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Record W4390451416 · doi:10.1111/1753-0407.13524

Diabetic neuropathy: A <scp>NRF2</scp> disease?

2023· review· en· W4390451416 on OpenAlexfundno aff
Monica Neagu, Carolina Constantin, Mihaela Surcel, Adriana Munteanu, Cristian Scheau, Ilinca Săvulescu-Fiedler, Constantin Căruntu

Bibliographic record

VenueJournal of Diabetes · 2023
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics, phytochemicals, and oxidative stress
Canadian institutionsnot available
FundersInstitute of Infection and ImmunityUnitatea Executiva pentru Finantarea Invatamantului Superior, a Cercetarii, Dezvoltarii si Inovarii
KeywordsMedicineDiabetes mellitusDiabetic neuropathyDiseaseInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

The transcription factor nuclear factor erythroid 2-related factor 2 (NRF2) has multifarious action with its target genes having redox-regulating functions and being involved in inflammation control, proteostasis, autophagy, and metabolic pathways. Therefore, the genes controlled by NRF2 are involved in the pathogenesis of myriad diseases, such as cardiovascular diseases, metabolic syndrome, neurodegenerative diseases, autoimmune disorders, and cancer. Amidst this large array of diseases, diabetic neuropathy (DN) occurs in half of patients diagnosed with diabetes and appears as an injury inflicted upon peripheral and autonomic nervous systems. As a complex effector factor, NRF2 has entered the spotlight during the search of new biomarkers and/or new therapy targets in DN. Due to the growing attention for NRF2 as a modulating factor in several diseases, including DN, this paper aims to update the recently discovered regulatory pathways of NRF2 in oxidative stress, inflammation and immunity. It presents the animal models that further facilitated the human studies in regard to NRF2 modulation and the possibilities of using NRF2 as DN biomarker and/or as target therapy.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.847
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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 head0.030
GPT teacher head0.293
Teacher spread0.263 · 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 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

Citations20
Published2023
Admission routes1
Has abstractyes

Explore more

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