The study of photoacoustic imaging without nanoparticles as a contrast agent for anti-body drug monitoring
Bibliographic record
Abstract
As an emerging hybrid Imaging, Photoacoustic became a powerful tool that can scan disease at the deeper site in tissue and monitor of drug delivery in vivo. PAI system used nano-particle as contrast agent to enhance the PA signal in deeper site in tissue. So this makes that PAI’s application have some limitation for monitoring of all kinds of anti-body drug, because of various anti-body’s absorption excitation. In this study, we designed a PAI system with a tunable pulse OPO laser (from 450~700nm excitation wavelength) to show the optimal wavelength for monitoring of the antibody drug; doxorubicin having peak absorption at near 500nm excitation without any nano-particle combine. We made a gelatin phantoms having 4 different concentration doxorubicin as an anti-body drug; Doxorubicin concentration were in- 0mg/ml, 0.5mg/ml, 1mg/ml, and 2mg/ml. We found that 500nm is optimization wavelength to produce PA peak signal and PAI can be tool to monitor of anti-body drug without contrast agent.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".