Trafficking, Ubiquitination, and Down-regulation of the Human Platelet-activating Factor Receptor
Bibliographic record
Abstract
Platelet-activating factor (PAF) is a potent phospholipid mediator involved in various disease states such as allergic asthma, atherosclerosis and psoriasis. The human PAF receptor (PAFR) is a member of the G protein-coupled receptor family. Following PAF stimulation, cells become rapidly desensitized; this refractory state can be maintained for hours and is dependent on PAFR phosphorylation, internalization, and down-regulation. In this report, we characterized ligand-induced, long term PAFR desensitization, and pathways leading to its degradation. Some GPCRs are known to be targeted to proteasomes for degradation while others traffic via the early/late endosomes toward lysosomes. Specific inhibitors of lysosomal proteases and inhibitors of the proteasome were effective in reducing the ligand-induced PAFR down-regulation by 40 and 25%, respectively, indicating the importance of receptor targeting to both lysosomes and proteasomes in long term cell desensitization to PAF. The effects of the proteasome and lysosomal protease inhibitors were additive and, together, completely blocked ligand-induced degradation of PAFR. Using dominant-negative Rab5 and 7 and colocalization of the PAFR with the early endosome autoantigen I (EEAI) or transferrin, we confirmed that ligand-induced PAFR down-regulation was Rab5/7-dependent and involved lysosomal degradation. In addition, we also demonstrated that PAFR was ubiquitinated in an agonist-independent manner. However, a dominant negative ubiquitin ligase (NCbl) reduced PAFR ubiquitination and inhibited ligand-induced but not basal receptor degradation. Our results indicate that PAFR degradation can occur via both the proteasome and lysosomal pathways and ligand-stimulated degradation is ubiquitin-dependent.
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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".