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Long-term maintenance of in vitro cultures affects growth and secondary metabolism of St. John's Wort

2010· article· en· W2057501540 on OpenAlexaboutno aff
Adriana de Andrade Figueiró, Cynthia Manira Correa, Leandro Vieira Astarita, Eliane Romanato Santarém

Bibliographic record

VenueCiência Rural · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicNatural Compound Pharmacology Studies
Canadian institutionsnot available
FundersFundação de Amparo à Pesquisa do Estado do Rio Grande do SulConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsHypericinHypericum perforatumShootTissue cultureSecondary metabolismHorticultureMurashige and Skoog mediumMetabolismBiologyBotanyChemistryIn vitroBiosynthesisBiochemistryPharmacology

Abstract

fetched live from OpenAlex

Hypericum perforatum is a traditional medicinal plant with wound healing and antidepressant properties. Efficiency of micropropagation is often related to the long term maintenance of tissues in culture, which may alter the secondary metabolism of plants. The objective of this study was to evaluate growth and secondary metabolism of in vitro shoots of H. perforatum on short and long term maintenance of cultures (30 and 100 days). The effect of BA and NAA supplementation was evaluated during 30 days of culture. Adventitious shoots were cultivated on MS medium supplemented with 4.4mM BA alone or in combination with 0.05mM NAA for 30 days. A hormone-free medium was used as control. Shoots cultivated for 100 days were maintained in presence of 4.4mM BA. Biomass, multiplication of shoots, contents of phenolic compounds, flavonoids and hypericin were evaluated. No difference between BA and BA+NAA was observed on growth, multiplication of shoots and levels of flavonoids at the end of 30 days of culture. Production of phenolic compounds was promoted by addition of BA+NAA to the medium, whereas hypericin was increased by the presence of BA. The time of culture (30 and 100 days) affected all the parameters analyzed, except the levels of flavonoids in the short term experiment.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.752
Threshold uncertainty score0.221

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 head0.007
GPT teacher head0.240
Teacher spread0.232 · 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

Citations15
Published2010
Admission routes1
Has abstractyes

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