Cellular ROS imaging with hydro-Cy3 dye is strongly influenced by mitochondrial membrane potential

Background: Hydrocyanines are widely used as fluorogenic probes to monitor reactive oxygen species (ROS) generation in cells. Their brightness, stability to autoxidation and photobleaching, large signal change upon oxidation, pH independence and red/near infrared emission are particularly attractive for imaging ROS in live tissue. Methods: Using confocal fluorescence microscopy we have examined an interference of mitochondrial membrane potential (ΔΨm) with fluorescence intensity and localisation of a commercial hydro-Cy3 probe in respiring and non-respiring colon carcinoma HCT116 cells. Results: We found that the oxidised (fluorescent) form of hydro-Cy3 is highly homologous to the common ΔΨm-sensitive probe JC-1, which accumulates and aggregates only in ‘energised’ negatively charged mitochondrial matrix. Therefore, hydro-Cy3 oxidised by hydroxyl and superoxide radicals tends to accumulate in mitochondrial matrix, but dissipates and loses brightness as soon as ΔΨm is compromised. Experiments with mitochondrial inhibitor oligomycin and uncoupler FCCP, as well as a common ROS producer paraquat demonstrated that signals of the oxidised hydro-Cy3 probe rapidly and strongly decrease upon mitochondrial depolarisation, regardless of the rate of cellular ROS production. Conclusions: While analysing ROS-derived fluorescence of commercial hydrocyanine probes, an accurate control of ΔΨm is required. General significance: If not accounted for, non-specific effect of mitochondrial polarisation state on the behaviour of oxidised hydrocyanines can cause artefacts and data misinterpretation in ROS studies.

Current methods and advances in forecasting of wind power generation

Wind power generation differs from conventional thermal generation due to the stochastic nature of wind. Thus wind power forecasting plays a key role in dealing with the challenges of balancing supply and demand in any electricity system, given the uncertainty associated with the wind farm power output. Accurate wind power forecasting reduces the need for additional balancing energy and reserve power to integrate wind power. Wind power forecasting tools enable better dispatch, scheduling and unit commitment of thermal generators, hydro plant and energy storage plant and more competitive market trading as wind power ramps up and down on the grid. This paper presents an in-depth review of the current methods and advances in wind power forecasting and prediction. Firstly, numerical wind prediction methods from global to local scales, ensemble forecasting, upscaling and downscaling processes are discussed. Next the statistical and machine learning approach methods are detailed. Then the techniques used for benchmarking and uncertainty analysis of forecasts are overviewed, and the performance of various approaches over different forecast time horizons is examined. Finally, current research activities, challenges and potential future developments are appraised.