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Record W2320661604 · doi:10.1080/23262133.2016.1161697

Coordinating progenitor cell cycle exit and differentiation in the developing vertebrate retina

2016· letter· en· W2320661604 on OpenAlexaff
Amanda Miles, Vincent Tropepe

Bibliographic record

VenueNeurogenesis · 2016
Typeletter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinal Development and Disorders
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHomeoboxBiologyCell cycleCell fate determinationCellular differentiationCell biologyTranscription factorProgenitor cellGeneticsEpigeneticsGeneStem cell

Abstract

fetched live from OpenAlex

The proper development of the vertebrate retina relies heavily on producing the correct number and type of differentiated retinal cell types. To achieve this, proliferating retinal progenitor cells (RPCs) must exit the cell cycle at an appropriate time and correctly express a subset of differentiation markers that help specify retinal cell fate. Homeobox genes, which encode a family of transcription factors, have been accredited to both these processes, implicated in the transcriptional regulation of important cell cycle components, such as cyclins and cyclin-dependent kinases, and proneural genes. This dual regulation of homeobox genes allows these factors to help co-ordinate the transition from the proliferating RPC to postmitotic, differentiated cell. However, understanding the exact molecular targets of these factors remains a challenging task. This commentary highlights the current knowledge we have about how these factors regulate cell cycle progression and differentiation, with particular emphasis on a recent discovery from our lab demonstrating an antagonistic relationship between Vsx2 and Dmbx1 to control RPC proliferation. Future studies should aim to further understand the direct transcriptional targets of these genes, additional co-factors/interacting proteins and the possible recruitment of epigenetic machinery by these homeobox genes.

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)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.206
Threshold uncertainty score0.754

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.010
GPT teacher head0.217
Teacher spread0.208 · 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 designNot applicable
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

Citations19
Published2016
Admission routes1
Has abstractyes

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