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Record W4380200733 · doi:10.5539/jps.v12n1p60

Strong Allelopathic Activity in Purple Leaves of Transgenic Spiraea cantoniensis Containing Cyanidin 3-Glucoside Assayed by the Protoplast Co-culture Method with Digital Image Analysis

2023· article· en· W4380200733 on OpenAlexvenueno aff
Sakae Suzuki, Waki Nakagawa, Yutaka Sasamoto, Hamako Sasamoto

Bibliographic record

VenueJournal of Plant Studies · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant tissue culture and regeneration
Canadian institutionsnot available
Fundersnot available
KeywordsAllelopathyProtoplastBiologyBotanyAnthocyaninCyanidinBioassayPigmentSeedlingGerminationChemistry

Abstract

fetched live from OpenAlex

The protoplast co-culture method with digital image analysis (DIA-PP method), was used for in vitro bioassay of allelopathic activity in the leaves of in vitro cultured plants of Spiraea cantoniensis. Purple leaves of transgenic S. cantoniensis, containing an anthocyanin, cyanidin 3-glucoside showed strong inhibitory allelopathic activity, 100% inhibition of recipient lettuce protoplast division by 80 × 103 mL-1 of co-cultured protoplasts, while green leaves of non-transgenic S. cantoniensis showed only 20% inhibition. Cyanidin 3-glucoside which inhibited lettuce protoplast division 80% at 100 µM was evaluated as an allelochemical of transgenic S. cantoniensis. Inhibition was stronger at the cell division stage of lettuce protoplast growth than that at the other stages, i.e., cell wall formation stage and yellow pigment accumulation stage. The results were discussed comparatively with the strong inhibitory activity of non-transgenic S. thunbergii and other allelopathic plant species containing different anthocyanin or carotenoid pigments as putative allelochemicals.

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)0.001
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 score0.005
Threshold uncertainty score0.327

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.022
GPT teacher head0.307
Teacher spread0.286 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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