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Record W2084076721 · doi:10.1002/glia.20514

Contrasting potential of nitric oxide and peroxynitrite to mediate oligodendrocyte injury in multiple sclerosis

2007· article· en· W2084076721 on OpenAlexaff
Carolyn Jack, Jack P. Antel, Wolfgang Brück, Tanja Kuhlmann

Bibliographic record

VenueGlia · 2007
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
Fundersnot available
KeywordsPeroxynitriteOligodendrocyteMultiple sclerosisNitric oxideNitrotyrosineBiologyNeurogliaMicrogliaNitric oxide synthaseCell biologyProgrammed cell deathImmunologyMyelinInflammationBiochemistryNeuroscienceApoptosisCentral nervous systemSuperoxideEndocrinologyEnzyme

Abstract

fetched live from OpenAlex

Nitric oxide (NO) and peroxynitrite (ONOO(-)) are potential mediators of the injury and cytotoxicity occurring over time to oligodendrocytes in multiple sclerosis (MS) lesions. Our in vitro results indicate that human adult CNS-derived oligodendrocytes are relatively resistant to NO-mediated damage. In contrast, human oligodendrocytes are highly susceptible to peroxynitrite-mediated injury. In situ, we found that inducible nitric oxide synthase (iNOS) was expressed in astrocytes and macrophages in all active demyelinating and remyelinating MS lesions examined, yet no correlation was found between numbers of glial cells expressing iNOS and the extent of oligodendrocyte cell death. Nitrotyrosine groups, indicative of the presence of peroxynitrite in vivo, could be detected on astrocytes, macrophages, and oligodendrocytes in MS lesions. High numbers of nitrotyrosine-positive oligodendrocytes were found in one MS case that featured extensive oligodendrocyte cell death. Our results indicate that NO alone is unlikely to induce oligodendrocyte injury, whereas its more potent byproduct peroxynitrite is a potential mediator of injury to oligodendrocytes in MS.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.655
Threshold uncertainty score0.655

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.047
GPT teacher head0.298
Teacher spread0.252 · 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 designObservational
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

Citations71
Published2007
Admission routes1
Has abstractyes

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