Crosstalk between Notch and Sonic hedgehog signaling in a mouse model of amyotrophic lateral sclerosis
Bibliographic record
Abstract
The developmental morphogen Sonic hedgehog (Shh) may continue to play a sustaining role in adult motor neurons, of potential relevance to motor neuron diseases including amyotrophic lateral sclerosis. The Shh signaling pathway is incompletely understood and interactions with other signaling pathways are possible. We focus here on Notch, and first show that there is an almost linear reduction in light output from a Gli reporter in Shh Light II cells in the presence of increasing concentrations of the Notch inhibitor DAPT (r=0.982). Second, in the spinal cord of mutant superoxide dismutase mice, but not control mice, a key marker of Notch signaling changes with age. Before the onset of clinical signs, the Notch intracellular domain is expressed predominantly in motor neurons, but by 125 days of age, Notch intracellular domain expression is markedly reduced in motor neurons and increased in neighboring astroglia. Third, there is a parallel reduction in Gli protein expression in mutant superoxide dismutase mouse spinal motor neurons, consistent with the observed reduction in Notch signaling and also a redistribution of Gli away from the nucleus. Thus, there is a reduction in motor neuronal Notch signaling and associated changes in Shh signaling, occurring coincidentally with disease expression, that may contribute toward the dysfunction and death of motor neurons in amyotrophic lateral sclerosis.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".