Properties of cells through life and death – an acoustic microscopy investigation
Bibliographic record
Abstract
Current methods to evaluate the status of a cell are largely focused on fluorescent identification of molecular biomarkers. The invasive nature of these methods - requiring either fixation, chemical dyes, genetic alteration, or a combination of these - prevents subsequent analysis of samples. In light of this limitation, studies have considered the use of physical markers to differentiate cell stages. Acoustic microscopy is an ultrahigh frequency (>100 MHz) ultrasound technology that can be used to calculate the mechanical and physical properties of biological cells in real-time, thereby evaluating cell stage in live cells without invasive biomarker evaluation. Using acoustic microscopy, MCF-7 human breast adenocarcinoma cells within the G1, G2, and metaphase phases of the proliferative cell cycle, in addition to early and late programmed cell death, were examined. Physical properties calculated include the cell height, sound speed, acoustic impedance, cell density, adiabatic bulk modulus, and the ultrasonic attenuation. A total of 290 cells were measured, 58 from each cell phase, assessed using fluorescent and phase contrast microscopy. Cells actively progressing from G1 to metaphase were marked by a 28% decrease in attenuation, in contrast to the induction of apoptosis from G1, which was marked by a significant 81% increase in attenuation. Furthermore late apoptotic cells separated into 2 distinct groups based on ultrasound attenuation, suggesting that presently-unidentified sub-stages may exist within late apoptosis. A methodology has been implemented for the identification of cell stages without the use of chemical dyes, fixation, or genetic manipulation.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".