Mistletoe viscin: a hygro- and mechano-responsive cellulose-based adhesive for diverse material applications
Bibliographic record
Abstract
Mistletoe viscin is a natural cellulosic adhesive consisting of hierarchically organized cellulose microfibrils (CMFs) surrounded by a humidity-responsive matrix that enables mechanical drawing into stiff and sticky fibers. Here, we explored the processability and adhesive capacity of viscin and demonstrated its potential as a source material for various material applications, as well as a source for bioinspired design. Specifically, we revealed that viscin fibers exhibit humidity-activated self-adhesive properties that enable "contact welding" into complex 2D and 3D architectures under ambient conditions. We additionally discovered that viscin can be processed into stiff and transparent free-standing films via biaxial stretching in the hydrated state, followed by drying, whereby CMFs align along local stress fields. Furthermore, we determined that viscin adheres strongly to both synthetic materials (metals, plastics, and glass) and biological tissues, such as skin and cartilage. In particular, skin adhesion makes viscin a compelling candidate as a wound sealant, as we further demonstrate. These findings highlight the enormous potential of this hygro- and mechano-responsive fiber-reinforced adhesive for bioinspired and 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 | 0.000 |
| 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".