Induced Pluripotent Stem Cells Technology For Investigating Familial Dilated Cardiomyopathy Due To Lamin A/C Mutations

Mutations of LMNA gene, encoding the proteins Lamin A and C, are common causes of familial dilated cardiomyopathy (DCM), typically manifesting in association with cardiac conduction defects. LaminA/C regulate various nuclear functions, including gene transcription and chromatin organization. Most of human studies on LaminA/C so far were conducted on fibroblasts, while those focusing on cardiomyocytes (CMs) are scarce. Thus, we generated a human cardiac model of LMNA-dependent cardiomyopathy (LMNA-CMP) by differentiating CMs from induced pluripotent stem cells (iPSCs) carrying the K219T and R190W LMNA mutations (LMNA-CMs). In vitro, these cells recapitulate morphological features of DCM. RNA-sequencing experiments revealed profound differences between control and LMNA-CMs transcriptomes. Remarkably, the main cardiac sodium channel gene (SCN5A), was one of the most downregulated gene. Accordingly, electrophysiological studies in LMNA-CMs showed a significant reduction of the maximal upstroke velocity and the related properties of the action potential, accompanied by a reduction of the peak sodium currents and diminished conduction velocity. Functional experiments also revealed diminished contractile force in LMNA mutated cells. Biochemical studies confirmed the reduction of SCN5A gene, and its encoded protein Nav1.5, and showed an increased binding of LaminA/C to its promoter. A higher deposition of H3K27me3 marker, together with an increased binding of its catalysing complex PRC2, was also found at that genomic locus. Furthermore, 3D-FISH studies indicated a preferential localization of SCN5A gene at the nuclear periphery. Similar findings were obtained in relation to genes of the contractile pathways. Altogether, these data support a mechanism by which LaminA/C influence cardiac function by directly acting on transcriptional regulation of genes that control CMs functionality. Studies conducted on CMs from CRISPR/Cas9 gene-edited iPSCs proved the causality between the LMNA mutation and the observed phenotypes. Finally, experiments for evaluating the efficacy of Remodelin molecule also demonstrated that the generated models are suitable for drug testing

THE SMART BOOKSHELF

The smart bookshelf serves as a test-bed to study environments that are intelligently augmented by projector-camera devices. The system utilizes a camera pair and a projector coupled with an RFID reader to monitor and maintain the state of a real world library shelf. Using a simple calibration scheme, the homography induced by the world plane in which book spines approximately lie is estimated. As books are added to the shelf, a foreground detection algorithm which takes into account the projected information yields new pixels in each view that are then verified using a planar parallax constraint across both cameras to yield the precise location of the book spine. The system allows users to query for the presence of a books through a user interface, highlighting the spines of present book using the known locations obtained through foreground detection and transforming image pixels to their corresponding points in the projectors frame via a derived homography. The system also can display the state of the bookshelf at any time in the past. Utilizing RFID tags increases robustness and usefulness of the application. Tags encode information about a book such as the title, author, etc, that can be used to query the system. It is used in conjunction with the visual system to infer the state of the shelf. This work provides a novel foreground detection algorithm that works across views, using loose geometric constraints instead pixel color similarity to robustly isolate foreground pixels. The system also takes into account projected information which if not handled would be detrimental to the system. The intent of this work was to study the feasibility of an augmented reality system and use this application as a testbed to study the issues of building such a system

Beyond Modeling: All-Atom Olfactory Receptor Model Simulations

Olfactory receptors (ORs) are a type of GTP-binding protein-coupled receptor (GPCR). These receptors are responsible for mediating the sense of smell through their interaction with odor ligands. OR-odorant interactions marks the first step in the process that leads to olfaction. Computational studies on model OR structures can generate focused and novel hypotheses for further bench investigation by providing a view of these interactions at the molecular level beyond inferences that are drawn merely from static docking. Here we have shown the specific advantages of simulating the dynamic environment associated with OR-odorant interactions. We present a rigorous protocol which ranges from the creation of a computationally derived model of an olfactory receptor to simulating the interactions between an OR and an odorant molecule. Given the ubiquitous occurrence of GPCRs in the membranes of cells, we anticipate that our OR-developed methodology will serve as a model for the computational structural biology of all GPCRs

Social media engagement optimized : a deep analysis of Facebook posts by beer brands

Social Networking Sites, like Facebook, are excellent platforms to leverage consumer-brand relationships. Brands can connect with people by creating a fan page and publishing content that captures their attention. Fans respond by liking, commenting and sharing it. In 2014, 200.243 million liters of beer were sold. Given the global popularity of beer and given that its potential customers, generation Y, are heavy users of Facebook, it is crucial for practitioners to understand how to engage Facebook users. This study investigates what type of post optimizes online engagement in beer brands Facebook fan page. Which beer brand has higher levels of engagement? Is it for its post’s content? Is it for its architecture? Is it for the communication style? Or is it because they talk to a national audience instead of talking to the world? To answer these questions, we measured engagement by counting the number of Likes, Comments and Shares that six global beer brands received in each post of their Facebook fan page, from 01.07.2014 to 31.12.2014. Based on these scores, we used SPSS’ exploratory factor analysis to generate the variable Engagement. We, then, analyzed the respective 988 Facebook posts in terms of their Content, Architecture and Communication goals. Finally, an empirical analysis using linear regression was conducted on the posts. This model empirically contributes to the existing literature on social media marketing, but more importantly, it helps beer community managers in the hope to conquer the so called “generation.com”.As redes sociais, como o Facebook, são excelentes plataformas para alavancar a relação marca-consumidor. As marcas têm a oportunidade de interagir com os consumidores ao criar páginas de fãs. Estes podem gostar, comentar e partilhar os conteúdos publicados. Em 2014, 200,243 milhões de litros de cerveja foram vendidos. Dada a popularidade mundial da cerveja, e dado que os seus potenciais clientes, a Geração Y, são utilizadores frequentes do Facebook, é fundamental, perceber o que motiva os fãs a interagir com as páginas de marcas de cerveja. Este estudo investiga que tipo de publicações otimiza o envolvimento dos utilizadores de Facebook com páginas de marcas de cerveja. Que marca consegue mais envolvimento? Será devido ao conteúdo das publicações? Ou será pela forma que estas tomam? Será que o estilo de comunicação influencia a popularidade das publicações? Ou deve-se ao facto de falarem para uma audiência nacional em vez de falarem para o mundo? Para responder a estas perguntas, o envolvimento dos fãs foi medido em função do número de gostos, comentários e partilhas que as publicações, de seis marcas de cerveja, receberam entre 2014/01/07 e 2014/12/31. Com base nestes dados, utilizamos a análise fatorial do programa SPSS, com o intuito de gerar a variável “engagement”. Ainda, analisámos as 988 publicações em termos de Conteúdo, Forma e Objetivos de comunicação graças à utilização de uma regressão linear. Este modelo contribui empiricamente para a pesquisa em marketing digital e visa ajudar os “community managers” de marcas de cerveja a conquistar a chamada "generation.com"