The Role of Gap Junction Communication and Oxidative Stress in the Propagation of Toxic Effects among High-Dose α-Particle-Irradiated Human Cells
Bibliographic record
Abstract
We investigated the roles of gap junction communication and oxidative stress in modulating potentially lethal damage repair in human fibroblast cultures exposed to doses of α particles or γ rays that targeted all cells in the cultures. As expected, α particles were more effective than γ rays at inducing cell killing; further, holding γ-irradiated cells in the confluent state for several hours after irradiation promoted increased survival and decreased chromosomal damage. However, maintaining α-particle-irradiated cells in the confluent state for various times prior to subculture resulted in increased rather than decreased lethality and was associated with persistent DNA damage and increased protein oxidation and lipid peroxidation. Inhibiting gap junction communication with 18-α-glycyrrhetinic acid or by knockdown of connexin43, a constitutive protein of junctional channels in these cells, protected against the toxic effects in α-particle-irradiated cell cultures during confluent holding. Upregulation of antioxidant defense by ectopic overexpression of glutathione peroxidase protected against cell killing by α particles when cells were analyzed shortly after exposure. However, it did not attenuate the decrease in survival during confluent holding. Together, these findings indicate that the damaging effect of α particles results in oxidative stress, and the toxic effects in the hours after irradiation are amplified by intercellular communication, but the communicated molecule(s) is unlikely to be a substrate of glutathione peroxidase.
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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".