66 resultados para Concentrations de diazote


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Low circulating folate concentrations lead to elevations of plasma homocysteine. Even mild elevations of plasma homocysteine are associated with significantly increased risk of cardiovascular disease (CVD). Available evidence suggests that poor nutrition contributes to excessive premature CVD mortality in Australian Aboriginal people. The aim of the present study was to examine the effect of a nutrition intervention program conducted in an Aboriginal community on plasma homocysteine concentrations in a community-based cohort. From 1989, a health and nutrition project was developed, implemented and evaluated with the people of a remote Aboriginal community. Plasma homocysteine concentrations were measured in a community-based cohort of 14 men and 21 women screened at baseline, 6 months and 12 months. From baseline to 6 months there was a fall in mean plasma homocysteine of over 2|mol/L (P = 0.006) but no further change thereafter (P = 0.433). These changes were associated with a significant increase in red cell folate concentration from baseline to 6 months (P < 0.001) and a further increase from 6 to 12 months (P < 0.001). In multiple regression analysis, change in homocysteine concentration from baseline to 6 months was predicted by change in red cell folate (P = 0.002) and baseline homocysteine (P < 0.001) concentrations, but not by age, gender or baseline red cell folate concentration. We conclude that modest improvements in dietary quality among populations with poor nutrition (and limited disposable income) can lead to reductions in CVD risk.

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The Quantitative Assessment of Solar UV [ultraviolet] Exposure for Vitamin D Synthesis in Australian Adults (AusD) Study aimed to better define the relationship between sun exposure and serum 25-hydroxyvitamin D (25(OH)D) concentration. Cross-sectional data were collected between May 2009 and December 2010 from 1,002 participants aged 18-75 years in 4 Australian sites spanning 24° of latitude. Participants completed the following: 1) questionnaires on sun exposure, dietary vitamin D intake, and vitamin D supplementation; 2) 10 days of personal ultraviolet radiation dosimetry; 3) a sun exposure and physical activity diary; and 4) clinical measurements and blood collection for 25(OH)D determination. Our multiple regression model described 40% of the variance in 25(OH)D concentration; modifiable behavioral factors contributed 52% of the explained variance, and environmental and demographic or constitutional variables contributed 38% and 10%, respectively. The amount of skin exposed was the single strongest contributor to the explained variance (27%), followed by location (20%), season (17%), personal ultraviolet radiation exposure (8%), vitamin D supplementation (7%), body mass index (weight (kg)/height (m)2) (4%), and physical activity (4%). Modifiable behavioral factors strongly influence serum 25(OH)D concentrations in Australian adults. In addition, latitude was a strong determinant of the relative contribution of different behavioral factors.

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Due to the health impacts caused by exposures to air pollutants in urban areas, monitoring and forecasting of air quality parameters have become popular as an important topic in atmospheric and environmental research today. The knowledge on the dynamics and complexity of air pollutants behavior has made artificial intelligence models as a useful tool for a more accurate pollutant concentration prediction. This paper focuses on an innovative method of daily air pollution prediction using combination of Support Vector Machine (SVM) as predictor and Partial Least Square (PLS) as a data selection tool based on the measured values of CO concentrations. The CO concentrations of Rey monitoring station in the south of Tehran, from Jan. 2007 to Feb. 2011, have been used to test the effectiveness of this method. The hourly CO concentrations have been predicted using the SVM and the hybrid PLS–SVM models. Similarly, daily CO concentrations have been predicted based on the aforementioned four years measured data. Results demonstrated that both models have good prediction ability; however the hybrid PLS–SVM has better accuracy. In the analysis presented in this paper, statistic estimators including relative mean errors, root mean squared errors and the mean absolute relative error have been employed to compare performances of the models. It has been concluded that the errors decrease after size reduction and coefficients of determination increase from 56 to 81% for SVM model to 65–85% for hybrid PLS–SVM model respectively. Also it was found that the hybrid PLS–SVM model required lower computational time than SVM model as expected, hence supporting the more accurate and faster prediction ability of hybrid PLS–SVM model.

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Urban road dust comprises of a range of potentially toxic metal elements and plays a critical role in degrading urban receiving water quality. Hence, assessing the metal composition and concentration in urban road dust is a high priority. This study investigated the variability of metal composition and concentrations in road dust in 4 different urban land uses in Gold Coast, Australia. Samples from 16 road sites were collected and tested for selected 12 metal species. The data set was analyzed using both univariate and multivariate techniques. Outcomes of the data analysis revealed that the metal concentrations in road dust differ considerably within and between different land uses. Iron, aluminum, magnesium and zinc are the most abundant in urban land uses. It was also noted that metal species such as titanium, nickel, copper and zinc have the highest concentrations in industrial land use. The study outcomes revealed that soil and traffic related sources as key sources of metals deposited on road surfaces.

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Until recently, the low-abundance (LA) range of the serum proteome was an unexplored reservoir of diagnostic information. Today it is increasingly appreciated that a diagnostic goldmine of LA biomarkers resides in the blood stream in complexed association with more abundant higher molecular weight carrier proteins such as albumin and immunoglobulins. As we now look to the possibility of harvesting these LA biomarkers more efficiently through engineered nano-scale particles, mathematical approaches are needed in order to reveal the mechanisms by which blood carrier proteins act as molecular 'mops' for LA diagnostic cargo, and the functional relationships between bound LA biomarker concentrations and other variables of interest such as biomarker intravasation and clearance rates and protein half-lives in the bloodstream. Here we show, by simple mathematical modeling, how the relative abundance of large carrier proteins and their longer half-lives in the bloodstream work together to amplify the total blood concentration of these tiny biomarkers. The analysis further suggests that alterations in the production of biomarkers lead to gradual rather than immediate changes in biomarker levels in the blood circulation. The model analysis also points to the characteristics of artificial nano-particles that would render them more efficient harvesters of tumor biomarkers in the circulation, opening up possibilities for the early detection of curable disease, rather than simply better detection of advanced disease.

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This study demonstrates a novel method for testing the hypothesis that variations in primary and secondary particle number concentration (PNC) in urban air are related to residual fuel oil combustion at a coastal port lying 30 km upwind, by examining the correlation between PNC and airborne particle composition signatures chosen for their sensitivity to the elemental contaminants present in residual fuel oil. Residual fuel oil combustion indicators were chosen by comparing the sensitivity of a range of concentration ratios to airborne emissions originating from the port. The most responsive were combinations of vanadium and sulfur concentration ([S], [V]) expressed as ratios with respect to black carbon concentration ([BC]). These correlated significantly with ship activity at the port and with the fraction of time during which the wind blew from the port. The average [V] when the wind was predominantly from the port was 0.52 ng.m-3 (87%) higher than the average for all wind directions and 0.83 ng.m-3 (280%) higher than that for the lowest vanadium yielding wind direction considered to approximate the natural background. Shipping was found to be the main source of V impacting urban air quality in Brisbane. However, contrary to the stated hypothesis, increases in PNC related measures did not correlate with ship emission indicators or ship traffic. Hence at this site ship emissions were not found to be a major contributor to PNC compared to other fossil fuel combustion sources such as road traffic, airport and refinery emissions.

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Background Research has identified associations between serum 25(OH)D and a range of clinical outcomes in chronic kidney disease and wider populations. The present study aimed to investigate vitamin D deficiency/insufficiency in dialysis patients and the relationship with vitamin D intake and sun exposure. Methods A cross-sectional study was used. Participants included 30 peritoneal dialysis (PD) (43.3% male; 56.87 ± 16.16 years) and 26 haemodialysis (HD) (80.8% male; 63.58 ± 15.09 years) patients attending a department of renal medicine. Explanatory variables were usual vitamin D intake from diet/supplements (IU day−1) and sun exposure (min day−1). Vitamin D intake, sun exposure and ethnic background were assessed by questionnaire. Weight, malnutrition status and routine biochemistry were also assessed. Data were collected during usual department visits. The main outcome measure was serum 25(OH)D (nm). Results Prevalence of inadequate/insufficient vitamin D intake differed between dialysis modality, with 31% and 43% found to be insufficient (<50 nm) and 4% and 33% found to be deficient (<25 nm) in HD and PD patients, respectively (P < 0.001). In HD patients, there was a correlation between diet and supplemental vitamin D intake and 25(OH)D (ρ = 0.84, P < 0.001) and average sun exposure and 25(OH)D (ρ = 0.50, P < 0.02). There were no associations in PD patients. The results remained significant for vitamin D intake after multiple regression, adjusting for age, gender and sun exposure. Conclusions The results highlight a strong association between vitamin D intake and 25(OH)D in HD but not PD patients, with implications for replacement recommendations. The findings indicate that, even in a sunny climate, many dialysis patients are vitamin D deficient, highlighting the need for exploration of determinants and consequences.

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Corona discharge is responsible for the flux of small ions from overhead power lines, and is capable of modifying the ambient electrical environment, such as the air ion concentrations at ground level. Once produced, small ions quickly attach to aerosol particles in the air, producing ‘large ions’, approximately 1 nm to 1 µm in diameter. However, very few studies have measured air ion concentrations directly near high voltage transmission lines. The present study involved the simultaneously measurement of small ion concentration and net large ion concentration using air ion counters and an aerosol electrometer at four power line sites. Both positive and negative small ion concentration (<1.6nm), net large ion concentration (2nm-5μm) and particle number concentration (10nm-2μm) were measured using air ion counters and an aerosol electrometer at four power line sites. Measurements at sites 1 and 2 were conducted at both upwind and downwind sides. The results showed that total ion concentrations on the downwind side were 3-5 times higher than on the upwind side, while particle number concentrations did not show a significant difference. This result also shows that a large number of ions were emitted from the power lines at sites 1 and 2. Furthermore, both positive and negative ions were observed at different power line sites. Dominant positive ions were observed at site 1, with a concentration of 4.4 x 103 ions cm-3, which was 10 times higher than on the upwind side. Contrary to site 1, sites 2 to 4 showed negative ion emissions, with concentrations of -1.2 x 103, -460 and -410 ions cm-3, respectively. These values were higher than the background urban negative ion concentration of 400 cm-3. At site 1 and site 2, the net ion concentration and net particle charge concentration on downwind side of the lines showed same polarities. Further investigations were also conducted into the correlation between net ion concentration and net charge particle concentration 20 m downwind of the power lines at site 2. The two parameters showed a correlation coefficient of 0.72, indicating that a substantial number of ions could attach to particles and affect the particle charge status within a short distance from the source.

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Particle number concentrations vary significantly with environment and, in this study, we attempt to assess the significance of these differences. Towards this aim, we reviewed 85 papers that have reported particle number concentrations levels at 126 sites covering different environments. We grouped the results into eight categories according to measurement location including: road tunnel, on-road, road-side, street canyon, urban, urban background, rural, and clean background. From these reports, the overall median number concentration for each of the eight site categories was calculated. The eight location categories may be classified into four distinct groups. The mean median particle number locations for these four types were found to be statistically different from each other. Rural and clean background sites had the lowest concentrations of about 3x103 cm-3. Urban and urban background sites showed concentrations that were three times higher (9x103 cm-3). The mean concentration for the street canyon, roadside and on-road measurement sites was 4.6x104 cm-3, while the highest concentrations were observed in the road tunnels (8.6x104 cm-3). This variation is important when assessing human exposure-response for which there is very little data available, making it difficult to develop health guidelines, a basis for national regulations. Our analyses shows that the current levels in environments affected by vehicle emissions are 3 to 28 times higher than in the natural environments. At present, there is no threshold level in response to exposure to ultrafine particles. Therefore, future control and management strategies should target a decrease of these particles in urban environments by more than one order of magnitude to bring them down to the natural background. At present there is a long way to go to achieve this.

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Particle number concentrations vary significantly with environment and, in this study, we attempt to assess the significance of these differences. Towards this aim, we reviewed 85 papers that have reported particle number concentrations levels at 126 sites covering different environments. We grouped the results into eight categories according to measurement location including: road tunnel, on-road, road-side, street canyon, urban, urban background, rural, and clean background. Median values were calculated for each category. This review was restricted to papers that presented concentrations numerically. The majority of the reports were based on either CPC or SMPS measurements, with a limited number of papers reporting results from both instruments at the same site. Hence there were several overlaps between the number of CPC and SMPS measuring sites. Most of the studies reported multiple measurements at a given study site, while some studies included results from more than one site. From these reports, the overall median value for each location category was calculated...

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Introduction We have previously shown that the concentrations of D-dimer are significantly elevated in saliva compared with plasma. Saliva offers several advantages compared with blood analysis. We hypothesised that human saliva contains plasminogen activator inhibitor-1 (PAI-1) and that the concentrations are not affected by the time of saliva collection. The aim was to adopt and validate an immunoassay to quantify PAI-1 concentrations in saliva and to determine whether saliva collection time has an influence in the measurement. Materials and methods Two saliva samples (morning and afternoon) from the same day were collected from healthy subjects (N = 40) who have had no underlying heart conditions. A customized AlphaLISA® immunoassay (PerkinElmer®, MA, USA) was adopted and used to quantify PAI-1 concentrations. We validated the analytical performance of the customized immunoassay by calculating recovery of known amount of analyte spiked in saliva. Results: The recovery (95.03%), intra- (8.59%) and inter-assay (7.52%) variations were within the acceptable ranges. The median salivary PAI-1 concentrations were 394 pg/mL (interquartile ranges (IQR) 243.4-833.1 pg/mL) in the morning and 376 (129.1-615.4) pg/mL in the afternoon and the plasma concentration was 59,000 (24,000-110,000) pg/mL. Salivary PAI-1 did not correlate with plasma (P = 0.812). Conclusions The adopted immunoassay produced acceptable assay sensitivity and specificity. The data demonstrated that saliva contains PAI-1 and that its concentration is not affected by the time of saliva collection. There is no correlation between salivary and plasma PAI-1 concentrations. Further studies are required to demonstrate the utility of salivary PAI-1 in CVD risk factor studies.