Causative relationships of microbiota with the human’s health and diseases are one of the most challenging issues in modern microbiology. Progress in this field could provide new tools for diagnosis, prophylaxis, and treatment. A new automated approach is proposed, as an addition to the methods of multidimensional statistical analysis. This approach is based on a planar projection of multidimensional analytical data and is distinguished by technological simplicity and clarity of the process of operational diagnostics.
Aim of the study was to apply a new automated approach based on the method of mapping diagnostic fields to determine the informative parameters and the main patterns of eubiosis / dysbiosis of the human large intestine, and the development of chronic prostatitis with fertility loss in men.
Materials and methods. Using the method of mapping diagnostic fields, whose geometrization is based on multidimensional observations of the state of each subject, the dimension of the feature space is determined by calculating the resultant of each feature vector and for calculating the Voronoi diagram - a diagnostic palette. Two samples were used in the work: the first consisted of 126 strains isolated from 65 individuals examined for colon dysbiosis (18–45 years old), the second consisted of 124 tests taken from 73 men of reproductive age (20–45 years old).
Results. The cartography method of the resultants creates easily interpretable graphic documents based on the initial data and contributes to the prompt recognition of unknown states/diagnoses. The created cartograms remove the limitations of perspective visualization of multidimensional objects and significantly simplify data interpretation.
Conclusions. The effectiveness of cartographic diagnostics has been confirmed by comparing its results with clinical ones. Both initial observations and statistically processed material can be used as data.
References
1. Бухарин О.В., Перунова Н.Б. Микрoсимбиоценоз. Екатеринбург: УрО РАН, 2014. — 257 с.
2. Бухарин О.В., Перунова Н.Б., Иванова Е.В. Бифидофлора при ассоциативном симбиозе человека. Екатеринбург: УрО РАН, 2014. 212 с.
3. Davenport ER, et al. The human microbiome in evolution. BMC Biol. 2017; 15(1): 127.
4. Gavin PG, et al. Hamilton-Williams E.E. Intestinal metaproteomics reveals host-microbiota interactions in subjects at risk for type 1 diabetes. Diabetes Care. 2018; 41: 2178–2186.
5. Winter SE, Lopez CA, Bäumler AJ. The dynamics of gut-associated microbial communities during inflammation. EMBO Rep. 2013; 14(4): 319-327.
6. Бухарин О.В. и др. Иммунорегуляторный профиль микросимбионтов кишечного биотопа человека // Журнал микробиологии, эпидемиологии и иммунобиологии. — 2018. —№4. — С.42-51.
7. Шевырин А.А. и др. Диагностика и лечение пациентов с инфертильностью, развившейся на фоне хронического простатита // РМЖ. — 2020. — №13. — С.6-9.
8. Ефремов Е. А., Касатонова Е. В., Симаков В. В. Возможная роль предстательной железы в формировании идиопатического мужского бесплодия // Лечебное дело. — 2019. — №3. — С.74-80.
9. Бухарин О.В. и др. Характеристика микробиоты и цитокинового профиля спермоплазмы у больных хроническим бактериальным простатитом // Урология. — 2020. — №5. — С.276-282.
For citation
Nikiforov I.A., Ivanova E.V. Method of mapping resultants in solving problems of medical microbiology. Medical doctor and information technology. 2022; 3: 14-23. doi: 10.25881/18110193_2022_3_14.
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