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Record W2918786394 · doi:10.1186/s12918-019-0687-x

Effects of unpaired 1 gene overexpression on the lifespan of Drosophila melanogaster

2019· article· en· W2918786394 on OpenAlexfundno aff
Alexey Moskalev, Ekaterina Proshkina, Alex Zhavoronkov, Mikhail Shaposhnikov

Bibliographic record

VenueBMC Systems Biology · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics, Aging, and Longevity in Model Organisms
Canadian institutionsnot available
FundersMoscow Institute of Physics and TechnologyQueen's UniversityBrown UniversityTufts Medical CenterYale University
KeywordsDrosophila melanogasterBiologyLongevitystatJAK-STAT signaling pathwayGeneSignal transductionGene expressionJanus kinaseCell biologyGeneticsSTAT3Receptor tyrosine kinase

Abstract

fetched live from OpenAlex

BACKGROUND: The JAK/STAT signaling pathway is involved in many aging-related cellular functions. However, effects of overexpression of genes controlling JAK/STAT signal transduction on longevity of model organisms have not been studied. Here we evaluate the effect of overexpression of the unpaired 1 (upd1) gene, which encodes an activating ligand for JAK/STAT pathway, on the lifespan of Drosophila melanogaster. RESULTS: Overexpression of upd1 in the intestine caused a pronounced shortening of the median lifespan by 54.1-18.9%, and the age of 90% mortality by 40.9-19.1% in males and females, respectively. In fat body and in nervous system of male flies, an induction of upd1 overexpression increased the age of 90% mortality and median lifespan, respectively. An increase in upd1 expression enhanced mRNA levels of the JAK/STAT target genes domeless and Socs36E. CONCLUSIONS: Conditional overexpression of upd1 in different tissues of Drosophila imago induces pro-aging or pro-longevity effects in tissue-dependent manner. The effects of upd1 overexpression on lifespan are accompanied by the transcription activation of genes for the components of JAK/STAT pathway.

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 score0.005
Threshold uncertainty score0.459

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 head0.010
GPT teacher head0.218
Teacher spread0.208 · 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

Citations7
Published2019
Admission routes1
Has abstractyes

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