In vitro antioxidant, antibacterial, cytotoxic, and epigenetic screening of crude extract and fractions of the marine sponge Neopetrosia exigua from Mauritius waters
Bibliographic record
Abstract
The marine sponge Neopetrosia exigua is known as a goldmine of novel compounds, yet its pharmacological activities remain poorly characterised. Herein, this study investigates the bioactivities of N. exigua collected from Mauritius waters. The crude extract (dichloromethane: methanol), hexane, ethyl acetate and aqueous fractions obtained from N. exigua were subjected to in vitro antioxidant assays. Their antibacterial activities were evaluated using the broth microdilution method to determine the minimum inhibitory concentration (MIC). The cytotoxic and epigenetic activities were further screened using the MTT assay and a cell-based image system that measures de-repression of a silenced Green Fluorescent Protein (GFP) reporter gene, respectively. Significantly higher antioxidant activity was recorded for the ethyl acetate fraction as demonstrated by its significant ferric reducing antioxidant power, radical scavenging, and metal chelating activities relative to control (p < 0.05). The best antibacterial profile was presented by the ethyl acetate fraction against Cutibacterium acnes (MIC: 0.039 mg/ml), Streptococcus mutans (MIC: 0.078 mg/ml) and Mycobacterium smegmatis (MIC: 0.313 mg/ml). Similarly, the fraction displayed significant cytotoxicity against the human liposarcoma SW872 cells with IC50 value of 44.34 ± 2.64 µg/ml and GFP re-activation capacity of 43.79 ± 3.19 % (p < 0.05). This work conveys interesting data on the antioxidant, antimicrobial, and anticancer properties of N. exigua. In particular, this study indicates the promising potential of N. exigua as a reservoir of epigenetically active agents that can modulate transcription of silenced genes involved in carcinogenesis. Hence, further investigations to isolate the active constituents is actively warranted.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".