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Record W2795257963 · doi:10.1038/s41598-018-21822-y

AP-2ε Expression in Developing Retina: Contributing to the Molecular Diversity of Amacrine Cells

2018· article· en· W2795257963 on OpenAlexafffund
Saket Jain, Darryl Glubrecht, Devon R. Germain, Markus Moser, Roseline Godbout

Bibliographic record

VenueScientific Reports · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinal Development and Disorders
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsRetinaDiversity (politics)Expression (computer science)Computational biologyBiologyNeuroscienceComputer science

Abstract

fetched live from OpenAlex

AP-2 transcription factors play important roles in the regulation of gene expression during development. Four of the five members of the AP-2 family (AP-2α, AP-2β, AP-2γ and AP-2δ) have previously been shown to be expressed in developing retina. Mouse knockouts have revealed roles for AP-2α, AP-2β and AP-2δ in retinal cell specification and function. Here, we show that the fifth member of the AP-2 family, AP-2ε, is also expressed in amacrine cells in developing mammalian and chicken retina. Our data indicate that there are considerably fewer AP-2ε-positive cells in the developing mouse retina compared to AP-2α, AP-2β and AP-2γ-positive cells, suggesting a specialized role for AP-2ε in a subset of amacrine cells. AP-2ε, which is restricted to the GABAergic amacrine lineage, is most commonly co-expressed with AP-2α and AP-2β, especially at early stages of retinal development. Co-expression of AP-2ε and AP-2γ increases with differentiation. Analysis of previously published Drop-seq data from single retinal cells supports co-expression of multiple AP-2s in the same cell. Since AP-2s bind to their target sequences as either homodimers or heterodimers, our work suggests spatially- and temporally-coordinated roles for combinations of AP-2 transcription factors in amacrine cells during retinal development.

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 score0.051
Threshold uncertainty score0.290

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 science0.0000.001
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 head0.238
Teacher spread0.230 · 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

Citations6
Published2018
Admission routes2
Has abstractyes

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