Porcine Neonatal Blood Dendritic Cells, but Not Monocytes, Are More Responsive to TLRs Stimulation than Their Adult Counterparts
Bibliographic record
Abstract
The neonatal immune system is often considered as immature or impaired compared to the adult immune system. This higher susceptibility to infections is partly due to the skewing of the neonatal immune response towards a Th2 response. Activation and maturation of dendritic cells (DCs) play an important role in shaping the immune response, therefore, DCs are a target of choice for the development of efficient and protective vaccine formulations able to redirect the neonatal immune response to a protective Th1 response. As pigs are becoming more important for vaccine development studies due to their similarity to the human immune system, we decided to compare the activation and maturation of a subpopulation of porcine DCs in adult and neonatal pigs following stimulation with different TLR ligands, which are promising candidates for adjuvants in vaccine formulations. Porcine blood derived DCs (BDCs) were directly isolated from blood and consisted of a mix of conventional and plasmacytoid DCs. Following CpG ODN (TLR9 ligand) and imiquimod (TLR7 ligand) stimulation, neonatal BDCs showed higher levels of expression of costimulatory molecules and similar (CpG ODN) or higher (imiquimod) levels of IL-12 compared to adult BDCs. Another interesting feature was that only neonatal BDCs produced IFN-α after TLR7 or TLR9 ligand stimulation. Stimulation with CpG ODN and imiquimod also induced enhanced expression of several chemokines. Moreover, in a mixed leukocyte reaction assay, neonatal BDCs displayed a greater ability to induce lymphoproliferation. These findings suggest that when stimulated via TLR7 or TLR9 porcine DCs display similar if not better response than adult porcine DCs.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".