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Record W2996213711 · doi:10.3390/bioengineering6040112

Probing the Antitumor Mechanism of Solanum nigrum L. Aqueous Extract against Human Breast Cancer MCF7 Cells

2019· article· en· W2996213711 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBioengineering · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPhytochemical Studies and Bioactivities
Canadian institutionsUniversity of Saskatchewan
FundersCollege of Pharmacy and Nutrition, University of Saskatchewan
KeywordsSolanum nigrumMechanism (biology)ChemistryAqueous extractBreast cancerPharmacologyCancerCancer researchMedicineTraditional medicineInternal medicine

Abstract

fetched live from OpenAlex

Solanum nigrum L. is one of the major medicinal plants used to treat cancer. However, the functional mechanism of S. nigrum L. extract is still unknown in spite of numerous studies on its active components. In this study, we probed the potential anticancer mechanism of the aqueous extract of S. nigrum L. (AESN) towards human breast cancer cell line MCF7. At a concentration of 10 g/L, AESN caused 43% cytotoxicity, inhibited the migration, and suppressed the activities of hexokinase and pyruvate kinase by about 30% and 40%, respectively, towards the MCF7 cells. RT2-PCR analysis of a panel of 89 caner-related genes identified 13 upregulated and eight downregulated genes (>2-folds) in MCF7 cells upon AESN treatment. Gene ontology (GO) and functional disease ontology (FunDO) analyses show that the antitumor function of S. nigrum L. involves multiple genes and these genes are shared across other diseases or disorders.

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.

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 categoriesnone
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 score0.002
Threshold uncertainty score0.425

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.006
GPT teacher head0.210
Teacher spread0.204 · 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