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Record W2406425121 · doi:10.1242/dev.133595

A biological timer in the fat body comprised of Blimp-1, βFTZ-F1 and Shade regulates pupation timing in <i>Drosophila melanogaster</i>

2016· article· en· W2406425121 on OpenAlexfundno aff
Kazutaka Akagi, Moustafa Sarhan, Abdel-Rahman S. Sultan, Haruka Nishida, Azusa Koie, Takumi Nakayama, Hitoshi Ueda

Bibliographic record

VenueDevelopment · 2016
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology and Insect Physiology Research
Canadian institutionsnot available
FundersInstitute of GeneticsJapan Society for the Promotion of ScienceCultural Affairs and Missions Sector, Ministry of Higher EducationMinistry of Education, Culture, Sports, Science and Technology
KeywordsBiologyEcdysoneProthoracic glandDrosophila melanogasterRepressorCell biologyGene expressionGeneticsGene

Abstract

fetched live from OpenAlex

During the development of multicellular organisms, many events occur with precise timing. In Drosophila melanogaster, pupation occurs about 12 h after puparium formation and its timing is believed to be determined by the release of a steroid hormone, ecdysone (E), from the prothoracic gland. Here, we demonstrate that the ecdysone-20-monooxygenase Shade determines pupation timing by converting E to 20-hydroxyecdysone (20E) in the fat body, which is the organ that senses nutritional status. The timing of shade expression is determined by its transcriptional activator βFtz-f1. The βftz-f1 gene is activated after a decline in the expression of its transcriptional repressor Blimp-1, which is temporally expressed around puparium formation in response to a high titer of 20E. The expression level and stability of Blimp-1 is critical for the precise timing of pupation. Thus, we propose that Blimp-1 molecules function like sand in an hourglass in this precise developmental timer system. Furthermore, our data suggest that a biological advantage results from both the use of a transcriptional repressor for time determination and the association of developmental timing with nutritional status of the organism.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.482
Threshold uncertainty score0.217

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 head0.071
GPT teacher head0.296
Teacher spread0.224 · 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

Citations18
Published2016
Admission routes1
Has abstractyes

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