Nonuniform sampling and non-Fourier signal processing methods in multidimensional NMR

Beginning with the introduction of Fourier Transform NMR by Ernst and Anderson in 1966, time domain measurement of the impulse response (the free induction decay, FID) consisted of sampling the signal at a series of discrete intervals. For compatibility with the discrete Fourier transform (DFT), the intervals are kept uniform, and the Nyquist theorem dictates the largest value of the interval sufficient to avoid aliasing. With the proposal by Jeener of parametric sampling along an indirect time dimension, extension to multidimensional experiments employed the same sampling techniques used in one dimension, similarly subject to the Nyquist condition and suitable for processing via the discrete Fourier transform. The challenges of obtaining high-resolution spectral estimates from short data records using the DFT were already well understood, however. Despite techniques such as linear prediction extrapolation, the achievable resolution in the indirect dimensions is limited by practical constraints on measuring time. The advent of non-Fourier methods of spectrum analysis capable of processing nonuniformly sampled data has led to an explosion in the development of novel sampling strategies that avoid the limits on resolution and measurement time imposed by uniform sampling. The first part of this review discusses the many approaches to data sampling in multidimensional NMR, the second part highlights commonly used methods for signal processing of such data, and the review concludes with a discussion of other approaches to speeding up data acquisition in NMR

A systematic review of cost-effectiveness analyses of complex wound interventions reveals optimal treatments for specific wound types.

BackgroundComplex wounds present a substantial economic burden on healthcare systems, costing billions of dollars annually in North America alone. The prevalence of complex wounds is a significant patient and societal healthcare concern and cost-effective wound care management remains unclear. This article summarizes the cost-effectiveness of interventions for complex wound care through a systematic review of the evidence base.MethodsWe searched multiple databases (MEDLINE, EMBASE, Cochrane Library) for cost-effectiveness studies that examined adults treated for complex wounds. Two reviewers independently screened the literature, abstracted data from full-text articles, and assessed methodological quality using the Drummond 10-item methodological quality tool. Incremental cost-effectiveness ratios were reported, or, if not reported, calculated and converted to United States Dollars for the year 2013.ResultsOverall, 59 cost-effectiveness analyses were included; 71% (42 out of 59) of the included studies scored 8 or more points on the Drummond 10-item checklist tool. Based on these, 22 interventions were found to be more effective and less costly (i.e., dominant) compared to the study comparators: 9 for diabetic ulcers, 8 for venous ulcers, 3 for pressure ulcers, 1 for mixed venous and venous/arterial ulcers, and 1 for mixed complex wound types.ConclusionsOur results can be used by decision-makers in maximizing the deployment of clinically effective and resource efficient wound care interventions. Our analysis also highlights specific treatments that are not cost-effective, thereby indicating areas of resource savings. Please see related article: http://dx.doi.org/10.1186/s12916-015-0288-5

How can diagnostic assessment programs be implemented to enhance inter-professional collaborative care for cancer?

BackgroundInter-professional collaborative care (ICC) for cancer leads to multiple system, organizational, professional, and patient benefits, but is limited by numerous challenges. Empirical research on interventions that promote or enable ICC is sparse so guidance on how to achieve ICC is lacking. Research shows that ICC for diagnosis could be improved. Diagnostic assessment programs (DAPs) appear to be a promising model for enabling ICC. The purpose of this study was to explore how DAP structure and function enable ICC, and whether that may be associated with organizational and clinical outcomes.MethodsA case study approach will be used to explore ICC among eight DAPs that vary by type of cancer (lung, breast), academic status, and geographic region. To describe DAP function and outcomes, and gather information that will enable costing, recommendations expressed in DAP standards and clinical guidelines will be assessed through retrospective observational study. Data will be acquired from databases maintained by participating DAPs and the provincial cancer agency, and confirmed by and supplemented with review of medical records. We will conduct a pilot study to explore the feasibility of estimating the incremental cost-effectiveness ratio using person-level data from medical records and other sources. Interviews will be conducted with health professionals, staff, and referring physicians from each DAP to learn about barriers and facilitators of ICC. Qualitative methods based on a grounded approach will be used to guide sampling, data collection and analysis.DiscussionFindings may reveal opportunities for unique structures, interventions or tools that enable ICC that could be developed, implemented, and evaluated through future research. This information will serve as a formative needs assessment to identify the nature of ongoing or required improvements, which can be directly used by our decision maker collaborators, and as a framework by policy makers, cancer system managers, and DAP managers elsewhere to strategically plan for and implement diagnostic cancer services

DO IT Trial: vitamin D Outcomes and Interventions in Toddlers - a TARGet Kids! randomized controlled trial.

BackgroundVitamin D levels are alarmingly low (<75 nmol/L) in 65-70% of North American children older than 1 year. An increased risk of viral upper respiratory tract infections (URTI), asthma-related hospitalizations and use of anti-inflammatory medication have all been linked with low vitamin D. No study has determined whether wintertime vitamin D supplementation can reduce the risk of URTI and asthma exacerbations, two of the most common and costly illnesses of early childhood. The objectives of this study are: 1) to compare the effect of 'high dose' (2000 IU/day) vs. 'standard dose' (400 IU/day) vitamin D supplementation in achieving reductions in laboratory confirmed URTI and asthma exacerbations during the winter in preschool-aged Canadian children; and 2) to assess the effect of 'high dose' vitamin D supplementation on vitamin D serum levels and specific viruses that cause URTI.Methods/designThis study is a pragmatic randomized controlled trial. Over 4 successive winters we will recruit 750 healthy children 1-5 years of age. Participating physicians are part of a primary healthcare research network called TARGet Kids!. Children will be randomized to the 'standard dose' or 'high dose' oral supplemental vitamin D for a minimum of 4 months (200 children per group). Parents will obtain a nasal swab from their child with each URTI, report the number of asthma exacerbations and complete symptom checklists. Unscheduled physician visits for URTIs and asthma exacerbations will be recorded. By May, a blood sample will be drawn to determine vitamin D serum levels. The primary analysis will be a comparison of URTI rate between study groups using a Poisson regression model. Secondary analyses will compare vitamin D serum levels, asthma exacerbations and the frequency of specific viral agents between groups.DiscussionIdentifying whether vitamin D supplementation of preschoolers can reduce wintertime viral URTIs and asthma exacerbations and what dose is optimal may reduce population wide morbidity and associated health care and societal costs. This information will assist in determining practice and health policy recommendations related to vitamin D supplementation in healthy Canadian preschoolers

Identification of inhibitors of Plasmodium falciparum phosphoethanolamine methyltransferase using an enzyme-coupled transmethylation assay

<p>Abstract</p> <p>Background</p> <p>The phosphoethanolamine methyltransferase, PfPMT, of the human malaria parasite <it>Plasmodium falciparum</it>, a member of a newly identified family of phosphoethanolamine methyltransferases (PMT) found solely in some protozoa, nematodes, frogs, and plants, is involved in the synthesis of the major membrane phospholipid, phosphatidylcholine. PMT enzymes catalyze a three-step S-adenosylmethionine-dependent methylation of the nitrogen atom of phosphoethanolamine to form phosphocholine. In <it>P. falciparum</it>, this activity is a limiting step in the pathway of synthesis of phosphatidylcholine from serine and plays an important role in the development, replication and survival of the parasite within human red blood cells.</p> <p>Results</p> <p>We have employed an enzyme-coupled methylation assay to screen for potential inhibitors of PfPMT. In addition to hexadecyltrimethylammonium, previously known to inhibit PfPMT, two compounds dodecyltrimethylammonium and amodiaquine were also found to inhibit PfPMT activity <it>in vitro</it>. Interestingly, PfPMT activity was not inhibited by the amodiaquine analog, chloroquine, or other aminoquinolines, amino alcohols, or histamine methyltransferase inhibitors. Using yeast as a surrogate system we found that unlike wild-type cells, yeast mutants that rely on PfPMT for survival were sensitive to amodiaquine, and their phosphatidylcholine biosynthesis was inhibited by this compound. Furthermore NMR titration studies to characterize the interaction between amoidaquine and PfPMT demonstrated a specific and concentration dependent binding of the compound to the enzyme.</p> <p>Conclusion</p> <p>The identification of amodiaquine as an inhibitor of PfPMT <it>in vitro </it>and in yeast, and the biophysical evidence for the specific interaction of the compound with the enzyme will set the stage for the development of analogs of this drug that specifically inhibit this enzyme and possibly other PMTs.</p

GLOFRIM v1.0 - A globally applicable computational framework for integrated hydrological-hydrodynamic modelling

We here present GLOFRIM, a globally applicable computational framework for integrated hydrological-hydrodynamic modelling. GLOFRIM facilitates spatially explicit coupling of hydrodynamic and hydrologic models and caters for an ensemble of models to be coupled. It currently encompasses the global hydrological model PCR-GLOBWB as well as the hydrodynamic models Delft3D Flexible Mesh (DFM; solving the full shallow-water equations and allowing for spatially flexible meshing) and LISFLOOD-FP (LFP; solving the local inertia equations and running on regular grids). The main advantages of the framework are its open and free access, its global applicability, its versatility, and its extensibility with other hydrological or hydrodynamic models. Before applying GLOFRIM to an actual test case, we benchmarked both DFM and LFP for a synthetic test case. Results show that for sub-critical flow conditions, discharge response to the same input signal is near-identical for both models, which agrees with previous studies. We subsequently applied the framework to the Amazon River basin to not only test the framework thoroughly, but also to perform a first-ever benchmark of flexible and regular grids on a large-scale. Both DFM and LFP produce comparable results in terms of simulated discharge with LFP exhibiting slightly higher accuracy as expressed by a Kling-Gupta efficiency of 0.82 compared to 0.76 for DFM. However, benchmarking inundation extent between DFM and LFP over the entire study area, a critical success index of 0.46 was obtained, indicating that the models disagree as often as they agree. Differences between models in both simulated discharge and inundation extent are to a large extent attributable to the gridding techniques employed. In fact, the results show that both the numerical scheme of the inundation model and the gridding technique can contribute to deviations in simulated inundation extent as we control for model forcing and boundary conditions. This study shows that the presented computational framework is robust and widely applicable. GLOFRIM is designed as open access and easily extendable, and thus we hope that other large-scale hydrological and hydrodynamic models will be added. Eventually, more locally relevant processes would be captured and more robust model inter-comparison, benchmarking, and ensemble simulations of flood hazard on a large scale would be allowed for

NMR and Metabolomics—A Roadmap for the Future

Metabolomics investigates global metabolic alterations associated with chemical, biological, physiological, or pathological processes. These metabolic changes are measured with various analytical platforms including liquid chromatography-mass spectrometry (LC-MS), gas chromatographymass spectrometry (GC-MS) and nuclear magnetic resonance spectroscopy (NMR). While LC-MS methods are becoming increasingly popular in the field of metabolomics (accounting for more than 70% of published metabolomics studies to date), there are considerable benefits and advantages to NMR-based methods for metabolomic studies. In fact, according to PubMed, more than 926 papers on NMR-based metabolomics were published in 2021—the most ever published in a given year. This suggests that NMR-based metabolomics continues to grow and has plenty to offer to the scientific community. This perspective outlines the growing applications of NMR in metabolomics, highlights several recent advances in NMR technologies for metabolomics, and provides a roadmap for future advancements

Nonuniform sampling and maximum entropy reconstruction in multidimensional NMR

NMR spectroscopy is one of the most powerful and versatile analytic tools available to chemists. The discrete Fourier transform (DFT) played a seminal role in the development of modern NMR, including the multidimensional methods that are essential for characterizing complex biomolecules. However, it suffers from well-known limitations: chiefly the difficulty in obtaining high-resolution spectral estimates from short data records. Because the time required to perform an experiment is proportional to the number of data samples, this problem imposes a sampling burden for multidimensional NMR experiments. At high magnetic field, where spectral dispersion is greatest, the problem becomes particularly acute. Consequently multidimensional NMR experiments that rely on the DFT must either sacrifice resolution in order to be completed in reasonable time or use inordinate amounts of time to achieve the potential resolution afforded by high-field magnets.Maximum entropy (MaxEnt) reconstruction is a non-Fourier method of spectrum analysis that can provide high-resolution spectral estimates from short data records. It can also be used with nonuniformly sampled data sets. Since resolution is substantially determined by the largest evolution time sampled, nonuniform sampling enables high resolution while avoiding the need to uniformly sample at large numbers of evolution times. The Nyquist sampling theorem does not apply to nonuniformly sampled data, and artifacts that occur with the use of nonuniform sampling can be viewed as frequency-aliased signals. Strategies for suppressing nonuniform sampling artifacts include the careful design of the sampling scheme and special methods for computing the spectrum. Researchers now routinely report that they can complete an N-dimensional NMR experiment 3 times faster (a 3D experiment in one ninth of the time). As a result, high-resolution three- and four-dimensional experiments that were prohibitively time consuming are now practical. Conversely, tailored sampling in the indirect dimensions has led to improved sensitivity.Further advances in nonuniform sampling strategies could enable further reductions in sampling requirements for high resolution NMR spectra, and the combination of these strategies with robust non-Fourier methods of spectrum analysis (such as MaxEnt) represent a profound change in the way researchers conduct multidimensional experiments. The potential benefits will enable more advanced applications of multidimensional NMR spectroscopy to study biological macromolecules, metabolomics, natural products, dynamic systems, and other areas where resolution, sensitivity, or experiment time are limiting. Just as the development of multidimensional NMR methods presaged multidimensional methods in other areas of spectroscopy, we anticipate that nonuniform sampling approaches will find applications in other forms of spectroscopy

NMR and Metabolomics—A Roadmap for the Future

Metabolomics investigates global metabolic alterations associated with chemical, biological, physiological, or pathological processes. These metabolic changes are measured with various analytical platforms including liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS) and nuclear magnetic resonance spectroscopy (NMR). While LC-MS methods are becoming increasingly popular in the field of metabolomics (accounting for more than 70% of published metabolomics studies to date), there are considerable benefits and advantages to NMR-based methods for metabolomic studies. In fact, according to PubMed, more than 926 papers on NMR-based metabolomics were published in 2021—the most ever published in a given year. This suggests that NMR-based metabolomics continues to grow and has plenty to offer to the scientific community. This perspective outlines the growing applications of NMR in metabolomics, highlights several recent advances in NMR technologies for metabolomics, and provides a roadmap for future advancements