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Record W2432733435 · doi:10.1016/j.celrep.2016.05.053

The Insect Prothoracic Gland as a Model for Steroid Hormone Biosynthesis and Regulation

2016· article· en· W2432733435 on OpenAlexafffund
Qiuxiang Ou, Jie Zeng, Naoki Yamanaka, Christina Brakken-Thal, Michael B. O’Connor, Kirst King‐Jones

Bibliographic record

VenueCell Reports · 2016
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology and Insect Physiology Research
Canadian institutionsUniversity of Alberta
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of General Medical SciencesCanadian Institutes of Health Research
KeywordsProthoracic glandBiologyBombyx moriVertebrateSteroid hormoneInsectHormoneSteroidDrosophila melanogasterGeneBombyxFunction (biology)Cell biologySteroid hormone receptorNuclear receptorEcdysoneGeneticsEndocrinologyTranscription factor

Abstract

fetched live from OpenAlex

Steroid hormones are ancient signaling molecules found in vertebrates and insects alike. Both taxa show intriguing parallels with respect to how steroids function and how their synthesis is regulated. As such, insects are excellent models for studying universal aspects of steroid physiology. Here, we present a comprehensive genomic and genetic analysis of the principal steroid hormone-producing organs in two popular insect models, Drosophila and Bombyx. We identified 173 genes with previously unknown specific expression in steroid-producing cells, 15 of which had critical roles in development. The insect neuropeptide PTTH and its vertebrate counterpart ACTH both regulate steroid production, but molecular targets of these pathways remain poorly characterized. Identification of PTTH-dependent gene sets identified the nuclear receptor HR4 as a highly conserved target in both Drosophila and Bombyx. We consider this study to be a critical step toward understanding how steroid hormone production and release are regulated in all animal models.

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)0.001
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 score0.012
Threshold uncertainty score0.286

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.043
GPT teacher head0.289
Teacher spread0.245 · 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

Citations111
Published2016
Admission routes2
Has abstractyes

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