Electrophoresis of Composite Molecular Objects. 2. Competition between Sieving and Frictional Effects in Polymer Solutions
Bibliographic record
Abstract
We previously showed that labeling one end of single-stranded DNA molecules with a neutral label like streptavidin increases the interband separation of these hybrid DNA molecules when they are electrophoresed in denaturing cross-linked polyacrylamide gels. This separation process is called trapping electrophoresis because the dynamical properties of the analytes are strongly affected by random steric trapping in the gel. End-labeled ssDNA molecules can also be electrophoretically separated in free solution. This process is called end-labeled free solution electrophoresis, and the separation is then due to the extra hydrodynamic friction provided by the streptavidin label. In this article, we present a study of the capillary electrophoresis of DNA molecules end-labeled with streptavidin in the presence of non-cross-linked polymer solutions ranging from semidilute to ultradilute conditions. In the semidilute limit, sieving interactions dominate, and small DNA molecules move faster than larger ones. In the ultradilute limit, however, we recover free-solution-like separations where small molecules are more retarded than larger ones. We also observe a fascinating transition between these two regimes, for intermediate polymer concentrations and DNA sizes, where the competition between trapping, sieving, and frictional effects leads to nonmonotonic mobility−size relationships. Our theoretical analysis suggests a universal relationship between the mobility of labeled and unlabeled DNA molecules in all electrophoretic conditions.
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 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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".