Biomarkers of Nitrosative Stress: Development and validation of a new analytical method for 3-Nitrotyrosine quantification

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.

A Multiple Criteria Utility-based Approa h for the Unit Commitment with Wind Power and Pumped Storage Hydro

The integration of wind power in eletricity generation brings new challenges to unit commitment due to the random nature of wind speed. For this particular optimisation problem, wind uncertainty has been handled in practice by means of conservative stochastic scenario-based optimisation models, or through additional operating reserve settings. However, generation companies may have different attitudes towards operating costs, load curtailment, or waste of wind energy, when considering the risk caused by wind power variability. Therefore, alternative and possibly more adequate approaches should be explored. This work is divided in two main parts. Firstly we survey the main formulations presented in the literature for the integration of wind power in the unit commitment problem (UCP) and present an alternative model for the wind-thermal unit commitment. We make use of the utility theory concepts to develop a multi-criteria stochastic model. The objectives considered are the minimisation of costs, load curtailment and waste of wind energy. Those are represented by individual utility functions and aggregated in a single additive utility function. This last function is adequately linearised leading to a mixed-integer linear program (MILP) model that can be tackled by general-purpose solvers in order to find the most preferred solution. In the second part we discuss the integration of pumped-storage hydro (PSH) units in the UCP with large wind penetration. Those units can provide extra flexibility by using wind energy to pump and store water in the form of potential energy that can be generated after during peak load periods. PSH units are added to the first model, yielding a MILP model with wind-hydro-thermal coordination. Results showed that the proposed methodology is able to reflect the risk profiles of decision makers for both models. By including PSH units, the results are significantly improved.