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BACKGROUND: Nowadays, the use of social media is part of daily life, with more and more people, including governments and health organizations, using at least one platform regularly. Social media enables users to interact among large groups of people that share the same interests and suffer the same afflictions. Notably, these channels promote the ability to find and share information about health and medical conditions. OBJECTIVE: This study aimed to characterize the bowel disease (BD) community on Twitter, in particular how patients understand, discuss, feel, and react to the condition. The main questions were as follows: Which are the main communities and most influential users?; Where are the main content providers from?; What are the key biomedical and scientific topics under discussion? How are topics interrelated in patient communications?; How do external events influence user activity?; What kind of external sources of information are being promoted? METHODS: To answer these questions, a dataset of tweets containing terms related to BD conditions was collected from February to August 2018, accounting for a total of 24,634 tweets from 13,295 different users. Tweet preprocessing entailed the extraction of textual contents, hyperlinks, hashtags, time, location, and user information. Missing and incomplete information about the user profiles was completed using different analysis techniques. Semantic tweet topic analysis was supported by a lexicon-based entity recognizer. Furthermore, sentiment analysis enabled a closer look into the opinions expressed in the tweets, namely, gaining a deeper understanding of patients' feelings and experiences. RESULTS: Health organizations received most of the communication, whereas BD patients and experts in bowel conditions and nutrition were among those tweeting the most. In general, the BD community was mainly discussing symptoms, BD-related diseases, and diet-based treatments. Diarrhea and constipation were the most commonly mentioned symptoms, and cancer, anxiety disorder, depression, and chronic inflammations were frequently part of BD-related tweets. Most patient tweets discussed the bad side of BD conditions and other related conditions, namely, depression, diarrhea, and fibromyalgia. In turn, gluten-free diets and probiotic supplements were often mentioned in patient tweets expressing positive emotions. However, for the most part, tweets containing mentions to foods and diets showed a similar distribution of negative and positive sentiments because the effects of certain food components (eg, fiber, iron, and magnesium) were perceived differently, depending on the state of the disease and other personal conditions of the patients. The benefits of medical cannabis for the treatment of different chronic diseases were also highlighted. CONCLUSIONS: This study evidences that Twitter is becoming an influential space for conversation about bowel conditions, namely, patient opinions about associated symptoms and treatments. So, further qualitative and quantitative content analyses hold the potential to support decision making among health-related stakeholders, including the planning of awareness campaigns.
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Neoplasias do Colo/psicologia , Conhecimentos, Atitudes e Prática em Saúde , Síndrome do Intestino Irritável/psicologia , Mídias Sociais , Inquéritos e Questionários , Demografia , Saúde Global , HumanosRESUMO
BACKGROUND: Shared tasks and community challenges represent key instruments to promote research, collaboration and determine the state of the art of biomedical and chemical text mining technologies. Traditionally, such tasks relied on the comparison of automatically generated results against a so-called Gold Standard dataset of manually labelled textual data, regardless of efficiency and robustness of the underlying implementations. Due to the rapid growth of unstructured data collections, including patent databases and particularly the scientific literature, there is a pressing need to generate, assess and expose robust big data text mining solutions to semantically enrich documents in real time. To address this pressing need, a novel track called "Technical interoperability and performance of annotation servers" was launched under the umbrella of the BioCreative text mining evaluation effort. The aim of this track was to enable the continuous assessment of technical aspects of text annotation web servers, specifically of online biomedical named entity recognition systems of interest for medicinal chemistry applications. RESULTS: A total of 15 out of 26 registered teams successfully implemented online annotation servers. They returned predictions during a two-month period in predefined formats and were evaluated through the BeCalm evaluation platform, specifically developed for this track. The track encompassed three levels of evaluation, i.e. data format considerations, technical metrics and functional specifications. Participating annotation servers were implemented in seven different programming languages and covered 12 general entity types. The continuous evaluation of server responses accounted for testing periods of low activity and moderate to high activity, encompassing overall 4,092,502 requests from three different document provider settings. The median response time was below 3.74 s, with a median of 10 annotations/document. Most of the servers showed great reliability and stability, being able to process over 100,000 requests in a 5-day period. CONCLUSIONS: The presented track was a novel experimental task that systematically evaluated the technical performance aspects of online entity recognition systems. It raised the interest of a significant number of participants. Future editions of the competition will address the ability to process documents in bulk as well as to annotate full-text documents.
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MOTIVATION: Single cells often show stochastic behaviour and variations in the physiological state of individual cells affect the behaviour observed in cell populations. This may be partially explained by variations in the concentration and spatial location of molecules within and in the vicinity of each cell. METHODS: This paper introduces an agent-based model that represents single-molecule transport through the cellular envelope of Escherichia coli at the micrometre scale. This model enables broader observation of molecular transport throughout the different membrane layers and the study of the effect of molecular concentration in cellular noise. Simulations considered various low molecular weight molecules, i.e. ampicillin, bosentan, coumarin, saquinavir, and terbutaline, and a gradient of molecular concentrations. The model ensured stochasticity in the location of the agents, using diffusing spherical particles with physical dimensions. RESULTS: Simulation results were validated against theoretical and experimental data. For example, theoretically, ampicillin molecules take 0.6â¯s to cross the entire cell envelope, and computational simulations took 0.68â¯s, 0.68â¯s, 0.70â¯s, and 0.69â¯s, for concentrations of 1.44⯵M, 13.21⯵M, 26.4⯵M and 105.61⯵M, respectively. Replicate standard deviation decreased with growing initial concentrations of the molecules. In turn, no clear relationship could be observed between molecular size and variability. CONCLUSIONS: This work presented a novel agent-based model to study the effect of the initial concentration of low molecular weight molecules on cellular noise. Cellular noise during molecule diffusion was found to be concentration-dependent and size-independent. The new model holds considerable potential for future, more complex analyses, when emerging experimental data may enable modelling of membrane transport mechanisms.
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Transporte Biológico/fisiologia , Membrana Celular , Parede Celular , Escherichia coli , Modelos Biológicos , Antibacterianos/química , Antibacterianos/metabolismo , Membrana Celular/química , Membrana Celular/metabolismo , Parede Celular/química , Parede Celular/metabolismo , Simulação por Computador , Difusão , Escherichia coli/química , Escherichia coli/citologia , Escherichia coli/metabolismo , Análise de SistemasRESUMO
Experimental incapacity to track microbe-microbe interactions in structures like biofilms, and the complexity inherent to the mathematical modelling of those interactions, raises the need for feasible, alternative modelling approaches. This work proposes an agent-based representation of the diffusion of N-acyl homoserine lactones (AHL) in a multicellular environment formed by Pseudomonas aeruginosa and Candida albicans. Depending on the spatial location, C. albicans cells were variably exposed to AHLs, an observation that might help explain why phenotypic switching of individual cells in biofilms occurred at different time points. The simulation and algebraic results were similar for simpler scenarios, although some statistical differences could be observed (p < 0.05). The model was also successfully applied to a more complex scenario representing a small multicellular environment containing C. albicans and P. aeruginosa cells encased in a 3-D matrix. Further development of this model may help create a predictive tool to depict biofilm heterogeneity at the single-cell level.
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Acil-Butirolactonas/química , Candida albicans/metabolismo , Modelos Teóricos , Pseudomonas aeruginosa/metabolismo , Percepção de Quorum , Biofilmes , Candida albicans/fisiologia , Difusão , Pseudomonas aeruginosa/fisiologiaRESUMO
The complex virulence attributes of Candida albicans are an attractive target to exploit in the development of new antifungals and anti-virulence strategies to combat C. albicans infections. Particularly, quorum sensing (QS) has been reported as critical for virulence regulation in C. albicans. This work presents two knowledge networks with up-to-date information about QS regulation and experimentally tested anti-QS and anti-virulence agents for C. albicans. A semi-automatic bioinformatics workflow that combines literature mining and expert curation was used to retrieve otherwise scattered information from the scientific literature. The network representation offers an innovative and continuously updatable means for the Candida research community to query QS and virulence data systematically and in a user-friendly way. Notably, the reconstructed networks show the complexity of QS regulation and the impact that some molecules have on the inhibition of virulence mechanisms responsible for infection establishment (e.g. hyphal development) and perseverance (e.g. biofilm formation). In the future, the compiled knowledge may be used to build decision-making models that help infer new knowledge of practical significance. The knowledge networks are publicly available at http://pcquorum.org/. This Web platform enables the exploration of fungal virulence cues as well as reported inhibitors in a user-friendly fashion.
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Candida albicans/patogenicidade , Mineração de Dados , Percepção de Quorum , Software , Virulência , Biologia Computacional , InternetRESUMO
Database URL: http://markyt.org.
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Curadoria de Dados/métodos , Mineração de Dados/métodos , Modelos TeóricosRESUMO
Antimicrobial combinations involving antimicrobial peptides (AMPs) attract considerable attention within current antimicrobial and anti-resistance research. The objective of this study was to review the available scientific literature on the effects of antimicrobial combinations involving colistin (polymyxin E), polymyxin B and nisin, which are US Food and Drug Administration (FDA)-approved AMPs broadly tested against prominent multidrug-resistant pathogens. A bioinformatics approach based on literature mining and manual expert curation supported the reconstruction of experimental evidence on the potential of these AMP combinations, as described in the literature. Network analysis enabled further characterisation of the retrieved antimicrobial agents, targets and combinatory effects. This systematic analysis was able to output valuable information on the studies conducted on colistin, polymyxin B and nisin combinations. The reconstructed networks enable the traversal and browsing of a large number of agent combinations, providing comprehensive details on the organisms, modes of growth and methodologies used in the studies. Therefore, network analysis enables a bird's-eye view of current research trends as well as in-depth analysis of specific drugs, organisms and combinatory effects, according to particular user interests. The reconstructed knowledge networks are publicly accessible at http://sing-group.org/antimicrobialCombination/. Hopefully, this resource will help researchers to look into antimicrobial combinations more easily and systematically. User-customised queries may help identify missing and less studied links and to generate new research hypotheses.
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Antibacterianos/uso terapêutico , Colistina/uso terapêutico , Quimioterapia Combinada/métodos , Nisina/uso terapêutico , Polimixina B/uso terapêutico , Animais , Pesquisa Biomédica/métodos , HumanosRESUMO
Quorum sensing plays a pivotal role in Pseudomonas aeruginosa's virulence. This paper reviews experimental results on antimicrobial strategies based on quorum sensing inhibition and discusses current targets in the regulatory network that determines P. aeruginosa biofilm formation and virulence. A bioinformatics framework combining literature mining with information from biomedical ontologies and curated databases was used to create a knowledge network of potential anti-quorum sensing agents for P. aeruginosa. A total of 110 scientific articles, corresponding to 1,004 annotations, were so far included in the network and are analysed in this work. Information on the most studied agents, QS targets and methods is detailed. This knowledge network offers a unique view of existing strategies for quorum sensing inhibition and their main regulatory targets and may be used to readily access otherwise scattered information and to help generate new testable hypotheses. This knowledge network is publicly available at http://pcquorum.org/ .
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Antibacterianos/farmacologia , Biofilmes/efeitos dos fármacos , Biologia Computacional , Pseudomonas aeruginosa/efeitos dos fármacos , Percepção de Quorum/efeitos dos fármacos , Virulência/efeitos dos fármacos , Pseudomonas aeruginosa/metabolismo , Pseudomonas aeruginosa/patogenicidade , Pseudomonas aeruginosa/fisiologia , Fatores de Virulência/metabolismoRESUMO
Considerable research efforts are being invested in the development of novel antimicrobial therapies effective against the growing number of multi-drug resistant pathogens. Notably, the combination of different agents is increasingly explored as means to exploit and improve individual agent actions while minimizing microorganism resistance. Although there are several databases on antimicrobial agents, scientific literature is the primary source of information on experimental antimicrobial combination testing. This work presents a semi-automated database curation workflow that supports the mining of scientific literature and enables the reconstruction of recently documented antimicrobial combinations. Currently, the database contains data on antimicrobial combinations that have been experimentally tested against Pseudomonas aeruginosa, Staphylococcus aureus, Escherichia coli, Listeria monocytogenes and Candida albicans, which are prominent pathogenic organisms and are well-known for their wide and growing resistance to conventional antimicrobials. Researchers are able to explore the experimental results for a single organism or across organisms. Likewise, researchers may look into indirect network associations and identify new potential combinations to be tested. The database is available without charges.Database URL: http://sing.ei.uvigo.es/antimicrobialCombination/.
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Anti-Infecciosos , Peptídeos Catiônicos Antimicrobianos , Curadoria de Dados , Mineração de Dados , Bases de Dados Factuais , Processamento Eletrônico de Dados , Animais , Anti-Infecciosos/química , Peptídeos Catiônicos Antimicrobianos/química , Peptídeos Catiônicos Antimicrobianos/genética , Bactérias/genética , Bactérias/metabolismo , Infecções Bacterianas/tratamento farmacológico , Infecções Bacterianas/genética , Infecções Bacterianas/metabolismo , Candida albicans/genética , Candida albicans/metabolismo , Candidíase/tratamento farmacológico , Candidíase/genética , Candidíase/metabolismo , HumanosRESUMO
Biomedical text mining methods and technologies have improved significantly in the last decade. Considerable efforts have been invested in understanding the main challenges of biomedical literature retrieval and extraction and proposing solutions to problems of practical interest. Most notably, community-oriented initiatives such as the BioCreative challenge have enabled controlled environments for the comparison of automatic systems while pursuing practical biomedical tasks. Under this scenario, the present work describes the Markyt Web-based document curation platform, which has been implemented to support the visualisation, prediction and benchmark of chemical and gene mention annotations at BioCreative/CHEMDNER challenge. Creating this platform is an important step for the systematic and public evaluation of automatic prediction systems and the reusability of the knowledge compiled for the challenge. Markyt was not only critical to support the manual annotation and annotation revision process but also facilitated the comparative visualisation of automated results against the manually generated Gold Standard annotations and comparative assessment of generated results. We expect that future biomedical text mining challenges and the text mining community may benefit from the Markyt platform to better explore and interpret annotations and improve automatic system predictions.Database URL: http://www.markyt.org, https://github.com/sing-group/Markyt.
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Mineração de Dados/métodos , Genes , Processamento de Linguagem Natural , Preparações Farmacêuticas , Software , Animais , HumanosRESUMO
This work presents a molecular-scale agent-based model for the simulation of enzymatic reactions at experimentally measured concentrations. The model incorporates stochasticity and spatial dependence, using diffusing and reacting particles with physical dimensions. We developed strategies to adjust and validate the enzymatic rates and diffusion coefficients to the information required by the computational agents, i.e., collision efficiency, interaction logic between agents, the time scale associated with interactions (e.g., kinetics), and agent velocity. Also, we tested the impact of molecular location (a source of biological noise) in the speed at which the reactions take place. Simulations were conducted for experimental data on the 2-hydroxymuconate tautomerase (EC 5.3.2.6, UniProt ID Q01468) and the Steroid Delta-isomerase (EC 5.3.3.1, UniProt ID P07445). Obtained results demonstrate that our approach is in accordance to existing experimental data and long-term biophysical and biochemical assumptions.
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Simulação de Dinâmica Molecular , Esteroide Isomerases/química , Esteroide Isomerases/metabolismo , Difusão , CinéticaRESUMO
Chemoprevention is the use of natural and/or synthetic substances to block, reverse, or retard the process of carcinogenesis. In this field, the use of antitumor peptides is of interest as, (i) these molecules are small in size, (ii) they show good cell diffusion and permeability, (iii) they affect one or more specific molecular pathways involved in carcinogenesis, and (iv) they are not usually genotoxic. We have checked the Web of Science Database (23/11/2015) in order to collect papers reporting on bioactive peptide (1691 registers), which was further filtered searching terms such as "antiproliferative," "antitumoral," or "apoptosis" among others. Works reporting the amino acid sequence of an antiproliferative peptide were kept (60 registers), and this was complemented with the peptides included in CancerPPD, an extensive resource for antiproliferative peptides and proteins. Peptides were grouped according to one of the following mechanism of action: inhibition of cell migration, inhibition of tumor angiogenesis, antioxidative mechanisms, inhibition of gene transcription/cell proliferation, induction of apoptosis, disorganization of tubulin structure, cytotoxicity, or unknown mechanisms. The main mechanisms of action of those antiproliferative peptides with known amino acid sequences are presented and finally, their potential clinical usefulness and future challenges on their application is discussed.
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Antineoplásicos , Bases de Dados de Proteínas , Neoplasias , Neovascularização Patológica , Peptídeos , Animais , Antineoplásicos/química , Antineoplásicos/uso terapêutico , Movimento Celular/efeitos dos fármacos , Proliferação de Células/efeitos dos fármacos , Humanos , Neoplasias/tratamento farmacológico , Neoplasias/metabolismo , Neovascularização Patológica/tratamento farmacológico , Neovascularização Patológica/metabolismo , Peptídeos/química , Peptídeos/uso terapêuticoRESUMO
Recent computational methodologies, such as individual-based modelling, pave the way to the search for explanatory insight into the collective behaviour of molecules. Many reviews offer an up-to-date perspective about such methodologies, but little is discussed about the practical information requirements involved. The biological information used as input should be easily and routinely determined in the laboratory, publicly available and, preferably, organized in programmatically accessible databases. This review is the first to provide a systematic and comprehensive overview of available resources for the modelling of metabolic events at the molecular scale. The glycolysis pathway of Escherichia coli, which is one of the most studied pathways in Microbiology, serves as case study. This curation addressed structural information about E. coli (i.e. defining the simulation environment), the reactions forming the glycolysis pathway including the enzymes and the metabolites (i.e. the molecules to be represented), the kinetics of each reaction (i.e. behavioural logic of the molecules) and diffusion parameters for all enzymes and metabolites (i.e. molecule movement in the environment). Furthermore, the interpretation of relevant biological features, such as molecular diffusion and enzyme kinetics, and the connection of experimental determination and simulation validation are detailed. Notably, the information from classical theories, such as enzymatic rates and diffusion coefficients, is translated to simulation parameters, such as collision efficiency and particle velocity.
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Modelos Biológicos , Bases de Dados Factuais , Escherichia coli , Cinética , SoftwareRESUMO
Agent-based modelling is being used to represent biological systems with increasing frequency and success. This paper presents the implementation of a new tool for biomolecular reaction modelling in the open source Multiagent Simulator of Neighborhoods framework. The rationale behind this new tool is the necessity to describe interactions at the molecular level to be able to grasp emergent and meaningful biological behaviour. We are particularly interested in characterising and quantifying the various effects that facilitate biocatalysis. Enzymes may display high specificity for their substrates and this information is crucial to the engineering and optimisation of bioprocesses. Simulation results demonstrate that molecule distributions, reaction rate parameters, and structural parameters can be adjusted separately in the simulation allowing a comprehensive study of individual effects in the context of realistic cell environments. While higher percentage of collisions with occurrence of reaction increases the affinity of the enzyme to the substrate, a faster reaction (i.e., turnover number) leads to a smaller number of time steps. Slower diffusion rates and molecular crowding (physical hurdles) decrease the collision rate of reactants, hence reducing the reaction rate, as expected. Also, the random distribution of molecules affects the results significantly.
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Modelos BiológicosRESUMO
BACKGROUND AND OBJECTIVE: Biofilms are receiving increasing attention from the biomedical community. Biofilm-like growth within human body is considered one of the key microbial strategies to augment resistance and persistence during infectious processes. The Biofilms Experiment Workbench is a novel software workbench for the operation and analysis of biofilms experimental data. The goal is to promote the interchange and comparison of data among laboratories, providing systematic, harmonised and large-scale data computation. METHODS: The workbench was developed with AIBench, an open-source Java desktop application framework for scientific software development in the domain of translational biomedicine. Implementation favours free and open-source third-parties, such as the R statistical package, and reaches for the Web services of the BiofOmics database to enable public experiment deposition. RESULTS: First, we summarise the novel, free, open, XML-based interchange format for encoding biofilms experimental data. Then, we describe the execution of common scenarios of operation with the new workbench, such as the creation of new experiments, the importation of data from Excel spreadsheets, the computation of analytical results, the on-demand and highly customised construction of Web publishable reports, and the comparison of results between laboratories. CONCLUSIONS: A considerable and varied amount of biofilms data is being generated, and there is a critical need to develop bioinformatics tools that expedite the interchange and comparison of microbiological and clinical results among laboratories. We propose a simple, open-source software infrastructure which is effective, extensible and easy to understand. The workbench is freely available for non-commercial use at http://sing.ei.uvigo.es/bew under LGPL license.