A new wide field-of-view confocal imaging system and its applications in drug discovery and pathology
Bibliographic record
Abstract
Conventional widefield light microscopy and confocal scanning microscopy have been indispensable for pathology and drug discovery research. Clinical specimens from diseased tissues are examined, new drug candidates are tested on drug targets, and the morphological and molecular biological changes of cells and tissues are observed. High throughput screening of drug candidates requires highly efficient screening instruments. A standard biomedical slide is 1 by 3 inches (25.4 by 76.2 mm) in size. A typical tissue specimen is 10 mm in diameter. To form a high resolution image of the entire specimen, a conventional widefield light microscope must acquire a large number of small images of the specimen, and then tile them together, which is tedious, inefficient and error-prone. A patented new wide field-of-view confocal scanning laser imaging system has been developed for tissue imaging, which is capable of imaging an entire microscope slide without tiling. It is capable of operating in brightfield, reflection and epi-fluorescence imaging modes. Three (red, green and blue (RGB)) lasers are used to produce brightfield and reflection images, and to excite various fluorophores. This new confocal system makes examination of large biomedical specimens more efficient, and makes fluorescence examination of large specimens possible for the first time without tiling. Description of the new confocal technology and applications of the imaging system in pathology and drug discovery research, for example, imaging large tissue specimens, tissue microarrays, and zebrafish sections, are reported in this paper.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".