No abstract

612.76The biomechanical properties of the blood of rats with insult caused by an insufficient blood supply of the cerebrum or a hemorrhage have been experimentally investigated. The hemorheological characteristics at the initial stages of the disease and at the stages of its correction have been obtained. The hemorheological status in the case of local cerebral ischemia has been determined.One of the most serious diseases of modern society is insult, which often leads to a fatal outcome. It is known that the main reason for an insult is an insufficient blood supply of some cerebrum zones, i.e., ischemia leading to the death of nerve cells [1,2]. The blood supply depends substantially on the biomechanical (rheological) properties of the blood (hemorheological properties). However, the role of hemorheological disturbances in the development of insult is not understood. In particular, the time of their appearance is an open question, even though it is known that the blood fluidity is adversely affected as an ischemic insult develops [3][4][5]. There are only a few experimental investigations devoted to the hemorheological disturbances arising when limited areas of the cerebrum are affected [6,7]. The rheological properties of the blood in the case of hemorrhagic insult caused by a cerebral hemorrhage [8] were practically not investigated [8]. These problems are the subject of our experimental investigation.Materials and Methods. In all series of experiments, we investigated the biomechanical properties of the venous blood of rats, stabilized with trilon B (0.002 g/ml), at 25 o C. Below is the procedure of determining the parameters desired.The apparent viscosity of the blood was estimated by the results of investigation of samples in a coaxial-cylindrical rotational viscosimeter (thickness of the spacing 1.5 mm, rate of shear 2-130 sec −1 ) with the use of the Caisson approximation τ 1 ⁄ 2 = τ 0 1 ⁄ 2 + kγ . 1 ⁄ 2 . The quantity k 2 was used as the viscosity coefficient [9].The main determinant of the blood viscosity Ht was estimated by the standard method after the centrifugation of the blood in an MTsG-8 centrifuge (8000 800 min −1 , 6 min).The deformational properties of the erythrocytes were investigated in the process of filtration of 250 µl of their diluted suspension through nucleoporous filters (3 µm); the coefficient of erythrocyte stiffness was calculated by the formula IR = [(T 1 − T 2 )/(T 2 ⋅Htc)]⋅100.The kinetics of erythrocyte aggregation was determined by the intensity of backward light scattering I measured in a coaxial-cylindrical aggregometer (blood-layer thickness 0.9 mm, rate of shear 0-610 sec −1 ). The characteristic time of spontaneous aggregation T a was estimated by the change in I for the time t with the use of the formula T a = t/(1/I), i.e., the hyperbola I(t) was straightened, and the cotangent of the angle between the straight line 1/I and t was calculated. The hydrodynamic-strength coefficient β of aggregates was determined by the measured dependence of I on the rate of shear γ . and ...

Liver involvement in systemic lupus erythematosus is common and in most cases clinical course is asymptomatic, that makes diagnosis difficult. Determination of the cause of the liver involvement is important to select treatment and to evaluate the prognosis of the disease.The aim of the research was to characterize the clinical features of liver involvement in patients with systemic lupus erythematosus and identify the most significant clinical and laboratory parameters for the differential diagnosis of lupus hepatitis.Materials and methods. The study included 313 patients with systemic lupus erythematosus observed in the E.M. Tareev Clinic of Rheumatology, Internal Medicine and Occupational Diseases of I.M. Sechenov First Moscow State Medical University (Sechenov University) in the period from 2001 to 2019. The verification of diagnosis of systemic lupus erythematosus was based on the criteria of the American College of Rheumatology (1997). Patients examination included complete blood count, biochemical and immunological blood tests and an abdominal ultrasonography. In 13 cases hepatic autoantibodies (ASMA, anti-LKM-1, LC-1, SLA-LP, AMA-M2) were analyzed, in 4 – magnetic resonance cholangiopancreatography and in 6 – liver biopsy were made.Results. Liver involvement were represented by an increase of liver enzymes in 58 (18.5%) cases. Chronic viral hepatitis C was diagnosed in 4 (1.3%) patients. Drug-induced hepatitis was found in 17 (5.4%) patients. Autoimmune liver diseases occured in 2 (0.6%) patients. In 2 (0.6%) patients, liver damage was associated with thrombotic microangiopathy (atypical hemolytic uremic syndrome, hereditary thrombophilia). In 15 (4.8%) cases, the most likely diagnosis was NAFLD. Lupus hepatitis was the most likely cause in 18 (5.7%) patients. Differential diagnosis in cases of liver involvement in patients with systemic lupus erythematosus requires assessment of risk factors for various liver diseases, age of the patients, level of liver enzymes, lupus activity, ultrasound signs of liver steatosis and secondary antiphospholipid syndrome.Determining the cause of the liver involvement for the patients with the systemic lupus erythematosus allows establishing better treatment tactic and improvement of the prognosis.

Background:Within the last decade, rapid development of artificial neural networks and machine reading programs and their introduction into medical practice is reported [1,2,3]. Recently, an innovative program, based on the artificial intelligence (AI) technologies (a neural network and machine reading) that analyses knee X-ray images for determining the radiographic stage of OA was created. It was launched on the Osteoscan.ru website and is available for use by patients and doctors.Objectives:to validate the system ability to accurately stage OA through machine interpretation of standard knee radiographs.Methods:Initially, 1300 x-rays of both knee joints where used to teach the neural network. Of these, 350 were presented in the form of film scans, 950 in the DICOM format.The accuracy of the system in recognition of OA stage by knee radiographs was evaluated on a quality control sample of 130 cases (of all 1300). Independently, the radiographs were assessed by certified radiologists (considered the “gold standard”) and the System.Results:In 124 out of 130 cases the conclusion of a specialist and the System was the same, which represents 95.4% predictive power. Coincidence or discrepancy is a qualitative attribute, so, the accuracy of the estimation was calculated. Assuming a discrepancy of 0, and coincidence - of 1, µ = 0,954, the standard error sp= 1.8%. It can be concluded that in 95% of cases the accuracy of the system assessment will be in the range from 91.8% to 99%.Conclusion:Osteosan is a program developed on the base of AI technologies, analyzes radiographic images of the knee joints for determining OA stage. It provides high accuracy in OA stage determining by assessing knee radiographs, in 95% of cases, the accuracy of the system varies from 91.8% to 99%.References:[1]Fischl B, Salat DH, van der Kouwe AJ, Makris N, Ségonne F, Quinn BT, Dale AM. Sequence-independent segmentation of magnetic resonance images. Neuroimage. 2004;23 Suppl 1:S69-84[2]Faust O, Acharya U R, Ng EY, Ng KH, Suri JS. Algorithms for the automated detection of diabetic retinopathy using digital fundus images: a review. J Med Syst. 2012; 36(1): 145-57.[3]Balyen L, Peto T. Promising Artificial Intelligence-Machine Learning-Deep Learning Algorithms in Ophthalmology. Asia Pac J Ophthalmol (Phila). 2019; 8(3): 264-272.Disclosure of Interests:Olga Georginova Speakers bureau: GlaxoSmithKline Consumer Healthcare, Margarita Kobzar Employee of: GSK Consumer Healthcare