Changes in the Metabolome of Picea balfouriana Embryogenic Tissues That Were Linked to Different Levels of 6-BAP by Gas Chromatography-Mass Spectrometry Approach
Bibliographic record
Abstract
Embryogenic cultures of Picea balfouriana, which is an important commercial species for reforestation in Southern China, easily lose their embryogenic ability during long-term culture. Embryogenic tissue that proliferated at lower concentrations (3.6 μM and 2.5 μM) of 6-benzylaminopurine (6-BAP) were more productive, and generated 113 ± 6 and 89 ± 3 mature embryos per 100 mg embryogenic tissue, respectively. A metabolomic approach was used to study the changes in metabolites linked to embryogenic competence related to three different 6-BAP concentrations (2.5 μM, 3.6 μM, and 5 μM). A total of 309 compounds were obtained, among which 123 metabolites mapped to Kyoto Encyclopedia of Genes and genomes (KEGG) pathways. The levels of 35 metabolites were significantly differentially regulated among the three 6-BAP treatments, and 32 metabolites differed between the 2.5 μM and 5 μM treatments. A total of 17 metabolites appeared only once among the three comparisons. The combination of a score plot and a loading plot showed that in the samples with higher embryogenic ability (3.6 μM and 2.5 μM), up-regulated metabolites were mostly amino acids and down-regulated metabolites were mostly primary carbohydrates (especially sugars). These results suggested that 6-BAP may influence embryogenic competence by nitrogen metabolism, which could cause an increase in amino acid levels and higher amounts of aspartate, isoleucine, and leucine in tissues with higher embryogenic ability. Furthermore, we speculated that 6-BAP may affect the amount of tryptophan in tissues, which would change the indole-3-acetic acid levels and influence the embryogenic ability.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".