A laboratory inter-comparison of the importance of serum serotonin levels in the measurement of a range of radiation-induced bystander effects: Overview of study and results presentation
Bibliographic record
Abstract
PURPOSE: Recent research has suggested that serotonin may play an important role in the expression of radiation-induced bystander effects. Serotonin levels in serum were reported to range from 6-22 μM and to correlate inversely with the magnitude of cellular colony-forming ability in medium transfer bystander assays. That is, high serotonin concentration correlated with a low cloning efficiency in cultures receiving medium derived from irradiated cells. METHODS: Because of the potential importance of this observation, the European Union's Non-targeted Effects Integrated Project (NOTE) performed an inter-comparison exercise where serum samples with high and low serotonin levels were distributed to seven laboratories which then performed their own assay to determine the magnitude of the bystander effect. RESULTS: The results provided some support for a role for serotonin in four of the laboratories. Two saw no difference between the samples and one gave inconclusive results. In this summary paper, full data sets are presented from laboratories whose data was inconclusive or insufficient for a full paper. Other data are published in full in the special issue. CONCLUSION: The data suggest that there may be multiple bystander effects and that the underlying mechanisms may be modulated by both the culture conditions and the intrinsic properties of the cells used in the assay.
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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 | 0.015 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".