Bioactives from marine resources as natural health products: A review.
Bibliographic record
Abstract
The oceans are a rich source of a myriad of structurally different and unique natural products that are mainly found in invertebrates, with potential applications in different disciplines. Microbial infection and cancer are the leading causes of death worldwide. The discovery of new sources of therapy for microbial infections is an urgent requirement owing to the emergence of pathogenic microorganisms that are resistant to existing therapies. Marine bioactives have been demonstrated to be promising sources for the discovery and development of novel antimicrobial and anticancer compounds. Several marine compounds are confirmed to have antibacterial effects, and most marine-based antifungal compounds are cytotoxic. Numerous antitumor marine natural products, derived mainly from not only sponges or molluscs but also bryozoans and cyanobacteria, exhibit potent antimitotic activity. In addition, marine biodiversity offers some possible leads or new drugs to treat human immunodeficiency virus. A majority of marine-derived drugs are currently in clinical trials or under preclinical evaluation. Furthermore, marine-based drugs approved by the US Food and Drug Administration are available in the market. This review summarizes the sources, mechanisms of action, and potential utilization of marine natural products such as peptides, alkaloids, polyketides, polyphenols, terpenoids, and sterols as antifungal, antibacterial, antiviral, and anticancer compounds. SIGNIFICANCE STATEMENT: Utilization of natural bioactive compounds from marine resources is a crucial advancement in the field of health care and wellness. A valuable source of potent compounds with therapeutic potential exists in marine organisms. These bioactives offer promising medicinal value for disease prevention, promoting overall wellbeing, and advancing pharmaceutical and nutraceutical industries. Their sustainable extraction and utilization not only benefit human health but also contribute to the conservation of marine ecosystems. This transformative approach enhances global health outcomes and sustainability.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".