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Considering snowmelt in mountainous areas as the important source of streamflow, the snow accumulation/melting processes are vital for accurate simulation of the hydrological regimes. The lack of snow-related data and its uncertainties/conceptual ambiguity in snowpack modeling are the different challenges of developing hydroclimatological models. To tackle these challenges, Global Gridded Snow Products (GGSPs) are introduced, which effectively simplify the identification of the spatial characteristics of snow hydrological variables. This research aims to investigate the performance of multi-source GGSPs using multi-stage calibration strategies in hydrological modeling. The used GGSPs were Snow-Covered Area (SCA) and Snow Water Equivalent (SWE), implemented individually or jointly to calibrate an appropriate water balance model. The study area was a mountainous watershed located in Western Iran with a considerable contribution of snowmelt to the generated streamflow. The results showed that using GGSPs as complementary information in the calibration process, besides streamflow time series, could improve the modeling accuracy compared to the conventional calibration, which is only based on streamflow data. The SCA with NSE, KGE, and RMSE values varying within the ranges of 0.47-0.57, 0.54-0.65, and 4-6.88, respectively, outperformed the SWE with the corresponding metrics of 0.36-0.59, 0.47-0.60, and 5.22-7.46, respectively, in simulating the total streamflow of the watershed. In addition to the superiority of the SCA over SWE, the two-stage calibration strategy reduced the number of optimized parameters in each stage and the dependency of internal processes on the streamflow and improved the accuracy of the results compared with the conventional calibration strategy. On the other hand, the consistent contribution of snowmelt to the total generated streamflow (ranging from 0.9 to 1.47) and the ratio of snow melting to snowfall (ranging from 0.925 to 1.041) in different calibration strategies and models resulted in a reliable simulation of the model.
RESUMEN
Introduction: Currently, drug-induced reactive oxygen species (ROS) mediating apoptosis pathway have extensively been investigated in designing effective strategies for colorectal cancer (CRC) chemotherapy. Bovine pancreatic ribonuclease A (RNase A) represents a new class of cytotoxic and non-mutagenic enzymes, and has gained more attention as a potential anticancer modality; however, the cytosolic ribonuclease inhibitors (RIs) restrict the clinical application of this enzyme. Nowadays, nanotechnology-based diagnostic and therapeutic systems have provided potential solutions for cancer treatments. Methods: In this study, the gold nanoparticles (AuNPs) were synthesized, stabilized by polyethylene glycol (PEG), functionalized, and covalently conjugated with RNase A. The physicochemical properties of engineered nanobiomedicine (AuNPs-PEG-RNase A) were characterized by scanning electron microscope (SEM), dynamic light scattering (DLS), and UV-vis spectrum. Then, its biological impacts including cell viability, apoptosis, and ROS production were evaluated in the SW-480 cells. Results: The engineered nanobiomedicine, AuNPs-PEG-RNase A, was found to effectively induce apoptosis in SW-480 cells and result in a significant reduction in cancer cell viability. Besides, the maximum production of ROS was obtained after the treatment of cells with an IC50 dose of AuNPs-PEG-RNase A. Conclusion: Based on the efficient ROS-responsiveness and the anticancer activity of RNase A of the engineered nanomedicine, this nanoscaled biologics may be considered as a potential candidate for the treatment of CRC.
RESUMEN
Despite many beneficial outcomes of the conventional enzyme replacement therapy (ERT), several limitations such as the high-cost of the treatment and various inadvertent side effects including the occurrence of an immunological response against the infused enzyme and development of resistance to enzymes persist. These issues may limit the desired therapeutic outcomes of a majority of the lysosomal storage diseases (LSDs). Furthermore, the biodistribution of the recombinant enzymes into the target cells within the central nervous system (CNS), bone, cartilage, cornea, and heart still remain unresolved. All these shortcomings necessitate the development of more effective diagnosis and treatment modalities against LSDs. Taken all, maximizing the therapeutic response with minimal undesired side effects might be attainable by the development of targeted enzyme delivery systems (EDSs) as a promising alternative to the LSDs treatments, including different types of mucopolysaccharidoses ( MPSs ) as well as Fabry, Krabbe, Gaucher and Pompe diseases.
