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Record W2524593212 · doi:10.1139/cjp-2016-0484

Binding interaction between 2-methoxy-5-fluoro phenyl boronic acid and sugars: Effect of structural change of sugars on binding affinity

2016· article· en· W2524593212 on OpenAlexaffvenue
P. Bhavya, Raveendra Melavanki, D. Nagaraja, H.S. Geethanjali, Raviraj Kusanur, M.N. Manjunatha

Bibliographic record

VenueCanadian Journal of Physics · 2016
Typearticle
Languageen
FieldChemistry
TopicMolecular Sensors and Ion Detection
Canadian institutionsHorizon College and Seminary
Fundersnot available
KeywordsMutarotationBoronic acidChemistryFuranoseArabinoseXyloseIntramolecular forceFluorescenceAqueous solutionStereochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

The binding interaction of 2-methoxy-5-fluoro phenyl boronic acid with various sugars like dextrose, arabinose, xylose, sucrose, and lactose is investigated in aqueous medium at pH 7.4 using the fluorescence spectroscopic method. Fluorescence intensity is reduced upon addition of sugars. The change in the intensity is attributed to breaking of intramolecular hydrogen bonding and to the lesser stability of boronic ester. Data are analyzed using the Benesi–Hildebrand equation and Lineweaver–Burk equation. The estimated binding constants are greater in mono sugars arabinose and xylose. The fact that a structural change in sugar arises due to mutarotation plays a major role in binding interactions. The furanose form of the sugar is found to be more favoured for binding.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.024
GPT teacher head0.260
Teacher spread0.237 · 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 source (direct Gemma or distilled Codex), 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

Citations5
Published2016
Admission routes2
Has abstractyes

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