Immune dysregulation may contribute to disease pathogenesis in spinal muscular atrophy mice
Bibliographic record
Abstract
Spinal muscular atrophy (SMA) has long been solely considered a neurodegenerative disorder. However, recent work has highlighted defects in many other cell types that could contribute to disease aetiology. Interestingly, the immune system has never been extensively studied in SMA. Defects in lymphoid organs could exacerbate disease progression by neuroinflammation or immunodeficiency. Smn depletion led to severe alterations in the thymus and spleen of two different mouse models of SMA. The spleen from Smn depleted mice was dramatically smaller at a very young age and its histological architecture was marked by mislocalization of immune cells in the Smn2B/- model mice. In comparison, the thymus was relatively spared in gross morphology but showed many histological alterations including cortex thinning in both mouse models at symptomatic ages. Thymocyte development was also impaired as evidenced by abnormal population frequencies in the Smn2B/- thymus. Cytokine profiling revealed major changes in different tissues of both mouse models. Consistent with our observations, we found that survival motor neuron (Smn) protein levels were relatively high in lymphoid organs compared to skeletal muscle and spinal cord during postnatal development in wild type mice. Genetic introduction of one copy of the human SMN2 transgene was enough to rescue splenic and thymic defects in Smn2B/- mice. Thus, Smn is required for the normal development of lymphoid organs, and altered immune function may contribute to SMA disease pathogenesis.
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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) | 0.003 | 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".