Bibliographic record
Abstract
The Fc receptor is expressed on the surface of RAW macrophages that can engulf IgG opsonized particles by phagocytosis. Isolation and characterization of these receptors and the identification of proteins involved is challenging. Live-cell Affinity Receptor Chromatography (LARC) (Janowski 2008) resulted in the identification of 336 proteins which are found to be specifically associated with the activated Fc receptor in RAW 264.7 macrophage cells. The proteins isolated were analyzed for protein-protein interactions using various analytical techniques including data mining through the use of iHOP, protein interaction databases such as Cytoscape, Osprey and STRING and literature searches, in order to create a signalling interaction pathway involving the proteins that are activated and associated with the Fcy receptor during receptor-mediated phagocytosis. The phospholipase C family of proteins have been previously identified as important in phagocytosis, and were identified by LARC. The selected isoforms were confirmed in RAW 264.7 cells via Western Blots, antibody staining, and live-cell confocal microscopy with fluorescently linked fusion proteins to verify the localization of the phospholipases, specifically PLC-β₃, PLC-β₄, PLC-y₁, PLC-d₁, PLC-ε₁ and PLC like -2 to the activated receptor complex.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".