Bullet-DNP Enables NMR Spectroscopy of Pyruvate and Amino Acids at Nanomolar to Low Micromolar Concentrations.

Hyperpolarized pyruvate is a widely used marker to track metabolism in vivo and a benchmark molecule for hyperpolarization methods. Here, we show how a combination of improved bullet-DNP instrumentation, an optimized sample preparation and a further sensitivity increase via a 13C-1H polarization transfer after dissolution enable the observation of pyruvate at a concentration of 250 nM immediately after dissolution. At this concentration, the experiment employs a total mass of pyruvate of only 20 ng or 180 pmol. If the concentration is increased to 45 µM, pyruvate may be detected 1 min after dissolution with a signal-to-noise ratio exceeding 50. The procedure can be extended to observe a mixture of amino acids at low micromolar concentrations.

Utilizing Molecular Dynamics Simulations, Machine Learning, Cryo-EM, and NMR Spectroscopy to Predict and Validate Protein Dynamics.

Protein dynamics play a crucial role in biological function, encompassing motions ranging from atomic vibrations to large-scale conformational changes. Recent advancements in experimental techniques, computational methods, and artificial intelligence have revolutionized our understanding of protein dynamics. Nuclear magnetic resonance spectroscopy provides atomic-resolution insights, while molecular dynamics simulations offer detailed trajectories of protein motions. Computational methods applied to X-ray crystallography and cryo-electron microscopy (cryo-EM) have enabled the exploration of protein dynamics, capturing conformational ensembles that were previously unattainable. The integration of machine learning, exemplified by AlphaFold2, has accelerated structure prediction and dynamics analysis. These approaches have revealed the importance of protein dynamics in allosteric regulation, enzyme catalysis, and intrinsically disordered proteins. The shift towards ensemble representations of protein structures and the application of single-molecule techniques have further enhanced our ability to capture the dynamic nature of proteins. Understanding protein dynamics is essential for elucidating biological mechanisms, designing drugs, and developing novel biocatalysts, marking a significant paradigm shift in structural biology and drug discovery.

Time-resolved NMR detection of prolyl-hydroxylation in intrinsically disordered region of HIF-1α.

Prolyl-hydroxylation is an oxygen-dependent posttranslational modification (PTM) that is known to regulate fibril formation of collagenous proteins and modulate cellular expression of hypoxia-inducible factor (HIF) α subunits. However, our understanding of this important but relatively rare PTM has remained incomplete due to the lack of biophysical methodologies that can directly measure multiple prolyl-hydroxylation events within intrinsically disordered proteins. Here, we describe a real-time 13C-direct detection NMR-based assay for studying the hydroxylation of two evolutionarily conserved prolines (P402 and P564) simultaneously in the intrinsically disordered oxygen-dependent degradation domain of hypoxic-inducible factor 1α by exploiting the "proton-less" nature of prolines. We show unambiguously that P564 is rapidly hydroxylated in a time-resolved manner while P402 hydroxylation lags significantly behind that of P564. The differential hydroxylation rate was negligibly influenced by the binding affinity to prolyl-hydroxylase enzyme, but rather by the surrounding amino acid composition, particularly the conserved tyrosine residue at the +1 position to P564. These findings support the unanticipated notion that the evolutionarily conserved P402 seemingly has a minimal impact in normal oxygen-sensing pathway.

Nuclear magnetic resonance-based metabolomics with machine learning for predicting progression from prediabetes to diabetes.

Background: Identification of individuals with prediabetes who are at high risk of developing diabetes allows for precise interventions. We aimed to determine the role of nuclear magnetic resonance (NMR)-based metabolomic signature in predicting the progression from prediabetes to diabetes. Methods: This prospective study included 13,489 participants with prediabetes who had metabolomic data from the UK Biobank. Circulating metabolites were quantified via NMR spectroscopy. Cox proportional hazard (CPH) models were performed to estimate the associations between metabolites and diabetes risk. Supporting vector machine, random forest, and extreme gradient boosting were used to select the optimal metabolite panel for prediction. CPH and random survival forest (RSF) models were utilized to validate the predictive ability of the metabolites. Results: During a median follow-up of 13.6 years, 2525 participants developed diabetes. After adjusting for covariates, 94 of 168 metabolites were associated with risk of progression to diabetes. A panel of nine metabolites, selected by all three machine-learning algorithms, was found to significantly improve diabetes risk prediction beyond conventional risk factors in the CPH model (area under the receiver-operating characteristic curve, 1 year: 0.823 for risk factors + metabolites vs 0.759 for risk factors, 5 years: 0.830 vs 0.798, 10 years: 0.801 vs 0.776, all p < 0.05). Similar results were observed from the RSF model. Categorization of participants according to the predicted value thresholds revealed distinct cumulative risk of diabetes. Conclusions: Our study lends support for use of the metabolite markers to help determine individuals with prediabetes who are at high risk of progressing to diabetes and inform targeted and efficient interventions. Funding: Shanghai Municipal Health Commission (2022XD017). Innovative Research Team of High-level Local Universities in Shanghai (SHSMU-ZDCX20212501). Shanghai Municipal Human Resources and Social Security Bureau (2020074). Clinical Research Plan of Shanghai Hospital Development Center (SHDC2020CR4006). Science and Technology Commission of Shanghai Municipality (22015810500).

Absolute Metabolite Quantification in Individuals with Glioma and Healthy Individuals Using Whole-Brain Three-dimensional MR Spectroscopic and Echo-planar Time-resolved Imaging.

BACKGROUND: MR spectroscopic imaging (MRSI) can be used to quantify an extended brain metabolic profile but is confounded by changes in tissue water levels due to disease. PURPOSE: To develop a fast absolute quantification method for metabolite concentrations combining whole-brain MRSI with echo-planar time-resolved imaging (EPTI) relaxometry in individuals with glioma and healthy individuals. MATERIALS AND METHODS: In this prospective study performed from August 2022 to August 2023, using internal water as concentration reference, the MRSI-EPTI quantification method was compared with the conventional method using population-average literature relaxation values. Healthy participants and participants with mutant IDH1 gliomas underwent imaging at 3 T with a 32-channel coil. Real-time navigated adiabatic spiral three-dimensional MRSI scans were acquired in approximately 8 minutes and reconstructed with a super-resolution pipeline to obtain brain metabolic images at 2.4-mm isotropic resolution. High-spatial-resolution multiparametric EPTI was performed in 3 minutes, with 1-mm isotropic resolution, to correct the relaxation and proton density of the water reference signal. Bland-Altman analysis and the Wilcoxon signed rank test were used to compare absolute quantifications from the proposed and conventional methods. RESULTS: Six healthy participants (four male; mean age, 37 years ± 11 [SD]) and nine participants with glioma (six male; mean age, 41 years ± 15; one with wild-type IDH1 and eight with mutant IDH1) were included. In healthy participants, there was good agreement (+4% bias) between metabolic concentrations derived using the two methods, with a CI of plus or minus 26%. In participants with glioma, there was large disagreement between the two methods (+39% bias) and a CI of plus or minus 55%. The proposed quantification method improved tumor contrast-to-noise ratio (median values) for total N-acetyl-aspartate (EPTI: 0.541 [95% CI: 0.217, 0.910]; conventional: 0.484 [95% CI: 0.199, 0.823]), total choline (EPTI: 1.053 [95% CI: 0.681, 1.713]; conventional: 0.940 [95% CI: 0.617, 1.295]), and total creatine (EPTI: 0.745 [95% CI: 0.628, 0.909]; conventional: 0.553 [95% CI: 0.444, 0.828]) (P = .03 for all). CONCLUSION: The whole-brain MRSI-EPTI method provided fast absolute quantification of metabolic concentrations with individual-specific corrections at 2.4-mm isotropic resolution, yielding concentrations closer to the true value in disease than the conventional literature-based corrections. © RSNA, 2024 Supplemental material is available for this article.

AB006. The use of magnetic resonance spectroscopy in the differential diagnosis of paediatric intracranial tumours.

BACKGROUND: Despite different intracranial tumour subtypes varying largely in their prognoses and recommended treatment regimens, they can have markedly similar appearances on standard radiology, especially in paediatric patients where they tend to occur in the midline. There is a need for a non-invasive, accurate method of determining tumour diagnosis to help expedite treatment planning. Existing studies have found magnetic resonance spectroscopy (MRS) to have value in diagnosing intracranial tumours in adults. The aim of this study was to investigate whether MRS could be accurate in diagnosing and grading paediatric intracranial tumours. METHODS: The hospital database was retrospectively searched for paediatric intracranial tumour patients ≤18 years that had 1.5 T MRS data available. Medical and demographic data were collected from existing records including MRS metabolites N-acetylaspartate (NAA), creatine (Cr), and choline (Cho), and final histopathologic diagnosis. MRS metabolites were then statistically compared against final histopathologic diagnosis. RESULTS: In total, 166 patients were included. In the overall cohort, the tumour to control tissue Cr ratio was significantly higher in grade 1 than grade 4 tumours (P=0.03), and tumour Cho/Cr was significantly higher in grade 4 than grade 1 tumours (P=0.004). When analyzing tumour subtypes, control tissue Cr was significantly higher in embryonal/germ cell tumours than glial tumours (P=0.044). Binary logistic regression models including MRS metabolite ratios and age, sex, and tumour location covariates could diagnose grade 4 tumours [area under the curve (AUC) =0.857], and grade 1 tumours (AUC =0.766) with reasonable accuracy. CONCLUSIONS: This study suggests that MRS has benefits in the non-invasive diagnosis of paediatric intracranial tumours, in particular, identifying low- and high-grade tumours. Future advances in MRS technology, and larger cross-sectional studies will be necessary to improve the clinical integration of MRS for accurate non-invasive paediatric intracranial tumour diagnosis.

Monitoring of Isothermal Crystallization and Time-Temperature Transformation of Amorphous Felodipine: The Time-Domain Nuclear Magnetic Resonance Method.

The isothermal crystallization process of felodipine has been investigated using the time-domain Nuclear Magnetic Resonance (NMR) method for amorphous bulk and ground samples. The obtained induction and crystallization times were then used to construct the time-temperature-transformation (TTT) diagram, both above and below the glass transition temperature (Tg). The Nose temperature was found equal to 363 K. Furthermore, the dynamics of crystalline and amorphous felodipine were compared across varying temperatures. Molecular dynamics simulations were also employed to explore the hydrogen-bond interactions and dynamic properties of both systems.

Age and visual cortex inhibition: a TMS-MRS study.

Paired-pulse transcranial magnetic stimulation is a valuable tool for investigating inhibitory mechanisms in motor cortex. We recently demonstrated its use in measuring cortical inhibition in visual cortex, using an approach in which participants trace the size of phosphenes elicited by stimulation to occipital cortex. Here, we investigate age-related differences in primary visual cortical inhibition and the relationship between primary visual cortical inhibition and local GABA+ in the same region, estimated using magnetic resonance spectroscopy. GABA+ was estimated in 28 young (18 to 28 years) and 47 older adults (65 to 84 years); a subset (19 young, 18 older) also completed a paired-pulse transcranial magnetic stimulation session, which assessed visual cortical inhibition. The paired-pulse transcranial magnetic stimulation measure of inhibition was significantly lower in older adults. Uncorrected GABA+ in primary visual cortex was also significantly lower in older adults, while measures of GABA+ that were corrected for the tissue composition of the magnetic resonance spectroscopy voxel were unchanged with age. Furthermore, paired-pulse transcranial magnetic stimulation-measured inhibition and magnetic resonance spectroscopy-measured tissue-corrected GABA+ were significantly positively correlated. These findings are consistent with an age-related decline in cortical inhibition in visual cortex and suggest paired-pulse transcranial magnetic stimulation effects in visual cortex are driven by GABAergic mechanisms, as has been demonstrated in motor cortex.

Metabolomic profiling of elite female soccer players: urinary biomarkers over a championship season.

INTRODUCTION: In soccer, most studies evaluate metabolic profile changes in male athletes, often using data from a single match. Given the current landscape of women's soccer and the effects of biological sex on the physiological response and adaptation to exercise, more studies targeting female athletes and analyzing pre- and post-game moments throughout the season are necessary. OBJECTIVES: To describe the metabolomics profile of female soccer athletes from an elite team in Brazil. The study observed the separation of groups in three pre- and post-game moments and identified the discriminating metabolites. METHODS: The study included 14 female soccer athletes. Urine samples were collected and analyzed using Nuclear Magnetic Resonance in pre-game and immediate post-game moments over three national championship games. The metabolomics data were then used to generate OPLS-DA and VIP plots. RESULTS: Forty-three metabolites were identified in the samples. OPLS-DA analyses demonstrated a progressive separation between pre-post conditions, as supported by an increasing Q2 value (0.534, 0.625, and 0.899 for games 1, 2 and 3, respectively) and the first component value (20.2% and 19.1% in games 1 and 2 vs. 29.9% in game 3). Eight out of the fifteen most discriminating metabolites appeared consistently across the three games: glycine, formate, citrate, 3-hydroxyvalerate, glycolic acid, trimethylamine, urea, and dimethylglycine. CONCLUSION: The main difference between the three games was the increasing separation between groups throughout the championship. Since the higher VIP-scores metabolites are linked to energy and protein metabolism, this separation may be attributed several factors, one being the accumulation of fatigue.

Optimization and validation of echo times of point-resolved spectroscopy for cystathionine detection in gliomas.

BACKGROUND: Cystathionine accumulates selectively in 1p/19q-codeleted gliomas, and can serve as a possible noninvasive biomarker. This study aims to optimize the echo time (TE) of point-resolved spectroscopy (PRESS) for cystathionine detection in gliomas, and evaluate the diagnostic accuracy of PRESS for 1p/19q-codeletion identification. METHODS: The TE of PRESS was optimized with numerical and phantom analysis to better resolve cystathionine from the overlapping aspartate multiplets. The optimized and 97 ms TE PRESS were then applied to 84 prospectively enrolled patients suspected of glioma or glioma recurrence to examine the influence of aspartate on cystathionine quantification by fitting the spectra with and without aspartate. The diagnostic performance of PRESS for 1p/19q-codeleted gliomas were assessed. RESULTS: The TE of PRESS was optimized as (TE1, TE2) = (17 ms, 28 ms). The spectral pattern of cystathionine and aspartate were consistent between calculation and phantom. The mean concentrations of cystathionine in vivo fitting without aspartate were significantly higher than those fitting with full basis-set for 97 ms TE PRESS (1.97 ± 2.01 mM vs. 1.55 ± 1.95 mM, p < 0.01), but not significantly different for 45 ms method (0.801 ± 1.217 mM and 0.796 ± 1.217 mM, p = 0.494). The cystathionine concentrations of 45 ms approach was better correlated with those of edited MRS than 97 ms counterparts (r = 0.68 vs. 0.49, both p < 0.01). The sensitivity and specificity for discriminating 1p/19q-codeleted gliomas were 66.7% and 73.7% for 45 ms method, and 44.4% and 52.5% for 97 ms method, respectively. CONCLUSION: The 45 ms TE PRESS yields more precise cystathionine estimates than the 97 ms method, and is anticipated to facilitate noninvasive diagnosis of 1p/19q-codeleted gliomas, and treatment response monitoring in those patients. Medium diagnostic performance of PRESS for 1p/19q-codeleted gliomas were observed, and warrants further investigations.

Maize Grain Metabolite Profiling by NMR: Effects of Growing Year, Variety, and Cropping System.

Considering that maize (Zea mays L.) is a staple food for a large segment of the population worldwide, many attempts have been made to improve the nutritional value of its grain and at the same time to achieve sustainable cropping systems. The present study aimed to characterize the composition and nutritional value of maize grain as influenced by cropping system, genetic background (variety), and growing year using untargeted NMR metabolomics. The composition of both water- (sugars and polyols, organic acids, and amino acids) and liposoluble metabolites (free and esterified fatty acids, sterols, and lipids) extracted from the maize grain was determined. Multivariate statistical analyses (PCA and ANOVA) pointed to the growing year and the variety as the most important random and fixed factors, respectively, influencing the metabolite profile. The samples were separated along PC1 and PC3 according to the growing year and the variety, respectively. A higher content of citric acid and diunsaturated fatty acids and a lower content of tyrosine, trigonelline, and monounsaturated fatty acids was observed in the organic with respect to the conventional variety. The effect of the cropping system was overwhelmed by the random effect of the growing year. The results provide novel knowledge on the influence of agronomic practices on maize micronutrient contents.

Hyperpolarized 13C NMR Reveals Pathway Regulation in Lactococcus lactis and Metabolic Similarities and Differences Across the Tree of Life.

The control of metabolic networks is incompletely understood, even for glycolysis in highly studied model organisms. Direct real-time observations of metabolic pathways can be achieved in cellular systems with 13C NMR using dissolution Dynamic Nuclear Polarization (dDNP NMR). The method relies on a short-lived boost of NMR sensitivity using a redistribution of nuclear spin states to increase the alignment of the magnetic moments by more than four orders of magnitude. This temporary boost in sensitivity allows detection of metabolism with sub-second time resolution. Here, we hypothesized that dDNP NMR would be able to investigate molecular phenotypes that are not easily accessible with more conventional methods. The use of dDNP NMR allows real-time insight into carbohydrate metabolism in a Gram-positive bacterium (Lactoccocus lactis), and comparison to other bacterial, yeast and mammalian cells shows differences in the kinetic barriers of glycolysis across the kingdoms of life. Nevertheless, the accumulation of non-toxic precursors for biomass at kinetic barriers is found to be shared across the kingdoms of life. We further find that the visualization of glycolysis using dDNP NMR reveals kinetic characteristics in transgenic strains that are not evident when monitoring the overall glycolytic rate only. Finally, dDNP NMR reveals that resting Lactococcus lactis cells use the influx of carbohydrate substrate to produce acetoin rather than lactate during the start of glycolysis. This metabolic regime can be emulated using suitably designed substrate mixtures to enhance the formation of the C4 product acetoin more than 400-fold. Overall, we find that dDNP NMR provides analytical capabilities that may help to clarify the intertwined mechanistic determinants of metabolism and the optimal usage of biotechnologically important bacteria.

A Quantitative Comparison of 31P Magnetic Resonance Spectroscopy RF Coil Sensitivity and SNR between 7T and 10.5T Human MRI Scanners Using a Loop-Dipole 31P-1H Probe.

In vivo phosphorus-31 (31P) magnetic resonance spectroscopy (MRS) imaging (MRSI) is an important non-invasive imaging tool for studying cerebral energy metabolism, intracellular nicotinamide adenine dinucleotide (NAD) and redox ratio, and mitochondrial function. However, it is challenging to achieve high signal-to-noise ratio (SNR) 31P MRS/MRSI results owing to low phosphorus metabolites concentration and low phosphorous gyromagnetic ratio (γ). Many works have demonstrated that ultrahigh field (UHF) could significantly improve the 31P-MRS SNR. However, there is a lack of studies of the 31P MRSI SNR in the 10.5 Tesla (T) human scanner. In this study, we designed and constructed a novel 31P-1H dual-frequency loop-dipole probe that can operate at both 7T and 10.5T for a quantitative comparison of 31P MRSI SNR between the two magnetic fields, taking into account the RF coil B1 fields (RF coil receive and transmit fields) and relaxation times. We found that the SNR of the 31P MRS signal is 1.5 times higher at 10.5T as compared to 7T, and the power dependence of SNR on magnetic field strength (B0) is 1.9.

The Diffusion Exchange Ratio (DEXR): A minimal sampling of diffusion exchange spectroscopy to probe exchange, restriction, and time-dependence.

Water exchange is increasingly recognized as an important biological process that can affect the study of biological tissue using diffusion MR. Methods to measure exchange, however, remain immature as opposed to those used to characterize restriction, with no consensus on the optimal pulse sequence (s) or signal model (s). In general, the trend has been towards data-intensive fitting of highly parameterized models. We take the opposite approach and show that a judicious sub-sample of diffusion exchange spectroscopy (DEXSY) data can be used to robustly quantify exchange, as well as restriction, in a data-efficient manner. This sampling produces a ratio of two points per mixing time: (i) one point with equal diffusion weighting in both encoding periods, which gives maximal exchange contrast, and (ii) one point with the same total diffusion weighting in just the first encoding period, for normalization. We call this quotient the Diffusion EXchange Ratio (DEXR). Furthermore, we show that it can be used to probe time-dependent diffusion by estimating the velocity autocorrelation function (VACF) over intermediate to long times (∼2-500ms). We provide a comprehensive theoretical framework for the design of DEXR experiments in the case of static or constant gradients. Data from Monte Carlo simulations and experiments acquired in fixed and viable ex vivo neonatal mouse spinal cord using a permanent magnet system are presented to test and validate this approach. In viable spinal cord, we report the following apparent parameters from just 6 data points: τk=17±4ms, fNG=0.72±0.01, Reff=1.05±0.01µm, and κeff=0.19±0.04µm/ms, which correspond to the exchange time, restricted or non-Gaussian signal fraction, an effective spherical radius, and permeability, respectively. For the VACF, we report a long-time, power-law scaling with ≈t-2.4, which is approximately consistent with disordered domains in 3-D. Overall, the DEXR method is shown to be highly efficient, capable of providing valuable quantitative diffusion metrics using minimal MR data.

Quantitative determination of C-polysaccharide in Streptococcus pneumoniae capsular polysaccharides by enzyme-linked immunosorbent assay.

Capsular polysaccharides of Streptococcus pneumoniae are used in pneumococcal polysaccharide and protein-conjugate vaccines. Cell-wall polysaccharide (C-Ps) is a critical impurity that must be kept at low levels in purified polysaccharide preparations. Hence, accurate and precise methods for determining C-Ps are needed. Currently available methods include nuclear magnetic resonance (NMR) spectroscopy and high-performance anion-exchange chromatography with pulsed amperometric detection (HPAEC-PAD). Both these methods suffer from their own limitations; therefore, we developed a simple and efficient enzyme-linked immunosorbent assay (ELISA) for accurate and precise quantification of C-Ps in samples of any serotype of pneumococcal capsular polysaccharide without interference. We quantified C-Ps in preparations of 14 serotype polysaccharides using newly developed ELISA method and compared the results with C-Ps values obtained using two previously reported methods, 1H NMR and HPAEC-PAD. The C-Ps value determined using 1H NMR for serotype 5 was 21.08%, whereas the values obtained using HPAEC-PAD and ELISA were 2.38% and 2.89% respectively, indicating some interference in 1H NMR method. The sensitivity of the ELISA method is higher because the sample is used directly unlike HPAEC-PAD method where sample is subjected to harsh treatment, such as acid digestion and quantify C-Ps based on peak area of ribitol or AAT. Furthermore, 1H NMR and HPAEC-PAD are expensive and laborious methods. Our work, underscores the simple and efficient ELISA that can be used for quantification of C-Ps in pneumococcal polysaccharide preparations.

Quantification of high-density lipoprotein particle number by proton nuclear magnetic resonance: don't believe the numbers.

PURPOSE OF REVIEW: Proton nuclear magnetic resonance (NMR) can rapidly assess lipoprotein concentrations and sizes in biological samples. It may be especially useful for quantifying high-density lipoprotein (HDL), which exhibits diverse particle sizes and concentrations. We provide a critical review of the strengths and limitations of NMR for quantifying HDL subclasses. RECENT FINDINGS: Recent studies using NMR have shed light on HDL's role in various disorders, ranging from residual cardiovascular risk to host susceptibility to infection. However, accurately quantifying HDL particle number, size, and concentration (HDL-P) remains a challenge. Discrepancies exist between NMR and other methods such as gel electrophoresis, ion mobility analysis and size-exclusion chromatography in estimating the abundance of HDL species and the ratio of apolipoprotein A-I (APOA1) to HDL particles. SUMMARY: NMR is a low-cost method for quantifying HDL-P that is readily applicable to clinical and translational studies. However, inconsistencies between the results of NMR quantification of HDL-P and other independent methods hinder the interpretation of NMR results. Because proton NMR apparently fails to accurately quantify the sizes and concentrations of HDL, the relevance of such studies to HDL biology poses challenges. This limits our understanding of pathophysiological implications of HDL-P as determined by NMR, particularly in determining cardiovascular disease (CVD) risk.

Multimodal investigation of neuropathology and neurometabolites in mild cognitive impairment and late-life depression with 11C-PiB beta-amyloid PET and 7T magnetic resonance spectroscopy.

Positron emission tomography (PET) and magnetic resonance spectroscopy (1H-MRS) are complementary techniques that can be applied to study how proteinopathy and neurometabolism relate to cognitive deficits in preclinical stages of Alzheimer's disease (AD)-mild cognitive impairment (MCI) and late-life depression (LLD). We acquired beta-amyloid (Aß) PET and 7 T 1H-MRS measures of GABA, glutamate, glutathione, N-acetylaspartate, N-acetylaspartylglutamate, myo-inositol, choline, and lactate in the anterior and posterior cingulate cortices (ACC, PCC) in 13 MCI and 9 LLD patients, and 13 controls. We used linear regression to examine associations between metabolites, Aß, and cognitive scores, and whether metabolites and Aß explained cognitive scores better than Aß alone. In the ACC, higher Aß was associated with lower GABA in controls but not MCI or LLD patients, but results depended upon MRS data quality control criteria. Greater variance in California Verbal Learning Test scores was better explained by a model that combined ACC glutamate and Aß deposition than by models that only included one of these variables. These findings identify preliminary associations between Aß, neurometabolites, and cognition.

Development of a certified reference material for D-phenylalanine with evaluation of enantiomeric purity.

D-Phenylalanine (D-Phe) is a small chiral organic molecule that is both an important pharmaceutical intermediate and used as a calibrator for quantifying amino acids in liquid chromatography-circular dichroism. We have developed a process for a national certified reference material (CRM) for D-Phe following ISO 17034:2016. The identity of D-Phe was confirmed using mass spectrometry (MS) and nuclear magnetic resonance (NMR), infrared, and ultraviolet (UV) spectroscopy. The absolute optical conformation was also determined using circular dichroism (CD) spectroscopy and optical rotation measurements. Impurities were identified via liquid chromatography (LC) with a UV-Vis detector and a charged aerosol detector (CAD) and LC-MS. Both mass balance and quantitative NMR were employed for value assessment, and the associated uncertainty was evaluated. The certified purity was determined to be 0.995 ± 0.003 g/g, a validation that was confirmed by CD using L-Phe CRM as a calibrator. Twenty milligrams of raw material was packed in sealed brown glass tubes for storage, and no inhomogeneity was observed. Stability tests revealed that the D-Phe CRM remained stable at -20 °C for at least 26 months, at 4 °C for at least 14 days, and at 25 °C and 60 °C for at least 7 days. The D-Phe CRM can be used to ensure the accuracy and reliability of D-Phe quantitation in the pharmaceutical field and also as a calibrator to ensure traceability to the International System of Units (SI) for L-Phe quantitation and protein purity analysis using LC-CD methods. The approach outlined in this paper also has potential for use in the development of other chiral CRMs.

A multilevel LC-HRMS and NMR correlation workflow towards foodomics advancement: Application in table olives.

Foodomics employs advanced analytical techniques to provide answers regarding food composition, authenticity control, marker identification and issues related to food quality and safety. Nuclear magnetic resonance (NMR) spectroscopy and chromatography hyphenated to mass spectrometry (MS) are the main analytical platforms used in this field. Nevertheless, they are rarely employed in an integrated manner, and even then, the contribution of each technique remains vague. Table olives (Olea europaea L.) are a food commodity of high economic and nutritional value with an increasing production tendency over the last two decades, which, however, suffers from extensive fraud incidents and quality determination uncertainties. Thus, the current attempt aims towards two axes with the first being the multilevel integration of LC-HRMS and NMR data of the same samples and table olives being the selected matrix. In more detail, UPLC-HRMS/MS-based analysis was compared at different stages within an untargeted metabolomics workflow with an NMR-based study and the complementarity of the two platforms was evaluated. Furthermore, statistical heterospectroscopy (SHY), rarely employed in foodomics, combining the spectroscopic with spectrometric datasets and aiming to increase the confidence level of annotated biomarkers was applied. Amongst these lines, the second parallel axis of this study was the detailed characterization of table olives' metabolome in search for quality markers considering the impact of geographical (from Northern to Southern Greece) and botanical origin (Kalamon, Konservolia, Chalkidikis cultivars), as well as processing parameters (Spanish, Greek). To that end, using deep dereplication tools including statistical methods, with SHY employed for the first time in table olives, different biomarkers, belonging to the classes of phenyl alcohols, phenylpropanoids, flavonoids, secoiridoids and triterpenoids were identified as responsible for the observed classifications. The current binary pipeline, focusing on biomarkers' identification confidence, could be suggested as a meaningful workflow not only in olive-based products, but also in food quality control and foodomics in general.

HRMAS 1H NMR and CPMAS 13C NMR spectroscopies coupled with chemometrics for the metabolomic investigation of commercial teas.

In this study, the metabolome of different types of tea (i.e., black, green and earl grey) is explored by means of HRMAS 1H (i.e., semisolid state) NMR and CPMAS 13C (i.e., solid state) NMR spectroscopies. By elaborating the metabolomic data with unsupervised and supervised chemometric tools (PCA, PLS-DA), it was possible to set up classification models with the aim to discriminate the different types of tea as based on differences in their chemical composition. Both the applications of the NMR spectroscopies also allowed to obtain information about the metabolic biomarkers leading the differentiation among teas. These were mainly represented by phenolic compounds. Also, some non-phenolic compounds, such as amino acids, carbohydrates, and terpenoids, played important roles in shaping tea quality. The findings of this study provided useful insights into the application of solid and semisolid state NMR spectroscopies, in combination with chemometrics, in the context of food authentication and traceability.