Perceptions of Magnetic Resonance Imaging During Pregnancy: A Newfoundland and Labrador Perspective.

OBJECTIVES: This study aimed to identify enablers and barriers to participation in MRI for clinical indications and scientific research, and to determine the perceptions of MRI performed during pregnancy. METHODS: We conducted a survey of 156 pregnant people in Newfoundland and Labrador including sociodemographic information, obstetrical history, MRI history, and willingness to participate in an MRI. Categorical variables were analyzed using a Fisher exact test and open-ended questions were analyzed using thematic analysis. RESULTS: In total, 80% of participants reported willingness to receive an MRI while pregnant for clinical indications compared to 24% for research. Only 10% reported prior knowledge about MRI during pregnancy and most participants (94%) wanted additional information from their physician before feeling comfortable with the procedure. Participants who knew someone with complications during pregnancy were more likely to be willing to participate in an MRI for research (uncorrected P < 0.05). Participants' positive perceptions towards MRI during pregnancy for clinical indications were that it was a necessary and useful procedure, while the negative perceptions identified MRI as unsafe. For research MRI, participants' positive perceptions included that it would add to the advancement of knowledge and the negative perceptions were that it was an unnecessary and risky procedure. CONCLUSIONS: Strategies are needed to improve patient knowledge about the benefits and safety of MRI during pregnancy. The present study suggests recruitment for research should incorporate education on safety concerns and relative risk, personal stories about the benefits of MRI in diagnosing pregnancy complications and should highlight the contribution to advancing scientific knowledge.

Maternal exposure to polystyrene nanoplastics alters fetal brain metabolism in mice.

INTRODUCTION: Plastics used in everyday materials accumulate as waste in the environment and degrade over time. The impacts of the resulting particulate micro- and nanoplastics on human health remain largely unknown. In pregnant mice, we recently demonstrated that exposure to nanoplastics throughout gestation and during lactation resulted in changes in brain structure detected on MRI. One possible explanation for this abnormal postnatal brain development is altered fetal brain metabolism. OBJECTIVES: To determine the effect of maternal exposure to nanoplastics on fetal brain metabolism. METHODS: Healthy pregnant CD-1 mice were exposed to 50 nm polystyrene nanoplastics at a concentration of 106 ng/L through drinking water during gestation. Fetal brain samples were collected at embryonic day 17.5 (n = 18-21 per group per sex) and snap-frozen in liquid nitrogen. Magic angle spinning nuclear magnetic resonance was used to determine metabolite profiles and their relative concentrations in the fetal brain. RESULTS: The relative concentrations of gamma-aminobutyric acid (GABA), creatine and glucose were found to decrease by 40%, 21% and 30% respectively following maternal nanoplastic exposure when compared to the controls (p < 0.05). The change in relative concentration of asparagine with nanoplastic exposure was dependent on fetal sex (p < 0.005). CONCLUSION: Maternal exposure to polystyrene nanoplastics caused abnormal fetal brain metabolism in mice. The present study demonstrates the potential impacts of nanoplastic exposure during fetal development and motivates further studies to evaluate the risk to human pregnancies.

Optimization of Diffusion-Ordered NMR Spectroscopy Experiments for High-Throughput Automation in Human Metabolic Phenotyping.

The diffusion-ordered nuclear magnetic resonance spectroscopy (DOSY) experiment allows the calculation of diffusion coefficient values of metabolites in complex mixtures. However, this experiment has not yet been broadly used for metabolic profiling due to lack of a standardized protocol. Here we propose a pipeline for the DOSY experimental setup and data processing in metabolic phenotyping studies. Due to the complexity of biological samples, three experiments (a standard DOSY, a relaxation-edited DOSY, and a diffusion-edited DOSY) have been optimized to provide DOSY metabolic profiles with peak-picked diffusion coefficients for over 90% of signals visible in the one-dimensional 1H general biofluid profile in as little as 3 min 36 s. The developed parameter sets and tools are straightforward to implement and can facilitate the use of DOSY for metabolic profiling of human blood plasma and urine samples.

A Computationally Lightweight Algorithm for Deriving Reliable Metabolite Panel Measurements from 1D 1H NMR.

Small Molecule Enhancement SpectroscopY (SMolESY) was employed to develop a unique and fully automated computational solution for the assignment and integration of 1H nuclear magnetic resonance (NMR) signals from metabolites in challenging matrices containing macromolecules (herein blood products). Sensitive and reliable quantitation is provided by instant signal deconvolution and straightforward integration bolstered by spectral resolution enhancement and macromolecular signal suppression. The approach is highly efficient, requiring only standard one-dimensional 1H NMR spectra and avoiding the need for sample preprocessing, complex deconvolution, and spectral baseline fitting. The performance of the algorithm, developed using >4000 NMR serum and plasma spectra, was evaluated using an additional >8800 spectra, yielding an assignment accuracy greater than 99.5% for all 22 metabolites targeted. Further validation of its quantitation capabilities illustrated a reliable performance among challenging phenotypes. The simplicity and complete automation of the approach support the application of NMR-based metabolite panel measurements in clinical and population screening applications.

pJRES Binning Algorithm (JBA): a new method to facilitate the recovery of metabolic information from pJRES 1H NMR spectra.

MOTIVATION: Data processing is a key bottleneck for 1H NMR-based metabolic profiling of complex biological mixtures, such as biofluids. These spectra typically contain several thousands of signals, corresponding to possibly few hundreds of metabolites. A number of binning-based methods have been proposed to reduce the dimensionality of 1 D 1H NMR datasets, including statistical recoupling of variables (SRV). Here, we introduce a new binning method, named JBA ("pJRES Binning Algorithm"), which aims to extend the applicability of SRV to pJRES spectra. RESULTS: The performance of JBA is comprehensively evaluated using 617 plasma 1H NMR spectra from the FGENTCARD cohort. The results presented here show that JBA exhibits higher sensitivity than SRV to detect peaks from low-abundance metabolites. In addition, JBA allows a more efficient removal of spectral variables corresponding to pure electronic noise, and this has a positive impact on multivariate model building. AVAILABILITY AND IMPLEMENTATION: The algorithm is implemented using the MWASTools R/Bioconductor package. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Quantitative Lipoprotein Subclass and Low Molecular Weight Metabolite Analysis in Human Serum and Plasma by 1H NMR Spectroscopy in a Multilaboratory Trial.

We report an extensive 600 MHz NMR trial of quantitative lipoprotein and small-molecule measurements in human blood serum and plasma. Five centers with eleven 600 MHz NMR spectrometers were used to analyze 98 samples including 20 quality controls (QCs), 37 commercially sourced, paired serum and plasma samples, and two National Institute of Science and Technology (NIST) reference material 1951c replicates. Samples were analyzed using rigorous protocols for sample preparation and experimental acquisition. A commercial lipoprotein subclass analysis was used to quantify 105 lipoprotein subclasses and 24 low molecular weight metabolites from the NMR spectra. For all spectrometers, the instrument specific variance in measuring internal QCs was lower than the percentage described by the National Cholesterol Education Program (NCEP) criteria for lipid testing [triglycerides <2.7%; cholesterol <2.8%; low-density lipoprotein (LDL) cholesterol <2.8%; high-density lipoprotein (HDL) cholesterol <2.3%], showing exceptional reproducibility for direct quantitation of lipoproteins in both matrixes. The average relative standard deviations (RSDs) for the 105 lipoprotein parameters in the 11 instruments were 4.6% and 3.9% for the two NIST samples, whereas they were 38% and 40% for the 37 commercially sourced plasmas and sera, respectively, showing negligible analytical compared to biological variation. The coefficient of variance (CV) obtained for the quantification of the small molecules across the 11 spectrometers was below 15% for 20 out of the 24 metabolites analyzed. This study provides further evidence of the suitability of NMR for high-throughput lipoprotein subcomponent analysis and small-molecule quantitation with the exceptional required reproducibility for clinical and other regulatory settings.

Characterizing the Biochemical Response to Schistosoma mansoni Infection and Treatment with Praziquantel in Preschool and School Aged Children.

Schistosomiasis is a widespread chronic neglected tropical disease prevalent mostly in children in under-resourced rural areas. Its pathological effects have been clinically characterized, yet the molecular-level effects are understudied. In this study, the biochemical effects of Schistosoma mansoni infection and praziquantel treatment were studied in 130 preschool aged and 159 school aged infected children and 11 noninfected children in Azaguié, Côte d'Ivoire. Urine samples were collected prior to receiving 20, 40, or 60 mg/kg of praziquantel or a placebo, as well as 24 h post-treatment, and at the 3-week follow up. Urinary metabolic phenotypes were measured using 1H NMR spectroscopy, and metabolic variation associated with S. mansoni infection and praziquantel administration was identified using multivariate statistical techniques. Discriminatory metabolic signatures were detected between heavily infected and noninfected children at baseline as well as according to the dose of praziquantel administered 24 h post treatment. These signatures were primarily associated with the metabolic activity of the gut microbiota, gut health and growth biomarkers and energy and liver metabolism. These analyses provide insights into the metabolic phenotype of schistosomiasis and treatment with praziquantel in two important demographics.

J-Resolved 1H NMR 1D-Projections for Large-Scale Metabolic Phenotyping Studies: Application to Blood Plasma Analysis.

1H nuclear magnetic resonance (NMR) spectroscopy-based metabolic phenotyping is now widely used for large-scale epidemiological applications. To minimize signal overlap present in 1D 1H NMR spectra, we have investigated the use of 2D J-resolved (JRES) 1H NMR spectroscopy for large-scale phenotyping studies. In particular, we have evaluated the use of the 1D projections of the 2D JRES spectra (pJRES), which provide single peaks for each of the J-coupled multiplets, using 705 human plasma samples from the FGENTCARD cohort. On the basis of the assessment of several objective analytical criteria (spectral dispersion, attenuation of macromolecular signals, cross-spectral correlation with GC-MS metabolites, analytical reproducibility and biomarker discovery potential), we concluded that the pJRES approach exhibits suitable properties for implementation in large-scale molecular epidemiology workflows.