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Record W1498691589 · doi:10.1016/j.celrep.2015.05.033

Fasting, but Not Aging, Dramatically Alters the Redox Status of Cysteine Residues on Proteins in Drosophila melanogaster

2015· erratum· en· W1498691589 on OpenAlexfundno aff
Katja E. Menger, Andrew M. James, Helena M. Cochemé, Michael E. Harbour, Edward T. Chouchani, Shujing Ding, Ian M. Fearnley, Linda Partridge, Michael P. Murphy

Bibliographic record

VenueCell Reports · 2015
Typeerratum
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRedox biology and oxidative stress
Canadian institutionsnot available
FundersBiotechnology and Biological Sciences Research CouncilMedical Research CouncilWellcome TrustResearch Councils UKCanadian Institute for Theoretical Astrophysics
KeywordsCysteineRedoxDrosophila melanogasterResidue (chemistry)ChemistryBiochemistryOxidative phosphorylationCysteine metabolismMelanogasterEnzymeGeneOrganic chemistry

Abstract

fetched live from OpenAlex

Altering the redox state of cysteine residues on protein surfaces is an important response to environmental challenges. Although aging and fasting alter many redox processes, the role of cysteine residues is uncertain. To address this, we used a redox proteomic technique, oxidative isotope-coded affinity tags (OxICAT), to assess cysteine-residue redox changes in Drosophila melanogaster during aging and fasting. This approach enabled us to simultaneously identify and quantify the redox state of several hundred cysteine residues in vivo. Cysteine residues within young flies had a bimodal distribution with peaks at ∼10% and ∼85% reversibly oxidized. Surprisingly, these cysteine residues did not become more oxidized with age. In contrast, 24 hr of fasting dramatically oxidized cysteine residues that were reduced under fed conditions while also reducing cysteine residues that were initially oxidized. We conclude that fasting, but not aging, dramatically alters cysteine-residue redox status in D. melanogaster.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.014
GPT teacher head0.260
Teacher spread0.246 · 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.

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

Citations73
Published2015
Admission routes1
Has abstractyes

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