The role of neurotrophins in the maintenance of the spinal cord motor neurons and the dorsal root ganglia proprioceptive sensory neurons
Bibliographic record
Abstract
The aim of this study was to approach the question of neuronal dependence on neurotrophins during embryonic development in mice in a way other than gene targeting. We employed amyogenic mouse embryos and fetuses that develop without any skeletal myoblasts or skeletal muscle and consequently lose motor and proprioceptive neurons. We hypothesized that if, in spite of the complete inability to maintain motor and proprioceptive neurons, the remaining spinal and dorsal root ganglia tissues of amyogenic fetuses still contain any of the neurotrophins, that particular neurotrophin alone is not sufficient for the maintenance of motor and proprioceptive neurons. Moreover, if the remaining spinal and dorsal root ganglia tissues still contain any of the neurotrophins, that particular neurotrophin alone may be sufficient for the maintenance of the remaining neurons (i.e., mostly non-muscle- and a few muscle-innervating neurons). To test the role of the spinal cord and dorsal root ganglia tissues in the maintenance of its neurons, we performed immunohistochemistry employing double-mutant and control tissues and antibodies against neurotrophins and their receptors. Our data suggested that: (a) during the peak of motor neuron cell death, the spinal cord and dorsal root ganglia distribution of neurotrophins was not altered; (b) the distribution of BDNF, NT-4/5, TrkB and TrkC, and not NT-3, was necessary for the maintenance of the spinal cord motor neurons; (c) the distribution of BDNF, NT-4/5 and TrkC, and not NT-3 and Trk B, was necessary for the maintenance of the DRG proprioceptive neurons; (d) NT-3 was responsible for the maintenance of the remaining neurons and glia in the spinal cord and dorsal root ganglia (possibly via TrkB).
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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 | 0.000 |
| 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) | 0.000 | 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 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".