Single red blood cell oxygenation saturation imaging with multispectral photoacoustic microscopy
Bibliographic record
Abstract
In the last decade, photoacoustic techniques have been used extensively to acquire label free oxygen saturation (SO2) images of blood vessels both in vivo and ex vivo. Recent advances in photoacoustic microscopy have pushed the in vivo resolution limit of photoacoustic SO2mapping to that of a single cell. In this work, we use a photoacoustic microscope equipped with a 0.9 GHz ultrasound transducer and a fiber coupled 532 nm Nd:YAG laser source to generate sub-cellular resolution SO2maps of single red blood cells (RBC) ex vivo. Stimulated Raman scattering (SRS) within the optical fiber produces secondary peaks in the laser output spectrum, which can be isolated as discrete photoacoustic excitation sources by using optical bandpass filters. Photoacoustic images acquired at the different excitation wavelengths are co-registered, and a local SO2map for the RBC is created. Untreated RBCs, as well as RBCs that had been chemically deoxygenated with sodium dithionite were imaged with the system. The resultant SO2maps show a high percentage of SO2through out the untreated cell, as well as localized pockets of both high and low SO2in the treated cell. For the untreated cell, the mean and median SO2values were 72 and 73%, respectively, while for the treated cell they were 56% and 57%. This multispectral PA technique has potential applications in assessing chromophore distribution and oxygen transfer kinetics at the sub-cellular level.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".