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Background: kidney transplant recipients are exposed to multiple pathogenic pathways that may alter short and long-term allograft survival. Metabolomic profiling is useful for detecting potential biomarkers of kidney disease with a predictive capacity. This field is still under development in kidney transplantation and metabolome analysis is faced with analytical challenges. We performed a cross-sectional study including stable kidney transplant patients and aimed to search for relevant associations between baseline plasmatic and urinary metabolites and relevant outcomes over a follow-up period of 3 years. Methods: we performed a cross-sectional study including 72 stable kidney transplant patients with stored plasmatic and urinary samples at the baseline evaluation which were there analyzed by nuclear magnetic resonance in order to quantify and describe metabolites. We performed a 3-year follow-up and searched for relevant associations between renal failure outcomes and baseline metabolites. Between-group comparisons were made after classification by observed estimated glomerular filtration rate slope during the follow-up: positive slope and negative slope. Results : The mean estimated GFR (glomerular filtration rate) was higher at baseline in the patients who exhibited a negative slope during the follow-up (63.4 mL/min/1.73 m 2 vs. 55.8 mL/min/1.73 m 2 , p = 0,019). After log transformation and division by urinary creatinine, urinary dimethylamine (3.63 vs. 3.16, p = 0.027), hippuric acid (7.33 vs. 6.29, p = 0.041), and acetone (1.88 vs. 1, p = 0.023) exhibited higher concentrations in patients with a negative GFR slope when compared to patients with a positive GFR slope. By computing a linear regression, a significant low-strength regression equation between the log 2 transformed plasmatic level of glycine and the estimated glomerular filtration rate was found ( F (1,70) = 5.15, p = 0.026), with an R 2 of 0.069. Several metabolites were correlated positively with hand grip strength (plasmatic tyrosine with r = 0.336 and p = 0.005 and plasmatic leucine with r = 0.371 and p = 0.002). Other urinary metabolites were found to be correlated negatively with hand grip strength (dimethylamine with r = -0.250 and p = 0.04, citric acid with r = -0.296 and p = 0.014, formic acid with r = -0.349 and p = 0.004, and glycine with r = -0.306 and p = 0.01). Conclusions : some metabolites had different concentrations compared to kidney transplant patients with negative and positive slopes, and significant correlations were found between hand grip strength and urinary and plasmatic metabolites.

Most patients presenting in an emergency unit with acute coronary syndromes (ACS) (which include non-ST-elevation myocardial infarction (NSTEMI), ST-elevation MI (STEMI), and unstable angina) usually meet at least two cardiovascular risk factors, such as dyslipidemia, arterial hypertension, diabetes mellitus type 2, obesity, history of or current smoking, etc. Most ACS patients suffer from a type of dyslipidemia, and in addition to this there are ACS patients rushed into the emergency units for which the feeding status is unknown. Thus, we set out to evaluate the effect of fasting on 16 blood metabolite concentrations and 114 lipoprotein parameters on one control group and a group of statin-treated ACS patients hospitalized in a cardiovascular emergency unit, using Nuclear Magnetic Resonance (NMR) spectroscopy. The results indicated trends (in terms of number of cases, but not necessarily in terms of the magnitude of the effect) for as many as four metabolites and 48 lipoproteins. The effect was defined as a trend for results showing over 70% of the cases from either one or both groups that experienced parameter changes in the same direction (i.e., either increased or decreased). In terms of magnitude, the effect is rather low, leading to the overall conclusion that in cardiovascular (CV) emergency units, the blood samples analyzed in any feeding status would provide close results and very valuable information regarding prognosis and for fast decisions on patient's proper management.

The saponification value of fats and oils is one of the most common quality indices, reflecting the mean molecular weight of the constituting triacylglycerols. Proton nuclear magnetic resonance ( 1 H-NMR) spectra of fats and oils display specific resonances for the protons from the structural patterns of the triacylglycerols (i.e., the glycerol backbone), methylene (-CH 2 -) groups, double bonds (-CH=CH-) and the terminal methyl (-CH 3 ) group from the three fatty acyl chains. Consequently, chemometric equations based on the integral values of the 1 H-NMR resonances allow for the calculation of the mean molecular weight of triacylglycerol species, leading to the determination of the number of moles of triacylglycerol species per 1 g of fat and eventually to the calculation of the saponification value (SV), expressed as mg KOH/g of fat. The algorithm was verified on a series of binary mixtures of tributyrin (TB) and vegetable oils (i.e., soybean and rapeseed oils) in various ratios, ensuring a wide range of SV. Compared to the conventional technique for SV determination (ISO 3657:2013) based on titration, the obtained 1 H-NMR-based saponification values differed by a mean percent deviation of 3%, suggesting the new method is a convenient and rapid alternate approach. Moreover, compared to other reported methods of determining the SV from spectroscopic data, this method is not based on regression equations and, consequently, does not require calibration from a database, as the SV is computed directly and independently from the 1 H-NMR spectrum of a given oil/fat sample.

Nuclear magnetic resonance (NMR) metabolomics is currently popular enough to attract both specialized and non-specialized NMR groups involving both analytical trained personnel and newcomers, including undergraduate students. Recent interlaboratory studies performed by established NMR metabolomics groups demonstrated high reproducibility of the state-of-the-art NMR equipment and SOPs. There is, however, no assessment of NMR reproducibility when mixing both analytical experts and newcomers. An interlaboratory assessment of NMR quantitation reproducibility was performed using two NMR instruments belonging to different laboratories and involving several operators with different backgrounds and metabolomics expertise for the purpose of assessing the limiting factors for data reproducibility in a multipurpose NMR environment. The variability induced by the operator, automatic pipettes, NMR tubes and NMR instruments was evaluated in order to assess the limiting factors for quantitation reproducibility. The results estimated the expected reproducibility data in a real-life multipurpose NMR laboratory to a maximum 4% variability, demonstrating that the current NMR equipment and SOPs may compensate some of the operator-induced variability.