Amplifying the Macromolecular Crowding Effect Using Nanoparticles
Bibliographic record
Abstract
The melting temperature (T(m)) of DNA is affected not only by salt but also by the presence of high molecular weight (MW) solutes, such as polyethylene glycol (PEG), acting as a crowding agent. For short DNAs in a solution of low MW PEGs, however, the change of excluded volume upon melting is very small, leading to no increase in T(m). We demonstrate herein that by attaching 12-mer DNAs to gold nanoparticles, the excluded volume change was significantly increased upon melting, leading to increased T(m) even with PEG 200. Larger AuNPs, higher MW PEGs, and higher PEG concentrations show even larger effects in stabilizing the DNA. This study reveals a unique and fundamental feature at nanoscale due to geometric effects. It also suggests that weak interactions can be stabilized by a combination of polyvalent binding and the enhanced macromolecular crowding effect using nanoparticles.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".