Modeling enzymatic hydrolysis of lignocellulosic substrates using fluorescent confocal microscopy II: Pretreated biomass
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Bibliographic record
Abstract
In this study, we extend imaging and modeling work that was done in Part I of this report for a pure cellulose substrate (filter paper) to more industrially relevant substrates (untreated and pretreated hardwood and switchgrass). Using confocal fluorescence microscopy, we are able to track both the structure of the biomass particle via its autofluorescence, and bound enzyme from a commercial cellulase cocktail supplemented with a small fraction of fluorescently labeled Trichoderma reseii Cel7A. Imaging was performed throughout hydrolysis at temperatures relevant to industrial processing (50°C). Enzyme bound predominantly to areas with low autofluorescence, where structure loss and lignin removal had occurred during pretreatment; this confirms the importance of these processes for successful hydrolysis. The overall shape of both untreated and pretreated hardwood and switchgrass particles showed little change during enzymatic hydrolysis beyond a drop in autofluorescence intensity. The permanence of shape along with a relatively constant bound enzyme signal throughout hydrolysis was similar to observations previously made for filter paper, and was consistent with a modeling geometry of a hollowing out cylinder with widening pores represented as infinite slits. Modeling estimates of available surface areas for pretreated biomass were consistent with previously reported experimental results.
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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