Beyond the noise : high fidelity MR signal processing

This thesis describes a variety of methods developed to increase the sensitivity and resolution of liquid state nuclear magnetic resonance (NMR) experiments. NMR is known as one of the most versatile non-invasive analytical techniques yet often suffers from low sensitivity. The main contribution to this low sensitivity issue is a presence of noise and level of noise in the spectrum is expressed numerically as “signal-to-noise ratio”. NMR signal processing involves sensitivity and resolution enhancement achieved by noise reduction using mathematical algorithms. A singular value decomposition based reduced rank matrix method, composite property mapping, in particular is studied extensively in this thesis to present its advantages, limitations, and applications. In theory, when the sum of k noiseless sinusoidal decays is formatted into a specific matrix form (i.e., Toeplitz), the matrix is known to possess k linearly independent columns. This information becomes apparent only after a singular value decomposition of the matrix. Singular value decomposition factorises the large matrix into three smaller submatrices: right and left singular vector matrices, and one diagonal matrix containing singular values. Were k noiseless sinusoidal decays involved, there would be only k nonzero singular values appearing in the diagonal matrix in descending order providing the information of the amplitude of each sinusoidal decay. The number of non-zero singular values or the number of linearly independent columns is known as the rank of the matrix. With real NMR data none of the singular values equals zero and the matrix has full rank. The reduction of the rank of the matrix and thus the noise in the reconstructed NMR data can be achieved by replacing all the singular values except the first k values with zeroes. This noise reduction process becomes difficult when biomolecular NMR data is to be processed due to the number of resonances being unknown and the presence of a large solvent peak

透析患者の身体活動と高比重リポタンパクコレステロール分画、レシチン：コレステロール転送蛋白

中村学園大学平成20年

Shortening NMR diffusion experimental times

NMR diffusion measurements have become the method of choice for measuring diffusing due to their wide applicability, speed of measurement, enormous range of accessible diffusion coefficients (from gas ~10-6 m2s-1 to large polymers ~10-15 m2s-1), and the ability to measure diffusion over a specified timescale, Δ, which greatly adds to the power of NMR diffusion measurements as it allows the ability to probe porous media [1,2]. The weakness of NMR diffusion measurements lies in their inherent insensitivity. Consequently, many experiments are in theory possible but in practice would simply consume too much spectrometer time and therefore become impractical. Even in cases where the total measurement time is not a limitation, making the measurement faster expands the horizons of diffusion measurements to study reaction kinetics [3,4], as well as simply increasing throughput

Overview of the nomenclature and network of contributors to the development of bioreactors for human gut simulation using bibliometric tools: a fragmented landscape

The evolution of complex in vitro models of the human gastrointestinal system to interrogate the biochemical functionality of the gut microbiome has augmented our understanding of its role in human physiology and pathology. With 5718 authors from 52 countries, gut bioreactor research reflects the growing awareness of our need to understand the contribution of the gut microbiome to human health. Although a large body of knowledge has been generated from in vitro models, it is scattered and defined by application-specific terminologies. To better grasp the capacity of bioreactors and further our knowledge of the human gastrointestinal system, we have conducted a cross-field bibliometric search and mapped the evolution of human gastrointestinal in vitro research. We present reference material with the aim of identifying key authors and bioreactor types to enable researchers to make decisions regarding the choice of method for simulating the human gut in the context of microbiome functionality

Rapid and Self-Administrable Capillary Blood Microsampling Demonstrates Statistical Equivalence with Standard Venous Collections in NMR-Based Lipoprotein Analysis

We investigated plasma and serum blood derivatives from capillary blood microsamples (500 μL, MiniCollect® tubes) and corresponding venous blood (10 mL vacutainers). Samples from twenty healthy participants were analysed by 1H-NMR and 112 lipoprotein subfraction parameters; 3 supramolecular phospholipid composite (SPC) parameters from SPC1, SPC2, and SPC3 subfractions; 2 N-acetyl signals from α-1-acid glycoprotein (Glyc), GlycA and GlycB; and 3 calculated parameters, SPC (total), SPC3/SPC2, Glyc (total)—were assessed. Using linear regression between capillary and venous collection sites, explained variance (Adj. R2 ≥ 0.8, p < 0.001) was witnessed for 86% of plasma parameters (103/120), and 88% of serum parameters (106/120), indicating capillary lipoprotein, SPC, and Glyc concentration follows changes in venous concentra-tions. These results indicate capillary blood microsamples are suitable for sampling in remote areas and for high-frequency longitudinal sampling of the majority of lipoproteins, SPCs, and Glycs

Shortening NMR experimental times

Conventionally, arrayed nuclear magnetic resonance experiments, such as diffusion and relaxation, are performed with the same number of scans (NS) at each iteration despite the signal‐to‐noise ratio being more than sufficient for many of the iterations. Here, we propose a simple yet effective approach that significantly shortens experimental times by varying NS through the arrayed experiments while keeping the signal‐to‐noise ratio essentially the same and retaining experimental accuracy