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Record W2909259272 · doi:10.1038/s42003-018-0253-x

Insulin signaling in Drosophila melanogaster mediates Aβ toxicity

2018· article· en· W2909259272 on OpenAlexfundno aff
Yunpeng Huang, Zhihui Wan, Zhiqing Wang, Bing Zhou

Bibliographic record

VenueCommunications Biology · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEndoplasmic Reticulum Stress and Disease
Canadian institutionsnot available
FundersUniversidad de Buenos AiresChina Postdoctoral Science FoundationInstitute of GeneticsTsinghua UniversityNational Natural Science Foundation of China
KeywordsDrosophila melanogasterToxicityInsulinDrosophila (subgenus)Insulin receptorBiologyGeneticsMedicineInternal medicineEndocrinologyInsulin resistanceGene

Abstract

fetched live from OpenAlex

Abstract Alzheimer’s disease (AD) and diabetes are clinically positively correlated. However, the connection between them is not clarified. Here, using Drosophila as a model system, we show that reducing insulin signaling can effectively suppress the toxicity from Aβ (Amyloid beta 42) expression. On the other hand, Aβ accumulation led to the elevation of fly insulin-like peptides (ILPs) and activation of insulin signaling in the brain. Mechanistically, these observations are attributed to a reciprocal competition between Drosophila insulin-like peptides and Aβ for the activity of insulin-degrading enzyme (IDE). Intriguingly, peripheral insulin signaling is decreased despite its heightened activity in the brain. While many upstream factors may modify Aβ toxicity, our results suggest that insulin signaling is the main downstream executor of Aβ damage, and thus may serve as a promising target for Alzheimer’s treatment in non-diabetes patients. This study explains why more Alzheimer’s cases are found in diabetes patients.

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 score0.161
Threshold uncertainty score0.397

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 science0.0010.000
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 head0.022
GPT teacher head0.301
Teacher spread0.279 · 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

Citations23
Published2018
Admission routes1
Has abstractyes

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