THP-1 cells transduced with CD16A utilize Fcγ receptor I and III in the phagocytosis of IgG-sensitized human erythrocytes and platelets
Bibliographic record
Abstract
Fc gamma receptors (FcγRs) are critical effector receptors for immunoglobulin G (IgG) antibodies. On macrophages, FcγRs mediate multiple effector functions, including phagocytosis, but the individual contribution of specific FcγRs to phagocytosis has not been fully characterized. Primary human macrophage populations, such as splenic macrophages, can express FcγRI, FcγRIIA, and FcγRIIIA. However, there is currently no widely available monocyte or macrophage cell line expressing all these receptors. Common sources of monocytes for differentiation into macrophages, such as human peripheral blood monocytes and the monocytic leukemia cell line THP-1, generally lack the expression of FcγRIIIA (CD16A). Here, we utilized a lentiviral system to generate THP-1 cells stably expressing human FcγRIIIA (CD16F158). THP-1-CD16A cells treated with phorbol 12-myristate 13-acetate for 24 hours phagocytosed anti-D-opsonized human red blood cells primarily utilizing FcγRI with a lesser but significant contribution of IIIA while phagocytosis of antibody-opsonized human platelets equally utilized FcγRI and Fcγ IIIA. Despite the well-known ability of FcγRIIA to bind IgG in cell free systems, this receptor did not appear to be involved in either RBC or platelet phagocytosis. These transgenic cells may constitute a valuable tool for studying macrophage FcγR utilization and function.
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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 | 0.001 |
| 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".