<i>In Vivo</i>NMDA Receptor Activation Accelerates Motor Unit Maturation, Protects Spinal Motor Neurons, and Enhances SMN2 Gene Expression in Severe Spinal Muscular Atrophy Mice
Bibliographic record
Abstract
Spinal muscular atrophy (SMA), a lethal neurodegenerative disease that occurs in childhood, is caused by the misexpression of the survival of motor neuron (SMN) protein in motor neurons. It is still unclear whether activating motor units in SMA corrects the delay in the postnatal maturation of the motor unit resulting in an enhanced neuroprotection. In the present work, we demonstrate that an adequate NMDA receptor activation in a type 2 SMA mouse model significantly accelerated motor unit postnatal maturation, counteracted apoptosis in the spinal cord, and induced a marked increase of SMN expression resulting from a modification of SMN2 gene transcription pattern. These beneficial effects were dependent on the level of NMDA receptor activation since a treatment with high doses of NMDA led to an acceleration of the motor unit maturation but favored the apoptotic process and decreased SMN expression. In addition, these results suggest that the NMDA-induced acceleration of motor unit postnatal maturation occurred independently of SMN. The NMDA receptor activating treatment strongly extended the life span in two different mouse models of severe SMA. The analysis of the intracellular signaling cascade that lay downstream the activated NMDA receptor revealed an unexpected reactivation of the CaMKII/AKT/CREB (cAMP response element-binding protein) pathway that induced an enhanced SMN expression. Therefore, pharmacological activation of spinal NMDA receptors could constitute a useful strategy for both increasing SMN expression and limiting motor neuron death in SMA spinal cord.
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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 | 0.000 | 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 | 0.001 |
| 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".