MECHANISTIC INVESTIGATION OF BRD4 INHIBITION IN MYC DEPENDENT TUMORS

The c-myc gene encodes for a transcription factor involved in the regulation of different cellular mechanisms, ranging from cell cycle control and apoptosis to cellular metabolism. Myc is frequently altered in human cancer either by genomic rearrangement or by alteration of upstream regulatory pathways. Myc crucial role both in tumor formation and maintenance makes it an attractive molecular target for cancer therapy. Unfortunately, Myc is intrinsically resilient to direct pharmacological targeting using small molecules. To overcome this issue, alternative therapeutic avenues have been explored. In the last years, independent groups showed that BET proteins inhibition leads to a strong Myc downregulation in Multiple Myelomas and Acute Myeloid Leukemias, with consequent cell cycle arrest and tumor regression. To support the hypothesis of a direct and specific effect on Myc levels mediated by BET proteins, two different working models were proposed depending on c-myc location (translocated versus endogenous). In order to extend these observations and improve our understanding of the mechanism of action of BETs inhibitors, we evaluated global transcriptional alteration and chromatin profiles in Burkitt\u2019s Lymphomas in response to JQ1. Our results demonstrate that BETs inhibitors efficacy is dependent on global alteration of RNA PolII dynamics, due to the role of BRD4 in regulating elongation. Yet, despite a pervasive eviction of BRD4 from chromatin and the global effect on RNA PolII observed following BETs inhibition, the transcriptional alterations are limited to a subset of genes. These genes are characterized by promoter regions heavily marked by H3K27Ac, high binding of BRD4 and Transcription Factors (Myc and E2F1) and RNA PolII. These JQ1 sensitive genes are consistent among different cell lines and characterized by high expression levels. Prominent promoter saturation and high RNA PolII pausing render their expression rate-limited by transcriptional elongation. Indeed the same genes are selectively targeted by pharmacological treatments affecting components of the elongation machinery. Thus, selective transcriptional effects following JQ1 treatment are linked to BETs role in regulating transcriptional elongation. These observations highlight the role of BETs protein in regulating gene expression and provide a rationale to explain how broad inhibition of elongation may lead to a selective transcriptional response

In vivo analysis of staphylococcus aureus-infected mice reveals differential temporal and spatial expression patterns of fhuD2

Staphylococcus aureus is an opportunistic human pathogen and a major cause of invasive infections such as bacteremia, endocarditis, pneumonia and wound infections. FhuD2 is a staphylococcal lipoprotein involved in the uptake of iron-hydroxymate and is under the control of the iron uptake regulator Fur. The protein is part of an investigational multi-component vaccine formulation that has shown protective efficacy in several murine models of infection. Even though fhuD2 expression was shown to be upregulated in murine kidneys infected with S. aureus, it is unknown whether the bacterium undergoes increased iron deprivation during prolonged infection. Furthermore, different infection niches of S. aureus might provide different environments and iron availability resulting in different fhuD2 expression pattern within different host organs. To address these questions, we characterized the in vitro expression of the fhuD2 gene and confirmed Fur-dependent iron-regulation of its expression. We further investigated its expression in mice infected with a bioluminescent reporter strain of S. aureus expressing the luciferase operon under the control of the fhuD2 promoter. The emission of bioluminescence in different organs was followed over a seven-day time course, as well as quantitative real-time PCR analysis of the RNA transcribed from the endogenous fhuD2 gene. Using this approach, we could show that fhuD2 expression was induced during infection in all organs analyzed and that differences in expression were observed in the temporal expression profiles, and between infected organs. Our data suggest that S. aureus undergoes increased iron deprivation during progression of infection in diverse host organs and accordingly induces dedicated iron acquisition mechanisms. Since FhuD2 plays a central role in providing the pathogen with the required iron, further knowledge of the patterns of fhuD2 expression in vivo during infection is instrumental in better defining the role of this antigen in S. aureus pathogenesis and as a vaccine antigen

Conflict management in adult sibling relationships: Differences in interpersonal power, sibling influence, and conflict tactic use among sibling types

This study examined differences in conflict management-related perceptions and behaviors as a function of Gold’s (1989) adult sibling types. Participants were 157 adults who reported on their relationship with a sibling by completing a series of self-report measures about themselves and the sibling administered in paper-and-pencil format. Results revealed that adult siblings who classified their relationship as intimate perceived more positive sibling interpersonal power and parallel sibling influence, and were more likely to use prosocial conflict tactics with their sibling during conflicts. Conversely, adult siblings who characterized their relationship as apathetic/hostile were more likely to desire differentiation and to use dysfunctional conflict tactics during conflict with their sibling. In addition, across sibling types, perceptions of siblings’ power and influence predicted conflict tactic usage. This investigation extends available research by demonstrating destructive outcomes associated with the apathetic/hostile adult sibling type (e.g., increased use of violence as a conflict tactic). Further, across adult sibling types, this study provides insight into why emerging adult siblings use both constructive and destructive tactics during conflict with each other.

Progressive failure analysis of shallow foundations on soils with strain-softening behaviour

n/

Group selection models in prebiotic evolution

The evolution of enzyme production is studied analytically using ideas of the group selection theory for the evolution of altruistic behavior. In particular, we argue that the mathematical formulation of Wilson's structured deme model ({\it The Evolution of Populations and Communities}, Benjamin/Cumings, Menlo Park, 1980) is a mean-field approach in which the actual environment that a particular individual experiences is replaced by an {\it average} environment. That formalism is further developed so as to avoid the mean-field approximation and then applied to the problem of enzyme production in the prebiotic context, where the enzyme producer molecules play the altruists role while the molecules that benefit from the catalyst without paying its production cost play the non-altruists role. The effects of synergism (i.e., division of labor) as well as of mutations are also considered and the results of the equilibrium analysis are summarized in phase diagrams showing the regions of the space of parameters where the altruistic, non-altruistic and the coexistence regimes are stable. In general, those regions are delimitated by discontinuous transition lines which end at critical points.Comment: 22 pages, 10 figure

Signals of Warped Extra Dimensions at the LHC

We discuss the signatures of the spin-2 graviton excitations predicted by the Randall-Sundrum model with one warped extra dimension, in dilepton and diphoton production at LHC. By using a specific angular analysis, we assess the ranges in mass and coupling constant where such gravitons can be discriminated against competitor spin-1 and spin-0 objects, that potentially could manifest themselves in these processes with the same mass and rate of events. Depending on the value of the coupling constant to quarks and leptons, the numerical results indicate graviton identification mass ranges up to 1.1-2.4 TeV and 1.6-3.2 TeV for LHC nominal energy of 14 TeV and time-integrated luminosity of 10 and 100~${\rm fb}^{-1}$, respectively.Comment: 8 pages, Talk given at QCD@Work - International Workshop on QCD - Theory and Experiment, 20 - 23 June, 2010, Martina Franca Ital

Fast Ultrahigh-Density Writing of Low Conductivity Patterns on Semiconducting Polymers

The exceptional interest in improving the limitations of data storage, molecular electronics, and optoelectronics has promoted the development of an ever increasing number of techniques used to pattern polymers at micro and nanoscale. Most of them rely on Atomic Force Microscopy to thermally or electrostatically induce mass transport, thereby creating topographic features. Here we show that the mechanical interaction of the tip of the Atomic Force Microscope with the surface of a class of conjugate polymers produces a local increase of molecular disorder, inducing a localized lowering of the semiconductor conductivity, not associated to detectable modifications in the surface topography. This phenomenon allows for the swift production of low conductivity patterns on the polymer surface at an unprecedented speed exceeding 20 $\mu m s^{-1}$; paths have a resolution in the order of the tip size (20 nm) and are detected by a Conducting-Atomic Force Microscopy tip in the conductivity maps.Comment: 22 pages, 6 figures, published in Nature Communications as Article (8 pages

Counterfactual Explanations Using Optimization With Constraint Learning

Counterfactual explanations embody one of the many interpretability techniques that receive increasing attention from the machine learning community. Their potential to make model predictions more sensible to the user is considered to be invaluable. To increase their adoption in practice, several criteria that counterfactual explanations should adhere to have been put forward in the literature. We propose counterfactual explanations using optimization with constraint learning (CE-OCL), a generic and flexible approach that addresses all these criteria and allows room for further extensions. Specifically, we discuss how we can leverage an optimization with constraint learning framework for the generation of counterfactual explanations, and how components of this framework readily map to the criteria. We also propose two novel modeling approaches to address data manifold closeness and diversity, which are two key criteria for practical counterfactual explanations. We test CE-OCL on several datasets and present our results in a case study. Compared against the current state-of-the-art methods, CE-OCL allows for more flexibility and has an overall superior performance in terms of several evaluation metrics proposed in related work