Self-assembly/disassembly hysteresis of nanoparticles composed of marginally soluble, short elastin-like polypeptides
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Elastin-like polypeptides (ELPs) are a fascinating biomaterial that has undergone copious development for a variety of therapeutic applications including as a nanoscale drug delivery vehicle. A comprehensive understanding of ELP self-assembly is lacking and this knowledge gap impedes the advancement of ELP-based biomaterials into the clinical realm. The systematic examination of leucine-containing ELPs endeavors to expand existing knowledge about fundamental assembly-disassembly behaviours. RESULTS: It was observed that these marginally soluble, short ELPs tend to behave consistently with previous observations related to assembly-related ELP phase transitions but deviated in their disassembly. It was found that chain length, concentration and overall sequence hydrophobicity may influence the irreversible formation of sub-micron particles as well as the formation of multi-micron scale, colloidally unstable aggregates. Amino acid composition affected surface charge and packing density of the particles. Particle stability upon dilution was found to vary depending upon chain length and hydrophobicity, with particles composed of longer and/or more hydrophobic ELPs being more resistant to disassembly upon isothermal dilution. CONCLUSIONS: Taken together, these results suggest marginally soluble ELPs may self-assemble but not disassemble as expected and that parameters including particle size, zeta potential and dilution resistance would benefit from widespread systematic evaluations. This information has the potential to reveal novel preparation methods capable of expanding the utility of all existing ELP-based biomaterials.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 it