Potential nanotechnology-based diagnostic and therapeutic approaches for Meniere's disease.

Meniere's disease (MD) is a progressive inner ear disorder involving recurrent and prolonged episodes or attacks of vertigo with associated symptoms, resulting in a significantly reduced quality of life for sufferers. In most cases, MD starts in one ear; however, in one-third of patients, the disorder progresses to the other ear. Unfortunately, the etiology of the disease is unknown, making the development of effective treatments difficult. Nanomaterials, including nanoparticles (NPs) and nanocarriers, offer an array of novel diagnostic and therapeutic applications related to MD. NPs have specific features such as biocompatibility, biochemical stability, targetability, and enhanced visualization using imaging tools. This paper provides a comprehensive and critical review of recent advancements in nanotechnology-based diagnostic and therapeutic approaches for MD. Furthermore, the crucial challenges adversely affecting the use of nanoparticles to treat middle ear disorders are investigated. Finally, this paper provides recommendations and future directions for improving the performances of nanomaterials on theragnostic applications of MD.

A Smart Multi-Sensor Device to Detect Distress in Swimmers.

Drowning is considered amongst the top 10 causes of unintentional death, according to the World Health Organization (WHO). Therefore, anti-drowning systems that can save lives by preventing and detecting drowning are much needed. This paper proposes a robust and waterproof sensor-based device to detect distress in swimmers at varying depths and different types of water environments. The proposed device comprises four main components, including heart rate, blood oxygen level, movement, and depth sensors. Although these sensors were designed to work together to boost the system's capability as an anti-drowning device, each could operate independently. The sensors were able to determine the heart rate to an accuracy of 1 beat per minute (BPM), 1% SpO2, the acceleration with adjustable sensitivities of ±2 g, ±4 g, ±8 g, and ±16 g, and the depth up to 12.8 m. The data obtained from the sensors were sent to a microcontroller that compared the input data to adjustable threshold values to detect dangerous situations. Being in hazardous situations for more than a specific time activated the alarming system. Based on the comparison made in the program and measuring the time of submersion, a message indicating drowning or safe was sent to a lifeguard to continuously monitor the swimmer' condition via Wi-Fi to an IP address reachable by a mobile phone or laptop. It is also possible to continuously monitor the sensor outputs on the device's display or the connected mobile phone or laptop. The threshold values could be adjusted based on biometric parameters such as swimming conditions (swimming pool, beach, depth, etc.) and swimmers health and conditions. The functionality of the proposed device was thoroughly tested over a wide range of parameters and under different conditions, both in air and underwater. It was demonstrated that the device could detect a range of potentially hazardous aquatic situations. This work will pave the way for developing an effective drowning sensing system that could save tens of thousands of lives across the globe every year.