Bioactive Natural Products from Plants and Biotechnological Approaches for their Production
Bibliographic record
Abstract
Bioactive natural products are economically important as drugs, fragrances, pigments, food additives and pesticides. The biotechnological tools are important to select, multiply, improve and analyze medicinal plants for production of such products. The utilization of medicinal plant cells for the production of natural or recombinant compounds of commercial interest has gained increasing attention over the past decades. Plant tissue culture systems are possible source of valuable medicinal compounds, fragrances and colorants, which cannot be produced by microbial cells or chemical synthesis. In vitro production of bioactive natural products in plant cell suspension culture has been reported from various medicinal plants and bioreactors are the key step towards commercial production. Genetic transformation is a powerful tool for enhancing the productivity of novel products; especially by Agrobacterium tumefacians. Combinatorial biosynthesis is another approach in the generation of novel natural products and for the production of rare and expensive natural products. Recent advances in the molecular biology, enzymology and bioreactor technology of plant cell culture suggest that these systems may become a viable source of important secondary metabolites. Genetic fingerprinting could be a powerful tool in the field of medicinal plants to be used for correct germplasm identification. In addition, when linked to emerging tools such as metabolomics and proteomics, providing fingerprints of the plant's metabolites or protein composition, it gives data on phenotypic variation, caused by growth conditions or environmental factors, and also yield data on the genes involved in the biosynthesis. DNA profiling techniques like DNA microarrays serve as suitable high throughput tools for the simultaneous analysis of multiple genes and analysis of gene expression that becomes necessary for providing clues about regulatory mechanisms, biochemical pathways and broader cellular functions. New and powerful tools in functional genomics can be used in combination with metabolomics to elucidate biosynthetic pathways of natural products.
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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 | 0.001 |
| 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 | 0.001 | 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".