The Accessible Cellulose Surface Influences Cellulase Synergism during the Hydrolysis of Lignocellulosic Substrates
Bibliographic record
Abstract
Effective enzymatic hydrolysis of insoluble cellulose requires the synergistic action of a suite of cellulase components. Most previous studies have only assessed cellulase synergism on model cellulosic substrates. When the actions of individual and combinations of cellulases (Cel7A, Cel6A, Cel7B, Cel5A) were assessed on various pretreated lignocellulosic substrates, Cel7A was shown to be the major contributor to overall cellulose hydrolysis, with the other enzymes synergistically enhancing its hydrolytic efficiency, at least partially, by facilitating Cel7A desorption (assessed by a double-sandwich enzyme-linked immunosorbent assay). When the influences of various substrate physicochemical characteristics on the effectiveness of enzyme synergism were assessed, a strong relationship was observed between cellulose accessibility (as determined by the cellulose binding module technique) and the degree of synergism, with greater synergy observed on the more disorganized/accessible cellulose surface.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".