Force-fluctuation physics of confined DNA: probing the breakdown of the Marko-Siggia law
Bibliographic record
Abstract
Introduction: The study of polymers in nanofluidic systems such as nanopores and nanochannels is an important avenue of research in the physical and life sciences today. Complex nanofluidic devices containing varying topography are ideal for quantifying the behaviour of polymers under confinement. This study investigates the Marko-Siggia force-extension relationship under confinement. We measure the transverse fluctuations of deoxyribonucleic acid (DNA) confined between two pits in a nanofluidic slit to measure the potential breakdown of this model. Methods: We took images of fluorescently tagged single DNA molecules in the nanopit array with video- fluorescence microscopy and analyzed the standard deviation of the peak position along the direction of the molecular extension. Results: We were able to measure the parabolic relation between position and the strength of transverse fluctuations. By examining the peak variance as a function of slit height, our results indicate that the two dimensional version of the force-fluctuation relationship may be appropriate in the limit of strong confinement. However, we could not consistently measure the absolute length of the DNA stretched between two pits, which prevented us from fully exploring the force-extension and force-fluctuation relationships of confined DNA. Conclusions: These experiments further demonstrate that nanofluidic confinement serves as a useful tool for testing the extreme properties of polymers, and our results suggest further investigation into the breakdown of the Marko-Siggia force law.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".