Incorporation of β-actin loading control into zymography
Bibliographic record
Abstract
Gelatin zymography and immunoblot are widely used gel electrophoresis techniques to study matrix metalloproteinases-2 and -9. Each method has its advantages and disadvantages. Zymography is exquisitely sensitive but offers no loading control to ensure equal sample loading. Immunoblot is a 100-1000-fold less sensitive, but allows for the probing of a sample loading control such as β-actin to ensure accurate protein loading. In this report, we describe two simple protocols that combine gelatin zymography to study MMP-2 and -9 levels with an in-gel β-actin immunoblot loading control, thus combining sensitivity and accuracy in a single assay. The protocols incorporate the loading of molecular weight markers to demarcate MMP-2/-9 from the β-actin. The first protocol utilizes the overlay of a 10% zymography gel over a 5% Tris-Glycine separating gel from which the β-actin is transferred. The second protocol involves the direct transfer of the β-actin from a single 10% zymography gel.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.031 | 0.013 |
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".