Discrete-to-continuum models for biomedical applications of RNA nanotubes
Bibliographic record
Abstract
RNA macromolecular structures are very important in the currently boosting field of bionanotechnology, including a range of biomedical applications. In order to expand the applications of these RNA nanoclusters obtained from the self assembly of the ribonucleic acid (RNA) building blocks, it is critical to be able to better understand and predict their properties. Therefore, we model the RNA nanotubes of different sizes using molecular dynamics simulations and then study the mechanical properties of such nanotubes with continuum models implemented with the finite element methodology. We present details of our novel discrete-to-continuum models, and explain how the atomistic models in this field can be used to develop the continuum macroscopic models which would allow to calculate elastic properties of RNA nanotubes using the finite element method. By using the elastic constants available for nucleic acids, we demonstrate how to obtain the distribution of the displacement field due to stress along different directions of the RNA nanotube. These new results pave the road to our better understanding of RNA nanotube stability in biomedical applications.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".