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Record W2003227842 · doi:10.1155/2009/925309

Cross‐Talk between PPARs and the Partners of RXR: A Molecular Perspective

2009· article· en· W2003227842 on OpenAlexaff
Lap Shu Alan Chan, Richard A. Wells

Bibliographic record

VenuePPAR Research · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPeroxisome Proliferator-Activated Receptors
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsPerspective (graphical)MedicineComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

The PPARs are integral parts of the RXR-dependent signaling networks. Many other nuclear receptor subfamily 1 members also require RXR as their obligatory heterodimerization partner and they are often co-expressed in any given tissue. Therefore, the PPARs often complete with other RXR-dependent nuclear receptors and this competition has important biological implications. Thorough understanding of this cross-talk at the molecular level is crucial to determine the detailed functional roles of the PPARs. At the level of DNA binding, most RXR heterodimers bind selectively to the well-known "DR1 to 5" DNA response elements. As a result, many heterodimers share the same DR element and must complete with each other for DNA binding. At the level of heterodimerization, the partners of RXR share the same RXR dimerization interface. As a result, individual nuclear receptors must complete with each other for RXR to form functional heterodimers. Cross-talk through DNA binding and RXR heterodimerization present challenges to the study of these nuclear receptors that cannot be adequately addressed by current experimental approaches. Novel tools, such as engineered nuclear receptors with altered dimerization properties, are currently being developed. These tools will enable future studies to dissect specific RXR heterodimers and their signaling pathways.

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)0.002
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0030.007
Open science0.0010.001
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0030.001

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 head0.041
GPT teacher head0.424
Teacher spread0.382 · 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 designTheoretical or conceptual
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

Citations74
Published2009
Admission routes1
Has abstractyes

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