Generation and function of astroglial lipoproteins from Niemann–Pick type C1-deficient mice
Bibliographic record
Abstract
NPC (Niemann-Pick type C) disease is a progressive neurological disorder characterized by defects in intracellular cholesterol trafficking, accumulation of cholesterol in the endosomal system and impaired cholesterol homoeostasis. Although these alterations appear to occur in all NPC1-deficient cell types, the consequences are most profound in the nervous system. Since glial cells are important mediators of brain cholesterol homoeostasis, we proposed that defective generation and/or function of lipoproteins released by glia might contribute to the neurological abnormalities associated with NPC disease. We found that, as in other cell types, Npc1-/- glia accumulate cholesterol intracellularly. We hypothesized that this sequestration of cholesterol in glia might restrict the availability of cholesterol for lipoprotein production. Cerebellar astroglia were cultured from a murine model of NPC disease to compare the lipoproteins generated by these cells and wild-type glia. The experiments demonstrate that the amount of cholesterol in glia-conditioned medium is not reduced by NPC1 deficiency. Similarly, cholesterol efflux to apo (apolipoprotein) A1 or glial expression of the transporter ATP-binding-cassette transporter A1 was not decreased by NPC1 deficiency. In addition, the ratio of apo E:cholesterol and the density distribution of lipoproteins in Npc1-/- and Npc1+/+ glia-conditioned medium are indistinguishable. Importantly, in a functional assay, apo E-containing lipoproteins generated by Npc1-/- and Npc1+/+ glia each stimulate axonal elongation of neurons by approx. 35%. On the basis of these observations, we speculate that the neuropathology characteristic of NPC disease can quite probably be ascribed to impaired processes within neurons in the brain rather than defective lipoprotein production by astroglia.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".