TD-NMR in Quality Control: Standard Applications

Cobo, Marcio Fernando; Deublein, Eleonore J.; Haber, Agnes; Kwamen, Rance; Nimbalkar, Manoj; Decker, Frank

doi:10.1007/978-3-319-28388-3_12

Cited by 5 publications

(4 citation statements)

References 17 publications

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“…Thus, for the analysis of solid fat content (SFC), the SFC contribution from the solid and liquid portion of the samples was measured up to the instrument dead time (10 μs), whereas the contribution from the liquid part was measured after the complete decay of the signals from solid (70 μs). The SFC of different samples was calculated using the equation where S S + L is the NMR signal owing to both the fractions of liquid and solid, S L is the NMR signal related to the liquid component of the samples, and f is the correction factor that accounts for the instrument dead time and corrects the amplitude of the solid fraction of the pulse …”

Section: Methodsmentioning

confidence: 99%

Interplay of Aging and Lot-to-Lot Variability on the Physical and Chemical Properties of Excipients: A Case Study of Mono- and Diglycerides

et al. 2021

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The present study investigates the chemical composition governing the physical properties of mono- and diglycerides (MDGs) at the microstructural level, as a function of aging and lot-to-lot variability. The physical structure of the MDG plays a vital role in ameliorating the emulsion stability and is widely explored in diverse research horizons related to the pharmaceutical, cosmetic, and food industries. In an effort to understand the mechanism of emulsion stabilization, physical properties were extensively evaluated in selective commercial lots to determine if there is a correlation between the chemical composition of MDG and physical properties. The solid state of the MDG samples with different aging profiles was characterized using X-ray scattering, differential scanning calorimetry, attenuated total reflection-Fourier transform infrared spectroscopy, and NMR relaxometry. Moreover, the kinetic aspect of solid-state transformation was also evaluated via treating MDG samples with a heat–cool cycle. The chemical composition of MDGs was quantified using a quantitative NMR (qNMR) method. Interestingly, the X-ray scattering results demonstrated a change in the MDG polymorphic form and an increase in the %β content as a function of aging. The increase in the %β content led to the formation of rigid crystal structures of MDG, as evident from the NMR relaxometry. Chemical quantification of isomeric composition revealed chemical composition change as a potentially critical factor responsible for the altered physical structures of MDG with respect to aging and lot-to-lot variability. The findings correlated the solid-state transformation with the change in the chemical composition of the MDG as a combined effect of aging and lot-to-lot variability. This work serves as a basis to better understand the interdependency of the physicochemical properties of MDG. Furthermore, the present work can also be used as guidance for setting up the specifications of MDG, as per the required polymorphic form for a multitude of applications.

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Section: Methodsmentioning

confidence: 99%

Interplay of Aging and Lot-to-Lot Variability on the Physical and Chemical Properties of Excipients: A Case Study of Mono- and Diglycerides

et al. 2021

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“…In fact, a number of research publications have highlighted the need for including routine QA/QC checks in NMR metabolomics. [74][75][76][77] Since the intra-laboratory and inter-laboratory variations between NMR metabolomics datasets are smaller than for MS, QC may be limited to using pooled biological samples (pooled quality control; PQC) by combining together a small aliquot from each replicate in the dataset. PQC can be used to shim and tune the NMR, and can also be repeatedly analyzed at regular intervals throughout the NMR data collection to ensure system stability.…”

Section: Increasing Scientific Rigor and Confidence: Role Of Qa/qc In...mentioning

confidence: 99%

“…Nevertheless, the same rigorous QA/QC procedures are equally relevant and important to NMR‐based metabolomics. In fact, a number of research publications have highlighted the need for including routine QA/QC checks in NMR metabolomics 74–77 . Since the intra‐laboratory and inter‐laboratory variations between NMR metabolomics datasets are smaller than for MS, QC may be limited to using pooled biological samples (pooled quality control; PQC) by combining together a small aliquot from each replicate in the dataset.…”

Section: Increasing Scientific Rigor and Confidence: Role Of Qa/qc In...mentioning

confidence: 99%

Closing the gap between in vivo and in vitro omics: using QA/QC to strengthen ex vivo NMR metabolomics

Maroli

Powers

2021

NMR in Biomedicine

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Metabolomics aims to achieve a global quantitation of the pool of metabolites within a biological system. Importantly, metabolite concentrations serve as a sensitive marker of both genomic and phenotypic changes in response to both internal and external stimuli. NMR spectroscopy greatly aids in the understanding of both in vitro and in vivo physiological systems and in the identification of diagnostic and therapeutic biomarkers. Accordingly, NMR is widely utilized in metabolomics and fluxomics studies due to its limited requirements for sample preparation and chromatography, its non‐destructive and quantitative nature, its utility in the structural elucidation of unknown compounds, and, importantly, its versatility in the analysis of in vitro, in vivo, and ex vivo samples. This review provides an overview of the strengths and limitations of in vitro and in vivo experiments for translational research and discusses how ex vivo studies may overcome these weaknesses to facilitate the extrapolation of in vitro insights to an in vivo system. The application of NMR‐based metabolomics to ex vivo samples, tissues, and biofluids can provide essential information that is close to a living system (in vivo) with sensitivity and resolution comparable to those of in vitro studies. The success of this extrapolation process is critically dependent on high‐quality and reproducible data. Thus, the incorporation of robust quality assurance and quality control checks into the experimental design and execution of NMR‐based metabolomics experiments will ensure the successful extrapolation of ex vivo studies to benefit translational medicine.

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“…Spin-echo sequence has been used to measure moisture and oil content. The oil content is calculated by the echo intensity at 7 ms and the moisture content by the difference between the FID (at 50 μs) and echo intensities [ 2 ].…”

Section: Introductionmentioning

confidence: 99%

Recent 1D and 2D TD–NMR Pulse Sequences for Plant Science

Monaretto

Moraes

Colnago

2021

Plants

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Time domain nuclear magnetic resonance (TD–NMR) has been widely applied in plant science in the last four decades. Several TD–NMR instruments and methods have been developed for laboratory, green-house, and field studies. This mini-review focuses on the recent TD–NMR pulse sequences applied in plant science. One of the sequences measures the transverse relaxation time (T2) with minimal sample heating, using a lower refocusing flip angle and consequently lower specific absorption rate than that of conventional CPMG. Other sequences are based on a continuous wave free precession (CWFP) regime used to enhance the signal-to-noise ratio, to measure longitudinal (T1) and transverse relaxation time in a single shot experiment, and as alternative 2D pulse sequences to obtain T1–T2 and diffusion-T1 correlation maps. This review also presents some applications of these sequences in plant science.

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TD-NMR in Quality Control: Standard Applications

Cited by 5 publications

References 17 publications

Interplay of Aging and Lot-to-Lot Variability on the Physical and Chemical Properties of Excipients: A Case Study of Mono- and Diglycerides

Interplay of Aging and Lot-to-Lot Variability on the Physical and Chemical Properties of Excipients: A Case Study of Mono- and Diglycerides

Closing the gap between in vivo and in vitro omics: using QA/QC to strengthen ex vivo NMR metabolomics

Recent 1D and 2D TD–NMR Pulse Sequences for Plant Science

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