Granulocyte–macrophage colony‐stimulating factor promotes survival of dopaminergic neurons in the 1‐methyl‐4‐phenyl‐1,2,3,6‐tetrahydropyridine‐induced murine Parkinson’s disease model
Bibliographic record
Abstract
Granulocyte-macrophage colony-stimulating factor (GM-CSF) is a hematopoietic cytokine that has the potential for clinical application. The biological effects of GM-CSF have been well characterized, and include stimulation of bone marrow hematopoietic stem cell proliferation and inhibition of apoptosis of hematopoietic cells. In contrast, the therapeutic effects of GM-CSF on the central nervous system in acute injury such as stroke and spinal cord injury have been reported only recently. To better understand the protective effect of GM-CSF on dopaminergic neurons in Parkinson's disease (PD), we investigated the effect of GM-CSF on the survival of dopamine neurons and changes in locomotor behavior in a murine PD model. We investigated the neuroprotective effects of GM-CSF in 1-methyl-4-phenylpyridinium (MPP+)-treated PC12 cells as well as in embryonic mouse primary mesencephalic neurons (PMNs) in vitro. To investigate the role of GM-CSF in vivo, we prepared a mouse 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) PD model, and examined the effects of GM-CSF on dopaminergic neuron survival in the substantia nigra and on locomotor behavior. Treatment with GM-CSF significantly reduced MPP+-induced dopaminergic cell death in PC12 cells and PMNs in vitro. GM-CSF modulated the expression of apoptosis-related proteins, Bcl-2 and Bax, in vitro. Furthermore, administration of GM-CSF (50 microg/kg body weight/day) in vivo for 7 days protected dopaminergic neurons in the substantia nigra and improved locomotor behavior in a mouse MPTP model of PD.
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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) | 0.001 | 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".