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Record W1981446106 · doi:10.1080/14786419.2014.995653

<i>In vitro</i>antioxidant and antiproliferative activities of six international basil cultivars

2015· article· en· W1981446106 on OpenAlexaff
Hosam O. Elansary, Eman A. Mahmoud

Bibliographic record

VenueNatural Product Research · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEssential Oils and Antimicrobial Activity
Canadian institutionsUniversity of Guelph
FundersDepartment of Agriculture, Forestry and Fisheries
KeywordsHeLaDPPHChemistryAntioxidantLinoleic acidRosmarinic acidTraditional medicineOcimumApoptosisBasilicumBiochemistryIn vitroFatty acidMedicine

Abstract

fetched live from OpenAlex

The total phenolic, flavonoid and tannin contents in leaves extracts of Ocimum basilicum (OB) (Lamiaceae) international cultivars, as well as their overall antioxidant activities using DPPH and linoleic acid assays, were investigated. Furthermore, the antiproliferative and cytotoxic activities against line HeLa, MCF-7, Jurkat, HT-29, T24, MIAPaCa-2 cancer cells and one normal human cell line HEK-293 were examined. DPPH and linoleic acid assays ranged from 75.8% to 93.3% and from 74.5% to 97.1%; respectively. O. b. 'purple ruffle', O. b. 'dark opale', O. b. 'genovese', O. b. 'anise', O. b. 'bush green' and O. b. L. (OBL) varied in their antiproliferative and cytotoxic activities, influenced cell cycle progression and stimulated apoptosis in most cancer cells. OBL exhibited the highest antioxidant and antiproliferative activities. OB extracts not only improve taste but also have certain anticancer activity against diverse cancer cells due to the presence of compounds such as rosmarinic acid, chicoric acid and caftaric acid. Thus, OB represents a potent source of anticancer materials.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.056
GPT teacher head0.333
Teacher spread0.276 · 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

Citations48
Published2015
Admission routes1
Has abstractyes

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