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Record W4366825948 · doi:10.3390/antiox12050981

Unfolding the Interactions between Endoplasmic Reticulum Stress and Oxidative Stress

2023· review· en· W4366825948 on OpenAlexafffund
Gideon Ong, Susan E. Logue

Bibliographic record

VenueAntioxidants · 2023
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEndoplasmic Reticulum Stress and Disease
Canadian institutionsCancerCare ManitobaChildren's Hospital Research Institute of ManitobaUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCancerCare Manitoba FoundationResearch Manitoba
KeywordsUnfolded protein responseEndoplasmic reticulumOxidative stressCell biologyReactive oxygen speciesMitochondrionSignal transductionHomeostasisContext (archaeology)ChemistryBiologyBiochemistry

Abstract

fetched live from OpenAlex

Oxidative stress is caused by an imbalance in cellular redox state due to the accumulation of reactive oxygen species (ROS). While homeostatic levels of ROS are important for cell physiology and signaling, excess ROS can induce a variety of negative effects ranging from damage to biological macromolecules to cell death. Additionally, oxidative stress can disrupt the function of redox-sensitive organelles including the mitochondria and endoplasmic reticulum (ER). In the case of the ER, the accumulation of misfolded proteins can arise due to oxidative stress, leading to the onset of ER stress. To combat ER stress, cells initiate a highly conserved stress response called the unfolded protein response (UPR). While UPR signaling, within the context of resolving ER stress, is well characterised, how UPR mediators respond to and influence oxidative stress is less defined. In this review, we evaluate the interplay between oxidative stress, ER stress and UPR signaling networks. Specifically, we assess how UPR signaling mediators can influence antioxidant responses.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.044
GPT teacher head0.346
Teacher spread0.302 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations189
Published2023
Admission routes2
Has abstractyes

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