Molecular Composition of Leaves and Stems of Genetically Modified Bt and Near‐Isogenic Non‐Bt Maize—Characterization of Lignin Patterns
Bibliographic record
Abstract
Transformation of crops, including maize (Zea mays L.), with the cry1Ab gene from Bacillus thuringiensis to combat lepidopteran pests results in pleiotropic effects regarding lignin biosynthesis. Lignin patterns in stems and leaves of two genetically modified Bt-maize varieties (Novelis T and Valmont T) were studied along with their non-Bt near-isolines (Nobilis and Prelude, respectively). Molecular-level based thermochemolysis using tetramethylammonium hydroxide (TMAH) in combination with gas chromatography-mass spectrometry (GC-MS) was used to quantitate the total lignin contents and to identify monomeric lignin subunits including p-hydroxyphenyl (P), guaiacyl (G), and syringyl (S) moieties. The results were supplemented and confirmed by cupric oxide oxidation. The stems of the transgenic lines had higher concentrations of total lignin than the respective isogenic lines: Valmont T/Prelude by 18% and Novelis T/Nobilis by 28%. In contrast, differences in the total lignin concentration of leaves between the transgenic and the respective near-isogenic lines were marginal. There were significant modifications in the ratio of p-hydroxyphenyl/guaiacyl/syringyl molecular marker units of stem lignin between transgenic and isogenic lines. The guaiacyl units (in particular the G18 marker) accounted chiefly for the higher total lignin contents in the transgenic lines. The leaf lignin patterns did not show significant differences in molecular markers between isogenic and transgenic lines. TMAH-induced thermochemolysis--conducted in both the on-line and off-line modes--provided detailed information on the molecular composition of lignin, thus proving superior to the established "wet chemistry" methods of lignin determination.
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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".