Determinants of phagocytic receptor mobility: cytoskeletal picket fences and the pericellular glycocalyx coat.
Bibliographic record
Abstract
Abstract Phagocytosis is initiated by clustering of receptors upon exposure to target particles bearing multiple ligands. Clustering depends on the ability of receptors to move laterally in the plane of the membrane. Intrinsic proteins were originally thought to diffuse freely along the fluid mosaic of the membrane, but more recent observations indicate that mobility can be severely restricted by the existence of a cytoskeletal fence anchored to the plasmalemma via transmembrane “pickets”. However, the molecular nature of these putative pickets, the manner whereby they associate with the cytoskeleton, and their role in phagocytosis have not been investigated. Based on its abundance and structural features, we surmised that CD44 may serve as a picket in macrophages. We used single-molecule tracking to study its behavior and how it affects the mobility of phagocytic receptors. In addition, because its extracellular domain can bind hyaluronic acid, we found that CD44 serves as a transmembrane connector between the pericellular (glycocalyx) coat and the cytoskeleton. The pericellular coat curtails access of particles to the comparatively short phagocytic receptors. The implications of this transmembrane framework to phagocytosis were investigated and will be discussed.
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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".