Improving the Autofluorescence of Lophira alata Woody Cells via the Removal of Extractives
Bibliographic record
Abstract
The autofluorescence phenomenon is an inherent characteristic of lignified cells. However, in the case of Lophira alata (L. alata), the autofluorescence is nearly imperceptible during occasional fluorescence observations. The aim of this study is to investigate the mechanism behind the quenching of lignin’s autofluorescence in L. alata by conducting associated experiments. Notably, the autofluorescence image of L. alata observed using optical microscopy appears to be quite indistinct. Abundant extractives are found in the longitudinal parenchyma, fibers, and vessels of L. alata. Remarkably, when subjected to a benzene–alcohol extraction treatment, the autofluorescence of L. alata becomes progressively enhanced under a fluorescence microscope. Additionally, UV–Vis absorption spectra demonstrate that the extractives derived from L. alata exhibit strong light absorption within the wavelength range of 200–500 nm. This suggests that the abundant extractives in L. alata are probably responsible for the autofluorescence quenching observed in the cell walls. Moreover, the presence and quantity of these extractives have a significant impact on the fluorescence intensity of lignin in wood, resulting in a significant decrease therein. In future studies, it would be interesting to explore the role of complex compounds such as polyphenols or terpenoids, which are present in the abundant extractives, in interfering with the fluorescence quenching of lignin in L. alata.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".