930 resultados para monitoring user activity


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Various test methods exist for measuring heat of cement hydration; however, most current methods require expensive equipment, complex testing procedures, and/or extensive time, thus not being suitable for field application. The objectives of this research are to identify, develop, and evaluate a standard test procedure for characterization and quality control of pavement concrete mixtures using a calorimetry technique. This research project has three phases. Phase I was designed to identify the user needs, including performance requirements and precision and bias limits, and to synthesize existing test methods for monitoring the heat of hydration, including device types, configurations, test procedures, measurements, advantages, disadvantages, applications, and accuracy. Phase II was designed to conduct experimental work to evaluate the calorimetry equipment recommended from the Phase I study and to develop a standard test procedure for using the equipment and interpreting the test results. Phase II also includes the development of models and computer programs for prediction of concrete pavement performance based on the characteristics of heat evolution curves. Phase III was designed to study for further development of a much simpler, inexpensive calorimeter for field concrete. In this report, the results from the Phase I study are presented, the plan for the Phase II study is described, and the recommendations for Phase III study are outlined. Phase I has been completed through three major activities: (1) collecting input and advice from the members of the project Technical Working Group (TWG), (2) conducting a literature survey, and (3) performing trials at the CP Tech Center’s research lab. The research results indicate that in addition to predicting maturity/strength, concrete heat evolution test results can also be used for (1) forecasting concrete setting time, (2) specifying curing period, (3) estimating risk of thermal cracking, (4) assessing pavement sawing/finishing time, (5) characterizing cement features, (6) identifying incompatibility of cementitious materials, (7) verifying concrete mix proportions, and (8) selecting materials and/or mix designs for given environmental conditions. Besides concrete materials and mix proportions, the configuration of the calorimeter device, sample size, mixing procedure, and testing environment (temperature) also have significant influences on features of concrete heat evolution process. The research team has found that although various calorimeter tests have been conducted for assorted purposes and the potential uses of calorimeter tests are clear, there is no consensus on how to utilize the heat evolution curves to characterize concrete materials and how to effectively relate the characteristics of heat evolution curves to concrete pavement performance. The goal of the Phase II study is to close these gaps.

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Some root-associated pseudomonads sustain plant growth by suppressing root diseases caused by pathogenic fungi. We investigated to which extent select cereal cultivars influence expression of relevant biocontrol traits (i.e., root colonization efficacy and antifungal activity) in Pseudomonas fluorescens CHA0. In this representative plant-beneficial bacterium, the antifungal metabolites 2,4-diacetylphloroglucinol (DAPG), pyrrolnitrin (PRN), pyoluteorin (PLT), and hydrogen cyanide (HCN) are required for biocontrol. To monitor host plant effects on the expression of biosynthetic genes for these compounds on roots, we developed fluorescent dual-color reporters suited for flow cytometric analysis using fluorescence-activated cell sorting (FACS). In the dual-label strains, the constitutively expressed red fluorescent protein mCherry served as a cell tag and marker for root colonization, whereas reporter fusions based on the green fluorescent protein allowed simultaneous recording of antifungal gene expression within the same cell. FACS analysis revealed that expression of DAPG and PRN biosynthetic genes was promoted in a cereal rhizosphere, whereas expression of PLT and HCN biosynthetic genes was markedly less sustained. When analyzing the response of the bacterial reporters on roots of a selection of wheat, spelt, and triticale cultivars, we were able to detect subtle species- and cultivar-dependent differences in colonization and DAPG and HCN gene expression levels. The expression of these biocontrol traits was particularly favored on roots of one spelt cultivar, suggesting that a careful choice of pseudomonad-cereal combinations might be beneficial to biocontrol. Our approach may be useful for selective single-cell level analysis of plant effects in other bacteria-root interactions.

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INTRODUCTION: Continuous EEG (cEEG) is increasingly used to monitor brain function in neuro-ICU patients. However, its value in patients with coma after cardiac arrest (CA), particularly in the setting of therapeutic hypothermia (TH), is only beginning to be elucidated. The aim of this study was to examine whether cEEG performed during TH may predict outcome. METHODS: From April 2009 to April 2010, we prospectively studied 34 consecutive comatose patients treated with TH after CA who were monitored with cEEG, initiated during hypothermia and maintained after rewarming. EEG background reactivity to painful stimulation was tested. We analyzed the association between cEEG findings and neurologic outcome, assessed at 2 months with the Glasgow-Pittsburgh Cerebral Performance Categories (CPC). RESULTS: Continuous EEG recording was started 12 ± 6 hours after CA and lasted 30 ± 11 hours. Nonreactive cEEG background (12 of 15 (75%) among nonsurvivors versus none of 19 (0) survivors; P < 0.001) and prolonged discontinuous "burst-suppression" activity (11 of 15 (73%) versus none of 19; P < 0.001) were significantly associated with mortality. EEG seizures with absent background reactivity also differed significantly (seven of 15 (47%) versus none of 12 (0); P = 0.001). In patients with nonreactive background or seizures/epileptiform discharges on cEEG, no improvement was seen after TH. Nonreactive cEEG background during TH had a positive predictive value of 100% (95% confidence interval (CI), 74 to 100%) and a false-positive rate of 0 (95% CI, 0 to 18%) for mortality. All survivors had cEEG background reactivity, and the majority of them (14 (74%) of 19) had a favorable outcome (CPC 1 or 2). CONCLUSIONS: Continuous EEG monitoring showing a nonreactive or discontinuous background during TH is strongly associated with unfavorable outcome in patients with coma after CA. These data warrant larger studies to confirm the value of continuous EEG monitoring in predicting prognosis after CA and TH.

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Introduction: Continuous EEG (cEEG) is increasingly used to monitor brain function in neuro-ICU patients. However, its value in patients with coma after cardiac arrest (CA), particularly in the setting of therapeutic hypothermia (TH), is only beginning to be elucidated. The aim of this study was to examine whether cEEG performed during TH may predict outcome. Methods: From April 2009 to April 2010, we prospectively studied 34 consecutive comatose patients treated with TH after CA who were monitored with cEEG, initiated during hypothermia and maintained after rewarming. EEG background reactivity to painful stimulation was tested. We analyzed the association between cEEG findings and neurologic outcome, assessed at 2 months with the Glasgow-Pittsburgh Cerebral Performance Categories (CPC). Results: Continuous EEG recording was started 12 ± 6 hours after CA and lasted 30 ± 11 hours. Nonreactive cEEG background (12 of 15 (75%) among nonsurvivors versus none of 19 (0) survivors; P < 0.001) and prolonged discontinuous "burst-suppression" activity (11 of 15 (73%) versus none of 19; P < 0.001) were significantly associated with mortality. EEG seizures with absent background reactivity also differed significantly (seven of 15 (47%) versus none of 12 (0); P = 0.001). In patients with nonreactive background or seizures/epileptiform discharges on cEEG, no improvement was seen after TH. Nonreactive cEEG background during TH had a positive predictive value of 100% (95% confidence interval (CI), 74 to 100%) and a false-positive rate of 0 (95% CI, 0 to 18%) for mortality. All survivors had cEEG background reactivity, and the majority of them (14 (74%) of 19) had a favorable outcome (CPC 1 or 2). Conclusions: Continuous EEG monitoring showing a nonreactive or discontinuous background during TH is strongly associated with unfavorable outcome in patients with coma after CA. These data warrant larger studies to confirm the value of continuous EEG monitoring in predicting prognosis after CA and TH.

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OBJECTIVES: In the absence of a gold standard, the assessment of physical activity in children remains difficult. To record physical activity with a pedometer and to examine to what extent it is correlated with VO2max. METHODS: Survey on physical activity and fitness; 233 Swiss adolescents aged 11 to 15 carried a pedometer (Pedoboy) during seven consecutive days. VO2max was estimated through an endurance shuttle run test. RESULTS: The physical activity recorded by the pedometer did not vary from one day to the other (p > 0.05). The physical activity was higher among boys than among girls (p < 0.001) and higher among younger adolescents (6th versus 8th grade; p < 0.001). The correlation between physical activity and estimated VO2max was 0.30 (p < 0.01). CONCLUSIONS: The use of a pedometer to assess physical activity over one entire week is feasible among adolescents. The record provided by the pedometer gives an objective measure of the usual physical activity and, as such, is relatively well correlated with aerobic capacity.

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Introduction: Therapeutic drug monitoring (TDM) aims at optimizing treatment by individualizing dosage regimen based on measurement of blood concentrations. Maintaining concentrations within a target range requires pharmacokinetic and clinical capabilities. Bayesian calculation represents a gold standard in TDM approach but requires computing assistance. In the last decades computer programs have been developed to assist clinicians in this assignment. The aim of this benchmarking was to assess and compare computer tools designed to support TDM clinical activities.¦Method: Literature and Internet search was performed to identify software. All programs were tested on common personal computer. Each program was scored against a standardized grid covering pharmacokinetic relevance, user-friendliness, computing aspects, interfacing, and storage. A weighting factor was applied to each criterion of the grid to consider its relative importance. To assess the robustness of the software, six representative clinical vignettes were also processed through all of them.¦Results: 12 software tools were identified, tested and ranked. It represents a comprehensive review of the available software's characteristics. Numbers of drugs handled vary widely and 8 programs offer the ability to the user to add its own drug model. 10 computer programs are able to compute Bayesian dosage adaptation based on a blood concentration (a posteriori adjustment) while 9 are also able to suggest a priori dosage regimen (prior to any blood concentration measurement), based on individual patient covariates, such as age, gender, weight. Among those applying Bayesian analysis, one uses the non-parametric approach. The top 2 software emerging from this benchmark are MwPharm and TCIWorks. Other programs evaluated have also a good potential but are less sophisticated (e.g. in terms of storage or report generation) or less user-friendly.¦Conclusion: Whereas 2 integrated programs are at the top of the ranked listed, such complex tools would possibly not fit all institutions, and each software tool must be regarded with respect to individual needs of hospitals or clinicians. Interest in computing tool to support therapeutic monitoring is still growing. Although developers put efforts into it the last years, there is still room for improvement, especially in terms of institutional information system interfacing, user-friendliness, capacity of data storage and report generation.

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Objectives: Therapeutic drug monitoring (TDM) aims at optimizing treatment by individualizing dosage regimen based on blood concentrations measurement. Maintaining concentrations within a target range requires pharmacokinetic (PK) and clinical capabilities. Bayesian calculation represents a gold standard in TDM approach but requires computing assistance. The aim of this benchmarking was to assess and compare computer tools designed to support TDM clinical activities.¦Methods: Literature and Internet were searched to identify software. Each program was scored against a standardized grid covering pharmacokinetic relevance, user-friendliness, computing aspects, interfacing, and storage. A weighting factor was applied to each criterion of the grid to consider its relative importance. To assess the robustness of the software, six representative clinical vignettes were also processed through all of them.¦Results: 12 software tools were identified, tested and ranked. It represents a comprehensive review of the available software characteristics. Numbers of drugs handled vary from 2 to more than 180, and integration of different population types is available for some programs. Nevertheless, 8 programs offer the ability to add new drug models based on population PK data. 10 computer tools incorporate Bayesian computation to predict dosage regimen (individual parameters are calculated based on population PK models). All of them are able to compute Bayesian a posteriori dosage adaptation based on a blood concentration while 9 are also able to suggest a priori dosage regimen, only based on individual patient covariates. Among those applying Bayesian analysis, MM-USC*PACK uses a non-parametric approach. The top 2 programs emerging from this benchmark are MwPharm and TCIWorks. Others programs evaluated have also a good potential but are less sophisticated or less user-friendly.¦Conclusions: Whereas 2 software packages are ranked at the top of the list, such complex tools would possibly not fit all institutions, and each program must be regarded with respect to individual needs of hospitals or clinicians. Programs should be easy and fast for routine activities, including for non-experienced users. Although interest in TDM tools is growing and efforts were put into it in the last years, there is still room for improvement, especially in terms of institutional information system interfacing, user-friendliness, capability of data storage and automated report generation.

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This study aimed to investigate the behaviour of two indicators of influenza activity in the area of Barcelona and to evaluate the usefulness of modelling them to improve the detection of influenza epidemics. DESIGN: Descriptive time series study using the number of deaths due to all causes registered by funeral services and reported cases of influenza-like illness. The study concentrated on five influenza seasons, from week 45 of 1988 to week 44 of 1993. The weekly number of deaths and cases of influenza-like illness registered were processed using identification of a time series ARIMA model. SETTING: Six large towns in the Barcelona province which have more than 60,000 inhabitants and funeral services in all of them. MAIN RESULTS: For mortality, the proposed model was an autoregressive one of order 2 (ARIMA (2,0,0)) and for morbidity it was one of order 3 (ARIMA (3,0,0)). Finally, the two time series were analysed together to facilitate the detection of possible implications between them. The joint study of the two series shows that the mortality series can be modelled separately from the reported morbidity series, but the morbidity series is influenced as much by the number of previous cases of influenza reported as by the previous mortality registered. CONCLUSIONS: The model based on general mortality is useful for detecting epidemic activity of influenza. However, because there is not an absolute gold standard that allows definition of the beginning of the epidemic, the final decision of when it is considered an epidemic and control measures recommended should be taken after evaluating all the indicators included in the influenza surveillance programme.

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This case study deals with a rock face monitoring in urban areas using a Terrestrial Laser Scanner. The pilot study area is an almost vertical, fifty meter high cliff, on top of which the village of Castellfollit de la Roca is located. Rockfall activity is currently causing a retreat of the rock face, which may endanger the houses located at its edge. TLS datasets consist of high density 3-D point clouds acquired from five stations, nine times in a time span of 22 months (from March 2006 to January 2008). The change detection, i.e. rockfalls, was performed through a sequential comparison of datasets. Two types of mass movement were detected in the monitoring period: (a) detachment of single basaltic columns, with magnitudes below 1.5 m3 and (b) detachment of groups of columns, with magnitudes of 1.5 to 150 m3. Furthermore, the historical record revealed (c) the occurrence of slab failures with magnitudes higher than 150 m3. Displacements of a likely slab failure were measured, suggesting an apparent stationary stage. Even failures are clearly episodic, our results, together with the study of the historical record, enabled us to estimate a mean detachment of material from 46 to 91.5 m3 year¿1. The application of TLS considerably improved our understanding of rockfall phenomena in the study area.

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The reliable and objective assessment of chronic disease state has been and still is a very significant challenge in clinical medicine. An essential feature of human behavior related to the health status, the functional capacity, and the quality of life is the physical activity during daily life. A common way to assess physical activity is to measure the quantity of body movement. Since human activity is controlled by various factors both extrinsic and intrinsic to the body, quantitative parameters only provide a partial assessment and do not allow for a clear distinction between normal and abnormal activity. In this paper, we propose a methodology for the analysis of human activity pattern based on the definition of different physical activity time series with the appropriate analysis methods. The temporal pattern of postures, movements, and transitions between postures was quantified using fractal analysis and symbolic dynamics statistics. The derived nonlinear metrics were able to discriminate patterns of daily activity generated from healthy and chronic pain states.

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Tumour immunologists strive to develop efficient tumour vaccination and adoptive transfer therapies that enlarge the pool of tumour-specific and -reactive effector T-cells in vivo. To assess the efficiency of the various strategies, ex vivo assays are needed for the longitudinal monitoring of the patient's specific immune responses providing both quantitative and qualitative data. In particular, since tumour cell cytolysis is the end goal of tumour immunotherapy, routine immune monitoring protocols need to include a read-out for the cytolytic efficiency of Ag-specific cells. We propose to combine current immune monitoring techniques in a highly sensitive and reproducible multi-parametric flow cytometry based cytotoxicity assay that has been optimised to require low numbers of Ag-specific T-cells. The possibility of re-analysing those T-cells that have undergone lytic activity is illustrated by the concomitant detection of CD107a upregulation on the surface of degranulated T-cells. To date, the LiveCount Assay provides the only possibility of assessing the ex vivo cytolytic activity of low-frequency Ag-specific cytotoxic T-lymphocytes from patient material.

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Assessing the total energy expenditure (TEE) and the levels of physical activity in free-living conditions with non-invasive techniques remains a challenge. The purpose of the present study was to investigate the accuracy of a new uniaxial accelerometer for assessing TEE and physical-activity-related energy expenditure (PAEE) over a 24 h period in a respiratory chamber, and to establish activity levels based on the accelerometry ranges corresponding to the operationally defined metabolic equivalent (MET) categories. In study 1, measurement of the 24 h energy expenditure of seventy-nine Japanese subjects (40 (SD 12) years old) was performed in a large respiratory chamber. During the measurements, the subjects wore a uniaxial accelerometer (Lifecorder; Suzuken Co. Ltd, Nagoya, Japan) on their belt. Two moderate walking exercises of 30 min each were performed on a horizontal treadmill. In study 2, ten male subjects walked at six different speeds and ran at three different speeds on a treadmill for 4 min, with the same accelerometer. O2 consumption was measured during the last minute of each stage and was expressed in MET. The measured TEE was 8447 (SD 1337) kJ/d. The accelerometer significantly underestimated TEE and PAEE (91.9 (SD 5.4) and 92.7 (SD 17.8) % chamber value respectively); however, there was a significant correlation between the two values (r 0.928 and 0.564 respectively; P<0.001). There was a strong correlation between the activity levels and the measured MET while walking (r(2) 0.93; P<0.001). Although TEE and PAEE were systematically underestimated during the 24 h period, the accelerometer assessed energy expenditure well during both the exercise period and the non-structured activities. Individual calibration factors may help to improve the accuracy of TEE estimation, but the average calibration factor for the group is probably sufficient for epidemiological research. This method is also important for assessing the diurnal profile of physical activity.

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Human biomonitoring is a widely used method in the assessment of occupational exposure to chemical substances and recommended biological limits are published periodically for interpretation and decision-making. However, it is increasingly recognized that a large variability is associated with biological monitoring, making interpretation less efficient than assumed. In order to improve the applicability of biological monitoring, specific factors responsible for this variability should be identified and their contribution quantified. Among these factors, age and sex are easily identifiable, and present knowledge about pharmaceutical chemicals suggests that they play an important role on the toxicokinetics of occupational chemical agents, and therefore on the biological monitoring results.The aim of the present research project was to assess the influence of age and sex on biological indicators corresponding to organic solvents. This has been done experimentally and by toxicokinetic computer simulation. Another purpose was to explore the effect of selected CYP2E1 polymorphisms on the toxicokinetic profile.Age differences were identified by numerical simulations using a general toxicokinetic model from a previous study which was applied to 14 chemicals, representing 21 specific biological entities, with, among others, toluene, phenol, lead and mercury. These models were runn with the modified parameters, indicating in some cases important differences due to age. The expected changes are mostly of the order of 10-20 %, but differences up to 50 % were observed in some cases. These differences appear to depend on the chemical and on the biological entity considered.Sex differences were quantified by controlled human exposures, which were carried out in a 12 m3 exposure chamber for three organic solvents separately: methyl ethyl ketone, 1-methoxy-2-propanol and 1,1,1-trichloroethane. The human volunteer groups were composed 12 of ten young men and fifteen young women, the latter subdivided into those with and without hormonal contraceptive. They were exposed during six hours at rest and at half of the threshold limit value. The kinetics of the parent compounds (organic volatiles) and their metabolite(s) were followed in blood, urine and expired air over time. Analyses of the solvent and their metabolites were performed by using headspace gas chromatography, CYP2E1 genotypes by using PCR-based RFLP methods. Experimental data were used to calibrate the toxicokinetic models developed for the three solvents. The results obtained for the different biomarkers of exposure mainly showed an effect on the urinary levels of several biomarkers among women due to the use of hormonal contraceptive, with an increase of about 50 % in the metabolism rate. The results also showed a difference due to the genotype CYP2E1*6, when exposed to methyl ethyl ketone, with a tendency to increase CYP2E1 activity when volunteers were carriers of the mutant allele. Simulations showed that it is possible to use simple toxicokinetic tools in order to predict internal exposure when exposed to organic solvents. Our study suggests that not only physiological differences but also exogenous sex hormones could influence CYP2E1 enzyme activity. The variability among the urinary biological indicators levels gives evidence of an interindividual susceptibility, an aspect that should have its place in the approaches for setting limits of occupational exposure.

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BACKGROUND: Measurement of plasma renin activity (PRA) is the gold standard for monitoring mineralocorticoid treatment in humans with primary hypoadrenocorticism (PH). OBJECTIVES: To compare PRA in dogs with newly diagnosed PH, dogs with diseases mimicking PH, and healthy dogs, and evaluate measurement of PRA to monitor therapeutic effects in dogs with PH treated with different mineralocorticoids. ANIMALS: Eleven dogs with newly diagnosed PH (group 1), 10 dogs with diseases mimicking PH (group 2), 21 healthy dogs (group 3), 17 dogs with treated PH (group 4). METHODS: In group 1, PRA was measured before treatment and at different times after initiating treatment. In groups 2 and 3, PRA was measured at initial presentation only. In group 4, no baseline PRA was obtained but PRA was measured once or every 1-6 months during treatment. Mineralocorticoid treatment consisted of fludrocortisone acetate (FC) or desoxycorticosterone pivalate (DOCP). RESULTS: Plasma renin activity before treatment was increased in dogs with PH compared to normal dogs and dogs with diseases mimicking PH with median activity of 27, 0.8, and 1.0 ng/mL/h, respectively. In dogs with PH, PRA decreased and normalized with mineralocorticoid treatment using DOCP but not with FC. In dogs treated with DOCP, PRA was lower than in dogs treated with FC. Plasma sodium concentrations were higher and potassium concentrations were lower with DOCP treatment compared to FC treatment. CONCLUSION AND CLINICAL IMPORTANCE: Plasma renin activity is a reliable tool for monitoring mineralocorticoid treatment. DOCP treatment more effectively suppresses PRA compared to FC in dogs with PH.

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Background: Thus far, the correlation of noninvasive markers with endoscopic activity in ulcerative colitis (UC) according to the modified Baron Index is unknown. We aimed to evaluate the correlation between endoscopic activity and fecal calprotectin (FC), C-reactive protein (CRP), blood leukocytes, and the Lichtiger Index (clinical score). Methods: UC patients undergoing complete colonoscopy were prospectively enrolled and scored clinically and endoscopically in an independent fashion. Fecal and blood samples were analyzed in UC patients and controls. Results: We enrolled 228 UC patients and 52 controls. Endoscopic disease activity correlated best with FC (Spearman's rank correlation coefficient r = 0.821), followed by the Lichtiger Index (r = 0.682), CRP (r = 0.556), and leukocytes (r = 0.401). FC was the only marker discriminating between different grades of endoscopic activity (grade 0, 20}11 mg/g; grade 1, 44}34 mg/g; grade 2, 111}74 mg/g; grade 3, 330}332 mg/g; grade 4, 659}319 mg/g; P = 0.0018 for discriminating grade 0 vs. 1 and P < 0.001 for discriminating all other grades). FC had the highest overall accuracy (91%) to detect endoscopically active disease (modified Baron Index _2), followed by the Lichtiger Index of _4 (77%), CRP larger than 5 mg/L (69%) and blood leukocytosis (58%). Conclusions: FC better correlated with the endoscopic disease activity than clinical activity, CRP, and blood leukocytes. The strong correlation with endoscopic disease activity suggests that FC represents a useful biomarker for noninvasive monitoring of disease activity in UC patients.