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Record W4413003716 · doi:10.3390/ijms26157520

Antioxidants and Reactive Oxygen Species: Shaping Human Health and Disease Outcomes

2025· review· en· W4413003716 on OpenAlexaff
Charles F. Manful, Eric Fordjour, Dasinaa Subramaniam, Albert Adu Sey, Lord Abbey, Raymond Thomas

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2025
Typereview
Languageen
FieldNursing
TopicVitamin C and Antioxidants Research
Canadian institutionsDalhousie UniversityWestern UniversityMemorial University of Newfoundland
Fundersnot available
KeywordsOxidative stressReactive oxygen speciesReactive nitrogen speciesAntioxidantMedicineDiseaseBioinformaticsPharmacologyBiologyCell biologyBiochemistryPathologyInternal medicine

Abstract

fetched live from OpenAlex

Reactive molecules, including oxygen and nitrogen species, serve dual roles in human physiology. While they function as essential signaling molecules under normal physiological conditions, they contribute to cellular dysfunction and damage when produced in excess by normal metabolism or in response to stressors. Oxidative/nitrosative stress is a pathological state, resulting from the overproduction of reactive species exceeding the antioxidant capacity of the body, which is implicated in several chronic human diseases. Antioxidant therapies aimed at restoring redox balance and preventing oxidative/nitrosative stress have demonstrated efficacy in preclinical models. However, their clinical applications have met with inconsistent success owing to efficacy, safety, and bioavailability concerns. This summative review analyzes the role of reactive species in human pathophysiology, the mechanisms of action of antioxidant protection, and the challenges that hinder their translation into effective clinical therapies in order to evaluate potential emerging strategies such as targeted delivery systems, precision medicine, and synergistic therapeutic approaches, among others, to overcome current limitations. By integrating recent advances, this review highlights the value of targeting reactive species in the prevention and management of chronic diseases.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score0.661

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
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 head0.093
GPT teacher head0.448
Teacher spread0.355 · 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 designOther design
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

Citations70
Published2025
Admission routes1
Has abstractyes

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