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Record W3120573421 · doi:10.3390/antiox10010075

Counteracting Effects of Glutathione on the Glutamate-Driven Excitation/Inhibition Imbalance in First-Episode Schizophrenia: A 7T MRS and Dynamic Causal Modeling Study

2021· article· en· W3120573421 on OpenAlexafffund
Roberto Limongi, Peter Jeon, Jean Théberge, Lena Palaniyappan

Bibliographic record

VenueAntioxidants · 2021
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsSt Joseph's Health CareLawson Health Research InstituteWestern University
FundersCanadian Institutes of Health Research
KeywordsGlutamate receptorGlutamatergicGlutathioneNeuroscienceExcitatory postsynaptic potentialNMDA receptorChemistryOxidative stressFunctional magnetic resonance imagingInhibitory postsynaptic potentialPsychologyBiochemistryReceptor

Abstract

fetched live from OpenAlex

Oxidative stress plays a key role in the pathophysiology of schizophrenia. While free radicals produced by glutamatergic excess and oxidative metabolism have damaging effects on brain tissue, antioxidants such as glutathione (GSH) counteract these effects. The interaction between glutamate (GLU) and GSH is centered on N-Methyl-D-aspartate (NMDA) receptors. GSH levels increase during glutamate-mediated excitatory neuronal activity, which serves as a checkpoint to protect neurons from oxidative damage and reduce excitatory overdrive. We studied the possible influence of GSH on the glutamate-mediated dysconnectivity in 19 first-episode schizophrenia (FES) patients and 20 healthy control (HC) subjects. Using ultra-high field (7 Tesla) magnetic resonance spectroscopy (MRS) and resting state functional magnetic resonance imaging (fMRI), we measured GSH and GLU levels in the dorsal anterior cingulate cortex (dACC) and blood-oxygenation level-dependent activity in both the dACC and the anterior insula (AI). Using spectral dynamic causal modeling, we found that when compared to HCs, in FES patients inhibitory activity within the dACC decreased with GLU levels whereas inhibitory activity in both the dACC and AI increased with GSH levels. Our model explains how higher levels of GSH can reverse the downstream pathophysiological effects of a hyperglutamatergic state in FES. This provides an initial insight into the possible mechanistic effect of antioxidant system on the excitatory overdrive in the salience network (dACC-AI).

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.787
Threshold uncertainty score0.413

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 head0.013
GPT teacher head0.298
Teacher spread0.285 · 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

Citations40
Published2021
Admission routes2
Has abstractyes

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