ABSTRACT Nanoparticle (NP)‐based drug delivery faces a major challenge due to rapid clearance by the immune system, primarily through opsonization and phagocytosis. To address this, we developed paclitaxel (PTX)‐loaded gelatin nanoparticles (GNPs) coated with mouse serum albumin (MSA) (MSA@PTX‐loaded GNPs) for localized tumor therapy. Physicochemical characterization confirmed successful MSA coating, leading to an increase in hydrodynamic size (∼120 nm) and a shift in surface charge from −11.50 mV (blank GNPs) to …

Microplastics as micropollutants are widely spread in aquatic areas that can have a toxic effect on aquatic life. To reduce the potential risk they pose, it is essential to detect the microplastics and the source of the contamination of the environment. Here, we designed and developed a droplet-based microfluidic impedance flow cytometer for in situ detection of microplastics in water. Impedance spectroscopy enables the direct measurement of the electrical features of microplastics as they move in water, allowing …

The utilization of gas sensors has the potential to enhance worker safety, mitigate environmental issues, and enable early diagnosis of chronic diseases. However, traditional sensors designed for such applications are often bulky, expensive, difficult to operate, and require large sample volumes. By employing microfluidic technology to miniaturize gas sensors, we can address these challenges and usher in a new era of gas sensors suitable for point-of-care and point-of-use applications. In this review paper, we sys…

Predicting cardiac conditions remains one of the most formidable tasks within the medical field today, with heart disease claiming a life every minute in the contemporary landscape. The data-rich healthcare industry necessitates the application of data science for efficient data processing. Given the intricate nature of prognosticating heart-related disorders, the automation of this process becomes a necessity, aiming to mitigate potential risks and offer timely alerts to patients. In this research endeavor, the h…

Feature redundancy minimization is a noticeable topic in today’s research world. Almost in every case of machine learning algorithm, feature selection (FS) creates a great necessity to ensure a good level of classification problem. So, in case of feature selection algorithms, the characteristics to reduce the redundant feature as well as selecting the relevant feature or ranking of the features is equally important. But the problem is most of the FS method are focused on either feature subset selection or feature …