Bibliographic record
Abstract
Solid particles such as pathogens, dying cells, and debris are engulfed by macrophages and neutrophils and sequestered into a phagosome. Phagosomes fuse with early and late endosomes and ultimately with lysosomes to mature into phagolysosomes, a process known as phagosome maturation. The formation of highly acidic and degradative phagolysosomes plays an important role in degradation of the internalized particle. We employed siRNA and pharmacological tools to demonstrate that phosphatidylinositol-3,5-bisphosphate [PI(3,5)P2], synthesized by the PIKfyve lipid kinase, is required for phagosome maturation. However, the mechanism by which PI(3,5)P2 controls phagosome maturation remained uncharacterized. We hypothesized that PI(3,5)P2 may control phagosome-lysosome fusion partly by stimulating TRPML1, a lysosomal Ca2+ channel gated by PI(3,5)P2. Upon opening of the channel, lysosomal Ca2+ would diffuse and trigger phagosome-lysosome fusion since Ca2+ is known to induce membrane fusion post-docking of SNARE proteins. In addition, we also demonstrated that the lipid kinase PIKfyve coordinates the neutrophils immune response by controlling phagosome maturation and regulating Rac GTPase activity. PIKfyve produces both PI(3,5)P2 and phosphatidylinositol-5-phosphate (PI5P); therefore, it might control phagosome maturation through production of PI(3,5)P2 and activation of TRPML1 as well as regulates ROS production and chemotaxis through synthesis of PI5P, which leads to the activation of Tiam1, and Rac GTPase.
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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 | 0.000 |
| 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".