A comparison between isolated blood dendritic cells and monocyte‐derived dendritic cells in pigs
Bibliographic record
Abstract
Various dendritic cell (DC) populations exist that differ in phenotype and ability to present antigen to T cells. For example, plasmacytoid DCs (pDCs) are less potent T cell activators compared with conventional DCs (cDCs). Here, we compared porcine blood DCs (BDCs), containing pDCs and cDCs, and monocyte-derived DCs (MoDC), consisting of cDCs, in their phenotype, ability to uptake antigen, activation and maturation and their ability to present antigen to autologous T cells. Pigs represent an important animal model, whose immune system in many respects closely resembles that of humans. For example, the distribution of Toll-like receptors is similar to that of humans, in contrast to that of mice. Here we demonstrate that both populations endocytose foreign material. Following lipopolysaccharide stimulation, CD80/86 and chemokine receptor (CCR)7 expression was increased in both populations as was the expression of the chemokine ligands (CCL)-2, CCL-4, CCL-20 and CXCL-2. Although basal and post-stimulation protein concentrations of interleukins 6 and 8 and tumour necrosis factor-alpha were higher in MoDCs, protein concentrations showed a higher fold increase in BDCs. Antigen-specific proliferation of autologous T cells was induced by MoDCs and BDCs. Interestingly, while MoDCs induced stronger proliferation in naive T cells, no difference in proliferation was observed when primed T cells were studied. These results demonstrate that isolated porcine BDCs are highly responsive to stimulation with lipopolysaccharide and are functionally able to drive primed T-cell proliferation to the same extent as MoDCs.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".