The actin cytoskeleton facilitates complement-mediated activation of cytosolic phospholipase A<sub>2</sub>
Bibliographic record
Abstract
Cytosolic PLA(2)-alpha (cPLA(2)) and metabolites of arachidonic acid (AA) are key mediators of complement-dependent glomerular epithelial cell (GEC) injury. Assembly of C5b-9 increases cytosolic Ca(2+) concentration and results in transactivation of receptor tyrosine kinases and activation of PLC-gamma 1 and the 1,2-diacylglycerol (DAG)-PKC pathway. Ca(2+) and PKC are essential for membrane association and increased catalytic activity of cPLA(2). This study addresses the role of the actin cytoskeleton in cPLA(2) activation. Depolymerization of F-actin by cytochalasin D or latrunculin B reduced complement-dependent [(3)H]AA release, as well as the complement-induced increase in cPLA(2) activity. These effects were due to inhibition of [(3)H]DAG production and PKC activation, implying interference with PLC. Complement-dependent [(3)H]AA release was also reduced by jasplakinolide, a compound that stabilizes F-actin and organizes actin filaments at the cell periphery, and calyculin A, which induces condensation of actin filaments at the plasma membrane. The latter drugs did not affect [(3)H]DAG production, suggesting their inhibitory actions were downstream of PKC. Neither cytochalasin D, latrunculin B, nor calyculin A affected association of cPLA(2) with microsomal membranes, and cytochalasin D and latrunculin B did not alter the localization of the endoplasmic reticulum. Stable transfection of constitutively active RhoA induced formation of stress fibers, stabilized F-actin, and attenuated the complement-induced increase in [(3)H]AA. Thus in GEC, cPLA(2) activation is dependent, in part, on actin remodeling. By regulating complement-mediated activation of cPLA(2), the actin cytoskeleton may contribute to the pathophysiology of GEC injury.
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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) | 0.002 | 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".