Neuromuscular Development in the Absence of Programmed Cell Death: Phenotypic Alteration of Motoneurons and Muscle
Bibliographic record
Abstract
The widespread, massive loss of developing neurons in the central and peripheral nervous system of birds and mammals is generally considered to be an evolutionary adaptation. However, until recently, models for testing both the immediate and long-term consequences of preventing this normal cell loss have not been available. We have taken advantage of several methods for preventing neuronal death in vivo to ask whether rescued neurons [e.g., motoneurons (MNs)] differentiate normally and become functionally incorporated into the nervous system. Although many aspects of MN differentiation occurred normally after the prevention of cell death (including the expression of several motoneuron-specific markers, axon projections into the ventral root and peripheral nerves, ultrastructure, dendritic arborization, and afferent axosomatic synapses), other features of the neuromuscular system (MNs and muscle) were abnormal. The cell bodies and axons of MNs were smaller than normal, many MN axons failed to become myelinated or to form functional synaptic contacts with target muscles, and a subpopulation of rescued cells were transformed from alpha- to gamma-like MNs. Additionally, after the rescue of MNs in myogenin glial cell line-derived neurotrophic factor (MyoGDNF) transgenic mice, myofiber differentiation of extrafusal skeletal muscle was transformed and muscle physiology and motor behaviors were abnormal. In contrast, extrafusal myofiber phenotype, muscle physiology, and (except for muscle strength tests) motor behaviors were all normal after the rescue of MNs by genetic deletion of the proapoptotic gene Bax. However, there was an increase in intrafusal muscle fibers (spindles) in Bax knock-out versus both wild-type and MyoGDNF mice. Together, these data indicate that after the prevention of MN death, the neuromuscular system becomes transformed in novel ways to compensate for the presence of the thousands of excess cells.
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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) | 0.001 | 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".