Background/Aim. It is known that glaucoma is associated with elevated intraocular pressure and obesity, yet the precise etiology remains unclear. The aim of this study was to determine whether there is a potential causality between the volume of retrobulbar adipose tissue and the level of intraocular pressure in obese subjects compared with non-obese. Methods. A total of 100 subjects were divided according to the body mass index (BMI), into two groups: normal weight (n = 50, BMI = 18-24.9 kg/m2) and obese (n = 50, BMI ? 30 kg/m2) subjects. Anthropometric measurements, body composition analysis, measurement of intraocular pressure, as well as magnetic resonance imaging (MRI) of the head at the level of the optic nerve, and the derived retrobulbar adipose tissue volume, were undertaken in all subjects. Results. The obese subjects, as compared with normal weight ones, had a significantly higher mean retrobulbar adipose tissue volume (6.23 cm3 vs 4.85 cm3, p < 0.01) and intraocular pressure (15.96 mmHg vs 12.99 mmHg, p < 0.01). Furthermore, intraocular pressure correlated positively with retrobulbar adipose tissue volume. Conclusion. In obese people, elevated intraocular pressure may be caused by changes in ocular blood flow, affected by the physical pressure exerted by higher retrobulbar adiposity, and/or by internal vascular changes secondary to complications of obesity. These findings indicate the need for more frequent measurement of intraocular pressure in obese individuals to earlier detect glaucoma, and in so doing prevent irreversible blindness.

The recent global COVID-19 pandemic has revealed that the current healthcare system in modern society can hardly cope with the increased number of patients. Part of the load can be alleviated by incorporating smart healthcare infrastructure in the current system to enable patient’s remote monitoring and personalized treatment. Technological advances in communications and sensing devices have enabled the development of new, portable, and more power-efficient biomedical sensors, as well as innovative healthcare applications. Nevertheless, such applications require reliable, resilient, and secure networks. This paper aims to identify the communication requirements for mass deployment of such smart healthcare sensors by providing the overview of underlying Internet of Things (IoT) technologies. Moreover, it highlights the importance of information theory in understanding the limits and barriers in this emerging field. With this motivation, the paper indicates how data compression and entropy used in security algorithms may pave the way towards mass deployment of such IoT healthcare devices. Future medical practices and paradigms are also discussed.

Pattern of brain asymmetries varies with handedness, gender, age, and with variety of genetic and social factors. Large-scale neuroimaging analyses can optimize the detection of asymmetric features and confirm the factors that might modulate pattern of brain asymmetries. We attempted to evaluate eventual differences between genders in hemodynamic responses to a simple language task.