Structure‐function studies for in vitro chemical inhibition of Fcγ receptor–mediated phagocytosis
Bibliographic record
Abstract
BACKGROUND: Previous studies [Transfusion 2005;45:384] showed that certain chemical compounds containing sulfur-reactive groups can inhibit Fcgamma receptor (FcgammaR)-mediated phagocytosis in vitro. These studies, however, did not prove that only sulfur functionality-induced reactivity was efficacious. In an effort to develop a drug-based approach for the future treatment of immune-mediated cytopenias, these earlier findings have now been extended and this chemically induced interference with FcgammaR-mediated phagocytosis of anti-D-coated red cells (RBCs) was examined to assess the optimal structural requirements for the inhibitory effect. STUDY DESIGN AND METHODS: Chemical compounds were purchased or synthesized and used for the assessment of which chemical moiety(-ies) were required for successful inhibition of in vitro phagocytosis of anti-D-coated RBCs with a monocyte monolayer assay. RESULTS: Using compounds having similar structures but differences in reactive moieties, it was proved that the only chemical moiety that was required for inhibition of FcgammaR-mediated phagocytosis in vitro was a disulfide bond. It is also shown, however, that a p-nitrophenyl group provides significant enhancement to the inhibitory effect of disulfide-containing compounds. Involvement of carbonyl and hydroxyl functional groups was also able to be ruled out. CONCLUSION: Our results confirm and extend previous studies that suggested that only those compounds that target free sulfhydryl groups on the monocyte-macrophage are most effective at blocking phagocytosis of antibody-coated RBCs in vitro. It is also shown that p-nitrophenyl substituent groups have an enhancing effect on the efficacy of disulfide bond-containing compounds. These findings should aid in the design of a drug-based approach for the future treatment of immune cytopenias.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".