MétaCan
Menu
Back to cohort
Record W4212932139 · doi:10.3390/nu14040786

Cancer Cell Inhibiting Sea Cucumber (Holothuria leucospilota) Protein as a Novel Anti-Cancer Drug

2022· article· en· W4212932139 on OpenAlexaff
Ruizhen Ru, Yanzheng Guo, Juanxuan Mao, Zonghe Yu, Wen Huang, Xudong Cao, Huijian Hu, Minjie Meng, Lihong Yuan

Bibliographic record

VenueNutrients · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEchinoderm biology and ecology
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsHaCaTCancerCancer cellBiologyCell culturePharmacologyChemistryGenetics

Abstract

fetched live from OpenAlex

Cancer remains the primary cause of death worldwide. To develop less toxic anti-cancer drugs to relieve the suffering and improve the survival of cancer patients is the major focus in the anti-cancer field. To this end, marine creatures are being extensively studied for their anti-cancer effects, since extracts from at least 10% of the marine organisms have been shown to possess anti-tumor activities. As a classic Chinese traditional medicine, sea cucumbers and compounds extracted from the sea cucumbers, such as polysaccharides and saponins, have recently been shown to exhibit anti-cancer, anti-inflammatory, and anti-oxidant effects. Holothuria leucospilota (H. leucospilota) is a tropical edible sea cucumber species that has been successfully cultivated and farmed in large scales, providing a readily available source of raw materials to support the development of novel marine anti-cancer drugs. However, very few studies have so far been performed on the biological activities of H. leucospilota. In this study, we first investigated the anti-cancer effect of H. leucospilota protein on three cancer cell lines (i.e., HepG2, A549, Panc02) and three normal cell lines (NIH-3T3, HaCaT, 16HBE). Our data showed that H. leucospilota protein decreased the cell viabilities of HepG2, A549, HaCaT, 16HBE in a concentration-dependent manner, while Panc02 and NIH-3T3 in a time- and concentration-dependent manner. We also found that the inhibitory effect of H. leucospilota protein (≥10 μg/mL) on cell viability is near or even superior to EPI, a clinical chemotherapeutic agent. In addition, our data also demonstrated that H. leucospilota protein significantly affected the cell cycle and induced apoptosis in the three cancer cell lines investigated; in comparison, it showed no effects on the normal cell lines (i.e., NIH-3T3, HaCaT and 16HBE). Finally, our results also showed that H. leucospilota protein exhibited the excellent performance in inhibiting cell immigrations. In conclusion, H. leucospilota protein targeted the cancer cell cycles and induced cancer cell apoptosis; its superiority to inhibit cancer cell migration compared with EPI, shows the potential as a promising anti-cancer drug.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.268
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.000

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 head0.017
GPT teacher head0.236
Teacher spread0.219 · 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 teacher head, not a consensus.

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

Citations36
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueNutrientsSame topicEchinoderm biology and ecologyFrench-language works237,207