The Internet of Healthcare Things (IoHT) is an essential IoT domain that encompasses the necessary capabilities to transform the current healthcare system. IoHT generates, transfers, manages, stores, and processes highly confidential medical data and sensitive personal information. Thus, IoHT is a critical application from a security perspective and is most favorably targeted by attackers. Several security-breaching attempts can be carried out due to the vulnerabilities of the IoHT that put classified data at constant risk. Henceforth, this work aims to inspect the performance of 6LoWPAN-RPL-based `Patient-Centric IoHT’ in the presence of malicious intruders conducting blackhole, rank, and DoDAG attacks in both normal and emergency operational modes of the mentioned resource-constraint network. PC-IoHT is simulated on the Cooja simulator and Contiki-OS for each attack with two and four intruders (out of 10 motes) for both operation modes. Several performance evaluation parameters are used to assess the overall performance of the considered PC-IoHT. The attacks’ impact on PC-IoHT is analyzed by comparing blackhole, rank, and DoDAG attacks with the no-attack scenario.

Obesity, which is characterized by an excessive accumulation of body fat, is one of the critical factors causing metabolic syndrome. Many studies have been performed to identify appropriate agents to control obesity, but toxicity remains a problem. Herein, we identified that phenylbutyrate (PBA), which has been used to treat urea cycle disorder with very low toxicity for a long time, efficiently inhibited high fat-induced body weight gain in a diet-induced obesity mouse model (DIO model). PBA treatment decreased body fat mass and increased lean composition. Moreover, PBA increased brown adipose tissue (BAT) activity by increasing glucose uptake, thereby improving glucose tolerance and insulin tolerance. Interestingly, PBA could induce the expression of phosphofructokinase (PFKL), a key enzyme in the glycolytic pathway, and knocking down PFKL dramatically repressed the expression level of Ucp1 as well as those of Prdm16, Cidea, Pgc1α, and Pparγ, which are marker genes for BAT activation. These results strongly suggested that PBA could increase energy expenditure by increasing BAT activity via the induction of PFKL. Taken together, PBA could be used as a therapeutic agent for people with obesity to prevent the development of metabolic syndrome.

The Korean Pathfinder Lunar Orbiter (KPLO)-MAGnetometer (KMAG) consists of three triaxial fluxgate sensors (MAG1, MAG2, and MAG3) to measure the magnetic field around the Moon. The three sensors are mounted in the order of MAG3, MAG2, and MAG1 inside a 1.2 m long boom away from the satellite body. Before it arrived on the Moon, we compared the magnetic field measurements taken by DSCOVR and KPLO in the solar wind to verify the measurement performance of the KMAG instrument. We found that there were artificial disturbances in the KMAG measurement data, such as step-like and spike-like disturbances, which were produced by the spacecraft body. To remove spacecraft-generated disturbances, we applied a multi-sensor method, employing the gradiometer technique and principal component analysis and using KMAG magnetic field data and confirmed the successful elimination of spacecraft-generated disturbances. This indicates that the multi-sensor method is able to clean the magnetic field data measured onboard the KPLO.