Characteristics of Cellulose Nanofibrils from Transgenic Trees with Reduced Expression of Cellulose Synthase Interacting 1
Bibliographic record
Abstract
Cellulose nanofibrils can be derived from the native load-bearing cellulose microfibrils in wood. These microfibrils are synthesized by a cellulose synthase enzyme complex that resides in the plasma membrane of developing wood cells. It was previously shown that transgenic hybrid aspen trees with reduced expression of CSI1 have different wood mechanics and cellulose microfibril properties. We hypothesized that these changes in the native cellulose may affect the quality of the corresponding nanofibrils. To test this hypothesis, wood from wild-type and transgenic trees with reduced expression of CSI1 was subjected to oxidative nanofibril isolation. The transgenic wood-extracted nanofibrils exhibited a significantly lower suspension viscosity and estimated surface area than the wild-type nanofibrils. Furthermore, the nanofibril networks manufactured from the transgenics exhibited high stiffness, as well as reduced water uptake, tensile strength, strain-to-break, and degree of polymerization. Presumably, the difference in wood properties caused by the decreased expression of CSI1 resulted in nanofibrils with distinctive qualities. The observed changes in the physicochemical properties suggest that the differences were caused by changes in the apparent nanofibril aspect ratio and surface accessibility. This study demonstrates the possibility of influencing wood-derived nanofibril quality through the genetic engineering of trees.
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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".