Heat-activated growth of metastable and length-defined DNA fibers expands traditional polymer assembly
Bibliographic record
Abstract
Biopolymers such as nucleic acids and proteins exhibit dynamic backbone folding, wherein site-specific intramolecular interactions determine overall structure. Proteins then hierarchically assemble into supramolecular polymers such as microtubules, that are robust yet dynamic, constantly growing or shortening to adjust to cellular needs. The combination of dynamic, energy-driven folding and growth with structural stiffness and length control is difficult to achieve in synthetic polymer self-assembly. Here we show that highly charged, monodisperse DNA-oligomers assemble via seeded growth into length-controlled supramolecular fibers during heating; when the temperature is lowered, these metastable fibers slowly disassemble. Furthermore, the specific molecular structures of oligomers that promote fiber formation contradict the typical theory of block copolymer self-assembly. Efficient curling and packing of the oligomers - or 'curlamers' - determine morphology, rather than hydrophobic to hydrophilic ratio. Addition of a small molecule stabilises the DNA fibers, enabling temporal control of polymer lifetime and underscoring their potential use in nucleic-acid delivery, stimuli-responsive biomaterials, and soft robotics.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".