Reconstruction and Simulation of Neocortical Microcircuitry.

We present a first-draft digital reconstruction of the microcircuitry of somatosensory cortex of juvenile rat. The reconstruction uses cellular and synaptic organizing principles to algorithmically reconstruct detailed anatomy and physiology from sparse experimental data. An objective anatomical method defines a neocortical volume of 0.29 ± 0.01 mm(3) containing ~31,000 neurons, and patch-clamp studies identify 55 layer-specific morphological and 207 morpho-electrical neuron subtypes. When digitally reconstructed neurons are positioned in the volume and synapse formation is restricted to biological bouton densities and numbers of synapses per connection, their overlapping arbors form ~8 million connections with ~37 million synapses. Simulations reproduce an array of in vitro and in vivo experiments without parameter tuning. Additionally, we find a spectrum of network states with a sharp transition from synchronous to asynchronous activity, modulated by physiological mechanisms. The spectrum of network states, dynamically reconfigured around this transition, supports diverse information processing strategies. PAPERCLIP: VIDEO ABSTRACT.

NeuroMorphoVis: a collaborative framework for analysis and visualization of neuronal morphology skeletons reconstructed from microscopy stacks.

Motivation: From image stacks to computational models, processing digital representations of neuronal morphologies is essential to neuroscientific research. Workflows involve various techniques and tools, leading in certain cases to convoluted and fragmented pipelines. The existence of an integrated, extensible and free framework for processing, analysis and visualization of those morphologies is a challenge that is still largely unfulfilled. Results: We present NeuroMorphoVis, an interactive, extensible and cross-platform framework for building, visualizing and analyzing digital reconstructions of neuronal morphology skeletons extracted from microscopy stacks. Our framework is capable of detecting and repairing tracing artifacts, allowing the generation of high fidelity surface meshes and high resolution volumetric models for simulation and in silico imaging studies. The applicability of NeuroMorphoVis is demonstrated with two case studies. The first simulates the construction of three-dimensional profiles of neuronal somata and the other highlights how the framework is leveraged to create volumetric models of neuronal circuits for simulating different types of in vitro imaging experiments. Availability and implementation: The source code and documentation are freely available on https://github.com/BlueBrain/NeuroMorphoVis under the GNU public license. The morphological analysis, visualization and surface meshing are implemented as an extensible Python API (Application Programming Interface) based on Blender, and the volume reconstruction and analysis code is written in C++ and parallelized using OpenMP. The framework features are accessible from a user-friendly GUI (Graphical User Interface) and a rich CLI (Command Line Interface). Supplementary information: Supplementary data are available at Bioinformatics online.

Reconstruction and visualization of large-scale volumetric models of neocortical circuits for physically-plausible in silico optical studies.

BACKGROUND: We present a software workflow capable of building large scale, highly detailed and realistic volumetric models of neocortical circuits from the morphological skeletons of their digitally reconstructed neurons. The limitations of the existing approaches for creating those models are explained, and then, a multi-stage pipeline is discussed to overcome those limitations. Starting from the neuronal morphologies, we create smooth piecewise watertight polygonal models that can be efficiently utilized to synthesize continuous and plausible volumetric models of the neurons with solid voxelization. The somata of the neurons are reconstructed on a physically-plausible basis relying on the physics engine in Blender. RESULTS: Our pipeline is applied to create 55 exemplar neurons representing the various morphological types that are reconstructed from the somatsensory cortex of a juvenile rat. The pipeline is then used to reconstruct a volumetric slice of a cortical circuit model that contains ∼210,000 neurons. The applicability of our pipeline to create highly realistic volumetric models of neocortical circuits is demonstrated with an in silico imaging experiment that simulates tissue visualization with brightfield microscopy. The results were evaluated with a group of domain experts to address their demands and also to extend the workflow based on their feedback. CONCLUSION: A systematic workflow is presented to create large scale synthetic tissue models of the neocortical circuitry. This workflow is fundamental to enlarge the scale of in silico neuroscientific optical experiments from several tens of cubic micrometers to a few cubic millimeters. AMS SUBJECT CLASSIFICATION: Modelling and Simulation.

Feeding a diet containing a fructooligosaccharide mix can enhance Salmonella vaccine efficacy in mice.

Fructooligosaccharides (FOS) are considered prebiotics because of their ability to promote growth of specific beneficial gut bacteria, such as bifidobacteria. Some studies reported potential immune-modulating properties. The aim of this study was to investigate the effect of FOS:inulin mix on murine response to Salmonella vaccine and evaluate the relevance toward protection against Salmonella infection. Balb/c mice were fed a diet containing 5% FOS:inulin mix or a control diet 1 wk before oral immunization with a suboptimal dose of live attenuated Salmonella typhimurium vaccine. Four weeks after vaccination, mice were infected with LD100 of virulent S. typhimurium. Specific blood Salmonella immunoglobulin G and fecal immunoglobulin A significantly increased in mice fed the diet containing prebiotics compared with control mice 4 wk postimmunization. Peritoneal macrophage phagocytic activity also significantly increased in FOS:inulin-fed mice at 1 wk postimmunization compared with control mice. No detectable effects were observed on the percentage of lymphoid cell subsets in the spleen. However, production of cytokines, interferon-gamma, interleukin-12, and tumor necrosis factor alpha, was numerically increased in spleen cell cultures stimulated with mitogens from FOS:inulin-fed mice 1 and 4 wk postimmunization. Salmonella translocation to lymphoid organs was not affected by feeding FOS:inulin. However, the improved response to Salmonella vaccine was concomitant with an increase in the survival rate of FOS:inulin-fed mice upon challenge with virulent Salmonella. No detectable effects were observed on the composition or the metabolic activity of the microbiota. Overall, the data suggest that a diet supplemented with FOS:inulin mix stimulates mucosal immunity and seems to improve efficacy of an oral vaccine.

Lipid deposition on the tongue after oral processing of medium-chain triglycerides and impact on the perception of mouthfeel.

Lipids between the tongue and palate strongly contribute to the sensory impact of a product. Mouthfeel is a sensory attribute responsible for distinguishing reduced fat from full fat food products. The aim of this work was to quantify the distribution, deposition, and retention of lipids on the tongue and palate upon oral processing and relate this to texture. The thickness of lipid deposition was measured in mouth by fluorescence. A trained panel evaluated the perceived intensity of samples to describe lipid Mouthfeel. The thickness of lipid deposition on the tongue shows spatial variation (10-100 microm) and stopped increasing after intakes higher than 8 mL of medium-chain triglycerides (MCTs). After 2 min, only 25% of the lipid deposition was retained on oral surfaces. A difference in the thickness of lipid deposition of 25 microm resulted in significantly different perception. This work describes the in-mouth behavior of food lipids and its influence on texture perception.

Delayed volatile compound release properties of self-assembly structures in emulsions.

Temporal release and retention of aroma compounds from structured emulsions (where unsaturated monoglycerides are added to the oil) and conventional oil-in-water emulsions were studied using in vitro dynamic headspace analysis by proton-transfer reaction mass spectrometry and static headspace analysis by gas chromatography-mass spectrometry. Under dynamic conditions, the structured emulsion exhibited delayed release compared to the oil-in-water emulsion containing the same lipid content of 5%. The time to maximum concentration T max of amphiphilic and lipophilic aroma compounds increased by a factor of 1.2 (for 3 E-hexenal) to 1.9 (for octanal). The aroma release profile of the 5% lipid structured emulsion was close to that obtained for the oil-in-water emulsion containing 10% lipid. Under static conditions, the 5% lipid structured emulsion retained more of the most lipophilic aroma compounds than its counterpart 5% oil-in-water nonstructured emulsion. The present study provides potential solutions for modulating aroma release profiles of reduced-fat foods by self-assembly structures.

Comparison of nosespace, headspace, and sensory intensity ratings for the evaluation of flavor absorption by fat.

The goal of this study was to better understand the correspondence between sensory perception and in-nose compound concentration. Five aroma compounds at three different concentrations increasing by factors of 4 were added to four matrixes (water, skim milk, 2.7% fat milk, and 3.8% fat milk). These were evaluated by nosespace analysis with detection by proton transfer reaction mass spectrometry (PTR-MS), using five panelists. These same panelists evaluated the perceived intensity of each compound in the matrixes at the three concentrations. PTR-MS quantification found that the percent released from an aqueous solution swallowed immediately was between 0.1 and 0.6%, depending on the compound. The nosespace and sensory results showed the expected effect of fat on release, where lipophilic compounds showed reductions in release as fat content increases. The effect is less than that observed in headspace studies. A general correlation between nosespace concentration and sensory intensity ratings was found. However, examples of perceptual masking were found where higher fat milks showed reductions in aroma compound intensity ratings, even if the nosespace concentrations were the same.

Everyday eating experiences of chocolate and non-chocolate snacks impact postprandial anxiety, energy and emotional states.

Social and psychological stressors are both a part of daily life and are increasingly recognized as contributors to individual susceptibility to develop diseases and metabolic disorders. The present study investigated how snacks differing in sensory properties and presentation can influence ratings of affect in consumers with different levels of dispositional anxiety. This study examines the relationships between a pre-disposition to anxiety and food using a repeated exposures design with three interspersed test days over a period of two weeks. The study was conducted on ninety free-living male (n = 28) and female (n = 62) Dutch participants aged between 18 and 35 years old, with a BMI between 18 and 25 kg/m(2) and different anxiety trait levels assessed using State-Trait Anxiety Inventory tests. The study was randomized by age, gender, anxiety trait score, and followed a parallel open design. Three test products: dark chocolate, a milk chocolate snack and crackers with cheese spread (control), which differed in composition, sensory properties and presentation, were evaluated. Changes in self-reported anxiety, emotion, and energetic states were assessed as a function of eating the snacks just after consumption and up to one hour. The repeated exposure design over a period of two weeks enabled the investigations of potential cumulative effects of regular consumption of the food products. The milk chocolate snack resulted in the decrease of anxiety in high anxiety trait subjects, whereas dark chocolate and cheese and crackers respectively improved the anxiety level and the energetic state of low anxiety trait participants. The mood effects were not altered with repeated exposure, and the magnitude of changes was similar on each test day, which illustrates the repeatability of the effects of the food on subjective measures of postprandial wellness.

Reliability of Threshold and Suprathreshold Methods for Taste Phenotyping: Characterization with PROP and Sodium Chloride.

The present study aimed to compare the accuracy and reliability of four standard methods used for classification of people as taster or non-tasters based on their sensitivity to PROP (6-n-propylthiouracil). A panel consisting of 21 subjects was tested for threshold and suprathreshold sensitivity of sodium chloride, PROP, and genotyped for TAS2R38. Two threshold methods, staircase and modified Harris-Kalmus, were used to obtain detection and recognition thresholds and compared for accuracy and repeatability. Similarly, two suprathreshold techniques, the just noticeable differences (JND) and the general labeled magnitude scale (gLMS), were used to determine Weber fractions and individual psychophysical functions and compared for accuracy and repeatability. Results show both threshold methods have been able to correctly separate people into two groups of tasters and non-tasters, with the staircase method having a lower variability among subjects. On the suprathreshold front, we found differences in sensitivity between tasters and non-tasters when comparing Weber fractions and psychophysical functions; however, our data suggest that clustering people without previous knowledge of their taster status is less accurate when using Weber fractions. Intensity ratings are more reliable to classify people into tasters and non-tasters. Results show that the staircase for threshold measurement and the gLMS methods are more reliable methods than Harris-Kalmus and JND for phenotyping people and can be used in large-scale studies in the quest to discover new genotype-phenotype associations.

Rapid identification of differentiation markers from whole epithelial cells by matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry and statistical analysis.

Matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOFMS) was applied to identify markers for cellular differentiation. The differentiation of a human colon epithelial carcinoma T84 cell line was monitored over a period of 28 days by transepithelial electrical resistance (TER) measurements, alkaline phosphatase (AP) assay, and MALDI-TOF mass spectral fingerprints combined with statistical analysis. MALDI-MS generated specific mass spectral fingerprints characteristic of cell differentiation. Twenty-two ions were selected as diagnostic signals of fully differentiated T84 cells. Ten protein ion signals, detected by MALDI-MS and validated by statistical analysis, were proposed as T84 cell differentiation markers. Among these signals, ubiquitin was identified as a T84 cell differentiation marker by nanospray liquid chromatography/tandem mass spectrometry (nanoLC/MS/MS). Moreover, depending on the concentration of the cells seeded on the growth support, it was possible to predict the timing of the exponential phase and of cellular differentiation by MALDI-MS-derived marker ions. MALDI-TOFMS was compared to other methods for the determination of cellular differentiation: TER measurements are rapid but yield limited information as to the cellular differentiation state. AP assays are more specific for the differentiation state but take more time. By contrast, MALDI-MS has been found to be a fast, sensitive and precise method for cell differentiation assessment and provides the opportunity for multiplexing and high throughput. Moreover, the consumable costs per assay are very low.

The Global Error Assessment (GEA) model for the selection of differentially expressed genes in microarray data.

MOTIVATION: Microarray technology has become a powerful research tool in many fields of study; however, the cost of microarrays often results in the use of a low number of replicates (k). Under circumstances where k is low, it becomes difficult to perform standard statistical tests to extract the most biologically significant experimental results. Other more advanced statistical tests have been developed; however, their use and interpretation often remain difficult to implement in routine biological research. The present work outlines a method that achieves sufficient statistical power for selecting differentially expressed genes under conditions of low k, while remaining as an intuitive and computationally efficient procedure. RESULTS: The present study describes a Global Error Assessment (GEA) methodology to select differentially expressed genes in microarray datasets, and was developed using an in vitro experiment that compared control and interferon-gamma treated skin cells. In this experiment, up to nine replicates were used to confidently estimate error, thereby enabling methods of different statistical power to be compared. Gene expression results of a similar absolute expression are binned, so as to enable a highly accurate local estimate of the mean squared error within conditions. The model then relates variability of gene expression in each bin to absolute expression levels and uses this in a test derived from the classical ANOVA. The GEA selection method is compared with both the classical and permutational ANOVA tests, and demonstrates an increased stability, robustness and confidence in gene selection. A subset of the selected genes were validated by real-time reverse transcription-polymerase chain reaction (RT-PCR). All these results suggest that GEA methodology is (i) suitable for selection of differentially expressed genes in microarray data, (ii) intuitive and computationally efficient and (iii) especially advantageous under conditions of low k. AVAILABILITY: The GEA code for R software is freely available upon request to authors.