Multimodal 3D photoacoustic remote sensing and confocal fluorescence microscopy imaging
Bibliographic record
Abstract
SIGNIFICANCE: Complementary absorption and fluorescence contrast could prove useful for a wide range of biomedical applications. However, current absorption-based photoacoustic microscopy systems require the ultrasound transducers to physically touch the samples, thereby increasing contamination and limiting strong optical focusing in reflection mode. AIM: We sought to develop an all-optical system for imaging cells and tissues using the three combined imaging modalities: photoacoustic remote sensing (PARS), epifluorescence, and confocal laser scanning microscopy (CLSM). APPROACH: A PARS subsystem with ultraviolet excitation was used to obtain label-free absorption-contrast images of nucleic acids in ex vivo tissue samples. Co-integrated epifluorescence and CLSM subsystems were used to verify the 2D and 3D nuclei distribution. RESULTS: Complementary absorption and fluorescence contrast were demonstrated in phantom imaging experiments and subsequent cell and tissue imaging experiments. Lateral and axial resolution of ultraviolet-PARS (UV-PARS) is shown to be 0.39 and 1.6 μm, respectively, with 266-nm light. CLSM lateral and axial resolution was measured as 0.97 and 2.0 μm, respectively. This resolution is sufficient to image individual cell layers with fine optical sectioning. UV-PARS images of cell nuclei are validated in thick tissue using CLSM. CONCLUSIONS: Multimodal absorption and fluorescence contrast are obtained with a non-contact all-optical microscopy system for the first time and utilized to obtain images of cells and tissues with subcellular resolution.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 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".