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The Nrf2-Keap1/ARE signaling pathway in aquatic animals

2025· review· en· W4408982813 on OpenAlexaff
Dan‐Dan Bian, Xue Zhang, Xi-Rong Zhu, Wenhui Tang, Peng Qin, Yaohui Chen, Gang Wang, Dai-Zhen Zhang, Boping Tang, Qiu‐Ning Liu

Bibliographic record

VenueInternational Journal of Biological Macromolecules · 2025
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics, phytochemicals, and oxidative stress
Canadian institutionsMinistry of Agriculture
FundersQinglan Project of Jiangsu Province of ChinaNational Natural Science Foundation of China
KeywordsKEAP1ZoologyBiologyComputational biologyBiochemistryTranscription factorGene

Abstract

fetched live from OpenAlex

The complex and fluctuating conditions of aquatic ecosystems make aquatic organisms vulnerable to oxidative stress. The Nrf2-Keap1/ARE signaling pathway serves as an important intracellular defense mechanism, particularly for aquatic organisms exposed to environmental stressors and toxic substances. Environmental stimuli can disrupt an organism's internal redox balance, leading to cellular oxidative stress responses. To counteract these effects, cells develop intricate defense mechanisms, with the Nrf2-Keap1/ARE signaling pathway is playing a crucial role. In this pathway, the nuclear transcription factor Nrf2 translocates into the nucleus to initiate the transcription of antioxidant genes, thereby reducing reactive oxygen species (ROS)-induced cellular damage and maintaining the organism's oxidative-antioxidative equilibrium. While research on this pathway in mammals is well-established, studies on aquatic organisms are still limited. This review provides a comprehensive analysis of the regulatory functions of the Nrf2-Keap1/ARE pathway on oxidative stress and delves into the molecular structures of Nrf2, Keap1, and ARE, offering insights into the physiological regulation of antioxidant defenses in aquatic organisms.

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)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.971
Threshold uncertainty score0.868

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.033
GPT teacher head0.330
Teacher spread0.296 · 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 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

Citations28
Published2025
Admission routes1
Has abstractyes

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