521 research outputs found

    Potential impact of a maternal vaccine for RSV: a mathematical modelling study

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    Respiratory syncytial virus (RSV) is a major cause of respiratory morbidity and one of the main causes of hospitalisation in young children. While there is currently no licensed vaccine for RSV, a vaccine candidate for pregnant women is undergoing phase 3 trials. We developed a compartmental age-structured model for RSV transmission, validated using linked laboratory-confirmed RSV hospitalisation records for metropolitan Western Australia. We adapted the model to incorporate a maternal RSV vaccine, and estimated the expected reduction in RSV hospitalisations arising from such a program. The introduction of a vaccine was estimated to reduce RSV hospitalisations in Western Australia by 6-37% for 0-2month old children, and 30-46% for 3-5month old children, for a range of vaccine effectiveness levels. Our model shows that, provided a vaccine is demonstrated to extend protection against RSV disease beyond the first three months of life, a policy using a maternal RSV vaccine could be effective in reducing RSV hospitalisations in children up to six months of age, meeting the objective of a maternal vaccine in delaying an infant's first RSV infection to an age at which severe disease is less likely

    A Comparison of Initial Antiretroviral Therapy in the Swiss HIV Cohort Study and the Recommendations of the International AIDS Society-USA

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    BACKGROUND: In order to facilitate and improve the use of antiretroviral therapy (ART), international recommendations are released and updated regularly. We aimed to study if adherence to the recommendations is associated with better treatment outcomes in the Swiss HIV Cohort Study (SHCS). METHODS: Initial ART regimens prescribed to participants between 1998 and 2007 were classified according to IAS-USA recommendations. Baseline characteristics of patients who received regimens in violation with these recommendations (violation ART) were compared to other patients. Multivariable logistic and linear regression analyses were performed to identify associations between violation ART and (i) virological suppression and (ii) CD4 cell count increase, after one year. RESULTS: Between 1998 and 2007, 4189 SHCS participants started 241 different ART regimens. A violation ART was started in 5% of patients. Female patients (adjusted odds ratio aOR 1.83, 95%CI 1.28-2.62), those with a high education level (aOR 1.49, 95%CI 1.07-2.06) or a high CD4 count (aOR 1.53, 95%CI 1.02-2.30) were more likely to receive violation ART. The proportion of patients with an undetectable viral load (<400 copies/mL) after one year was significantly lower with violation ART than with recommended regimens (aOR 0.54, 95% CI 0.37-0.80) whereas CD4 count increase after one year of treatment was similar in both groups. CONCLUSIONS: Although more than 240 different initial regimens were prescribed, violations of the IAS-USA recommendations were uncommon. Patients receiving these regimens were less likely to have an undetectable viral load after one year, which strengthens the validity of these recommendations

    Evaluation of Xpert® MTB/RIF and ustar easyNAT™ TB IAD for diagnosis of tuberculous lymphadenitis of children in Tanzania : a prospective descriptive study

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    Fine needle aspiration biopsy has become a standard approach for diagnosis of peripheral tuberculous lymphadenitis. The aim of this study was to compare the performance of Xpert MTB/RIF and Ustar EasyNAT TB IAD nucleic acid amplification assays, against acid-fast bacilli microscopy, cytology and mycobacterial culture for the diagnosis of TB lymphadenitis in children from a TB-endemic setting in Tanzania.; Children of 8 weeks to 16 years of age, suspected of having TB lymphadenitis, were recruited at a district hospital in Tanzania. Fine needle aspirates of lymph nodes were analysed using acid-fast bacilli microscopy, liquid TB culture, cytology, Xpert MTB/RIF and EasyNAT. Latent class analysis and comparison against a composite reference standard comprising "culture and/or cytology" was done, to assess the performance of Xpert MTB/RIF and EasyNAT for the diagnosis of TB lymphadenitis.; Seventy-nine children were recruited; 4 were excluded from analysis. Against a composite reference standard of culture and/or cytology, Xpert MTB/RIF and EasyNAT had a sensitivity and specificity of 58 % and 93 %; and 19 % and 100 % respectively. Relative to latent class definitions, cytology had a sensitivity of 100 % and specificity of 94.7 %.; Combining clinical assessment, cytology and Xpert MTB/RIF may allow for a rapid and accurate diagnosis of childhood TB lymphadenitis. Larger diagnostic evaluation studies are recommended to validate these findings and on Xpert MTB/RIF to assess its use as a solitary initial test for TB lymphadenitis in children

    A self-organized model for cell-differentiation based on variations of molecular decay rates

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    Systemic properties of living cells are the result of molecular dynamics governed by so-called genetic regulatory networks (GRN). These networks capture all possible features of cells and are responsible for the immense levels of adaptation characteristic to living systems. At any point in time only small subsets of these networks are active. Any active subset of the GRN leads to the expression of particular sets of molecules (expression modes). The subsets of active networks change over time, leading to the observed complex dynamics of expression patterns. Understanding of this dynamics becomes increasingly important in systems biology and medicine. While the importance of transcription rates and catalytic interactions has been widely recognized in modeling genetic regulatory systems, the understanding of the role of degradation of biochemical agents (mRNA, protein) in regulatory dynamics remains limited. Recent experimental data suggests that there exists a functional relation between mRNA and protein decay rates and expression modes. In this paper we propose a model for the dynamics of successions of sequences of active subnetworks of the GRN. The model is able to reproduce key characteristics of molecular dynamics, including homeostasis, multi-stability, periodic dynamics, alternating activity, differentiability, and self-organized critical dynamics. Moreover the model allows to naturally understand the mechanism behind the relation between decay rates and expression modes. The model explains recent experimental observations that decay-rates (or turnovers) vary between differentiated tissue-classes at a general systemic level and highlights the role of intracellular decay rate control mechanisms in cell differentiation.Comment: 16 pages, 5 figure

    Network model of immune responses reveals key effectors to single and co-infection dynamics by a respiratory bacterium and a gastrointestinal helminth

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    Co-infections alter the host immune response but how the systemic and local processes at the site of infection interact is still unclear. The majority of studies on co-infections concentrate on one of the infecting species, an immune function or group of cells and often focus on the initial phase of the infection. Here, we used a combination of experiments and mathematical modelling to investigate the network of immune responses against single and co-infections with the respiratory bacterium Bordetella bronchiseptica and the gastrointestinal helminth Trichostrongylus retortaeformis. Our goal was to identify representative mediators and functions that could capture the essence of the host immune response as a whole, and to assess how their relative contribution dynamically changed over time and between single and co-infected individuals. Network-based discrete dynamic models of single infections were built using current knowledge of bacterial and helminth immunology; the two single infection models were combined into a co-infection model that was then verified by our empirical findings. Simulations showed that a T helper cell mediated antibody and neutrophil response led to phagocytosis and clearance of B. bronchiseptica from the lungs. This was consistent in single and co-infection with no significant delay induced by the helminth. In contrast, T. retortaeformis intensity decreased faster when co-infected with the bacterium. Simulations suggested that the robust recruitment of neutrophils in the co-infection, added to the activation of IgG and eosinophil driven reduction of larvae, which also played an important role in single infection, contributed to this fast clearance. Perturbation analysis of the models, through the knockout of individual nodes (immune cells), identified the cells critical to parasite persistence and clearance both in single and co-infections. Our integrated approach captured the within-host immuno-dynamics of bacteria-helminth infection and identified key components that can be crucial for explaining individual variability between single and co-infections in natural populations

    Picosecond Transient Thermoreflectance: Time-Resolved Studies of Thin Film Thermal Transport

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    The advent of new and sophisticated material growth processes (molecular beam epitaxy, chemical vapor deposition and ion sputter deposition) has produced new exotic materials such as amorphous alloys and compositionally modulated structures [1]. The atomic level structure of these materials can be proved by techniques such as x-ray diffraction. The electrical and thermal transport properties are also used to characterize these materials, which are usually deposited as thin films onto supporting substrates. Although the substrate may be electrically isolated from the film, complete thermal isolation is more difficult to achieve and thermal transport measurements are complicated.</p

    Global and decomposition evolutionary support vector machine approaches for time series forecasting

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    Multi-step ahead Time Series Forecasting (TSF) is a key tool for support- ing tactical decisions (e.g., planning resources). Recently, the support vector machine emerged as a natural solution for TSF due to its nonlinear learning capabilities. This paper presents two novel Evolutionary Support Vector Machine (ESVM) methods for multi-step TSF. Both methods are based on an Estimation Distribution Algorithm (EDA) search engine that automatically performs a simultaneous variable (number of inputs) and model (hyperparameters) selection. The Global ESVM (GESVM) uses all past patterns to fit the support vector machine, while the Decomposition ESVM (DESVM) separates the series into trended and stationary effects, using a distinct ESVM to forecast each effect and then summing both predictions into a sin- gle response. Several experiments were held, using six time series. The proposed approaches were analyzed under two criteria and compared against a recent Evolu- tionary Artificial Neural Network (EANN) and two classical forecasting methods, Holt-Winters and ARIMA. Overall, the DESVM and GESVM obtained competitive and high quality results. Furthermore, both ESVM approaches consume much less computational effort when compared with EANN.The authors wish to thank Ramon Sagarna for introducing the subject of EDA. The work of P. Cortez was supported by FEDER (program COMPETE and FCT) under project FCOMP-01-0124-FEDER-022674

    A meta-analysis of long-term effects of conservation agriculture on maize grain yield under rain-fed conditions

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    Conservation agriculture involves reduced tillage, permanent soil cover and crop rotations to enhance soil fertility and to supply food from a dwindling land resource. Recently, conservation agriculture has been promoted in Southern Africa, mainly for maize-based farming systems. However, maize yields under rain-fed conditions are often variable. There is therefore a need to identify factors that influence crop yield under conservation agriculture and rain-fed conditions. Here, we studied maize grain yield data from experiments lasting 5 years and more under rain-fed conditions. We assessed the effect of long-term tillage and residue retention on maize grain yield under contrasting soil textures, nitrogen input and climate. Yield variability was measured by stability analysis. Our results show an increase in maize yield over time with conservation agriculture practices that include rotation and high input use in low rainfall areas. But we observed no difference in system stability under those conditions. We observed a strong relationship between maize grain yield and annual rainfall. Our meta-analysis gave the following findings: (1) 92% of the data show that mulch cover in high rainfall areas leads to lower yields due to waterlogging; (2) 85% of data show that soil texture is important in the temporal development of conservation agriculture effects, improved yields are likely on well-drained soils; (3) 73% of the data show that conservation agriculture practices require high inputs especially N for improved yield; (4) 63% of data show that increased yields are obtained with rotation but calculations often do not include the variations in rainfall within and between seasons; (5) 56% of the data show that reduced tillage with no mulch cover leads to lower yields in semi-arid areas; and (6) when adequate fertiliser is available, rainfall is the most important determinant of yield in southern Africa. It is clear from our results that conservation agriculture needs to be targeted and adapted to specific biophysical conditions for improved impact

    Inhomogeneous Point-Processes to Instantaneously Assess Affective Haptic Perception through Heartbeat Dynamics Information

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    This study proposes the application of a comprehensive signal processing framework, based on inhomogeneous point-process models of heartbeat dynamics, to instantaneously assess affective haptic perception using electrocardiogram-derived information exclusively. The framework relies on inverse-Gaussian point-processes with Laguerre expansion of the nonlinear Wiener-Volterra kernels, accounting for the long-term information given by the past heartbeat events. Up to cubic-order nonlinearities allow for an instantaneous estimation of the dynamic spectrum and bispectrum of the considered cardiovascular dynamics, as well as for instantaneous measures of complexity, through Lyapunov exponents and entropy. Short-term caress-like stimuli were administered for 4.3?25?seconds on the forearms of 32 healthy volunteers (16 females) through a wearable haptic device, by selectively superimposing two levels of force, 2?N and 6?N, and two levels of velocity, 9.4?mm/s and 65?mm/s. Results demonstrated that our instantaneous linear and nonlinear features were able to finely characterize the affective haptic perception, with a recognition accuracy of 69.79% along the force dimension, and 81.25% along the velocity dimension
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