The inhibitory receptor Siglec-E controls antigen-presenting cell activation and T cell–mediated transplant rejection
Bibliographic record
Abstract
After transplantation, inflammation and tissue injury release danger signals that activate myeloid cells, driving adaptive immune responses and acute rejection. Current immunosuppressants primarily target T cells but inadequately control innate immunity. Regulatory signals controlling innate responses in transplantation remain elusive. The sialic acid-binding immunoglobulin-like lectin-E (Siglec-E, or SigE) binds sialylated ligands to suppress inflammation. In mouse heart transplants, SigE is up-regulated in graft-infiltrating myeloid cells, including dendritic cells (DCs). SigE deficiency in recipients, but not donors, accelerates acute rejection by enhancing DC activation, nuclear factor κB (NF-κB) signaling, and tumor necrosis factor-α (TNF-α) production, thereby boosting alloreactive T cell responses. Conversely, SigE overexpression on DCs reduces activation by danger signals and their T cell allostimulatory capacity. The human homologs Siglecs-7 and -9 were up-regulated in rejecting allograft biopsies, and their higher expression correlated with improved allograft survival. Thus, SigE/7/9 is a crucial inhibitory receptor controlling antigen-presenting cell activation and T cell-mediated transplant rejection, offering therapeutic potential.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| 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 teacher head, 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".