Annexin‐1‐deficient dendritic cells acquire a mature phenotype during differentiation
Bibliographic record
Abstract
Dendritic cells play a key role in the adaptive immune system by influencing T-cell differentiation. Annexin-1 (Anx-A1) has recently been shown to modulate the adaptive immune response by regulating T-cell activation and differentiation. Here we investigated the role of endogenous Anx-A1 in dendritic cells as major cellular counterpart of T-cell-driven immune response. We found that Anx-A1(-/-) bone marrow-derived dendritic cells show an increased number of CD11c(+) cells expressing high levels of some maturation markers, such as CD40, CD54, and CD80, coupled to a decreased capacity to take up antigen compared to control Anx-A1(+/+) cells. However, analysis of LPS-treated dendritic cells from Anx-A1(-/-) mice demonstrated a diminished up-regulation of maturation markers, a decreased migratory activity in vivo, and an attenuated production of the inflammatory cytokines interleukin (IL)-1beta, tumor necrosis factor (TNF)-alpha, and IL-12. This defect was also accompanied by impaired nuclear factor (NF)-kappaB/DNA-binding activity and lack of Anx-A1 signaling, as demonstrated by the reduced activation of extracellular-signal regulated kinase (ERK)1/2 and Akt compared to cells from control littermates. As a consequence of this phenotype, Anx-A1(-/-) dendritic cells showed an impaired capacity to stimulate T-cell proliferation and differentiation in mixed leukocyte reaction. Together, these findings suggest that inhibition of Anx-A1 expression or function in dendritic cells might represent a useful way to modulate the adaptive immune response and pathogen-induced T-cell-driven immune diseases.
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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 | 0.000 | 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 | 0.001 | 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 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".