Involvement of Caveolin-1 in CD83 Internalization in Mouse Dendritic Cells
Bibliographic record
Abstract
To become potent T-cell stimulators, DCs need to mature. Treatment with soluble CD83 (sCD83) induces immune tolerance and protects against transplant rejection by maintaining dendritic cells in an immature, tolerogenic state. Until now, the mechanism through which sCD83 keeps DCs immature has not been investigated. The internalizing pathway of CD83 was screened by Western blot, and the direct interactions between internalized proteins were verified through coimmunoprecipitation (co-IP) and transmission electron microscopy (TEM). CD83 plasma membrane levels were detected by Western blot using a plasma membrane protein extraction protocol. The changes in CD83 surface levels in DCs were detected by flow cytometry. Caveolin-1 function was detected in a kidney transplant model. In this study, we demonstrated that caveolin-1 could affect CD83 level during endocytosis in mouse DCs. Caveolin-1 coprecipitates with CD83, as demonstrated by co-IP analysis. TEM morphometric analysis of the entire CD83 distribution associated with internalized caveolin-1 demonstrated a significant interaction in cellular vesicles. sCD83 reduces endogenous CD83 plasma membrane levels, and caveolin-1 knockdown reverts CD83 levels in plasma membrane. sCD83 treatment decreases CD83 surface levels in DCs. siRNA to caveolin-1 in DCs inhibits this effect of sCD83. The effects of sCD83-treated DCs were proved in CD1 mice. Knocking down caveolin-1 in DCs obstructs the effects of sCD83 on kidney transplant. In conclusion, our data indicated that a caveolin-dependent endocytic pathway is involved in CD83 internalization in DCs and that caveolin-1 is involved in the activity of DCs.
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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 | 0.001 | 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".