Self-healing silk from the sea: role of helical hierarchical structure in<i>Pinna nobilis</i>byssus mechanics
Bibliographic record
Abstract
The byssus fibers of Mytilus mussel species have become an important role model in bioinspired materials research due to their impressive properties (e.g. high toughness, self-healing); however, Mytilids represent only a small subset of all byssus-producing bivalves. Recent studies have revealed that byssus from other species possess completely different protein composition and hierarchical structure. In this regard, Pinna nobilis byssus is especially interesting due to its very different morphology, function and its historical use for weaving lightweight golden fabrics, known as sea silk. P. nobilis byssus was recently discovered to be comprised of globular proteins organized into a helical protein superstructure. In this work, we investigate the relationships between this hierarchical structure and the mechanical properties of P. nobilis byssus threads, including energy dissipation and self-healing capacity. To achieve this, we performed in-depth mechanical characterization, as well as tensile testing coupled with in situ X-ray scattering. Our findings reveal that P. nobilis byssus, like Mytilus, possesses self-healing and energy damping behavior and that the initial elastic behavior of P. nobilis byssus is due to stretching and unraveling of the previously observed helical building blocks comprising the byssus. These findings have biological relevance for understanding the convergent evolution of mussel byssus for different species, and also for the field of bio-inspired materials.
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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".