Transcript profiling of human dendritic cells maturation‐induced under defined culture conditions: comparison of the effects of tumour necrosis factor alpha, soluble CD40 ligand trimer and interferon gamma
Bibliographic record
Abstract
Using cDNA arrays, we characterized patterns of gene expression in populations of human dendritic cells (DCs) produced for clinical use. Culture and maturation induction of myeloid adherent cells under serum-free conditions yielded DCs with phenotypes similar to those described in serum-based systems. Analysis of gene expression in DCs treated with tumour necrosis factor alpha, soluble CD40L trimer or interferon gamma, however, showed specific patterns for each factor examined. Our studies document the expression of several transcripts that have not hitherto been described in DCs and/or differentially regulated according to the differentiation state of the DCs, and suggest important functional differences among the DC populations examined. In addition, DC maturation directs changes in the levels of mRNA specific for transcriptional regulators that effect the production of cytokines (e.g. BCL-6, c-rel). Other changes observed, including alteration in the gene expression profile of adhesion molecules and chemokine receptors such as CD44H, CD 49B, Rantes R, CXCR5 and CD37, suggest differences in trafficking potential between the populations studied. This broad-based description of DC populations, produced under serum-free conditions, has enabled us to better define intermediate stages of DC maturation as well as the differentiation-inducing effects of cytokines on these cells.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".