Abstract

Objective is to study the features of impaired activation of T and B lymphocytes in order to predicting severe cytomegalovirus infection in newborns. Materials and methods. 133 newborns with cytomegalovirus infection were examined. Immediately after diagnosing cytomegalovirus infection, all patients observed were immunologically ex amined, including assessing count of peripheral blood T and B lymphocytes, as well as their intercellular interaction by using flow cytometry immunostaining for CD3, CD3+CD28–, CD3+CD28+, CD3–CD28+, CD4, CD8, CD20, CD20+CD40+, CD28, CD40. The test was performed by using a Beckman Coulter Epics XL laser flow cytofluorometer. Depending on the condition severity, all children were divided into two groups: 1 — cytomegalovirus infection, severe form — 60 subjects (45.1%); 2 — cytomegalovirus infection, moderate form — 73 subjects (54.9%). Results of the entire set of studied indicators for cellular and humoral arms of immune system revealed statistically significant differences for the prognosis of severe cytomegalovirus infection: CD3+CD28–, CD20, CD20+CD40+, CD4. T lymphocytes with CD3+CD28+ activation markers, through which costimulating signals necessary for the activation of T helper cells are exerted cell-intrinsic features, serving as an important factor ensuring immune response. Using the “classification trees” method, we developed a differentiated approach to forecast severe cytomegalovirus infection in newborns. Systems of inequalities were obtained, four of which classify a subgroup of newborns with severe cytomegalovirus infection. The consistent application of the obtained inequalities makes it possible to isolate from the input stream of sick patients with a prognosis of the development of severe cytomegalovirus infection. The proposed diagnostic rules can be considered as screening markers for predicting a severe cytomegalovirus infection in newborns, which makes possible the timely onset of specific therapy.

Highlights

  • Objective is to study the features of impaired activation of T and B lymphocytes in order to predicting severe cytomegalovirus infection in newborns

  • Инфекция и иммунитет amined, including assessing count of peripheral blood T and B lymphocytes, as well as their intercellular interaction by using flow cytometry immunostaining for CD3, CD3+CD28, CD3+CD28+, CD3–CD28+, CD4, CD8, CD20, CD20+CD40+, CD28, CD40

  • T lymphocytes with CD3+CD28+ activation markers, through which costimulating signals necessary for the activation of T helper cells are exerted cell-intrinsic features, serving as an important factor ensuring immune response

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Summary

ПРОГНОЗ ТЯЖЕЛОЙ ФОРМЫ ЦИТОМЕГАЛОВИРУСНОЙ ИНФЕКЦИИ У НОВОРОЖДЕННЫХ ДЕТЕЙ

ФГБОУ ВО Ростовский государственный медицинский университет Минздрава России, г. Цель исследования — изучить особенности экспрессии костимуляторных молекул CD28, CD40 при активации Т- и В-лимфоцитов и разработать прогностический алгоритм диагностики тяжелой формы цитомегаловирусной инфекции у новорожденных детей. С помощью метода «деревья классификации» нам удалось разработать дифференцированный подход к прогнозу тяжелой формы цитомегаловирусной инфекции у новорожденных детей. Четыре из которых классифицируют подгруппу новорожденных с тяжелым течением цитомегаловирусной инфекции. Последовательное применение полученных неравенств позволяет выделить из входного потока больных пациентов с прогнозом развития тяжелой формы цитомегаловирусной инфекции. При помощи ROC-анализа диагностической ценности вышеуказанного метода прогноза тяжелой формы ЦМВИ было показано, что информативность используемых иммунологических параметров характеризуется как «отличная», о чем свидетельствует площадь под кривой (AUC — 0,974). Предложенный диагностический алгоритм можно использовать для прогноза тяжелой формы цитомегаловирусной инфекции у новорожденных, что делает возможным своевременное начало специфической терапии.

Материалы и методы
Immunological index
Значимость различий между группами Relevance differences between groups
Chance of detecting a risk factor in the control group
Findings
Конфликт интересов

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