Frequency-domain photothermoacoustic and ultrasonic imaging of blood and opto-thermal effects of plasmonic nanoparticle concentrations
Bibliographic record
Abstract
We describe the use of combined ultrasonic imaging (USI) and photoacoustic radar imaging (PARI) with linear chirp laser modulation to provide visualization of blood with and without the use of gold nanoparticles. A blood vessel simulating sample (S1) containing pure sheep blood was shown to be an optically weak absorbing medium which satisfies thermal but not acoustic confinement. On the contrary, the blood-gold combinations (S2) using 10% and S3 (20%) Au concentrations behaved as optically strongly absorbing media. A heating efficiency of 0.54 to 8.60×10(3) K cm(2) (-1) was determined for Au NPs. The optimal optical power modulation spectral density was determined to be in the range of 0.5 to 0.8 MHz and 0.3 to 1.0 MHz for USI and PARI, respectively. USI produced a better structural image while PARI produced a better functional image of the simulated blood vessel in the order of S2>S3>S1 due to enhanced signal-to-noise ratio. Two-dimensional images of the simulated blood vessel were also obtained. In summary, the PA signal does not increase linearly with Au NP concentration and the change of blood osmolarity due to temperature increase can cause thermo-hemolysis of red blood cells which in turn degrades the PA signal and thus the blood imaging quality. On the other hand, USI produced the best structural image, S4, due to the strong US reflection response from Au NPs and its insensitivity to the presence of blood.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 teacher head, 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".