Munc13-4 Regulates Granule Secretion in Human Neutrophils
Bibliographic record
Abstract
The neutrophil plays a central role in the innate host immune defense. Regulated exocytosis of its granules and release of antimicrobial and cytotoxic substances are key events to limit the spread of pathogens. However, the molecular mechanisms that control exocytosis of neutrophil granules are ill-defined. Recently, it was shown that Munc13-4 is essential for the priming of granules in several hematopoietic cells. In this study, we show that Munc13-4 is expressed in human neutrophils, and that its expression is increased during granulocytic differentiation of HL-60 and PLB-985 cells. Cell fractionation analysis reveals that Munc13-4 is mainly cytosolic and is recruited rapidly to membranes following stimulation with fMLF (N-formyl-methionyl-leucyl-phenylalanine). Moreover, a pool of Munc13-4 associated with mobilizable secondary and tertiary granules is relocalized to the plasma membrane after stimulation with fMLF. The fMLF-induced translocation of Munc13-4 is strictly dependent on calcium in neutrophils. C2 domains of Munc13-4 are essential for binding to phospholipid vesicles in a Ca(2+)-independent manner. Finally, down-regulation of Munc13-4 using small interfering RNA decreases exocytosis of tertiary granules in PLB-985 cells, whereas overexpression of Munc13-4 enhances secretion of MMP-9 (matrix metalloproteinase-9) from tertiary granules. Our findings suggest a role for Munc13-4 as a component of the secretory machinery in neutrophils.
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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".