Low dose ionizing radiation and the immune response: what is the role of non-targeted effects?
Bibliographic record
Abstract
OBJECTIVES: This review aims to trace the historical narrative surrounding the low dose effects of radiation on the immune system and how our understanding has changed from the beginning of the 20th century to now. The particular focus is on the non-targeted effects (NTEs) of low dose ionizing radiation (LDIR) which are effects that occur when irradiated cells emit signals that cause effects in the nearby or distant non-irradiated cells known as radiation induced bystander effect (RIBE). Moreover, radiation induced genomic instability (RIGI) and abscopal effect (AE) also regarded as NTE. This was prompted by our recent discovery that ultraviolet A (UVA) photons are emitted by the irradiated cells and that these photons can trigger NTE such as the RIBE in unirradiated recipients of these photons. Given the well-known association between UV radiation and the immune response, where these biophotons may pose as bystander signals potentiating processes in deep tissues as a consequence of LDIR, it is timely to review the field with a fresh lens. Various pathways and immune components that contribute to the beneficial and adverse types of modulation induced by LDR will also be revisited. CONCLUSION: There is limited evidence for LDIR induced immune effects by way of a non-targeted mechanism in biological tissue. The literature examining low to medium dose effects of ionizing radiation on the immune system and its components is complex and controversial. Early work was compromised by lack of good dosimetry while later work mainly looks at the involvement of immune response in radiotherapy. There is a lack of research in the LDIR/NTE field focusing on immune response although bone marrow stem cells and lineages were critical in the identification and characterization of NTE where effects like RIGI and RIBE were heavily researched. This may be in part, a result of the difficulty of isolating NTE in whole organisms which are essential for good immune response studies. Models involving inter organism transmission of NTE are a promising route to overcome these issues.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".