The Parkinson's disease‐associated <scp>GPR</scp>37 receptor‐mediated cytotoxicity is controlled by its intracellular cysteine‐rich domain
Bibliographic record
Abstract
GPR37, also known as parkin-associated endothelin-like receptor (Pael-R), is an orphan G protein-coupled receptor (GPCR) that aggregates intracellularly in a juvenile form of Parkinson's disease. However, little is known about the structure or function of this receptor. Here, in order to better understand the functioning of this receptor, we focused on the GPR37 C-terminal tail, in particular on a cystein-enriched region. Thus, we aimed to reveal the role of these residues on receptor plasma membrane expression and function, and also whether the presence of this cysteine-rich domain is linked to the previously described receptor-mediated cytotoxicity. Interestingly, while the deletion of six cysteine residues within this region did not affect receptor internalization it promoted GPR37 plasma membrane expression and signaling. Furthermore, the removal of the C-terminal cysteine-rich domain protected against GPR37-mediated apoptosis and cell death. Overall, we identified a GPR37 domain, namely the C-terminal tail cysteine-rich domain, which played a critical role in receptor cell surface expression, function and GPR37-mediated cytotoxicity. These results might contribute to better comprehend the pathophysiology (i.e. in Parkinson's disease) of this rather unknown member of the GPCR family.
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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".