Activation Via Multiple Signaling Pathways Induces Down-Regulation of Platelet-Activating Factor Receptors on Human B Lymphocytes
Bibliographic record
Abstract
Platelet-activating factor receptor (PAFR) has been identified in B cell lines and primary human B cells, but the regulation of PAFR during B cell activation has not been completely elucidated. In the present study, we have investigated the effects of B cell activation on PAFR binding parameters, PAFR mRNA and PAF-triggered intracellular calcium mobilization. The human B lymphoid cell line LA350 was shown to exhibit high levels of PAFR (48,550 +/- 4,310 sites/cell) as determined by radio-ligand binding assay with PAFR antagonist [3H]WEB2086. Treatment with phorbol 12,13-dibutyrate caused a biphasic reduction of PAFR binding. The early phase was inhibited by the protein kinase C inhibitor bisindolylmaleimide I (BIM), whereas the late phase was not blocked by BIM, protein tyrosine kinase inhibitor genistein, or the mitogen-activated protein kinase/extracellular signal-related kinase inhibitor PD98059. However, staurosporine, a broad-spectrum protein kinase inhibitor, completely inhibited the late phase down-regulation. Ionomycin also decreased [3H]WEB2086 binding sites, whereas the combination of PDB and ionomycin induced a greater reduction than either agent alone. Cross-linking of B cell receptor by anti-IgM Ab also induced down-regulation of PAFR, which was abolished by genistein or PD98059, but not by BIM or staurosporine. The decrease in surface PAFR number was closely paralleled by the reduction in PAFR mRNA both in LA350 cells and human tonsillar B cells, and was associated with decreased response to PAF indicated by decreased intracellular calcium mobilization. These data show that multiple signaling pathways are involved in down-regulating PAFR expression during B cell activation and development.
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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 | 0.000 |
| 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".