Exploiting Favorable Silicone—Protein Interactions: Stabilization against Denaturation at Oil—Water Interfaces
Bibliographic record
Abstract
Water-in-silicone oil emulsions were prepared using either silicone surfactants containing pendant polyethylene oxide (PEO) side chains (DC3225C) or terminal Si(OEt) 3 groups. The aqueous solutions contained either the enzymes α-chymotrypsin or alkaline phosphatase (DC3225C emulsions) or the surface active protein human serum albumin (TES-PDMS emulsions). Labelled albumin was shown to reside almost exclusively at the oil/water interface in the emulsion. The activity of the enzymes was followed over time by first breaking the emulsion and then performing standard enzyme assays on the aqueous phase. The enzymes were observed to undergo denaturation, as measured by reduced enzymatic activity, as a result of the mechanical energy used to make and break the emulsion. However, the rate of enzyme denaturation in the emulsions was lower than that observed for the aqueous control which had not been exposed to silicone. These results are consistent with favorable interactions between PEO or Si(OEt) 3 groups (or hydrolytic byproducts in the latter case) and the proteins that not only stabilize the interface of a water-in-oil emulsion, but also the protein, which normally would otherwise undergo efficient denaturation in the presence of silicone oil.
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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 | 0.000 | 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) | 0.002 | 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".