Features of preimaginal and imaginal feeding of calliphoridae of the Far Eastern region of Russia are considered, ecological complexes and trophic groupings are distinguished, and their species composition is indicated. Aspects of calliphoridae' synantropism are discussed.

Лаборатория биотехнологии стволовых клеток (зав. -проф. Н.А. Онищенко) ФГБУ «ФНЦ трансплантологии и искусственных органов им. академика В.И. Шумакова» Министерства здравоохранения РФ (директор -академик РАМН, проф. С.В. Готье), Москва, Российская Федерация Авторы обосновывают варианты иммунного реагирования организма при трансплантации органов сущес-твованием индивидуальных специфических программ реагирования на аллоантигены, которые, исполь-зуя естественные активационные и тормозные механизмы, формируют различную степень устойчивости двух физиологических стереотипов «поведения иммунной системы» -эффекторного и толерогенного. Для идентификации индивидуального доминирующего стереотипа иммунного реагирования реципиента на трансплантат и прогнозирования изменений иммунного гомеостаза в организме авторы предлагают использовать показатели реактивности иммунной системы -консервативность и пластичность, которые могут быть выявлены подбором соответствующих биомаркеров. В настоящее время широко использует-ся система маркеров, характеризующих воспалительные реакции (инфекции/воспаления), для выявле-ния отторжения и сопутствующих осложнений. Для прогнозирования индивидуального доминирующего стереотипа реагирования при иммунологически спокойном течении посттрансплантационного периода авторы предлагают изучать систему информационно значимых клеточных маркеров адаптивного имму-нитета и использовать их для формирования комплексных информативных иммуно-клеточных диагнос-тических модулей.Ключевые слова: стереотипы иммунного ответа, трансплантация органов, биомаркеры. The authors prove variants of immune reacting of an human organism in organ transplantation by existence of individual specifi c programs of reacting on alloantigens which, using natural activatory and inhibitory mechanisms, form various degree of stability of two physiological stereotypes of "behavior of immune system" -effectoric and tolerogenic. For identifi cation of an individual predominant stereotype of recipient immune reacting on a graft and for forecasting changes of an immunological homeostasis in a human organism, authors suggest to use indexes of reactance of immune system -conservatism and plasticity which can be taped by selection of the conforming biomarkers. Now the system of markers characterizing infl ammatory reactions (infections/ infl ammation) for recognition organ rejection and related complications, is widely used. For forecasting of an individual dominant stereotype of reacting in immunologically quiet post-transplant follow-up authors suggest to study a system of informative cellular markers of adaptive immunity and to use them for a formation of complex informative diagnostic immuno-cellular modules. INDIVIDUAL STABILITY OF STEREOTYPES OF IMMUNE REACTING AND MODERN POSSIBILITIES OF THEIR DIAGNOSTIC IN ORGAN TRANSPLANTATION (IMMUNE-PHYSIOLOGICAL ANALYSIS OF A PROBLEM)

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In recent years, the trend of applying intelligent technologies at all stages of construction has become increasingly popular. Particular attention is paid to computer vision methods for detecting various aspects in monitoring the structural state of materials, products and structures. This paper considers the solution of a scientific problem in the area of construction flaw detection using the computer vision method. The convolutional neural network (CNN) U-Net to segment violations of the microstructure of the hardened cement paste that occurred after the application of the load is shown. The developed algorithm makes it possible to segment cracks and calculate their areas, which is necessary for the subsequent evaluation of the state of concrete by a process engineer. The proposed intelligent models, which are based on the U-Net CNN, allow segmentation of areas containing a defect with an accuracy level required for the researcher of 60%. It has been established that model 1 is able to detect both significant damage and small cracks. At the same time, model 2 demonstrates slightly better indicators of segmentation quality. The relationship between the formulation, the proportion of defects in the form of cracks in the microstructure of hardened cement paste samples and their compressive strength has been established. The use of crack segmentation in the microstructure of a hardened cement paste using a convolutional neural network makes it possible to automate the process of crack detection and calculation of their proportion in the studied samples of cement composites and can be used to assess the state of concrete.