A 3D numerical study of the collateral capacity of the circle of Willis with anatomical variation in the posterior circulation

Background

The Circle of Willis (CoW) is the most important collateral pathway of the cerebral artery. The present study aims to investigate the collateral capacity of CoW with anatomical variation when unilateral internalcarotid artery (ICA) is occluded.

Methods

Basing on MRI data, we have reconstructed eight 3D models with variations in the posterior circulation of the CoW and set four different degrees of stenosis in the right ICA, namely 24%, 43%, 64% and 79%, respectively. Finally, a total of 40 models are performed with computational fluid dynamics simulations. All of the simulations share the same boundary condition with static pressure and the volume flow rate (VFR) are obtained to evaluate their collateral capacity.

Results

As for the middle cerebral artery (MCA) and the anterior cerebral artery (ACA), the transitional-type model possesses the best collateral capacity. But for the posterior cerebral artery (PCA), unilateral stenosis of ICA has the weakest influence on the unilateral posterior communicating artery (PCoA) absent model. We also find that the full fetal-type posterior circle of Willis is an utmost dangerous variation which must be paid more attention.

Conclusion

The results demonstrate that different models have different collateral capacities in coping stenosis of unilateral ICA and these differences can be reflected by different outlets. The study could be used as a reference for neurosurgeon in choosing the best treatment strategy.

     

Optimization of fecal sample preparation for untargeted LC-HRMS based metabolomics

Introduction

Collecting feces is easy. It offers direct outcome to endogenous and microbial metabolites.

Objectives

In a context of lack of consensus about fecal sample preparation, especially in animal species, we developed a robust protocol allowing untargeted LC-HRMS fingerprinting.

Methods

The conditions of extraction (quantity, preparation, solvents, dilutions) were investigated in bovine feces.

Results

A rapid and simple protocol involving feces extraction with methanol (1/3, M/V) followed by centrifugation and a step filtration (10 kDa) was developed.

Conclusion

The workflow generated repeatable and informative fingerprints for robust metabolome characterization.

     

A novel method to harvest <Emphasis Type="Italic">Chlorella</Emphasis> sp. by co-flocculation/air flotation

Objectives

To develop a more effective dissolved air flotation process for harvesting microalgae biomass, a co-flocculation/air flotation (CAF) system was developed that uses an ejector followed by a helix tube flocculation reactor (HTFR) as a co-flocculation device to harvest Chlorella sp. 64.01.

Results

The optimal size distribution of micro-bubbles and an air release efficiency of 96 % were obtained when the flow ratio of inlet fluid (raw water) to motive fluid (saturated water) of the ejector was 0.14. With a reaction time of 24 s in the HTFR, microalgae cells and micro-bubbles were well flocculated, and these aerated flocs caused a fast rising velocity (96 m/h) and high harvesting efficiency (94 %).

Conclusions

In a CAF process, micro-bubbles can be encapsulated into microalgae flocs, which makes aerated flocs more stable. CAF is an effective approach to harvesting microalgae.

     

Iridoid and phenylethanoid/phenylpropanoid metabolite profiles of <Emphasis Type="Italic">Scrophularia</Emphasis> and <Emphasis Type="Italic">Verbascum</Emphasis> species used medicinally in North America

Introduction

Botanicals containing iridoid and phenylethanoid/phenylpropanoid glycosides are used worldwide for the treatment of inflammatory musculoskeletal conditions that are primary causes of human years lived with disability, such as arthritis and lower back pain.

Objectives

We report the analysis of candidate anti-inflammatory metabolites of several endemic Scrophularia species and Verbascum thapsus used medicinally by peoples of North America.

Methods

Leaves, stems, and roots were analyzed by ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) and partial least squares-discriminant analysis (PLS-DA) was performed in MetaboAnalyst 3.0 after processing the datasets in Progenesis QI.

Results

Comparison of the datasets revealed significant and differential accumulation of iridoid and phenylethanoid/phenylpropanoid glycosides in the tissues of the endemic Scrophularia species and Verbascum thapsus.

Conclusions

Our investigation identified several species of pharmacological interest as good sources for harpagoside and other important anti-inflammatory metabolites.

     

Intensive determination of storage condition effects on human plasma metabolomics

Introduction

Human plasma metabolomics offer powerful tools for understanding disease mechanisms and identifying clinical biomarkers for diagnosis, efficacy prediction and patient stratification. Although storage conditions can affect the reliability of data from metabolites, strict control of these conditions remains challenging, particularly when clinical samples are included from multiple centers. Therefore, it is necessary to consider stability profiles of each analyte.

Objectives

The purpose of this study was to extract unstable metabolites from vast metabolome data and identify factors that cause instability.

Method

Plasma samples were obtained from five healthy volunteers, were stored under ten different conditions of time and temperature and were quantified using leading-edge metabolomics. Instability was evaluated by comparing quantitation values under each storage condition with those obtained after ?80 °C storage.

Result

Stability profiling of the 992 metabolites showed time- and temperature-dependent increases in numbers of significantly changed metabolites. This large volume of data enabled comparisons of unstable metabolites with their related molecules and allowed identification of causative factors, including compound-specific enzymatic activity in plasma and chemical reactivity. Furthermore, these analyses indicated extreme instability of 1-docosahexaenoylglycerol, 1-arachidonoylglycerophosphate, cystine, cysteine and N⁶-methyladenosine.

Conclusion

A large volume of data regarding storage stability was obtained. These data are a contribution to the discovery of biomarker candidates without misselection based on unreliable values and to the establishment of suitable handling procedures for targeted biomarker quantification.

     

Feed-forward neural network model for hunger and satiety related VAS score prediction

Background

An artificial neural network approach was chosen to model the outcome of the complex signaling pathways in the gastro-intestinal tract and other peripheral organs that eventually produce the satiety feeling in the brain upon feeding.

Methods

A multilayer feed-forward neural network was trained with sets of experimental data relating concentration-time courses of plasma satiety hormones to Visual Analog Scales (VAS) scores. The network successfully predicted VAS responses from sets of satiety hormone data obtained in experiments using different food compositions.

Results

The correlation coefficients for the predicted VAS responses for test sets having i) a full set of three satiety hormones, ii) a set of only two satiety hormones, and iii) a set of only one satiety hormone were 0.96, 0.96, and 0.89, respectively. The predicted VAS responses discriminated the satiety effects of high satiating food types from less satiating food types both in orally fed and ileal infused forms.

Conclusions

From this application of artificial neural networks, one may conclude that neural network models are very suitable to describe situations where behavior is complex and incompletely understood. However, training data sets that fit the experimental conditions need to be available.

     

Group-wise ANOVA simultaneous component analysis for designed <Emphasis Type="Italic">omics</Emphasis> experiments

Introduction

Modern omics experiments pertain not only to the measurement of many variables but also follow complex experimental designs where many factors are manipulated at the same time. This data can be conveniently analyzed using multivariate tools like ANOVA-simultaneous component analysis (ASCA) which allows interpretation of the variation induced by the different factors in a principal component analysis fashion. However, while in general only a subset of the measured variables may be related to the problem studied, all variables contribute to the final model and this may hamper interpretation.

Objectives

We introduce here a sparse implementation of ASCA termed group-wise ANOVA-simultaneous component analysis (GASCA) with the aim of obtaining models that are easier to interpret.

Methods

GASCA is based on the concept of group-wise sparsity introduced in group-wise principal components analysis where structure to impose sparsity is defined in terms of groups of correlated variables found in the correlation matrices calculated from the effect matrices.

Results

The GASCA model, containing only selected subsets of the original variables, is easier to interpret and describes relevant biological processes.

Conclusions

GASCA is applicable to any kind of omics data obtained through designed experiments such as, but not limited to, metabolomic, proteomic and gene expression data.

     

Markov modeling in hepatitis B screening and linkage to care

Background

With up to 240 million people chronically infected with hepatitis B worldwide, including an estimated 2 million in the United States, widespread screening is needed to link the infected to care and decrease the possible consequences of untreated infection, including liver cancer, cirrhosis and death. Screening is currently fraught with challenges in both the developed and developing world. New point-of-care tests may have advantages over standard-of-care tests in terms of cost-effectiveness and linkage to care. Stochastic modeling is applied here for relative utility assessment of point-of-care tests and standard-of-care tests for screening.

Methods

We analyzed effects of point-of-care versus standard-of-care testing using Markov models for disease progression in individual patients. Simulations of large cohorts with distinctly quantified models permitted the assessment of particular screening schemes. The validity of the trends observed is supported by sensitivity analyses for the simulation parameters.

Results

Increased utilization of point-of-care screening was shown to decrease hepatitis B-related mortalities and increase life expectancy at low projected expense.

Conclusions

The results suggest that standard-of-care screening should be substituted by point-of-care tests resulting in improved linkage to care and decrease in long-term complications.

     

Application of the backstepping method to the prediction of increase or decrease of infected population

Background

In mathematical epidemiology, age-structured epidemic models have usually been formulated as the boundary-value problems of the partial differential equations. On the other hand, in engineering, the backstepping method has recently been developed and widely studied by many authors.

Methods

Using the backstepping method, we obtained a boundary feedback control which plays the role of the threshold criteria for the prediction of increase or decrease of newly infected population. Under an assumption that the period of infectiousness is same for all infected individuals (that is, the recovery rate is given by the Dirac delta function multiplied by a sufficiently large positive constant), the prediction method is simplified to the comparison of the numbers of reported cases at the current and previous time steps.

Results

Our prediction method was applied to the reported cases per sentinel of influenza in Japan from 2006 to 2015 and its accuracy was 0.81 (404 correct predictions to the total 500 predictions). It was higher than that of the ARIMA models with different orders of the autoregressive part, differencing and moving-average process. In addition, a proposed method for the estimation of the number of reported cases, which is consistent with our prediction method, was better than that of the best-fitted ARIMA model ARIMA(1,1,0) in the sense of mean square error.

Conclusions

Our prediction method based on the backstepping method can be simplified to the comparison of the numbers of reported cases of the current and previous time steps. In spite of its simplicity, it can provide a good prediction for the spread of influenza in Japan.

     

NMRProcFlow: a graphical and interactive tool dedicated to 1D spectra processing for NMR-based metabolomics

Introduction

Concerning NMR-based metabolomics, 1D spectra processing often requires an expert eye for disentangling the intertwined peaks.

Objectives

The objective of NMRProcFlow is to assist the expert in this task in the best way without requirement of programming skills.

Methods

NMRProcFlow was developed to be a graphical and interactive 1D NMR (¹H & ¹³C) spectra processing tool.

Results

NMRProcFlow (http://nmrprocflow.org), dedicated to metabolic fingerprinting and targeted metabolomics, covers all spectra processing steps including baseline correction, chemical shift calibration and alignment.

Conclusion

Biologists and NMR spectroscopists can easily interact and develop synergies by visualizing the NMR spectra along with their corresponding experimental-factor levels, thus setting a bridge between experimental design and subsequent statistical analyses.

     

Phosphodiesterase 4 inhibitors and drugs of abuse: current knowledge and therapeutic opportunities

Background

Long-term exposure to drugs of abuse causes an upregulation of the cAMP-signaling pathway in the nucleus accumbens and other forebrain regions, this common neuroadaptation is thought to underlie aspects of drug tolerance and dependence. Phosphodiesterase 4 (PDE4) is an enzyme that the selective hydrolyzes intracellular cAMP. It is expressed in several brain regions that regulate the reinforcing effects of drugs of abuse.

Objective

Here, we review the current knowledge about central nervous system (CNS) distribution of PDE4 isoforms and the effects of systemic and brain-region specific inhibition of PDE4 on behavioral models of drug addiction.

Methods

A systematic literature search was performed using the Pubmed.

Results

Using behavioral sensitization, conditioned place preference and drug self-administration as behavioral models, a large number of studies have shown that local or systemic administration of PDE4 inhibitors reduce drug intake and/or drug seeking for psychostimulants, alcohol, and opioids in rats or mice.

Conclusions

Preclinical studies suggest that PDE4 could be a therapeutic target for several classes of substance use disorder. We conclude by identifying opportunities for the development of subtype-selective PDE4 inhibitors that may reduce addiction liability and minimize the side effects that limit the clinical potential of non-selective PDE4 inhibitors. Several PDE4 inhibitors have been clinically approved for other diseases. There is a promising possibility to repurpose these PDE4 inhibitors for the treatment of drug addiction as they are safe and well-tolerated in patients.

     

Crosstalk between catecholamines and erythropoiesis

Background

Erythropoiesis is regulated by a range of intrinsic and extrinsic factors, including different cytokines. Recently, the role of catecholamines has been highlighted in the development of erythroid cell lineages.

Objective

This study focuses on the biological links interconnecting erythroid development and the sympathetic nervous system. The emerging evidence that underscores the role of catecholamines in the regulation of erythropoietin and other erythropoiesis cytokines are thoroughly reviewed, in addition to elements such as iron and the leptin hormone that are involved in erythropoiesis.

Methods

Relevant English-language studies were identified and retrieved from the PubMed search engine (1981–2017) using the following keywords: “Erythropoiesis”, “Catecholamines”, “Nervous system”, and “Cytokines.”

Results

Chronic social stress alters and suppresses erythroid development. However, the physiological release of catecholamines is an additional stimulator of erythropoiesis in the setting of anemia. Therefore, the severity and timing of catecholamine secretion might distinctly regulate erythroid homeostasis.

Conclusion

Understanding the relationship of catecholamines with different elements of the erythroid islands will be essential to find the tightly regulated production of red blood cells (RBCs) in both chronic and physiological catecholamine activation.

     

Non-invasive urinary metabolomic profiling discriminates prostate cancer from benign prostatic hyperplasia

Introduction

Prostate cancer (PCa) is one of the most common malignancies in men worldwide. Serum prostate specific antigen (PSA) level has been extensively used as a biomarker to detect PCa. However, PSA is not cancer-specific and various non-malignant conditions, including benign prostatic hyperplasia (BPH), can cause a rise in PSA blood levels, thus leading to many false positive results.

Objectives

In this study, we evaluated the potential of urinary metabolomic profiling for discriminating PCa from BPH.

Methods

Urine samples from 64 PCa patients and 51 individuals diagnosed with BPH were analysed using ¹H nuclear magnetic resonance (¹H-NMR). Comparative analysis of urinary metabolomic profiles was carried out using multivariate and univariate statistical approaches.

Results

The urine metabolomic profile of PCa patients is characterised by increased concentrations of branched-chain amino acids (BCAA), glutamate and pseudouridine, and decreased concentrations of glycine, dimethylglycine, fumarate and 4-imidazole-acetate compared with individuals diagnosed with BPH.

Conclusion

PCa patients have a specific urinary metabolomic profile. The results of our study underscore the clinical potential of metabolomic profiling to uncover metabolic changes that could be useful to discriminate PCa from BPH in a clinical context.

     

Application of residual polysaccharide-degrading enzymes in dried shiitake mushrooms as an enzyme preparation in food processing

Objective

To examine the activities of residual enzymes in dried shiitake mushrooms, which are a traditional foodstuff in Japanese cuisine, for possible applications in food processing.

Results

Polysaccharide-degrading enzymes remained intact in dried shiitake mushrooms and the activities of amylase, β-glucosidase and pectinase were high. A potato digestion was tested using dried shiitake powder. The enzymes reacted with potato tuber specimens to solubilize sugars even under a heterogeneous solid-state condition and that their reaction modes were different at 38 and 50 °C.

Conclusion

Dried shiitake mushrooms have a potential use in food processing as an enzyme preparation.

     

The degradation of nucleotide triphosphates extracted under boiling ethanol conditions is prevented by the yeast cellular matrix

Introduction

Boiling ethanol extraction is a frequently used method for metabolomics studies of biological samples. However, the stability of several central carbon metabolites, including nucleotide triphosphates, and the influence of the cellular matrix on their degradation have not been addressed.

Objectives

To study how a complex cellular matrix extracted from yeast (Saccharomyces cerevisiae) may affect the degradation profiles of nucleotide triphosphates extracted under boiling ethanol conditions.

Methods

We present a double-labelling LC–MS approach with a ¹³C-labeled yeast cellular extract as complex surrogate matrix, and ¹³C¹⁵N-labeled nucleotides as internal standards, to study the effect of the yeast matrix on the degradation of nucleotide triphosphates.

Results

While nucleotide triphosphates were degraded to the corresponding diphosphates in pure solutions, degradation was prevented in the presence of the yeast matrix under typical boiling ethanol extraction conditions.

Conclusions

Extraction of biological samples under boiling ethanol extraction conditions that rapidly inactivate enzyme activity are suitable for labile central energy metabolites such as nucleotide triphosphates due to the stabilizing effect of the yeast matrix. The basis of this phenomenon requires further study.

Graphical abstract

Open image in new window

     

Discovery of A-type procyanidin dimers in yellow raspberries by untargeted metabolomics and correlation based data analysis

Introduction

Raspberries are becoming increasingly popular due to their reported health beneficial properties. Despite the presence of only trace amounts of anthocyanins, yellow varieties seems to show similar or better effects in comparison to conventional raspberries.

Objectives

The aim of this work is to characterize the metabolic differences between red and yellow berries, focussing on the compounds showing a higher concentration in yellow varieties.

Methods

The metabolomic profile of 13 red and 12 yellow raspberries (of different varieties, locations and collection dates) was determined by UPLC–TOF-MS. A novel approach based on Pearson correlation on the extracted ion chromatograms was implemented to extract the pseudospectra of the most relevant biomarkers from high energy LC–MS runs. The raw data will be made publicly available on MetaboLights (MTBLS333).

Results

Among the metabolites showing higher concentration in yellow raspberries it was possible to identify a series of compounds showing a pseudospectrum similar to that of A-type procyanidin polymers. The annotation of this group of compounds was confirmed by specific MS/MS experiments and performing standard injections.

Conclusions

In berries lacking anthocyanins the polyphenol metabolism might be shifted to the formation of a novel class of A-type procyanidin polymers.

     

Orthostatic responses in adolescent chronic fatigue syndrome: contributions from expectancies as well as gravity

Background

Orthostatic intolerance is common in chronic fatigue syndrome (CFS), and several studies have documented an abnormal sympathetic predominance in the autonomic cardiovascular response to gravitational stimuli. The aim of this study was to explore whether the expectancies towards standing are contributors to autonomic responses in addition to the gravitational stimulus itself.

Methods

A total of 30 CFS patients (12–18 years of age) and 39 healthy controls underwent 20° head-up tilt test and a motor imagery protocol of standing upright. Beat-to-beat cardiovascular variables were recorded.

Results

At supine rest, CFS patients had significantly higher heart rate, diastolic blood pressure, and mean arterial blood pressure, and lower stroke index and heart rate variability (HRV) indices. The response to 20° head-up tilt was identical in the two groups. The response to imaginary upright position was characterized by a stronger increase of HRV indices of sympathetic predominance (power in the low-frequency range as well as the ratio low-frequency: high-frequency power) among CFS patients.

Conclusions

These results suggest that in CFS patients expectancies towards orthostatic challenge might be additional determinants of autonomic cardiovascular modulation along with the gravitational stimulus per se.

     

Identification of usual interstitial pneumonia pattern using RNA-Seq and machine learning: challenges and solutions

Background

We developed a classifier using RNA sequencing data that identifies the usual interstitial pneumonia (UIP) pattern for the diagnosis of idiopathic pulmonary fibrosis. We addressed significant challenges, including limited sample size, biological and technical sample heterogeneity, and reagent and assay batch effects.

Results

We identified inter- and intra-patient heterogeneity, particularly within the non-UIP group. The models classified UIP on transbronchial biopsy samples with a receiver-operating characteristic area under the curve of ~?0.9 in cross-validation. Using in silico mixed samples in training, we prospectively defined a decision boundary to optimize specificity at ≥85%. The penalized logistic regression model showed greater reproducibility across technical replicates and was chosen as the final model. The final model showed sensitivity of 70% and specificity of 88% in the test set.

Conclusions

We demonstrated that the suggested methodologies appropriately addressed challenges of the sample size, disease heterogeneity and technical batch effects and developed a highly accurate and robust classifier leveraging RNA sequencing for the classification of UIP.

     

Crystal structure of <Emphasis Type="Italic">Escherichia coli</Emphasis> protein ybgI,a toroidal structure with a dinuclear metal site

Background

The protein encoded by the gene ybgI was chosen as a target for a structural genomics project emphasizing the relation of protein structure to function.

Results

The structure of the ybgI protein is a toroid composed of six polypeptide chains forming a trimer of dimers. Each polypeptide chain binds two metal ions on the inside of the toroid.

Conclusion

The toroidal structure is comparable to that of some proteins that are involved in DNA metabolism. The di-nuclear metal site could imply that the specific function of this protein is as a hydrolase-oxidase enzyme.

     

Crop metabolomics: from diagnostics to assisted breeding

Background

Until recently, plant metabolomics have provided a deep understanding on the metabolic regulation in individual plants as experimental units. The application of these techniques to agricultural systems subjected to more complex interactions is a step towards the implementation of translational metabolomics in crop breeding.

Aim of Review

We present here a review paper discussing advances in the knowledge reached in the last years derived from the application of metabolomic techniques that evolved from biomarker discovery to improve crop yield and quality.

Key Scientific Concepts of Review

Translational metabolomics applied to crop breeding programs.