MétaCan
Menu
Back to cohort

Polymorphs of Theophylline Characterized by DNP Enhanced Solid-State NMR

2015· article· en· W2285443854 on OpenAlexfundno aff
Arthur C. Pinon, Aaron J. Rossini, Cory M. Widdifield, David Gajan, Lyndon Emsley

Bibliographic record

VenueMolecular Pharmaceutics · 2015
Typearticle
Languageen
FieldChemistry
TopicAdvanced NMR Techniques and Applications
Canadian institutionsnot available
FundersEuropean Research CouncilNatural Sciences and Engineering Research Council of Canada
KeywordsTheophyllineSolid-state nuclear magnetic resonanceMagic angle spinningChemistrySolid-stateMoleculeNuclear magnetic resonance spectroscopyPolymorphism (computer science)Analytical Chemistry (journal)CrystallographyPhysical chemistryMaterials scienceStereochemistryOrganic chemistryNuclear magnetic resonance

Abstract

fetched live from OpenAlex

We show how dynamic nuclear polarization (DNP) enhanced solid-state NMR spectroscopy can be used to characterize polymorphs and solvates of organic solids. We applied DNP to three polymorphs and one hydrated form of the asthma drug molecule theophylline. For some forms of theophylline, sample grinding and impregnation with the radical-containing solution, which are necessary to prepare the samples for DNP, were found to induce polymorphic transitions or desolvation between some forms. We present protocols for sample preparation for solid-state magic-angle spinning (MAS) DNP experiments that avoid the polymorphic phase transitions in theophylline. These protocols include cryogrinding, grinding under inert atmosphere, and the appropriate choice of the impregnating liquid. By applying these procedures, we subsequently demonstrate that two-dimensional correlation experiments, such as (1)H-(13)C and (1)H-(15)N HETCOR or (13)C-(13)C INADEQUATE, can be obtained at natural isotopic abundance in reasonable times, thus enabling more advanced structural characterization of polymorphs.

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 score0.001
Threshold uncertainty score0.003

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 integrity0.0000.000
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 head0.027
GPT teacher head0.344
Teacher spread0.317 · 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

Citations94
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueMolecular PharmaceuticsSame topicAdvanced NMR Techniques and ApplicationsFrench-language works237,207