A high-resolution MACROscope with differential phase contrast, transmitted light, confocal fluorescence, and hyperspectral capabilities for large-area tissue imaging
Bibliographic record
Abstract
Recent advances in imaging technology have contributed greatly to biological science. Confocal fluorescence microscopes can acquire two-dimensional and three-dimensional images of biological samples such as live or fixed cells and tissues. Specimens that are large (e.g., a 10 mm/spl times/10 mm tissue section) and overfill the field of view (FOV) of typical microscope objectives require the use of image tiling to cover the entire specimen. This can be time consuming and cause artifacts in the composite image. The MACROscope system (Biomedical Photometrics Inc., Waterloo, ON, Canada) is a confocal device with a 22 mm/spl times/70 mm FOV designed for imaging large tissue sections in a single frame. The prototype demonstrated here can obtain images in reflected, transmitted, fluorescence, phase contrast, and hyperspectral modes. The new spectral imaging mode is characterized with a series of test targets, and sampled spectra are compared to a commercial spectrometer. Fluorescence images of human SiHa tumor xenografts stained with CD31-Cy3, showing blood vessel location, and EF5-Cy5, showing areas of tissue hypoxia, were collected. Differential phase contrast images of the same section, as well as human epithelial cells, were recorded to assess the phase contrast mode. Additionally, fluorescence images of Cytokeratin-Cy3 stained squamous cell carcinoma tissue sections were captured. Finally, red, green, blue transmitted light images of human tongue were obtained. This new device avoids the need for image tiling and provides simultaneous imaging of multiple fluorescently labeled tissue-specific markers in large biological samples. This enables time- and cost-efficient imaging of (immuno)histopathological samples. This device may also serve in the imaging of high-throughput DNA and tissue arrays.
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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 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".