Vol 49, No 9 (2018)

Nuclear magnetic resonance (NMR) is a powerful instrumental technique suited to characterize and identify organic substances, and has been successfully applied in the analysis of complex matrices such as biological and environmental samples. In a previous work, we demonstrated the ability of unsupervised contribution analysis (UCA) to process complex mixtures to identify the number of independent constituents and deconvolute mixed signals into specific signal sources. In this work, we evaluated the deconvolving ability of this algorithm to access underlying spectral information—we used UCA to estimate the number of contributing species and respective contributing sources and scores and with that information performed selective ¹H-NMR signal suppression. We found that, in optimal NMR conditions, independently of signal source type, UCA allows us to correctly (a) estimate the number of independent contributions, (b) retrieve specific signal sources and (c) respective mixing information, allowing us to (d) characterize each contribution using signal sources and (e) quantify each specific contribution by means of its mixing information. This unsupervised soft-modeling method allows (f) individual contribution estimation and (g) respective removal from collected spectra, thus (h) enhancing spectra information for minor contributing species.

The main observation in this work is a decrease in the modulation frequency of the primary electron spin-echo decay (ESEEM) of the \({\text{P}}_{ 7 0 0}^{ + }\) cofactor in the reaction center of Photosystem I (PS I) from cyanobacteria Synechocystis sp. PCC 6803 embedded in dry trehalose matrix as the temperature rises from 150 K to room temperature. From the previous studies of the EPR spectrum shape of this system, it is known that, in dry trehalose matrix at room temperature, the distance between \({\text{P}}_{ 7 0 0}^{ + }\) and \({\text{A}}_{ 1}^{ - }\) spins does not increase compared to the distance measured in glycerol–water solution at cryogenic temperature. From the present ESEEM study, we conclude that the decrease of modulation frequency with rising temperature in trehalose matrix can be fully attributed to the influence of accelerated spin–lattice relaxation of \({\text{A}}_{ 1}^{ - }\). Our calculations show that this requires a decrease in the spin–lattice relaxation time from 3 to 1 μs. To the best of our knowledge, this is the first time that a shift in the ESEEM frequency due to the dipole–dipole interaction between the spins is observed that is caused by spin–lattice relaxation. Based on the above-mentioned results, we formulate a model of the protective effect of trehalose matrix on the electron transfer in the reaction center of PS I that is based on different hydrogen-bond networks between trehalose, local water, and protein.

Iterative shrinkage algorithms like parallel coordinate descent and separable surrogate functional use wavelet thresholding with uniform and empirically selected threshold values to recover the under-sampled magnetic resonance (MR) images. In this paper, an adaptive thresholding parameter, for the recovery of static and dynamic MR images, is derived and used in wavelet domain shrinkage. A modified iterative shrinkage thresholding algorithm based on the derived parameter is also proposed. Simulation results show that adaptive wavelet thresholding yields significantly higher signal-to-noise ratio and correlation than the fixed thresholding value. The algorithm based on the adaptive threshold is experimentally tested for static and dynamic MR images with varying acceleration rates, and it has been shown that it outperforms the fixed thresholding value algorithm.

Sodium is a key element in a living organism. The increase of its concentration is an indicator of many pathological conditions. ²³Na magnetic resonance imaging (MRI) is a quantitative method that allows to determine the sodium content in tissues and organs in vivo. This method has not yet entered clinical practice widely, but it has already been used as a clinical research tool to investigate diseases such as brain tumors, breast cancer, stroke, multiple sclerosis, hypertension, diabetes, ischemic heart disease, osteoarthritis. The active development of the ²³Na MRI is promoted by the growth of available magnetic fields, the expansion of hardware capabilities, and the development of pulse sequences with ultra-short echo time.