78 research outputs found

    Characterization of a recent malaria outbreak in the autonomous indigenous region of Guna Yala, Panama

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    BackgroundThis study aims to describe the epidemiological and entomological factors associated with a recent malaria outbreak that occurred in 2012 in a socially marginalized population from Guna Yala Comarca in Panama.MethodsA descriptive and observational study was conducted by analysing demographic and epidemiological data from all malaria cases registered during 2012 in the Comarca Guna Yala, Panama. Malaria intensity indicators were calculated during the study period. Entomological evaluations were performed monthly, from October to December 2012, in the three communities that presented the most intense malaria transmission during the first semester of 2012. Anopheles breeding habitats were also characterized.ResultsDuring the studied period, 6754 blood smears were examined (17.8 % of the total population), and 143 were confirmed as positive for Plasmodium vivax. A significant increase of malaria transmission risk indicators (API: 3.8/1000, SPR: 2.1 %) was observed in Guna Yula, when compared with previous years, and also in comparison with estimates from the whole country. Anopheles albimanus was the most abundant and widespread (877; 72.0 %) vector species found in the three localities, followed by Anopheles punctimacula (231; 19.0 %) and Anopheles aquasalis (110; 9.0 %). Three An. albimanus pools were positive for P. vivax, showing an overall pooled prevalence estimate of 0.014.ConclusionsData analysis confirmed that during 2012 a malaria epidemic occurred in Guna Yala. Panama. This study provides baseline data on the local epidemiology of malaria in this vulnerable region of Panama. This information will be useful for targeting control strategies by the National Malaria Control Programme

    Critical Dynamics in Genetic Regulatory Networks: Examples from Four Kingdoms

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    The coordinated expression of the different genes in an organism is essential to sustain functionality under the random external perturbations to which the organism might be subjected. To cope with such external variability, the global dynamics of the genetic network must possess two central properties. (a) It must be robust enough as to guarantee stability under a broad range of external conditions, and (b) it must be flexible enough to recognize and integrate specific external signals that may help the organism to change and adapt to different environments. This compromise between robustness and adaptability has been observed in dynamical systems operating at the brink of a phase transition between order and chaos. Such systems are termed critical. Thus, criticality, a precise, measurable, and well characterized property of dynamical systems, makes it possible for robustness and adaptability to coexist in living organisms. In this work we investigate the dynamical properties of the gene transcription networks reported for S. cerevisiae, E. coli, and B. subtilis, as well as the network of segment polarity genes of D. melanogaster, and the network of flower development of A. thaliana. We use hundreds of microarray experiments to infer the nature of the regulatory interactions among genes, and implement these data into the Boolean models of the genetic networks. Our results show that, to the best of the current experimental data available, the five networks under study indeed operate close to criticality. The generality of this result suggests that criticality at the genetic level might constitute a fundamental evolutionary mechanism that generates the great diversity of dynamically robust living forms that we observe around us

    Nutritional Systems Biology Modeling: From Molecular Mechanisms to Physiology

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    The use of computational modeling and simulation has increased in many biological fields, but despite their potential these techniques are only marginally applied in nutritional sciences. Nevertheless, recent applications of modeling have been instrumental in answering important nutritional questions from the cellular up to the physiological levels. Capturing the complexity of today's important nutritional research questions poses a challenge for modeling to become truly integrative in the consideration and interpretation of experimental data at widely differing scales of space and time. In this review, we discuss a selection of available modeling approaches and applications relevant for nutrition. We then put these models into perspective by categorizing them according to their space and time domain. Through this categorization process, we identified a dearth of models that consider processes occurring between the microscopic and macroscopic scale. We propose a “middle-out” strategy to develop the required full-scale, multilevel computational models. Exhaustive and accurate phenotyping, the use of the virtual patient concept, and the development of biomarkers from “-omics” signatures are identified as key elements of a successful systems biology modeling approach in nutrition research—one that integrates physiological mechanisms and data at multiple space and time scales

    ERBB2 in Cat Mammary Neoplasias Disclosed a Positive Correlation between RNA and Protein Low Expression Levels: A Model for erbB-2 Negative Human Breast Cancer

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    Human ERBB2 is a proto-oncogene that codes for the erbB-2 epithelial growth factor receptor. In human breast cancer (HBC), erbB-2 protein overexpression has been repeatedly correlated with poor prognosis. In more recent works, underexpression of this gene has been described in HBC. Moreover, it is also recognised that oncogenes that are commonly amplified or deleted encompass point mutations, and some of these are associated with HBC. In cat mammary lesions (CMLs), the overexpression of ERBB2 (27%–59.6%) has also been described, mostly at the protein level and although cat mammary neoplasias are considered to be a natural model of HBC, molecular information is still scarce. In the present work, a cat ERBB2 fragment, comprising exons 10 to 15 (ERBB2_10–15) was achieved for the first time. Allelic variants and genomic haplotype analyses were also performed, and differences between normal and CML populations were observed. Three amino acid changes, corresponding to 3 non-synonymous genomic sequence variants that were only detected in CMLs, were proposed to damage the 3D structure of the protein. We analysed the cat ERBB2 gene at the DNA (copy number determination), mRNA (expression levels assessment) and protein levels (in extra- and intra protein domains) in CML samples and correlated the last two evaluations with clinicopathological features. We found a positive correlation between the expression levels of the ERBB2 RNA and erbB-2 protein, corresponding to the intracellular region. Additionally, we detected a positive correlation between higher mRNA expression and better clinical outcome. Our results suggest that the ERBB2 gene is post-transcriptionally regulated and that proteins with truncations and single point mutations are present in cat mammary neoplastic lesions. We would like to emphasise that the recurrent occurrence of low erbB-2 expression levels in cat mammary tumours, suggests the cat mammary neoplasias as a valuable model for erbB-2 negative HBC.POCI/CVT/62940/2004 and by the PhD grants (SFRH/BD/23406/2005 and SFRH/BD/31754/2006, of the Science and Technology Foundation (FCT) from Portugal

    Multi-messenger observations of a binary neutron star merger

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    On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta
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