Temporospatial Flavonoids Metabolism Variation in Ginkgo biloba Leaves
Bibliographic record
Abstract
Ginkgo ( Ginkgo biloba L.) is a high-value medicinal tree species characterized by its flavonoids beneficial effects that are abundant in leaves. We performed a temporospatial comprehensive transcriptome and metabolome dynamics analyses of clonally propagated Ginkgo plants at four developmental stages (time: May to August) across three different environments (space) to unravel leaves flavonoids biosynthesis variation. Principal component analysis revealed clear gene expression separation across samples from different environments and leaf-developmental stages. We found that flavonoid-related metabolism was more active in the early stage of leaf development, and the content of total flavonoid glycosides and the expression of some genes in flavonoid biosynthesis pathway peaked in May. We also constructed a co-expression regulation network and identified eight GbMYB s and combining with other TF genes (3 GbERF s, 1 GbbHLH , and 1 GbTrihelix ) positively regulated the expression of multiple structural genes in the flavonoid biosynthesis pathway. We found that part of these GbTF s (Gb_11316, Gb_32143, and Gb_00128) expressions was negatively correlated with mean minimum temperature and mean relative humidity, while positively correlated with sunshine duration. This study increased our understanding of the molecular mechanisms of flavonoids biosynthesis in Ginkgo leaves and provided insight into the proper production and management of Ginkgo commercial plantations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 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".