Clec12a inhibits MSU-induced immune activation through lipid raft expulsion
Bibliographic record
Abstract
Monosodium uric acid (MSU) crystal, the etiological agent of gout, has been shown to trigger innate immune responses via multiple pathways. It is known that MSU-induced lipid sorting on plasma membrane promotes the phosphorylation of Syk and eventually leads to the activation of phagocytes. However, whether this membrane lipid-centric mechanism is regulated by other processes is unclear. Previous studies showed that Clec12a, a member of the C-type lectin receptor family, is reported to recognize MSU and suppresses this crystalline structure-induced immune activation. How this scenario is integrated into the lipid sorting-mediated inflammatory responses by MSU, and particularly, how Clec12a intercepts lipid raft-originated signaling cascade remains to be elucidated. Here, we found that the ITIM motif of Clec12a is dispensable for its inhibition of MSU-mediated signaling; instead, the transmembrane domain of Clec12a disrupts MSU-induced lipid raft recruitment and thus attenuates downstream signals. Single amino acid mutagenesis study showed the critical role of phenylalanine in the transmembrane region for the interactions between C-type lectin receptors and lipid rafts, which is critical for the regulation of MSU-mediated lipid sorting and phagocyte activation. Overall, our study provides new insights for the molecular mechanisms of solid particle-induced immune activation and may lead to new strategies in inflammation control.
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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".