Flow cytometric measurement of calpain activity in living cells
Bibliographic record
Abstract
BACKGROUND: Calpains are intracellular, calcium-sensitive, neutral cysteine proteases that play crucial roles in many physiological and pathological processes. Calpain regulation is complex and activity is poorly correlated with calpain protein levels. Therefore a full understanding of calpain function requires robust methods for measuring activity. METHODS: We describe and characterize a flow cytometric method for measuring calpain activity in live cells. This method uses the BOC-LM-CMAC reagent that readily diffuses into cells where it reacts with free thiols to enhance retention. RESULTS: We show that the reagent is cleaved specifically by calpains and follows saturation kinetics. We use the assay to measure calpain activation following PDGF stimulation of rat fibroblasts. We also show that the calpain inhibitor PD150606 inhibits calpain with a K(i) of 12.5 muM and show that Mek inhibitors PD89059 and U0126 also suppress calpain activity. We also show that the assay can measure calpain activity in subpopulations of cells present in unfractionated cord blood or in HL60 human myelomonocytic leukemia cells. CONCLUSION: Taken together, these experiments demonstrate that this assay is a reliable and useful method for measuring calpain activity in multiple cell types.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".