Expression of calcium‐binding proteins and nNOS in the human vestibular and precerebellar brainstem
Bibliographic record
Abstract
Information about the position and movement of the head in space is coded by vestibular receptors and relayed to four nuclei that comprise the vestibular nuclear complex (VNC). Many additional brainstem nuclei are involved in the processing of vestibular information, receiving signals either directly from the eighth nerve or indirectly via projections from the VNC. In cats, squirrel monkeys, and macaque monkeys, we found neurochemically defined subdivisions within the medial vestibular nucleus (MVe) and within the functionally related nucleus prepositus hypoglossi (PrH). In humans, different studies disagree about the borders, sizes, and possible subdivisions of the vestibular brainstem. In an attempt to clarify this organization, we have begun an analysis of the neurochemical characteristics of the human using brains from the Witelson Normal Brain Collection and standard techniques for antigen retrieval and immunohistochemistry. Using antibodies to calbindin, calretinin, parvalbumin, and nitric oxide synthase, we find neurochemically defined subdivisions within the MVe similar to the subdivisions described in cats and monkeys. The neurochemical organization of PrH is different. We also find unique neurochemical profiles for several structures that suggest reclassification of nuclei. These data suggest both quantitative and qualitative differences among cats, monkeys, and humans in the organization of the vestibular brainstem. These results have important implications for the analysis of changes in that organization subsequent to aging, disease, or loss of input.
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) | 0.000 | 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) | 0.002 | 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 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".