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Record W6967781178 · doi:10.5281/zenodo.1156051

In Vitro-Cytotoxicity Studies Of Methanolic Leaf Extract Of Memocylon Umbellatum Burm.F. Against Breast Cancer.

2017· article· en· W6967781178 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2017
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacology and Nanomedicine Research
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsPhytochemicalMedicinal plantsCancer cell linesMTT assaySaponinHerb

Abstract

fetched live from OpenAlex

The Memocylon umbellatum is a shrub widely found in the western Ghats of Karnataka ,India. The leaf extracts of the plant is being used for various medicinal purposes such as used to cure diseases Ghonerria and also used for the treatment for eye irritations. Our study was aimed to analyze the phytochemical constituents present in the methanolic leaf extract of Memocylon umbellatum and further to study its cyto-toxic activity on the MCF-7 (Breast cancer line). Extraction of phytochemicals was done by using soxhlet apparatus. The methanolic extract was tested for the preliminary phytochemical analysis by using standard methods. Test showed the presence of phytochemicals such as Tannins, Lignin, Flavanoids, Steroids, Phenols, and Glycosides. Further, the cytotoxic nature of methanolic extract was explored by performing MTT assay on MCF-7 cell line. The methanolic leaves extract of Memocylon umbellatum evidenced the inhibition of MCF-7 cancer cell lines. Thus, active compounds of the extract could be of potential medicinal application.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient 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 score0.223
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.200
GPT teacher head0.467
Teacher spread0.266 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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Same venueZenodo (CERN European Organization for Nuclear Research)Same topicPharmacology and Nanomedicine ResearchFrench-language works237,207