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Record W2767028946 · doi:10.1128/mcb.00295-17

Loss of Extracellular Signal-Regulated Kinase 1/2 in the Retinal Pigment Epithelium Leads to RPE65 Decrease and Retinal Degeneration

2017· article· en· W2767028946 on OpenAlexaff
Aswin Pyakurel, Delphine Balmer, Marc K. Saba-El-Leil, Caroline Kizilyaprak, Jean Daraspe, Bruno M. Humbel, Laure Voisin, Yun Le, Johannes von Lintig, Sylvain Meloche, Raphaël Roduit

Bibliographic record

VenueMolecular and Cellular Biology · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinal Development and Disorders
Canadian institutionsUniversité de MontréalInstitute for Research in Immunology and Cancer
FundersNational Eye InstituteUniversity of Pennsylvania
KeywordsRPE65Retinal pigment epitheliumBiologyRetinal degenerationCell biologyVisual phototransductionMacular degenerationRetinaRetinalExtracellularKinaseSignal transductionCancer researchNeuroscienceBiochemistryOphthalmologyMedicine

Abstract

fetched live from OpenAlex

Recent work suggested that the activity of extracellular signal-regulated kinase 1/2 (ERK1/2) is increased in the retinal pigment epithelium (RPE) of age-related macular degeneration (ARMD) patients and therefore could be an attractive therapeutic target. Notably, ERK1/2 pathway inhibitors are used in cancer therapy, with severe and noncharacterized ocular side effects. To decipher the role of ERK1/2 in RPE cells, we conditionally disrupted the Erk1 and Erk2 genes in mouse RPE. The loss of ERK1/2 activity resulted in a significant decrease in the level of RPE65 expression, a decrease in ocular retinoid levels concomitant with low visual function, and a rapid disorganization of RPE cells, ultimately leading to retinal degeneration. Our results identify the ERK1/2 pathway as a direct regulator of the visual cycle and a critical component of the viability of RPE and photoreceptor cells. Moreover, our results caution about the need for a very fine adjustment of kinase inhibition in cancer or ARMD treatment in order to avoid ocular side effects.

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 score0.013
Threshold uncertainty score0.735

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 head0.008
GPT teacher head0.237
Teacher spread0.229 · 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

Citations28
Published2017
Admission routes1
Has abstractyes

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