Ultrasound Imaging of Apoptosis: Spectroscopic Detection of DNA-Damage Effects at High and Low Frequencies
Bibliographic record
Abstract
A new noninvasive method for the detection of DNA damage using mid-to high-frequency ultrasound (10-60 MHz) has been developed. Ultrasound imaging and quantitative analysis methods are used to detect cell death occurring in response to anticancer therapies in cell samples in vitro, in rat brain tissue ex vivo, and in cancer mouse models in vivo. Experimental evidence indicates that the mechanism behind this ultrasonic detection is linked to changes in the size and acoustic properties of the cell nucleus occurring with forms of cell death, and in particular apoptosis. Nuclear changes associated with cell death can result in up to 16-fold increase in ultrasound backscatter intensity and changes in spectral slope that are consistent with theoretical predictions. Furthermore, color-coded images can be generated based on specific ultrasound parameters in order to identify the regions of cell death in tumor ultrasound images with treatments. These results provide a foundation for future investigations regarding the use of ultrasound in preclinical and clinical settings to noninvasively monitor tumor responses to specific interventions that induce cell death.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".