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Record W4404485113 · doi:10.3390/antiox13111401

Oxidative Stress in an African Ground Squirrel, a Case of Healthy Aging and Reproduction

2024· article· en· W4404485113 on OpenAlexaff
Paul J. Jacobs, Sjoerd Vos, Chelsea E. Bishop, Daniel W. Hart, Nigel C. Bennett, Jane M. Waterman

Bibliographic record

VenueAntioxidants · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBat Biology and Ecology Studies
Canadian institutionsUniversity of Manitoba
FundersNatural Environment Research CouncilNational Research Foundation
KeywordsOxidative stressReproductionGround squirrelOxidative damageBiologyEcologySquirrel monkeyEndocrinology

Abstract

fetched live from OpenAlex

Oxidative stress plays a crucial role in mediating life-history processes, where it can compromise survival and reproduction through harmful alterations to DNA, lipids, and proteins. In this study, we investigated oxidative stress in Cape ground squirrels (Xerus inauris), a longer-lived African ground squirrel species with a high reproductive skew and unique life history strategies. We measured oxidative stress as total antioxidant capacity (TAC), total oxidant status (TOS), and an oxidative stress index (OSI) in blood plasma from individuals of approximately known ages. Our results reveal a distinct pattern of decreasing oxidative stress with age, consistent across both sexes. Females exhibited lower OSI and TOS levels than males. Males employing different life-history strategies, namely natal (staying at home), had significantly lower oxidative stress compared to the band (roaming male groups), likely due to variations in metabolic rate, activity, and feeding rates. However, both strategies exhibited reduced oxidative stress with age, though the underlying mechanisms require further investigation. We propose that selection pressures favoring survival contributed to the observed reduction in oxidative stress with age, potentially maximizing lifetime reproductive success in this species.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.447
Threshold uncertainty score0.822

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.037
GPT teacher head0.291
Teacher spread0.254 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2024
Admission routes1
Has abstractyes

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