Sono-photodynamic combination therapy: a review on sensitizers.

Cancer is characterized by the dysregulation of cell signaling pathways at several steps. The majority of current anticancer therapies involve the modulation of a single target. A tumor-targeting drug-delivery system consists of a tumor detection moiety and a cytotoxic material joined directly or through a suitable linker to form a conjugate. Photodynamic therapy has been used for more than 100 years to treat tumors. One of the present goals of photodynamic therapy research is to enhance the selective targeting of tumor cells in order to reduce the risk and extension of unwanted side-effects, caused by normal cell damage. Sonodynamic therapy is a promising new treatment for patients with cancer. It treats cancer with ultrasound and sonosensitive agents. Porphyrin compounds often serve as photosensitive and sonosensitive agents. The combination of these two methods makes cancer treatment more effective. The present review provides an overview of photodynamic therapy, sonodynamic therapy, sono-photodynamic therapy and the four sensitizers which are suitable candidates for combined sono-photodynamic therapy.

An environmental monitoring system for managing spatiotemporal sensor data over sensor networks.

In a wireless sensor network, sensors collect data about natural phenomena and transmit them to a server in real-time. Many studies have been conducted focusing on the processing of continuous queries in an approximate form. However, this approach is difficult to apply to environmental applications which require the correct data to be stored. In this paper, we propose a weather monitoring system for handling and storing the sensor data stream in real-time in order to support continuous spatial and/or temporal queries. In our system, we exploit two time-based insertion methods to store the sensor data stream and reduce the number of managed tuples, without losing any of the raw data which are useful for queries, by using the sensors' temporal attributes. In addition, we offer a method for reducing the cost of the join operations used in processing spatiotemporal queries by filtering out a list of irrelevant sensors from query range before making a join operation. In the results of the performance evaluation, the number of tuples obtained from the data stream is reduced by about 30% in comparison to a naïve approach, thereby decreasing the query execution time.

Design of sensor data processing steps in an air pollution monitoring system.

Environmental monitoring is required to understand the effects of various kinds of phenomena such as a flood, a typhoon, or a forest fire. To detect the environmental conditions in remote places, monitoring applications employ the sensor networks to detect conditions, context models to understand phenomena, and computing technology to process the large volumes of data. In this paper, we present an air pollution monitoring system to provide alarm messages about potentially dangerous areas with sensor data analysis. We design the data analysis steps to understand the detected air pollution regions and levels. The analyzed data is used to track the pollution and to give an alarm. This implemented monitoring system is used to mitigate the damages caused by air pollution.