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Record W3166246301 · doi:10.21203/rs.3.rs-552319/v1

Comparison of the Interaction Modes Between Cellulase and Bovine Serum Albumin /Lignosulfonate /Polyethylene Glycol in Promoting Lignocellulose Saccharification

2021· preprint· en· W3166246301 on OpenAlexaff
Peipei Wang, Tian Liu, Jiaqi Guo, Yongcan Jin, Huining Xiao, Jiuyou Lin, Junlong Song

Bibliographic record

VenueResearch Square · 2021
Typepreprint
Languageen
FieldEngineering
TopicBiofuel production and bioconversion
Canadian institutionsUniversity of New Brunswick
FundersPriority Academic Program Development of Jiangsu Higher Education InstitutionsNational Natural Science Foundation of ChinaNanjing Forestry University
KeywordsCellulasePolyethylene glycolHydrolysisBovine serum albuminChemistryBiochemistryFood sciencePulp and paper industryChromatographyChemical engineeringEngineering

Abstract

fetched live from OpenAlex

Abstract Background: Bovine serum albumin (BSA), polyethylene glycol (PEG) and lignosulfonate (LS) have been extensively employed as synergistic agents in lignocellulose saccharification, albeit it has not been fully understood how they interact with enzymes from the perspectives of molecular interactions. Herein, we attempted to unveil the promotion mechanisms of BSA, PEG and LS for lignocellulose saccharification from the perspective of their respective interaction with cellulase using Quartz Crystal Microbalance with Dissipation monitoring (QCM-D), Surface Plasmon Resonance (SPR), and Small Angle X-ray Scattering (SAXS) to investigate their respective interaction and the complex formation. In the meanwhile, we compared the effects of adding these additives into the enzymatic hydrolysis of pure cellulose (Avicel) and green liquor-pretreated lignocellulose (GL).Results: The results showed that BSA and LS could bind to cellulase to form complexes, whereas PEG did not. However, PEG had a high affinity to lignin or lignin derivatives. In term for Avicel and GL substrates, the results showed that BSA and PEG promoted the enzymatic hydrolysis of both substrates, while LS had a promoting effect for GL only and inhibited some extent for Avicel. Conclusions: This study showed that synergistic agents of LS, BSA, and PEG have different interaction modes with cellulase. BSA and LS form complexes with cellulase and the formed complexes prevent from nonproductive binding by residue lignin; whereas PEG prevents from nonproductive binding by forming a thin layer on residue lignin which actually serve as steric hindrance. This investigation will help us to understand the sophisticated interactions among the components in the complicated enzymatic system, especially the interactions between enzymes and synergistic agents. It will be helpful in the design and utilization of synergistic additives in the lignocellulose biorefinery process as well.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.078
GPT teacher head0.366
Teacher spread0.288 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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