Selenium (Se) is a rare and essential element for the human body and other living organisms because of its role in the structure of several proteins and having anti-oxidant properties to reduce oxidative stress at cells. Some microorganisms can absorb Se oxyanions and convert them into zero-valent Se (Se0) in the nanoscale dimensions, which can be used for producing Se nanoparticles (SeNPs). In the present study, SeNPs were intracellularly biosynthesised by yeast Nematospora coryli, which is an inexpensive method and does not involve using materials hazardous for human and environment. The produced NPs were refined by a two-phase system and then characterised and identified by ultraviolet-visible, X-ray diffraction, X-ray fluorescence, transmission electron microscope, and Fourier transform infrared spectroscopy analyses. The structural analysis of biosynthesised SeNPs showed spherical-shaped NPs with size ranging from 50 to 250 nm. Also, extracted NPs were applied to explore their anti-candida and anti-oxidant activities. The results of this investigation confirm the biological properties of Se.

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Using control charts for monitoring therapeutic processes has become popular lately. As the application of traditional control charts in the therapeutic processes may be misleading due to the inherent differences between patients, a multifactor correlated risk measure is considered in monitoring of these processes. Therefore, using risk-adjusted control charts for monitoring the therapeutic processes is of interest to practitioners. Furthermore, in health care monitoring, statistical models should account for abnormal distributions and outlier data to minimize misinterpretations of monitoring schemes. This study proposes a risk-adjusted multivariate Tukey's cumulative sum (RA-MTCUSUM) control chart. The proposed method is a combination of the accelerated failure time (AFT) regression model, the Tukey's control chart (TCC) featuring robustness against abnormality, and the multivariate cumulative sum (MCUSUM) control chart for monitoring multivariable process. Simulation experiments are performed to evaluate the performance of the proposed control chart using the average run length (ARL) measure. Results show that the RA-MTCUSUM control chart has better performance in comparison with traditional ones for monitoring various distributions (normal and non-normal). Based on the simulation results, outlier data do not disturb the proposed control chart's performance. Moreover, applying the RA-MTCUSUM control chart to a real-world dataset related to sepsis patients of a hospital located in Tehran, Iran indicates that the control chart has more reasonable performance than the traditional control charts in the real applications due to its robustness.

There exist multitude of therapeutic processes and the results are commonly observed during various dependent steps. For studying such processes that are referred to as multistage therapeutic processes, two concepts are of particular importance; risk adjustment and cascade property. To monitor such processes, a variety of control charts including model‐based control charts are used. In order to design model‐based control charts, analysts must first recognize a suitable model to identify the multistage processes by considering process risks and cascade property. Based on the identified model, the control charts can be proposed. In this study, a risk‐adjusted time‐variant linear state space model is introduced. Afterward, the model order and its parameters are estimated based on Hankel singular value decomposition (HSVD) and prediction error minimization (PEM) methods. Then, the group multivariate exponentially weighted moving average (GMEWMA) control chart is used to monitor a multistage multivariate therapeutic process. To evaluate the performance of the model‐based control chart, a simulation study as well as a two‐stage thyroid cancer surgery was used. Results show that the proposed control chart performs well for predicting and monitoring of multistage multivariate therapeutic processes in real world.

Background: Calcium phosphates are chemically similar to bone minerals. The biocompatibility, bioactivity, and high similarity of these substances to body organs such as bone have made them a good choice for disease diagnosis and treatment. Here, the main use of calcium phosphates is diagnosis and treatment of cancers. Hydroxyapatite is a bioactive material with a high affinity for DNA and protein. Recently, hydroxyapatite nanoparticles exhibit different properties than those of bulk hydroxyapatite in chemistry and biology. In general, the anticancer effects of hydroxyapatite nanoparticles have been attributed to high amounts of endocytosis in cancer cells and inhibits of protein synthesis in cells. Methods: Herein, we evaluated the structure, properties, and methods of synthesis of hydroxyapatite nanoparticles. Moreover, the mechanism of inhibition of hydroxyapatite nanoparticles on cancer cells and recent advances in this field have been examined. Conclusion: Hydroxyapatite nanoparticles had the ability to eliminate the development of cancer cells in vitro and in vivo. In the live tissue environment, injection of hydroxyapatite nanoparticles at the tumor’s surrounding area had a significant decrease in tumor size (about 50%).