Physiological and Ecological Mechanisms and Metabolic Pathway Analysis of Active Compound Accumulation in <i>Leonurus japonicus</i> Houtt.
Why this work is in the frame
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Bibliographic record
Abstract
Leonurus japonicus Houtt. is a commonly used medicinal plant in traditional Chinese medicine. It contains many active ingredients, such as alkaloids, flavonoids and diterpenoids, so it is widely used in gynecology, cardiovascular and cerebrovascular diseases, and anti-inflammation, etc. In recent years, multi-omics studies and molecular biology research have gradually clarified how these major active components (such as leonurine, tribulus terephthine, diterpenoids, etc.) accumulate in different organs and under different environments. At the physiological level, some key enzymes (such as ADC, UGT, and SCPL) are very important. The gene clusters they belong to have been amplified and new functions have emerged. These changes have made the synthesis of active ingredients smoother and also given them more obvious accumulation characteristics in plants. Environmental factors can also have an impact, such as pH, climate, soil and geographical location. These conditions can change the supply of substrates and the activity of enzymes, thereby affecting the content of active ingredients. The study of metabolic pathways can not only assist in molecular breeding and more precise cultivation, but also provide a scientific basis for the quality control of medicinal materials and the development of new drugs. In the future, under the perspective of systems biology, integrating multi-omics data and combining it with gene function verification and ecological adaptation research is expected to promote more efficient molecular regulation of the active components of Leonurus japonicus. At the same time, it can also facilitate the sustainable utilization of resources and the modern development of their medicinal value.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 it