Application of Time-of-Flight-Secondary Ion Mass Spectrometry for the Detection of Enzyme Activity on Solid Wood Substrates
Why this work is in the frame
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Bibliographic record
Abstract
Time-of-flight-secondary ion mass spectrometry (TOF-SIMS) is a surface analysis technique that is herein demonstrated to be a viable tool for the detection of enzyme activity on solid substrates. Proof-of-principle experiments are presented that utilize commercial cellulase and laccase enzymes, which are known to modify major polymeric components of wood (i.e., cellulose and lignin, respectively). Enzyme activity is assessed through principle component analysis (PCA) as well as through peak ratios intended to measure selective enzymatic wood degradation. Spectral reproducibility of the complex wood substrates is found to be within 5% relative standard deviation (RSD), allowing for relative quantification of changes in wood composition. Procedures are also presented to identify and avoid the influence of mass interferences from protein adsorption by the enzyme solutions. The activity of a cellulase cocktail is clearly evident through the TOF-SIMS spectra and is supported by high-pressure liquid chromatography (HPLC) measurements of sugar release and by complementary X-ray photoelectron spectroscopy (XPS) measurements of the wood surfaces. Laccase activity, which is mediated through small organic molecules, can be detected in the TOF-SIMS spectra through a decrease in G and S lignin peaks. This work has positive implications for the development of qualitative, high-throughput screening assays for enzyme activity on industrially relevant, lignocellulosic substrates.
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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 it