Heterogeneous populations from in vitro cultures of antigen presenting cells in pigs
Bibliographic record
Abstract
Dendritic cells (DCs) are the most potent antigen presenting cells (APCs). Because of the difficulty in obtaining these cells directly from tissues, different sources of DCs are frequently used for in vitro experimentation and many of their biological and functional characteristics were studied using these systems. Until recently, it was assumed that specific culture conditions polarized the differentiation of either DCs or macrophages (Macs); however, it was shown that some DC culture systems in other species generate heterogeneous cell populations that can be identified according to their CD11c and MHC class II (MHC-II) expression. Following this approach, porcine DCs were directly isolated from peripheral blood or differentiated in vitro by culturing bone marrow (BM) progenitor cells or blood monocytes treated with growth factors. Mostly homogeneous monocyte-derived DCs (MoDCs) were obtained with similar phenotype and phagocytic characteristics to that of blood DCs. On the contrary, BM-derived DC (BMDC) cultures generated two distinct heterogeneous populations identified as MHC-II+ and MHC-II++ cells. BMDCs MHC-II+ had similar phenotypic and phagocytic characteristics to those of MoDCs and blood DCs. However, BMDCs MHC-II++ population expressed a higher amount of surface markers and transcribed genes associated with Macs-lineage exhibiting a higher phagocytic capacity than all the other cells. Noteworthy, every cell system expressed different genetic signatures. These results will help interpreting and re-interpreting data obtained using in vitro systems.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".