Cadmium affects focal adhesion kinase (FAK) in mesangial cells: Involvement of CaMK‐II and the actin cytoskeleton
Bibliographic record
Abstract
The toxic metal ion cadmium (Cd(2+)) induces pleiotropic effects on cell death and survival, in part through effects on cell signaling mechanisms and cytoskeletal dynamics. Linking these phenomena appears to be calmodulin-dependent activation of the Ca(2+)/calmodulin-dependent protein kinase II (CaMK-II). Here we show that interference with the dynamics of the filamentous actin cytoskeleton, either by stabilization or destabilization, results in disruption of focal adhesions at the ends of organized actin structures, and in particular the loss of vinculin and focal adhesion kinase (FAK) from the contacts is a result. Low-level exposure of renal mesangial cells to CdCl2 disrupts the actin cytoskeleton and recapitulates the effects of manipulation of cytoskeletal dynamics with biological agents. Specifically, Cd(2+) treatment causes loss of vinculin and FAK from focal contacts, concomitant with cytoskeletal disruption, and preservation of cytoskeletal integrity with either a calmodulin antagonist or a CaMK-II inhibitor abrogates these effects of Cd(2+). Notably, inhibition of CaMK-II decreases the migration of FAK-phosphoTyr925 to a membrane-associated compartment where it is otherwise sequestered from focal adhesions in a Cd(2+)-dependent manner. These results add further insight into the mechanism of the CaMK-II-dependent effects of Cd(2+) on cellular 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 | 0.000 |
| 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".