APols-Aided Protein Precipitation: A Rapid Method for Concentrating Proteins for Proteomic Analysis
Bibliographic record
Abstract
Amphipols (APols) are a newly designed and milder class of detergent. They have been used primarily in protein structure analysis for membrane protein trapping and stabilization. We have recently demonstrated that APols can be used as an alternative detergent for proteome extraction and digestion, to achieve a "One-stop" single-tube workflow for proteomics. In this workflow, APols are removed by precipitation after protein digestion without depleting the digested peptides. Here, we took further advantage of this precipitation characteristic of APols to concentrate proteins from diluted samples. In contrast with tryptic peptides, a decrease in pH leads to the unbiased co-precipitation of APols with proteins, including globular hydrophilic proteins. We demonstrated that this precipitation is a combined effect of acid precipitation and the APols' protein interactions. Also, we have been able to demonstrate that APols-aided protein precipitation works well on diluted samples, such as secretome sample, and provides a rapid method for protein concentration.
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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 | 0.002 | 0.001 |
| 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".