BK channel agonist represents a potential therapeutic approach for lysosomal storage diseases
Bibliographic record
Abstract
Abstract Efficient lysosomal Ca2+ release plays an essential role in lysosomal trafficking. We have recently shown that lysosomal big conductance Ca2+-activated potassium (BK) channel forms a physical and functional coupling with the lysosomal Ca2+ release channel Transient Receptor Potential Mucolipin-1 (TRPML1). BK and TRPML1 forms a positive feedback loop to facilitate lysosomal Ca2+ release and subsequent lysosome membrane trafficking. However, it is unclear whether the positive feedback mechanism is common for other lysosomal storage diseases (LSDs) and whether BK channel agonists rescue abnormal lysosomal storage in LSDs. In this study, we assessed the effect of BK agonist, NS1619 and NS11021 in a number of LSDs including NPC1, mild cases of mucolipidosis type IV (ML4) (TRPML1-F408∆), Niemann-Pick type A (NPA) and Fabry disease. We found that TRPML1-mediated Ca2+ release was compromised in these LSDs. BK activation corrected the impaired Ca2+ release in these LSDs and successfully rescued the abnormal lysosomal storage of these diseases by promoting TRPML1-mediated lysosomal exocytosis. Our study suggests that BK channel activation stimulates the TRPML1-BK positive reinforcing loop to correct abnormal lysosomal storage in LSDs. Drugs targeting BK channel represent a potential therapeutic approach for LSDs.
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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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".