Agonist-induced aggregation of Chinese hamster ovary cells coexpressing the human receptors for fibrinogen (integrin αIIbβ3) and the platelet-activating factor: dissociation between adhesion and aggregation
Bibliographic record
Abstract
This work reports the establishment of a Chinese hamster ovary (CHO) cell line stably coexpressing the human alphaIIbbeta3 integrin and the platelet-activating factor receptor (PAFR). These cells aggregate in response to PAF in a Ca(++), alphaIIbbeta3, and soluble fibrinogen (Fg)-dependent manner that is prevented by PAF antagonists or alphaIIbbeta3 blockade. The aggregating response is accompanied by enhanced binding of fibrinogen and the activation-dependent IgM PAC1. This model has permitted us to identify, for the first time, intracellular signals distinctly associated with either alphaIIbbeta3-mediated adhesion or aggregation. Nonreceptor activation of protein kinase C (PKC) by phorbol ester produced cellular adhesion and spreading onto immobilized Fg, but it was not a sufficient signal to provoke cellular aggregation. Moreover, inhibition of PKC impeded the PAF stimulation of cellular adhesion, whereas the aggregation was not prevented. The PAF-induced cellular aggregation was distinctly associated with signaling events arising from the liganded Fg receptor and the agonist-induced stimulation of a calcium/calmodulin-dependent signaling pathway. Sustained tyrosine phosphorylation of both mitogen-activated protein kinase (MAPK) and an approximately 100-kd protein was associated with the PAF-induced aggregation, whereas phosphorylation of focal adhesion kinase (FAK) was preferably associated with cellular adherence and spreading onto immobilized Fg.
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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 | 0.000 |
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 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".