A critique on the structural analysis of lignins and application of novel tandem mass spectrometric strategies to determine lignin sequencing
Bibliographic record
Abstract
This review is devoted to the application of MS using soft ionization methods with a special emphasis on electrospray ionization, atmospheric pressure photoionization and matrix-assisted laser desorption/ionization MS and tandem MS (MS/MS) for the elucidation of the chemical structure of native and modified lignins. We describe and critically evaluate how these soft ionization methods have contributed to the present-day knowledge of the structure of lignins. Herein, we will introduce new nomenclature concerning the chemical state of lignins, namely, virgin released lignins (VRLs) and processed modified lignins (PML). VRLs are obtained by liberation of lignins through degradation of vegetable matter by either chemical hydrolysis and/or enzymatic hydrolysis. PMLs are produced by subjecting the VRL to a series of further chemical transformations and purifications that are likely to alter their original chemical structures. We are proposing that native lignin polymers, present in the lignocellulosic biomass, are not made of macromolecules linked to cellulose fibres as has been frequently reported. Instead, we propose that the lignins are composed of vast series of linear related oligomers, having different lengths that are covalently linked in a criss-cross pattern to cellulose and hemicellulose fibres forming the network of vegetal matter. Consequently, structural elucidation of VRLs, which presumably have not been purified and processed by any other type of additional chemical treatment and purification, may reflect the structure of the native lignin. In this review, we present an introduction to a MS/MS top-down concept of lignin sequencing and how this technique may be used to address the challenge of characterizing the structure of VRLs. Finally, we offer the case that although lignins have been reported to have very high or high molecular weights, they might not exist on the basis that such polymers have never been identified by the mild ionizing techniques used in modern MS.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".