Effect of genetic background on the phenotype of the<i>Smn<sup>2B/-</sup></i>mouse model of spinal muscular atrophy
Bibliographic record
Abstract
Spinal muscular atrophy (SMA) is caused by mutations or deletions in the Survival Motor Neuron 1 (SMN1) gene in humans. Modifiers of the SMA symptoms have been identified and genetic background has a substantial effect in the phenotype and survival of the severe mouse model of SMA. Previously, we generated the less severe Smn2B/- mice on a mixed genetic background. To assess the phenotype of Smn deficiency on a pure genetic background, we produced Smn2B/2B congenic mice on either the C57BL/6 (BL6) or FVB strain background and characterized them at the 6th generation by breeding to Smn+/- mice. Smn2B/- mice from these crosses were evaluated for growth, survival, muscle atrophy, motor neuron loss, motor behaviour, and neuromuscular junction pathology. FVB Smn2B/- mice had a shorter life span than BL6 Smn2B/- mice (median of 19 days vs. 25 days). Similarly, all other defects assessed occurred at earlier stages in FVB Smn2B/-mice when compared to BL6 Smn2B/-mice. However, there were no differences in Smn protein levels in the spinal cords of these mice. Interestingly, levels of Plastin 3, a putative modifier of SMA, were significantly induced in spinal cords of BL6 Smn2B/- mice but not of FVB Smn2B/-mice. Our studies demonstrate that the phenotype in Smn2B/-mice is more severe in the FVB background than in the BL6 background, which could potentially be explained by the differential induction of genetic modifiers.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".