Promising Phytoconstituents in Antiangiogenesis Drug Development
Bibliographic record
Abstract
Angiogenesis, the process of forming new blood vessels from existing ones, is crucial in both physiological and pathological conditions, such as tumor growth, metastasis, and inflammatory disorders. Targeting angiogenesis has emerged as a promising therapeutic strategy. Recent research has increasingly focused on the role of bioactive components found in food in regulating angiogenesis, although there are certain limitations. This review provides a comprehensive examination of the origins, composition, pharmacological activities, and mechanisms of action of these components in medicinal foods, reflecting the growing intersection of medicine and nutrition. The goal is to aid in preventing angiogenesis-related complications and fostering healthier habits. The insights offered in this review aim to advance the development of effective, low-toxicity antiangiogenic drugs. Additionally, there has been a notable rise in interest in plant-derived compounds with antiangiogenic properties. This review investigates the potential of phytoconstituents from plants as drug candidates targeting angiogenesis, exploring their mechanisms of action, the research conducted thus far, and the challenges associated with transitioning these compounds into clinical applications.
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 | 0.000 |
| 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".