Sorting nexin 10 regulates lysosomal ionic homeostasis via ClC-7 by controlling PI(3,5)P2
Bibliographic record
Abstract
Mutations or ablation of Snx10 are associated with neurodegeneration, blindness, and osteopetrosis. The similarities between osteoclasts and macrophages prompted us to analyze the role of Snx10 in phagocytosis. Deletion of Snx10 impaired phagosome resolution. Defective resolution was caused by reduced Cl- accumulation within (phago)lysosomes, replicating the phenotype reported in macrophages lacking ClC-7, a lysosomal 2Cl-/H+ antiporter. Delivery of ClC-7 to (phago)lysosomes was unaffected by ablation of Snx10, but its activity was markedly depressed. Snx10 was found to regulate ClC-7 activity indirectly by controlling the availability of phosphatidylinositol 3,5-bisphosphate (PI[3,5]P2), which inhibits ClC-7. By limiting the formation of PI(3,5)P2, Snx10 enables the accumulation of luminal Cl- in phagosomes and lysosomes, which is required for their optimal degradative function. Our data suggest that Snx10 regulates the delivery of PI 3-phosphate (PI[3]P), the precursor of PI(3,5)P2, from earlier endocytic compartments to (phago)lysosomes. By controlling the traffic of phosphoinositides, Snx10 regulates phagosomal resolution and possibly accounts for the impaired bone resorption in Snx10-deficient osteoclasts.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".