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Record W2024344447 · doi:10.1002/hup.1076

Lack of association of GPX1 and MnSOD genes with symptom severity and response to clozapine treatment in schizophrenia subjects

2009· article· en· W2024344447 on OpenAlexaff
Renan P. Souza, Maria Tampakeras, Vince Basile, Takahiro Shinkai, Daniela Valadão Rosa, Steven G. Potkin, Herbert Y. Meltzer, Jeffrey A. Lieberman, Marco Aurélio Romano‐Silva, James L. Kennedy

Bibliographic record

VenueHuman Psychopharmacology Clinical and Experimental · 2009
Typearticle
Languageen
FieldNeuroscience
TopicTryptophan and brain disorders
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsClozapineGPX1Internal medicineOxidative stressSchizophrenia (object-oriented programming)Glutathione peroxidaseMedicineAntioxidantLipid peroxidationEndocrinologyPsychiatrySuperoxide dismutaseBiologyBiochemistry

Abstract

fetched live from OpenAlex

Abnormal activities of critical antioxidant enzymes and other indices of lipid peroxidation in plasma and red blood cells were detected in patients with schizophrenia. Other results have shown that oxidative stress may be modulated by clozapine. Based on that and some studies already found different clinical relations between reactive oxygen species and negative and positive symptoms, we evaluated association between clinical response and the polymorphism in the human glutathione peroxidase (GPX1) (Pro200Leu, rs1050450) and manganese SOD (MNSOD) (Ala16Val, rs4880) gene in 216 clozapine-treated patients with schizophrenia. No association was found with these two functional polymorphisms and clozapine response and symptom change after 6 months. No correlations were found between positive/negative symptoms score and both polymorphisms. Our results present that GPX1 (Pro200Leu) and MNSOD (Ala16Val) polymorphisms seem do not play a central role in the clozapine response, although studies in larger and independent samples are necessary to confirm our findings.

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 score0.485
Threshold uncertainty score0.467

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 head0.053
GPT teacher head0.412
Teacher spread0.359 · 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

Citations17
Published2009
Admission routes1
Has abstractyes

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