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Record W2521980950 · doi:10.1002/elps.201600213

Enantioseparation of hydroxyeicosatetraenoic acids by hydroxypropyl‐γ‐cyclodextrin‐modified micellar electrokinetic chromatography

2016· article· en· W2521980950 on OpenAlexaff
Shuji Kodama, Shota Nakajima, Hiromichi Ozaki, Ryota Takemoto, Yutaka Itabashi, A. Kuksis

Bibliographic record

VenueElectrophoresis · 2016
Typearticle
Languageen
FieldChemistry
TopicAnalytical Chemistry and Chromatography
Canadian institutionsUniversity of Toronto
FundersJapan Society for the Promotion of ScienceHokkaido UniversityMinistry of Education, Culture, Sports, Science and Technology
KeywordsEnantiomerChemistryChromatographyMicellar electrokinetic chromatographyCyclodextrinResolution (logic)StereochemistryElectrophoresis

Abstract

fetched live from OpenAlex

Complete resolution of hydroxyeicosatetraenoic acid (HETE) enantiomers was achieved using hydroxypropyl-γ-cyclodextrin (HP-γ-CD)-modified MEKC. The optimum running conditions were determined to be utilizing a 30 mM phosphate-15 mM borate buffer (pH 9.0) containing 30 mM HP-γ-CD and 75 mM SDS as the BGE, application of +30 kV as the effective voltage, and carrying out the experiment at 15°C. The eluents were detected at 235 nm. The method was used successfully for the simultaneous separations of (S)- and (R)-enantiomers of regioisomeric 8-, 11-, 12-, and 15-HETEs. Subsequently, the optimized method was applied to evaluate the stereochemistry of 8- and 12-HETEs from the marine red algae, Gracilaria vermiculophylla and Gracilaria arcuata, respectively. The 8-HETE was found to be a mixture of 98% (R)-enantiomer and 2% (S)-enantiomer, while the 12-HETE was a mixture of 98% (S)-enantiomer and 2% (R)-enantiomer. The present study demonstrates that the HP-γ-CD-modified MEKC method is simple and sensitive and provides unambiguous information on the configuration of natural and synthetic HETEs.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.024
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.004
GPT teacher head0.197
Teacher spread0.193 · 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.

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

Citations23
Published2016
Admission routes1
Has abstractyes

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