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Regulation of the Rapsyn Promoter by Kaiso and δ-Catenin

2004· article· en· W2157796706 on OpenAlexafffund
Marianna Rodova, Michael N. VanSaun, Juliet M. Daniel, M. J. Werle

Bibliographic record

VenueMolecular and Cellular Biology · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicWnt/β-catenin signaling in development and cancer
Canadian institutionsMcMaster University
FundersNational Institute of Neurological Disorders and StrokeCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsBiologyCell biology

Abstract

fetched live from OpenAlex

Rapsyn is a synapse-specific protein that is required for clustering acetylcholine receptors at the neuromuscular junction. Analysis of the rapsyn promoter revealed a consensus site for the transcription factor Kaiso within a region that is mutated in a subset of patients with congenital myasthenic syndrome. Kaiso is a POZ-zinc finger family transcription factor which recognizes the specific core consensus sequence CTGCNA (where N is any nucleotide). Previously, the only known binding partner for Kaiso was the cell adhesion cofactor, p120 catenin. Here we show that delta-catenin, a brain-specific member of the p120 catenin subfamily, forms a complex with Kaiso. Antibodies against Kaiso and delta-catenin recognize proteins in the nuclei of C2C12 myocytes and at the postsynaptic domain of the mouse neuromuscular junction. Endogenous Kaiso in C2C12 cells coprecipitates with the rapsyn promoter in vivo as shown by chromatin immunoprecipitation assay. Minimal promoter assays demonstrated that the rapsyn promoter can be activated by Kaiso and delta-catenin; this activation is apparently muscle specific. These results provide the first experimental evidence that rapsyn is a direct sequence-specific target of Kaiso and delta-catenin. We propose a new model of synapse-specific transcription that involves the interaction of Kaiso, delta-catenin, and myogenic transcription factors at the neuromuscular junction.

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 score0.012
Threshold uncertainty score0.382

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 head0.004
GPT teacher head0.196
Teacher spread0.192 · 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

Citations115
Published2004
Admission routes2
Has abstractyes

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