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Record W2162623019 · doi:10.1091/mbc.e05-05-0388

Differential Intranuclear Organization of Transcription Factors Sp1 and Sp3

2005· article· en· W2162623019 on OpenAlexaff
Shihua He, Jianmin Sun, Lin Li, James Davie

Bibliographic record

VenueMolecular Biology of the Cell · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Chromatin Dynamics
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsBiologyChromatin immunoprecipitationSp1 transcription factorNuclear matrixTranscription factorMolecular biologyCAAT boxCell nucleusCell biologyPromoterChromatinGene expressionGeneGeneticsNucleus

Abstract

fetched live from OpenAlex

Sp1 and Sp3 are ubiquitously expressed mammalian transcription factors that activate or repress the expression of a variety of genes and are thought to compete for the same DNA binding site. We used indirect immunofluorescence microscopy and image deconvolution to show that Sp1 and Sp3 are organized into distinct nonoverlapping domains in human breast and ovarian cells. Domains of Sp1 and Sp3 infrequently associate with sites of transcription. Sp3 partitions with the tightly bound nuclear protein fraction of hormone responsive MCF-7 breast cancer cells, whereas only a subpopulation of Sp1 is found in that fraction. Both Sp1 and Sp3 are bound to the nuclear matrix, and the nuclear matrix-associated sites of Sp1 and Sp3 are different. Indirect immunofluorescence studies demonstrate that Sp1 and Sp3 associate with histone deacetylases 1 and 2 and with the estrogen receptor alpha, albeit at low frequencies in MCF-7 cells. Chromatin immunoprecipitation (ChIP) and re-ChIP assays revealed that although both Sp1 and Sp3 bind to the estrogen-responsive trefoil factor 1 promoter in MCF-7 cells, they do not occupy the same promoter. Our results demonstrate the different features of Sp1 and Sp3, providing further evidence that Sp3 is not a functional equivalent of Sp1.

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 score0.004
Threshold uncertainty score0.272

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 head0.003
GPT teacher head0.179
Teacher spread0.176 · 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

Citations67
Published2005
Admission routes1
Has abstractyes

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