2 resultados para New statistics for monitoring

em Instituto Politécnico do Porto, Portugal


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Mathematical models and statistical analysis are key instruments in soil science scientific research as they can describe and/or predict the current state of a soil system. These tools allow us to explore the behavior of soil related processes and properties as well as to generate new hypotheses for future experimentation. A good model and analysis of soil properties variations, that permit us to extract suitable conclusions and estimating spatially correlated variables at unsampled locations, is clearly dependent on the amount and quality of data and of the robustness techniques and estimators. On the other hand, the quality of data is obviously dependent from a competent data collection procedure and from a capable laboratory analytical work. Following the standard soil sampling protocols available, soil samples should be collected according to key points such as a convenient spatial scale, landscape homogeneity (or non-homogeneity), land color, soil texture, land slope, land solar exposition. Obtaining good quality data from forest soils is predictably expensive as it is labor intensive and demands many manpower and equipment both in field work and in laboratory analysis. Also, the sampling collection scheme that should be used on a data collection procedure in forest field is not simple to design as the sampling strategies chosen are strongly dependent on soil taxonomy. In fact, a sampling grid will not be able to be followed if rocks at the predicted collecting depth are found, or no soil at all is found, or large trees bar the soil collection. Considering this, a proficient design of a soil data sampling campaign in forest field is not always a simple process and sometimes represents a truly huge challenge. In this work, we present some difficulties that have occurred during two experiments on forest soil that were conducted in order to study the spatial variation of some soil physical-chemical properties. Two different sampling protocols were considered for monitoring two types of forest soils located in NW Portugal: umbric regosol and lithosol. Two different equipments for sampling collection were also used: a manual auger and a shovel. Both scenarios were analyzed and the results achieved have allowed us to consider that monitoring forest soil in order to do some mathematical and statistical investigations needs a sampling procedure to data collection compatible to established protocols but a pre-defined grid assumption often fail when the variability of the soil property is not uniform in space. In this case, sampling grid should be conveniently adapted from one part of the landscape to another and this fact should be taken into consideration of a mathematical procedure.

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Background: The nitration of tyrosine residues in proteins is associated with nitrosative stress, resulting in the formation of 3-nitrotyrosine (3-NT). 3-NT levels in biological samples have been associated with numerous physiological and pathological conditions. For this reason, several attempts have been made in order to develop methods that accurately quantify 3-NT in biological samples. Regarding chromatographic methods, they seem to be very accurate, showing very good sensibility and specificity. However, accurate quantification of this molecule, which is present at very low concentrations both at physiological and pathological states, is always a complex task and a target of intense research. Objectives: We aimed to develop a simple, rapid, low-cost and sensitive 3-NT quantification method for use in medical laboratories as an additional tool for diagnosis and/or treatment monitoring of a wide range of pathologies. We also aimed to evaluate the performance of the HPLC-based method developed here in a wide range of biological matrices. Material and methods: All experiments were performed on a Hitachi LaChrom Elite® HPLC system and separation was carried out using a Lichrocart® 250-4 Lichrospher 100 RP-18 (5μm) column. The method was further validated according to ICH guidelines. The biological matrices tested were serum, whole blood, urine, B16 F-10 melanoma cell line, growth medium conditioned with the same cell line, bacterial and yeast suspensions. Results: From all the protocols tested, the best results were obtained using 0.5% CH3COOH:MeOH:H2O (15:15:70) as the mobile phase, with detection at wavelengths 215, 276 and 356 nm, at 25ºC, and using a flow rate of 1 mL/min. By using this protocol, it was possible to obtain a linear calibration curve (correlation coefficient = 1), limits of detection and quantification in the order of ng/mL, and a short analysis time (<15 minutes per sample). Additionally, the developed protocol allowed the successful detection and quantification of 3-NT in all biological matrices tested, with detection at 356 nm. Conclusion: The method described in this study, which was successfully developed and validated for 3-NT quantification, is simple, cheap and fast, rendering it suitable for analysis in a wide range of biological matrices.