A Flexible Semi-automated Assay for Assessing Radiation-sensitization and Toxicity in the Mouse Intestine
Bibliographic record
Abstract
BACKGROUND/AIM: The aim of this study was to develop an enhanced intestinal toxicity assay with three outputs assessing proliferation, villi morphology and DNA damage after irradiation. MATERIALS AND METHODS: Whole 5 cm jejunal lengths were collected from mice following total body x-ray irradiation (0-15 Gy) at 0-84 h. Tissues were wrapped into swirls for cryopreservation and immunohistochemically stained for EdU, CD31, and γH2AX. A semi-automated image analysis was developed for the proliferation, villi morphology, and DNA damage models. RESULTS: Proliferation assessed via EdU staining varied with cycles of damage repair, hyperproliferation, and homeostasis after radiation, with the time to onset of each cycle variable based on radiation dose. An analysis model evaluating the amount of proliferation per unit length of jejunum analyzed was developed, with a dose-response curve identified at 48 h post treatment. The villi length model measured the length of intact and healthy CD31-stained capillary beds between the crypts and villi tips at 3.5 days post treatment within a 0-10 Gy dose range. The DNA damage model evaluated the intensity of γH2AX staining within cellular nuclei, with a useful dose-response identified at 1 h post-radiation treatment. CONCLUSION: This assay demonstrates flexibility for assessing radiation-induced damage, with analysis of proliferation, villi length, or direct DNA damage achievable at defined time points and within useful radiation dose curves. The software-assisted image analysis allows for rapid, comprehensive, and objective data generation with an assay turnover time of days instead of weeks on samples that are representative of most of the treated jejunum.
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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 | 0.002 | 0.001 |
| 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) | 0.002 | 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".