Live imaging of amyotrophic lateral sclerosis pathogenesis: Disease onset is characterized by marked induction of GFAP in Schwann cells
Bibliographic record
Abstract
Amyotrophic lateral sclerosis (ALS) is a late-onset neurological disease characterized by progressive loss of motor neurons. At present, the pathological events precipitating disease onset and the exact pattern of disease progression are not fully understood. Recent studies suggest that glial cells, in particular activated astrocytes, can release factors that can directly kill motor neurons. To further investigate the involvement of glial cells (astrocytes and Schwann cells) in the pathogenesis of ALS, we generated ALS-(GFAP-luciferase/SOD(G93A)) reporter mouse in which upregulation of glial fibrillary acidic protein (GFAP) can be visualized from live animals throughout the different stages of disease. Our results suggest that the disease in mice is initiated simultaneously in the spinal cord and in the peripheral nerves and is characterized by several cycles of GFAP upregulation. Immunohistochemical analysis confirmed that the induction GFAP bioluminescence signals were associated with the significant increases in GFAP immunoreactivity. The first pathological GFAP signals occurring at 25-30 days were asymptomatic and detectable at the level of lumbar spinal cord projections and at the periphery. These early events were then followed by GFAP promoter inductions that were associated with the distinct clinical symptoms. As expected, the onset of paralysis (112 days) was associated with the gradual and marked GFAP upregulation in the spinal cord. Interestingly, however, the disease onset (90 days) was characterized by sharp and synchronized induction of GFAP in peripheral nerve Schwann cells suggesting that peripheral nerves pathology/denervation and associated Schwann cell stress may play an important role in the ALS 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) | 0.000 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".