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Record W4365483648 · doi:10.1667/rade-22-00201.1

RENEB Inter-Laboratory Comparison 2021: The Cytokinesis-Block Micronucleus Assay

2023· article· en· W4365483648 on OpenAlexaff
Anne Vral, David Endesfelder, Katalin Balázs, Christina Beinke, C. Cuceu Petrenci, F. Finot, Guy Garty, Rositsa Hristova, Ilonka Ivanova, Y. Lee, K. Lumniczky, Marcela Milanová, Octávia Monteiro Gil, Ursula Oestreicher, Jelena Pajić, Ngoc-Duy Pham, Gianpaolo Perletti, Ki Moon Seong, Sylwester Sommer, T. Szatmári, Antonella Testa, Aleš Tichý, Thi My Hien Tran, Ruth C. Wilkins, Matthias Port, M. Abend, Ans Baeyens

Bibliographic record

VenueRadiation Research · 2023
Typearticle
Languageen
FieldMedicine
TopicRadiation Therapy and Dosimetry
Canadian institutionsHealth Canada
FundersMinistry of Defense
KeywordsBiodosimetryMicronucleus testMicronucleusTriageNuclear medicineDosimetryBinucleated cellsMedicineMedical physicsToxicologyIrradiationBiologyPhysicsInternal medicineToxicityIonizing radiationEmergency medicine

Abstract

fetched live from OpenAlex

The goal of the RENEB inter-laboratory comparison 2021 exercise was to simulate a large-scale radiation accident involving a network of biodosimetry labs. Labs were required to perform their analyses using different biodosimetric assays in triage mode scoring and to rapidly report estimated radiation doses to the organizing institution. This article reports the results obtained with the cytokinesis-block micronucleus assay. Three test samples were exposed to blinded doses of 0, 1.2 and 3.5 Gy X-ray doses (240 kVp, 13 mA, ∼75 keV, 1 Gy/min). These doses belong to 3 triage categories of clinical relevance: a low dose category, for no exposure or exposures inferior to 1 Gy, requiring no direct treatment of subjects; a medium dose category, with doses ranging from 1 to 2 Gy, and a high dose category, after exposure to doses higher than 2 Gy, with the two latter requiring increasing medical attention. After irradiation the test samples (no. 1, no. 2 and no. 3) were sent by the organizing laboratory to 14 centers participating in the micronucleus assay exercise. Laboratories were asked to setup micronucleus cultures and to perform the micronucleus assay in triage mode, scoring 500 binucleated cells manually, or 1,000 binucleated cells in automated/semi-automated mode. One laboratory received no blood samples, but scored pictures from another lab. Based on their calibration curves, laboratories had to provide estimates of the administered doses. The accuracy of the reported dose estimates was further analyzed by the micronucleus assay lead. The micronucleus assay allowed classification of samples in the corresponding clinical triage categories (low, medium, high dose category) in 88% of cases (manual scoring, 88%; semi-automated scoring, 100%; automated scoring, 73%). Agreement between scoring laboratories, assessed by calculating the Fleiss' kappa, was excellent (100%) for semi-automated scoring, good (83%) for manual scoring and poor (53%) for fully automated scoring. Correct classification into triage scoring dose intervals (reference dose ±0.5 Gy for doses ≤2.5 Gy, or reference dose ±1 Gy for doses >2.5 Gy), recommended for triage biodosimetry, was obtained in 79% of cases (manual scoring, 73%; semi-automated scoring, 100%; automated scoring, 67%). The percentage of dose estimates whose 95% confidence intervals included the reference dose was 58% (manual scoring, 48%; semiautomated scoring, 72%; automated scoring, 60%). For the irradiated samples no. 2 and no. 3, a systematic shift towards higher dose estimations was observed. This was also noticed with the other cytogenetic assays in this intercomparison exercise. Accuracy of the rapid triage modality could be maintained when the number of manually scored cells was scaled down to 200 binucleated cells. In conclusion, the micronucleus assay, preferably performed in a semi-automated or manual scoring mode, is a reliable technique to perform rapid biodosimetry analysis in large-scale radiation emergencies.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.179
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.003

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.

Opus teacher head0.071
GPT teacher head0.422
Teacher spread0.350 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations16
Published2023
Admission routes1
Has abstractyes

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