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Simplified diagram of a nuclear magnetic resonance spectrometer. At the heart of the 1H NMR spectrometer is a superconducting magnet. This must be kept at 4 K, so needs to be emerged in liquid helium, which is prevented from evaporating by vacuum and nitrogen jackets. The probe, containing the RF coil sits in the bottom of the magnet within its bore. The sample is always contained within the 1H NMR tube; it is gently dropped into the probe on a cushion of air. Here the superconducting magnet causes the protons to spin and the RF coil sends RF pulses to excite them and collects the free-induction decay as they relax back to equilibrium. The pulse programs are created using the computer and sent to the console, which acts both as a radiofrequency transmitter and receiver. The signals are amplified on transmission and receipt. The FIDs are Fourier transformed (mathematically deconvoluted) to produce 1H NMR spectra of intensity versus chemical shift (δ) using the computer.
Source publication
The ability to phenotype metabolic profiles in serum has increased substantially in recent years with the advent of metabolomics. Metabolomics is the study of the metabolome, defined as those molecules with an atomic mass less than 1.5 kDa. There are two main metabolomics methods: mass spectrometry (MS) and proton nuclear magnetic resonance (1H NMR...
Context in source publication
Context 1
... H NMR spectroscopy is a technique that exploits the magnetic properties of protons in order to obtain information about the structure of a molecule, and hence its identity [17]. The sample is placed in a strong magnetic field and electromagnetic radiation, in the form of radiofrequency pulses, is used to excite the protons (Fig. 1). As the protons relax back to equilibrium the energy is recorded as an oscillating electromagnetic signal, called the free induction decay (FID). This is analogous to a number of bells ringing out after they have been simultaneously struck e each frequency of each bell will be overlaid and they will decay together. This complex ...Similar publications
In Van cats, changes in serum mineral (Na-Sodium, K-Potassium, Ca-Calcium, P-Phosphorus, Mg-Magnesium, Cl-Chlorine and Fe-Iron) and metabolite concentrations (TG-Triglycerides, COL-Cholesterol, T.Prot.-Total protein and ALP-Alkaline phosphatase) were investigated before, during and after the pregnancy. A total of 22 mature cats (19 queens and 3 fer...
Citations
... However, few studies have examined the use of metabolomics and HF mortality. [6][7][8][9] Nuclear magnetic resonance (NMR) spectroscopy has been used to study metabolomics in cardiovascular disease 10 and shown high comparability with conventional chemistry measurements. 11 Specifically, the Vantera NMR Clinical Analyzer is a clinically deployed high-throughput targeted platform, on which a metabolomics assay suitable for large epidemiological studies was developed. ...
... 11 Specifically, the Vantera NMR Clinical Analyzer is a clinically deployed high-throughput targeted platform, on which a metabolomics assay suitable for large epidemiological studies was developed. 10,[12][13][14][15][16] This targeted metabolomics assay can measure several classes of metabolites from stored blood samples, including a standard lipid panel, lipoprotein particles, ketone bodies, branched-chain amino acids, additional small molecule metabolites, and a marker of systemic inflammation. We chose to evaluate a commercially available assay capable of measuring several metabolites from a single blood sample, because of its clinical applicability. ...
BACKGROUND
Heart failure is heterogeneous syndrome with persistently high mortality. Nuclear magnetic resonance spectroscopy enables high-throughput metabolomics, suitable for precision phenotyping. We aimed to use targeted metabolomics to derive a metabolic risk score (MRS) that improved mortality risk stratification in heart failure.
METHODS
Nuclear magnetic resonance was used to measure 21 metabolites (lipoprotein subspecies, branched-chain amino acids, alanine, GlycA, ketone bodies, glucose, and citrate) in plasma collected from a heart failure community cohort. The MRS was derived using LASSO penalized Cox regression and temporal validation. The association between the MRS and mortality and whether risk stratification was improved over the Meta-Analysis Global Group in Chronic Heart Failure clinical risk score and NT-proBNP (N-terminal pro-B-type natriuretic peptide) levels were assessed.
RESULTS
The study included 1382 patients (median age, 78 years, 52% men, 43% reduced ejection fraction) with a 5-year survival rate of 48% (95% CI, 46%–51%). The MRS included 9 metabolites measured. In the validation data set, a 1 SD increase in the MRS was associated with a large increased rate of death (hazard ratio, 2.2 [95% CI, 1.9–2.5]) that remained after adjustment for Meta-Analysis Global Group in Chronic Heart Failure score and NT-proBNP (hazard ratio, 1.6 [95% CI, 1.3–1.9]). These associations did not differ by ejection fraction. The integrated discrimination and net reclassification indices, and Uno’s C statistic, indicated that the addition of the MRS improved discrimination over Meta-Analysis Global Group in Chronic Heart Failure and NT-proBNP.
CONCLUSIONS
This MRS developed in a heart failure community cohort was associated with a large excess risk of death and improved risk stratification beyond an established risk score and clinical markers.
... Additionally, metal doping can act as a promoter to generate more oxygen vacancies, leading to improved activation of reactants and lower reaction barriers. [46][47][48][49] Zhou et al. [72] conducted DFT calculations to investigate the effects of low-concentration (<2%) single Ga substitution and high-concentration (2-10%) www.advancedsciencenews.com www.small-journal.com double Ga substitution on the catalytic activity of CeO 2 for alkyne hydrogenation. ...
Activation of small molecules is considered to be a central concern in the theoretical investigation of environment‐ and energy‐related catalytic conversions. Sub‐nanostructured frustrated Lewis pairs (FLPs) have been an emerging research hotspot in recent years due to their advantages in small molecule activation. Although the progress of catalytic applications of FLPs is increasingly reported, the fundamental theories related to the structural formation, site regulation, and catalytic mechanism of FLPs have not yet been fully developed. Given this, it is attempted to demonstrate the underlying theory of FLPs formation, corresponding regulation methods, and its activation mechanism on small molecules using CeO2 as the representative metal oxide. Specifically, this paper presents three fundamental principles for constructing FLPs on CeO2 surfaces, and feasible engineering methods for the regulation of FLPs sites are presented. Furthermore, cases where typical small molecules (e.g., hydrogen, carbon dioxide, methane oxygen, etc.) are activated over FLPs are analyzed. Meanwhile, corresponding future challenges for the development of FLPs‐centered theory are presented. The insights presented in this paper may contribute to the theories of FLPs, which can potentially provide inspiration for the development of broader environment‐ and energy‐related catalysis involving small molecule activation.
... In this sense, different metabolomic studies were carried out in patients who suffered a stroke. Thus, metabolomic analysis via nuclear magnetic resonance (NMR) allows determining the concentrations of metabolites in different biofluids, and the simultaneous detection and quantification of these molecules at a low cost and high speed [16][17][18]. ...
More than 12 million people around the world suffer a stroke every year, one every 3 s. Stroke has a variety of causes and is often the result of a complex interaction of risk factors related to age, genetics, gender, lifestyle, and some cardiovascular and metabolic diseases. Despite this evidence, it is not possible to prevent the onset of stroke. The use of innovative methods for metabolite analysis has been explored in the last years to detect new stroke biomarkers. We use NMR spectroscopy to identify small molecule variations between different stages of stroke risk. The Framingham Stroke Risk Score was used in people over 63 years of age living in long-term care facilities (LTCF) to calculate the probability of suffering a stroke. Using this parameter, three study groups were formed: low stroke risk (LSR, control), moderate stroke risk (MSR) and high stroke risk (HSR). Univariate statistical analysis showed seven metabolites with increasing plasma levels across different stroke risk groups, from LSR to HSR: isoleucine, asparagine, formate, creatinine, dimethylsulfone and two unidentified molecules, which we termed “unknown-1” and “unknown-3”. These metabolic markers can be used for early detection and to detect increasing stages of stroke risk more efficiently.
... It has emerged as a potential method for identifying new disease-risk biomarkers and offers novel perspectives on the molecular mechanisms, biological processes, and disease pathways implicated [3]. In the field of metabolomic profiling, serum proton nuclear magnetic resonance (1H-NMR) spectroscopy allows for the simultaneous evaluation of a large number of circulating metabolites in a fast and reproducible manner [4]. To date, we and others have demonstrated this tool to be a valid and robust method to assess inflammation in different diseases with an underlying metabolic mechanism [5][6][7]. ...
Background and aim
Circulating biomarkers of metabolic and cardiovascular diseases can help in the early detection and prevention of those diseases. Using proton nuclear magnetic resonance (1H-NMR), we aimed to study the plasma levels of low-molecular-weight metabolites (LMWMs) in a cohort of 307 patients with metabolic diseases to assess their relationships with type-2 diabetes (T2D) and incident atherosclerotic cardiovascular disease (ASCVD).
Methods
We conducted a cross-sectional and prospective study. We included 307 patients attending the Lipid Unit of our University Hospital for the treatment of the following metabolic disturbances and associated disorders: T2D (73.9%), obesity (58.7%), and hypertension (55.1%). 1H-NMR was used to study the plasma levels of 13 LMWMs. LMWM serum concentrations were evaluated in patients with and without T2D. and the correlations with several parameters and their associations with T2D were analyzed. The association between LMWM levels at baseline and the development of ASCVD in patients with T2D after 10 years of follow-up was also evaluated.
Results
Among the LMWMs measured, the branched-chain amino acids (BCAAs) valine, leucine and isoleucine showed a positive association with several clinical and lipid-related biochemical parameters and inflammatory markers (p < 0.05). Likewise, these three BCAAS were associated with diabetes even after adjusting for covariates (p < 0.05). During the follow-up period of 10 years, 29 of the 185 patients with diabetes at baseline (15.68%) developed ASCVD. After adjusting for clinical covariates, baseline levels of valine and alanine were associated with the development of ASCVD (p < 0.05).
Conclusion
Overall, our results indicated that plasma levels of LMWMs measured by 1H-NMR could be potential biomarkers associated with T2D. Moreover, alanine and valine can help in the early detection of the cardiovascular risk associated with this metabolic disease.
... 16−18 Acute and chronic inflammatory processes are associated with higher levels of circulating glycosylated proteins that result from the addition of glucosamine-rich and galactosamine-rich glycan chains to specific protein residues. 19 The specific response of the acetyl group of the galactosamine-or glucosamine-protein bond and the acetyl groups of Nacetylneuraminic acid under a magnetic field can be characterized as the basis of glycoprotein (Glyc)A or GlycB signals, respectively, identified by proton nuclear magnetic resonance ( 1 H NMR). 20 1 H NMR also offers the possibility of simultaneous advanced lipoprotein profiling 21,22 and is useful and efficient for determining the risk of metabolic-related pathologies in certain clinical populations. 23,24 Thus, based on (1) the potential of 1 H NMR to analyze, in a single acquisition, specific glycoprotein and lipoprotein parameters from a small volume of blood plasma, (2) the relationship between metabolic and inflammatory processes, and (3) the importance of detecting metabolic changes (in lipoproteins and protein glycosylation) that occur in the early stages of psychotic disorders, we compared the standardized 1 H NMR parameters among healthy controls (HCs), patients diagnosed with ARMS, FEP patients, and psychotic patients in the critical period (CP) using a cross-sectional design. ...
Minimally invasive prognostic markers of inflammation and dyslipidemia in individuals with a risk of psychosis, also called "at-risk mental state" (ARMS), or in the first episode of psychosis (FEP) are of utmost clinical importance to prevent cardiovascular disorders. We analyzed the plasma concentration of inflammation-linked glycoproteins (Glycs) and lipoprotein subclasses by proton nuclear magnetic resonance (1H NMR) in a single acquisition. Study participants were healthy controls (HCs, N = 67) and patients with ARMS (N = 58), FEP (N = 110), or early psychosis diagnosis with ≥2 episodes (critical period (CP), N = 53). Clinical biomarkers such as high-sensitivity C-reactive protein, interleukin 6, fibrinogen, insulin, and lipoproteins were also measured. Although all participants had normal lipoprotein profiles and no inflammation according to conventional biomarkers, a gradual increase in the Glyc 1H NMR levels was observed from HCs to CP patients; this increase was statistically significant for GlycA (CP vs HC). In parallel, a progressive and significant proatherogenic 1H NMR lipoprotein profile was also identified across stages of psychosis (ARMS and CP vs HC). These findings highlight the potential of using 1H NMR Glyc and lipoprotein profiling to identify blood changes in individuals with ARMS or FEP and pave the way for applications using this technology to monitor metabolic and cardiovascular risks in clinical psychiatry.
... In addition, for membrane proteins, obtaining high-quality crystal structures is still full of uncertainties. On the other hand, without crystallization, NMR can directly analyze the structure of proteins in solution and provide valuable information about internal protein dynamics [17]. However, it requires the labelling of protein backbone and/or amino acid residues with NMRsensitive isotopes and is limited to small proteins below 50 kD [18]. ...
Drug discovery is a crucial part of human healthcare and has dramatically benefited human lifespan and life quality in recent centuries, however, it is usually time- and effort-consuming. Structural biology has been demonstrated as a powerful tool to accelerate drug development. Among different techniques, cryo-electron microscopy (cryo-EM) is emerging as the mainstream of structure determination of biomacromolecules in the past decade and has received increasing attention from the pharmaceutical industry. Although cryo-EM still has limitations in resolution, speed and throughput, a growing number of innovative drugs are being developed with the help of cryo-EM. Here, we aim to provide an overview of how cryo-EM techniques are applied to facilitate drug discovery. The development and typical workflow of cryo-EM technique will be briefly introduced, followed by its specific applications in structure-based drug design, fragment-based drug discovery, proteolysis targeting chimeras, antibody drug development and drug repurposing. Besides cryo-EM, drug discovery innovation usually involves other state-of-the-art techniques such as artificial intelligence (AI), which is increasingly active in diverse areas. The combination of cryo-EM and AI provides an opportunity to minimize limitations of cryo-EM such as automation, throughput and interpretation of medium-resolution maps, and tends to be the new direction of future development of cryo-EM. The rapid development of cryo-EM will make it as an indispensable part of modern drug discovery.
... We chose to focus on blood metabolites because they reflect the interaction with other individual and environmental exposures, endogenous metabolism, and co-metabolism by gut microbiota [37]. We also focused on MS instead of NMR because MS captures a broader range of metabolites than NMR, with robust specificity on lipoprotein subfractions [38,39]. ...
Diet is one of the most important exposures that may affect health throughout life span. Investigations on dietary patterns rather than single food components are gaining in popularity because they take the complexity of the whole dietary context into account. Adherence to such dietary patterns can be measured by using metabolomics, which allows measurements of thousands of molecules simultaneously. Derived metabolite signatures of dietary patterns may reflect the consumption of specific groups of foods or their constituents originating from the dietary pattern per se, or the physiological response toward the food-derived metabolites, their interaction with endogenous metabolism, and exogenous factors such as gut microbiota. Here, we review and discuss blood metabolite fingerprints of healthy dietary patterns. The plasma concentration of several food-derived metabolites-such as betaines from whole grains and n - 3 polyunsaturated fatty acids and furan fatty acids from fish-seems to consistently reflect the intake of common foods of several healthy dietary patterns. The metabolites reflecting shared features of different healthy food indices form biomarker panels for which specific, targeted assays could be developed. The specificity of such biomarker panels would need to be validated, and proof-of-concept feeding trials are needed to evaluate to what extent the panels may mediate the effects of dietary patterns on disease risk indicators or if they are merely food intake biomarkers. Metabolites mediating health effects may represent novel targets for precision prevention strategies of clinical relevance to be verified in future studies.
... Therefore, EWAS on detailed lipoprotein measures are warranted. A helpful tool in this regard is nuclear magnetic resonance (NMR), which allows fine profiling of lipoproteins at a large scale [34][35][36]. NMR has successfully identified several new markers of metabolic disease [35,36]. Up to now, three studies, including our previous investigation, have evaluated associations between serum metabolic measures and DNA methylation-with a limited sample size or a limited number of measures-identifying several loci linked to disease response mechanisms or environmental insults [29,37,38]. ...
Background
The discovery of robust and trans-ethnically replicated DNA methylation markers of metabolic phenotypes, has hinted at a potential role of epigenetic mechanisms in lipid metabolism. However, DNA methylation and the lipid compositions and lipid concentrations of lipoprotein sizes have been scarcely studied. Here, we present an epigenome-wide association study (EWAS) ( N = 5414 total) of mostly lipid-related metabolic measures, including a fine profiling of lipoproteins. As lipoproteins are the main players in the different stages of lipid metabolism, examination of epigenetic markers of detailed lipoprotein features might improve the diagnosis, prognosis, and treatment of metabolic disturbances.
Results
We conducted an EWAS of leukocyte DNA methylation and 226 metabolic measurements determined by nuclear magnetic resonance spectroscopy in the population-based KORA F4 study ( N = 1662) and replicated the results in the LOLIPOP, NFBC1966, and YFS cohorts ( N = 3752). Follow-up analyses in the discovery cohort included investigations into gene transcripts, metabolic-measure ratios for pathway analysis, and disease endpoints. We identified 161 associations ( p value < 4.7 × 10 ⁻¹⁰ ), covering 16 CpG sites at 11 loci and 57 metabolic measures. Identified metabolic measures were primarily medium and small lipoproteins, and fatty acids. For apolipoprotein B-containing lipoproteins, the associations mainly involved triglyceride composition and concentrations of cholesterol esters, triglycerides, free cholesterol, and phospholipids. All associations for HDL lipoproteins involved triglyceride measures only. Associated metabolic measure ratios, proxies of enzymatic activity, highlight amino acid, glucose, and lipid pathways as being potentially epigenetically implicated. Five CpG sites in four genes were associated with differential expression of transcripts in blood or adipose tissue. CpG sites in ABCG1 and PHGDH showed associations with metabolic measures, gene transcription, and metabolic measure ratios and were additionally linked to obesity or previous myocardial infarction, extending previously reported observations.
Conclusion
Our study provides evidence of a link between DNA methylation and the lipid compositions and lipid concentrations of different lipoprotein size subclasses, thus offering in-depth insights into well-known associations of DNA methylation with total serum lipids. The results support detailed profiling of lipid metabolism to improve the molecular understanding of dyslipidemia and related disease mechanisms.
... In electron microscopy, this could be the image representing the shape of the molecule. However, only experimental information is not enough to build an accurate atomic model, additional molecular structural knowledge is often required is the amino acid sequence of a protein along with geometrical features such as bond lengths and bond angles (Rankin et al. 2014). The creation of a consistent protein model requires a set of experimental data and modeling related parameters (Carroni and Saibil 2016). ...
Proteins are very flexible biomolecules. The accurate knowledge of protein structure is very important from its functional point of view. In protein structure prediction, the three-dimensional structure of a protein is modeled from its amino acid sequence using knowledge-based approaches. Computational algorithms and tools have made significant improvements in the field of structural modeling. Protein structure prediction methods include comparative modeling (homology modeling), threading, and ab initio approach. Several tools and software have been developed for the 3D modeling of proteins. Each protein modeling methods have certain limitations that should be kept in mind while selecting a tool for structure modeling. The structural details of X-ray crystallography and nuclear magnetic resonance spectroscopy-verified protein structures guide the development of modeling software and also useful in assessing the accuracy of the protein model.
... The most versatile and widely used method is 1 H qNMR. Each molecule with hydrogen atoms gives a characteristic signal with a shape that is quantum mechanically distinctive, and the area is proportional to the concentration of the molecule (55,56). Using standard equipment, qNMR can resolve the concentrations of target molecules down to the micromolar range. ...
Despite great progress in the management of atherosclerosis (AS), its subsequent cardiovascular disease (CVD) remains the leading cause of morbidity and mortality. This is probably due to insufficient risk detection using routine lipid testing; thus, there is a need for more effective approaches relying on new biomarkers. Quantitative nuclear magnetic resonance (qNMR) metabolomics is able to phenotype holistic metabolic changes, with a unique advantage in regard to quantifying lipid-protein complexes. The rapidly increasing literature has indicated that qNMR-based lipoprotein particle number, particle size, lipid components, and some molecular metabolites can provide deeper insight into atherogenic diseases and could serve as novel promising determinants. Therefore, this article aims to offer an updated review of the qNMR biomarkers of AS and CVD found in epidemiological studies, with a special emphasis on lipoprotein-related parameters. As more researches are performed, we can envision more qNMR metabolite biomarkers being successfully translated into daily clinical practice to enhance the prevention, detection and intervention of atherosclerotic diseases.
