Sequence of Synaptogenesis in the Fetal and Neonatal Cerebellar System - Part 1: Guillain-Mollaret Triangle (Dentato-Rubro-Olivo-Cerebellar Circuit)
Bibliographic record
Abstract
Precise temporal and spatial sequences of synaptogenesis occur in the cerebellar system, as in other synaptic circuits of the brain. In postmortem brain sections of 172 human fetuses and neonates, synaptophysin immunoreactivity was studied in nuclei of the Guillain-Mollaret triangle: dentato-olivo-rubro-cerebellar circuit. Synaptophysin demonstrates not only progressive increase in synaptic vesicles in each structure, but also shows the development of shape from amorphous globular neuronal aggregates to undulated nuclei. Intensity of synaptophysin reactivity is strong before the mature shape of these nuclei is achieved. Accessory olivary and deep cerebellar nuclei are intensely stained earlier than the principal olivary and dentate nuclei. The dorsal blades of both form earlier than the ventral, with reactivity initially peripheral. Initiation of synaptophysin reactivity is at 13 weeks in the inferior olive (r6, r7) and at 16 weeks in the dentate (r2). Initial synaptic vesicles are noted at 13 weeks in the red nucleus (r0); synapses form initially on the small neurons at 13 weeks but thereafter simultaneously on small and large neurons. Form and reactivity follow caudorostral, dorsoventral and mediolateral gradients in the axes of the rhombencephalon. This study provides control data to serve as a basis for interpreting aberrations in synaptogenesis in malformations of the cerebellar system, genetic disorders and acquired insults to the cerebellum and brainstem during fetal life, applicable to tissue sections and complementing biochemical and molecular techniques.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".