Application of Time-of-Flight-Secondary\nIon Mass Spectrometry\nfor 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)\nis a\nsurface analysis technique that is herein demonstrated to be a viable\ntool for the detection of enzyme activity on solid substrates. Proof-of-principle\nexperiments are presented that utilize commercial cellulase and laccase\nenzymes, which are known to modify major polymeric components of wood\n(i.e., cellulose and lignin, respectively). Enzyme activity is assessed\nthrough principle component analysis (PCA) as well as through peak\nratios intended to measure selective enzymatic wood degradation. Spectral\nreproducibility of the complex wood substrates is found to be within\n5% relative standard deviation (RSD), allowing for relative quantification\nof changes in wood composition. Procedures are also presented to identify\nand avoid the influence of mass interferences from protein adsorption\nby the enzyme solutions. The activity of a cellulase cocktail is clearly\nevident through the TOF-SIMS spectra and is supported by high-pressure\nliquid chromatography (HPLC) measurements of sugar release and by\ncomplementary X-ray photoelectron spectroscopy (XPS) measurements\nof the wood surfaces. Laccase activity, which is mediated through\nsmall organic molecules, can be detected in the TOF-SIMS spectra through\na decrease in G and S lignin peaks. This work has positive implications\nfor the development of qualitative, high-throughput screening assays\nfor 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) | 0.010 | 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