Laboratory Automation for Cytogenetic Biodosimetry and Inter-Laboratory Comparison of the Dicentric Assay
Bibliographic record
Abstract
The dicentric chromosome assay (DCA) is the gold standard biodosimetry method for radiation dose assessment. The DCA can be used for quickly assessing dose to individuals in the early period aftermath of a radiological or nuclear incident for optimum medical aid. DCAs application in radiation mass casualties necessitates greater sample processing and chromosome aberration analysis capacity. Therefore, automated sample processing, chromosome aberration analysis, and establishment of a co-operative network of cytogenetic laboratories are essential. Recent efforts at the Armed Forces Radiobiology Research Institute (AFRRI) focussed on increasing sample processing via automation, technology integration, and implementation of a laboratory information management system (LIMS) for resources and data. We developed a high-throughput, flexible, modular, and scalable robotic blood handling system, which represents a beta version for automated blood handling aiding increased throughput. Other components of the automated cytogenetic biodosimetry laboratory include sample and reagent bar-code tracking, metaphase harvesters and a spreader, slide stainer, a high-throughput metaphase finder, and multiple satellite chromosome-aberration analysis systems all integrated with LIMS. Because use of a cooperative network for chromosome aberration analysis and dose assessment by DCA requires routine quality control exercises among partner laboratories, the National Institute for Allergies and Infectious Diseases (NIAID) and AFRRI sponsored an interlaboratory comparison study to determine DCAs validity and accuracy among five laboratories following the guidelines of International Organization for Standardization.Blood samples irradiated at the AFRRI were shipped to all laboratories, which constructed individual calibration curves in the 0.0- to 5.0-Gy range for 60-Co gamma-rays and assessed the dose to dose-blinded samples. For all laboratories, the estimated coefficients of the fitted curves were within the 99.7% confidence intervals (CIs); but the observed dicentric yields differed. When each laboratory assessed radiation doses to four dose-blinded blood samples by comparing the observed dicentric yield with the laboratorys own calibration curve, the actual doses were within 99.75% CI for the assessed dose. Across the dose range, the error in the estimated doses, compared to the physical doses, was from 15% underestimation to 15% overestimation. Our efforts to improve diagnostic biodosimetry response by the DCA aiding optimum medical treatment for radiation exposed individuals in mass casualties. Acknowledgment: AFRRI and National Institute of Allergy and Infectious Diseases, NIH, Bethesda, MD, supported this research under Inter Agency Agreement, Y1-AI-5045-04.
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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 | 0.022 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.010 |
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".