Theoretical Hyperbolic Model of a Partial Agonism: Explicit Formulas for Affinity, Efficacy and Amplification

The quantitative analysis of receptor-mediated effect is based on experimental concentration-response data in which the independent variable, the concentration of a receptor ligand, is linked with a dependent variable, the biological response. The steps between the drug–receptor interaction and the subsequent biological effect are to some extent unknown. The shape of the fitting curve of the experimental data may give some in-sights into the nature of the concentration–receptor–response (C-R-R) mechanism. It can be evaluated by non-linear regression analysis of the experimental data points of the independent and dependent variables, which could be considered as a history of the interaction between the drug and receptors. However, this information is not enough to evaluate such important parameters of the mechanism as the dissociation constant (affinity) and efficacy. There are two ways to provide more detailed information about the C-R-R mechanism: (i) an experimental way for obtaining data with new or

Development of operational performance models for truck-lane restrictions on freeway corridors

Highways are generally designed to serve a mixed traffic flow that consists of passenger cars, trucks, buses, recreational vehicles, etc. The fact that the impacts of these different vehicle types are not uniform creates problems in highway operations and safety. A common approach to reducing the impacts of truck traffic on freeways has been to restrict trucks to certain lane(s) to minimize the interaction between trucks and other vehicles and to compensate for their differences in operational characteristics. ^ The performance of different truck lane restriction alternatives differs under different traffic and geometric conditions. Thus, a good estimate of the operational performance of different truck lane restriction alternatives under prevailing conditions is needed to help make informed decisions on truck lane restriction alternatives. This study develops operational performance models that can be applied to help identify the most operationally efficient truck lane restriction alternative on a freeway under prevailing conditions. The operational performance measures examined in this study include average speed, throughput, speed difference, and lane changes. Prevailing conditions include number of lanes, interchange density, free-flow speeds, volumes, truck percentages, and ramp volumes. ^ Recognizing the difficulty of collecting sufficient data for an empirical modeling procedure that involves a high number of variables, the simulation approach was used to estimate the performance values for various truck lane restriction alternatives under various scenarios. Both the CORSIM and VISSIM simulation models were examined for their ability to model truck lane restrictions. Due to a major problem found in the CORSIM model for truck lane modeling, the VISSIM model was adopted as the simulator for this study. ^ The VISSIM model was calibrated mainly to replicate the capacity given in the 2000 Highway Capacity Manual (HCM) for various free-flow speeds under the ideal basic freeway section conditions. Non-linear regression models for average speed, throughput, average number of lane changes, and speed difference between the lane groups were developed. Based on the performance models developed, a simple decision procedure was recommended to select the desired truck lane restriction alternative for prevailing conditions. ^

Tropical seagrass-associated macroalgae distributions and trends relative to water quality

Tropical coastal marine ecosystems including mangroves, seagrass beds and coral reef communities are undergoing intense degradation in response to natural and human disturbances, therefore, understanding the causes and mechanisms present challenges for scientist and managers. In order to protect our marine resources, determining the effects of nutrient loads on these coastal systems has become a key management goal. Data from monitoring programs were used to detect trends of macroalgae abundances and develop correlations with nutrient availability, as well as forecast potential responses of the communities monitored. Using eight years of data (1996–2003) from complementary but independent monitoring programs in seagrass beds and water quality of the Florida Keys National Marine Sanctuary (FKNMS), we: (1) described the distribution and abundance of macroalgae groups; (2) analyzed the status and spatiotemporal trends of macroalgae groups; and (3) explored the connection between water quality and the macroalgae distribution in the FKNMS. In the seagrass beds of the FKNMS calcareous green algae were the dominant macroalgae group followed by the red group; brown and calcareous red algae were present but in lower abundance. Spatiotemporal patterns of the macroalgae groups were analyzed with a non-linear regression model of the abundance data. For the period of record, all macroalgae groups increased in abundance (Abi) at most sites, with calcareous green algae increasing the most. Calcareous green algae and red algae exhibited seasonal pattern with peak abundances (Φi) mainly in summer for calcareous green and mainly in winter for red. Macroalgae Abi and long-term trend (mi) were correlated in a distinctive way with water quality parameters. Both the Abi and mi of calcareous green algae had positive correlations with NO3−, NO2−, total nitrogen (TN) and total organic carbon (TOC). Red algae Abi had a positive correlation with NO2−, TN, total phosphorus and TOC, and the mi in red algae was positively correlated with N:P. In contrast brown and calcareous red algae Abi had negative correlations with N:P. These results suggest that calcareous green algae and red algae are responding mainly to increases in N availability, a process that is happening in inshore sites. A combination of spatially variable factors such as local current patterns, nutrient sources, and habitat characteristics result in a complex array of the macroalgae community in the seagrass beds of the FKNMS.

Effects of shading on calcareous benthic periphyton in a short-hydroperiod oligotrophic wetland (Everglades, FL, USA)

The effects of shade on benthic calcareous periphyton were tested in a short-hydroperiod oligotrophic subtropical wetland (freshwater Everglades). The experiment was a split-plot design set in three sites with similar environmental characteristics. At each site, eight randomly selected 1-m2 areas were isolated individually in a shade house, which did not spectrally change the incident irradiance but reduced it quantitatively by 0, 30, 50, 60, 70, 80, 90 and 98%. Periphyton mat was sampled monthly under each shade house for a 5 month period while the wetland was flooded. Periphyton was analyzed for thickness, DW, AFDW, chlorophyll a (chl a) and incubated in light and dark BOD bottles at five different irradiances to assess its photosynthesis–irradiance (PI) curve and respiration. The PI curves parameters P max, I k and eventually the photoinhibition slope (β) were determined following non-linear regression analyses. Taxonomic composition and total algal biovolume were determined at the end of the experiment. The periphyton composition did not change with shade but the PI curves were significantly affected by it. I k increased linearly with increasing percent irradiance transmittance (%IT = 1−%shade). P max could be fitted with a PI curve equation as it increased with %IT and leveled off after 10%IT. For each shade level, the PI curve was used to integrate daily photosynthesis for a day of average irradiance. The daily photosynthesis followed a PI curve equation with the same characteristics as P max vs. %IT. Thus, periphyton exhibited a high irradiance plasticity under 0–80% shade but could not keep up the same photosynthetic level at higher shade, causing a decrease in daily GPP at 98% shade levels. The plasticity was linked to an increase in the chl a content per cell in the 60–80% shade, while this increase was not observed at lower shade likely because it was too demanding energetically. Thus, chl a is not a good metric for periphyton biomass assessment across variously shaded habitats. It is also hypothesized that irradiance plasticity is linked to photosynthetic coupling between differently comprised algal layers arranged vertically within periphyton mats that have different PI curves.

Residence Time Distribution (Rtd) Associated with Statistical Weighted Moments to Fit Mathematical Models Using In Industrial Systems Diagnosis

This work presents a computational, called MOMENTS, code developed to be used in process control to determine a characteristic transfer function to industrial units when radiotracer techniques were been applied to study the unit´s performance. The methodology is based on the measuring the residence time distribution function (RTD) and calculate the first and second temporal moments of the tracer data obtained by two scintillators detectors NaI positioned to register a complete tracer movement inside the unit. Non linear regression technique has been used to fit various mathematical models and a statistical test was used to select the best result to the transfer function. Using the code MOMENTS, twelve different models can be used to fit a curve and calculate technical parameters to the unit.

Association between LDL-C, Non HDL-C, and Apolipoprotein B Levels with Coronary Plaque Regression

Background:Previous reports have inferred a linear relationship between LDL-C and changes in coronary plaque volume (CPV) measured by intravascular ultrasound. However, these publications included a small number of studies and did not explore other lipid markers.Objective:To assess the association between changes in lipid markers and regression of CPV using published data.Methods:We collected data from the control, placebo and intervention arms in studies that compared the effect of lipidlowering treatments on CPV, and from the placebo and control arms in studies that tested drugs that did not affect lipids. Baseline and final measurements of plaque volume, expressed in mm3, were extracted and the percentage changes after the interventions were calculated. Performing three linear regression analyses, we assessed the relationship between percentage and absolute changes in lipid markers and percentage variations in CPV.Results:Twenty-seven studies were selected. Correlations between percentage changes in LDL-C, non-HDL-C, and apolipoprotein B (ApoB) and percentage changes in CPV were moderate (r = 0.48, r = 0.47, and r = 0.44, respectively). Correlations between absolute differences in LDL-C, non‑HDL-C, and ApoB with percentage differences in CPV were stronger (r = 0.57, r = 0.52, and r = 0.79). The linear regression model showed a statistically significant association between a reduction in lipid markers and regression of plaque volume.Conclusion:A significant association between changes in different atherogenic particles and regression of CPV was observed. The absolute reduction in ApoB showed the strongest correlation with coronary plaque regression.

Non-destructive linear model for leaf area estimation in Vernonia ferruginea Less

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Non-Cardiac Surgery in Developing Countries: Epidemiological Aspects and Economical Opportunities - The Case of Brazil

Background: Worldwide distribution of surgical interventions is unequal. Developed countries account for the majority of surgeries and information about non-cardiac operations in developing countries is scarce. The purpose of our study was to describe the epidemiological data of non-cardiac surgeries performed in Brazil in the last years. Methods and Findings: This is a retrospective cohort study that investigated the time window from 1995 to 2007. We collected information from DATASUS, a national public health system database. The following variables were studied: number of surgeries, in-hospital expenses, blood transfusion related costs, length of stay and case fatality rates. The results were presented as sum, average and percentage. The trend analysis was performed by linear regression model. There were 32,659,513 non-cardiac surgeries performed in Brazil in thirteen years. An increment of 20.42% was observed in the number of surgeries in this period and nowadays nearly 3 million operations are performed annually. The cost of these procedures has increased tremendously in the last years. The increment of surgical cost was almost 200%. The total expenses related to surgical hospitalizations were more than $10 billion in all these years. The yearly cost of surgical procedures to public health system was more than $1.27 billion for all surgical hospitalizations, and in average, U$445.24 per surgical procedure. The total cost of blood transfusion was near $98 million in all years and annually approximately $10 million were spent in perioperative transfusion. The surgical mortality had an increment of 31.11% in the period. Actually, in 2007, the surgical mortality in Brazil was 1.77%. All the variables had a significant increment along the studied period: r square (r(2)) = 0.447 for the number of surgeries (P = 0.012), r(2) = 0.439 for in-hospital expenses (P = 0.014) and r(2) = 0.907 for surgical mortality (P = 0.0055). Conclusion: The volume of surgical procedures has increased substantially in Brazil through the past years. The expenditure related to these procedures and its mortality has also increased as the number of operations. Better planning of public health resource and strategies of investment are needed to supply the crescent demand of surgery in Brazil.

Likelihood-based estimation of the regression model with scrambled responses

A significant problem in the collection of responses to potentially sensitive questions, such as relating to illegal, immoral or embarrassing activities, is non-sampling error due to refusal to respond or false responses. Eichhorn & Hayre (1983) suggested the use of scrambled responses to reduce this form of bias. This paper considers a linear regression model in which the dependent variable is unobserved but for which the sum or product with a scrambling random variable of known distribution, is known. The performance of two likelihood-based estimators is investigated, namely of a Bayesian estimator achieved through a Markov chain Monte Carlo (MCMC) sampling scheme, and a classical maximum-likelihood estimator. These two estimators and an estimator suggested by Singh, Joarder & King (1996) are compared. Monte Carlo results show that the Bayesian estimator outperforms the classical estimators in almost all cases, and the relative performance of the Bayesian estimator improves as the responses become more scrambled.

Resting energy expenditure in white and non-white severely obese women

This study aimed to compare the resting energy expenditure (REE) of white and non-white severely obese Brazilian women. REE was examined in 83 severely obese Brazilian women (n = 58 white and 25 non-white) with mean (+/- SD) age 42.99 +/- 11.35 and body mass index 46.88 +/- 6.22 kg/m(2) who were candidates for gastric bypass surgery. Body composition was assessed by air displacement plethysmography (ADP) BOD PODO body composition system (Life Measurement Instruments, Concord, CA) and REE was measured, under established protocol, with an open-circuit calorimeter (Deltatrac II MBM-200, Datex-Ohmeda, Madison, WI, USA). There was no significant difference between the REE of white and non-white severely obese women (1,953 +/- 273 and 1,906 +/- 271 kcal/d, respectively; p = 0.48). However, when adjusted for fat free mass (MLG), REE was significantly higher in non-white severely obese women (difference between groups of 158.4 kcal, p < 0.01). REE in white women was positively and significantly correlated to C-reactive protein (PCR) (r = 0.41.8; P < 0.001) and MLG (r = 0.771; P < 0.001). In the non-white women, REE was only significantly correlated to MLG (r = 0.753; P < 0.001). The multiple linear regression analysis showed that skin color, MLG and PCR were the significant determinants of REE (R(2) = 0.55). This study showed that, after adjustment for MLG, non-white severely obese women have a higher REE than the white ones. The association of body composition inflammation factors and REE in severely obese Brazilian women remains to be further investigated.

Using neural networks and support vector regression to relate marchetti dilatometer test parameters and maximum shear modulus

In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.

Using neural networks and support vector regression to relate marchetti dilatometer test parameters and maximum shear modulus

In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.

PREVALENCE OF ANTIBODIES AGAINST INFLUENZA VIRUS IN NON-VACCINATED EQUINES FROM THE BRAZILIAN PANTANAL

The prevalence of antibodies against Equine Influenza Virus (EIV) was determined in 529 equines living on ranches in the municipality of Poconé, Pantanal area of Brazil, by means of the hemagglutination inhibition test, using subtype H3N8 as antigen. The distribution and possible association among positive animal and ranches were evaluated by the chi-square test, spatial autoregressive and multiple linear regression models. The prevalence of antibodies against EIV was estimated at 45.2% (95% CI 30.2 - 61.1%) with titers ranging from 20 to 1,280 HAU. Seropositive equines were found on 92.0% of the surveyed ranches. Equine from non-flooded ranches (66.5%) and negativity in equine infectious anemia virus (EIAV) (61.7%) were associated with antibodies against EIV. No spatial correlation was found among the ranches, but the ones located in non-flooded areas were associated with antibodies against EIV. A negative correlation was found between the prevalence of antibodies against EIV and the presence of EIAV positive animals on the ranches. The high prevalence of antibodies against EIV detected in this study suggests that the virus is circulating among the animals, and this statistical analysis indicates that the movement and aggregation of animals are factors associated to the transmission of the virus in the region.

Echocardiographic parameters associated with pulmonary congestion in outpatients with Chagas' cardiomyopathy and non-chagasic cardiomyopathy

INTRODUCTION: Despite significant left ventricular (LV) systolic dysfunction and cardiomegaly, pulmonary congestion does not seem to be a major finding in Chagas' cardiomyopathy (CC). This study sought to identify echocardiographic parameters associated with pulmonary congestion in CC and in dilated cardiomyopathy of other etiologies, such as non-CC (NCC), and to compare pulmonary venous hypertension between the two entities. METHODS: A total of 130 consecutive patients with CC and NCC, with similar echocardiographic characteristics, were assessed using Doppler echocardiography and chest radiography. Pulmonary venous vessel abnormalities were graded using a previously described pulmonary congestion score, and this score was compared with Doppler echocardiographic parameters. RESULTS: NCC patients were older than CC patients (62.4 ± 13.5 × 47.8 ± 11.2, p = 0.00), and there were more male subjects in the CC group (66.2% × 58.5%, p = 0.4). Pulmonary venous hypertension was present in 41 patients in the CC group (63.1%) and in 63 (96.9%) in the NCC group (p = 0.0), the mean lung congestion score being 3.2 ± 2.3 and 5.9 ± 2.6 (p = 0.0), respectively. On linear regression multivariate analysis, the E/e' ratio (β = 0.13; p = 0.0), LV diastolic diameter (β = 0.06; p = 0.06), left atrial diameter (β = 0.51; p = 0.08), and right ventricular (RV) end-diastolic diameter (β = 0.02; p = 0.48) were the variables that correlated with pulmonary congestion in both groups. CONCLUSIONS: Pulmonary congestion was less significant in patients with CC. The degree of LV of systolic and diastolic dysfunction and the RV diameter correlated with pulmonary congestion in both groups. The E/e' ratio was the hallmark of pulmonary congestion in both groups.

Left Atrial Volume Determinants in Patients with Non-Ischemic Dilated Cardiomyopathy

Background:Left atrial volume (LAV) is a predictor of prognosis in patients with heart failure.Objective:We aimed to evaluate the determinants of LAV in patients with dilated cardiomyopathy (DCM).Methods:Ninety patients with DCM and left ventricular (LV) ejection fraction ≤ 0.50 were included. LAV was measured with real-time three-dimensional echocardiography (eco3D). The variables evaluated were heart rate, systolic blood pressure, LV end-diastolic volume and end-systolic volume and ejection fraction (eco3D), mitral inflow E wave, tissue Doppler e´ wave, E/e´ ratio, intraventricular dyssynchrony, 3D dyssynchrony index and mitral regurgitation vena contracta. Pearson´s coefficient was used to identify the correlation of the LAV with the assessed variables. A multiple linear regression model was developed that included LAV as the dependent variable and the variables correlated with it as the predictive variables.Results:Mean age was 52 ± 11 years-old, LV ejection fraction: 31.5 ± 8.0% (16-50%) and LAV: 39.2±15.7 ml/m2. The variables that correlated with the LAV were LV end-diastolic volume (r = 0.38; p < 0.01), LV end-systolic volume (r = 0.43; p < 0.001), LV ejection fraction (r = -0.36; p < 0.01), E wave (r = 0.50; p < 0.01), E/e´ ratio (r = 0.51; p < 0.01) and mitral regurgitation (r = 0.53; p < 0.01). A multivariate analysis identified the E/e´ ratio (p = 0.02) and mitral regurgitation (p = 0.02) as the only independent variables associated with LAV increase.Conclusion:The LAV is independently determined by LV filling pressures (E/e´ ratio) and mitral regurgitation in DCM.