Efficient Laplace NMR methods for biological nanoparticles, ionic liquids and porous materials research
|Author:||Ullah, Md Sharif1,2|
1University of Oulu Graduate School
2University of Oulu, Faculty of Science, Physics, NMR Research Unit (NMR)
|Online Access:||PDF Full Text (PDF, 1.7 MB)|
|Persistent link:|| http://urn.fi/urn:isbn:9789526234755
Oulu : University of Oulu,
|Publish Date:|| 2022-12-15
|Thesis type:||Doctoral Dissertation
|Defence Note:||Academic dissertation to be presented with the assent of the Doctoral Training committee of Technology and Natural Sciences of the University of Oulu for public discussion in the auditorium IT116, Linnanmaa, on 1 December 2022, at 12 noon
Professor Ville-Veikko Telkki
Associate Professor Vladimir Zhivonitko
Doctor Otto Mankinen
Associate Professor Petrik Galvosas
Doctor Kathryn Anderssen
Professor Dimitrios Sakellariou
Professor Ville-Veikko Telkki
The thesis aims to characterize extracellular vesicles (EVs) utilizing nuclear magnetic resonance (NMR) and develop different ultrafast Laplace NMR (UF LNMR) methods. LNMR consists of diffusion and relaxation NMR experiments and provides detailed information about molecular rotational and translational motion. A multidimensional approach substantially enhances the resolution and information content of LNMR. However, multidimensional LNMR experiments are slow because of the need to repeat the experiment with incremented evolution time. The utilization of an ultrafast approach in multidimensional LNMR experiments significantly reduces the experiment time. In the UF LNMR approach, the evolution times are encoded in different layers of a sample. This way, the data of a multidimensional experiment can be read in a single scan, shortening the experiment time by one to three orders of magnitude. The single scan approach allows hyperpolarization techniques to boost the experimental sensitivity by several orders of magnitude.
In the first part of the thesis, we demonstrate that diffusion-ordered spectroscopy (DOSY) is an NMR tool to characterize various EV samples extracted from milk as well as embryonic kidney and renal carcinoma cells based on their size distributions. The DOSY NMR allows one to determine a broad size distribution ranging from 1 to 500 nm. Transmission electron microscopy (TEM) and nanoparticle tracking analysis (NTA) confirm the DOSY NMR size distribution. However, the NTA analysis cannot detect any particle below 70 nm. A complementary hyperpolarized chemical exchange saturation transfer (hyper-CEST) 129Xe NMR study confirms the presence of small and large nanoparticles in the EV samples.
In the second part of the thesis, we introduced a novel single scan UF LNMR called UF T2-T2 relaxation exchange spectroscopy (REXSY) method to quantify the molecular exchange using T2 relaxation as a contrast. We studied a halogen-free orthoborate-based ionic liquid (IL) to validate the method. It allowed us to quantify the molecular exchange that occurred between the aggregates and free ions. The results obtained from UF REXSY are in good agreement with conventional reference experiments. The UF REXSY method provides the means of analyzing molecular exchange processes in different fields, such as cellular metabolism and ion transport in electrolytes, with higher sensitivity and efficiency.
In the final part of the thesis, we demonstrated a modified UF T1-T2 correlation experiment suitable for nonlinear sampling of T1 data. The method leads to the optimal sampling of exponential data. The technique uses frequency-swept pulses whose frequency increases nonlinearly with time. As proof-of-principle, we exploited the method in analyzing single- and double-tube doped water systems and porous materials. The nonlinear sampling resulted in enhanced resolution. This approach can also be used in other multidimensional UF LNMR experiments, such as diffusion experiments.
Osajulkaisut / Original papers
Osajulkaisut eivät sisälly väitöskirjan elektroniseen versioon. / Original papers are not included in the electronic version of the dissertation.
Report series in physical sciences
|Type of Publication:||
G5 Doctoral dissertation (articles)
|Field of Science:||
114 Physical sciences
116 Chemical sciences
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