Gelsolin and Non-muscle Myosin IIA Interact to Mediate Calcium-regulated Collagen Phagocytosis
Bibliographic record
Abstract
The formation of adhesion complexes is the rate-limiting step for collagen phagocytosis by fibroblasts, but the role of Ca(2+) and the potential interactions of actin-binding proteins in regulating collagen phagocytosis are not well defined. We found that the binding of collagen beads to fibroblasts was temporally and spatially associated with actin assembly at nascent phagosomes, which was absent in gelsolin null cells. Analysis of tryptic digests isolated from gelsolin immunoprecipitates indicated that non-muscle (NM) myosin IIA may bind to gelsolin. Immunostaining and immunoprecipitation showed that gelsolin and NM myosin IIA associated at collagen adhesion sites. Gelsolin and NM myosin IIA were both required for collagen binding and internalization. Collagen binding to cells initiated a prolonged increase of [Ca(2+)](i), which was absent in cells null for gelsolin or NM myosin IIA. Collagen bead-induced increases of [Ca(2+)](i) were associated with phosphorylation of the myosin light chain, which was dependent on gelsolin. NM myosin IIA filament assembly, which was dependent on myosin light chain phosphorylation and increased [Ca(2+)](i), also required gelsolin. Ionomycin-induced increases of [Ca(2+)](i) overcame the block of myosin filament assembly in gelsolin null cells. We conclude that gelsolin and NM myosin IIA interact at collagen adhesion sites to enable NM myosin IIA filament assembly and localized, Ca(2+)-dependent remodeling of actin at the nascent phagosome and that these steps are required for collagen phagocytosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".