Evidence map›Paper›PMID 26304859›Full record

ArticleThe AAPS journal2015

2D-Cosy NMR Spectroscopy as a Quantitative Tool in Biological Matrix: Application to Cyclodextrins.

Gilles Dufour, Brigitte Evrard, Pascal de Tullio

Open access · bronzeAbstract read
In one paragraph

Article in The AAPS journal, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
3.8field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 24 citations in OpenAlex.

  1. Applications of quantitativeJournal of pharmaceutical analysis · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Gilles DufourCHU, Laboratory of Pharmaceutical Technology and Biopharmacy, Department of Pharmacy, University of Liege, Tower 4, 2nd floor, Avenue de l'hôpital,1, 4000, Liège, Belgium. gilles.dufour@ulg.ac.be.
Brigitte EvrardCHU, Laboratory of Pharmaceutical Technology and Biopharmacy, Department of Pharmacy, University of Liege, Tower 4, 2nd floor, Avenue de l'hôpital,1, 4000, Liège, Belgium.
Pascal de TullioLaboratory of Medicinal Chemistry, Department of Pharmacy, Center for Interdisciplinary Research on Medicines (CIRM), University of Liege, 4000, Liège, Belgium.
University of Liège · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Classical analytical quantifications in biological matrices require time-consuming sample pre-treatments and extractions. Nuclear magnetic resonance (NMR) analysis does not require heavy sample treatments or extractions which therefore increases its accuracy in quantification. In this study, even if quantitative (q)NMR could not be applied to 2D spectra, we demonstrated that cross-correlations and diagonal peak intensities have a linear relationship with the analyzed pharmaceutical compound concentration. This work presents the validation process of a 2D-correlation spectroscopy (COSY) NMR quantification of 2-hydroxypropyl-β-cyclodextrin in plasma. Specificity, linearity, precision (repeatability and intermediate precision), trueness, limits of quantification (LOQs), and accuracy were used as validation criteria. 2D-NMR could therefore be used as a valuable and accurate analytical technique for the quantification of pharmaceutical compounds, including hardly detectable compounds such as cyclodextrins or poloxamers, in complex biological matrices based on a calibration curve approach.

Indexed as

CyclodextrinsHumansMagnetic Resonance SpectroscopyCyclodextrins2D-NMRbiological matricescyclodextrinspoloxamersquantification

Identifiers

PMID26304859
PMCPMC4627452
OpenAlexW1960321557

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.