A Microfluidic Cytometer for Quantitative Evaluation of Radiation Dose by γ-H2AX
Bibliographic record
Abstract
Evaluation of radiation dose is very important for the detection of radiation damage. γ-H2AX is a popular biological dosimeter to evaluate the radiation effect. Typically, bulky and expensive commercial flow cytometers are used to detect γ-H2AX. This paper presents a miniaturized and highly sensitive cytometer using a microfluidic chip for evaluating the radiation dose by detecting the mean immunofluorescence intensity of γ-H2AX. A compact optical focusing system and a shift-phase differential amplifier are designed to improve the detection sensitivity. Sample lymphocyte cells are stained by FITC fluorescent dye after being irradiated by UVC. Comparison experiments between the developed miniature cytometer and a commercial flow cytometer were conducted under different radiation doses. The developed microfluidic cytometer can also demonstrate a good linear correlation between the measured fluorescence intensity and the irradiation dose with a detection limit similar to that of the commercial flow cytometer. The developed cytometer can evaluate quantitatively the radiation dose by the mean fluorescence intensity of γ-H2AX with a significantly smaller amount of blood samples than a commercial flow cytometer.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".