Bibliographic record
Abstract
To realize the economical production of ethanol and other bio-based chemicals from lignocellulosic biomass by consolidated bioprocessing (CBP), various cellulases from different sources were tested to improve the level of cellulase secretion in the yeast Saccharomyces cerevisiae by screening an optimal translational fusion partner (TFP) as both a secretion signal and fusion partner. Among them, four indispensable cellulases for cellulose hydrolysis, including Chaetomium thermophilum cellobiohydrolase (CtCBH1), Chrysosporium lucknowense cellobiohydrolase (ClCBH2), Trichoderma reesei endoglucanase (TrEGL2), and Saccharomycopsis fibuligera β-glucosidase (SfBGL1), were identified to be highly secreted in active form in yeast. Despite variability in the enzyme levels produced, each recombinant yeast could secrete approximately 0.6-2.0 g/L of cellulases into the fermentation broth. The synergistic effect of the mixed culture of the four strains expressing the essential cellulases with the insoluble substrate Avicel and several types of cellulosic biomass was demonstrated to be effective. Co-fermentation of these yeast strains produced approximately 14 g/L ethanol from the pre-treated rice straw containing 35 g/L glucan with 3-fold higher productivity than that of wild type yeast using a reduced amount of commercial cellulases. This process will contribute to the cost-effective production of bioenergy such as bioethanol and biochemicals from cellulosic biomass.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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; both teacher heads agree on what is shown here.
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".