Simultaneous Phase Transition of ELP Tagged Molecules and Free ELP: An Efficient and Reversible Capture System
Bibliographic record
Abstract
In this paper, we demonstrate proof-of-principle for a method that allows selective recovery of molecules present at very low concentrations in complex mixtures. The method makes use of an elastin-like polypeptide (ELP) as a coaggregant for the capture of an ELP tagged recombinant protein present at concentrations as low as 10 pM, with a recovery higher than 90%. This coaggregation process was found to be independent of the concentration, at least up to 10 pM concentration of the ELP tagged protein. The coaggregation process is highly specific as was demonstrated by spiking crude cell lysate with the ELP tagged recombinant protein to a final concentration of 1 nM and recovering more than 80% of it to a high level of purity. The method should be particularly useful for high-throughput proteomic studies, where small amounts of poorly expressed proteins could be recovered for analysis by mass spectrometry. In a more general context, the concept presented in this paper provides a method that is highly efficient, specific, and fully reversible, which should render it useful in areas other than recombinant protein purification.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".