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Record W2082458666 · doi:10.2298/jsc0504601s

Manganese superoxide dismutase (MnSOD) catalyzes NO-dependent tyrosine residue nitration

2005· article· en· W2082458666 on OpenAlexaff
Srđan Đ. Stojanović, Dragana Stanić-Vučinić, Milan Nikolić, Smiljana Raicevic, Mihajlo Spasić, Vesna Niketić

Bibliographic record

VenueJournal of the Serbian Chemical Society · 2005
Typearticle
Languageen
FieldMedicine
TopicNitric Oxide and Endothelin Effects
Canadian institutionsInstitute for Biological Sciences
Fundersnot available
KeywordsPeroxynitriteNitrationChemistrySuperoxideTyrosineSuperoxide dismutaseBiochemistryEnzymeOxidative stressIn vivoNitric oxideBiologyOrganic chemistry

Abstract

fetched live from OpenAlex

The peroxynitrite-induced nitration of manganese superoxide dismutase (MnSOD) tyrosine residue, which causes enzyme inactivation, is well established. This led to suggestions that MnSOD nitration and inactivation in vivo, detected in various diseases associated with oxidative stress and overproduction of nitric monoxide (NO), conditions which favor peroxynitrite formation, is also caused by peroxynitrite. However, our previous in vitro study demonstrated that exposure of MnSOD to NO led to NO conversion into nitrosonium (NO+) and nitroxyl (NO?) species, which caused enzyme modifications and inactivation. Here it is reported that MnSOD is tyrosine nitrated upon exposure to NO, as well as that MnSOD nitration contributes to inactivation of the enzyme. Collectively, these observations provide a compelling argument supporting the generation of nitrating species in MnSOD exposed to NO and shed a new light on MnSOD tyrosine nitration and inactivation in vivo. This may represent a novel mechanism by which MnSOD protects cell from deleterious effects associated with overproduction of NO. However, extensive MnSOD modification and inactivation associated with prolonged exposure to NO will amplify the toxic effects caused by increased cell superoxide and NO levels.

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 score0.024
Threshold uncertainty score0.420

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.008
GPT teacher head0.240
Teacher spread0.232 · 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

Citations4
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the Serbian Chemical SocietySame topicNitric Oxide and Endothelin EffectsFrench-language works237,207