Mesencephalosynapsis and aqueductal stenosis
Bibliographic record
Abstract
Mesencephalosynapsis is characterized by a failure of the dorsal brainstem colliculi to separate into distinct lateral masses (non-cleavage, a.k.a. "fusion"). It is linked to ventriculomegaly and aqueductal stenosis but other associations have not been systematically examined. We reviewed a large cohort of fetal hydrocephalus cases to explore associations of aqueductal stenosis, mesencephalosynapsis, and other pathologies. Among 115 cases of fetal obstructive hydrocephalus (15-41 weeks gestation), mesencephalosynapsis was seen in 44 cases (38.3%). We graded the wide range of abnormal aqueductal histology; mesencephalosynapsis was associated with 67% of severe, 35% of mild, and 10% of borderline aqueductal pathologies. In 75% of cases, it was associated with other CNS anomalies, including rhombencephalosynapsis, holoprosencephaly, hemifacial microsomia, and amniotic rupture sequence. We also identified 2 cases of aqueductal stenosis associated with brainstem tegmental injury, probably ischemic in origin, without mesencephalosynapsis. Clinical and genetic associations of mesencephalosynapsis included diabetic embryopathy, amniotic rupture sequence, chromosomal abnormalities, and mutations in TBCD132, FRAS1, and NECTIN1. This is the largest review of the histology of fetal aqueductal stenosis to date. We conclude that mesencephalosynapsis points to a defect in embryonic brainstem patterning and may be isolated, associated with other malformations, and that it is found in heritable and non-heritable conditions.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".