Intradermally Administered Retinoic Acid or Vitamin D3‐Loaded Liposomes Induce Tolerogenic Skin Dendritic Cells
Bibliographic record
Abstract
In vivo targeting of dendritic cells (DCs) with nanocarriers containing tolerogenic adjuvants is an attractive strategy to dampen inflammation. Here, we used ex vivo skin vaccination to examine the effect of intradermal injection of liposomes loaded with the tolerogenic adjuvants all-trans retinoic acid (RA) and vitamin D3 (VD3). We investigated the effect of intradermal liposome injection on skin DCs and the skin DC-induced T cell response. Our study shows that intradermal injection of RA or VD3-loaded anionic phospholipid 1,2-distearoyl-sn-glycero-3-phosphoglycerol (DSPG) liposomes selectively induces CD14+ dermal DC (DDC) migration while reducing migration of CD1a dim DDCs. Migrated CD14+ DDCs displayed a partially immature phenotype. RA or VD3 liposome-treated CD1a dim DDCs exhibited reduced expression of maturation markers and induced expression of coinhibitory immunoglobulin-like transcript 3 (ILT3). VD3 liposome-treated CD14+ DDCs, as well as, CD1a dim DDCs, exhibited reduced expression of maturation markers, induction of coinhibitory molecules ILT3, and programmed death-ligand 1 (PD-L1). Migrated DCs from RA or VD3 liposome-injected skin differentiated naïve CD4+ T cells into FoxP3+ CD127 low and ICOS+ Tregs, expressing functional regulatory markers. Thus, our findings provide further substantiation for in vivo DC-modulating vaccines with tolerogenic liposomes as a putative clinical therapy for autoimmune diseases and allergies.
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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 | 0.001 |
| 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".