Intercellular Communication Amplifies Stressful Effects in High-Charge, High-Energy (HZE) Particle-Irradiated Human Cells
Bibliographic record
Abstract
Understanding the mechanisms that underlay the biological effects of particulate radiations is essential for space exploration and for radiotherapy. Here, we investigated the role of gap junction intercellular communication (GJIC) in modulating harmful effects induced in confluent cultures wherein most cells are traversed by one or more radiation tracks. We focused on the effect of radiation quality (linear energy transfer; LET) on junctional propagation of DNA damage and cell death among the irradiated cells. Confluent normal human fibroblasts were exposed to graded doses of 1 GeV protons (LET ~0.2 keV/μm) or 1 GeV/u iron ions (LET ~151 keV/μm) and were assayed for clonogenic survival and for micronucleus formation, a reflection of DNA damage, shortly after irradiation and following longer incubation periods. Iron ions were ~2.7 fold more effective than protons at killing 90% of the cells in the exposed cultures when assayed within 5–10 minutes after irradiation. When cells were held in the confluent state for several hours after irradiation, substantial potentially lethal damage repair (PLDR), coupled with a reduction in micronucleus formation, occurred in cells exposed to protons, but not in those exposed to iron ions. In fact, such confluent holding after exposure to a similarly toxic dose of iron ions enhanced the induced toxic effect. However, following iron ion irradiation, inhibition of GJIC by 18-α-glycyrrhetinic acid eliminated the enhanced toxicity and reduced micronucleus formation to levels below those detected in cells assayed shortly after irradiation. The data show that low-LET radiation induces strong PLDR within hours, but that high-LET radiation with similar immediate toxicity does not induce PLDR and its toxicity increases with time following irradiation. The results also show that GJIC among irradiated cells amplifies stressful effects following exposure to high-, but not low-LET radiation, and that GJIC has only minimal effect on cellular recovery following low-LET irradiation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".