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Nuclear Trafficking of the G-Protein−Coupled Parathyroid Hormone Receptor

2008· review· en· W2066440600 on OpenAlexaff
Patricia H. Watson, Bryce W. Pickard

Bibliographic record

VenueCritical Reviews in Eukaryotic Gene Expression · 2008
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Kinase Regulation and GTPase Signaling
Canadian institutionsWestern University
Fundersnot available
KeywordsParathyroid hormoneParathyroid hormone receptorNuclear receptorChemistryReceptorHormone receptorInternal medicineMedicineBiochemistryGeneCalciumTranscription factor

Abstract

fetched live from OpenAlex

G-protein-coupled receptors are a family of receptors that signal primarily through heterotrimeric G proteins. However, new evidence has emerged to show that the signaling capabilities of the receptors are beyond those of traditional signaling cascades. One such example is that the parathyroid hormone (PTH) type 1 receptor is found not only at the plasma membrane but also in the nucleus of cells in cell lines and tissues. This review discusses the emerging concepts of nuclear PTH signaling and relates this information to the growing field of nuclear G-protein-coupled receptors. We review recently published studies on the mechanism of PTH nuclear localization, its role in the cell nucleus, and the contrasting roles ligands play in regulating the receptors' nuclear localization. The review also discusses the importance of nuclear G-protein-coupled receptors and future directions for research in this field.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.006

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 head0.036
GPT teacher head0.314
Teacher spread0.278 · 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 designNot applicable
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

Citations10
Published2008
Admission routes1
Has abstractyes

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