Global gene expression profiling of a mouse model of ovarian clear cell carcinoma caused by ARID1A and PIK3CA mutations implicates a role for inflammatory cytokine signaling

Ovarian clear-cell carcinoma (OCCC) is an aggressive form of epithelial ovarian cancer (EOC). OCCC represents 5-25% of all EOC incidences and is the second leading cause of death from ovarian cancer (Glasspool and McNeish, 2013) [1]. A recent publication by Chandler et al. reported the first mouse model of OCCC that resembles human OCCC both genetically and histologically by inducing a localized deletion of ARID1A and the expression of the PIK3CAH1047R substitution mutation (Chandler et al., 2015) [2]. We utilized Affymetrix Mouse Gene 2.1 ST arrays for the global gene expression profiling of mouse primary OCCC tumor samples and animal-matched normal ovaries to identify cancer-dependent gene expression. We describe the approach used to generate the differentially expressed genes from the publicly available data deposited at the Gene Expression Omnibus (GEO) database under the accession number GSE57380. These data were used in cross-species comparisons to publically available human OCCC gene expression data and allowed the identification of coordinately regulated genes in both mouse and human OCCC and supportive of a role for inflammatory cytokine signaling in OCCC pathogenesis (Chandler et al., 2015) [2]

Primordial Nucleosynthesis Constraints on Z' Properties

In models involving new TeV-scale Z' gauge bosons, the new U(1)' symmetry often prevents the generation of Majorana masses needed for a conventional neutrino seesaw, leading to three superweakly interacting ``right-handed'' neutrinos nu_R, the Dirac partners of the ordinary neutrinos. These can be produced prior to big bang nucleosynthesis by the Z' interactions, leading to a faster expansion rate and too much ^4He. We quantify the constraints on the Z' properties from nucleosynthesis for Z' couplings motivated by a class of E_6 models parametrized by an angle theta_E6. The rate for the annihilation of three approximately massless right-handed neutrinos into other particle pairs through the Z' channel is calculated. The decoupling temperature, which is higher than that of ordinary left-handed neutrinos due to the large Z' mass, is evaluated, and the equivalent number of new doublet neutrinos Delta N_nu is obtained numerically as a function of the Z' mass and couplings for a variety of assumptions concerning the Z-Z' mixing angle and the quark-hadron transition temperature T_c. Except near the values of theta_E6 for which the Z' decouples from the right-handed neutrinos, the Z' mass and mixing constraints from nucleosynthesis are much more stringent than the existing laboratory limits from searches for direct production or from precision electroweak data, and are comparable to the ranges that may ultimately be probed at proposed colliders. For the case T_c = 150 MeV with the theoretically favored range of Z-Z' mixings, Delta N_nu 4.3 TeV for any value of theta_E6. Larger mixing or larger T_c often lead to unacceptably large Delta N_nu except near the nu_R decoupling limit.Comment: 22 pages, 5 figures; two additional references adde

Architektury kognitywne, czyli jak zbudować sztuczny umysł

Architektury kognitywne (AK) są próbą stworzenia modeli komputerowych integrujących wiedzę o działaniu umysłu. Ich zadaniem jest implementacja konkretnych schematów działania funkcji poznawczych umożliwiająca testowanie tych funkcji na szerokiej gamie zagadnień. Wiele architektur kognitywnych opracowano w celu symulacji procesu komunikacji pomiędzy człowiekiem i złożonymi maszynami (HCI, Human-Computer Interfaces), symulowania czasów reakcji oraz różnych psychofizycznych zależności. Można to do pewnego stopnia osiągnąć budując modele układu poznawczego na poziomie symbolicznym, z wiedzą w postaci reguł logicznych. Istnieją też projekty, które próbują powiązać procesy poznawcze z aktywacją modułów reprezentujących konkretne obszary mózgu, zgodnie z obserwacjami w eksperymentach z funkcjonalnym rezonansem magnetycznym (fMRI). Dużą grupę stanowią architektury oparte na podejściu logicznym, które mają na celu symulację wyższych czynności poznawczych, przede wszystkim procesów myślenia i rozumowania. Niektóre z projektów rozwoju architektur poznawczych skupiają większe grupy badawcze działające od wielu dziesięcioleci. Ogólnie architektury kognitywne podzielić można na 3 duże grupy: architektury symboliczne (oparte na funkcjonalnym rozumieniu procesów poznawczych); architektury emergentne, oparte na modelach koneksjonistycznych; oraz architektury hybrydowe, wykorzystujące zarówno modele neuronowe jak i reguły symboliczne. W ostatnich latach znacznie wzrosło zainteresowanie architekturami inspirowanymi przez neurobiologię (BICA, Brain Inspired Cognitive Architectures). Jak sklasyfikować różne architektury, jakie wyzwania należy przed nimi postawić, jak oceniać postępy w ich rozwoju, czego nam brakuje do stworzenia pełnego modelu umysłu? Krytyczny przegląd istniejących architektur kognitywnych, ich ograniczeń i możliwości pozwala na sformułowanie ogólnych wniosków dotyczących kierunków ich rozwoju czego nam brakuje do stworzenia pełnego modelu umysłu? Krytyczny przegląd istniejących architektur kognitywnych, ich ograniczeń i możliwości pozwala na sformułowanie ogólnych wniosków dotyczących kierunków ich rozwoju oraz wysunięcie własnych propozycji budowy nowej architektury

A dynamic neural field approach to natural and efficient human-robot collaboration

A major challenge in modern robotics is the design of autonomous robots that are able to cooperate with people in their daily tasks in a human-like way. We address the challenge of natural human-robot interactions by using the theoretical framework of dynamic neural fields (DNFs) to develop processing architectures that are based on neuro-cognitive mechanisms supporting human joint action. By explaining the emergence of self-stabilized activity in neuronal populations, dynamic field theory provides a systematic way to endow a robot with crucial cognitive functions such as working memory, prediction and decision making . The DNF architecture for joint action is organized as a large scale network of reciprocally connected neuronal populations that encode in their firing patterns specific motor behaviors, action goals, contextual cues and shared task knowledge. Ultimately, it implements a context-dependent mapping from observed actions of the human onto adequate complementary behaviors that takes into account the inferred goal of the co-actor. We present results of flexible and fluent human-robot cooperation in a task in which the team has to assemble a toy object from its components.The present research was conducted in the context of the fp6-IST2 EU-IP Project JAST (proj. nr. 003747) and partly financed by the FCT grants POCI/V.5/A0119/2005 and CONC-REEQ/17/2001. We would like to thank Luis Louro, Emanuel Sousa, Flora Ferreira, Eliana Costa e Silva, Rui Silva and Toni Machado for their assistance during the robotic experiment

Specification of the near-Earth space environment with SHIELDS

Predicting variations in the near-Earth space environment that can lead to spacecraft damage and failure is one example of “space weather” and a big space physics challenge. A project recently funded through the Los Alamos National Laboratory (LANL) Directed Research and Development (LDRD) program aims at developing a new capability to understand, model, and predict Space Hazards Induced near Earth by Large Dynamic Storms, the SHIELDS framework. The project goals are to understand the dynamics of the surface charging environment (SCE), the hot (keV) electrons representing the source and seed populations for the radiation belts, on both macro- and micro-scale. Important physics questions related to particle injection and acceleration associated with magnetospheric storms and substorms, as well as plasma waves, are investigated. These challenging problems are addressed using a team of world-class experts in the fields of space science and computational plasma physics, and state-of-the-art models and computational facilities. A full two-way coupling of physics-based models across multiple scales, including a global MHD (BATS-R-US) embedding a particle-in-cell (iPIC3D) and an inner magnetosphere (RAM-SCB) codes, is achieved. New data assimilation techniques employing in situ satellite data are developed; these provide an order of magnitude improvement in the accuracy in the simulation of the SCE. SHIELDS also includes a post-processing tool designed to calculate the surface charging for specific spacecraft geometry using the Curvilinear Particle-In-Cell (CPIC) code that can be used for reanalysis of satellite failures or for satellite design

Biodistribution of 64 Cu in Inflamed Rats Following Administration of Two Anti-Inflammatory Copper Complexes

64Cu was administered in two anti-inflammatory formulations to normal rats and to rats with 2 forms of local inflammation, namely (a) an acute paw oedema (elicited with carrageenan) or (b) a chronic granulomatous response to an implanted irritant (Mycobacterium tuberculosis in a polyurethane sponge). The copper formulations used were (i) a slow release one consisting of Cu(II) salicylate applied dermally with ethanol/DMSO and (ii) short acting hydrophilic complex (Cu(I)Cu(II)-penicillamine)5- given subcutaneously. Three types of changes in copper biodistribution with these forms of inflammation were discerned based on determination of 64Cu and copper content in the following organs: inflammatory locus (foot or sponge implant), kidney, liver, spleen, adrenals, brain, blood, thymus, heart, and skin (site of application). The most evident changes were in the kidneys, liver, spleen, adrenals, thymus and serum from animals with chronic granulomatous inflammation. In contrast, a short term acute inflammatory stress (carrageenan paw oedema) had little effect. While copper D-penicillamine (applied subcutaneously) appeared to move as a bolus through the animals, the results with the percutaneous copper salicylate formulation are consistent with it providing a slow release source of copper(II). Exogenous 64Cu from both formulations was sequestered at inflammatory sites (relative to serum). This may partly explain how applied copper complexes can be anti-inflammatory

Modern temporal network theory: A colloquium

The power of any kind of network approach lies in the ability to simplify a complex system so that one can better understand its function as a whole. Sometimes it is beneficial, however, to include more information than in a simple graph of only nodes and links. Adding information about times of interactions can make predictions and mechanistic understanding more accurate. The drawback, however, is that there are not so many methods available, partly because temporal networks is a relatively young field, partly because it more difficult to develop such methods compared to for static networks. In this colloquium, we review the methods to analyze and model temporal networks and processes taking place on them, focusing mainly on the last three years. This includes the spreading of infectious disease, opinions, rumors, in social networks; information packets in computer networks; various types of signaling in biology, and more. We also discuss future directions.Comment: Final accepted versio

Novel genetic loci associated with hippocampal volume

The hippocampal formation is a brain structure integrally involved in episodic memory, spatial navigation, cognition and stress responsiveness. Structural abnormalities in hippocampal volume and shape are found in several common neuropsychiatric disorders. To identify the genetic underpinnings of hippocampal structure here we perform a genome-wide association study (GWAS) of 33,536 individuals and discover six independent loci significantly associated with hippocampal volume, four of them novel. Of the novel loci, three lie within genes (ASTN2, DPP4 and MAST4) and one is found 200 kb upstream of SHH. A hippocampal subfield analysis shows that a locus within the MSRB3 gene shows evidence of a localized effect along the dentate gyrus, subiculum, CA1 and fissure. Further, we show that genetic variants associated with decreased hippocampal volume are also associated with increased risk for Alzheimer's disease (rg =-0.155). Our findings suggest novel biological pathways through which human genetic variation influences hippocampal volume and risk for neuropsychiatric illness