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Record W2201304529 · doi:10.3390/molecules201219786

Antiproliferative Activities of Water Infusions from Leaves of Five Cornus L. Species

2015· article· en· W2201304529 on OpenAlexfundno aff
Vladimír Forman, M Haladová, D Grančai, M Ficková

Bibliographic record

VenueMolecules · 2015
Typearticle
Languageen
FieldMedicine
TopicPhytochemicals and Antioxidant Activities
Canadian institutionsnot available
FundersFaculté de pharmacie, Université de MontréalVedecká Grantová Agentúra MŠVVaŠ SR a SAVMinisterstvo školstva, vedy, výskumu a športu Slovenskej republiky
KeywordsBiologyHorticultureBotany

Abstract

fetched live from OpenAlex

Cornaceae plants are known for their edible berries, and their leaves are used as tea. In the present study aqueous leaf extracts from Cornus mas (CM), C. alba (CA), C. flaviramea (CF), C. kousa (CK), and C. officinalis (CO) were tested for their antiproliferative activity in human breast cancer cells (MCF-7). Dose- (50-750 µg/mL) and time (24, 48, 72 h)-dependent antiproliferative effects were measured by WST-1, and correlated with the content of flavonoids (FL), total hydroxycinnamic derivatives (THD), total polyphenols (TP) and tannins (T). Extracts induced time dependent decreases in cell survival; CA, CO and CM were the most effective (11.2%, 10.3% and 11.1%, after 72 h). The ED50 (effective dose) values were similar for all extracts and times tested. The THD and TP were identical in all samples, while a two-fold higher T content was present in CK and CO, and of FL in CF. The maximal effects (% of surviving cells) negatively correlated with the T and TP levels, and positively with FL and THD. The results demonstrate the significant antiproliferative effects of the tested water extracts in MCF-7 cells, in which CA, CO and CM are the most effective; and the effectiveness is related to the T and TP contents.

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 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 score0.009
Threshold uncertainty score0.309

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 head0.028
GPT teacher head0.258
Teacher spread0.230 · 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.

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

Citations27
Published2015
Admission routes1
Has abstractyes

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