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Record W2003529763 · doi:10.1097/fpc.0b013e3280119d50

Polymorphisms predicted to alter function in Prostaglandin E2 synthase and Prostaglandin E2 receptors

2007· article· en· W2003529763 on OpenAlexaff
Jeannette Bigler, Justin Sibert, Elizabeth M. Poole, Christopher S. Carlson, John D. Potter, Cornelia M. Ulrich

Bibliographic record

VenuePharmacogenetics and Genomics · 2007
Typearticle
Languageen
FieldMedicine
TopicInflammatory mediators and NSAID effects
Canadian institutionsAmgen (Canada)
FundersNational Cancer Institute
KeywordsProstaglandin E2 receptorProstaglandin E2ProstaglandinBiologyReceptorPharmacogeneticsGeneticsGenePharmacologyEndocrinologyGenotype

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVE: Prostaglandin synthesis is the primary target of aspirin and other nonsteroidal antiinflammatory drugs, and thus is a pathway of major interest to pharmacology, pharmacogenetics, and epidemiology. Several lines of evidence implicate prostaglandin E2 in carcinogenesis; this study aimed to identify genetic variants in genes related to prostaglandin E2 synthesis and signaling. METHODS: We resequenced the coding regions of human prostaglandin E2 synthase (PGES), and prostaglandin E2 receptors EP1, EP2, and EP4 in 48 African-Americans and 47 Caucasians. RESULTS AND CONCLUSIONS: We identified 23 variants, 6 of which cause amino acid changes. The non-synonymous polymorphisms in PGES, EP1, and EP2 were present only among African-Americans; both populations carried non-synonymous polymorphisms in EP4. We used two sequence homology-based programs, SIFT and PolyPhen, to predict the impact of these polymorphisms. These programs predicted that the amino-acid changes p.Phe119Val in EP1, p.Ala44Glu in EP2, and possibly p.Val7Glu in PGES, p.Thr176Ile in EP4 and p.Gly420Asp in EP4 are likely to affect protein function. Thus, these variants may be relevant for inflammatory conditions, carcinogenesis, and pharmacogenetics.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.108
Threshold uncertainty score0.910

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 head0.011
GPT teacher head0.267
Teacher spread0.256 · 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
Published2007
Admission routes1
Has abstractyes

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