Increased Radiosensitivity in Cells of Two Human Cell Lines Treated with Bystander Medium from Irradiated Repair-Deficient Cells
Bibliographic record
Abstract
Radiation-induced bystander factors have been shown to be more toxic if they are from medium harvested from irradiated repair-deficient cells. The aim of this study was to test the hypothesis that the radiosensitivity of repair-proficient cells can be increased by exposing them to medium-borne factors harvested from sensitive cells and vice versa. Cells from a mismatch repair (MMR)-deficient cell line (Raji 10) with a sensitive response to radiation or the wild-type parent cell line were irradiated to 0.5 Gy gamma rays and then monitored for growth rate in their own medium or in the alternative conditioned medium. In other experiments, cells or conditioned medium were added to reporter cells (HPV-G, which are relatively sensitive keratinocytes, or highly radioresistant HT29 cells). The subsequent responses of the two cell lines to a 0.5-Gy dose of (60)Co gamma rays were measured. The results show that prior exposure of resistant cells to medium from irradiated sensitive cells reduced the clonogenic survival of the subsequently irradiated resistant cells. The reverse is also true. Measurement of the apoptosis index and BCL2 expression confirmed that the harvested medium was capable of modulating apoptosis after irradiation. This may have important applications in tumor therapy and also in the understanding of mechanisms involved in induction of adaptive responses.
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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 | 0.001 |
| 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".