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Record W1984822819 · doi:10.1002/cbic.200700116

Selective Detection of Sugar Phosphates by Capillary Electrophoresis/Mass Spectrometry and Its Application to an Engineered <i>E. coli</i> Host

2007· article· en· W1984822819 on OpenAlexaff
Joseph P. M. Hui, Jie Yang, Jon S. Thorson, Evelyn C. Soo

Bibliographic record

VenueChemBioChem · 2007
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsInstitute for Marine Biosciences
FundersNational Institute of Allergy and Infectious DiseasesNational Cancer InstituteNational Institutes of Health
KeywordsChemistrySugar phosphatesMass spectrometryChromatographyCapillary electrophoresisElectrosprayTandem mass spectrometrySugarBiochemistryBioconversionHexosePhosphateEnzymeFermentation

Abstract

fetched live from OpenAlex

A highly selective method employing capillary electrophoresis and electrospray mass spectrometry (CE-ESMS) with precursor ion scanning for fragment ions characteristic of phosphate-linked sugars was developed for the determination of "unnatural" sugar phosphates generated in vivo, as part of a natural product glycorandomization study. Cell lysates from an engineered E. coli host were probed for "natural" and "unnatural" sugar phosphates resulting from in vivo galactokinase (GalK) bioconversions, and tandem mass spectrometry experiments were performed to confirm the identities of the sugar phosphates. Among the 22 cell lysates that were studied, 13 were found to contain the expected natural and "unnatural" sugar phosphates. This was in agreement with the GalK in vitro conversion yields, in which an in vitro yield of <or=15 % coincided with a lack of observable in vivo bioconversion. In addition, the CE-ESMS and precursor ion scanning method was capable of separating sugar phosphate regioisomers such as hexose-6-phosphate and hexose-1-phosphate.

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)
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 score0.076
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.003
GPT teacher head0.189
Teacher spread0.186 · 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

Citations24
Published2007
Admission routes1
Has abstractyes

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