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Record W32084907 · doi:10.1089/ind.2014.0019

The Study of Cellulose Structure and Depolymerization Through Single-Molecule Methods

2015· article· en· W32084907 on OpenAlexaff
Markus Rose, Mouhanad Babi, Jose Moran‐Mirabal

Bibliographic record

VenueIndustrial Biotechnology · 2015
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsCellulaseCelluloseDepolymerizationLignocellulosic biomassChemistryBiomass (ecology)Materials scienceChemical engineeringNanotechnologyOrganic chemistryGeology

Abstract

fetched live from OpenAlex

Renewable energy has gained importance due to rising energy demands and diminishing fossil resources. Lignocellulosic biomass, with a core consisting of crystalline cellulose, has the potential to become a renewable source of fermentable sugars for energy production. However, to utilize this resource, biomass has to be broken down through physical, chemical, or enzymatic treatments. The biochemical hydrolysis of cellulose by cellulases offers an economical alternative to hazardous chemicals. Thus, complete knowledge of the molecular interactions between cellulases and cellulose would help to optimize the efficiency of industrial enzyme cocktails. Single-molecule (SM) methods study molecular events by visualizing individual molecules instead of measuring averages, thereby providing a detailed view of nanoscale processes with high spatial and temporal resolution. SM fluorescence microscopy utilizes enzyme and cellulose labeling, along with localization and tracking algorithms, to yield particle or fluorophore positions with nanoscale precision. Similarly, high-speed atomic force microscopy utilizes a high aspect ratio probe that is brought into close proximity and scanned across the sample to visualize the surface topography and its evolution over time. Both SM techniques have been recently applied to the study of cellulase-cellulose interactions and used to probe enzyme-binding orientation, affinity and reversibility, non-catalytic and catalytic surface motion, and the effect of molecular crowding on enzyme mobility. This review aims to showcase SM techniques and how they have been applied to study cellulose structure and cellulose depolymerization by cellulases. While the study of cellulase-cellulose interactions and cellulose depolymerization through SM microscopy is still a young field, these methods have already contributed to our understanding of the nanoscale processes involved in biomass conversion. Further application of SM techniques could elucidate molecular mechanisms involved in enzyme synergism, as well as the molecular changes that take place as cellulose fibrils are converted into soluble sugars.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.021
Threshold uncertainty score0.394

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.099
GPT teacher head0.362
Teacher spread0.263 · 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 teacher head, 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

Citations10
Published2015
Admission routes1
Has abstractyes

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