Culture of myeloid dendritic cells from bone marrow precursors
Bibliographic record
Abstract
Myeloid dendritic cells (DCs) are frequently used to study the interactions between innate and adaptive immune mechanisms and the early response to infection. Because these are the most potent antigen presenting cells, DCs are being increasingly used as a vaccine vector to study the induction of antigen-specific immune responses. In this video, we demonstrate the procedure for harvesting tibias and femurs from a donor mouse, processing the bone marrow and differentiating DCs in vitro. The properties of DCs change following stimulation: immature dendritic cells are potent phagocytes, whereas mature DCs are capable of antigen presentation and interaction with CD4+ and CD8+ T cells. This change in functional activity corresponds with the upregulation of cell surface markers and cytokine production. Many agents can be used to mature DCs, including cytokines and toll-like receptor ligands. In this video, we demonstrate flow cytometric comparisons of expression of two co-stimulatory molecules, CD86 and CD40, and the cytokine, IL-12, following overnight stimulation with CpG or mock treatment. After differentiation, DCs can be further manipulated for use as a vaccine vector or to generate antigen-specific immune responses by in vitro pulsing using peptides or proteins, or transduced using recombinant viral vectors.
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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) | 0.004 | 0.005 |
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".