The haemopoietic growth factor, Flt3L, alters the immune response induced by transcutaneous immunization
Bibliographic record
Abstract
Topical application of antigen induces antigen-specific humoral and cellular immune responses. In this study we examined whether expansion of dendritic cells (DC) by Flt3 ligand (Flt3L) treatment influences the induction of immune responses following transcutaneous immunization. Mice were treated intraperitoneally with Flt3L or phosphate-buffered saline (PBS) and immunized transcutaneously with hen egg lysozyme (HEL). Flt3L-treated mice developed lower HEL-specific cellular and humoral immune responses than PBS-treated mice. However, in the presence of cholera toxin (CT), a potent adjuvant for mucosal and transcutaneous immunization, Flt3L-treated mice developed significantly higher cellular and humoral immune responses to HEL when compared to PBS-treated mice. We assessed whether the immunomodulatory effects of CT were a result of activation of epidermal dendritic cells (Langerhans' cells; LC). Our results indicate that within 8-12 hr of topical application of CT, epidermal LC cells lose their dendritic morphology and become rounder in appearance. In addition, we observed enhanced expression of major histocompatibility complex (MHC) class II, and of adhesion molecules CD11c and intracellular adhesion molecule-1 (ICAM-1). Our observations support the concept that the state of activation of DC in the skin is central to the regulation of immune responses. This information is relevant to the design of effective transcutaneous vaccination strategies.
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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".