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Record W2053995146 · doi:10.1021/bi051152f

Autocatalytic Cleavage of Myelin Basic Protein: An Alternative to Molecular Mimicry

2005· article· en· W2053995146 on OpenAlexaff
Cheryl D’Souza, D. D. Wood, Yi‐Min She, Mario A. Moscarello

Bibliographic record

VenueBiochemistry · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPrion Diseases and Protein Misfolding
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMimicryAutocatalysisChemistryCleavage (geology)MyelinMolecular mimicryBiochemistryBiophysicsComputational biologyCell biologyBiologyNeuroscienceGeneticsZoologyCentral nervous systemAntigen

Abstract

fetched live from OpenAlex

Although multiple sclerosis (MS) is thought to be an autoimmune disease, the mechanisms by which immunodominant epitopes are generated and lymphocytes are activated are not known. Here, myelin basic protein-component 1 (MBP-C1) from MS tissue was shown to undergo autocatalytic cleavage at slightly alkaline pH. Importantly, one of the major peptides released contained the immunodominant epitope 84-89. Interestingly, MBP isolated from MS patients showed a faster time course of cleavage and a more robust release of epitope 84-89 than MBP isolated from normal individuals. The cleavage reaction was not inhibited by protease inhibitors, except for phenylmethanesulfonyl fluoride (PMSF), a serine protease inhibitor. Since PMSF inhibition suggested a role for a serine residue in the cleavage, we labeled myelin basic protein with diisopropyl fluorophosphate (DFP), known to bind active site serine residues. Mass spectrometry was used to identify the labeled peptide, which consisted of residues 140-152. Since this peptide contained a single serine residue, we concluded it to be the active serine. The importance of this cleavage mechanism is that it provides for a ready source of the immunodominant peptide for sensitization of T-cells. It is not necessary to invoke other mechanisms such as molecular mimicry.

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 score0.014
Threshold uncertainty score0.892

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 head0.008
GPT teacher head0.261
Teacher spread0.253 · 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

Citations47
Published2005
Admission routes1
Has abstractyes

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