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Record W4382500930 · doi:10.1016/j.jafr.2023.100621

Green seaweed Caulerpa racemosa - Chemical constituents, cytotoxicity in breast cancer cells and molecular docking simulation

2023· article· en· W4382500930 on OpenAlexaff
Grace Sanger, Djuhria Wonggo, Nurmeilita Taher, Verly Dotulong, Aurielle Annalicia Setiawan, Happy Kurnia Permatasari, Sidik Maulana, Fahrul Nurkolis, Apollinaire Tsopmo, Bonglee Kim

Bibliographic record

VenueJournal of Agriculture and Food Research · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSeaweed-derived Bioactive Compounds
Canadian institutionsCarleton University
FundersUniversitas Sam RatulangiUniversitas Gadjah Mada
KeywordsDPPHEthyl acetateChemistryPhytochemicalCytotoxicityAntioxidantTraditional medicineMTT assayChromatographyBiochemistryCell growthIn vitroMedicine

Abstract

fetched live from OpenAlex

Marine and terrestrial organisms are rich in chemical compounds with medicinal and pharmacological properties, including antitumor agents for chemoprevention. Caulerpa racemosa, a marine species, is a potential source of novel compounds with therapeutic agents for human cancer. This study aimed to determine the anticancer activity of C. racemosa extracts in breast cancer cells, identify compounds, and determine the mechanism using computational models. Seaweed (C. racemosa) was taken from North Sulawesi, Indonesia; Followed by authentication and identification according to the previously published protocol and extracted with three different solvent: hexane, ethyl acetate, and ethanol. C. racemosa were evaluated for cytotoxicity against breast cancer MCF-7 cells using MTT (3-(4,5-dimethylthiazol-2-yl)-2-5-diphenyltetrazolium bromide) assay. Antioxidant activities were assessed based on free radical scavenging (2,2-diphenyl-1-picrylhydrazyl (DPPH)) and ferric-reducing antioxidant power (FRAP) assays. The phytochemical constituents were identified with a liquid chromatography-electrospray ionization quadrupole time-of-flight mass spectrometry (LC-ESI-QTOF-MS) system. The interaction of the identified compounds with human epidermal growth factor 2 (HER2) protein was achieved by molecular docking with PyRx-vina application and protein-ligand complex visualization. The hexane extract exhibited the highest cytotoxicity against breast cancer cells, followed by the ethyl acetate and the ethanol extract (IC50 23.7 ± 2.0; 66.7 ± 5.8 and 182.7 ± 14.3 μg/mL). The best antioxidant sample for DPPH was the ethyl acetate extract (IC50 21.5 ± 2.0 μg/mL) while the hexane extract was the most active in the FRAP value (14.5 ± 1.3 μg gallic acid equivalent/g). Data from LC-ESI-QTOF-MS allowed the identification of 21 compounds. The molecular docking study showed that 12 of the compounds could prevent tumors in breast cancer by acting as inhibitors of the anti-apoptotic HER2 protein. C. racemosa has potential in the chemoprevention of breast cancer through its radical scavenging capacity and inhibition of the HER2 protein. More studies are needed to investigate the efficacy of extracts in different models.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.050
GPT teacher head0.317
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations21
Published2023
Admission routes1
Has abstractyes

Explore more

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