Development of an automaton recognizer of tissue pathologies caused by Chlamydia infection

¹ Perm Institute of the FPS of Russia, 125, Karpinskogo St., Perm, 614012, Russia
² Perm National Research Polytechnic University, Perm, 614990, Russia
³ Northern Trans-Ural State Agricultural University, 7, Republic St., Tyumen, Russia
⁴ Perm State Agrarian-Technological University named after academician D N Pryanishnikov, 23, Petropavlovskaja Str, 614990, Perm
⁵ Tyumen Industrial University, Tyumen, Russia

Abstract

Chlamydia belongs to such diseases, in which the blood-brain barrier permeability is disturbed leading to degenerative changes of brain cells and development of neurological symptoms in animals. Chlamydiae disrupt the barrier function of endothelium, which inside blood vessels forms a semipermeable barrier between the contents of vessels and surrounding tissues. As a result of this process, part of the endothelial cytes slough into the lumen of blood vessels and destroying, contributes to the generalization of infection in the body. Chlamydia infection affecting mammals and birds is caused by antigenically related microorganisms from the Chlamydiacea family. Under animal chlamydia a whole range of diseases is considered, which, due to their polymorphic nature, cannot be united by a specific symptom complex, and sometimes affect all systems and organs. Due to the lack of organotropism and host specificity in different representatives of chlamydiae, the clinic of chlamydiae is extremely diverse. As a diagnosis of this disease, as well as the accuracy of the results, the histological method of examination of pathological material is used. In the process of the conducted research qualitative and quantitative characteristics of pathomorphological changes of cellular structures were determined, with the identification of indicators. All pathological processes occurring in the cell of the organism we have divided into three main groups: cell membrane pathology, cell membrane pathology, and Mitochondria pathology. We developed a decision support module for preliminary diagnosis of pathologies. A truth table of the relationship between indicators and pathology groups was developed. Minimization of disjunctive normal form was carried out using finite automata theory.