MONITORING POTENTIAL DRUG INTERACTIONS AND REACTIONS VIA NETWORK ANALYSIS OF INSTAGRAM USER TIMELINES

Much recent research aims to identify evidence for Drug-Drug Interactions (DDI) and Adverse Drug reactions (ADR) from the biomedical scientific literature. In addition to this "Bibliome", the universe of social media provides a very promising source of large-scale data that can help identify DDI and ADR in ways that have not been hitherto possible. Given the large number of users, analysis of social media data may be useful to identify under-reported, population-level pathology associated with DDI, thus further contributing to improvements in population health. Moreover, tapping into this data allows us to infer drug interactions with natural products-including cannabis-which constitute an array of DDI very poorly explored by biomedical research thus far. Our goal is to determine the potential of Instagram for public health monitoring and surveillance for DDI, ADR, and behavioral pathology at large. Most social media analysis focuses on Twitter and Facebook, but Instagram is an increasingly important platform, especially among teens, with unrestricted access of public posts, high availability of posts with geolocation coordinates, and images to supplement textual analysis. Using drug, symptom, and natural product dictionaries for identification of the various types of DDI and ADR evidence, we have collected close to 7000 user timelines spanning from October 2010 to June 2015.We report on 1) the development of a monitoring tool to easily observe user-level timelines associated with drug and symptom terms of interest, and 2) population-level behavior via the analysis of co-occurrence networks computed from user timelines at three different scales: monthly, weekly, and daily occurrences. Analysis of these networks further reveals 3) drug and symptom direct and indirect associations with greater support in user timelines, as well as 4) clusters of symptoms and drugs revealed by the collective behavior of the observed population. This demonstrates that Instagram contains much drug- and pathology specific data for public health monitoring of DDI and ADR, and that complex network analysis provides an important toolbox to extract health-related associations and their support from large-scale social media data

City-wide Analysis of Electronic Health Records Reveals Gender and Age Biases in the Administration of Known Drug-Drug Interactions

The occurrence of drug-drug-interactions (DDI) from multiple drug dispensations is a serious problem, both for individuals and health-care systems, since patients with complications due to DDI are likely to reenter the system at a costlier level. We present a large-scale longitudinal study (18 months) of the DDI phenomenon at the primary- and secondary-care level using electronic health records (EHR) from the city of Blumenau in Southern Brazil (pop. $\approx 340,000$). We found that 181 distinct drug pairs known to interact were dispensed concomitantly to 12\% of the patients in the city's public health-care system. Further, 4\% of the patients were dispensed drug pairs that are likely to result in major adverse drug reactions (ADR)---with costs estimated to be much larger than previously reported in smaller studies. The large-scale analysis reveals that women have a 60\% increased risk of DDI as compared to men; the increase becomes 90\% when considering only DDI known to lead to major ADR. Furthermore, DDI risk increases substantially with age; patients aged 70-79 years have a 34\% risk of DDI when they are dispensed two or more drugs concomitantly. Interestingly, a statistical null model demonstrates that age- and female-specific risks from increased polypharmacy fail by far to explain the observed DDI risks in those populations, suggesting unknown social or biological causes. We also provide a network visualization of drugs and demographic factors that characterize the DDI phenomenon and demonstrate that accurate DDI prediction can be included in healthcare and public-health management, to reduce DDI-related ADR and costs

INFORMAL STRATEGIZING IN A PUBLIC ORGANIZATION

Strategy as Practice analyzes what people do in relation to the development of strategy in organizations, providing insights into current issues in strategy that require a more micro level of understanding (JOHNSON et al., 2007). Considering the perspective of strategy as practice arising from the emerging strategies, we noticed the lack of studies to understand how these activities occur in a daily basis of organization characterizing as informal strategies (WHITTINGTON, 2007). Therefore, this study proposes to address this issue, showing the occurrence of informal strategizing at a public organization under the strategy-as-practice perspective. For this we held a qualitative research through a single case study (EISENHARDT, 1989) in a municipality in southern Brazil. Data were collected through semi-structured interviews with officials of different levels of the organization; direct observation, with notebook guide and analysis of documents provided by the organization, encouraging the triangulation of data. Informal strategies were mainly identified on customer service activities when an applicant’s request is not strictly met under the law or the legislation is dubious and opens room for double-meaning surveying, interpretation and information communication

CANA: A python package for quantifying control and canalization in Boolean Networks

Logical models offer a simple but powerful means to understand the complex dynamics of biochemical regulation, without the need to estimate kinetic parameters. However, even simple automata components can lead to collective dynamics that are computationally intractable when aggregated into networks. In previous work we demonstrated that automata network models of biochemical regulation are highly canalizing, whereby many variable states and their groupings are redundant (Marques-Pita and Rocha, 2013). The precise charting and measurement of such canalization simplifies these models, making even very large networks amenable to analysis. Moreover, canalization plays an important role in the control, robustness, modularity and criticality of Boolean network dynamics, especially those used to model biochemical regulation (Gates and Rocha, 2016; Gates et al., 2016; Manicka, 2017). Here we describe a new publicly-available Python package that provides the necessary tools to extract, measure, and visualize canalizing redundancy present in Boolean network models. It extracts the pathways most effective in controlling dynamics in these models, including their effective graph and dynamics canalizing map, as well as other tools to uncover minimum sets of control variables.Comment: Submitted to the Systems Biology section of Frontiers in Physiolog

Mining social media data for biomedical signals and health-related behavior

Social media data has been increasingly used to study biomedical and health-related phenomena. From cohort level discussions of a condition to planetary level analyses of sentiment, social media has provided scientists with unprecedented amounts of data to study human behavior and response associated with a variety of health conditions and medical treatments. Here we review recent work in mining social media for biomedical, epidemiological, and social phenomena information relevant to the multilevel complexity of human health. We pay particular attention to topics where social media data analysis has shown the most progress, including pharmacovigilance, sentiment analysis especially for mental health, and other areas. We also discuss a variety of innovative uses of social media data for health-related applications and important limitations in social media data access and use.Comment: To appear in the Annual Review of Biomedical Data Scienc

Redes sociais digitais: uma análise de utilização pelas instituições de ensino superior do sistema ACAFE de Santa Catarina

Is known that knowledge is collaborative and has fueled the emergence of numerous proposals in network environments that enable the exchange of information. Strategically, these social networks are increasingly being used by Higher Education Institutions as elements of institutional strengthening and expansion of brand relationship. This study sought to identify the social networks used by Higher Education Institutions belonging to the ACAFE system of Santa Catarina – Brazil – describing the use of these environments as a strategic tool. The research is characterized as exploratory and descriptive, with a intentional sample. The analysis of the use of social networks has confirmed the high diversity of Twitter, highlighting it as the most used tool being present in 81% of HEI, followed by the use of Blogs, with 56% of presence in the institution’s website. Through interview was also assessed a manager's concern for control and maintenance of social networks.RESUMOSabe-se que o conhecimento é colaborativo e vem fomentando o surgimento das inúmeras propostas de ambientes em rede que possibilitam a troca de informações. De maneira estratégica, estas redes sociais são cada vez mais utilizadas pelas Instituições de Ensino Superior como elementos de fortalecimento da marca institucional e ampliação do relacionamento. Assim, este trabalho procurou identificar as redes sociais utilizadas pelas Instituições de Ensino Superior do sistema ACAFE de Santa Catarina e descrever a utilização destes ambientes como ferramenta estratégica. A pesquisa se caracteriza como exploratória descritiva, com amostragem intencional. A análise das redes sociais confirmou a alta representatividade do Twitter, destacando-o como a ferramenta mais utilizada, por estar presente em 81% das IES, seguido pela utilização de Blogs, com 56% de presença nos sites das instituições. Por meio de entrevista foi aferida também uma preocupação por parte dos gestores IES no controle e manutenção das redes sociais

ESTUDO DE CASO NO SEGMENTO GASTRONÔMICO COM A UTILIZAÇÃO DA API DO GOOGLE MAPS E GOOGLE ANALYTICS

Este artigo apresenta a implementação de um sistema web para a catalogação e divulgação de ambientes gastronômicos, mais conhecidos como “Botecos” sendo o ponto auge do sistema a divulgação da “Baixa Gastronomia”. Foi utilizada a WebML em seus modelos de dados e de hiperlinks para transpor os requisitos do sistema em sua especificação. O desenvolvimento seguiu as técnicas de usabilidade na web para ter uma fácil interação com o usuário. A técnica de programação conhecida como Ajax foi usada para aumentar esta interação. A API do Google Maps foi utilizada para mostrar a localização dos estabelecimentos diretamente em um mapa. O software permite, por meio de uma área administrativa, o cadastramento de “Botecos”, fotos, vídeos e personalidades para estes e ainda a inclusão de notícias na capa do sistema na forma de Blog. Palavras-chave: Boteco. Baixa gastronomia. WebML. Usabilidade na web. Google Maps

A utilização do observatório da educação como inteligência competitiva em uma instituição de ensino superior

Devido a grande demanda de cursos e a acirrada competição no mercado educacional, torna-se imprescindível que as Instituições de Ensino Superior (IES) tenham em mãos informações e dados relevantes para a tomada de decisão. Surge neste processo a Inteligência Competitiva para auxiliar a tomada de decisão dos gestores, criando assim uma vantagem competitiva adquirida com as informações sobre que estão disponíveis no mercado. Os programas de pós-graduação a nível stricto sensu em administração passam por uma reestruturação na tentativa de se adequar as constantes mudanças externas e internas da educação superior. O SIOE, Sistemas de Informação Observatório da Educação, provê para estas IES, uma possibilidade de acompanharem o desempenho de produção dos seus docentes, podendo assim, realizar ajustes ao longo do trajeto, que auxiliem o alcance das metas organizacionais. A amostra das IES estudadas para este trabalho é composta por 4 instituições em Blumenau. O presente trabalho tem como objetivo identificar a percepção e conhecimento dos entrevistados a respeito de Inteligência Competitiva, a forma na qual ela é utilizada na organização e como funciona tal processo. Para isto, apresenta-se como modelo o SIOE, que tem por objetivo servir como avaliador de desempenho dos docentes pertencentes ao quadro do programa, fornecendo dados e informações que sejam pertinentes à gestão e que os mesmos possam tomar as melhores decisões guiando a organização à criação de uma vantagem que seja o mais sustentável possível

A utilização do observatório da educação como inteligência competitiva em uma instituição de ensino superior

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