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Record W2929860547 · doi:10.1242/dmm.037259

<i>fs(1)h</i> controls metabolic and immune function and enhances survival via AKT and FOXO in <i>Drosophila</i>

2019· article· en· W2929860547 on OpenAlexfundno aff
Jessica Sharrock, Alicia Estacio‐Gómez, Jake Jacobson, Katrin Kierdorf, Tony D. Southall, Marc Dionne

Bibliographic record

VenueDisease Models & Mechanisms · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCRISPR and Genetic Engineering
Canadian institutionsnot available
FundersBiotechnology and Biological Sciences Research CouncilMedical Research CouncilImperial College LondonMedical Research Council CanadaWellcome TrustGlaxoSmithKline
KeywordsImmune systemDrosophila (subgenus)Protein kinase BBiologyFunction (biology)PI3K/AKT/mTOR pathwayCell biologyImmunologyGeneticsSignal transductionGene

Abstract

fetched live from OpenAlex

ABSTRACT The Drosophila fat body is the primary organ of energy storage as well as being responsible for the humoral response to infection. Its physiological function is of critical importance to the survival of the organism; however, many molecular regulators of its function remain ill-defined. Here, we show that the Drosophila melanogaster bromodomain-containing protein FS(1)H is required in the fat body for normal lifespan as well as metabolic and immune homeostasis. Flies lacking fat body fs(1)h exhibit short lifespan, increased expression of immune target genes, an inability to metabolize triglyceride, and low basal AKT activity, mostly resulting from systemic defects in insulin signalling. Removal of a single copy of the AKT-responsive transcription factor foxo normalises lifespan, metabolic function, uninduced immune gene expression and AKT activity. We suggest that the promotion of systemic insulin signalling activity is a key in vivo function of fat body fs(1)h. This article has an associated First Person interview with the first author of the paper.

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 score0.295
Threshold uncertainty score0.730

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 head0.005
GPT teacher head0.228
Teacher spread0.223 · 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

Citations10
Published2019
Admission routes1
Has abstractyes

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