The Internal Structure of the Velvet Worm Projectile Slime: A Small‐Angle Scattering Study
Bibliographic record
Abstract
For prey capture and defense, velvet worms eject an adhesive slime which has been established as a model system for recyclable complex liquids. Triggered by mechanical agitation, the liquid bio-adhesive rapidly transitions into solid fibers. In order to understand this mechanoresponsive behavior, here, the nanostructural organization of slime components are studied using small-angle scattering with neutrons and X-rays. The scattering intensities are successfully described with a three-component model accounting for proteins of two dominant molecular weight fractions and nanoscale globules. In contrast to the previous assumption that high molecular weight proteins-the presumed building blocks of the fiber core-are contained in the nanoglobules, it is found that the majority of slime proteins exist freely in solution. Only less than 10% of the slime proteins are contained in the nanoglobules, necessitating a reassessment of their function in fiber formation. Comparing scattering data of slime re-hydrated with light and heavy water reveals that the majority of lipids in slime are contained in the nanoglobules with homogeneous distribution. Vibrating mechanical impact under exclusion of air neither leads to formation of fibers nor alters the bulk structure of slime significantly, suggesting that interfacial phenomena and directional shearing are required for fiber formation.
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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".