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Current Applied Materials - Current Issue
Volume 3, Issue 1, 2024
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Development and Optimization of Polymeric Nanoparticles and their In vitro Deposition Studies Using Modified TSI
Authors: Bhushan R. Rane, Pranit S. Waghchaure, Akash J. Amkar and Ashish R. JainBackgroundTo deliver the drug through the pulmonary route, polymers like oleoyl-carboxymethyl chitosan (O-CMC), chitosan, and HPMC (hydroxypropyl methylcellulose) K4M are well known for their effective mucoadhesive properties. Drug-loaded polymeric nanoparticles have the potential for a therapeutic response for the targeted site is a beneficial approach.
ObjectiveThe present study is to develop polymeric nanoparticles (PNPs) utilizing mucoadhesive polymers with varying concentrations as well as to develop the PNPs for pulmonary delivery.
MethodsPolymeric nanoparticles are developed by homogenization and solvent evaporation methods and characterized by modified twin-stage impinger to study in vitro deposition.
ResultsThe characterization of pirfenidone-loaded polymeric nanoparticles (PFD-PNPs) reveals that the mean particle size of O-CMC-PNPs is 140.8 nm ± 20, found to be less than CS-PNPs and HPMC-PNPs. The polydispersibility index reveals that the particles of all prepared formulations are homogenous. At the same time, the zeta potential of O-CMC-PNPs is 40.8 mV ± 5.64, and the entrapment efficiency is 91% ± 1.2, which is better as compared to Chitosan and HPMC K4M PNPs and makes them efficient for pulmonary delivery. Findings from the in vitro deposition study using modified TSI show that 88.5% of the drug delivered through nebulization from both the stage of right and left sides of the TSI suggests effective deposition in the lungs of O-CMC PNPs, and it may move to the deeper regions because of the lowest diameter of the particles. Sustaining release of the drug was found in the O-CMC PNPs for 8 hours, compared with 5 and 7 hours for HPMC PNPs and Chitosan PNPs, respectively.
ConclusionsOverall, the results of the O-CMC-PNPs highlight that the prepared nanoparticles with O-CMC would be effective for pulmonary delivery instead of chitosan and HPMC K4M.
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Remote Sensing Revolution: Mapping Land Productivity and Vegetation Trends with Unmanned Aerial Vehicles (UAVs)
Authors: Shrikant Harle, Amol Bhagat and Ashish Kumar DashThis review paper offers a comprehensive exploration of the multifaceted applications of Unmanned Aerial Vehicles (UAVs) in various domains, showcasing their transformative impact in addressing complex challenges. The evaluation of cloud-based UAV systems' stability reveals their robustness and reliability, underlining their significance in numerous industries. Additionally, their role in enhancing robot navigation in intricate environments signifies a substantial advancement in robotics and automation. The integration of blockchain technology for secure Internet of Things (IoT) data transfer emphasizes the critical importance of data integrity and confidentiality in the IoT era. Furthermore, the optimization of energy-efficient data collection in IoT networks through UAVs demonstrates their potential to revolutionize data-driven decision-making processes, particularly in fields reliant on data accuracy and timeliness. The paper also highlights the application of deep reinforcement learning to enhance UAV-assisted IoT data collection, showcasing the synergy between advanced machine learning techniques and UAV technology. Finally, the discussion underscores the pivotal role of UAVs in precision agriculture, where they facilitate ecological farming practices and monitor environmental conditions, contributing to the pursuit of sustainable and efficient agriculture. This review reaffirms UAVs' status as transformative tools, reshaping industries and unlocking new frontiers of innovation and problem-solving. With ongoing technological advancements, UAVs are poised to play an increasingly central role in a wide range of applications, promising a future marked by ground breaking possibilities. Key findings include the dominance of the United States and China in the field, exploration of characteristics such as crop production, and innovative UAV-based methods for grassland mapping, maize growth assessment, and Arctic plant species monitoring. The research underscores the potential of UAVs in bridging field data and satellite mapping, providing valuable insights into diverse applications, from soil analysis to yield predictions, highlighting their transformative role in environmental monitoring and precision agriculture.
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