Whole-mount Immunohistochemistry: A High-throughput Screen for Patterning Defects in the Mouse Cerebellum
Bibliographic record
Abstract
Large-scale mouse mutagenesis experiments now under way require appropriate screening methods. An important class of potential mutants comprises those with defects in the development of normal cerebellar patterning. Cerebellar defects are likely to be identified often because they typically result in ataxia. Immunohistochemistry (IHC) is commonly used to reveal cerebellar organization. In particular, the antigen zebrin II (=aldolase C), expressed by stripes of Purkinje cells, has been valuable in revealing cerebellar pattern abnormalities. The development of whole-mount procedures in Drosophila, chick, and Xenopus embryos allows complex patterns to be studied in situ while preserving the integrity of the structure. By combining procedures originally designed for embryonic and early postnatal tissue analyses, we have developed a whole-mount IHC protocol using anti-zebrin II, which reveals the complex topography of Purkinje cells in the adult mouse cerebellum. Furthermore, the procedure is effective with a number of other antigens and works well on both perfusion-fixed and immersion-fixed tissue. By use of this approach, normal adult murine cerebellar topography and patterning defects caused by mutation can be studied without the need for three-dimensional reconstruction.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 | 0.000 |
| 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".