CD45 Regulates TLR-Induced Proinflammatory Cytokine and IFN-β Secretion in Dendritic Cells
Bibliographic record
Abstract
CD45 is a leukocyte-specific protein tyrosine phosphatase and an important regulator of AgR signaling in lymphocytes. However, its function in other leukocytes is not well-understood. In this study, we examine the function of CD45 in dendritic cells (DCs). Analysis of DCs from CD45-positive and CD45-null mice revealed that CD45 is not required for the development of DCs but does influence DC maturation induced by TLR agonists. CD45 affected the phosphorylation state of Lyn, Hck, and Fyn in bone marrow-derived DCs and dysregulated LPS-induced Lyn activation. CD45 affected TLR4-induced proinflammatory cytokine and IFN-beta secretion and TLR4-activated CD45-null DCs had a reduced ability to activate NK and Th1 cells to produce IFN-gamma. Interestingly, the effect of CD45 on TLR-induced cytokine secretion depended on the TLR activated. Analysis of CD45-negative DCs indicated a negative effect of CD45 on TLR2 and 9, MyD88-dependent cytokine production, and a positive effect on TLR3 and 4, MyD88-independent IFN-beta secretion. This indicates a new role for CD45 in regulating TLR-induced responses in DCs and implicates CD45 in a wider regulatory role in innate and adaptive immunity.
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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 | 0.001 | 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".