Correlation between morphologic carotid plaque findings based on color-Doppler and CT multidetector angiography with intraopertive findings in carotid artery stenosis

Bacground/Aim. Vast majority of patients with corotid artery sclerosis do not have transitory ischemic attacks (TIA) as working to the persistent silent disease, but stroke is the first sign. Precise and early diagnosis of the carotid artery disease and plaques are very important. The aim of this study was to determine how the composition / identity of diagnostic methods, color-Doppler, ultrasonography (US) CT multidetector angio (MDCTA) scan and intraoperative (IO) findings, as well as the morphology of plaques in patients with haemodynamic significant stenosis of the internal carotid artery. Methods. Carotid plaques were observed by two diagnostic methods, US and MDCTA, and these findings were correlated with the IO findings. Results. In 62 patients both carotid artheries were examined and 83 plaques were observed. There were 68 surgical interventions. The structure of plaques was divided into four types: lipid, fibrous, fibrocalcified and calcified plaque. US showed: lipid plaques 10.8%; fibrous 1.2%; fibrocalcified 44.6% and calcified 43.4%, and the MDCTA lipid plaques 8.4%; fibrocalcified 48.2% and calcified 43.4%. Intraoperative findings were: lipid plaques 10.3%; fibrocalcified 41.2% and calcified 48.5%. A statistically highly significant agreement between the US and MDCTA in the diagnosis of plaque morphology was obtained (Cramer's V = 0.919, p < 0.01; Lambda = 0.921, p < 0.01) and also statistically significant agreement between US and IO findings (Cramer' s V = 0.831, p < 0.01; Lambda = 0.859, p < 0.01). A statistically highly significant agreement between MDCTA and IO findings in plaque morphology was found, as well (Cramer's V = 0.815, p < 0.01; Lambda = 0.829, p < 0.01). Conclusion. There is statistically highly significant correlation between US and MDCTA diagnostic methods in the evaluation of plaque morphology in surgically significant stenosis of internal carotid artery as well as their agreement with the intraoperative finding

Gait Phases Recognition from Accelerations and Ground Reaction Forces: Application of Neural Networks

The goal of this study was to test the applicability of accelerometer as the sensor for assessment of the walking. We present here the comparison of gait phases detected from the data recorded by force sensing resistors mounted in the shoe insoles, non-processed acceleration and processed acceleration perpendicular to the direction of the foot. The gait phases in all three cases were detected by means of a neural network. The output from the neural network was the gait phase, while the inputs were data from the sensors. The results show that the errors were in the ranges: 30 ms (2.7%) – force sensors; 150 ms (13.6%) – nonprocessed acceleration, and 120 ms (11%) – processed acceleration data. This result suggests that it is possible to use the accelerometer as the gait phase detector, however, with the knowledge that the gait phases are time shifted for about 100 ms with respect the neural network predicted times

Alopecia areata.

Alopecia areata is an autoimmune disorder characterized by transient, non-scarring hair loss and preservation of the hair follicle. Hair loss can take many forms ranging from loss in well-defined patches to diffuse or total hair loss, which can affect all hair-bearing sites. Patchy alopecia areata affecting the scalp is the most common type. Alopecia areata affects nearly 2% of the general population at some point during their lifetime. Skin biopsies of affected skin show a lymphocytic infiltrate in and around the bulb or the lower part of the hair follicle in the anagen (hair growth) phase. A breakdown of immune privilege of the hair follicle is thought to be an important driver of alopecia areata. Genetic studies in patients and mouse models have shown that alopecia areata is a complex, polygenic disease. Several genetic susceptibility loci were identified to be associated with signalling pathways that are important to hair follicle cycling and development. Alopecia areata is usually diagnosed based on clinical manifestations, but dermoscopy and histopathology can be helpful. Alopecia areata is difficult to manage medically, but recent advances in understanding the molecular mechanisms have revealed new treatments and the possibility of remission in the near future. Nat Rev Dis Primers 2017 Mar 16; 3:1701