A hypothalamic-thalamostriatal circuit that controls approach-avoidance conflict in rats

Survival depends on a balance between seeking rewards and avoiding potential threats, but the neural circuits that regulate this motivational conflict remain largely unknown. Using an approach-food vs. avoid-predator threat conflict test in rats, we identified a subpopulation of neurons in the anterior portion of the paraventricular thalamic nucleus (aPVT) which express corticotrophin-releasing factor (CRF) and are preferentially recruited during conflict. Inactivation of aPVTCRF neurons during conflict biases animal’s response toward food, whereas activation of these cells recapitulates the food-seeking suppression observed during conflict. aPVTCRF neurons project densely to the nucleus accumbens (NAc), and activity in this pathway reduces food seeking and increases avoidance. In addition, we identified the ventromedial hypothalamus (VMH) as a critical input to aPVTCRF neurons, and demonstrated that VMH-aPVT neurons mediate defensive behaviors exclusively during conflict. Together, our findings describe a hypothalamic-thalamostriatal circuit that suppresses reward-seeking behavior under the competing demands of avoiding threats.Fil: Engelke, D. S.. The University of Texas Health Science Center; Estados UnidosFil: Zhang, X. O.. The University of Texas Health Science Center; Estados UnidosFil: O’Malley, J. J.. The University of Texas Health Science Center; Estados UnidosFil: Fernandez Leon, Jose Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires. Sede Olavarría del Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aire. Universidad Nacional del Centro de la Provincia de Buenos Aires. Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires. Sede Olavarría del Centro de Investigaciones en Física e Ingeniería del Centro de la Provincia de Buenos Aires; ArgentinaFil: Li, S.. University of Manitoba; CanadáFil: Kirouac, G. J.. University of Manitoba; CanadáFil: Beierlein, M.. The University of Texas Health Science Center; Estados UnidosFil: Do Monte, F. H.. The University of Texas Health Science Center; Estados Unido

Measurement of velocities in gas-liquid two-phase flow using Laser Doppler Velocimetry

Measurements of bubble and liquid velocities in two-phase flow have been made using a new forward/backward scattering Laser Doppler Velocimetry (LDV) technique. This work was performed in a 6.4 by 11.1 mm vertical duct using known air/water mixtures. A standard LDV fiber optic probe was used to measure the bubble velocity, using direct backscattered light. A novel retro-reflector and lens assembly permitted the same probe to measure the liquid velocity with direct forward-scattered light. The bubble velocity was confirmed by independent measurements with a high-speed video system. The liquid velocity was confirmed by demonstrating the dominance of the liquid seed data rate in the forward-scatter measurement. Experimental data are presented to demonstrate the accuracy of the technique for a wide range of flow conditions, from bubbles as small as 0.75-mm-diam to slugs as large as 10-mm wide by 30-mm long. In the slug regime, the LDV technique performed velocity measurements for both phases, for void fractions up to 50%, which was the upper limit of our experimental investigation

PERT: A Method for Expression Deconvolution of Human Blood Samples from Varied Microenvironmental and Developmental Conditions

The cellular composition of heterogeneous samples can be predicted using an expression deconvolution algorithm to decompose their gene expression profiles based on pre-defined, reference gene expression profiles of the constituent populations in these samples. However, the expression profiles of the actual constituent populations are often perturbed from those of the reference profiles due to gene expression changes in cells associated with microenvironmental or developmental effects. Existing deconvolution algorithms do not account for these changes and give incorrect results when benchmarked against those measured by well-established flow cytometry, even after batch correction was applied. We introduce PERT, a new probabilistic expression deconvolution method that detects and accounts for a shared, multiplicative perturbation in the reference profiles when performing expression deconvolution. We applied PERT and three other state-of-the-art expression deconvolution methods to predict cell frequencies within heterogeneous human blood samples that were collected under several conditions (uncultured mono-nucleated and lineage-depleted cells, and culture-derived lineage-depleted cells). Only PERT's predicted proportions of the constituent populations matched those assigned by flow cytometry. Genes associated with cell cycle processes were highly enriched among those with the largest predicted expression changes between the cultured and uncultured conditions. We anticipate that PERT will be widely applicable to expression deconvolution strategies that use profiles from reference populations that vary from the corresponding constituent populations in cellular state but not cellular phenotypic identity

A Systems Model for Immune Cell Interactions Unravels the Mechanism of Inflammation in Human Skin

Inflammation is characterized by altered cytokine levels produced by cell populations in a highly interdependent manner. To elucidate the mechanism of an inflammatory reaction, we have developed a mathematical model for immune cell interactions via the specific, dose-dependent cytokine production rates of cell populations. The model describes the criteria required for normal and pathological immune system responses and suggests that alterations in the cytokine production rates can lead to various stable levels which manifest themselves in different disease phenotypes. The model predicts that pairs of interacting immune cell populations can maintain homeostatic and elevated extracellular cytokine concentration levels, enabling them to operate as an immune system switch. The concept described here is developed in the context of psoriasis, an immune-mediated disease, but it can also offer mechanistic insights into other inflammatory pathologies as it explains how interactions between immune cell populations can lead to disease phenotypes

Identification of Hub Genes Related to the Recovery Phase of Irradiation Injury by Microarray and Integrated Gene Network Analysis

BACKGROUND: Irradiation commonly causes long-term bone marrow injury charactertized by defective HSC self-renewal and a decrease in HSC reserve. However, the effect of high-dose IR on global gene expression during bone marrow recovery remains unknown. METHODOLOGY: Microarray analysis was used to identify differentially expressed genes that are likely to be critical for bone marrow recovery. Multiple bioinformatics analyses were conducted to identify key hub genes, pathways and biological processes. PRINCIPAL FINDINGS: 1) We identified 1302 differentially expressed genes in murine bone marrow at 3, 7, 11 and 21 days after irradiation. Eleven of these genes are known to be HSC self-renewal associated genes, including Adipoq, Ccl3, Ccnd1, Ccnd2, Cdkn1a, Cxcl12, Junb, Pten, Tal1, Thy1 and Tnf; 2) These 1302 differentially expressed genes function in multiple biological processes of immunity, including hematopoiesis and response to stimuli, and cellular processes including cell proliferation, differentiation, adhesion and signaling; 3) Dynamic Gene Network analysis identified a subgroup of 25 core genes that participate in immune response, regulation of transcription and nucleosome assembly; 4) A comparison of our data with known irradiation-related genes extracted from literature showed 42 genes that matched the results of our microarray analysis, thus demonstrated consistency between studies; 5) Protein-protein interaction network and pathway analyses indicated several essential protein-protein interactions and signaling pathways, including focal adhesion and several immune-related signaling pathways. CONCLUSIONS: Comparisons to other gene array datasets indicate that global gene expression profiles of irradiation damaged bone marrow show significant differences between injury and recovery phases. Our data suggest that immune response (including hematopoiesis) can be considered as a critical biological process in bone marrow recovery. Several critical hub genes that are key members of significant pathways or gene networks were identified by our comprehensive analysis

Gender and the Communication of Emotion Via Touch

We reanalyzed a data set consisting of a U.S. undergraduate sample (N = 212) from a previous study (Hertenstein et al. 2006a) that showed that touch communicates distinct emotions between humans. In the current reanalysis, we found that anger was communicated at greater-than-chance levels only when a male comprised at least one member of a communicating dyad. Sympathy was communicated at greater-than-chance levels only when a female comprised at least one member of the dyad. Finally, happiness was communicated only if females comprised the entire dyad. The current analysis demonstrates gender asymmetries in the accuracy of communicating distinct emotions via touch between humans

Inflammatory Gene Regulatory Networks in Amnion Cells Following Cytokine Stimulation: Translational Systems Approach to Modeling Human Parturition

A majority of the studies examining the molecular regulation of human labor have been conducted using single gene approaches. While the technology to produce multi-dimensional datasets is readily available, the means for facile analysis of such data are limited. The objective of this study was to develop a systems approach to infer regulatory mechanisms governing global gene expression in cytokine-challenged cells in vitro, and to apply these methods to predict gene regulatory networks (GRNs) in intrauterine tissues during term parturition. To this end, microarray analysis was applied to human amnion mesenchymal cells (AMCs) stimulated with interleukin-1β, and differentially expressed transcripts were subjected to hierarchical clustering, temporal expression profiling, and motif enrichment analysis, from which a GRN was constructed. These methods were then applied to fetal membrane specimens collected in the absence or presence of spontaneous term labor. Analysis of cytokine-responsive genes in AMCs revealed a sterile immune response signature, with promoters enriched in response elements for several inflammation-associated transcription factors. In comparison to the fetal membrane dataset, there were 34 genes commonly upregulated, many of which were part of an acute inflammation gene expression signature. Binding motifs for nuclear factor-κB were prominent in the gene interaction and regulatory networks for both datasets; however, we found little evidence to support the utilization of pathogen-associated molecular pattern (PAMP) signaling. The tissue specimens were also enriched for transcripts governed by hypoxia-inducible factor. The approach presented here provides an uncomplicated means to infer global relationships among gene clusters involved in cellular responses to labor-associated signals