Nuclear Magnetic Resonance Profiling Research Articles

Different profiles of soil phosphorous compounds depending on tree species and availability of soil phosphorus in a tropical rainforest in French Guiana

BackgroundThe availability of soil phosphorus (P) often limits the productivities of wet tropical lowland forests. Little is known, however, about the metabolomic profile of different chemical P compounds with potentially different uses and about the cycling of P and their variability across space under different tree species in highly diverse tropical rainforests.ResultsWe hypothesised that the different strategies of the competing tree species to retranslocate, mineralise, mobilise, and take up P from the soil would promote distinct soil 31P profiles. We tested this hypothesis by performing a metabolomic analysis of the soils in two rainforests in French Guiana using 31P nuclear magnetic resonance (NMR). We analysed 31P NMR chemical shifts in soil solutions of model P compounds, including inorganic phosphates, orthophosphate mono- and diesters, phosphonates, and organic polyphosphates. The identity of the tree species (growing above the soil samples) explained > 53% of the total variance of the 31P NMR metabolomic profiles of the soils, suggesting species-specific ecological niches and/or species-specific interactions with the soil microbiome and soil trophic web structure and functionality determining the use and production of P compounds. Differences at regional and topographic levels also explained some part of the the total variance of the 31P NMR profiles, although less than the influence of the tree species. Multivariate analyses of soil 31P NMR metabolomics data indicated higher soil concentrations of P biomolecules involved in the active use of P (nucleic acids and molecules involved with energy and anabolism) in soils with lower concentrations of total soil P and higher concentrations of P-storing biomolecules in soils with higher concentrations of total P.ConclusionsThe results strongly suggest “niches” of soil P profiles associated with physical gradients, mostly topographic position, and with the specific distribution of species along this gradient, which is associated with species-specific strategies of soil P mineralisation, mobilisation, use, and uptake.

Phytochemical variation between hydrochloric and tartaric acid-derived alkaloidal extracts of Erythrina fusca Lour. leaves: A proton NMR-based approach

Erythrina fusca Lour. (Fabaceae) has been used traditionally to relieve toothache and migraine headaches, cleansing putrid ulcers, and reducing skin inflammations and irritation. Interestingly, most of the reported biological activities on the plant are attributed to its Erythrina alkaloids which are usually extracted through the acid-base method. While the selection of acids for the extraction process is crucial, there is limited information on comparing the efficacy of strong organic and inorganic acids in extracting Erythrina alkaloids, and, more broadly, other types of alkaloids. In this study, comparison between hydrochloric acid (HCl) and tartaric acid (H2T) was made to extract the Erythrina alkaloids. From the same mass (10 g) of the crude methanolic leaf extract, a significantly higher (9-fold) alkaloidal yield was obtained using H2T compared to the HCl. The alkaloidal extracts displayed different proton nuclear magnetic resonance (1H NMR) profile where identification of their phytochemical constituents was done extensively through comparison with respective data of previously isolated compounds from the Erythrina species. Forty-seven phytochemicals were identified in the HCl extract and they were mostly alkaloids. While the H2T extract not only contained alkaloids, but also flavonoids, and pterocarpans. Cumulatively, 83 phytochemicals were identified from the extracts, including 35 alkaloids, 18 flavonoids, 14 pterocarpans, 9 terpenes, 3 phenols, and 4 saponins. Based on multivariate analysis (MVDA), the alkaloids erysodine (1), erysovine (2), erysopine (3), warangalone (39), calopocarpin (53), and dolichin A (60) were found in both alkaloidal extracts. The PLS-DA model further identified the variation in the two extracts where the HCl extract was characterized by the flavonoids lupinifolin (41) and erythrisenegalone (43). Conversely, the H2T extract contained a broader range of phytochemicals, including the alkaloids glucoerysodine (21) and erythratidinone (28), the flavonoids 5,3′-dihydroxy-4′‑methoxy-5′-(3-methyl-1,3-butadienyl)-2′′,2′′dimethylpyrano-[5,6:6,7]-isoflavanone (51), 5,3′-dihydroxy-5′-(3‑hydroxy-3-methyl-1-butenyl)-4′‑methoxy-2′′,2′′dimethylpyrano-[5,6:6,7]-isoflavanone (52), and catechin (82), the pterocarpans calopocarpin (53) and sandwicensin (63), the terpenes loliolide (70), ursolic acid (80), propyloxyamyrin (83), and stigmast-3-en-4-one (73), the saponins sigmoisides A, B, and E (75, 76, and 77), and the phenol methyl gallate (81). The present findings highlight the value of targeting the extraction process for alkaloids, in this instance Erythrina alkaloids, using different type of acids. Furthermore, these compounds may be considered potential markers that were selectively extracted through the acid-base extraction process.

Nature and structure of NTA Traditional Homeopathically Manufactured Medicines.

Background: Research using several different methods has demonstrated the materiality, including nanoparticles (NPs) and molecular shapes, in High Homeopathic Potentizations (HHPs). This presentation is a summary of all the evidence gathered by the DynHom research project. Methods: We used the Nuclear Magnetic Resonance (NMR), Nano Tracking Analyzer (NTA), Electronic microscopy (SEM-EDX), Infrared spectroscopy (FTIR), pH measurements to examine dilutions of commonly used homeopathic medicines and controls. The homeopathic medicines tested were specially prepared according to the European pharmacopoeia standards. We compared the homeopathic dilutions/dynamizations with simple dilutions and solvents controls. Results: We observed specific NMR profiles, the presence of particles with specific size distribution and electric fields, dry material (crystals) with a specific molecular structure even more obvious in HHPs. Conclusion: Homeopathic medicines do contain particles with a specific size distribution even in HHPs diluted beyond the Avogadro/Loschmidt limit. They also contain molecules in particular concentrations according to each source material. This specificity can be attributed to the manufacturing and potentization process. This material demonstrates that the step-by-step process (dynamized or not) does not match the theoretical expectations in a dilution process. The starting material, the type of containers and dilution/dynamization method influence the nature and concentration of these NPs.

Geographical classification of opium samples from Myanmar and Afghanistan by NMR profiling and chemometrics.

This study presents a new strategy to discriminate between opium samples obtained from different geographical regions. Nuclear magnetic resonance (NMR) profiling and chemometrics were applied to geographical classification of opium originating from Myanmar and Afghanistan, which are two major opium producing countries in the world. A total of 50 Myanmar and 46 Afghanistan authentic opium samples were analyzed by 1 H-NMR, and the chemical profiles were characterized. Different sample preparation procedures, data processing methods, and chemometrics were compared to obtain the best classification effect. It was found that drying and the addition of buffer solutions were unnecessary for classification purposes; thus, the gum opium samples were extracted directly with CD3 OD, which shortened sample preparation time. A full discrimination between the two geographical origins was achieved by 1 H-NMR profiling and orthogonal partial least squares discriminant analysis. All 30 opium samples were classified correctly by the developed orthogonal partial least squares discriminant analysis model. Compared with traditional chromatography and mass spectrometry profiling methods, the 1 H-NMR profiling method was faster (with instrument analysis time of less than 3min) and reproducible. This study provides new insights into the applying of NMR profiling and chemometrics to rapid drug profiling analysis.

PDP1 is a key metabolic gatekeeper and modulator of drug resistance in FLT3-ITD-positive acute myeloid leukemia

High metabolic flexibility is pivotal for the persistence and therapy resistance of acute myeloid leukemia (AML). In 20–30% of AML patients, activating mutations of FLT3, specifically FLT3-ITD, are key therapeutic targets. Here, we investigated the influence of FLT3-ITD on AML metabolism. Nuclear Magnetic Resonance (NMR) profiling showed enhanced reshuffling of pyruvate towards the tricarboxylic acid (TCA) cycle, suggesting an increased activity of the pyruvate dehydrogenase complex (PDC). Consistently, FLT3-ITD-positive cells expressed high levels of PDP1, an activator of the PDC. Combining endogenous tagging of PDP1 with genome-wide CRISPR screens revealed that FLT3-ITD induces PDP1 expression through the RAS signaling axis. PDP1 knockdown resulted in reduced cellular respiration thereby impairing the proliferation of only FLT3-ITD cells. These cells continued to depend on PDP1, even in hypoxic conditions, and unlike FLT3-ITD-negative cells, they exhibited a rapid, PDP1-dependent revival of their respiratory capacity during reoxygenation. Moreover, we show that PDP1 modifies the response to FLT3 inhibition. Upon incubation with the FLT3 tyrosine kinase inhibitor quizartinib (AC220), PDP1 persisted or was upregulated, resulting in a further shift of glucose/pyruvate metabolism towards the TCA cycle. Overexpression of PDP1 enhanced, while PDP1 depletion diminished AC220 resistance in cell lines and peripheral blasts from an AC220-resistant AML patient in vivo. In conclusion, FLT3-ITD assures the expression of PDP1, a pivotal metabolic regulator that enhances oxidative glucose metabolism and drug resistance. Hence, PDP1 emerges as a potentially targetable vulnerability in the management of AML.

NMR-based metabolomics in giant cell arteritis and polymyalgia rheumatica sequential sera differentiates active and inactive disease.

Giant Cell Arteritis-(GCA) is an inflammatory disease following a chronic, relapsing course. The metabolic alterations related to the intense inflammatory process during the active phase and to the rapid impact of steroid treatment, remain unknown. The study aims to investigate the serum metabolome in active and inactive disease state. 110 serum samples from 50 patients [33-GCA and 17-Polymyalgia rheumatica-(PMR)] at 3 time points, 0-(V1: active disease), 1 and 6 months-(V2 and V3: remission) of treatment with glucocorticosteroids (GCs), were subjected to Nuclear Magnetic Resonance (NMR)-based metabolomic analysis. Multi- and univariate statistical analyses were utilized to unveil metabolome alterations following treatment. Distinct metabolic profiles were identified between activity and remission, independently to disease type. N-acetylglycoproteins and cholines of bound phospholipids, emerged as predictive markers of disease activity. Altered levels of 4 out of the 21 small molecules were also observed, including increased levels of phenylalanine, and decreased of glutamine, alanine, and creatinine in active disease. Metabolic fingerprinting discriminated GCA from PMR in remission. GCA and PMR patients exhibited characteristic lipid alterations as a response and/or adverse effect of GCs treatment. Correlation analysis showed that several identified biomarkers were further associated with acute phase reactants, C-Reactive Protein and Erythrocyte Sedimentation Rate. The NMR profile of serum metabolome could identify and propose sensitive biomarkers of inflammation. Metabolome alterations, following GCs treatment, could provide predictors for future steroid-induced side effects.

Quantum chemical investigation of predominant conformation of the antibiotic azithromycin in water and DMSO solutions: thermodynamic and NMR analysis.

Azithromycin (AZM) is a macrolide-type antibiotic used to prevent and treat serious infections (mycobacteria or MAC) that significantly inhibit bacterial growth. Knowledge of the predominant conformation in solution is of fundamental importance for advancing our understanding of the intermolecular interactions of AZM with biological targets. We report an extensive density functional theory (DFT) study of plausible AZM structures in solution considering implicit and explicit solvent effects. The best match between the experimental and theoretical nuclear magnetic resonance (NMR) profiles was used to assign the preferred conformer in solution, which was supported by the thermodynamic analysis. Among the 15 distinct AZM structures, conformer M14, having a short intramolecular C6-OH … N H-bond, is predicted to be dominant in water and dimethyl sulfoxide (DMSO) solutions. The results indicated that the X-ray structure backbone is mostly conserved in solution, showing that large flexible molecules with several possible conformations may assume a preferential spatial orientation in solution, which is the molecular structure that ultimately interacts with biological targets.

Real-time in-situ measurement of hydrogel swelling by single sided NMR

Swelling factor and swelling rate are key characteristics of hydrogels. Here, a new method is presented for accurate in-situ monitoring of hydrogel swelling in real-time using single-sided nuclear magnetic resonance (NMR) profiling. The method reduces experimenter bias and uncertainty intrinsic to common weighing and caliper methods. Moreover, NMR allows monitoring of samples that may otherwise be inaccessible to other methods, for instance in opaque or sealed containers. The method is straightforward and does not require deep knowledge of NMR principles from the experimenter. This NMR profiling method estimates similar swelling factors to those using the weigh and caliper method, with precision equivalent to the weigh method and significantly better than with caliper. Unlike weigh and caliper methods, NMR profiling additionally provides dynamic swelling rates over time, without needing to touch or modify the sample.

1471-P: Metabolomic Profiling of Type 2 Diabetes Pathway-Partitioned Polygenic Risk Scores Offers Insights into Disease Etiology

Previous studies have identified type 2 diabetes (T2D) subtypes using clinical phenotypes and/or genetic information. This study aimed to identify molecular signatures associated with genetically based T2D subtypes. We analyzed data from ~100,000 unrelated European UK Biobank participants without T2D and not taking lipid-lowering medications. T2D subtypes were characterized using five polygenic scores denoting three forms of insulin resistance (lipodystrophy, obesity, and impaired lipid/hepatic metabolism) and two subtypes of insulin secretion (beta-cell dysfunction and impaired proinsulin synthesis). Nuclear magnetic resonance profiles of 249 plasma metabolites on the Nightingale platform were tested for association with T2D subtypes using linear regression adjusted for age, sex, batch, and ancestry-derived principal components; P<0.0002 was considered significant. Independent validation was conducted in two independent cohorts, including 720 from the ANTORCHA cohort. In general, the T2D subtypes driven by insulin resistance were characterized by alterations in lipid and lipoproteins, while the impaired insulin secretion subtypes showed aberrant plasma amino acid levels. The lipodystrophy cluster showed the most distinct molecular signature, with higher concentrations of extremely large, very large, and large VLDL particles which were enriched by triglycerides and phospholipids, and lower concentrations of HDL. The beta-cell dysfunction cluster was characterized by higher concentrations of amino acids (alanine, valine, leucine, and tyrosine). These associations were broadly consistent after adjusting for BMI, and the pattern of alterations in lipid metabolites was partially replicated in the ANTORCHA cohort. We identified specific metabolic signatures related to T2D genetic clusters before T2D onset, offering further characterization of the putative underlying pathways. Disclosure M.Sevilla: None. I.Lamiquiz-moneo: None. K.Smith: None. M.Canyelles: None. J.C.Florez: Consultant; AstraZeneca, Novo Nordisk, Other Relationship; AstraZeneca, Merck & Co., Inc. A.Manning: None. F.Civeira: None. J.Merino: None. M.Udler: None. Funding American Diabetes Association (9-22-PDFPM-04 to M.S.)

Asthma-protective agents in dust from traditional farm environments

Growing up on traditional European or US Amish dairy farms in close contact with cows and hay protects children against asthma, and airway administration of extracts from dust collected from cowsheds of those farms prevents allergic asthma in mice. This study sought to begin identifying farm-derived asthma-protective agents. Our work unfolded along 2 unbiased and independent but complementary discovery paths. Dust extracts (DEs) from protective and nonprotective farms (European and Amish cowsheds vs European sheep sheds) were analyzed by comparative nuclear magnetic resonance profiling and differential proteomics. Bioactivity-guided size fractionation focused on protective Amish cowshed DEs. Multiple invitro and invivo functional assays were used in both paths. Some of the proteins thus identified were characterized by in-solution and in-gel sodium dodecyl sulfate-polyacrylamide gel electrophoresis enzymatic digestion/peptide mapping followed by liquid chromatography/mass spectrometry. The cargo carried by these proteins was analyzed by untargeted liquid chromatography-high-resolution mass spectrometry. Twelve carrier proteins of animal and plant origin, including the bovine lipocalins Bos d 2 and odorant binding protein, were enriched in DEs from protective European cowsheds. Apotent asthma-protective fraction of Amish cowshed DEs (≈0.5% of the total carbon content of unfractionated extracts) contained 7 animal and plant proteins, including Bos d 2 and odorant binding protein loaded with fatty acid metabolites from plants, bacteria, and fungi. Animals and plants from traditional farms produce proteins that transport hydrophobic microbial and plant metabolites. When delivered to mucosal surfaces, these agents might regulate airway responses.

Advanced insight on the water dynamics of anisotropic hydrogels by field-cycling nuclear magnetic resonance: Application of 3-Tau model

Fast field cycling (FFC) nuclear magnetic resonance (NMR) relaxometry is used to investigate an anisotropic polygalacturonate hydrogel formed by the diffusion of calcium ions from an external reservoir (external gelation). Such a hydrogel has a gradient of polymer density accompanied by a gradient of the mesh size of its 3D network. The NMR relaxation process is dominated by the interaction of proton spins between water molecules located at polymer interfaces and in nanoporous spaces. The FFC NMR experiment provides the spin-lattice relaxation rate R1ω as a function of Larmor frequency ω producing dispersion (NMRD) curves that are highly sensitive to the dynamics of the protons at the surfaces. The hydrogel is sliced into three parts and the NMR profile for each hydrogel slice is measured. The NMRD data for each slice is interpreted using the 3-Tau Model with the aid of user-friendly fitting software called 3TM. The key fit parameters include three nano-dynamical time constants and the average “mesh size” which collectively determine the bulk water and water surface layer contribution to the total relaxation rate. The results are consistent with independent studies where comparison is possible.

Spatially Correlated Nuclear Magnetic Resonance Profiles as a Tool for Precision Agriculture

Nuclear magnetic resonance (NMR) profiling, sample georeferentiaton, and geostatistics are applied to evaluate the spatial variability of metabolic expression of durum wheat in fields managed by precision agriculture. Durum wheat at three different vegetation stages, grown in two different places of the Basilicata region, in Italy, is analyzed by NMR. The spatial variability, within each field, of metabolites, quantified by NMR, is evidenced by appropriate geostatistic tools through the definition of a suitable metabolic index. Metabolic maps are compared to highlight the effects of soil and farming strategies.

Longitudinal perturbations of plasma nuclear magnetic resonance profiles in neonatal encephalopathy.

Neonatal encephalopathy (NE) is a major cause of mortality and severe neurological disability in the neonatal period and beyond. We hypothesized that the degree of brain injury is reflected in the molecular composition of peripheral blood samples. A sub-cohort of 28 newborns included in the HYPOTOP trial was studied. Brain injury was assessed by magnetic resonance imaging (MRI) once per patient and neurodevelopment at 24 months of age was evaluated using the Bayley III Scales of Infant and Toddler Development. The nuclear magnetic resonance (NMR) profile of 60 plasma samples collected before, during, and after cooling was recorded. In total, 249 molecular features were quantitated in plasma samples from newborns and postnatal age showed to affect detected NMR profiles. Lactate, beta-hydroxybutyrate, pyruvate, and three triglyceride biomarkers showed the ability to discern between different degrees of brain injury according to MRI scores. The prediction performance of lactate was superior as compared to other clinical and biochemical parameters. This is the first longitudinal study of an ample compound panel recorded by NMR spectroscopy in plasma from NE infants. The serial determination of lactate confirms its solid position as reliable candidate biomarker for predicting the severity of brain injury. The use of nuclear magnetic resonance (NMR) spectroscopy enables the simultaneous quantitation of 249 compounds in a small volume (i.e., 100 μL) of plasma. Longitudinal perturbations of plasma NMR profiles were linked to magnetic resonance imaging (MRI) outcomes of infants with neonatal encephalopathy (NE). Lactate, beta-hydroxybutyrate, pyruvate, and three triglyceride biomarkers showed the ability to discern between different degrees of brain injury according to MRI scores. Lactate is a minimally invasive candidate biomarker for early staging of MRI brain injury in NE infants that might be readily implemented in clinical guidelines for NE outcome prediction.

Correlation of chemical profiles obtained from 1 H-NMR and LC-MS metabolomics with α-glucosidase inhibition activity for varietal selections of Ficus deltoidea.

Ficus deltoidea Jack (Moraceae) is a plant used in Malaysia to treat various ailments, including diabetes. The presence of several varieties raises essential questions regarding which is the potential bioactive variety and what are the bioactive metabolites. Here, we explored the phytochemical diversity of the seven varieties from Peninsular Malaysia using Nuclear Magnetic Resonance (NMR) and Liquid Chromatography-Mass Spectrometry (LC-MS) analyses and correlated it with the α-glucosidase inhibitory activity. The Nuclear Overhauser Effect Spectroscopy (NOESY) One-Dimensional (1D)-NMR and LC-MS data were processed, annotated, and correlated with in vitro α-glucosidase inhibitory using multivariate data analysis. The α-glucosidase results demonstrated that different varieties have varying inhibitory effects, with the highest inhibition rate being F. deltoidea var. trengganuensis and var. kunstleri. Furthermore, diverse habitats and plant ages could also influence the inhibitory rate. The heat map from NMR and LC-MS profiles showed unique patterns according to varying levels of α-glucosidase inhibition rate. The Partial Least Squares (PLS) model constructed from both NMR and LC-MS further confirmed the correlation between the α-glucosidase inhibition rate of F. deltoidea varieties and its metabolite profiles. The Variable Influence on Projection (VIP) and correlation coefficient (p(corr)) values values were used to determine the highly relevant metabolites for explaining the anticipated inhibitory action. NMR and LC-MS annotations allow the identification of flavan-3-ols and proanthocyanidins as the key bioactive factors. Our current results demonstrated the value of multivariate data analysis to predict the quality of herbal materials from both biological and chemical aspects.

NMRpQuant: an automated software for large scale urinary total protein quantification by one-dimensional 1H NMR profiles.

Summary 1H nuclear magnetic resonance (NMR) spectroscopy is an established bioanalytical technology for metabolic profiling of biofluids in both clinical and large-scale population screening applications. Recently, urinary protein quantification has been demonstrated using the same 1D 1H NMR experimental data captured for metabolic profiling. Here, we introduce NMRpQuant, a freely available platform that builds on these findings with both novel and further optimized computational NMR approaches for rigorous, automated protein urine quantification. The results are validated by interlaboratory comparisons, demonstrating agreement with clinical/biochemical methodologies, pointing at a ready-to-use tool for routine protein urinalyses.Availability and implementation NMRpQuant was developed on MATLAB programming environment. Source code and Windows/macOS compiled applications are available at https://github.com/pantakis/NMRpQuant, and working examples are available at https://doi.org/10.6084/m9.figshare.18737189.v1.Supplementary information Supplementary data are available at Bioinformatics online.

O-258 Nuclear magnetic resonance profiling of the vaginal metabolome in adverse early pregnancy outcomes

Abstract Study question Is the vaginal metabolome predictive of early pregnancy outcomes? Summary answer The vaginal metabolome is moderately predictive of live normally-sited pregnancies when compared to a pregnancy with an adverse outcome. What is known already Approximately 15% of all pregnancies are lost in the first trimester and a further 1-2% are ectopic. To date, no non-invasive and clinically useful tests have been developed to differentiate live normally-sited pregnancies from non-viable and ectopic pregnancies. Metabolomics is the comprehensive analysis of small molecules in biological samples used to identify disease biomarkers. The vaginal metabolome has previously been shown to be predictive of later adverse pregnancy outcomes including preterm birth. In this study, we aimed to identify biomarkers of live normally-sited pregnancies when compared to non-viable intrauterine and ectopic pregnancies using NMR metabolomic profiling of vaginal swabs (LVS). Study design, size, duration This was a prospective cohort study (EXPEDITE). 222 pregnant women <10 weeks’ gestation with pain and/or bleeding were recruited over a period of 36 months at the Liverpool Women’s Hospital, a tertiary referral centre. Pregnancy outcomes were categorised according to ESHRE guidelines as live normally-sited pregnancy, miscarriage, tubal ectopic pregnancy or pregnancy of unknown location (PUL). Participants/materials, setting, methods Participants consented to self-collecting a LVS, which was extracted in acetonitrile and analysis by NMR spectroscopy; 1D 1H and 2D 1H-13C. Spectra were acquired at 25 °C on a 700 MHz spectrometer. Relative metabolite abundances underwent univariate and multivariate statistical analysis using MetaboAnalyst 5.0 and custom-built R scripts (p-value false discovery rate adjusted). Area under receiver operating characteristic curve (AUC) values were used to evaluate predictive models. Main results and the role of chance Our cohort of 222 women were categorised in to 100 (45 %) live normally-sited pregnancies, 29 (13 %) tubal ectopic pregnancies, 52 (23 %) miscarriages and 31 (14%) pregnancies of unknown location (PUL). Ten spectra from rare or uncertain pregnancy outcomes (e.g. molar pregnancy) were excluded. Univariate statistical analysis of all four groups identified isoleucine levels as significantly higher (p < 0.05) in live normally-sited pregnancies compared with all groups with adverse pregnancy outcome groups. Multivariate partial least squares discriminant analysis (PLS-DA) models of all groups failed to accurately predict pregnancy outcomes. To enhance the predictive models, miscarriage, tubal ectopic pregnancy and PUL groups were combined and compared to live normally-sited pregnancies. Univariate analysis revealed levels of several metabolites (including isoleucine, tyrosine and maltose) as significantly altered in live normally-sited pregnancies compared with all other outcomes. PLS-DA models demonstrated modest discrimination between live normally-sited pregnancies versus other outcomes (AUC = 0.75). In summary, this study has identified a vaginal metabolite profile and potential biomarkers associated with live normally-sited pregnancy in the first trimester. Limitations, reasons for caution The number of tubal ectopic pregnancies and PULs were relatively low compared to other outcomes. Additionally, several factors that may influence the vaginal metabolome, including infection and the vaginal microbiome, were not characterised in this study. Wider implications of the findings These findings may be useful in the development of diagnostic tests to confirm an intrauterine pregnancy and exclude potential life-threatening pregnancies. It is well established that the microbiome contributes to the vaginal metabolome. As such, our findings will inform future correlative studies of vaginal microbiome and metabolome in early pregnancy. Trial registration number NA

Using nuclear magnetic resonance urine metabolomics to develop a prediction model of early stages of renal disease in subjects with type 2 diabetes

Type 2 diabetes mellitus (DM2) is a multimorbidity, long-term condition, and one of the worldwide leading causes of chronic kidney disease (CKD) –a silent disease, usually detected when non-reversible renal damage have already occurred. New strategies and more effective laboratory methods are needed for more opportune diagnosis of DM2-CKD. This study comprises clinical parameters and nuclear magnetic resonance (NMR)-based urine metabolomics data from 60 individuals (20–65 years old, 67.7% females), sorted in 5 experimental groups (healthy subjects; diabetic patients without any clinical sign of CKD; and patients with mild, moderate, and severe DM2-CKD), according to KDIGO. DM2-CKD produces a continuous variation of the urine metabolome, characterized by an increase/decrement of a group of metabolites that can be used to monitor CKD progression (trigonelline, hippurate, phenylalanine, glycolate, dimethylamine, alanine, 2-hydroxybutyrate, lactate, and citrate). NMR profiles were used to obtain a statistical model, based on partial least squares analysis (PLS-DA) to discriminate among groups. The PLS-DA model yielded good validation parameters (sensitivity, specificity, and area under the curve (AUC) of the receiver operating characteristic curve (ROC) plot: 0.692, 0.778 and 0.912, respectively) and, thus, it can differentiate between subjects with DM2-CKD in early stages, from subjects with a mild or severe condition. This metabolic signature exhibits a molecular variation associated to DM2-CKD, and data suggests it can be used to predict risk of DM2-CKD in patients without clinical signs of renal disease, offering a new alternative to current diagnosis methods.

HPLC-MS, GC and NMR Profiling of Bioactive Lipids of Human Milk and Milk of Dairy Animals (Cow, Sheep, Goat, Buffalo, Camel, Red Deer)

For non-bovine milks, information regarding bioactive lipids is fragmented, unreliable or unavailable. The purpose of the current study was to analyse bioactive lipids in the milk of dairy animals using modern analytical methods to achieve the most reliable results. Bioactive lipids in human milk were also analysed and used as a reference. A suite of modern analytical methods was employed, namely High Performance Liquid Chromatography-Mass Spectrometry (HPLC-MS), Gas Chromatography (GC) and Nuclear Magnetic Resonance (NMR). The total lipid content was determined, and phospholipid, fatty acid, neutral glycosphingolipids and ganglioside (GM3 and GD3) levels were measured. Lipid classes in selected milks were reliably characterised for the first time, including gangliosides in deer, camel and sheep; cerebrosides in deer, camel and buffalo; plasmalogens in deer, buffalo and goat and phospholipids in deer. Our study demonstrated the advantage of utilising a range of analytical techniques in order to characterise a diverse set of bioactive lipids.

Duration of dry and humidified incubation of single-step embryo culture medium and oxygen tension during sham culture do not alter medium composition.

Background: The extended embryo culture using single-step medium gained popularity in clinical in vitro fertilisation (IVF). However, there are concerns about the degradation of unstable medium components and their negative effects on the developing embryos. Further, dry-incubation can increase osmolality, which can in-turn enhance the concentration of constituents of the media and their stability. Hence, this study was conducted to understand the immediate changes in the culture media constituents in relation to clinically comparable situations such as single-step extended embryo culture and use of dry and humidified-incubation in two-different gaseous conditions. Methods: Commercially available single-step medium was sham-cultured in droplets under oil in two different conditions viz. dry (37°C; 6%CO 2; 5%O 2) and humidified (37°C; 6% CO 2; atmospheric O 2) for 0h, 72h, and 120h intervals. Droplets were subjected to the sensitivity-enhanced nuclear magnetic resonance (NMR)-based profiling using 800 MHz NMR equipped with a cryogenically cooled micro-coil (1.7mm) probe. NMR profile of the embryo culture medium between the two groups were comprehensively assessed. Results: A total of ten amino acids and four energy substrates were identified from the culture medium. The medium constituents identified showed a non-significant increase in the dry-incubation group at 72h and then declined at 120h. Humidified incubation had no effects on the level of the identified medium constituents until 120h. No significant differences in the levels of medium constituents identified were observed between the dry and humidified-groups at various time-points tested. Conclusions: A non-significant variation in the levels of medium constituents observed in the dry-incubation of single-step medium most unlikely to influence a clinical outcome. However, the impact of these subtle changes on the (epi)genetic integrity of the embryos in a clinical set-up to be addressed.

Quantitative study of CO2 huff-n-puff enhanced oil recovery in tight formation using online NMR technology

Recent evidence suggests that CO2 huff-n-puff can significantly enhance the oil recovery in tight/shale oil reservoirs after primary depletion. However, the key driving forces of CO2 huff-n-puff for oil displacement, especially their effect on the enhanced oil recovery are still unclear. In addition, the CO2 effective distance in matrix, which is a critical parameter impacting the performance of huff-n-puff, has not been accurately studied. In this work, to identify and quantify the contribution of the related enhanced-oil-recovery (EOR) mechanisms, an online nuclear magnetic resonance (NMR) instrument was used to monitor the real-time migration of the matrix oil at all stages of the CO2 huff-n-puff process. The experiment results show that the dissolved CO2 drive controlled by molecular diffusion is the dominant mechanism during the huff-n-puff process. This EOR mechanism mainly works on the oil stored in the macropores, while the oil stored in the micropores is hardly mobilized. Base on the dynamic oil saturation distributions converted from the 1-D NMR profiles during huff-n-puff, we designed a novel 2-D evaluation system, which focuses on microscopic displacement efficiency and CO2 effective distance, to investigate the effect of the operation parameters on oil production. We found that simply increasing the injection pressure mainly improves the displacement efficiency but has less effect on the expansion of the sweep area, which limits the CO2 huff-n-puff EOR on the reservoir scale. Lengthening the soaking period extends the effective distance significantly but delays oil production. A cyclic huff-n-puff scheme with variable soaking time was proposed to maintain a high oil production rate and a large sweep area. Periodic optimization of the soaking time in the cyclic CO2 huff-n-puff process is needed for an optimal development plan.