Integrins Specifically Associated with the Activated Phagocytic Receptor Complexes from Human U937 Macrophages and the Integrins of Human Blood
Bibliographic record
Abstract
Receptor complexes are a key locus in the treatment of disease and pain but remain difficult to isolate. The Fc receptor binds to IgG presented on micro particles and triggers phagocytosis that is required for the engulfment of bacteria and non-self, pathogen molecules. Circulating LDL may be converted to oxLDL that is recognized by scavenger or other innate receptors that trigger the production of free radicals and phagocytic engulfment. The Fc receptor complex was captured using its cognate ligand IgG bound to 2 micron polystyrene beads from live cells by live cell affinity receptor chromatography (LARC). Similarly, oxLDL was used to coat micro beads to isolate the oxLDL-scavenger receptor complexes. The ligand coated beads were presented to live human macrophage U937 cells and sampled over the course of cell binding and engulfment in saline experimental medium. The receptor complexes were isolated by disruption with a French press and sucrose gradient centrifugation. The receptor complexes were separated using a salt and acetonitrile gradient prior to digestion with trypsin. The peptides were analyzed by LC-ESI MS/MS using a linear ion trap (Thermo) with the SEQUEST algorithm. In addition ligand affinity chromatography was performed using IgG, oxLDL or anti CD36 microbeads incubated with crude extracts. Controls included uncoated, or ligand coated, beads incubated in crude extract and/or used experimental medium. Certain integrins were shown to be specifically associated with IgG versus oxLDL and/or control treatments. The functional requirement for these integrins was tested using silencing RNA and quantitative assays of phagocytosis using laser scanning confocal microscopy. For the first time we show a small but statistically significant role for integrins in IgG-Fcγ receptor mediated phagocytosis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".