Quantitative measurements of apoptotic cell properties using acoustic microscopy
Bibliographic record
Abstract
Time-resolved acoustic microscopy was used to measure properties of cells such as the thickness, sound velocity, acoustic impedance, density, bulk modulus, and attenuation, before and after apoptosis. A total of 12 cells were measured, 5 apoptotic and 7 non-apoptotic. Measurements made at 375 MHz showed a statistically significant increase in the cell thickness from 13.6 ± 3.1 μm to 17.3 ± 1.6 μm, and in the attenuation from 1.08 ± 0.21 dB/cm/MHz to 1.74 ± 0.36 dB/cm/MHz. The other parameters, such as the sound velocity, density, acoustic impedance, and bulk modulus remained similar within experimental error. Acoustic images obtained at 1.0 GHz showed increased RF-signal backscatter and a clear delineation of the nucleus and cytoplasm from apoptotic cells compared with non-apoptotic cells. Extensive activity was observed optically and acoustically within apoptotic cells. Acoustic measurements made one minute apart showed variations in the ultrasonic backscatter but not attenuation in the cells, which indicated rapid structural changes were occurring but not changes in bulk composition. The normalized crosscorrelation coefficient was used to quantify the variations in the backscatter RF-signal during apoptosis by comparing the first RF signal measured to each successive RF signal every 10 s. A coefficient of 1 indicates strong correlation, whereas a coefficient of 0 indicates no correlation. An average correlation coefficient of 0.93 ± 0.05 was measured for non-apoptotic cells, compared with 0.68 ± 0.17 for apoptotic cells, indicating that the RF signal as a function of time varied rapidly during apoptosis.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".