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Record W2051103031 · doi:10.1080/10715760310001643294

Increased Levels of Superoxide in Brains from Old Female Rats

2003· article· en· W2051103031 on OpenAlexfundno aff
Daniel Antier, H Carswell, M. Julia Brosnan, Carlene A. Hamilton, I. Mhairi Macrae, S. Groves, E. Jardine, John L. Reid, Anna F. Dominiczak

Bibliographic record

VenueFree Radical Research · 2003
Typearticle
Languageen
FieldMedicine
TopicAntioxidant Activity and Oxidative Stress
Canadian institutionsnot available
FundersYork University
KeywordsEndocrinologyInternal medicineHippocampusStriatumLucigeninSuperoxide dismutaseAgeingSuperoxideOxidative stressCortex (anatomy)Cerebral cortexBlotMedicineChemistryDopamineBiologyEnzymeNeuroscienceBiochemistry

Abstract

fetched live from OpenAlex

Hypertension, aging and a range of neurodegenerative diseases are associated with increased oxidative damage. The present study examined whether superoxide (O2*-) levels in brain are increased during aging in female rats, and the role of superoxide dismutase (SOD) and oestrogen in regulating O2*- levels. Young adult (3 month) and old (11 month) female spontaneously hypertensive stroke prone rats (SHRSP) and normotensive Wistar-Kyoto rats (WKY) were studied. O2*- levels were measured in brain homogenates by lucigenin chemiluminescence and SOD expression by Western blotting. Ageing significantly increased brain O2*- levels in WKY (cortex +216%, hippocampus +320%, striatum +225%) and to a greater extent in SHRSP (cortex +540%, hippocampus +580%, striatum +533%). Older SHRSP showed a decline in cortical Cu/Zn SOD expression compared to young adult SHRSP. Oestrogen did not attenuate O2*- levels. The results show a significant age-dependent increase in brain O2*- levels which is exaggerated in SHRSP. The excess cortical O2*- levels in the SHRSP may be associated with a down-regulation of Cu/Zn SOD but are not related to a decrease in oestrogen.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.143
GPT teacher head0.397
Teacher spread0.255 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations15
Published2003
Admission routes1
Has abstractyes

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