The Smn-Independent Beneficial Effects of Trichostatin A on an Intermediate Mouse Model of Spinal Muscular Atrophy
Bibliographic record
Abstract
Spinal muscular atrophy is an autosomal recessive neuromuscular disease characterized by the progressive loss of alpha motor neurons in the spinal cord. Trichostatin A (TSA) is a histone deacetylase inhibitor with beneficial effects in spinal muscular atrophy mouse models that carry the human SMN2 transgene. It is currently unclear whether TSA specifically targets the SMN2 gene or whether other genes respond to TSA and in turn provide neuroprotection in SMA mice. We have taken advantage of the Smn2B/- mouse model that does not harbor the human SMN2 transgene, to test the hypothesis that TSA has its beneficial effects through a non-SMN mediated pathway. TSA increased the median lifespan of Smn2B/- mice from twenty days to eight weeks. As well, there was a significant attenuation of weight loss and improved motor behavior. Pen test and righting reflex both showed significant improvement, and motor neurons in the spinal cord of Smn2B/- mice were protected from degeneration. Both the size and maturity of neuromuscular junctions were significantly improved in TSA treated Smn2B/- mice. Of interest, TSA treatment did not increase the levels of Smn protein in mouse embryonic fibroblasts or myoblasts obtained from the Smn2B/- mice. In addition, no change in the level of Smn transcripts or protein in the brain or spinal cord of TSA-treated SMA model mice was observed. Furthermore, TSA did not increase Smn protein levels in the hind limb muscle, heart, or liver of Smn2B/- mice. We therefore conclude that TSA likely exerts its effects independent of the endogenous mouse Smn gene. As such, identification of the pathways regulated by TSA in the Smn2B/- mice could lead to the development of novel therapeutics for treating 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) | 0.001 | 0.001 |
| 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 | 0.000 |
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".