Live imaging and analysis of postnatal mouse retinal development
Bibliographic record
Abstract
BACKGROUND: The explanted, developing rodent retina provides an efficient and accessible preparation for use in gene transfer and pharmacological experimentation. Many of the features of normal development are retained in the explanted retina, including retinal progenitor cell proliferation, heterochronic cell production, interkinetic nuclear migration, and connectivity. To date, live imaging in the developing retina has been reported in non-mammalian and mammalian whole-mount samples. An integrated approach to rodent retinal culture/transfection, live imaging, cell tracking, and analysis in structurally intact explants greatly improves our ability to assess the kinetics of cell production. RESULTS: In this report, we describe the assembly and maintenance of an in vitro, CO2-independent, live mouse retinal preparation that is accessible by both upright and inverted, 2-photon or confocal microscopes. The optics of this preparation permit high-quality and multi-channel imaging of retinal cells expressing fluorescent reporters for up to 48h. Tracking of interkinetic nuclear migration within individual cells, and changes in retinal progenitor cell morphology are described. Follow-up, hierarchical cluster screening revealed that several different dependent variable measures can be used to identify and group movement kinetics in experimental and control samples. CONCLUSIONS: Collectively, these methods provide a robust approach to assay multiple features of rodent retinal development using live imaging.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 |
| 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".