CD40 stimulation induces differentiation of acute lymphoblastic leukemia cells into dendritic cells.
Bibliographic record
Abstract
UNLABELLED: Despite the very high percentage of long-term remissions in acute lymphoblastic leukemia (ALL) in children, some of them suffer from recurrence of the disease. New treatment modalities, e.g. effective geno- and immunotherapy are needed. The use of neoplasmatic cells to present tumor antigens is one of the approaches in cancer vaccines. ALL cells lack the expression of costimulatory molecules and are poor antigen presenting cells (APCs) for T-cell activation. CD40/40L interaction stimulates B-cells to proliferate, differentiate, upregulate costimulatory molecules and increase antigen presentation. The aim of the study was to test the hypothesis that ALL cells can be turned into professional APCs by CD40L activation. Children with B-cell precursor ALL were enrolled into the study. Mononuclear cells from bone marrow or peripheral blood were stimulated with CD40L and interleukin 4. RESULTS: 1) after culture we noted upregulation of all assessed costimulatory, adhesion and activatory molecules i.e. CD1a, CD11c, CD40, CD54, CD80, CD83, CD86, CD123, HLA class I and II; 2) CD40L activated ALL cells induced proliferation of allogeneic T-cells (measured by [(3)H]thymidine incorporation). These results confirm the possibility of enhancing the immunogenicity of ALL cells with the CD40L system and indicate that this approach can be used in immunotherapeutic trials.
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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) | 0.003 | 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".