Dual Mechanism of <i>Amphiroa anceps</i>: Antiangiogenic and Anticancer Effects in Skin Cancer
Bibliographic record
Abstract
Skin cancer is diagnosed usually at the last stage and the available conventional treatments are costly and have various side-effects. It is therefore necessary to design a biocompatible alternative treatment approach. In our present study, the liposomal formulation of marine red algae Amphiroa anceps is investigated for its anticancer activity against skin cancer. The aqueous extract (HA) and the liposomal formulated aqueous extract (NHA) of A. anceps are characterized using Raman spectroscopy, high-performance liquid chromatography (HPLC) and scanning electron microscopy (SEM). SEM reveals the size of NHA to be around 150-230 nm. In HPLC, two prominent peaks at the retention time of 5.233 min and 5.775 min are observed. NHA exhibits anticancer activity in skin cancer cells (A375) dose-dependently, and the cell viability 100 µg/mL is 16% ± 2%. The in vitro biocompatibility assays using fibroblast cell viability and haemolysis assay, show that the NHA is safe and highly biocompatible. A step forward, the Chorioallantoic Membrane Assay assay reveals HA and NHA have anti-angiogenesis activity. Our study elucidates that NHA induces anticancer activity by cell necrosis and reducing new blood vessel formation, and can be a safe and promising therapeutic agent for cancer management.
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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) | 0.000 | 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) | 0.001 | 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 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".