Lysosomal Membranes from Beige Mice Contain Higher Than Normal Levels of Endoplasmic Reticulum Proteins
Bibliographic record
Abstract
Chediak-Higashi syndrome is characterized by dysfunctional giant organelles of common origin, that is, lysosomes, melanosomes, and platelet dense bodies. Its defective gene LYST encodes a large molecular weight protein whose function is unknown. The Beige mouse also defective in Lyst is a good model of the human disease. Purified lysosomes from Beige and normal black mouse livers were used to carry out a proteomics study. Two-dimensional gel electrophoretic separation of soluble lysosomal proteins of Beige and normal mice revealed no major differences. The cleavable isotope-coded affinity tag (cICAT) technique was used to compare the composition of Beige and normal lysosomal membrane proteins. While the levels of common proteins, that is, Lamp1, Lamp2, and Niemann-Pick type C1, were decreased in Beige mice, there was an increase in the levels of endoplasmic reticulum (ER) resident proteins, for example, cytochrome P450, NADPH-cytochrome P450 oxidoreductase, and flavin-containing monooxygenase. Confocal microscopy confirmed that another ER protein, calnexin, colocalizes with Lamp1 on membranes of giant lysosomes from fibroblasts of Chediak-Higashi syndrome patient. Our results suggest that LYST may play a role in either preventing inappropriate incorporation of proteins into the lysosomal membrane or in membrane recycling/maturation.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".