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Record W2760713789 · doi:10.5539/ijc.v9n4p40

Effect of a 50-Hz Magnetic Field on the Degradation of Plasmid in the Presence of Cu(II) Ions and Hydrogen Peroxide

2017· article· en· W2760713789 on OpenAlexvenueno aff
Yuuichi Kawashima, Honoka Fujii, Maresuke Nakayama, Masahiko Hasegawa, Satoru Shimanuki, Hidetake Miyata

Bibliographic record

VenueInternational Journal of Chemistry · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Genetic and Mutation Studies
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryHydrogen peroxideAgaroseDNA supercoilPlasmidAgarose gel electrophoresisDNAMagnetic fieldIonDegradation (telecommunications)CatalysisAnalytical Chemistry (journal)BiophysicsPhotochemistryChromatographyBiochemistryDNA replicationOrganic chemistry

Abstract

fetched live from OpenAlex

Power-line frequency (50/60 Hz) magnetic fields enhance DNA strand breaks in the cell. In order to understand the molecular mechanism underlying this phenomenon, we analyzed the conversion of plasmid from the supercoiled to the linear form. This conversion is promoted by hydroxyl radical generated by the reaction between Cu2+ and H2O2. The plasmid pHSG298 was incubated with 1 mM Cu2+ and 1 mM H2O2 and exposed to a 1.2 mT, 50-Hz magnetic field for 30, 60, and 90 min. The conversion of supercoiled DNA to linear DNA was analyzed by agarose gel electrophoresis. We found that exposure to the magnetic field for 90 min significantly enhanced the degree of conversion.

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 score0.055
Threshold uncertainty score0.059

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 head0.014
GPT teacher head0.257
Teacher spread0.243 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

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