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Record W7144501776

A high-protein diet-responsive gut hormone regulates behavioral and metabolic optimization in Drosophila melanogaster

2024· article· en· W7144501776 on OpenAlexfundno aff
Yoshinari Yuto, Nishimura Takashi, Yoshii Taishi, Kondo Shu, Tanimoto Hiromu, Kobayashi Tomoe, Matsuyama Makoto, Niwa Ryusuke

Bibliographic record

VenueInstitutional Repositories DataBase (IRDB) · 2024
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology and Insect Physiology Research
Canadian institutionsnot available
FundersCore Research for Evolutional Science and TechnologyLife Science Center for Survival Dynamics Tsukuba Advanced Research AllianceJapan Society for the Promotion of ScienceInstitute of GeneticsUniversity of TsukubaJapan Agency for Medical Research and Development
KeywordsDrosophila melanogasterEnteroendocrine cellCrosstalkHormoneNeuropeptideDrosophila (subgenus)Melanin-concentrating hormoneMetabolic pathway
DOInot available

Abstract

fetched live from OpenAlex

Protein is essential for all living organisms; however, excessive protein intake can have adverse effects, such as hyperammonemia. Although mechanisms responding to protein deficiency are well-studied, there is a significant gap in our understanding of how organisms adaptively suppress excessive protein intake. In the present study, utilizing the fruit fly, Drosophila melanogaster, we discover that the peptide hormone CCHamide1 (CCHa1), secreted by enteroendocrine cells in response to a high-protein diet (HPD), is vital for suppressing overconsumption of protein. Gut-derived CCHa1 is received by a small subset of enteric neurons that produce short neuropeptide F, thereby modulating protein-specific satiety. Importantly, impairment of the CCHa1-mediated gut-enteric neuronal axis results in ammonia accumulation and a shortened lifespan under HPD conditions. Collectively, our findings unravel the crosstalk of gut hormone and neuronal pathways that orchestrate physiological responses to prevent and adapt to dietary protein overload.

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 score0.073
Threshold uncertainty score0.852

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
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 head0.027
GPT teacher head0.295
Teacher spread0.268 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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