Phytochemical profiling in single plant cell by high performance liquid chromatography-mass spectrometry
Bibliographic record
Abstract
Phytochemicals are essential secondary plant metabolites which play important roles in the areas of plant biochemistry, pharmacy and medical science because of their significant bioactivities. Conventional analysis of phytochemicals in plants needs a complex combination of different extraction and separation steps. Here a simple and universal method for profiling phytochemicals in a single plant cell was demonstrated based on high performance liquid chromatography-mass spectrometry. Single purple and colorless cell samples (about 15 μm in size) found in the outer layer of a young stem of Forsythia suspensa, just inside the cuticles were collected and transferred by glass micropipettes from cell monolayers. At least 30 peaks were separated and detected, and 24 of these peaks were identified. Apart from several common plant metabolites in high abundance, like polysaccharides and amino acids, 9 phytochemicals that have special bioactivities in this plant and in medical treatment were successfully detected. Phytochemical differences between these two kinds of cells were also distinguished which was applied to investigate the heterogeneity of cells from different parts of plants and the dependency of important plant bioprocesses on phytochemical changes.
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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".