Smn deficiency causes neuritogenesis and neurogenesis defects in the retinal neurons of a mouse model of spinal muscular atrophy
Bibliographic record
Abstract
The eye is an excellent model for the study of neuronal development and pathogenesis of central nervous system disorders because of its relative ease of accessibility and the well-characterized cellular makeup. We have used this model to study spinal muscular atrophy (SMA), an autosomal recessive neuromuscular disease caused by deletions or mutations in the survival of motor neuron 1 gene (SMN1). We have investigated the expression pattern of mouse Smn mRNA and protein in the neural retina and the optic nerve of wild type mice. Smn protein is present in retinal ganglion cells and amacrine cells within the neural retina as well as in glial cells in the optic nerve. Histopathological analysis in phenotype stage SMA mice revealed that Smn deficiency is associated with a reduction in ganglion cell axon and glial cell number in the optic nerve, as well as compromised cellular processes and altered organization of neurofilaments in the neural retina. Whole mount preparation and retinal neuron primary culture provided further evidence of abnormal synaptogenesis and neurofilament accumulation in the neurites of Smn-deficient retinal neurons. A subset of amacrine cells is absent, in a cell-autonomous fashion, in the retina of SMA mice. Finally, the retinas of SMA mice have altered electroretinograms. Altogether, our study has demonstrated defects in axodendritic outgrowth and cellular composition in Smn-depleted retinal neurons, indicating a role for Smn in neuritogenesis and neurogenesis, and providing us with an insight into pathogenesis of SMA.
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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) | 0.001 | 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 | 0.001 | 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".