996 resultados para Time ranges
Resumo:
Paracoccidioides brasiliensis causes infection through inhalation by the host of airborne propagules from the mycelium phase of the fungus. This fungus reaches the lungs, differentiates into the yeast form and is then disseminated to virtually all parts of the body. Here we review the identification of differentially-expressed genes in host-interaction conditions. These genes were identified by analyzing expressed sequence tags (ESTs) from P. brasiliensis cDNA libraries. The P. brasiliensis was recovered from infected mouse liver as well as from fungal yeast cells incubated in human blood and plasma, mimicking fungal dissemination to organs and tissues and sites of infection with inflammation, respectively. In addition, ESTs from a cDNA library of P. brasiliensis mycelium undergoing the transition to yeast were previously analyzed. Together, these studies reveal significant changes in the expression of a number of genes of potential importance in the host-fungus interaction. In addition, the unique and divergent representation of transcripts when the cDNA libraries are compared suggests differential gene expression in response to specific niches in the host. This analysis of gene expression patterns provides details about host-pathogen interactions and peculiarities of sites within the host.
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Time series regression models are especially suitable in epidemiology for evaluating short-term effects of time-varying exposures on health. The problem is that potential for confounding in time series regression is very high. Thus, it is important that trend and seasonality are properly accounted for. Our paper reviews the statistical models commonly used in time-series regression methods, specially allowing for serial correlation, make them potentially useful for selected epidemiological purposes. In particular, we discuss the use of time-series regression for counts using a wide range Generalised Linear Models as well as Generalised Additive Models. In addition, recently critical points in using statistical software for GAM were stressed, and reanalyses of time series data on air pollution and health were performed in order to update already published. Applications are offered through an example on the relationship between asthma emergency admissions and photochemical air pollutants
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There is little literature about the clinical presentation and time-course of postoperative venous thromboembolism (VTE) in different surgical procedures. RIETE is an ongoing, prospective registry of consecutive patients with objectively confirmed, symptomatic acute VTE. In this analysis, we analysed the baseline characteristics, thromboprophylaxis and therapeutic patterns, time-course, and three-month outcome of all patients with postoperative VTE. As of January 2006, there were 1,602 patients with postoperative VTE in RIETE: 393 (25%) after major orthopaedic surgery (145 elective hip arthroplasty, 126 knee arthroplasty, 122 hip fracture); 207 (13%) after cancer surgery; 1,002 (63%) after other procedures. The percentage of patients presenting with clinically overt pulmonary embolism (PE) (48%, 48%, and 50% respectively), the average time elapsed from surgery to VTE (22 +/- 16, 24 +/- 16, and 21 +/- 15 days, respectively), and the three-month incidence of fatal PE (1.3%, 1.4%, and 0.8%, respectively), fatal bleeding (0.8%, 1.0%, and 0.2%, respectively), or major bleeding (2.3%, 2.9%, and 2.8%, respectively) were similar in the three groups. However, the percentage of patients who had received thromboprophylaxis (96%, 76% and 52%, respectively), the duration of prophylaxis (17 +/- 9.6, 13 +/- 8.9, and 12 +/- 11 days, respectively) and the mean daily doses of low-molecular-weight heparin (4,252 +/- 1,016, 3,260 +/- 1,141, and 3,769 +/- 1,650 IU, respectively), were significantly lower in those undergoing cancer surgery or other procedures. In conclusion, the clinical presentation, time-course, and three-month outcome of VTE was similar among the different subgroups of patients, but the use of prophylaxis in patients undergoing cancer surgery or other procedures was suboptimal.
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Reinforcement learning (RL) is a very suitable technique for robot learning, as it can learn in unknown environments and in real-time computation. The main difficulties in adapting classic RL algorithms to robotic systems are the generalization problem and the correct observation of the Markovian state. This paper attempts to solve the generalization problem by proposing the semi-online neural-Q_learning algorithm (SONQL). The algorithm uses the classic Q_learning technique with two modifications. First, a neural network (NN) approximates the Q_function allowing the use of continuous states and actions. Second, a database of the most representative learning samples accelerates and stabilizes the convergence. The term semi-online is referred to the fact that the algorithm uses the current but also past learning samples. However, the algorithm is able to learn in real-time while the robot is interacting with the environment. The paper shows simulated results with the "mountain-car" benchmark and, also, real results with an underwater robot in a target following behavior
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This paper deals with the problem of navigation for an unmanned underwater vehicle (UUV) through image mosaicking. It represents a first step towards a real-time vision-based navigation system for a small-class low-cost UUV. We propose a navigation system composed by: (i) an image mosaicking module which provides velocity estimates; and (ii) an extended Kalman filter based on the hydrodynamic equation of motion, previously identified for this particular UUV. The obtained system is able to estimate the position and velocity of the robot. Moreover, it is able to deal with visual occlusions that usually appear when the sea bottom does not have enough visual features to solve the correspondence problem in a certain area of the trajectory
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Effective empirical treatment is of paramount importance to improve the outcome of patients with Staphylococcus aureus bacteraemia. We aimed to evaluate a PCR-based rapid diagnosis of methicillin resistance (GeneXpert MRSA) after early detection of S. aureus bacteraemia using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). Patients with a first episode of S. aureus bacteraemia identified using MALDI-TOF MS were randomized in a prospective interventional open study between October 2010 and August 2012. In the control group, antibiotic susceptibility testing was performed after MALDI-TOF MS identification on blood culture pellets. In the intervention group, a GeneXpert MRSA was performed after S. aureus identification. The primary outcome was the performance of GeneXpert MRSA directly on blood cultures. We then assessed the impact of early diagnosis of methicillin resistance on the empirical treatment. In all, 197 episodes of S. aureus bacteraemia were included in the study, of which 106 were included in the intervention group. Median time from MALDI-TOF MS identification to GeneXpert MRSA result was 97 min (range 25-250). Detection of methicillin resistance using GeneXpert MRSA had a sensitivity of 99% and a specificity of 100%. There was less unnecessary coverage of MRSA in the intervention group (17.1% versus 29.2%, p 0.09). GeneXpert MRSA was highly reliable in diagnosing methicillin resistance when performed directly on positive blood cultures. This could help to avoid unnecessary prescriptions of anti-MRSA agents and promote the introduction of earlier adequate coverage in unsuspected cases.
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The automatic interpretation of conventional traffic signs is very complex and time consuming. The paper concerns an automatic warning system for driving assistance. It does not interpret the standard traffic signs on the roadside; the proposal is to incorporate into the existing signs another type of traffic sign whose information will be more easily interpreted by a processor. The type of information to be added is profuse and therefore the most important object is the robustness of the system. The basic proposal of this new philosophy is that the co-pilot system for automatic warning and driving assistance can interpret with greater ease the information contained in the new sign, whilst the human driver only has to interpret the "classic" sign. One of the codings that has been tested with good results and which seems to us easy to implement is that which has a rectangular shape and 4 vertical bars of different colours. The size of these signs is equivalent to the size of the conventional signs (approximately 0.4 m2). The colour information from the sign can be easily interpreted by the proposed processor and the interpretation is much easier and quicker than the information shown by the pictographs of the classic signs
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This article presents a new theory that separates the levels of communication and relates them circularly, namely, by separating time from space/meaning variables. Documenting this proposition requires sequential microdescriptions--a far-out project in the field of family therapy. In an extensive study of clinical and nonclinical families, starting with available microanalytic data on nonverbal parent-infant dialogue, distinct time organizations have been found to modify the degree of circularity between the levels of interaction according to the observed types of engagement, that is, consensual, conflictual, and paradoxical. The double description of the dyad as a totality versus the dyad as a framing/developing organization imparts crucial information on how development proceeds in dyadic, co-evolutive systems, and presumably in larger ones too. In this perspective, a model is elaborated and then applied to a case description in our therapeutic consultation.
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This study examined the validity and reliability of a sequential "Run-Bike-Run" test (RBR) in age-group triathletes. Eight Olympic distance (OD) specialists (age 30.0 ± 2.0 years, mass 75.6 ± 1.6 kg, run VO2max 63.8 ± 1.9 ml· kg(-1)· min(-1), cycle VO2peak 56.7 ± 5.1 ml· kg(-1)· min(-1)) performed four trials over 10 days. Trial 1 (TRVO2max) was an incremental treadmill running test. Trials 2 and 3 (RBR1 and RBR2) involved: 1) a 7-min run at 15 km· h(-1) (R1) plus a 1-min transition to 2) cycling to fatigue (2 W· kg(-1) body mass then 30 W each 3 min); 3) 10-min cycling at 3 W· kg(-1) (Bsubmax); another 1-min transition and 4) a second 7-min run at 15 km· h(-1) (R2). Trial 4 (TT) was a 30-min cycle - 20-min run time trial. No significant differences in absolute oxygen uptake (VO2), heart rate (HR), or blood lactate concentration ([BLA]) were evidenced between RBR1 and RBR2. For all measured physiological variables, the limits of agreement were similar, and the mean differences were physiologically unimportant, between trials. Low levels of test-retest error (i.e. ICC <0.8, CV<10%) were observed for most (logged) measurements. However [BLA] post R1 (ICC 0.87, CV 25.1%), [BLA] post Bsubmax (ICC 0.99, CV 16.31) and [BLA] post R2 (ICC 0.51, CV 22.9%) were least reliable. These error ranges may help coaches detect real changes in training status over time. Moreover, RBR test variables can be used to predict discipline specific and overall TT performance. Cycle VO2peak, cycle peak power output, and the change between R1 and R2 (deltaR1R2) in [BLA] were most highly related to overall TT distance (r = 0.89, p < 0. 01; r = 0.94, p < 0.02; r = 0.86, p < 0.05, respectively). The percentage of TR VO2max at 15 km· h(-1), and deltaR1R2 HR, were also related to run TT distance (r = -0.83 and 0.86, both p < 0.05).
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BACKGROUND We describe the diversity of two kinds of mycobacteria isolates, environmental mycobacteria and Mycobacterium bovis collected from wild boar, fallow deer, red deer and cattle in Doñana National Park (DNP, Spain), analyzing their association with temporal, spatial and environmental factors. RESULTS High diversity of environmental mycobacteria species and M. bovis typing patterns (TPs) were found. When assessing the factors underlying the presence of the most common types of both environmental mycobacteria and M. bovis TPs in DNP, we evidenced (i) host species differences in the occurrence, (ii) spatial structuration and (iii) differences in the degree of spatial association of specific types between host species. Co-infection of a single host by two M. bovis TPs occurred in all three wild ungulate species. In wild boar and red deer, isolation of one group of mycobacteria occurred more frequently in individuals not infected by the other group. While only three TPs were detected in wildlife between 1998 and 2003, up to 8 different ones were found during 2006-2007. The opposite was observed in cattle. Belonging to an M. bovis-infected social group was a significant risk factor for mycobacterial infection in red deer and wild boar, but not for fallow deer. M. bovis TPs were usually found closer to water marshland than MOTT. CONCLUSIONS The diversity of mycobacteria described herein is indicative of multiple introduction events and a complex multi-host and multi-pathogen epidemiology in DNP. Significant changes in the mycobacterial isolate community may have taken place, even in a short time period (1998 to 2007). Aspects of host social organization should be taken into account in wildlife epidemiology. Wildlife in DNP is frequently exposed to different species of non-tuberculous, environmental mycobacteria, which could interact with the immune response to pathogenic mycobacteria, although the effects are unknown. This research highlights the suitability of molecular typing for surveys at small spatial and temporal scales.
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Niche conservatism, the tendency of a species niche to remain unchanged over time, is often assumed when discussing, explaining or predicting biogeographical patterns. Unfortunately, there has been no basis for predicting niche dynamics over relevant timescales, from tens to a few hundreds of years. The recent application of species distribution models (SDMs) and phylogenetic methods to analysis of niche characteristics has provided insight to niche dynamics. Niche shifts and conservatism have both occurred within the last 100 years, with recent speciation events, and deep within clades of species. There is increasing evidence that coordinated application of these methods can help to identify species which likely fulfill one key assumption in the predictive application of SDMs: an unchanging niche. This will improve confidence in SDM-based predictions of the impacts of climate change and species invasions on species distributions and biodiversity.
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A compositional time series is obtained when a compositional data vector is observed atdifferent points in time. Inherently, then, a compositional time series is a multivariatetime series with important constraints on the variables observed at any instance in time.Although this type of data frequently occurs in situations of real practical interest, atrawl through the statistical literature reveals that research in the field is very much in itsinfancy and that many theoretical and empirical issues still remain to be addressed. Anyappropriate statistical methodology for the analysis of compositional time series musttake into account the constraints which are not allowed for by the usual statisticaltechniques available for analysing multivariate time series. One general approach toanalyzing compositional time series consists in the application of an initial transform tobreak the positive and unit sum constraints, followed by the analysis of the transformedtime series using multivariate ARIMA models. In this paper we discuss the use of theadditive log-ratio, centred log-ratio and isometric log-ratio transforms. We also presentresults from an empirical study designed to explore how the selection of the initialtransform affects subsequent multivariate ARIMA modelling as well as the quality ofthe forecasts
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PURPOSE: All kinds of blood manipulations aim to increase the total hemoglobin mass (tHb-mass). To establish tHb-mass as an effective screening parameter for detecting blood doping, the knowledge of its normal variation over time is necessary. The aim of the present study, therefore, was to determine the intraindividual variance of tHb-mass in elite athletes during a training year emphasizing off, training, and race seasons at sea level. METHODS: tHb-mass and hemoglobin concentration ([Hb]) were determined in 24 endurance athletes five times during a year and were compared with a control group (n = 6). An analysis of covariance was used to test the effects of training phases, age, gender, competition level, body mass, and training volume. Three error models, based on 1) a total percentage error of measurement, 2) the combination of a typical percentage error (TE) of analytical origin with an absolute SD of biological origin, and 3) between-subject and within-subject variance components as obtained by an analysis of variance, were tested. RESULTS: In addition to the expected influence of performance status, the main results were that the effects of training volume (P = 0.20) and training phases (P = 0.81) on tHb-mass were not significant. We found that within-subject variations mainly have an analytical origin (TE approximately 1.4%) and a very small SD (7.5 g) of biological origin. CONCLUSION: tHb-mass shows very low individual oscillations during a training year (<6%), and these oscillations are below the expected changes in tHb-mass due to Herythropoetin (EPO) application or blood infusion (approximately 10%). The high stability of tHb-mass over a period of 1 year suggests that it should be included in an athlete's biological passport and analyzed by recently developed probabilistic inference techniques that define subject-based reference ranges.
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The composition of the labour force is an important economic factor for a country.Often the changes in proportions of different groups are of interest.I this paper we study a monthly compositional time series from the Swedish LabourForce Survey from 1994 to 2005. Three models are studied: the ILR-transformed series,the ILR-transformation of the compositional differenced series of order 1, and the ILRtransformationof the compositional differenced series of order 12. For each of thethree models a VAR-model is fitted based on the data 1994-2003. We predict the timeseries 15 steps ahead and calculate 95 % prediction regions. The predictions of thethree models are compared with actual values using MAD and MSE and the predictionregions are compared graphically in a ternary time series plot.We conclude that the first, and simplest, model possesses the best predictive power ofthe three models