Human Monocyte–Derived Dendritic Cells Induce Naive T Cell Differentiation into T Helper Cell Type 2 (Th2) or Th1/Th2 Effectors
Bibliographic record
Abstract
The subset of dendritic cells (DCs) and the nature of the signal inducing DC maturation determine the capacity of DCs to generate polarized immune responses. In this study, we show that the ability of human monocyte-derived DCs (myeloid DC(1)) to promote T helper type 1 (Th1) or Th2 differentiation was also found to be critically dependent on stimulator/responder ratio. At a low ratio (1:300), mature DCs that have been differentiated after inflammatory (Staphylococcus aureus Cowan 1 or lipopolysaccharide) or T cell-dependent (CD40 ligand) stimulation induced naive T cells to become Th2 (interleukin [IL]-4(+), IL-5(+), interferon gamma) effectors. Th2 differentiation was dependent on B7-CD28 costimulation and enhanced by OX40-OX40 ligand interactions. However, high DC/T cell ratio (1:4) favored a mixed Th1/Th2 cell development. Thus, the fact that the same DC lineage stimulates polarized Th1 or Th2 responses may be relevant since it allows the antigen-presenting cells to initiate an appropriate response for the signal received at the peripheral sites. Controlling the number and the rate of DC migration to the T cell areas in lymphoid tissues may be important for the therapeutic use of DCs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.003 | 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".