Sound speed estimation in single cells using the ultrasound backscatter power spectrum
Bibliographic record
Abstract
The acoustic properties of single cells such as their size, sound speed and attenuation are known to change depending on the type, state or disease progression of a cell. Typically ultrasonic pulse echo methods on adherent cells are used. We propose using the ultrasound backscatter power spectrum on cells in suspension to extract the acoustic parameters. When the ultrasound wavelength is on the same order as the dimensions of the cell, periodically varying minima and maxima occur throughout the power spectrum that depend on the size and sound speed of the object. The ultrasound parameters can be determined by comparing the measured spectrum to a theoretical scattering model. We measured the backscattered ultrasound signals from single MCF7 breast cancer cells in suspension using a 375 MHz transducer. The cell diameter was determined through simultaneous optical imaging. The sound speed was calculated by adjusting the parameters in the scattering model until a good fit of the spectral features between the model and measured agreed. The average sound speed from 16 cells found to vary between 1577 to 1611 m/s when the density was fixed at 1050 kg/m3.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".