Endothelial cells stimulate growth of normal and cancerous breast epithelial cells in 3D culture

<p>Abstract</p> <p>Background</p> <p>Epithelial-stromal interaction provides regulatory signals that maintain correct histoarchitecture and homeostasis in the normal breast and facilitates tumor progression in breast cancer. However, research on the regulatory role of the endothelial component in the normal and malignant breast gland has largely been neglected. The aim of the study was to investigate the effects of endothelial cells on growth and differentiation of human breast epithelial cells in a three-dimensional (3D) co-culture assay.</p> <p>Methods</p> <p>Breast luminal and myoepithelial cells and endothelial cells were isolated from reduction mammoplasties. Primary cells and established normal and malignant breast cell lines were embedded in reconstituted basement membrane in direct co-culture with endothelial cells and by separation of Transwell filters. Morphogenic and phenotypic profiles of co-cultures was evaluated by phase contrast microscopy, immunostaining and confocal microscopy.</p> <p>Results</p> <p>In co-culture, endothelial cells stimulate proliferation of both luminal- and myoepithelial cells. Furthermore, endothelial cells induce a subpopulation of luminal epithelial cells to form large acini/ducts with a large and clear lumen. Endothelial cells also stimulate growth and cloning efficiency of normal and malignant breast epithelial cell lines. Transwell and gradient co-culture studies show that endothelial derived effects are mediated - at least partially - by soluble factors.</p> <p>Conclusion</p> <p>Breast endothelial cells - beside their role in transporting nutrients and oxygen to tissues - are vital component of the epithelial microenvironment in the breast and provide proliferative signals to the normal and malignant breast epithelium. These growth promoting effects of endothelial cells should be taken into consideration in breast cancer biology.</p

Experimental signatures of the mixed axial-gravitational anomaly in the Weyl semimetal NbP

Weyl semimetals are materials where electrons behave effectively as a kind of massless relativistic particles known asWeyl fermions. These particles occur in two flavours, or chiralities, and are subject to quantum anomalies, the breaking of a conservation law by quantum fluctuations. For instance, the number of Weyl fermions of each chirality is not independently conserved in parallel electric and magnetic field, a phenomenon known as the chiral anomaly. In addition, an underlying curved spacetime provides a distinct contribution to a chiral imbalance, an effect known as the mixed axial-gravitational anomaly, which remains experimentally elusive. However, the presence of a mixed gauge-gravitational anomaly has recently been tied to thermoelectrical transport in a magnetic field, even in flat spacetime, opening the door to experimentally probe such type of anomalies in Weyl semimetals. Using a temperature gradient, we experimentally observe a positive longitudinal magnetothermoelectric conductance (PMTC) in the Weyl semimetal NbP for collinear temperature gradients and magnetic fields (DT || B) that vanishes in the ultra quantum limit. This observation is consistent with the presence of a mixed axial-gravitational anomaly. Our work provides clear experimental evidence for the existence of a mixed axial-gravitational anomaly of Weyl fermions, an outstanding theoretical concept that has so far eluded experimental detection

The Role of the Medial Prefrontal Cortex in Regulating Social Familiarity-Induced Anxiolysis

Overcoming specific fears and subsequent anxiety can be greatly enhanced by the presence of familiar social partners, but the neural circuitry that controls this phenomenon remains unclear. To overcome this, the social interaction (SI) habituation test was developed in this lab to systematically investigate the effects of social familiarity on anxiety-like behavior in rats. Here, we show that social familiarity selectively reduced anxiety-like behaviors induced by an ethological anxiogenic stimulus. The anxiolytic effect of social familiarity could be elicited over multiple training sessions and was specific to both the presence of the anxiogenic stimulus and the familiar social partner. In addition, socially familiar conspecifics served as a safety signal, as anxiety-like responses returned in the absence of the familiar partner. The expression of the social familiarity-induced anxiolysis (SFiA) appears dependent on the prefrontal cortex (PFC), an area associated with cortical regulation of fear and anxiety behaviors. Inhibition of the PFC, with bilateral injections of the GABAA agonist muscimol, selectively blocked the expression of SFiA while having no effect on SI with a novel partner. Finally, the effect of D-cycloserine, a cognitive enhancer that clinically enhances behavioral treatments for anxiety, was investigated with SFiA. D-cycloserine, when paired with familiarity training sessions, selectively enhanced the rate at which SFiA was acquired. Collectively, these outcomes suggest that the PFC has a pivotal role in SFiA, a complex behavior involving the integration of social cues of familiarity with contextual and emotional information to regulate anxiety-like behavior

Convergent functional genomics of anxiety disorders: translational identification of genes, biomarkers, pathways and mechanisms

Anxiety disorders are prevalent and disabling yet understudied from a genetic standpoint, compared with other major psychiatric disorders such as bipolar disorder and schizophrenia. The fact that they are more common, diverse and perceived as embedded in normal life may explain this relative oversight. In addition, as for other psychiatric disorders, there are technical challenges related to the identification and validation of candidate genes and peripheral biomarkers. Human studies, particularly genetic ones, are susceptible to the issue of being underpowered, because of genetic heterogeneity, the effect of variable environmental exposure on gene expression, and difficulty of accrual of large, well phenotyped cohorts. Animal model gene expression studies, in a genetically homogeneous and experimentally tractable setting, can avoid artifacts and provide sensitivity of detection. Subsequent translational integration of the animal model datasets with human genetic and gene expression datasets can ensure cross-validatory power and specificity for illness. We have used a pharmacogenomic mouse model (involving treatments with an anxiogenic drug—yohimbine, and an anti-anxiety drug—diazepam) as a discovery engine for identification of anxiety candidate genes as well as potential blood biomarkers. Gene expression changes in key brain regions for anxiety (prefrontal cortex, amygdala and hippocampus) and blood were analyzed using a convergent functional genomics (CFG) approach, which integrates our new data with published human and animal model data, as a translational strategy of cross-matching and prioritizing findings. Our work identifies top candidate genes (such as FOS, GABBR1, NR4A2, DRD1, ADORA2A, QKI, RGS2, PTGDS, HSPA1B, DYNLL2, CCKBR and DBP), brain–blood biomarkers (such as FOS, QKI and HSPA1B), pathways (such as cAMP signaling) and mechanisms for anxiety disorders—notably signal transduction and reactivity to environment, with a prominent role for the hippocampus. Overall, this work complements our previous similar work (on bipolar mood disorders and schizophrenia) conducted over the last decade. It concludes our programmatic first pass mapping of the genomic landscape of the triad of major psychiatric disorder domains using CFG, and permitted us to uncover the significant genetic overlap between anxiety and these other major psychiatric disorders, notably the under-appreciated overlap with schizophrenia. PDE10A, TAC1 and other genes uncovered by our work provide a molecular basis for the frequently observed clinical co-morbidity and interdependence between anxiety and other major psychiatric disorders, and suggest schizo-anxiety as a possible new nosological domain

Rectification of Arithmetic Circuits with Craig Interpolants in Finite Fields

International audienceWhen formal verification of arithmetic circuits identifies the presence of a bug in the design, the task of rectification needs to be performed to correct the function implemented by the circuit so that it matches the given specification. In our recent work [26], we addressed the problem of rectification of buggy finite field arithmetic circuits. The problems are formulated by means of a set of polynomials (ideals) and solutions are proposed using concepts from computational algebraic geometry. Single-fix rectification is addressed – i.e. the case where any set of bugs can be rectified at a single net (gate output). We determine if single-fix rectification is possible at a particular net, formulated as the Weak Nullstellensatz test and solved using Gröbner bases. Subsequently, we introduce the concept of Craig interpolants in polynomial algebra over finite fields and show that the rectification function can be computed using algebraic interpolants. This article serves as an extension to our previous work, provides a formal definition of Craig interpolants in finite fields using algebraic geometry and proves their existence. We also describe the computation of interpolants using elimination ideals with Gröbner bases and prove that our procedure computes the smallest interpolant. As the Gröbner basis algorithm exhibits high computational complexity, we further propose an efficient approach to compute interpolants. Experiments are conducted over a variety of finite field arithmetic circuits which demonstrate the superiority of our approach against SAT-based approaches