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Record W3091387989 · doi:10.1111/jocd.13751

Teachings from COVID‐19 and aging—An oxidative process

2020· review· en· W3091387989 on OpenAlexaff
Misha Zarbafian, Steven Dayan, Sabrina G. Fabi

Bibliographic record

VenueJournal of Cosmetic Dermatology · 2020
Typereview
Languageen
FieldNursing
TopicVitamin C and Antioxidants Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Process (computing)Skin AgingMedicineVirologyComputer scienceDermatologyInternal medicine

Abstract

fetched live from OpenAlex

As of June 2020, the COVID-19 pandemic has totaled over 9 000 000 cases and 470 000 deaths globally (ref. 1). Emerging data from COVID-19 patients have suggested a clear role for oxidative stress in the pathogenesis of SARS-CoV-2, the pathogenic agent of COVID-19. Several comorbidities, including hypertension, diabetes, obesity, and aging, have been associated with an increase in baseline oxidative stress, likely explaining why such individuals at risk for poor outcomes with SARS-CoV-2 infection. Similarly, the concept of oxidative stress remains one of the best supported theories to explain the mechanism behind aging. Oxidative stress through both endogenous and exogenous sources has known deleterious effects in both aging and SARS-CoV-2 infection. Herein, we will review the role of oxidative stress as a key player in both aging and COVID-19 and highlight why some individuals may have better or poorer outcomes because of this. Additionally, we will discuss potential therapeutic pathways for effectively anti-aging as we take away from our learnings on COVID-19.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.982
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.061
GPT teacher head0.426
Teacher spread0.365 · 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 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

Citations13
Published2020
Admission routes1
Has abstractyes

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