The effect of proline on the network structure of major ampullate silks as inferred from their mechanical and optical properties
Bibliographic record
Abstract
The silk that orb-weaving spiders produce for use as dragline and for the frame of the web is spun from the major ampullate (MA) glands, and it is renowned for its exceptional toughness. The fibroins that make up MA silk have previously been organized into two major groupings, spidroin-1 and spidroin-2, based largely on differences in amino acid sequence. The most apparent difference between spidroin-1 and spidroin-2 fibroins is the lack of proline in spidroin-1. The MA silk of Araneus diadematus comprises two spidroin-2 fibroins, and is therefore proline-rich, whereas spidroin-1 is preferentially expressed in Nephila clavipes MA silk, and so this silk is proline deficient. Together, these two silks provide a system for testing the consequences of proline-rich and proline-deficient fibroin networks. This study measures the mechanical and optical properties of dry and hydrated Araneus and Nephila MA silks. Since proline acts to disrupt secondary structure, it is hypothesized that the fibroin network of Araneus MA silk will contain less secondary structure than the network of Nephila MA silk. Mechanical and optical studies clearly support this hypothesis. Although the dry properties of these two silks are indistinguishable, there are large differences between the hydrated silks. Nephila silk does not swell upon hydration to the same degree as Araneus silk. In addition, upon hydration, Nephila MA silk retains more of its initial dry stiffness, and retains more molecular order, as indicated by birefringence measurements.
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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) | 0.000 | 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".