Effect of Serum and Antioxidants on the Immunogenicity of Protein Kinase C-Activated Chronic Lymphocytic Leukemia Cells
Bibliographic record
Abstract
Since the intrinsically poor immunogenicity of chronic lymphocytic leukemia (CLL) cells might be a key factor in allowing them to avoid immune control mechanisms, the development of methods to enhance CLL cell immunogenicity might lead to improved disease control. The ability of CLL cells to stimulate T cells was increased significantly by the protein kinase C (PKC) agonist phorbol myristic acetate (PMA). However, under serum-free conditions, PMA-activated CLL cells died within 48 hours. Antioxidants, such as 2-mercaptoethanol (2-ME), or fetal calf serum could prevent the death of these cells but caused them to enter distinct states of differentiation. In the presence of 2-ME, PMA-activated CLL cells extended dendritic-like protrusions and exhibited increased T-cell stimulatory capacity. In the presence of serum, PMA-activated CLL cells developed fewer dendrites, made less IL-10 and more IL-12 p40 mRNA transcripts, and showed an increased capacity to induce IFN-gamma production by T cells. The effects of serum on the promotion of type 1 immune responses by phorbol ester-activated CLL cells were dominant and correlated with activation of the NF-kappaB signaling pathway. Other PKC agonists, such as Bryostatin-1 and a synthetic Bryostatin analog (Picolog), had similar effects on CLL cells. The observation that CLL cells can acquire features of dendritic cells that promote type 1 immunity may find clinical application in immunotherapeutic strategies for this disease.
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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) | 0.001 | 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 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".