Granulocyte-colony stimulating factor improves outcome in a mouse model of amyotrophic lateral sclerosis
Bibliographic record
Abstract
Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disease that results in progressive loss of motoneurons, motor weakness and death within 1-5 years after disease onset. Therapeutic options remain limited despite a substantial number of approaches that have been tested clinically. In particular, various neurotrophic factors have been investigated. Failure in these trials has been largely ascribed to problems of insufficient dosing or inability to cross the blood-brain barrier (BBB). We have recently uncovered the neurotrophic properties of the haematopoietic protein granulocyte-colony stimulating factor (G-CSF). The protein is clinically well tolerated and crosses the intact BBB. This study examined the potential role of G-CSF in motoneuron diseases. We investigated the expression of the G-CSF receptor in motoneurons and studied effects of G-CSF in a motoneuron cell line and in the SOD1(G93A) transgenic mouse model. The neurotrophic growth factor was applied both by continuous subcutaneous delivery and CNS-targeted transgenic overexpression. This study shows that given at the stage of the disease where muscle denervation is already evident, G-CSF leads to significant improvement in motor performance, delays the onset of severe motor impairment and prolongs overall survival of SOD1(G93A)tg mice. The G-CSF receptor is expressed by motoneurons and G-CSF protects cultured motoneuronal cells from apoptosis. In ALS mice, G-CSF increased survival of motoneurons and decreased muscular denervation atrophy. We conclude that G-CSF is a novel neurotrophic factor for motoneurons that is an attractive and feasible drug candidate for the treatment of ALS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".