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Sulfur Amino Acid Deficiency Depresses Brain Glutathione Concentration

2001· article· en· W20103498 on OpenAlexaff
Phyllis G. Paterson, Andrew W. Lyon, Huse Kamencic, Bernhard H.J. Juurlink

Bibliographic record

VenueNutritional Neuroscience · 2001
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSulfur Compounds in Biology
Canadian institutionsUniversity of SaskatchewanCameco (Canada)
Fundersnot available
KeywordsGlutathioneCystineMethionineAmino acidCysteineChemistryAntioxidantSulfurGlutathione peroxidaseBiochemistryInternal medicineEndocrinologyOxidative stressBiologyMedicineEnzyme

Abstract

fetched live from OpenAlex

Dietary sulfur amino acid content is a major determinant of glutathione concentration in some tissues. We examined whether brain glutathione (GSH), a key component of antioxidant defense important for minimizing ischemic injury, was also responsive to short-term sulfur amino acid deficiency. Female Long-Evans adult rats were fed a sulfur-deficient L-amino acid defined diet for five days; the control diet was supplemented with L-cystine and L-methionine (n = 6). Sulfur amino acid deficiency was confirmed by a reduction in liver cysteine and GSH concentrations, marked decreases in food intake, and weight loss. GSH concentration analyzed by reverse-phase high performance liquid chromatography was significantly depressed in the neocortex and thalamus of deficient rats. Brain cysteine was not decreased in a parallel manner. Classical glutathione peroxidase activity was increased in the liver and brain of sulfur amino acid deficient rats. This suggests an upregulation of antioxidant defense but these findings may be complicated by alterations in tissue composition. The depletion of brain GSH by a reduced supply of dietary precursors may be important during brain ischemia when the rate of GSH utilization and the need for synthesis are increased.

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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.021
GPT teacher head0.271
Teacher spread0.250 · 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

Citations20
Published2001
Admission routes1
Has abstractyes

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