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Record W2034149255 · doi:10.1139/o00-018

Effect of pineal indoles on activities of the antioxidant defense enzymes superoxide dismutase, catalase, and glutathione reductase, and levels of reduced and oxidized glutathione in rat tissues

2000· article· en· W2034149255 on OpenAlexvenueno aff
F Liu, T.B. Ng

Bibliographic record

VenueBiochemistry and Cell Biology · 2000
Typearticle
Languageen
FieldNeuroscience
TopicCircadian rhythm and melatonin
Canadian institutionsnot available
FundersChinese University of Hong KongUniversity of Hong Kong
KeywordsSuperoxide dismutaseGlutathione reductaseEndocrinologyMelatoninGlutathioneIntraperitoneal injectionInternal medicineAntioxidantCatalaseChemistryDismutaseKidneyEnzymeGlutathione peroxidaseBiochemistryBiologyMedicine

Abstract

fetched live from OpenAlex

Male Sprague-Dawley rats were randomly divided into four groups. Two of the groups received a single intraperitoneal injection of melatonin and 5-methoxytryptamine (5 mg/kg body weight), respectively, at 9 PM. One group received an intraperitoneal injection of 5-methoxytryptophol (5 mg/kg body weight) at 9 AM. The remaining group received alcoholic saline (vehicle) and served as the control. All rats were sacrificed 90 min after injection and the livers, kidneys, and brains were dissected. The activities of superoxide dismutase, catalase, and glutathione reductase in the organs were measured. It was found that both melatonin and 5-methoxytryptamine were approximately equipotent in enhancing the activities of superoxide dismutase and glutathione reductase in the kidney and liver, while 5-methoxytryptophol displayed a weaker effect. Both melatonin and 5-methoxytryptamine augmented the level of reduced glutathione in the kidney and liver, while 5-methoxytryptophol did so only in the kidney. All three pineal indoles increased the activity of superoxide dismutase and lowered the ratio of oxidized to reduced glutathione in the brain.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.523

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 studies0.0000.001
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 head0.009
GPT teacher head0.237
Teacher spread0.228 · 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 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

Citations124
Published2000
Admission routes1
Has abstractyes

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