Long-term Time Lapse Imaging of Mouse Cochlear Explants
Bibliographic record
Abstract
Here we present a method for long-term time-lapse imaging of live embryonic mouse cochlear explants. The developmental program responsible for building the highly ordered, complex structure of the mammalian cochlea proceeds for around ten days. In order to study changes in gene expression over this period and their response to pharmaceutical or genetic manipulation, long-term imaging is necessary. Previously, live imaging has typically been limited by the viability of explanted tissue in a humidified chamber atop a standard microscope. Difficulty in maintaining optimal conditions for culture growth with regard to humidity and temperature has placed limits on the length of imaging experiments. A microscope integrated into a modified tissue culture incubator provides an excellent environment for long term-live imaging. In this method we demonstrate how to establish embryonic mouse cochlear explants and how to use an incubator microscope to conduct time lapse imaging using both bright field and fluorescent microscopy to examine the behavior of a typical embryonic day (E) 13 cochlear explant and Sox2, a marker of the prosensory cells of the cochlea, over 5 days.
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 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) | 0.001 | 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 | 0.001 | 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".