NMR provides unprecedented molecular information, urgently needed by environmental researchers and policy makers. However, NMR is underutilized in environmental sciences due to the lack of available technologies, limited environmental-specific training opportunities, and easy-to-use workflows. NMR has considerable potential as a discovery tool for novel pollutants, and by-products, exemplified by the recent discovery of the degradation by-product of a rubber additive, 6PPD-quinone, now considered one of the most toxic compounds presently known. This work represents a proof-of-concept case study highlighting the use of NMR to profile effluents from 38 industries across Ontario, Canada. Wastewater effluents from various industrial sectors were analyzed using several 1D and 2D 1H/13C NMR and 19F experiments and were screened both unconcentrated and after lyophilization. Common species could be identified using human metabolic NMR databases, but environmental-specific NMR databases desperately need further development. An example of manually identifying unusual NMR signatures is included; these resulted from phosphinic and phosphonic acids originating from the electroplating industry, for which the environmental impacts are not well understood. Basic 1H NMR quantification is performed using ERETIC, while an optimized approach combining relaxation agents and steady-state-free-precession 19F NMR, to reduce detection limits (at 500 MHz) to sub-ppb (< 1 μg/L) in under 15 min, is demonstrated. The future potential of benchtop NMR (80 MHz) is also considered. This paper represents a guide to others interested in applying NMR spectroscopy to environmental media and demonstrates the potential of NMR as a complementary tool to assist MS in environmental pollutant and by-product discovery.

Background: Sugars are building blocks of polysaccharides, and they are involved in many food and biotechnological applications. However, current methods of analysis have several limitations, preventing our understanding about their functions and roles in different systems, such as biological mixtures. Thus, there is a constant need for analytical methods that allow their rigorous and convenient quantification. NMR-based methodologies have a great potential in sugar analysis, however the traditional Fourier transform approach is associated with significant challenges related to sensitivity, resolution and error prone processing steps. Results: A "clean" and straightforward 13C-detected NMR method for sugar analysis was developed. Nine sugars commonly found as building blocks of polysaccharides were analyzed with 1H and 13C NMR with the later found to be more effective due to the complexity of the mixtures. Minor tautomers were also identified and found to appear in relatively significant amounts in some cases. In addition to the traditional Fourier transform, integration-based approaches, CRAFT-based analysis was assessed for the quantification of sugars in a complex mixture. CRAFT utilizing Bayesian analysis was found to generate high quality and repeatable results in an automated and less error-prone manner. Finally, CRAFT allows for significant improvement in spectral resolution of the 2D HSQC, thus rendering the NMR assignment much more convenient, even for less experience users. Significance: This novel and systematic study for the quantification of sugars in complex mixtures with Fourier transform and CRAFT, will advance our capabilities for sugar quantification. It is also expected to lay the groundwork for the application of time-domain NMR data for targeted analysis and can be extended to other matrices.

Pure shift spectra significantly improve the resolution in NMR by collapsing all multiplet signals into singlets. Homonuclear BB decoupling is typically accomplished by selective inversion of passive spins midway between dwell points or chunks of dwell points during acquisition, and the magnetization is sampled when all the multiplet vector trajectories are at or very near their chemical shift trajectory. In the absence of such synchronous inversion, describing the chemical shift vector trajectory narrows down to (i) mathematically describing the FID in a tabular format of its component signals and (ii) sorting the table into subgroups, each describing a set of vectors (i.e., multiplet signals) that precess in unison around their chemical shift. A processing workflow, based on the CRAFT (Complete Reduction to Amplitude Frequency Table) technique, converts the 2D NMR data set into two-dimensional pure shift CRAFT table (CRAFTps). The CRAFTps table is a mathematical (tabular domain) descriptor of the input data in chemical shift terms that can be used to generate pure shift 2D and 1D spectra. The CRAFTps process is generic and applicable to routinely acquired 2D NMR data and requires no special pulse sequence element. Its applicability is demonstrated with examples of data from three major groups of correlation experiments routinely generated and used in organic structure elucidation by NMR. The CRAFTps process generates pure shift spectra that have significantly better sensitivity (S/N) (as much as ∼30× to 40×), resolution, and peak width compared to the FT2d counterpart. The process requires no user guidance and, hence, minimal bias.

The 2024 Zurich perfluorinated compounds (PFCs) summit reiterated the urgent need for non-selective analytical approaches for PFC detection. 19F NMR holds great potential, however, sensitivity limitations lead to long analysis times and/or the possibility of not detecting low concentration species. Steady State Free Precession (SSFP) NMR collects the signal in a steady state regime, allowing 100's of acquisitions in the timespan of a single traditional NMR scan. Unfortunately, data truncation from SSFP leads to artifacts and spectral broadening with Fourier transform, hindering interpretation. When non-Fourier based time-domain analysis is used, namely, complete reduction to amplitude frequency tables (CRAFT), limitations of SSFP are eliminated while sensitivity gains are retained. This work introduces the combined approach, then applies it for the measurement of PFCs in environmental and biological samples. In all cases, the approach reduces analysis time from many hours to minutes and/or greatly increases the range of compounds detected. For example, when PFOA was spiked into human blood, the detection limit improved ~50-fold vs standard NMR, while in a standard mixture, the approach detected compounds missed by LC-MS/MS. The technique can be adapted to any nucleus providing a facile approach to reduce experiment time and improve sensitivity of NMR in general.

Background: There are a few very specific inflammation biomarkers in blood, namely lipoprotein NMe+ signals of protein clusters (GlycA and GlycB) and a composite resonance of phospholipids (SPC). The relative integrals of these resonances provide clear indication of the unique metabolic changes associated with disease, specifically inflammatory conditions, often related to serious diseases such as cancer or COVID-19 infection. Relatively complicated, yet very efficient experimental methods have been introduced recently (DIRE, JEDI) to suppress the rest of the spectrum, thus allowing measurement of these integrals of interest. Methods: In this study, we introduce a simple alternative processing method using CRAFT (Complete Reduction to Amplitude-Frequency Table), a time-domain (FID) analysis tool which can highlight selected subsets of the spectrum by choice for quantitative analysis. The output of this approach is a direct, spreadsheet-based representation of the required peak amplitude (integral) values, ready for comparative analysis, completely avoiding all the convectional data processing and manipulation steps. The significant advantage of this alternative method is that it only needs a simple water-suppressed 1D spectrum with no further experimental manipulation whatsoever. In addition, there are no pre/post processing steps (such as baseline and/or phase), further minimizing potential dependency on subjective decisions by the user and providing an opportunity to automate the entire process. Results: We applied this methodology to horse serum samples to follow the presence of inflammation for cohorts with or without OCD (Osteochondritis Dissecans) conditions and find diagnostic separation of the of the cohorts through statistical methods. Conclusions: The powerful and simple CRAFT-based approach is suitable to extract selected biomarker information from complex NMR spectra and can be similarly applied to any other biofluid from any source or sample, also retrospectively. There is a potential to extend such a simple analysis to other, previously identified relevant markers as well.

Developments in untargeted nuclear magnetic resonance (NMR) metabolomics enable the profiling of thousands of biological samples. The exploitation of this rich source of information requires a detailed quantification of spectral features. However, the development of a consistent and automatic workflow has been challenging because of extensive signal overlap. To address this challenge, we introduce the software Spectral Automated NMR Decomposition (SAND). SAND follows on from the previous success of time-domain modeling and automatically quantifies entire spectra without manual interaction. The SAND approach uses hybrid optimization with Markov chain Monte Carlo methods, employing subsampling in both time and frequency domains. In particular, SAND randomly divides the time-domain data into training and validation sets to help avoid overfitting. We demonstrate the accuracy of SAND, which provides a correlation of ∼0.9 with ground truth on cases including highly overlapped simulated data sets, a two-compound mixture, and a urine sample spiked with different amounts of a four-compound mixture. We further demonstrate an automated annotation using correlation networks derived from SAND decomposed peaks, and on average, 74% of peaks for each compound can be recovered in single clusters. SAND is available in NMRbox, the cloud computing environment for NMR software hosted by the Network for Advanced NMR (NAN). Since the SAND method uses time-domain subsampling (i.e., random subset of time-domain points), it has the potential to be extended to a higher dimensionality and nonuniformly sampled data.

The goal of the qNMR Summit is to take stock of the status quo and the recent developments in qNMR research and applications in a timely and accurate manner. It provides a platform for both advanced and novice qNMR practitioners to receive a well-rounded update and discuss potential qNMR-related applications and collaborations. For over a decade, scientists from academia, industry, nonprofit institutions, and governmental bodies have focused on the standardization of qNMR methodology, as well as its metrological and pharmacopeial utility. This paper reviews key content of qNMR Summits 1.0 to 4.0 and puts into perspective the outcomes and available transcripts of the October 2019 Summit 5.0, with attendees from the United States, Canada, Japan, Korea, and several European countries. Summit presentations focused on qNMR methodology in the pharmaceutical industry, advanced quantitation algorithms, and promising developments.

The CRAFT (Complete Reduction to Amplitude Frequency Table) technique, based on Bayesian analysis approach, converts FID and/or interferogram (time domain) to a frequency-amplitude table (tabular domain) in a robust, automated, and time-efficient fashion. This mini review/perspective presents an introduction to CRAFT as a processing workflow followed by a discussion of several practical 1D and 2D examples of its applicability and associated benefit. CRAFT provides high quality quantitative results for complex systems without any need for conventional preprocessing steps, such as phase and baseline corrections. Two-dimensional time domain data are typically truncated, particularly in the evolution dimension, and conventional processing after zero-filling and t(1max)-matched apodization masks potentially available peak resolution. The line broadening introduced by extensive zero-filling and severe apodization functions leads to the lack of clear resolution of cross peaks. CRAFT decimation of interferograms, on the other hand, requires minimal or no apodization prior to extraction of the NMR parameters and significantly improves the spectral linewidth of the cross peaks along F-1 dimension compared to conventional (FT) processing. The tabular representation of the CRAFT2d cross peaks information can be visualized in a variety of frequency domain formats for conventional spectral interpretation as well as quantitative applications. A simple workflow to generate in silico oversampled interferogram (iSOS) is presented, and its potential benefit in CRAFT decimation of highly crowded 2D NMR is demonstrated. This report is meant as a collective thesis to present a potentially new paradigm in data processing that questions the need for hitherto unchallenged preprocessing steps, such as phase and baseline correction in 1D and zero-fill/severe apodization in 2D.

The recently published CRAFT (complete reduction to amplitude frequency table) technique converts the raw FID data (i.e., time domain data) into a table of frequencies, amplitudes, decay rate constants, and phases. It offers an alternate approach to decimate time-domain data, with minimal preprocessing step. It has been shown that application of CRAFT technique to process the t(1) dimension of the 2D data significantly improved the detectable resolution by its ability to analyze without the use of ubiquitous apodization of extensively zero-filled data. It was noted earlier that CRAFT did not resolve sinusoids that were not already resolvable in time-domain (i.e., t(1)max dependent resolution). We present a combined NUS-IST-CRAFT approach wherein the NUS acquisition technique (sparse sampling technique) increases the intrinsic resolution in time-domain (by increasing t(1)max), IST fills the gap in the sparse sampling, and CRAFT processing extracts the information without loss due to any severe apodization. NUS and CRAFT are thus complementary techniques to improve intrinsic and usable resolution. We show that significant improvement can be achieved with this combination over conventional NUS-IST processing. With reasonable sensitivity, the models can be extended to significantly higher t(1)max to generate an indirect-DEPT spectrum that rivals the direct observe counterpart.

Two‐dimensional (2D) data are typically truncated in both dimensions, but invariably and severely so in the indirect dimension. These truncated FIDs and/or interferograms are extensively zero filled, and Fourier transformation of such zero‐filled data is always preceded by a rapidly decaying apodization function. Hence, the frequency line width in the spectrum (at least parallel to the evolution dimension) is almost always dominated by the apodization function. Such apodization‐driven line broadening in the indirect (t1) dimension leads to the lack of clear resolution of cross peaks in the 2D spectrum. Time‐domain analysis (i.e. extraction of frequency, amplitudes, line width, and phase parameters directly from the FID, in this case via Bayesian modeling into a tabular format) of NMR data is another approach for spectral resonance characterization and quantification. The recently published complete reduction to amplitude frequency table (CRAFT) technique converts the raw FID data (i.e. time‐domain data) into a table of frequencies, amplitudes, decay rate constants, and phases. CRAFT analyses of time‐domain data require minimal or no apodization prior to extraction of the four parameters. We used the CRAFT processing approach for the decimation of the interferograms and compared the results from a variety of 2D spectra against conventional processing with and without linear prediction. The results show that use of the CRAFT technique to decimate the t1 interferograms yields much narrower spectral line width of the resonances, circumventing the loss of resolution due to apodization. Copyright © 2016 John Wiley & Sons, Ltd.

In high-throughput scenarios, a large number of similar NMR spectra from a single study need to be analyzed. The complexity of the data required the use of spectral databases to characterize resonances of interest and extract quantitative information. The recently reported CRAFT (Complete Reduction to Amplitude Frequency Table) technique, based on a Bayesian analysis approach, converts a time-domain FID to a frequency-amplitude table in a robust, automated, and time-efficient fashion. We report the application of the CRAFT technique to the extraction of quantitative information from the NMR spectra of complex mixtures - the targeted analysis of spent media from mammalian cell cultures and the untargeted profiling of soy supplement extracts. CRAFT, in a significantly automated fashion, converts the raw NMR spectra into a data-mining-friendly spreadsheet format with high fidelity and accuracy. The reported examples clearly demonstrate that the automated, time-domain data reduction by the CRAFT technique gives comparable results to traditional approaches. Moreover, the approach described herein allows for iterative adjustment of the post-CRAFT NMR parametric filters of the tabular data (such as linewidth and/or amplitude and/or frequency window thresholds) for reexamination. Such iterative parametric filters in conjunction with statistical analysis/guidance have the potential opportunity to develop analyte fingerprint databases for subsequent sample screening and library comparisons. Thus, this technique potentially allows for the development of rapid screening methods, both targeted and untargeted, to be implemented easily, and be employed effectively in high throughput environments.

A modified version of the attached proton test (APT) sequence for 13C spectral editing, which we call CRisis‐APT (CRAPT), is developed and tested on representative organic compounds. CRAPT incorporates 13C compensation for refocusing inefficiency with synchronized inversion sweeps (CRISIS) pulses in combination with 1H broadband inversion pulses to give improved compensation for variations in 1JCH along with improved refocusing efficiency. It is shown that CRAPT gives edited 13C spectra with only small losses in sensitivity (between 8% and 15% for strychnine, 1, menthol, 2, cholecalciferol, 3, and isotachysterol, 4), compared with basic 13C spectra obtained on the same compounds. CRAPT also gives significantly better signal/noise than DEPTQ for nonprotonated carbons. Therefore, we conclude that CRAPT is an improvement over APT or DEPTQ or a combination of DEPT135 with a full 13C spectrum for routine 13C spectral editing of organic compounds. Copyright © 2014 John Wiley & Sons, Ltd.

The intrinsic quantitative nature of NMR is increasingly exploited in areas ranging from complex mixture analysis (as in metabolomics and reaction monitoring) to quality assurance/control (QA/QC). One of the key advantages of NMR over other methods for quantitative analysis is that molar concentration can be determined directly from signal intensity, regardless of the chemical nature, and can be accomplished without requirement of reference substances. In this short review, we attempt to capture the various aspects of data collection and data analysis for NMR quantitative analysis of complex mixtures. While the requirements for quantitative data collection have been well recognized, the data analysis methodologies are fast growing. With significant increase in the computation speed, time-domain analysis (an alternative to FT) is emerging as potential alternative to frequency-domain analysis and poses a good opportunity for automatable processes for high-throughput NMR quantitation.

The intrinsic quantitative nature of NMR is increasingly exploited in areas ranging from complex mixture analysis (as in metabolomics and reaction monitoring) to quality assurance/control. Complex NMR spectra are more common than not, and therefore, extraction of quantitative information generally involves significant prior knowledge and/or operator interaction to characterize resonances of interest. Moreover, in most NMR‐based metabolomic experiments, the signals from metabolites are normally present as a mixture of overlapping resonances, making quantification difficult. Time‐domain Bayesian approaches have been reported to be better than conventional frequency‐domain analysis at identifying subtle changes in signal amplitude. We discuss an approach that exploits Bayesian analysis to achieve a complete reduction to amplitude frequency table (CRAFT) in an automated and time‐efficient fashion – thus converting the time‐domain FID to a frequency‐amplitude table. CRAFT uses a two‐step approach to FID analysis. First, the FID is digitally filtered and downsampled to several sub FIDs, and secondly, these sub FIDs are then modeled as sums of decaying sinusoids using the Bayesian approach. CRAFT tables can be used for further data mining of quantitative information using fingerprint chemical shifts of compounds of interest and/or statistical analysis of modulation of chemical quantity in a biological study (metabolomics) or process study (reaction monitoring) or quality assurance/control. The basic principles behind this approach as well as results to evaluate the effectiveness of this approach in mixture analysis are presented. Copyright © 2013 John Wiley & Sons, Ltd.

The epsilon 4 (E4) allele of apolipoprotein E (apoE) is the most significant genetic risk factor for developing late-onset Alzheimer's disease (AD). Cognitively normal apoE4 carriers have altered glucose utilization in brain regions affected in AD as determined by PET. Functional MRI and EEG measurements during memory tasks suggest altered connectivity and broader utilization of brain regions even in young cognitively healthy E4 carriers. E4 is also associated with smaller hippocampal volume and faster rates of atrophy in AD patients. Hippocampal atrophy is also often found in epilepsy. We recently reported the emergence of a seizure phenotype in aged apoE4 targeted replacement (TRE4) mice. To investigate structural brain changes in TRE4 mice, we performed high resolution in vivo MRI of young and aged TR mice with a 7 Tesla Varian spectrometer. Thirty-three slice images (250μm thickness, 98x98μm in-plane resolution, no gap) were acquired for each mouse. Image analysis was performed using custom software or hand drawn regions of interest to determine volumes. All imaging and analysis was done blinded. We report that hippocampal volume is reduced in aged TRE4 mice compared to TRE2 and TRE3 mice. Although young mice do not display a seizure phenotype, young female mice have reduced hippocampal volume and increased ventricular volume suggesting that apoE4 may result in reduced hippocampal development and predisposition to seizures. Seizure phenotype in TRE4 male mice is not completely penetrant, and aged TRE4 male mice with a severe seizure phenotype have reduced hippocampal volume in comparison to aged TRE4 male mice with very mild or no seizure phenotype suggesting a relationship between seizures and hippocampal volume in TRE4 mice. Stereological analysis of the hippocampus of TR mice is in progress and may reveal the cellular basis of the reduced hippocampal volume measured by MRI. Diffusion tensor imaging is also being employed to determine if TRE4 mice have further structural changes detectible by imaging. Our results provide evidence that old and young TRE4 mice have structural brain changes (reduced hippocampal volume) compared to TRE3 or TRE2 mice, suggesting a role for apoE4 in hippocampal integrity and possibly development.

We propose a family of doubly compensated multiplicity‐edited heteronuclear single quantum coherence (HSQC) pulse sequences. The key difference between our proposed sequences and the compensation of refocusing inefficiency with synchronized inversion sweeps (CRISIS)‐HSQC experiments they are based on is that the conventional rectangular 180° pulses on the proton channel in the latter have been replaced by the computer‐optimized broadband inversion pulses (BIPs) with superior inversion performance as well as much improved tolerance to B 1 field inhomogeneity. Moreover, all adiabatic carbon 180° pulses during the INEPT and reverse‐INEPT periods in the CRISIS‐HSQC sequences have also been replaced with the much shorter BIPs, while the adiabatic sweeps during the heteronuclear spin echo for multiplicity editing are kept in place in order to maintain the advantage of the CRISIS feature of the original sequences, namely J ‐independent refocusing of the one‐bond 1 H 13 C coupling constants. These modifications have also been implemented to the preservation of equivalent pathways (PEP)‐HSQC experiments. We demonstrate through a detailed comparison that replacing the proton 180° pulses with the BIPs provide additional sensitivity gain that can be mainly attributed to the improved tolerance to B 1 field inhomogeneity of the BIPs. The proposed sequences can be easily adapted for 19 F 13 C correlations. Copyright © 2008 John Wiley & Sons, Ltd.

Heteronuclear 19F-1H cross-polarization can be used effectively as a tool for both spectral filtering and editing in the NMR analysis of the increasing number of fluorine-containing compounds encountered in drug discovery. Combined with LC-MS, three-dimensional 19F-1H heteronuclear TOCSY filtered experiments based on this approach have enabled the simultaneous identification of a mixture of closely related dexamethasone derivatives without the need for isolation.

The nuclear Overhauser effect (NOE) is undoubtedly one of the most useful tools in NMR spectroscopy and is widely used in solving structural and conformational problems of small organic molecules and macromolecular systems alike. In particular, measurement of the kinetics of the NOE, often facilitated by selective 1D NOE buildup experiments, can generate invaluable quantitative distance information for the molecule being investigated. In practice, analysis of such kinetic NOE data routinely assumes a first-order approximation of the initial buildup rate. However, often times such an approximation holds true only for the shortest mixing times. As shown by Macura and others, the linear range of the NOE buildup obtained from 2D NOESY and exchange experiments can be substantially extended by simply scaling the NOE cross-peaks against the corresponding diagonal peaks. In this note, we demonstrate through a detailed analysis that the same approach can be applied to the analysis of 1D NOE data obtained with the DPFGSE NOE pulse sequence, one of the most widely used selective 1D NOE experiments today. We show that this approach allows the inclusion of data points acquired with much longer mixing times in the analysis and thus considerably improves the accuracy of the measured cross-relaxation rates and internuclear distances, while considerably simplifying the data analysis. Similar results can be obtained for the rotating frame DPFGSE ROE experiment.