Bio-acoustic signaling; exploring the potential of sound as a mediator of low-dose radiation and stress responses in the environment
Bibliographic record
Abstract
OBJECTIVES: This commentary reviews and evaluates the role of sound signals as part of the infosome of cells and organisms. Emission and receipt of sound has recently been identified as a potentially important universal signaling mechanism invoked when organisms are stressed. Recent evidence from plants, animals and microbes suggests that it could be a stimulus for specific or general molecular cellular stress responses in different contexts, and for triggering population level responses. This paper reviews the current status of the field with particular reference to the potential role of sound signaling as an immediate/early bystander effector (RIBE) during radiation-induced stress. CONCLUSIONS: While the chemical effectors involved in intercellular and inter-organismal signaling have been the subject of intense study in the field of Chemical Ecology, less appears to be known about physical signals in general and sound signals in particular. From this review we conclude that these signals are ubiquitous in each kingdom and behave very like physical bystander signals leading to regulation of metabolic pathways and gene expression patterns involved in adaptation, synchronization of population responses, and repair or defence against damage. We propose the hypothesis that acoustic energy released on interaction of biota with electromagnetic radiation may represent a signal released by irradiated cells leading to, or complementing, or interacting with, other responses, such as endosome release, responsible for signal relay within the unirradiated individuals in the targeted population.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".