A Role for Bioelectric Effects in the Induction of Bystander Signals by Ionizing Radiation?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The induction of "bystander effects" i.e. effects in cells which have not received an ionizing radiation track, is now accepted but the mechanisms are not completely clear. Bystander effects following high and low LET radiation exposure are accepted but mechanisms are still not understood. There is some evidence for a physical component to the signal. This paper tests the hypothesis that bioelectric or biomagnetic phenomena are involved. Human immortalized skin keratinocytes and primary explants of mouse bladder and fish skin, were exposed directly to ionizing radiation or treated in a variety of bystander protocols. Exposure of cells was conducted by shielding one group of flasks using lead, to reduce the dose below the threshold of 2mGy (60)Cobalt gamma rays established for the bystander effect. The endpoint for the bystander effect in the reporter system used was reduction in cloning efficiency (RCE). The magnitude of the RCE was similar in shielded and unshielded flasks. When cells were placed in a Faraday cage the magnitude of the RCE was less but not eliminated. The results suggest that liquid media or cell-cell contact transmission of bystander factors may be only part of the bystander mechanism. Bioelectric or bio magnetic fields may have a role to play. To test this further, cells were placed in a Magnetic Resonance Imaging (MRI) machine for 10 min using a typical head scan protocol. This treatment also induced a bystander response. Apart from the obvious clinical relevance, the MRI results further suggest that bystander effects may be produced by non-ionizing exposures. It is concluded that bioelectric or magnetic effects may be involved in producing bystander signaling cascades commonly seen following ionizing radiation exposure.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it