LRRK2 regulates the activation of the unfolded protein response and antigen presentation in macrophages during inflammation
Bibliographic record
Abstract
Abstract While the contribution of inflammation in the pathological process leading to Parkinson’s disease (PD) is well established, a growing body of evidence supports a role for the long-lasting adaptive immune system in the disease. We showed that, in inflammatory conditions, the PD-proteins PINK1 and Parkin negatively regulate the presentation of mitochondrial antigens on MHC I molecules, a process referred to as MitAP ( Mit ochondrial A ntigen P resentation). In the absence of PINK1, over-activation of this pathway in antigen-presenting cells (APCs) engages autoimmune mechanisms leading to the establishment of cytotoxic CD8 + T cells. Co-culture of dopaminergic neurons (DNs) with these T cells led to neuronal cell death, suggesting that the MitAP in DNs made them susceptible to T cell-mediated destruction. In the present study, we used a pharmacological and genetic approach to characterize the MitAP pathway at the molecular level. We showed that this antigen presentation pathway is induced in APCs in response to inflammatory signals through the sequential activation of TLR4, cGAS-STING and the Unfolded Protein Response (UPR). A “UPR motif” present on a STING cytoplasmic domain was shown to specifically activate the UPR sensor IRE1. Remarkably, the PD-related protein LRRK2, acted with STING upstream of the UPR to regulate the transition from innate to adaptive immunity, thereby identifying this PD-related protein as a key player in the immune response during inflammation.
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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 | 0.001 |
| 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".