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Metabolic changes in urine during and after pregnancy in a large, multiethnic population-based cohort study of gestational diabetes.
This study aims to identify novel markers for gestational diabetes (GDM) in the biochemical profile of maternal urine using NMR metabolomics. It also catalogs the general effects of pregnancy and delivery on the urine profile. Urine samples were collected at three time points (visit V1: gestational week 8-20; V2: week 28±2; V3 10-16 weeks post partum) from participants in the STORK Groruddalen program, a prospective, multiethnic cohort study of 823 healthy, pregnant women in Oslo, Norway, and analyzed using (1)H-NMR spectroscopy. Metabolites were identified and quantified where possible. PCA, PLS-DA and univariate statistics were applied and found substantial differences between the time points, dominated by a steady increase of urinary lactose concentrations, and an increase during pregnancy and subsequent dramatic reduction of several unidentified NMR signals between 0.5 and 1.1 ppm. Multivariate methods could not reliably identify GDM cases based on the WHO or graded criteria based on IADPSG definitions, indicating that the pattern of urinary metabolites above micromolar concentrations is not influenced strongly and consistently enough by the disease. However, univariate analysis suggests elevated mean citrate concentrations with increasing hyperglycemia. Multivariate classification with respect to ethnic background produced weak but statistically significant models. These results suggest that although NMR-based metabolomics can monitor changes in the urinary excretion profile of pregnant women, it may not be a prudent choice for the study of GDM.
Authors: Kelly D. Walton, Erin McNulty, Amy V. Nalls, Candace K. Mathiason.
Published: 01-07-2014
Reeves' muntjac deer (Muntiacus reevesi) are a small cervid species native to southeast Asia, and are currently being investigated as a potential model of prion disease transmission and pathogenesis. Vertical transmission is an area of interest among researchers studying infectious diseases, including prion disease, and these investigations require efficient methods for evaluating the effects of maternal infection on reproductive performance. Ultrasonographic examination is a well-established tool for diagnosing pregnancy and assessing fetal health in many animal species1-7, including several species of farmed cervids8-19, however this technique has not been described in Reeves' muntjac deer. Here we describe the application of transabdominal ultrasound to detect pregnancy in muntjac does and to evaluate fetal growth and development throughout the gestational period. Using this procedure, pregnant animals were identified as early as 35 days following doe-buck pairing and this was an effective means to safely monitor the pregnancy at regular intervals. Future goals of this work will include establishing normal fetal measurement references for estimation of gestational age, determining sensitivity and specificity of the technique for diagnosing pregnancy at various stages of gestation, and identifying variations in fetal growth and development under different experimental conditions.
23 Related JoVE Articles!
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Ultrasound Assessment of Endothelial-Dependent Flow-Mediated Vasodilation of the Brachial Artery in Clinical Research
Authors: Hugh Alley, Christopher D. Owens, Warren J. Gasper, S. Marlene Grenon.
Institutions: University of California, San Francisco, Veterans Affairs Medical Center, San Francisco, Veterans Affairs Medical Center, San Francisco.
The vascular endothelium is a monolayer of cells that cover the interior of blood vessels and provide both structural and functional roles. The endothelium acts as a barrier, preventing leukocyte adhesion and aggregation, as well as controlling permeability to plasma components. Functionally, the endothelium affects vessel tone. Endothelial dysfunction is an imbalance between the chemical species which regulate vessel tone, thombroresistance, cellular proliferation and mitosis. It is the first step in atherosclerosis and is associated with coronary artery disease, peripheral artery disease, heart failure, hypertension, and hyperlipidemia. The first demonstration of endothelial dysfunction involved direct infusion of acetylcholine and quantitative coronary angiography. Acetylcholine binds to muscarinic receptors on the endothelial cell surface, leading to an increase of intracellular calcium and increased nitric oxide (NO) production. In subjects with an intact endothelium, vasodilation was observed while subjects with endothelial damage experienced paradoxical vasoconstriction. There exists a non-invasive, in vivo method for measuring endothelial function in peripheral arteries using high-resolution B-mode ultrasound. The endothelial function of peripheral arteries is closely related to coronary artery function. This technique measures the percent diameter change in the brachial artery during a period of reactive hyperemia following limb ischemia. This technique, known as endothelium-dependent, flow-mediated vasodilation (FMD) has value in clinical research settings. However, a number of physiological and technical issues can affect the accuracy of the results and appropriate guidelines for the technique have been published. Despite the guidelines, FMD remains heavily operator dependent and presents a steep learning curve. This article presents a standardized method for measuring FMD in the brachial artery on the upper arm and offers suggestions to reduce intra-operator variability.
Medicine, Issue 92, endothelial function, endothelial dysfunction, brachial artery, peripheral artery disease, ultrasound, vascular, endothelium, cardiovascular disease.
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Fetal Echocardiography and Pulsed-wave Doppler Ultrasound in a Rabbit Model of Intrauterine Growth Restriction
Authors: Ryan Hodges, Masayuki Endo, Andre La Gerche, Elisenda Eixarch, Philip DeKoninck, Vessilina Ferferieva, Jan D'hooge, Euan M. Wallace, Jan Deprest.
Institutions: University Hospitals Leuven, Monash University, Victoria, Australia, Katholieke Universiteit Leuven, Institut d'Investigacions Biomediques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER).
Fetal intrauterine growth restriction (IUGR) results in abnormal cardiac function that is apparent antenatally due to advances in fetoplacental Doppler ultrasound and fetal echocardiography. Increasingly, these imaging modalities are being employed clinically to examine cardiac function and assess wellbeing in utero, thereby guiding timing of birth decisions. Here, we used a rabbit model of IUGR that allows analysis of cardiac function in a clinically relevant way. Using isoflurane induced anesthesia, IUGR is surgically created at gestational age day 25 by performing a laparotomy, exposing the bicornuate uterus and then ligating 40-50% of uteroplacental vessels supplying each gestational sac in a single uterine horn. The other horn in the rabbit bicornuate uterus serves as internal control fetuses. Then, after recovery at gestational age day 30 (full term), the same rabbit undergoes examination of fetal cardiac function. Anesthesia is induced with ketamine and xylazine intramuscularly, then maintained by a continuous intravenous infusion of ketamine and xylazine to minimize iatrogenic effects on fetal cardiac function. A repeat laparotomy is performed to expose each gestational sac and a microultrasound examination (VisualSonics VEVO 2100) of fetal cardiac function is performed. Placental insufficiency is evident by a raised pulsatility index or an absent or reversed end diastolic flow of the umbilical artery Doppler waveform. The ductus venosus and middle cerebral artery Doppler is then examined. Fetal echocardiography is performed by recording B mode, M mode and flow velocity waveforms in lateral and apical views. Offline calculations determine standard M-mode cardiac variables, tricuspid and mitral annular plane systolic excursion, speckle tracking and strain analysis, modified myocardial performance index and vascular flow velocity waveforms of interest. This small animal model of IUGR therefore affords examination of in utero cardiac function that is consistent with current clinical practice and is therefore useful in a translational research setting.
Medicine, Issue 76, Developmental Biology, Biomedical Engineering, Molecular Biology, Anatomy, Physiology, Cardiology, Fetal Therapies, Obstetric Surgical Procedures, Fetal Development, Surgical Procedures, Operative, intrauterine growth restriction, fetal echocardiography, Doppler ultrasound, fetal hemodynamics, animal model, clinical techniques
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Determination of the Transport Rate of Xenobiotics and Nanomaterials Across the Placenta using the ex vivo Human Placental Perfusion Model
Authors: Stefanie Grafmüller, Pius Manser, Harald F. Krug, Peter Wick, Ursula von Mandach.
Institutions: University Hospital Zurich, EMPA Swiss Federal Laboratories for Materials Testing and Research, University of Bern.
Decades ago the human placenta was thought to be an impenetrable barrier between mother and unborn child. However, the discovery of thalidomide-induced birth defects and many later studies afterwards proved the opposite. Today several harmful xenobiotics like nicotine, heroin, methadone or drugs as well as environmental pollutants were described to overcome this barrier. With the growing use of nanotechnology, the placenta is likely to come into contact with novel nanoparticles either accidentally through exposure or intentionally in the case of potential nanomedical applications. Data from animal experiments cannot be extrapolated to humans because the placenta is the most species-specific mammalian organ 1. Therefore, the ex vivo dual recirculating human placental perfusion, developed by Panigel et al. in 1967 2 and continuously modified by Schneider et al. in 1972 3, can serve as an excellent model to study the transfer of xenobiotics or particles. Here, we focus on the ex vivo dual recirculating human placental perfusion protocol and its further development to acquire reproducible results. The placentae were obtained after informed consent of the mothers from uncomplicated term pregnancies undergoing caesarean delivery. The fetal and maternal vessels of an intact cotyledon were cannulated and perfused at least for five hours. As a model particle fluorescently labelled polystyrene particles with sizes of 80 and 500 nm in diameter were added to the maternal circuit. The 80 nm particles were able to cross the placental barrier and provide a perfect example for a substance which is transferred across the placenta to the fetus while the 500 nm particles were retained in the placental tissue or maternal circuit. The ex vivo human placental perfusion model is one of few models providing reliable information about the transport behavior of xenobiotics at an important tissue barrier which delivers predictive and clinical relevant data.
Biomedical Engineering, Issue 76, Medicine, Bioengineering, Anatomy, Physiology, Molecular Biology, Biochemistry, Biophysics, Pharmacology, Obstetrics, Nanotechnology, Placenta, Pharmacokinetics, Nanomedicine, humans, ex vivo perfusion, perfusion, biological barrier, xenobiotics, nanomaterials, clinical model
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Isolation, Culture, and Imaging of Human Fetal Pancreatic Cell Clusters
Authors: Ana D. Lopez, Ayse G. Kayali, Alberto Hayek, Charles C. King.
Institutions: University of California, San Diego.
For almost 30 years, scientists have demonstrated that human fetal ICCs transplanted under the kidney capsule of nude mice matured into functioning endocrine cells, as evidenced by a significant increase in circulating human C-peptide following glucose stimulation1-9. However in vitro, genesis of insulin producing cells from human fetal ICCs is low10; results reminiscent of recent experiments performed with human embryonic stem cells (hESC), a renewable source of cells that hold great promise as a potential therapeutic treatment for type 1 diabetes. Like ICCs, transplantation of partially differentiated hESC generate glucose responsive, insulin producing cells, but in vitro genesis of insulin producing cells from hESC is much less robust11-17. A complete understanding of the factors that influence the growth and differentiation of endocrine precursor cells will likely require data generated from both ICCs and hESC. While a number of protocols exist to generate insulin producing cells from hESC in vitro11-22, far fewer exist for ICCs10,23,24. Part of that discrepancy likely comes from the difficulty of working with human fetal pancreas. Towards that end, we have continued to build upon existing methods to isolate fetal islets from human pancreases with gestational ages ranging from 12 to 23 weeks, grow the cells as a monolayer or in suspension, and image for cell proliferation, pancreatic markers and human hormones including glucagon and C-peptide. ICCs generated by the protocol described below result in C-peptide release after transplantation under the kidney capsule of nude mice that are similar to C-peptide levels obtained by transplantation of fresh tissue6. Although the examples presented here focus upon the pancreatic endoderm proliferation and β cell genesis, the protocol can be employed to study other aspects of pancreatic development, including exocrine, ductal, and other hormone producing cells.
Medicine, Issue 87, human fetal pancreas, islet cell cluster (ICC), transplantation, immunofluorescence, endocrine cell proliferation, differentiation, C-peptide
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A Strategy for Sensitive, Large Scale Quantitative Metabolomics
Authors: Xiaojing Liu, Zheng Ser, Ahmad A. Cluntun, Samantha J. Mentch, Jason W. Locasale.
Institutions: Cornell University, Cornell University.
Metabolite profiling has been a valuable asset in the study of metabolism in health and disease. However, current platforms have different limiting factors, such as labor intensive sample preparations, low detection limits, slow scan speeds, intensive method optimization for each metabolite, and the inability to measure both positively and negatively charged ions in single experiments. Therefore, a novel metabolomics protocol could advance metabolomics studies. Amide-based hydrophilic chromatography enables polar metabolite analysis without any chemical derivatization. High resolution MS using the Q-Exactive (QE-MS) has improved ion optics, increased scan speeds (256 msec at resolution 70,000), and has the capability of carrying out positive/negative switching. Using a cold methanol extraction strategy, and coupling an amide column with QE-MS enables robust detection of 168 targeted polar metabolites and thousands of additional features simultaneously.  Data processing is carried out with commercially available software in a highly efficient way, and unknown features extracted from the mass spectra can be queried in databases.
Chemistry, Issue 87, high-resolution mass spectrometry, metabolomics, positive/negative switching, low mass calibration, Orbitrap
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The Use of Gas Chromatography to Analyze Compositional Changes of Fatty Acids in Rat Liver Tissue during Pregnancy
Authors: Helena L. Fisk, Annette L. West, Caroline E. Childs, Graham C. Burdge, Philip C. Calder.
Institutions: University of Southampton.
Gas chromatography (GC) is a highly sensitive method used to identify and quantify the fatty acid content of lipids from tissues, cells, and plasma/serum, yielding results with high accuracy and high reproducibility. In metabolic and nutrition studies GC allows assessment of changes in fatty acid concentrations following interventions or during changes in physiological state such as pregnancy. Solid phase extraction (SPE) using aminopropyl silica cartridges allows separation of the major lipid classes including triacylglycerols, different phospholipids, and cholesteryl esters (CE). GC combined with SPE was used to analyze the changes in fatty acid composition of the CE fraction in the livers of virgin and pregnant rats that had been fed various high and low fat diets. There are significant diet/pregnancy interaction effects upon the omega-3 and omega-6 fatty acid content of liver CE, indicating that pregnant females have a different response to dietary manipulation than is seen among virgin females.
Chemistry, Issue 85, gas chromatography, fatty acid, pregnancy, cholesteryl ester, solid phase extraction, polyunsaturated fatty acids
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The Use of Magnetic Resonance Spectroscopy as a Tool for the Measurement of Bi-hemispheric Transcranial Electric Stimulation Effects on Primary Motor Cortex Metabolism
Authors: Sara Tremblay, Vincent Beaulé, Sébastien Proulx, Louis-Philippe Lafleur, Julien Doyon, Małgorzata Marjańska, Hugo Théoret.
Institutions: University of Montréal, McGill University, University of Minnesota.
Transcranial direct current stimulation (tDCS) is a neuromodulation technique that has been increasingly used over the past decade in the treatment of neurological and psychiatric disorders such as stroke and depression. Yet, the mechanisms underlying its ability to modulate brain excitability to improve clinical symptoms remains poorly understood 33. To help improve this understanding, proton magnetic resonance spectroscopy (1H-MRS) can be used as it allows the in vivo quantification of brain metabolites such as γ-aminobutyric acid (GABA) and glutamate in a region-specific manner 41. In fact, a recent study demonstrated that 1H-MRS is indeed a powerful means to better understand the effects of tDCS on neurotransmitter concentration 34. This article aims to describe the complete protocol for combining tDCS (NeuroConn MR compatible stimulator) with 1H-MRS at 3 T using a MEGA-PRESS sequence. We will describe the impact of a protocol that has shown great promise for the treatment of motor dysfunctions after stroke, which consists of bilateral stimulation of primary motor cortices 27,30,31. Methodological factors to consider and possible modifications to the protocol are also discussed.
Neuroscience, Issue 93, proton magnetic resonance spectroscopy, transcranial direct current stimulation, primary motor cortex, GABA, glutamate, stroke
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Multi-step Preparation Technique to Recover Multiple Metabolite Compound Classes for In-depth and Informative Metabolomic Analysis
Authors: Charmion Cruickshank-Quinn, Kevin D. Quinn, Roger Powell, Yanhui Yang, Michael Armstrong, Spencer Mahaffey, Richard Reisdorph, Nichole Reisdorph.
Institutions: National Jewish Health, University of Colorado Denver.
Metabolomics is an emerging field which enables profiling of samples from living organisms in order to obtain insight into biological processes. A vital aspect of metabolomics is sample preparation whereby inconsistent techniques generate unreliable results. This technique encompasses protein precipitation, liquid-liquid extraction, and solid-phase extraction as a means of fractionating metabolites into four distinct classes. Improved enrichment of low abundance molecules with a resulting increase in sensitivity is obtained, and ultimately results in more confident identification of molecules. This technique has been applied to plasma, bronchoalveolar lavage fluid, and cerebrospinal fluid samples with volumes as low as 50 µl.  Samples can be used for multiple downstream applications; for example, the pellet resulting from protein precipitation can be stored for later analysis. The supernatant from that step undergoes liquid-liquid extraction using water and strong organic solvent to separate the hydrophilic and hydrophobic compounds. Once fractionated, the hydrophilic layer can be processed for later analysis or discarded if not needed. The hydrophobic fraction is further treated with a series of solvents during three solid-phase extraction steps to separate it into fatty acids, neutral lipids, and phospholipids. This allows the technician the flexibility to choose which class of compounds is preferred for analysis. It also aids in more reliable metabolite identification since some knowledge of chemical class exists.
Bioengineering, Issue 89, plasma, chemistry techniques, analytical, solid phase extraction, mass spectrometry, metabolomics, fluids and secretions, profiling, small molecules, lipids, liquid chromatography, liquid-liquid extraction, cerebrospinal fluid, bronchoalveolar lavage fluid
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Metabolomic Analysis of Rat Brain by High Resolution Nuclear Magnetic Resonance Spectroscopy of Tissue Extracts
Authors: Norbert W. Lutz, Evelyne Béraud, Patrick J. Cozzone.
Institutions: Aix-Marseille Université, Aix-Marseille Université.
Studies of gene expression on the RNA and protein levels have long been used to explore biological processes underlying disease. More recently, genomics and proteomics have been complemented by comprehensive quantitative analysis of the metabolite pool present in biological systems. This strategy, termed metabolomics, strives to provide a global characterization of the small-molecule complement involved in metabolism. While the genome and the proteome define the tasks cells can perform, the metabolome is part of the actual phenotype. Among the methods currently used in metabolomics, spectroscopic techniques are of special interest because they allow one to simultaneously analyze a large number of metabolites without prior selection for specific biochemical pathways, thus enabling a broad unbiased approach. Here, an optimized experimental protocol for metabolomic analysis by high-resolution NMR spectroscopy is presented, which is the method of choice for efficient quantification of tissue metabolites. Important strengths of this method are (i) the use of crude extracts, without the need to purify the sample and/or separate metabolites; (ii) the intrinsically quantitative nature of NMR, permitting quantitation of all metabolites represented by an NMR spectrum with one reference compound only; and (iii) the nondestructive nature of NMR enabling repeated use of the same sample for multiple measurements. The dynamic range of metabolite concentrations that can be covered is considerable due to the linear response of NMR signals, although metabolites occurring at extremely low concentrations may be difficult to detect. For the least abundant compounds, the highly sensitive mass spectrometry method may be advantageous although this technique requires more intricate sample preparation and quantification procedures than NMR spectroscopy. We present here an NMR protocol adjusted to rat brain analysis; however, the same protocol can be applied to other tissues with minor modifications.
Neuroscience, Issue 91, metabolomics, brain tissue, rodents, neurochemistry, tissue extracts, NMR spectroscopy, quantitative metabolite analysis, cerebral metabolism, metabolic profile
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Construction of Vapor Chambers Used to Expose Mice to Alcohol During the Equivalent of all Three Trimesters of Human Development
Authors: Russell A. Morton, Marvin R. Diaz, Lauren A. Topper, C. Fernando Valenzuela.
Institutions: University of New Mexico Health Sciences Center.
Exposure to alcohol during development can result in a constellation of morphological and behavioral abnormalities that are collectively known as Fetal Alcohol Spectrum Disorders (FASDs). At the most severe end of the spectrum is Fetal Alcohol Syndrome (FAS), characterized by growth retardation, craniofacial dysmorphology, and neurobehavioral deficits. Studies with animal models, including rodents, have elucidated many molecular and cellular mechanisms involved in the pathophysiology of FASDs. Ethanol administration to pregnant rodents has been used to model human exposure during the first and second trimesters of pregnancy. Third trimester ethanol consumption in humans has been modeled using neonatal rodents. However, few rodent studies have characterized the effect of ethanol exposure during the equivalent to all three trimesters of human pregnancy, a pattern of exposure that is common in pregnant women. Here, we show how to build vapor chambers from readily obtainable materials that can each accommodate up to six standard mouse cages. We describe a vapor chamber paradigm that can be used to model exposure to ethanol, with minimal handling, during all three trimesters. Our studies demonstrate that pregnant dams developed significant metabolic tolerance to ethanol. However, neonatal mice did not develop metabolic tolerance and the number of fetuses, fetus weight, placenta weight, number of pups/litter, number of dead pups/litter, and pup weight were not significantly affected by ethanol exposure. An important advantage of this paradigm is its applicability to studies with genetically-modified mice. Additionally, this paradigm minimizes handling of animals, a major confound in fetal alcohol research.
Medicine, Issue 89, fetal, ethanol, exposure, paradigm, vapor, development, alcoholism, teratogenic, animal, mouse, model
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Accelerated Type 1 Diabetes Induction in Mice by Adoptive Transfer of Diabetogenic CD4+ T Cells
Authors: Gregory Berry, Hanspeter Waldner.
Institutions: Pennsylvania State University College of Medicine.
The nonobese diabetic (NOD) mouse spontaneously develops autoimmune diabetes after 12 weeks of age and is the most extensively studied animal model of human Type 1 diabetes (T1D). Cell transfer studies in irradiated recipient mice have established that T cells are pivotal in T1D pathogenesis in this model. We describe herein a simple method to rapidly induce T1D by adoptive transfer of purified, primary CD4+ T cells from pre-diabetic NOD mice transgenic for the islet-specific T cell receptor (TCR) BDC2.5 into NOD.SCID recipient mice. The major advantages of this technique are that isolation and adoptive transfer of diabetogenic T cells can be completed within the same day, irradiation of the recipients is not required, and a high incidence of T1D is elicited within 2 weeks after T cell transfer. Thus, studies of pathogenesis and therapeutic interventions in T1D can proceed at a faster rate than with methods that rely on heterogenous T cell populations or clones derived from diabetic NOD mice.
Immunology, Issue 75, Medicine, Cellular Biology, Molecular Biology, Microbiology, Anatomy, Physiology, Biomedical Engineering, Genetics, Surgery, Type 1 diabetes, CD4+ T cells, diabetogenic T cells, T cell transfer, diabetes induction method, diabetes, T cells, isolation, cell sorting, FACS, transgenic mice, animal model
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Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Authors: Phoebe Spetsieris, Yilong Ma, Shichun Peng, Ji Hyun Ko, Vijay Dhawan, Chris C. Tang, David Eidelberg.
Institutions: The Feinstein Institute for Medical Research.
The scaled subprofile model (SSM)1-4 is a multivariate PCA-based algorithm that identifies major sources of variation in patient and control group brain image data while rejecting lesser components (Figure 1). Applied directly to voxel-by-voxel covariance data of steady-state multimodality images, an entire group image set can be reduced to a few significant linearly independent covariance patterns and corresponding subject scores. Each pattern, termed a group invariant subprofile (GIS), is an orthogonal principal component that represents a spatially distributed network of functionally interrelated brain regions. Large global mean scalar effects that can obscure smaller network-specific contributions are removed by the inherent logarithmic conversion and mean centering of the data2,5,6. Subjects express each of these patterns to a variable degree represented by a simple scalar score that can correlate with independent clinical or psychometric descriptors7,8. Using logistic regression analysis of subject scores (i.e. pattern expression values), linear coefficients can be derived to combine multiple principal components into single disease-related spatial covariance patterns, i.e. composite networks with improved discrimination of patients from healthy control subjects5,6. Cross-validation within the derivation set can be performed using bootstrap resampling techniques9. Forward validation is easily confirmed by direct score evaluation of the derived patterns in prospective datasets10. Once validated, disease-related patterns can be used to score individual patients with respect to a fixed reference sample, often the set of healthy subjects that was used (with the disease group) in the original pattern derivation11. These standardized values can in turn be used to assist in differential diagnosis12,13 and to assess disease progression and treatment effects at the network level7,14-16. We present an example of the application of this methodology to FDG PET data of Parkinson's Disease patients and normal controls using our in-house software to derive a characteristic covariance pattern biomarker of disease.
Medicine, Issue 76, Neurobiology, Neuroscience, Anatomy, Physiology, Molecular Biology, Basal Ganglia Diseases, Parkinsonian Disorders, Parkinson Disease, Movement Disorders, Neurodegenerative Diseases, PCA, SSM, PET, imaging biomarkers, functional brain imaging, multivariate spatial covariance analysis, global normalization, differential diagnosis, PD, brain, imaging, clinical techniques
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Magnetic Resonance Spectroscopy of live Drosophila melanogaster using Magic Angle Spinning
Authors: Valeria Righi, Yiorgos Apidianakis, Laurence G. Rahme, A. Aria Tzika.
Institutions: Massachusetts General Hospital, Harvard Medical School, Shriners Burn Institute, Harvard Medical School, Massachusetts General Hospital, Harvard Medical School.
High-Resolution Magic Angle Spinning (HRMAS) proton magnetic resonance spectroscopy (1H-MRS) is a novel non-destructive technique that improves spectral line-widths and allows high-resolution spectra to be obtained from extracts, intact cells, cell cultures, and more importantly intact tissue to investigate relationships between metabolites and cellular processes. In vivo HRMAS 1H-MRS studies have yet to be reported in the live fruit fly Drosophila melanogaster. Drosophila, as a simpler genetic organism, allows the multiple biological functions and various evolutionarily conserved signaling pathways to be examined at the whole organism level and it is a useful model for investigating genetics and physiology. To this end, we developed and implemented an in vivo HRMAS 1H-MRS method to investigate live Drosophila at 14.1 T. Here, we outline an HRMAS 1H-MRS protocol for the molecular characterization of Drosophila with a conventional MR spectrometer equipped with an HRMAS probe. This technique is a novel, in vivo, non-destructive Drosophila metabolite measurement approach, which enables the identification of disease biomarkers and thus may contribute to novel therapeutic development.
Neuroscience, Issue 38, Magnetic Resonance Spectroscopy (MRS), High Resolution Magic Angle Spinning (HRMAS), Total Through Bond Correlation Spectroscopy (TOBSY), Drosophila melanogaster
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One-step Metabolomics: Carbohydrates, Organic and Amino Acids Quantified in a Single Procedure
Authors: James D. Shoemaker.
Institutions: Saint Louis University School of Medicine.
Every infant born in the US is now screened for up to 42 rare genetic disorders called "inborn errors of metabolism". The screening method is based on tandem mass spectrometry and quantifies acylcarnitines as a screen for organic acidemias and also measures amino acids. All states also perform enzymatic testing for carbohydrate disorders such as galactosemia. Because the results can be non-specific, follow-up testing of positive results is required using a more definitive method. The present report describes the "urease" method of sample preparation for inborn error screening. Crystalline urease enzyme is used to remove urea from body fluids which permits most other water-soluble metabolites to be dehydrated and derivatized for gas chromatography in a single procedure. Dehydration by evaporation in a nitrogen stream is facilitated by adding acetonitrile and methylene chloride. Then, trimethylsilylation takes place in the presence of a unique catalyst, triethylammonium trifluoroacetate. Automated injection and chromatography is followed by macro-driven custom quantification of 192 metabolites and semi-quantification of every major component using specialized libraries of mass spectra of TMS derivatized biological compounds. The analysis may be performed on the widely-used Chemstation platform using the macros and libraries available from the author. In our laboratory, over 16,000 patient samples have been analyzed using the method with a diagnostic yield of about 17%--that is, 17% of the samples results reveal findings that should be acted upon by the ordering physician. Included in these are over 180 confirmed inborn errors, of which about 38% could not have been diagnosed using previous methods.
Biochemistry, Issue 40, metabolomics, gas chromatography/mass spectrometry, GC/MS, inborn errors, vitamin deficiency, BNA analyses, carbohydrate, amino acid, organic acid, urease
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Concentration of Metabolites from Low-density Planktonic Communities for Environmental Metabolomics using Nuclear Magnetic Resonance Spectroscopy
Authors: R. Craig Everroad, Seiji Yoshida, Yuuri Tsuboi, Yasuhiro Date, Jun Kikuchi, Shigeharu Moriya.
Institutions: RIKEN Advanced Science Institute, Yokohama City University, RIKEN Plant Science Center, Nagoya University.
Environmental metabolomics is an emerging field that is promoting new understanding in how organisms respond to and interact with the environment and each other at the biochemical level1. Nuclear magnetic resonance (NMR) spectroscopy is one of several technologies, including gas chromatography–mass spectrometry (GC-MS), with considerable promise for such studies. Advantages of NMR are that it is suitable for untargeted analyses, provides structural information and spectra can be queried in quantitative and statistical manners against recently available databases of individual metabolite spectra2,3. In addition, NMR spectral data can be combined with data from other omics levels (e.g. transcriptomics, genomics) to provide a more comprehensive understanding of the physiological responses of taxa to each other and the environment4,5,6. However, NMR is less sensitive than other metabolomic techniques, making it difficult to apply to natural microbial systems where sample populations can be low-density and metabolite concentrations low compared to metabolites from well-defined and readily extractable sources such as whole tissues, biofluids or cell-cultures. Consequently, the few direct environmental metabolomic studies of microbes performed to date have been limited to culture-based or easily defined high-density ecosystems such as host-symbiont systems, constructed co-cultures or manipulations of the gut environment where stable isotope labeling can be additionally used to enhance NMR signals7,8,9,10,11,12. Methods that facilitate the concentration and collection of environmental metabolites at concentrations suitable for NMR are lacking. Since recent attention has been given to the environmental metabolomics of organisms within the aquatic environment, where much of the energy and material flow is mediated by the planktonic community13,14, we have developed a method for the concentration and extraction of whole-community metabolites from planktonic microbial systems by filtration. Commercially available hydrophilic poly-1,1-difluoroethene (PVDF) filters are specially treated to completely remove extractables, which can otherwise appear as contaminants in subsequent analyses. These treated filters are then used to filter environmental or experimental samples of interest. Filters containing the wet sample material are lyophilized and aqueous-soluble metabolites are extracted directly for conventional NMR spectroscopy using a standardized potassium phosphate extraction buffer2. Data derived from these methods can be analyzed statistically to identify meaningful patterns, or integrated with other omics levels for comprehensive understanding of community and ecosystem function.
Molecular Biology, Issue 62, environmental metabolomics, metabolic profiling, microbial ecology, plankton, NMR spectroscopy, PCA
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Assessment and Evaluation of the High Risk Neonate: The NICU Network Neurobehavioral Scale
Authors: Barry M. Lester, Lynne Andreozzi-Fontaine, Edward Tronick, Rosemarie Bigsby.
Institutions: Brown University, Women & Infants Hospital of Rhode Island, University of Massachusetts, Boston.
There has been a long-standing interest in the assessment of the neurobehavioral integrity of the newborn infant. The NICU Network Neurobehavioral Scale (NNNS) was developed as an assessment for the at-risk infant. These are infants who are at increased risk for poor developmental outcome because of insults during prenatal development, such as substance exposure or prematurity or factors such as poverty, poor nutrition or lack of prenatal care that can have adverse effects on the intrauterine environment and affect the developing fetus. The NNNS assesses the full range of infant neurobehavioral performance including neurological integrity, behavioral functioning, and signs of stress/abstinence. The NNNS is a noninvasive neonatal assessment tool with demonstrated validity as a predictor, not only of medical outcomes such as cerebral palsy diagnosis, neurological abnormalities, and diseases with risks to the brain, but also of developmental outcomes such as mental and motor functioning, behavior problems, school readiness, and IQ. The NNNS can identify infants at high risk for abnormal developmental outcome and is an important clinical tool that enables medical researchers and health practitioners to identify these infants and develop intervention programs to optimize the development of these infants as early as possible. The video shows the NNNS procedures, shows examples of normal and abnormal performance and the various clinical populations in which the exam can be used.
Behavior, Issue 90, NICU Network Neurobehavioral Scale, NNNS, High risk infant, Assessment, Evaluation, Prediction, Long term outcome
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Assessing Hepatic Metabolic Changes During Progressive Colonization of Germ-free Mouse by 1H NMR Spectroscopy
Authors: Peter Heath, Sandrine Paule Claus.
Institutions: The University of Reading, The University of Reading .
It is well known that gut bacteria contribute significantly to the host homeostasis, providing a range of benefits such as immune protection and vitamin synthesis. They also supply the host with a considerable amount of nutrients, making this ecosystem an essential metabolic organ. In the context of increasing evidence of the link between the gut flora and the metabolic syndrome, understanding the metabolic interaction between the host and its gut microbiota is becoming an important challenge of modern biology.1-4 Colonization (also referred to as normalization process) designates the establishment of micro-organisms in a former germ-free animal. While it is a natural process occurring at birth, it is also used in adult germ-free animals to control the gut floral ecosystem and further determine its impact on the host metabolism. A common procedure to control the colonization process is to use the gavage method with a single or a mixture of micro-organisms. This method results in a very quick colonization and presents the disadvantage of being extremely stressful5. It is therefore useful to minimize the stress and to obtain a slower colonization process to observe gradually the impact of bacterial establishment on the host metabolism. In this manuscript, we describe a procedure to assess the modification of hepatic metabolism during a gradual colonization process using a non-destructive metabolic profiling technique. We propose to monitor gut microbial colonization by assessing the gut microbial metabolic activity reflected by the urinary excretion of microbial co-metabolites by 1H NMR-based metabolic profiling. This allows an appreciation of the stability of gut microbial activity beyond the stable establishment of the gut microbial ecosystem usually assessed by monitoring fecal bacteria by DGGE (denaturing gradient gel electrophoresis).6 The colonization takes place in a conventional open environment and is initiated by a dirty litter soiled by conventional animals, which will serve as controls. Rodents being coprophagous animals, this ensures a homogenous colonization as previously described.7 Hepatic metabolic profiling is measured directly from an intact liver biopsy using 1H High Resolution Magic Angle Spinning NMR spectroscopy. This semi-quantitative technique offers a quick way to assess, without damaging the cell structure, the major metabolites such as triglycerides, glucose and glycogen in order to further estimate the complex interaction between the colonization process and the hepatic metabolism7-10. This method can also be applied to any tissue biopsy11,12.
Immunology, Issue 58, Germ-free animal, colonization, NMR, HR MAS NMR, metabonomics
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Sample Preparation of Mycobacterium tuberculosis Extracts for Nuclear Magnetic Resonance Metabolomic Studies
Authors: Denise K. Zinniel, Robert J. Fenton, Steven Halouska, Robert Powers, Raul G. Barletta.
Institutions: University of Nebraska-Lincoln, University of Nebraska-Lincoln.
Mycobacterium tuberculosis is a major cause of mortality in human beings on a global scale. The emergence of both multi- (MDR) and extensively-(XDR) drug-resistant strains threatens to derail current disease control efforts. Thus, there is an urgent need to develop drugs and vaccines that are more effective than those currently available. The genome of M. tuberculosis has been known for more than 10 years, yet there are important gaps in our knowledge of gene function and essentiality. Many studies have since used gene expression analysis at both the transcriptomic and proteomic levels to determine the effects of drugs, oxidants, and growth conditions on the global patterns of gene expression. Ultimately, the final response of these changes is reflected in the metabolic composition of the bacterium including a few thousand small molecular weight chemicals. Comparing the metabolic profiles of wild type and mutant strains, either untreated or treated with a particular drug, can effectively allow target identification and may lead to the development of novel inhibitors with anti-tubercular activity. Likewise, the effects of two or more conditions on the metabolome can also be assessed. Nuclear magnetic resonance (NMR) is a powerful technology that is used to identify and quantify metabolic intermediates. In this protocol, procedures for the preparation of M. tuberculosis cell extracts for NMR metabolomic analysis are described. Cell cultures are grown under appropriate conditions and required Biosafety Level 3 containment,1 harvested, and subjected to mechanical lysis while maintaining cold temperatures to maximize preservation of metabolites. Cell lysates are recovered, filtered sterilized, and stored at ultra-low temperatures. Aliquots from these cell extracts are plated on Middlebrook 7H9 agar for colony-forming units to verify absence of viable cells. Upon two months of incubation at 37 °C, if no viable colonies are observed, samples are removed from the containment facility for downstream processing. Extracts are lyophilized, resuspended in deuterated buffer and injected in the NMR instrument, capturing spectroscopic data that is then subjected to statistical analysis. The procedures described can be applied for both one-dimensional (1D) 1H NMR and two-dimensional (2D) 1H-13C NMR analyses. This methodology provides more reliable small molecular weight metabolite identification and more reliable and sensitive quantitative analyses of cell extract metabolic compositions than chromatographic methods. Variations of the procedure described following the cell lysis step can also be adapted for parallel proteomic analysis.
Infection, Issue 67, Mycobacterium tuberculosis, NMR, Metabolomics, homogenizer, lysis, cell extracts, sample preparation
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A Zebrafish Model of Diabetes Mellitus and Metabolic Memory
Authors: Robert V. Intine, Ansgar S. Olsen, Michael P. Sarras Jr..
Institutions: Rosalind Franklin University of Medicine and Science, Rosalind Franklin University of Medicine and Science.
Diabetes mellitus currently affects 346 million individuals and this is projected to increase to 400 million by 2030. Evidence from both the laboratory and large scale clinical trials has revealed that diabetic complications progress unimpeded via the phenomenon of metabolic memory even when glycemic control is pharmaceutically achieved. Gene expression can be stably altered through epigenetic changes which not only allow cells and organisms to quickly respond to changing environmental stimuli but also confer the ability of the cell to "memorize" these encounters once the stimulus is removed. As such, the roles that these mechanisms play in the metabolic memory phenomenon are currently being examined. We have recently reported the development of a zebrafish model of type I diabetes mellitus and characterized this model to show that diabetic zebrafish not only display the known secondary complications including the changes associated with diabetic retinopathy, diabetic nephropathy and impaired wound healing but also exhibit impaired caudal fin regeneration. This model is unique in that the zebrafish is capable to regenerate its damaged pancreas and restore a euglycemic state similar to what would be expected in post-transplant human patients. Moreover, multiple rounds of caudal fin amputation allow for the separation and study of pure epigenetic effects in an in vivo system without potential complicating factors from the previous diabetic state. Although euglycemia is achieved following pancreatic regeneration, the diabetic secondary complication of fin regeneration and skin wound healing persists indefinitely. In the case of impaired fin regeneration, this pathology is retained even after multiple rounds of fin regeneration in the daughter fin tissues. These observations point to an underlying epigenetic process existing in the metabolic memory state. Here we present the methods needed to successfully generate the diabetic and metabolic memory groups of fish and discuss the advantages of this model.
Medicine, Issue 72, Genetics, Genomics, Physiology, Anatomy, Biomedical Engineering, Metabolomics, Zebrafish, diabetes, metabolic memory, tissue regeneration, streptozocin, epigenetics, Danio rerio, animal model, diabetes mellitus, diabetes, drug discovery, hyperglycemia
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Large Scale Non-targeted Metabolomic Profiling of Serum by Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS)
Authors: Corey D. Broeckling, Adam L. Heuberger, Jessica E. Prenni.
Institutions: Colorado State University.
Non-targeted metabolite profiling by ultra performance liquid chromatography coupled with mass spectrometry (UPLC-MS) is a powerful technique to investigate metabolism. The approach offers an unbiased and in-depth analysis that can enable the development of diagnostic tests, novel therapies, and further our understanding of disease processes. The inherent chemical diversity of the metabolome creates significant analytical challenges and there is no single experimental approach that can detect all metabolites. Additionally, the biological variation in individual metabolism and the dependence of metabolism on environmental factors necessitates large sample numbers to achieve the appropriate statistical power required for meaningful biological interpretation. To address these challenges, this tutorial outlines an analytical workflow for large scale non-targeted metabolite profiling of serum by UPLC-MS. The procedure includes guidelines for sample organization and preparation, data acquisition, quality control, and metabolite identification and will enable reliable acquisition of data for large experiments and provide a starting point for laboratories new to non-targeted metabolite profiling by UPLC-MS.
Chemistry, Issue 73, Biochemistry, Genetics, Molecular Biology, Physiology, Genomics, Proteins, Proteomics, Metabolomics, Metabolite Profiling, Non-targeted metabolite profiling, mass spectrometry, Ultra Performance Liquid Chromatography, UPLC-MS, serum, spectrometry
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Purification of Transcripts and Metabolites from Drosophila Heads
Authors: Kurt Jensen, Jonatan Sanchez-Garcia, Caroline Williams, Swati Khare, Krishanu Mathur, Rita M. Graze, Daniel A. Hahn, Lauren M. McIntyre, Diego E. Rincon-Limas, Pedro Fernandez-Funez.
Institutions: University of Florida , University of Florida , University of Florida , University of Florida .
For the last decade, we have tried to understand the molecular and cellular mechanisms of neuronal degeneration using Drosophila as a model organism. Although fruit flies provide obvious experimental advantages, research on neurodegenerative diseases has mostly relied on traditional techniques, including genetic interaction, histology, immunofluorescence, and protein biochemistry. These techniques are effective for mechanistic, hypothesis-driven studies, which lead to a detailed understanding of the role of single genes in well-defined biological problems. However, neurodegenerative diseases are highly complex and affect multiple cellular organelles and processes over time. The advent of new technologies and the omics age provides a unique opportunity to understand the global cellular perturbations underlying complex diseases. Flexible model organisms such as Drosophila are ideal for adapting these new technologies because of their strong annotation and high tractability. One challenge with these small animals, though, is the purification of enough informational molecules (DNA, mRNA, protein, metabolites) from highly relevant tissues such as fly brains. Other challenges consist of collecting large numbers of flies for experimental replicates (critical for statistical robustness) and developing consistent procedures for the purification of high-quality biological material. Here, we describe the procedures for collecting thousands of fly heads and the extraction of transcripts and metabolites to understand how global changes in gene expression and metabolism contribute to neurodegenerative diseases. These procedures are easily scalable and can be applied to the study of proteomic and epigenomic contributions to disease.
Genetics, Issue 73, Biochemistry, Molecular Biology, Neurobiology, Neuroscience, Bioengineering, Cellular Biology, Anatomy, Neurodegenerative Diseases, Biological Assay, Drosophila, fruit fly, head separation, purification, mRNA, RNA, cDNA, DNA, transcripts, metabolites, replicates, SCA3, neurodegeneration, NMR, gene expression, animal model
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Basics of Multivariate Analysis in Neuroimaging Data
Authors: Christian Georg Habeck.
Institutions: Columbia University.
Multivariate analysis techniques for neuroimaging data have recently received increasing attention as they have many attractive features that cannot be easily realized by the more commonly used univariate, voxel-wise, techniques1,5,6,7,8,9. Multivariate approaches evaluate correlation/covariance of activation across brain regions, rather than proceeding on a voxel-by-voxel basis. Thus, their results can be more easily interpreted as a signature of neural networks. Univariate approaches, on the other hand, cannot directly address interregional correlation in the brain. Multivariate approaches can also result in greater statistical power when compared with univariate techniques, which are forced to employ very stringent corrections for voxel-wise multiple comparisons. Further, multivariate techniques also lend themselves much better to prospective application of results from the analysis of one dataset to entirely new datasets. Multivariate techniques are thus well placed to provide information about mean differences and correlations with behavior, similarly to univariate approaches, with potentially greater statistical power and better reproducibility checks. In contrast to these advantages is the high barrier of entry to the use of multivariate approaches, preventing more widespread application in the community. To the neuroscientist becoming familiar with multivariate analysis techniques, an initial survey of the field might present a bewildering variety of approaches that, although algorithmically similar, are presented with different emphases, typically by people with mathematics backgrounds. We believe that multivariate analysis techniques have sufficient potential to warrant better dissemination. Researchers should be able to employ them in an informed and accessible manner. The current article is an attempt at a didactic introduction of multivariate techniques for the novice. A conceptual introduction is followed with a very simple application to a diagnostic data set from the Alzheimer s Disease Neuroimaging Initiative (ADNI), clearly demonstrating the superior performance of the multivariate approach.
JoVE Neuroscience, Issue 41, fMRI, PET, multivariate analysis, cognitive neuroscience, clinical neuroscience
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Testing Nicotine Tolerance in Aphids Using an Artificial Diet Experiment
Authors: John Sawyer Ramsey, Georg Jander.
Institutions: Cornell University.
Plants may upregulate the production of many different seconday metabolites in response to insect feeding. One of these metabolites, nicotine, is well know to have insecticidal properties. One response of tobacco plants to herbivory, or being gnawed upon by insects, is to increase the production of this neurotoxic alkaloid. Here, we will demonstrate how to set up an experiment to address this question of whether a tobacco-adapted strain of the green peach aphid, Myzus persicae, can tolerate higher levels of nicotine than the a strain of this insect that does not infest tobacco in the field.
Plant Biology, Issue 15, Annual Review, Nicotine, Aphids, Plant Feeding Resistance, Tobacco
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JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

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In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.