Potentiation of the immunotherapeutic effect of autologous dendritic cells by pretreating hepatocellular carcinoma with low-dose radiation
Bibliographic record
Abstract
PURPOSE: To determine whether exposing hepatocellular carcinoma (HCC) to low dose radiation increases the efficacy of dendritic cell-mediated immunotherapy for HCC. METHODS: Tumour specimens collected from 20 recruited patients with HCC were cultured in primary culture (half successfully) and then exposed to low-dose radiation (0.5 Gy). Immature DCs derived from peripheral blood monocytes of patients were pulsed with autologous HCC cell lysates and matured with a cytokine cocktail. Autologous tumour lysate-pulsed DCs (TLP-DCs) were used to stimulate mixed lymphocytes, which were then tested for inhibitory effect on the growth of HCC cells. Surface markers of immunogenicity on primary HCC cells, MHC, and Fas were investigated before and after low-dose irradiation. RESULTS: Exposing HCC cells to low-dose (0.5 Gy) radiation enhanced the immunotherapeutic effect of TLP-DC-stimulated lymphocytes. Growth inhibition increased from 50.6+/-7.5% without irradiation to 74.3+/-4.3% with radiation. The expression of MHC class ll and Fas was upregulated after irradiating HCC cells. CONCLUSION: Exposing tumour cells to a low dose of radiation can enhance the immunotherapeutic effect of the autologous tumor lysate-pulsed DC vaccine.
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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".