Wholemount Immunohistochemistry for Revealing Complex Brain Topography
Bibliographic record
Abstract
The repeated and well-understood cellular architecture of the cerebellum make it an ideal model system for exploring brain topography. Underlying its relatively uniform cytoarchitecture is a complex array of parasagittal domains of gene and protein expression. The molecular compartmentalization of the cerebellum is mirrored by the anatomical and functional organization of afferent fibers. To fully appreciate the complexity of cerebellar organization we previously refined a wholemount staining approach for high throughput analysis of patterning defects in the mouse cerebellum. This protocol describes in detail the reagents, tools, and practical steps that are useful to successfully reveal protein expression patterns in the adult mouse cerebellum by using wholemount immunostaining. The steps highlighted here demonstrate the utility of this method using the expression of zebrinII/aldolaseC as an example of how the fine topography of the brain can be revealed in its native three-dimensional conformation. Also described are adaptations to the protocol that allow for the visualization of protein expression in afferent projections and large cerebella for comparative studies of molecular topography. To illustrate these applications, data from afferent staining of the rat cerebellum are included.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".