Immunogenic potential of mutations in mitochondrial DNA and possible implications in autoimmune disease (148.22)
Bibliographic record
Abstract
Abstract To seek the underlying cause of autoimmune diseases we tested the hypothesis that mutated self proteins from mitochondria are seen as foreign proteins. A total of 21 mitochondrial peptides were identified using epitope prediction tool, SYFPEITHI as likely HLA-A2 restricted peptides. In vitro T cell line assays were conducted based on MHC stabilization of the peptides on T2 cells. Ten peptides were identified and the significant correlations were observed between the insilico and in vitro binding affinities. To determine the frequency of T cellular memory for the identified mutated peptides, PBMCs from healthy donors were tested in INF gamma-ELISpot assays. Frequencies of T cells recognizing mutated self peptide ranged from as few as 10 in 200,000 to 90 in 200,000 of the PBMCs plated. Among A2-donors, significant T cell responses were seen with mean age of 61 years. Of the 21 peptides two peptides, named as P10 and P14 were identified to be immuno-dominant peptides based on the immunogenic response by most of the donors (both A2 and non-A2) tested. To further determine the phenotype of the responding T cells, T cell co-stimulation assays were done for selected peptides based on T2 binding and Elispot assay results. T cell co-stimulation assays further confirmed Elispot results and interestingly, both interferon gamma producing CD8+T cells and CD4+ T cells were identified. We propose and will discuss the role of these immunogenic peptides as “Enemies with-in”.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".