2,506 research outputs found
A novel strategy to incorporate coconut oil in dairy matrices
info:eu-repo/semantics/publishedVersio
Characterization of two Achromobacter xylosoxidans isolates from patients with pertussis-like symptoms
[email protected]: To characterize two Achromobacter xylosoxidans recovered from 2 patients diagnosed with pertussis during a Bordetella pertussis surveillance program. Methods: Nasopharyngeal swabs from 2 children under 1 year of age with clinical suspicion of pertussis were analyzed by culture and PCR. Results: Two Achromobacter xylosoxidans A8, closely related to Bordetella spp. were recovered from 2 patients diagnosed of pertussis, both carrying the ptxA gene and IS418 the pertussis toxin encoding gene. Subsequently, antibiotic susceptibility was evaluated by disk-diffusion method and by PCR. Conclusions: Although more detailed studies are needed, the present data highlight the possibility that Achromobacter xylosoxidans, closely related Bordetella pertussis microorganisms and not covered under the vaccine umbrella, might also result in cases of whooping cough. Thereby further surveillance is necessary to determine the extension and relevance of their pathogenic role in order to discriminate their real public health implication.This work has been supported by Sanofi Aventis del Peru.
JR has a fellowship from the program I3, of the ISCIII (grant number: CES11/012),
CG has a PhD fellowship of the ISCIII (FI12/00561). MJP has a fellowship from
CONCYTEC/FONDECYT.RevisiĂłn por pare
PercepçÔes sobre a saĂșde dos homens numa perspectiva relacional de gĂȘnero, Brasil, 2014
The actin-myosin regulatory MRCK kinases: regulation, biological functions and associations with human cancer
The contractile actin-myosin cytoskeleton provides much of the force required for numerous cellular activities such as motility, adhesion, cytokinesis and changes in morphology. Key elements that respond to various signal pathways are the myosin II regulatory light chains (MLC), which participate in actin-myosin contraction by modulating the ATPase activity and consequent contractile force generation mediated by myosin heavy chain heads. Considerable effort has focussed on the role of MLC kinases, and yet the contributions of the myotonic dystrophy-related Cdc42-binding kinases (MRCK) proteins in MLC phosphorylation and cytoskeleton regulation have not been well characterized. In contrast to the closely related ROCK1 and ROCK2 kinases that are regulated by the RhoA and RhoC GTPases, there is relatively little information about the CDC42-regulated MRCKα, MRCKÎČ and MRCKÎł members of the AGC (PKA, PKG and PKC) kinase family. As well as differences in upstream activation pathways, MRCK and ROCK kinases apparently differ in the way that they spatially regulate MLC phosphorylation, which ultimately affects their influence on the organization and dynamics of the actin-myosin cytoskeleton. In this review, we will summarize the MRCK protein structures, expression patterns, small molecule inhibitors, biological functions and associations with human diseases such as cancer
Covid-19 Dynamic Monitoring and Real-Time Spatio-Temporal Forecasting
Background: Periodically, humanity is often faced with new and emerging viruses that can be a significant global threat. It has already been over a century postâthe Spanish Flu pandemic, and we are witnessing a new type of coronavirus, the SARS-CoV-2, which is responsible for Covid-19. It emerged from the city of Wuhan (China) in December 2019, and within a few months, the virus propagated itself globally now resulting more than 50 million cases with over 1 million deaths. The high infection rates coupled with dynamic population movement demands for tools, especially within a Brazilian context, that will support health managers to develop policies for controlling and combating the new virus. /
Methods: In this work, we propose a tool for real-time spatio-temporal analysis using a machine learning approach. The COVID-SGIS system brings together routinely collected health data on Covid-19 distributed across public health systems in Brazil, as well as taking to under consideration the geographic and time-dependent features of Covid-19 so as to make spatio-temporal predictions. The data are sub-divided by federative unit and municipality. In our case study, we made spatio-temporal predictions of the distribution of cases and deaths in Brazil and in each federative unit. Four regression methods were investigated: linear regression, support vector machines (polynomial kernels and RBF), multilayer perceptrons, and random forests. We use the percentage RMSE and the correlation coefficient as quality metrics. /
Results: For qualitative evaluation, we made spatio-temporal predictions for the period from 25 to 27 May 2020. Considering qualitatively and quantitatively the case of the State of Pernambuco and Brazil as a whole, linear regression presented the best prediction results (thematic maps with good data distribution, correlation coefficient >0.99 and RMSE (%) <4% for Pernambuco and around 5% for Brazil) with low training time: [0.00; 0.04 ms], CI 95%. /
Conclusion: Spatio-temporal analysis provided a broader assessment of those in the regions where the accumulated confirmed cases of Covid-19 were concentrated. It was possible to differentiate in the thematic maps the regions with the highest concentration of cases from the regions with low concentration and regions in the transition range. This approach is fundamental to support health managers and epidemiologists to elaborate policies and plans to control the Covid-19 pandemics
COVID-SGIS: A Smart Tool for Dynamic Monitoring and Temporal Forecasting of Covid-19
Background: The global burden of the new coronavirus SARS-CoV-2 is increasing at an unprecedented rate. The current spread of Covid-19 in Brazil is problematic causing a huge public health burden to its population and national health-care service. To evaluate strategies for alleviating such problems, it is necessary to forecast the number of cases and deaths in order to aid the stakeholders in the process of making decisions against the disease. We propose a novel system for real-time forecast of the cumulative cases of Covid-19 in Brazil. /
Methods: We developed the novel COVID-SGIS application for the real-time surveillance, forecast and spatial visualization of Covid-19 for Brazil. This system captures routinely reported Covid-19 information from 27 federative units from the Brazil.io database. It utilizes all Covid-19 confirmed case data that have been notified through the National Notification System, from March to May 2020. Time series ARIMA models were integrated for the forecast of cumulative number of Covid-19 cases and deaths. These include 6-days forecasts as graphical outputs for each federative unit in Brazil, separately, with its corresponding 95% CI for statistical significance. In addition, a worst and best scenarios are presented. /
Results: The following federative units (out of 27) were flagged by our ARIMA models showing statistically significant increasing temporal patterns of Covid-19 cases during the specified day-to-day period: Bahia, MaranhĂŁo, PiauĂ, Rio Grande do Norte, AmapĂĄ, RondĂŽnia, where their day-to-day forecasts were within the 95% CI limits. Equally, the same findings were observed for EspĂrito Santo, Minas Gerais, ParanĂĄ, and Santa Catarina. The overall percentage error between the forecasted values and the actual values varied between 2.56 and 6.50%. For the days when the forecasts fell outside the forecast interval, the percentage errors in relation to the worst case scenario were below 5%. /
Conclusion: The proposed method for dynamic forecasting may be used to guide social policies and plan direct interventions in a cost-effective, concise, and robust manner. This novel tools can play an important role for guiding the course of action against the Covid-19 pandemic for Brazil and country neighbors in South America
Predictors of HBeAg status and hepatitis B viraemia in HIV-infected patients with chronic hepatitis B in the HAART era in Brazil
<p>Abstract</p> <p>Background</p> <p>HBV-HIV co-infection is associated with an increased liver-related morbidity and mortality. However, little is known about the natural history of chronic hepatitis B in HIV-infected individuals under highly active antiretroviral therapy (HAART) receiving at least one of the two drugs that also affect HBV (TDF and LAM). Information about HBeAg status and HBV viremia in HIV/HBV co-infected patients is scarce. The objective of this study was to search for clinical and virological variables associated with HBeAg status and HBV viremia in patients of an HIV/HBV co-infected cohort.</p> <p>Methods</p> <p>A retrospective cross-sectional study was performed, of HBsAg-positive HIV-infected patients in treatment between 1994 and 2007 in two AIDS outpatient clinics located in the SĂŁo Paulo metropolitan area, Brazil. The baseline data were age, sex, CD4 T+ cell count, ALT level, HIV and HBV viral load, HBV genotype, and duration of antiretroviral use. The variables associated to HBeAg status and HBV viremia were assessed using logistic regression.</p> <p>Results</p> <p>A total of 86 HBsAg patients were included in the study. Of these, 48 (56%) were using combination therapy that included lamivudine (LAM) and tenofovir (TDF), 31 (36%) were using LAM monotherapy, and 7 patients had no previous use of either one. Duration of use of TDF and LAM varied from 4 to 21 and 7 to 144 months, respectively. A total of 42 (48. 9%) patients were HBeAg positive and 44 (51. 1%) were HBeAg negative. The multivariate analysis revealed that the use of TDF for longer than 12 months was associated with undetectable HBV DNA viral load (serum HBV DNA level < 60 UI/ml) (<it>p </it>= 0. 047). HBeAg positivity was associated with HBV DNA > 60 UI/ml (p = 0. 001) and ALT levels above normality (<it>p </it>= 0. 038).</p> <p>Conclusion</p> <p>Prolonged use of TDF containing HAART is associated with undetectable HBV DNA viral load. HBeAg positivity is associated with HBV viremia and increased ALT levels.</p
Artificial graphene as a tunable Dirac material
Artificial honeycomb lattices offer a tunable platform to study massless
Dirac quasiparticles and their topological and correlated phases. Here we
review recent progress in the design and fabrication of such synthetic
structures focusing on nanopatterning of two-dimensional electron gases in
semiconductors, molecule-by-molecule assembly by scanning probe methods, and
optical trapping of ultracold atoms in crystals of light. We also discuss
photonic crystals with Dirac cone dispersion and topologically protected edge
states. We emphasize how the interplay between single-particle band structure
engineering and cooperative effects leads to spectacular manifestations in
tunneling and optical spectroscopies.Comment: Review article, 14 pages, 5 figures, 112 Reference
- âŠ