A Tripeptide-Stabilized Nanoemulsion of Oleic Acid
Bibliographic record
Abstract
We describe a method to produce a nanoemulsion composed of an oleic acids-Pt(II) core and a lysine-tyrosine-phenylalanine (KYF) coating (KYF-Pt-NE). The KYF-Pt-NE encapsulates Pt(II) at 10 wt. %, has a diameter of 107 ± 27 nm and a negative surface charge. The KYF-Pt-NE is stable in water and in serum, and is biologically active. The conjugation of a fluorophore to KYF allows the synthesis of a fluorescent nanoemulsion that is suitable for biological imaging. The synthesis of the nanoemulsion is performed in an aqueous environment, and the KYF-Pt-NE forms via self-assembly of a short KYF peptide and an oleic acids-platinum(II) conjugate. The self-assembly process depends on the temperature of the solution, the molar ratio of the substrates, and the flow rate of the substrate addition. Crucial steps include maintaining the optimal stirring rate during the synthesis, permitting sufficient time for self-assembly, and pre-concentrating the nanoemulsion gradually in a centrifugal concentrator.
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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) | 0.001 | 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".