad2 and Smad3 are differentially regulated post-translationally during the preparation phase of limb regeneration. Using specific antagonists for Smad2 and Smad3 we demonstrate that Smad2 is responsible for the action of TGF-β during regeneration, whereas Smad3 is not required. Smad2 target genes (Mmp2 and Mmp9) are inhibited in SB-431542-treated limbs, whereas non-canonical TGF-β targets (e.g. Mmp13) are unaffected. This is the first study to show that Smad2 and Smad3 are differentially regulated during regeneration and places Smad2 at the heart of TGF-β signaling supporting the regenerative process.

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 score0.009
Threshold uncertainty score0.547

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 head0.018
GPT teacher head0.239
Teacher spread0.221 · 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

Citations38
Published2016
Admission routes2
Has abstractyes

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