Robust Comparison of Protein Levels Across Tissues and Throughout Development Using Standardized Quantitative Western Blotting
Bibliographic record
Abstract
Western blotting is a technique that is commonly used to detect and quantify protein expression. Over the years, this technique has led to many advances in both basic and clinical research. However, as with many similar experimental techniques, the outcome of Western blot analyses is easily influenced by choices made in the design and execution of the experiment. Specific housekeeping proteins have traditionally been used to normalize protein levels for quantification, however, these have a number of limitations and have therefore been increasingly criticized over the past few years. Here, we describe a detailed protocol that we have developed to allow us to undertake complex comparisons of protein expression variation across different tissues, mouse models (including disease models), and developmental timepoints. By using a fluorescent total protein stain and introducing the use of an internal loading standard, it is possible to overcome existing limitations in the number of samples that can be compared within experiments and systematically compare protein levels across a range of experimental conditions. This approach expands the use of traditional western blot techniques, thereby allowing researchers to better explore protein expression across different tissues and samples.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".