Redetermination of cis-diaqua­diglycolato­zinc(II)

The title complex, [Zn(C2H3O3)2(H2O)2], was prepared and the crystal structure determined as part of a 67Zn solid state nuclear magnetic resonance study. In the title complex, the Zn atom has a disorted octa­hedral coordination comprising two bidentate glycolate ligands and two water mol­ecules. The water mol­ecules are cis to each other; one is trans to a carboxyl­ate O atom and the other trans to an alcohol O atom. The crystal structure has an extensive O—H⋯O hydrogen-bond network

Solid-state nuclear magnetic resonance of quadrupolar nuclei with applications to biological solids

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Chemistry, 1999.Vita.Includes bibliographical references.by David S. Rovnyak.Ph.D

Transcriptomic Responses of the Honey Bee Brain to Infection with Deformed Wing Virus

Managed colonies of European honey bees (Apis mellifera) are under threat from Varroa destructor mite infestation and infection with viruses vectored by mites. In particular, deformed wing virus (DWV) is a common viral pathogen infecting honey bees worldwide that has been shown to induce behavioral changes including precocious foraging and reduced associative learning. We investigated how DWV infection of bees affects the transcriptomic response of the brain. The transcriptomes of individual brains were analyzed using RNA-Seq after experimental infection of newly emerged adult bees with DWV. Two analytical methods were used to identify differentially expressed genes from the ~15,000 genes in the Apis mellifera genome. The 269 genes that had increased expression in DWV infected brains included genes involved in innate immunity such as antimicrobial peptides (AMPs), Ago2, and Dicer. Single bee brain NMR metabolomics methodology was developed for this work and indicates that proline is strongly elevated in DWV infected brains, consistent with the increased presence of the AMPs abaecin and apidaecin. The 1361 genes with reduced expression levels includes genes involved in cellular communication including G-protein coupled, tyrosine kinase, and ion-channel regulated signaling pathways. The number and function of the downregulated genes suggest that DWV has a major impact on neuron signaling that could explain DWV related behavioral changes

Determining Sequential Micellization Steps of Bile Salts With Multi-cmc Modeling

Hypothesis Bile salts exhibit complex concentration-dependent micellization in aqueous solution, rooted in a long-standing hypothesis of increasing size in bile aggregation that has historically focused on the measurement of only one CMC detected by a given method, without resolving successive stepwise aggregates. Whether bile aggregation is continuous or discrete, at what concentration does the first aggregate form, and how many aggregation steps occur, all remain as open questions. Experiments Bile salt critical micelle concentrations (CMCs) were investigated with NMR chemical shift titrations and a multi-CMC phase separation modeling approach developed herein. The proposed strategy is to establish a correspondence of the phase separation and mass action models to treat the first CMC; subsequent micellization steps, involving larger micelles, are then treated as phase separation events. Findings The NMR data and the proposed multi-CMC model reveal and resolve multiple closely spaced sequential preliminary, primary, and secondary discrete CMCs in dihydroxy and trihydroxy bile salt systems in basic (pH 12) solutions with a single model of one NMR data set. Complex NMR data are closely explained by the model. Four CMCs are established in deoxycholate below 100 mM (298 K, pH 12): 3.8 ± 0.5 mM, 9.1 ± 0.3 mM, 27 ± 2 mM, and 57 ± 4 mM, while three CMCs were observed in multiple bile systems, also under basic conditions. Global fitting leverages the sensitivity of different protons to different aggregation stages. In resolving these closely spaced CMCs, the method also obtains chemical shifts of these spectroscopically inaccessible (aka dark) states of the distinct micelles

NUScon: a community-driven platform for quantitative evaluation of nonuniform sampling in NMR

Although the concepts of nonuniform sampling (NUS) and non-Fourier spectral reconstruction in multidimensional NMR began to emerge 4 decades ago (Bodenhausen and Ernst, 1981; Barna and Laue, 1987), it is only relatively recently that NUS has become more commonplace. Advantages of NUS include the ability to tailor experiments to reduce data collection time and to improve spectral quality, whether through detection of closely spaced peaks (i.e., “resolution”) or peaks of weak intensity (i.e., “sensitivity”). Wider adoption of these methods is the result of improvements in computational performance, a growing abundance and flexibility of software, support from NMR spectrometer vendors, and the increased data sampling demands imposed by higher magnetic fields. However, the identification of best practices still remains a significant and unmet challenge. Unlike the discrete Fourier transform, non-Fourier methods used to reconstruct spectra from NUS data are nonlinear, depend on the complexity and nature of the signals, and lack quantitative or formal theory describing their performance. Seemingly subtle algorithmic differences may lead to significant variabilities in spectral qualities and artifacts. A community-based critical assessment of NUS challenge problems has been initiated, called the “Nonuniform Sampling Contest” (NUScon), with the objective of determining best practices for processing and analyzing NUS experiments. We address this objective by constructing challenges from NMR experiments that we inject with synthetic signals, and we process these challenges using workflows submitted by the community. In the initial rounds of NUScon our aim is to establish objective criteria for evaluating the quality of spectral reconstructions. We present here a software package for performing the quantitative analyses, and we present the results from the first two rounds of NUScon. We discuss the challenges that remain and present a roadmap for continued community-driven development with the ultimate aim of providing best practices in this rapidly evolving field. The NUScon software package and all data from evaluating the challenge problems are hosted on the NMRbox platform

Nonuniform sampling by quantiles

A flexible strategy for choosing samples nonuniformly from a Nyquist grid using the concept of statistical quantiles is presented for broad classes of NMR experimentation. Quantile-directed scheduling is intuitive and flexible for any weighting function, promotes reproducibility and seed independence, and is generalizable to multiple dimensions. In brief, weighting functions are divided into regions of equal probability, which define the samples to be acquired. Quantile scheduling therefore achieves close adherence to a probability distribution function, thereby minimizing gaps for any given degree of subsampling of the Nyquist grid. A characteristic of quantile scheduling is that one-dimensional, weighted NUS schedules are deterministic, however higher dimensional schedules are similar within a user-specified jittering parameter. To develop unweighted sampling, we investigated the minimum jitter needed to disrupt subharmonic tracts, and show that this criterion can be met in many cases by jittering within 25–50% of the subharmonic gap. For nD-NUS, three supplemental components to choosing samples by quantiles are proposed in this work: (i) forcing the corner samples to ensure sampling to specified maximum values in indirect evolution times, (ii) providing an option to triangular backfill sampling schedules to promote dense/uniform tracts at the beginning of signal evolution periods, and (iii) providing an option to force the edges of nD-NUS schedules to be identical to the 1D quantiles. Quantile-directed scheduling meets the diverse needs of current NUS experimentation, but can also be used for future NUS implementations such as off-grid NUS and more. A computer program implementing these principles (a.k.a. QSched) in 1D- and 2D-NUS is available under the general public license

A Closed-Form Solution for the Optimal Time Evolution of an Exponentially Decaying Signal with Thermal Noise

The signal-to-noise ratio of a monoexponentially decaying signal exhibits a maximum at an evolution time of approximately 1.26 T-2. It has previously been thought that there is no closed-form solution to express this maximum. We report in this note that this maximum can be represented in a specific, analytical closed form in terms of the negative real branch of an inverse function known as the Lambert W function. The Lambert function is finding increasing use in the solution of problems in a variety of areas in the physical sciences. (C) 2014 Wiley Periodicals, Inc

Identification of Edible Oils by Principal Component Analysis of H-1 NMR Spectra

Principal component analysis (PCA) is a statistical method widely used in chemometric studies to analyze large correlated sets of data. An undergraduate laboratory experiment involving PCA of H-1 NMR spectral data is described. Students collect NMR spectra of an unknown oil sample are provided with spectra of six oil standards (canola, corn, olive, peanut, sesame, and sunflower), and are asked to identify the unknown oil using score plots based on the PCA results. This laboratory experiment gives students hands-on experience collecting NMR spectra performing NMR spectral processing and utilizing freely available web-based software to subject the data to PCA and to prepare the subsequent scoring plots

Nonuniform sampling and maximum entropy reconstruction applied to the accurate measurement of residual dipolar couplings

Abstract Residual dipolar couplings (RDC) provide important global restraints for accurate structure determination by NMR. We show that nonuniform sampling in combination with maximum entropy reconstruction (MaxEnt) is a promising strategy for accelerating and potentially enhancing the acquisition of RDC spectra. Using MaxEnt-processed spectra of nonuniformly sampled data sets that are reduced up to one fifth relative to uniform sampling, accurate 13 C 0 -13 C a RDCs can be obtained that agree with an RMS of 0.67 Hz with those derived from uniformly sampled, Fourier transformed spectra. While confirming that frequency errors in MaxEnt spectra are very slight, an unexpected class of systematic errors was found to occur in the 6th significant figure of 13 C 0 chemical shifts of doublets obtained by MaxEnt reconstruction. We show that this error stems from slight line shape perturbations and predict it should be encountered in other nonlinear spectral estimation algorithms. In the case of MaxEnt reconstruction, the error can easily be rendered systematic by straightforward optimization of MaxEnt reconstruction parameters and self-cancels in obtaining RDCs from nonuniformly sampled, MaxEnt reconstructed spectra