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Record W2417915141 · doi:10.2298/jsc160226054d

Elicitation effects of synthetic 1,2,4,5-tetraoxane and 2,5-diphenyltiophene in shoot cultures of two Nepeta species

2016· article· en· W2417915141 on OpenAlexaff
Slavica Dmitrović, Marijana Škorić, Jelena Boljević, Neda Aničić, Ð. Božić, Danijela Mišić, Vuk V. Filipović, Dejan Opsenica

Bibliographic record

VenueJournal of the Serbian Chemical Society · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant tissue culture and regeneration
Canadian institutionsInstitute for Biological Sciences
FundersMinistarstvo Prosvete, Nauke i Tehnološkog Razvoja
KeywordsShootNepetaRosmarinic acidChemistryBotanyLamiaceaeHorticultureFood scienceBiologyBiochemistry

Abstract

fetched live from OpenAlex

The present study was aimed to investigate the elicitation possibility of the main secondary metabolites production in Nepeta cataria L. and N. pannonica L. plants, by exposing them to synthetic compounds from the group of tetraoxanes and tiophenes. The effect of DO63 (1,2,4,5-tetraoxane) and DOVF15 (2,5-diphenyl-tiophene) on the production of cis,trans-nepetalactone (NL) and rosmarinic acid (RA) in two Nepeta species, was investigated in shoots grown on culture medium with addition of synthetic compounds in concentrations ranging from 0.1 to 2 mg L-1. The content of targeted metabolites in tested in vitro shoots depended on the type and the concentration of applied synthetic compounds. Application of DO63, primarily in concentration of 0.1 mg L-1 to 1 mg L-1, affected only NL production in both Nepeta species resulting in increased NL content in treated shoots, while production of RA was not influenced. Addition of DOVF15 caused decrease of RA content in N. pannonica shoots and increase in N. cataria shoots, whereas NL production was not affected. The presented results highlight the possibility of DO63 and DOVF15 application for the elicitation of the main secondary metabolites production in species from the genus Nepeta.

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 score0.003
Threshold uncertainty score0.159

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 head0.005
GPT teacher head0.229
Teacher spread0.223 · 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

Citations4
Published2016
Admission routes1
Has abstractyes

Explore more

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