Autocatalytic Cleavage of Myelin Basic Protein: An Alternative to Molecular Mimicry
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".