Stem/progenitor cells in pituitary organ homeostasis and tumourigenesis

Evidence for the presence of pituitary gland stem cells has been provided over the last decade using a combination of approaches including in vitro clonogenicity assays, flow cytometric side population analysis, immunohistochemical analysis and genetic approaches. These cells have been demonstrated to be able to self-renew and undergo multipotent differentiation to give rise to all hormonal lineages of the anterior pituitary. Furthermore, evidence exists for their contribution to regeneration of the organ and plastic responses to changing physiological demand. Recently, stem-like cells have been isolated from pituitary neoplasms raising the possibility that a cytological hierarchy exists, in keeping with the cancer stem cell paradigm. In this manuscript, we review the evidence for the existence of pituitary stem cells, their role in maintaining organ homeostasis and the regulation of their differentiation. Furthermore, we explore the emerging concept of stem cells in pituitary tumours and their potential roles in these diseases

Information Leakage Games

We consider a game-theoretic setting to model the interplay between attacker and defender in the context of information flow, and to reason about their optimal strategies. In contrast with standard game theory, in our games the utility of a mixed strategy is a convex function of the distribution on the defender's pure actions, rather than the expected value of their utilities. Nevertheless, the important properties of game theory, notably the existence of a Nash equilibrium, still hold for our (zero-sum) leakage games, and we provide algorithms to compute the corresponding optimal strategies. As typical in (simultaneous) game theory, the optimal strategy is usually mixed, i.e., probabilistic, for both the attacker and the defender. From the point of view of information flow, this was to be expected in the case of the defender, since it is well known that randomization at the level of the system design may help to reduce information leaks. Regarding the attacker, however, this seems the first work (w.r.t. the literature in information flow) proving formally that in certain cases the optimal attack strategy is necessarily probabilistic

Learners’ frequent pattern discovering in a dynamic collaborative learning environment designed based on game theory

Background and Objectives:In any educational system, the optimal output of educational approach is of particular importance. Therefore, considering the personality characters of individuals and providing educational services in accordance with their characteristics are effective factors in learning and educational efficiency improvement. Analyzing the data related to learner’s behavior in an educational environment and implicitly discovering the learner’s personality based on their behavior is a well-noticed study in recent years. Over the last few years, using learners’ information such as number of friends, the level of activities in educational forum, writing style of learner, study duration, the difficulty of solved problem, the difficulty of presented example by learners, number of clicks, number of signs in sentences, the time spent doing homework are items that has been used to personal characteristic identification. This study is aimed at using teammates’ changing / not changing data in order to learners’ personality identification. For this purpose the teammates’ changing/ not changing data extracted from a dynamic collaborative learning environment that allows leaners to change their teammate during the different sessions of learning, are used. The design and implementation of mentioned dynamic collaborative learning environment is based on game theory. Game theory provides mathematical models of conflict and collaboration between intelligent rational decision-makers. Methods: In this paper, we collect teammates’ changing/not changing information of 119 randomly selected computer engineering students from a game theoretical dynamic collaborative learning environment. At the next step, using frequent pattern mining, as a tools of data mining, some aspects of the neo big 5 personality traits of learners are identified. In this survey, in order to evaluate the results, the extracted patterns from frequent pattern mining are compared with the neo big 5 personality questionnaire that have been filled by learners. In another part of research, using the Laplace’s rule of succession, valuable predictions were made about the probability of teammate’s changing of learners during the learning process. Findings: In this study, using frequent pattern mining in learners’ behaviour, we identified some neo big 5 personality traits such as those in the first (neuroticism), second (extraversion), and third (openness to experience) dimensions, with an acceptable support value. The results of this part of research can be used in any adaptive learning environment that adapt learning process for individual learners with different personality. At the next step of our study, we predicted the probability of the teammate changing in the sessions after. At this step, we had a prediction accuracy of up to 67.44%. Using the results of this part, teammate suggestion can be made to learner based on likelihood of their teammates’ changing. That is, higher teammate changing probability, more appropriate teammate suggestion to learner. Conclusion: The results of the present study can be used in any adaptive system that requires predicting group change behaviour or identifying personality dimensions based on behaviour.   ===================================================================================== COPYRIGHTS  ©2020 The author(s). This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, as long as the original authors and source are cited. No permission is required from the authors or the publishers.  ====================================================================================

Multi-Layer Cyber-Physical Security and Resilience for Smart Grid

The smart grid is a large-scale complex system that integrates communication technologies with the physical layer operation of the energy systems. Security and resilience mechanisms by design are important to provide guarantee operations for the system. This chapter provides a layered perspective of the smart grid security and discusses game and decision theory as a tool to model the interactions among system components and the interaction between attackers and the system. We discuss game-theoretic applications and challenges in the design of cross-layer robust and resilient controller, secure network routing protocol at the data communication and networking layers, and the challenges of the information security at the management layer of the grid. The chapter will discuss the future directions of using game-theoretic tools in addressing multi-layer security issues in the smart grid.Comment: 16 page

Social Media Monitoring of the Campaigns for the 2013 German Bundestag Elections on Facebook and Twitter

As more and more people use social media to communicate their view and perception of elections, researchers have increasingly been collecting and analyzing data from social media platforms. Our research focuses on social media communication related to the 2013 election of the German parliament [translation: Bundestagswahl 2013]. We constructed several social media datasets using data from Facebook and Twitter. First, we identified the most relevant candidates (n=2,346) and checked whether they maintained social media accounts. The Facebook data was collected in November 2013 for the period of January 2009 to October 2013. On Facebook we identified 1,408 Facebook walls containing approximately 469,000 posts. Twitter data was collected between June and December 2013 finishing with the constitution of the government. On Twitter we identified 1,009 candidates and 76 other agents, for example, journalists. We estimated the number of relevant tweets to exceed eight million for the period from July 27 to September 27 alone. In this document we summarize past research in the literature, discuss possibilities for research with our data set, explain the data collection procedures, and provide a description of the data and a discussion of issues for archiving and dissemination of social media data

MAPK pathway activation in the embryonic pituitary results in stem cell compartment expansion, differentiation defects and provides insights into the pathogenesis of papillary craniopharyngioma.

Despite the importance of the RAS-RAF-MAPK pathway in normal physiology and disease of numerous organs, its role during pituitary development and tumourigenesis remains largely unknown. Here we show that the over-activation of the MAPK pathway, through conditional expression of the gain-of-function alleles BrafV600E and KrasG12D in the developing mouse pituitary, results in severe hyperplasia and abnormal morphogenesis of the gland by the end of gestation. Cell-lineage commitment and terminal differentiation are disrupted, leading to a significant reduction in numbers of most of the hormone-producing cells before birth, with the exception of corticotrophs. Of note, Sox2+ve stem cells and clonogenic potential are drastically increased in the mutant pituitaries. Finally, we reveal that papillary craniopharyngioma (PCP), a benign human pituitary tumour harbouring BRAF p.V600E also contains Sox2+ve cells with sustained proliferative capacity and disrupted pituitary differentiation. Together, our data demonstrate a critical function of the MAPK pathway in controlling the balance between proliferation and differentiation of Sox2+ve cells and suggest that persistent proliferative capacity of Sox2+ve cells may underlie the pathogenesis of PCP

Evolutionary dynamics of tumor-stroma interactions in multiple myeloma

Cancer cells and stromal cells cooperate by exchanging diffusible factors that sustain tumor growth, a form of frequency-dependent selection that can be studied in the framework of evolutionary game theory. In the case of multiple myeloma, three types of cells (malignant plasma cells, osteoblasts and osteoclasts) exchange growth factors with different effects, and tumor-stroma interactions have been analysed using a model of cooperation with pairwise interactions. Here we show that a model in which growth factors have autocrine and paracrine effects on multiple cells, a more realistic assumption for tumor-stroma interactions, leads to different results, with implications for disease progression and treatment. In particular, the model reveals that reducing the number of malignant plasma cells below a critical threshold can lead to their extinction and thus to restore a healthy balance between osteoclast and osteoblast, a result in line with current therapies against multiple myeloma

Tumour compartment transcriptomics demonstrates the activation of inflammatory and odontogenic programmes in human adamantinomatous craniopharyngioma and identifies the MAPK/ERK pathway as a novel therapeutic target

Adamantinomatous craniopharyngiomas (ACPs) are clinically challenging tumours, the majority of which have activating mutations in CTNNB1. They are histologically complex, showing cystic and solid components, the latter comprised of different morphological cell types (e.g. β-catenin-accumulating cluster cells and palisading epithelium), surrounded by a florid glial reaction with immune cells. Here, we have carried out RNA sequencing on 18 ACP samples and integrated these data with an existing ACP transcriptomic dataset. No studies so far have examined the patterns of gene expression within the different cellular compartments of the tumour. To achieve this goal, we have combined laser capture microdissection with computational analyses to reveal groups of genes that are associated with either epithelial tumour cells (clusters and palisading epithelium), glial tissue or immune infiltrate. We use these human ACP molecular signatures and RNA-Seq data from two ACP mouse models to reveal that cell clusters are molecularly analogous to the enamel knot, a critical signalling centre controlling normal tooth morphogenesis. Supporting this finding, we show that human cluster cells express high levels of several members of the FGF, TGFB and BMP families of secreted factors, which signal to neighbouring cells as evidenced by immunostaining against the phosphorylated proteins pERK1/2, pSMAD3 and pSMAD1/5/9 in both human and mouse ACP. We reveal that inhibiting the MAPK/ERK pathway with trametinib, a clinically approved MEK inhibitor, results in reduced proliferation and increased apoptosis in explant cultures of human and mouse ACP. Finally, we analyse a prominent molecular signature in the glial reactive tissue to characterise the inflammatory microenvironment and uncover the activation of inflammasomes in human ACP. We validate these results by immunostaining against immune cell markers, cytokine ELISA and proteome analysis in both solid tumour and cystic fluid from ACP patients. Our data support a new molecular paradigm for understanding ACP tumorigenesis as an aberrant mimic of natural tooth development and opens new therapeutic opportunities by revealing the activation of the MAPK/ERK and inflammasome pathways in human ACP. KEYWORDS: Craniopharyngioma; IL1-β; Inflammasome; MAPK/ERK pathway; Odontogenesis; Paracrine signalling; Trametini

A Social-Aware approach for federated iot-mobile cloud using matching theory

In the Internet of Things (IoT) scenario, the deployment of integrated environments have pushed forward the collaboration of heterogeneous devices to match wide-ranging user requirements. However, several open challenges need to be solved such as the intrinsic unreliability of IoT devices as well as the variety in users' preferences when sharing their devices. In this paper, we give a contribution by proposing a novel hybrid paradigm to support the cooperation among IoT devices and exploit their unused resources. Our solution is based on the Social IoT concept (SIoT), where objects are connected to the Internet create a dynamic social network based on the rules set by their owner. In particular, we introduce the concept of Social Mobile-IoT Clouds (SMICs), where heterogeneous devices combine their resources to serve other co-location devices requirements. In the proposed mechanism, the notion of object sociality is considered to build the required trustworthiness among devices. To this aim, we make use of a Many to Many (M-M) assignment game based on matching theory to support the cooperation among devices. Our simulation results confirm the enhancements achievement in terms of percentage of resources being successfully assigned

P4QS : a peer-to-peer privacy preserving query service for location-based mobile applications

The location-based services provide an interesting combination of cyber and physical worlds. However, they can also threaten the users' privacy. Existing privacy preserving protocols require trusted nodes, with serious security and computational bottlenecks. In this paper, we propose a novel distributed anonymizing protocol based on peer-To-peer architecture. Each mobile node is responsible for anonymizing a specific zone. The mobile nodes collaborate in anonymizing their queries, without the need of getting access to any information about each other. In the proposed protocol, each request will be sent with a randomly chosen ticket. The encrypted response produced by the server is sent to a particular mobile node (called broker node) over the network, based on the hash value of this ticket. The user will query the broker to get the response. All parts of the messages are encrypted except the fields required for the anonymizer and the broker. This will secure the packet exchange over the P2P network. The proposed protocol was implemented and tested successfully, and the experimental results showed that it could be deployed efficiently to achieve user privacy in location-based services