High-frequency ultrasound scattering from microspheres and single cells
Bibliographic record
Abstract
Assessing the proportion of biological cells in a volume of interest undergoing structural changes, such as cell death, using high-frequency ultrasound (20-100 MHz), requires the development of a theoretical model of scattering by any arbitrary cell ensemble. A prerequisite to building such a model is to know the scattering by a single cell in different states. In this paper, a simple model for the high-frequency acoustic scattering by one cell is proposed. A method for deducing the backscatter transfer function from a single, subresolution scatterer is also devised. Using this method, experimental measurements of backscatter from homogeneous, subresolution polystyrene microspheres and single, viable eukaryotic cells, acquired across a broad, continuous range of frequencies were compared with elastic scattering theory and the proposed cell scattering model, respectively. The resonant features observed in the backscatter transfer function of microspheres were found to correspond accurately to theoretical predictions. Using the spacing of the major spectral peaks in the transfer functions obtained experimentally, it is possible to predict microsphere diameters with less than 4% error. Such good agreement was not seen between the cell model and the measured backscatter from cells. Possible reasons for this discrepancy are discussed.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".