Trafficking of Cholesterol from Cell Bodies to Distal Axons in Niemann Pick C1-deficient Neurons
Bibliographic record
Abstract
Niemann Pick type C (NPC) disease is a progressive neurodegenerative disorder. In cells lacking functional NPC1 protein, endocytosed cholesterol accumulates in late endosomes/lysosomes. We utilized primary neuronal cultures in which cell bodies and distal axons reside in separate compartments to investigate the requirement of NPC1 protein for transport of cholesterol from cell bodies to distal axons. We have recently observed that in NPC1-deficient neurons compared with wild-type neurons, cholesterol accumulates in cell bodies but is reduced in distal axons (Karten, B., Vance, D. E., Campenot, R. B., and Vance, J. E. (2002) J. Neurochem. 83, 1154-1163). We now show that NPC1 protein is expressed in both cell bodies and distal axons. In NPC1-deficient neurons, cholesterol delivered to cell bodies from low density lipoproteins (LDLs), high density lipoproteins, or cyclodextrin complexes was transported into axons in normal amounts, whereas transport of endogenously synthesized cholesterol was impaired. Inhibition of cholesterol synthesis with pravastatin in wild-type and NPC1-deficient neurons reduced axonal growth. However, LDLs restored a normal rate of growth to wild-type but not NPC1-deficient neurons treated with pravastatin. Thus, although LDL cholesterol is transported into axons of NPC1-deficient neurons, this source of cholesterol does not sustain normal axonal growth. Over the lifespan of NPC1-deficient neurons, these defects in cholesterol transport might be responsible for the observed altered distribution of cholesterol between cell bodies and axons and, consequently, might contribute to the neurological dysfunction in NPC disease.
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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".