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Record W4390507800 · doi:10.1242/dev.202372

Epidermal tyrosine catabolism is crucial for metabolic homeostasis and survival against high-protein diets in <i>Drosophila</i>

2024· article· en· W4390507800 on OpenAlexfundno aff
Hina Kosakamoto, Masayuki Miura, Fumiaki Obata

Bibliographic record

VenueDevelopment · 2024
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology and Insect Physiology Research
Canadian institutionsnot available
FundersInstitute of GeneticsJapan Agency for Medical Research and DevelopmentRIKENUehara Memorial FoundationJapan Science and Technology AgencyJapan Society for the Promotion of Science
KeywordsBiologyCatabolismEpidermis (zoology)RegulatorCell biologyDownregulation and upregulationProtein kinase AAMPKKinaseBiochemistryMetabolismGeneAnatomy

Abstract

fetched live from OpenAlex

The insect epidermis forms the exoskeleton and determines the body size of an organism. How the epidermis acts as a metabolic regulator to adapt to changes in dietary protein availability remains elusive. Here, we show that the Drosophila epidermis regulates tyrosine (Tyr) catabolism in response to dietary protein levels, thereby promoting metabolic homeostasis. The gene expression profile of the Drosophila larval body wall reveals that enzymes involved in the Tyr degradation pathway, including 4-hydroxyphenylpyruvate dioxygenase (Hpd), are upregulated by increased protein intake. Hpd is specifically expressed in the epidermis and is dynamically regulated by the internal Tyr levels. Whereas basal Hpd expression is maintained by insulin/IGF-1 signalling, Hpd induction on high-protein diet requires activation of the AMP-activated protein kinase (AMPK)-forkhead box O subfamily (FoxO) axis. Impairment of the FoxO-mediated Hpd induction in the epidermis leads to aberrant increases in internal Tyr and its metabolites, disrupting larval development on high-protein diets. Taken together, our findings uncover a crucial role of the epidermis as a metabolic regulator in coping with an unfavourable dietary environment.

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 score0.061
Threshold uncertainty score0.810

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 head0.038
GPT teacher head0.296
Teacher spread0.257 · 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

Citations11
Published2024
Admission routes1
Has abstractyes

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