Enhanced biochemical process for purifying xylo-oligosaccharides from pre-hydrolysis liquor
Bibliographic record
Abstract
Abstract Background Xylo-oligosaccharides (XOS) are promising biomass-derived chemicals that can be widely used in preparing medicines, food additives, and industrial chemicals. The pre-hydrolysis liquor (PHL) produced in the kraft-based dissolving pulp production process is rich in hemicelluloses and especially in XOS/xylan. Results In this study, a sustainable sequential process that included calcium hydroxide (CH), simultaneous laccase and xylanase (LX) and activated carbon (AC) treatments was proposed for more efficient recovery of XOS/xylan from PHL. Overall, the concentration of lignin, furfural and xylosugars decreased by 81.7 wt.%, 100 wt.% and 5.1 wt.%, respectively, but XOS concentration was increased by 36.6 wt.%. More importantly, the 2D-HSQC NMR and FT-IR were used in understanding the structure of sugar and lignin components in each step of the process and in the final products. The CH treatment mainly altered the chemical structure of XOS due to the release of acetyl groups, and downstream treatment steps have insignificant effect on XOS structures. Also, lignin carbohydrate complexes (LCC, i.e. PhGlc3) minimally existed in the purified XOS. The GPC and DSC results revealed that the molecular weight of the extracted lignin was 1768 ~ 2532 g/mol and it had a wide glass transition temperature (Tg) range (63 ~ 115 °C). Conclusions The results confirmed that a combination of sequentially treating PHL with calcium hydroxide (CH), simultaneous laccase and xylanase (LX) and activated carbon (AC) was effective in removing lignin and concentrating XOS in the PHL.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".