Pure Shift Research Articles

Pure Shift NMR in Continuous Flow.

Flow NMR is an expanding analytical approach with applications that include in-line analysis for process control and optimisation, and real-time reaction monitoring. The samples monitored by flow NMR are typically mixtures that yield complex 1D1H spectra. "Pure shift" NMR is a powerful approach to simplifying1H NMR spectra, but its standard implementation is not compatible with continuous flow because of interference between sample motion and the position-dependent spin manipulations that are required in pure shift NMR. Here we show that pure shift NMR spectra can be successfully collected for continuously flowing samples, thanks to an adapted acquisition scheme, robust solvent suppression, and a velocity-compensation strategy. The resulting method is used to collect ultrahigh resolution reaction monitoring data. Pure shift NMR spectra are expected to benefit many applications of flow NMR.

Rationalising spin relaxation during slice-selective refocusing pulses

Slice-selective refocusing pulses are powerful building blocks in contemporary magnetic resonance experiments, but their use in quantitative applications is complicated by the site-dependent signal loss they introduce. One source of this attenuation is the spin relaxation that occurs during such pulses, which causes losses that depend on the specific longitudinal and transverse relaxation time constants for a given resonance. This dependence is complicated both by any amplitude shaping of the radiofrequency pulse, and by the presence of the spatial encoding pulsed field gradient. The latter causes the net signal measured to be the weighted sum of signal contributions from a continuous range of offsets from resonance. In general, each offset will make a different contribution to the overall signal, and will be attenuated by a different mixture of longitudinal and transverse relaxation that is dictated by the different trajectories that the nuclear magnetisations take during experiments. Despite this complex behaviour, we present evidence from experiments and numerical simulations showing that in practical experimental applications a relatively simple empirical function can be used to accurately predict relaxational attenuation during slice-selective refocusing pulses. This approach may be of practical use in correcting for relaxational losses in quantitative applications of slice-selective pulse methods such as Zangger-Sterk pure shift NMR.

ELSA-PSYCHE: An Improved Method for Protecting Pure Shift Spectra from Artifacts.

Numerous 1H-1H J couplings contribute to complex multiplets in 1H nuclear magnetic resonance spectroscopy, leading to an ambiguous spectral assignment, particularly for strongly coupled protons. Although the PSYCHE approach has proven to be effective in simplifying complex spectra by collapsing J couplings, the PSYCHE pure shift spectrum of strongly coupled protons always suffers from sideband artifacts and baseline oscillations, which impede spectral identification. Herein, we introduce a novel universal technique designed to separate artifacts from the desired absorption-mode pure shift signals. This new study will significantly benefit the development of molecular structure elucidations and composition analysis in the fields of chemistry, biochemistry, and metabonomics.

Combining Fast Pure Shift NMR and GEMSTONE-Based Selective TOCSY for Efficient NMR Analysis of Complex Systems.

As one of the commonly used intact detection techniques, liquid NMR spectroscopy offers unparalleled insights into the chemical environments, structures, and dynamics of molecules. However, it generally encounters the challenges of crowded or even overlapped spectra, especially when probing complex sample systems containing numerous components and complicated molecular structures. Herein, we exploit a general NMR protocol for efficient NMR analysis of complex systems by combining fast pure shift NMR and GEMSTONE-based selective TOCSY. First, this protocol enables ultrahigh-selective observation on the coupling networks that are totally correlated with targeted resonances or components, even where they are situated in severely overlapped spectral regions. Second, pure shift simplification is introduced to enhance the spectral resolution and further resolve the subspectra containing spectral congestion, thus facilitating the dissection of overlapped spectra. Additionally, sparse sampling accompanied by spectral reconstruction is adopted to significantly accelerate acquisition and improve spectral quality. The advantages of this protocol were demonstrated on different complex sample systems, including a challenging compound of estradiol, a mixture of sucrose and d-glucose, and natural grape juice, verifying its feasibility and power, and boosting the potential application landscapes in various chemical fields.

Substitution of 2-oxoglutarate alters reaction outcomes of the Pseudomonas savastanoi ethylene-forming enzyme

In seeding plants, biosynthesis of the phytohormone ethylene, which regulates processes including fruit ripening and senescence, is catalyzed by 1-aminocyclopropane-1-carboxylic acid (ACC) oxidase. The plant pathogen Pseudomonas savastanoi (previously classified as: Pseudomonas syringae) employs a different type of ethylene-forming enzyme (psEFE), though from the same structural superfamily as ACC oxidase, to catalyze ethylene formation from 2-oxoglutarate (2OG) in an arginine dependent manner. psEFE also catalyzes the more typical oxidation of arginine to give L-Δ1-pyrroline-5-carboxylate (P5C), a reaction coupled to oxidative decarboxylation of 2OG giving succinate and CO2. We report on the effects of C3 and/or C4 substituted 2OG derivatives on the reaction modes of psEFE. 1H NMR assays, including using the pure shift method, reveal that, within our limits of detection, none of the tested 2OG derivatives is converted to an alkene; some are converted to the corresponding β-hydroxypropionate or succinate derivatives, with only the latter being coupled to arginine oxidation. The NMR results reveal that the nature of 2OG derivatization can affect the outcome of the bifurcating reaction, with some 2OG derivatives exclusively favoring the arginine oxidation pathway. Given that some of the tested 2OG derivatives are natural products, the results are of potential biological relevance. There are also opportunities for therapeutic or biocatalytic regulation of the outcomes of reactions catalyzed by 2OG-dependent oxygenases by the use of 2OG derivatives.

Fast Pure Shift NMR Spectroscopy Using Attention-Assisted Deep Neural Network.

Pure shift NMR spectroscopy enables the robust probing on molecular structure and dynamics, benefiting from great resolution enhancements. Despite extensive application landscapes in various branches of chemistry, the long experimental times induced by the additional time dimension generally hinder its further developments and practical deployments, especially for multi-dimensional pure shift NMR. Herein, this study proposes and implements the fast, reliable, and robust reconstruction for accelerated pure shift NMR spectroscopy with lightweight attention-assisted deep neural network. This deep learning protocol allows one to regain high-resolution signals and suppress undersampling artifacts, as well as furnish high-fidelity signal intensities along with the accelerated pure shift acquisition, benefitting from the introduction of the attention mechanism to highlight the spectral feature and information of interest. Extensive results of simulated and experimental NMR data demonstrate that this attention-assisted deep learning protocol enables the effective recovery of weak signals that are almost drown in the serious undersampling artifacts, and the distinction and recognition of close chemical shifts even though using merely 5.4% data, highlighting its huge potentials on fast pure shift NMR spectroscopy. As a result, this study affords a promising paradigm for the AI-assisted NMR protocols toward broader applications in chemistry, biology, materials, and life sciences, and among others.

Universally Quantitative Band-Selective Pure Shift NMR Spectroscopy.

NMR spectroscopy is often described as a quantitative analytical technique. Strictly, only the simple pulse-acquire experiment is universally quantitative, but the poor signal resolution of the 1H NMR pulse-acquie experiment frequently complicates quantitative analysis. Pure shift NMR techniques provide higher resolution, by reducing signal overlap, but they are susceptible to a variety of sources of site-dependent signal loss. Here, we introduce a new method that corrects for signal loss from such sources in band-selective pure shift NMR experiments, by performing different numbers of iterations of the same pulse sequence elements before acquisition to allow extrapolation back to the loss-free signal. We apply this method to both interferogram and semi-realtime acquisition modes, obtaining integrals within 1% of those acquired from a pulse-acquire experiment for a three-component mixture.

Making 1H-1H Couplings More Accessible and Accurate with Selective 2DJ NMR Experiments Aided by 13C Satellites.

1H-1H coupling constants are one of the primary sources of information for nuclear magnetic resonance (NMR) structural analysis. Several selective 2DJ experiments have been proposed that allow for their individual measurement at pure shift resolution. However, all of these experiments fail in the not uncommon case when coupled protons have very close chemical shifts. First, the coupling between protons with overlapping multiplets is inaccessible due to the inability of a frequency-selective pulse to invert just one of them. Second, the strong coupling condition affects the accuracy of coupling measurements involving third spins. These shortcomings impose a limit on the effectiveness of state-of-the-art experiments, such as G-SERF or PSYCHEDELIC. Here, we introduce two new and complementary selective 2DJ experiments that we coin SERFBIRD and SATASERF. These experiments overcome the aforementioned issues by utilizing the 13C satellite signals at natural isotope abundance, which resolves the chemical shift degeneracy. We demonstrate the utility of these experiments on the tetrasaccharide stachyose and the challenging case of norcamphor, for the latter achieving measurement of all JHH couplings, while only a few were accessible with PSYCHEDELIC. The new experiments are applicable to any organic compound and will prove valuable for configurational and conformational analyses.

Solvent Suppression in Pure Shift NMR.

Intense solvent signals in 1H solution-state NMR experiments typically cause severe distortion of spectra and mask nearby solute signals. It is often infeasible or undesirable to replace a solvent with its perdeuterated form, for example, when analyzing formulations in situ, when exchangeable protons are present, or for practical reasons. Solvent signal suppression techniques are therefore required. WATERGATE methods are well-known to provide good solvent suppression while enabling retention of signals undergoing chemical exchange with the solvent signal. Spectra of mixtures, such as pharmaceutical formulations, are often complicated by signal overlap, high dynamic range, the narrow spectral width of 1H NMR, and signal multiplicity. Here, we show that by combining WATERGATE solvent suppression with pure shift NMR, ultrahigh-resolution 1H NMR spectra can be acquired while suppressing intense solvent signals and retaining exchangeable 1H signals. The new method is demonstrated in the analysis of cyanocobalamin, a vitamin B12 supplement, and of an eye-drop formulation of atropine.

Shear buckling of ship structures rectangular elements

In the work to determine the spectrum of critical loads and the corresponding forms of a rectangular clamped panel (plate) buckling under the action of balanced tangential forces on its contour, the Bubnov-Galerkin method using polynomials in two coordinates is proposed. This problem of the ship skin element pure shift does not have an exact closed solution, and the known approximate solutions require an analysis of their accuracy and reliability. The aim of the work is to obtain and analyze analytical solutions using polynomials of various degrees. Approximating deflection functions satisfying all the boundary conditions of the problem are represented sequentially by polynomials of 10th, 12th, 14th, 16th and 18th degrees in two coordinates with undefined coefficients. The solution of the main differential equation of the problem is found approximately in the integral sense, as a result of which homogeneous systems of linear algebraic equations with respect to unknown coefficients of polynomials are obtained. These systems contain a shear load as a parameter. To obtain eigenvalues (critical loads), the determinants of the systems are equated to zero. Numerical results are obtained in the Maple analytical computing system. For each approximation (polynomial), a power equation with respect to the critical load, the solution of which is paired values differing in signs is obtained. The forms of buckling are oblique waves. For a ship skin square panel, the first form of buckling is a single bulge along the diagonal of the panel. The second form is obtained in the form of two bulges directed in opposite directions (symmetrically-antisymmetrically with respect to the diagonals), etc. The numerical results are compared with the results of other authors. It is established that with an increase in the number of the polynomial terms, the initial critical loads and forms of buckling are specified, first of all.

Effect of junction temperature on 1.3 µm InAs/GaAs quantum dot lasers directly grown on silicon

Laser junction temperature (Tj) is an essential parameter that directly affects the light power and lifetime of semiconductor lasers. Here, we investigate the effect of Tj on an InAs/GaAs quantum dot (QD) laser grown on a Si(001) substrate. Under 1% low pulsed current (1 µs pulse width and 100 µs period), the pure temperature-induced mode shift rate is 0.084 nm/°C. By increasing the duty cycle and measuring the corresponding mode wavelength shift, the laser’s Tj under the continuous-wave (Tj-CW) mode is predicted to be from 31.1 to 81.6 °C when the injection current increases from 100 to 550 mA. Next, the average thermal resistance is 36.2 °C/W. Moreover, the non-negligible increase in Tj-CW is analyzed to significantly reduce the mean-time-to-failure of Si-based QD laser, especially for cases under high CW injection currents. These results provide an accurate reference for the thermal analysis of silicon-based QD lasers and point the way to high performance on-chip light sources by improving the laser heat accumulation.

Spatially encoded pure-shift diffusion-ordered NMR spectroscopy yielded by chirp excitation

Spatially-encoded diffusion-ordered NMR spectroscopy (SPEN-DOSY) has emerged as a new time-efficient tool for the analysis of mixtures of small molecules in solution. Time efficiency is achieved using the concept of spatial parallelization of the effective gradient area, instead of the sequential incrementation used in conventional diffusion experiments. The data acquired with such sequences are then usually processed to extract diffusion coefficients, but cases when peak overlap in the 1H spectrum are difficult to address. Such limitation in conventional diffusion experiments is addressed via using the Pure Shift Yielded by CHirp Excitation (PSYCHE)-iDOSY sequence. Here we have adapted the PSYCHE-iDOSY sequence by using echo planar spectroscopic imaging (EPSI) to acquire SPEN-DOSY data. The pure shift mode of PSYCHE separates the overlapped components and a modified Stejskal-Tanner equation is used to extract the corresponding diffusion coefficient. The primary results obtained with the above-mentioned mixtures seem to open the possibility of separating complex mixtures in less time than PSYCHE-iDOSY.

Research on parallel control strategy of power converters based on fuzzy neural network

As pure electric vehicles shift toward intelligent technology, the energy demand for onboard equipment is on the rise. In this study, a parallel control strategy for two 3-kW DC–DC power converters was proposed to meet the power requirements of pure electric vehicle loads in this paper. First, the operation mode of the resonant power converter was analyzed. The operation mode of the power converter adopted the advantageous frequency conversion–phase shift control mode. Second, a parallel control method for Takagi–Sugeno-type fuzzy neural network converters with four inputs and a single output first-order was designed to meet the power demand based on the advantages of fuzzy control and neural networks. The neural networks can be trained automatically based on the established requirements, and the fuzzy rules formulated through fuzzy neural networks were more detailed and accurate. Finally, the proposed control strategy was validated by experiments. The experimental results showed that the proposed control strategy can ensure the stable operation of the power converter during switching under the set load. The output power of the primary and sub converters varies linearly, which can meet the load’s demand for high power. There is no need to develop higher-power power converters. These results can provide a new idea for the research of high-power power converters and reduce development costs.

Accelerated Pure Shift NMR Spectroscopy with Deep Learning.

Pure shift nuclear magnetic resonance (NMR) spectroscopy presents a promising solution to provide sufficient spectral resolution and has been increasingly applied in various branches of chemistry, but the optimal resolution is generally accompanied by long experimental times. We present a proof of concept of deep learning for fast, high-quality, and reliable pure shift NMR reconstruction. The deep learning (DL) protocol allows one to eliminate undersampling artifacts, distinguish peaks with close chemical shifts, and reconstruct high-resolution pure shift NMR spectroscopy along with accelerated acquisition. More meaningfully, the lightweight neural network delivers satisfactory reconstruction performance on personal computers by several hundred simulated data learning, which somewhat lifts the prohibiting demand for a large volume of real training samples and advanced computing hardware generally required in DL projects. Additionally, an M-to-S strategy applicable to common DL cases is further exploited to boost the network generalization capability. As a result, this study takes a meaningful step toward deep learning protocols for broad chemical applications.

Ultra-clean pure shift NMR with optimal water suppression for analysis of aqueous pharmaceutical samples.

Pure shift NMR experiments greatly enhance spectral resolution by collapsing multiplet structures into singlets and, with water suppression, can be used for aqueous samples. Here, we combine ultra-clean pure-shift NMR (SAPPHIRE) with two different internally encoded water suppression schemes to achieve optimal performance for small molecule and macrocyclic peptide pharmaceuticals in water and acetonitrile-water mixtures.

Implementation of pure shift 1 H NMR in metabolic phenotyping for structural information recovery of biofluid metabolites with complex spin systems.

NMR spectroscopy is a mainstay of metabolic profiling approaches to investigation of physiological and pathological processes. The one-dimensional proton pulse sequences typically used in phenotyping large numbers of samples generate spectra that are rich in information but where metabolite identification is often compromised by peak overlap. Recently developed pure shift (PS) NMR spectroscopy, where all J-coupling multiplicities are removed from the spectra, has the potential to simplify the complex proton NMR spectra that arise from biosamples and hence to aid metabolite identification. Here we have evaluated two complementary approaches to spectral simplification: the HOBS (band-selective with real-time acquisition) and the PSYCHE (broadband with pseudo-2D interferogram acquisition) pulse sequences. We compare their relative sensitivities and robustness for deconvolving both urine and serum matrices. Both methods improve resolution of resonances ranging from doublets, triplets and quartets to more complex signals such as doublets of doublets and multiplets in highly overcrowded spectral regions. HOBS is the more sensitive method and takes less time to acquire in comparison with PSYCHE, but can introduce unavoidable artefacts from metabolites with strong couplings, whereas PSYCHE is more adaptable to these types of spin system, although at the expense of sensitivity. Both methods are robust and easy to implement. We also demonstrate that strong coupling artefacts contain latent connectivity information that can be used to enhance metabolite identification. Metabolite identification is a bottleneck in metabolic profiling studies. In the case of NMR, PS experiments can be included in metabolite identification workflows, providing additional capability for biomarker discovery.

Review on NMR as a tool to analyse natural products extract directly: Molecular structure elucidation and biological activity analysis.

Natural products, the small organic molecules produced by plants, microbes and invertebrates, often present in the form of a mixture, this leads to the structural characterisation of natural extracts often requiring time-consuming multistep purification procedures. Nuclear magnetic resonance (NMR) technology is traditionally utilised as a tool for the structural elucidation of pure compounds. Contemporarily, an up-to-date trend in the application of NMR in natural product research is shifting to the direct NMR analysis of crude mixtures, to obtain molecular structure and biological activity information without performing cumbersome separation. To review works of literature on the evolution, principle and progress of NMR technologies for analysing mixtures, we focus on the successful application of NMR technologies in direct analysis of natural product extracts. Based on our research experience, academic tracking and extensive literature search, which involved, but not limited to, the use of various databases, like Web of Knowledge and PubMed. The keywords used, in various combinations, to retrieve recent literature on the successful application of NMR technologies to sheer natural product extracts, and excluded artificially natural product mixture and biofluid. NMR technologies for direct natural extracts analysis, including two-dimensional J-resolved spectroscopy (2D-JRES), pure shift NMR, diffusion-ordered NMR spectroscopy (DOSY), statistical correlation spectroscopy (STOCSY), concentration-ordered NMR spectroscopy (CORDY), saturation transfer difference (STD) and water-ligand observed via gradient spectroscopy (WaterLOGSY) were illustrated. By these methods, molecular structure and biological activity information will be directly obtained from NMR analysis of natural products extract, aiming to save experimental time and expenses.

Pure shift FESTA: An ultra-high resolution NMR tool for the analysis of complex fluorine-containing spin systems.

NMR measurements of molecules containing sparse fluorine atoms are becoming increasingly common due to their prevalence in medicinal chemistry. However, the presence of both homonuclear and heteronuclear scalar couplings severely complicates their analysis by NMR. In complex systems, FESTA, a heteronuclear spectral editing method, allows simplified 1 H NMR spectra to be obtained containing only 1 H signals from the same spin system as a chosen 19 F. Despite spectral simplification, signal overlap due to the presence of scalar couplings is often a problem in FESTA spectra. Here, we report a new experiment that combines FESTA and pure shift methods to provide fully decoupled ultra-high resolution FESTA spectra showing a single signal for each 1 H chemical environment. The utility of the method is demonstrated for the analysis of two complex fluorine-containing mixtures of pharmaceutical and biochemical interest.

Efficient determination of scalar coupling networks by band selective decoupled 2D NMR spectroscopy

Scalar (J) couplings constitute one of vital features observed in NMR spectroscopy and show valuable information for molecular structure elucidation and conformation analysis. However, existing J coupling measurement techniques are generally confined by the concerns of resolution, SNR, and experimental efficiency. Herein, we exploit an efficient 2D NMR protocol to deal with the above concerns by enabling rapid, sensitive, and high-resolution J coupling extraction. This protocol delivers full-resolved pure shift 2D absorption-mode spectroscopy to gain great convenience for efficient coupling measurements on overcrowded NMR signals. Resulting from band selective signal evolution, this protocol ensures high signal intensity with full magnetization preservation to meet the demand on probing low-concentration samples. This protocol focuses on accessing coupling information between specific two coupled spin families, and it is not applicable to all possible spin systems. Besides, it adopts echo-train selective refocusing acquisition to accelerate pure shift 2D J-edited implementations into pseudo-2D acquisition, and thus holding the experimental efficiency similar to conventional SERF experiments. Therefore, this study presents a promising tool for efficient extraction of J coupling networks, and takes an important step for coupling measurement techniques with wide applications on molecular conformation elucidation and stereochemical configuration analysis.

Wilcoxon rank-sum tests to detect one-sided mixture alternatives in group sequential clinical trials.

Traditional methods based on the assumption that the treatment distribution is a pure shift of the control distribution may not always hold. The possibility that an individual from the treatment group may not respond to the treatment motivates the use of a mixture distribution for the treatment group. This paper considers two test procedures based on the Wilcoxon rank-sum statistic for a group sequential design to detect the one-sided mixture alternative. Error spending functions are used for the allocation of error rates at each stage. The two tests are evaluated individually in determination of critical values and arm sizes and asymptotic multivariate normality is shown to hold for both. Upon comparison, the tests are presented to be asymptotically equivalent. Both test statistics maintain the Type I error rate even if is misspecified in the design alternative. A more general definition of the treatment effect is used with the mixture distribution. Method of moments estimators and constrained -means estimators for the treatment effect are evaluated.