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Record W2103984836 · doi:10.1081/erc-120016832

SF1 POLYMORPHISMS IN THE MOUSE AND STEROIDOGENIC POTENTIAL

2002· article· en· W2103984836 on OpenAlexaff
Bernard P. Schimmer, Martha Cordova, Jennivine Tsao, Claudia Frigeri

Bibliographic record

VenueEndocrine Research · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMechanisms of cancer metastasis
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSteroidogenic factor 1BiologyGeneticsTranscription factorGeneNuclear receptor

Abstract

fetched live from OpenAlex

ACTH-resistance in four mutant derivatives of a mouse adrenocortical tumor cell line results from a defect that reduces the activity of steroidogenic factor-1 (SF1) thereby preventing expression of the ACTH receptor and other SF1-dependent genes. The SF1 genes from these mutants contain a sequence difference that changes an Ala to Ser at codon 172. Steroidogenic factor-1(S172) represents a polymorphism rather than a spontaneous mutation since the two forms of SF1, SF1(A172), and SF1(S172), can be traced to the hybrid mouse strain (C57L/J x A/HeJ) from which the original adrenal tumor was derived. The SF1(S172) allele is amplified in three of the four mutant clones together with the neighboring genes germ cell nuclear factor and LIM homeobox2. The two forms of SF1 had only modest differences in transcriptional activity in reporter gene assays, suggesting that the SF1 polymorphism per se is not directly responsible for the loss of mc2r expression. Rather, ACTH resistance in this family of adrenocortical tumor cell mutants may be due to a closely linked gene on the SF1(S172) allele. Mouse strains with reportedly high steroidogenic capacity (C57Bl/6J, C57Bl/10J) also have the SF1(A172) allele while mouse strains with low steroidogenic capacity (C3H/HeJ, DBA/2J) have the SF1(S172) allele. These latter observations suggest that the two SF1 alleles also may be markers of steroidogenic potential among mouse strains.

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)0.001
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 score0.112
Threshold uncertainty score0.276

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.063
GPT teacher head0.338
Teacher spread0.275 · 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

Citations12
Published2002
Admission routes1
Has abstractyes

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