Biological Effects and Adaptive Response from Single and Repeated Computed Tomography Scans in Reticulocytes and Bone Marrow of C57BL/6 Mice
Bibliographic record
Abstract
This study investigated the biological effects and adaptive responses induced by single and repeated in vivo computed tomography (CT) scans. We postulated that, through the induction of low-level oxidative stress, repeated low-dose CT scans (20 mGy, 2 days/week, 10 weeks) could protect mice (C57BL/6) from acute effects of high-dose radiation (1 Gy, 2 Gy). The micronucleated reticulocyte (MN-RET) count increased linearly after exposure to single CT scans of doses ranging from 20 to 80 mGy (P = 0.033). Ten weeks of repeated CT scans (total dose 400 mGy) produced a slight reduction in spontaneous MN-RET levels relative to levels in sham CT-scanned mice (P = 0.04). Decreases of nearly 10% in γ-H2AX fluorescence levels were observed in the repeated CT-scanned mice after an in vitro challenge dose of 1 Gy (P = 0.017) and 2 Gy (P = 0.026). Spontaneous apoptosis levels (caspase 3 and 7 activation) were also significantly lower in the repeated CT-scanned mice than the sham CT-scanned mice (P < 0.01). In contrast, mice receiving only a single CT scan showed a 19% elevation in apoptosis (P < 0.02) and a 10% increase in γ-H2AX fluorescence levels after a 2-Gy challenge (P < 0.05) relative to sham CT controls. Overall, repeated CT scans seemed to confer resistance to larger doses in mice, whereas mice exposed to single CT scans exhibited transient genotoxicity, enhanced apoptosis, and characteristics of radiation sensitization.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".