Acoustic and photoacoustic imaging of spheroids
Bibliographic record
Abstract
Acoustic and photoacoustic high frequency imaging (50-100 MHz) can be used to generate images of cell constructs and spheroids with good spatial resolution and contrast. Here we demonstrate how co-registered acoustic and photoacoustic imaging can be used for imaging spheroids. Spheroids are widely used in cancer research and biology since they emulate a 3-dimensional environment such as that experienced in tumors. Spheroids were made by the hanging-drop method using the MCF-7 cancer cell line. To generate photoacoustic contrast, MCF-7 cells were incubated with optical absorbing nanoparticles (e.g. gold nanorods, 780nm absorption) for 24 hours and mixed with native MCF-7 cells prior to spheroid formation. The spheroids were between 0.5 mm and 1mm in diameter. Imaging was performed with the VisualSonics VEVO 770 (25-55 MHz) and a high-resolution SASAM acoustic/photoacoustic microscope for frequencies over 80 MHz (Kibero GmbH, Germany). The spheroid was imaged first using pulse echo ultrasound, then with photoacoustics immediately after. The necrotic core of the spheroid had a 20dB increase in ultrasound backscatter compared the viable cells surrounding the core, and the ultrasound/photoacoustic images of the spheroid were co-registered showing the distribution of the optical absorbing agents.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".