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Record W1977662354 · doi:10.1371/journal.pgen.1004624

Unkempt Is Negatively Regulated by mTOR and Uncouples Neuronal Differentiation from Growth Control

2014· article· en· W1977662354 on OpenAlexafffund
Amélie Avet‐Rochex, Nancy Carvajal, Christina Christoforou, Kelvin Yeung, Katja T. Maierbrugger, Carl Hobbs, Giovanna Lalli, Umut Cagin, Cédric Plachot, Helen McNeill, J.E. Bateman

Bibliographic record

VenuePLoS Genetics · 2014
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology and Insect Physiology Research
Canadian institutionsLunenfeld-Tanenbaum Research Institute
FundersCanadian Institutes of Health ResearchKing's College LondonWellcome TrustWellcome
KeywordsNeurogenesisPI3K/AKT/mTOR pathwayBiologyRegulatorCell biologyMechanistic target of rapamycinGenetic screenRPTORSignal transductionPhenotypeGeneticsGene

Abstract

fetched live from OpenAlex

Neuronal differentiation is exquisitely controlled both spatially and temporally during nervous system development. Defects in the spatiotemporal control of neurogenesis cause incorrect formation of neural networks and lead to neurological disorders such as epilepsy and autism. The mTOR kinase integrates signals from mitogens, nutrients and energy levels to regulate growth, autophagy and metabolism. We previously identified the insulin receptor (InR)/mTOR pathway as a critical regulator of the timing of neuronal differentiation in the Drosophila melanogaster eye. Subsequently, this pathway has been shown to play a conserved role in regulating neurogenesis in vertebrates. However, the factors that mediate the neurogenic role of this pathway are completely unknown. To identify downstream effectors of the InR/mTOR pathway we screened transcriptional targets of mTOR for neuronal differentiation phenotypes in photoreceptor neurons. We identified the conserved gene unkempt (unk), which encodes a zinc finger/RING domain containing protein, as a negative regulator of the timing of photoreceptor differentiation. Loss of unk phenocopies InR/mTOR pathway activation and unk acts downstream of this pathway to regulate neurogenesis. In contrast to InR/mTOR signalling, unk does not regulate growth. unk therefore uncouples the role of the InR/mTOR pathway in neurogenesis from its role in growth control. We also identified the gene headcase (hdc) as a second downstream regulator of the InR/mTOR pathway controlling the timing of neurogenesis. Unk forms a complex with Hdc, and Hdc expression is regulated by unk and InR/mTOR signalling. Co-overexpression of unk and hdc completely suppresses the precocious neuronal differentiation phenotype caused by loss of Tsc1. Thus, Unk and Hdc are the first neurogenic components of the InR/mTOR pathway to be identified. Finally, we show that Unkempt-like is expressed in the developing mouse retina and in neural stem/progenitor cells, suggesting that the role of Unk in neurogenesis may be conserved in mammals.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.541

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 head0.021
GPT teacher head0.235
Teacher spread0.214 · 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

Citations60
Published2014
Admission routes2
Has abstractyes

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