Membrane Trafficking during Phagosome Formation and Maturation
Bibliographic record
Abstract
This chapter addresses the vesicular trafficking events involved in the formation and maturation of the phagosome. The reported increase in surface area during phagocytosis is most readily explained by delivery of an internal pool of membranes to the plasmalemma. Recent studies demonstrated that specific and tertiary granules contain VAMP1 and VAMP2, while azurophilic granules contain VAMP1 and VAMP7, with STX4 and SNAP23 involved in the exocytosis of these distinct populations of granules. Lysobisphosphatidic acid (LBPA) is found in late phagosomes, where it is likely to complex ALIX and direct membrane fission and the intermediate stages of maturation. Phagosome formation and maturation are impressive microbicidal tools. For this reason pathogens have developed a remarkable variety of strategies to subvert this process. Some of the most virulent and persistent bacterial pathogens such as Mycobacterium and Leishmania in fact take advantage of the phagocytic machinery to gain access into the host cell interior, where they are able to circumvent the sophisticated killing mechanism of the maturing phagosome. At present the knowledge of phagosome maturation is rudimentary and largely extrapolated from that garnered for the endocytic pathway. Some extrapolation is probably warranted, but many unique features of phagosomes will only be revealed by direct studies of particle, preferably microbial, ingestion.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.012 |
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".