Creation of Myelomeningocele in the Fetal Rabbit
Bibliographic record
Abstract
OBJECTIVE: Myelomeningocele is a neural tube defect resulting in an exposed spinal cord, which leads to irreversible neurologic damage at birth. We proposed development of a fetal rabbit model of myelomeningocele to study in utero spinal cord injury and repair strategies. METHODS: New Zealand white rabbits (n = 10) at 22 days of gestation (term = 31 days) underwent laparotomy to expose the gravid uterus; a hysterotomy exposed the fetal hindlimbs and back. A three to four level lumbar laminectomy was performed, and the dura over the posterior spinal cord was removed. At 30 days of gestation, the does underwent C-section for fetal harvest, and total fetal number, length, weight, and the presence or absence of a spinal defect were recorded for all viable fetuses. RESULTS: All injured fetuses were smaller and weighed less than the nonoperated littermate controls, and histologic examination confirmed a spina bifida-like lesion of their spinal cords. CONCLUSIONS: We successfully created an exposed spinal cord defect in the fetal rabbit model similar to the lesion found in humans. Advantageous because of low animal cost, relatively large fetal size, multiple fetuses per pregnancy, and short total gestation, this model will allow us to study the mechanism of injury to the exposed spinal cord, and perhaps develop strategies to repair human myelomeningoceles.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".