Suppression of a broad spectrum of liver autoimmune pathologies by single peptide-MHC-based nanomedicines
Bibliographic record
Abstract
Peptide-major histocompatibility complex class II (pMHCII)-based nanomedicines displaying tissue-specific autoantigenic epitopes can blunt specific autoimmune conditions by re-programming cognate antigen-experienced CD4+ T-cells into disease-suppressing T-regulatory type 1 (TR1) cells. Here, we show that single pMHCII-based nanomedicines displaying epitopes from mitochondrial, endoplasmic reticulum or cytoplasmic antigens associated with primary biliary cholangitis (PBC) or autoimmune hepatitis (AIH) can broadly blunt PBC, AIH and Primary Sclerosing Cholangitis in various murine models in an organ- rather than disease-specific manner, without suppressing general or local immunity against infection or metastatic tumors. Therapeutic activity is associated with cognate TR1 cell formation and expansion, TR1 cell recruitment to the liver and draining lymph nodes, local B-regulatory cell formation and profound suppression of the pro-inflammatory capacity of liver and liver-proximal myeloid dendritic cells and Kupffer cells. Thus, autoreactivity against liver-enriched autoantigens in liver autoimmunity is not disease-specific and can be harnessed to treat various liver autoimmune diseases broadly.
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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) | 0.001 | 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".