SUBSTANTIATION OF CONCEPTUAL APPARATUS FOR MATHEMATICAL STUDIES ON THE HORMONE-PRODUCING CELLS ACTIVITY
About the author:
Ryabukha O. І.
METHODS AND METHODOLOGIES
Type of article:
Despite the opportunities opened by the use of modern diagnostic equipment, fundamental approaches to research in medicine remain largely empirical: studying the state and activities of any system is mainly performed through improvement of already existing areas or techniques. However, establishing the operation regularities of such a complicated biological system as the cell, requires creation of new research concepts, particularly the development and implementation of innovative expert systems for assessing changes in its state under the impact of various factors. Pathology of the thyroid gland occupies a significant place in the structure of general morbidity. Available information on the high sensitivity of this organ to various damaging factors confirms the need to deepen the study of its functioning, particularly, in clarifying features of the hormonopoiesis course under normal conditions and pathology. However, despite the undoubted importance of creating new approaches to elucidation of the causes and studying the mechanisms of adaptation processes and maladaptation development in the gland at the cellular and subcellular levels, mathematical technologies for objectivating the links between the thyrocyte organelles and between its cellular environment are not sufficiently developed. The present study is devoted to clarifying the conceptual apparatus for the mathematical research of the hormone-producing cells activity at the ultrastructural level of their organization. The step-by-step algorithm of the study is presented on the example of a follicular thyrocyte. Analysis of electron diffraction patterns, made according to generally recognized procedures, starts with the theoretical definition of the ultrastructures significant for implementation of a particular cell activity field. The following steps are digital assessment of their number and status and establishment of correlation links between them. The most functionally significant organelles are designated as “supporting”. On the basis of “factual” signs (ultrastructures of the studied field, between which significant correlation links have been traced), an individual correlation portrait is constructed as a variant of the correlation net. Referencing the “supporting” and “factual” features nomenclature, their comparison with the nomenclatures and the “nodal points” filling (locations of the largest correlation links aggregates) permit both to specify and generalize the obtained data on the state of organelles in each field of the hormone-producing cell’s activity. If considered necessary to deepen the study, determined are the organelle that has the most functional significance for the cell activity studies (“feedback system”), and another factor impacting the organelle (“action system”). In the “feedback system”, the “feedback object” is defined as the constituent element undergoing the greatest changes caused by the “action object”. In the “action object”, “points of action” are defined: the subsystems having the most links, particularly, significant ones. Since the activity of all the constituent elements is interconnected in a single biological system, determined are the elements outside the studied system and the most sensitive to it (the “attraction system”) and those components and sub-components which are the most greatly influenced by the studied conditions (“attraction objects” and “points of attraction”). In this case, the interaction between “points of feedback” and “points of attraction” is mediated by “points of action”, and becomes the basis for creating an integrative model of the hormone-producing cell’s activity. Practical implementation of the developed conceptual apparatus permits to investigate more intimate mechanisms of hormonopoiesis, to establish the most significant interconnections and interactions within the limits of the studied system and the systems associated with it, to characterize each field of the hormone-producing cell’s activity, to clarify their features, and to determine the potential and spare capacities of the cell.
mathematical technologies in medicine, thyroid gland, thyrocyte, correlation analysis, correlation nets
- Avtandilov GG. Meditsinskaya morfometriya: rukovodstvo. Moskva: Meditsina; 1990. 384 s. [in Russian].
- Gubler EV, Genkin AA. Primeneniye neparametricheskikh kriteriyev statistiki v mediko-biologicheskikh issledovaniyakh. Leningrad: Meditsina; 1973. 143 s. [in Russian].
- Davydovskiy IV. Obshchaya patologiya cheloveka. 2-ye izd. Moskva: Meditsina; 1969. Vvedeniye; s. 15-37. [in Russian].
- Teppermen Dzh, Teppermen Kh. Fiziologiya obmena veshchestv i endokrinnoy sistemy; per. s angl. Moskva: Mir; 1989. 656 s. [in Russian].
- Kettayl VM, Arki RA. Patofiziologiya endokrinnoy sistemy; per. s angl. Moskva: Izdatel’stvo BINOM; 2016. 336 s. [in Russian].
- Khripkov IS. Sostoyaniye mestnykh regulyatornykh sistem shchitovidnoy zhelezy pri eksperimental’nom blastomogeneze. V: Tverdokhlib IV, redactor. Materialy III Vseukr. nauk. morfolohich. konf. Karpovs’ki chytannya; 2006 Kvit 11-14; Dnipropetrovs’k. Dnipropetrovs’k: Porohy; 2006, s. 70-2. [in Russian].
- Ryabukha OІ. Ul’trastrukturni osoblyvosti syntetychnoyi diyal’nosti folikulyarnykh tyrotsytiv pry pryymanni orhanichnoho yodu v umovakh alimentarnoho yododefitsytu. Visn. problem biol. i med. 2017;2(140):134-9. [in Ukrainian].
- Ryabukha OІ. Doslidzhennya syntetychnoyi diyal’nosti folikulyarnykh tyrotsytiv pry pryymanni neorhanichnoho yodu v umovakh alimentarnoho yododefitsytu. Visn. problem biol. i med. 2017;3(141):218-23. DOI: 10.29254/2077-4214-2017-4-3-141-218-23 [in Ukrainian].
- Ryabukha OI. Perspektyvy zastosuvannya novykh pidkhodiv do vprovadzhennya matematychnykh tekhnolohiy dlya vyvchennya diyal’nosti klityny. Medychna informatyka ta inzheneriya. 2018;1:67-75. DOI: 10.11603/mie.1996-1960.2018.1.8894 [in Ukrainian].
- Lutsenko MT. Tsitofiziologiya. Novosibirsk; Blagoveshchensk: SO RAMN; 2011. 216 s. [in Russian].
- Ryabukha OІ. Ob’’yektyvizatsiya morfofunktsional’noho stanu tyrotsyta shlyakhom vyznachennya profiliv yoho spetsial’nykh mozhlyvostey. Tavricheskiy medico-biologicheskiy vestnik. 2006;9(3/3):156-8. Dostupno: https://drive.google.com/file/d/1d7vWEk0C0eERR0YtNEZuvTDB55oFjY2/view?usp=sharing [in Ukrainian].
- Plashchevaya EV, Smirnov VA, Nigej NV, Lysak VA. Osnovnyye vidy vrachebnoy logiki. V: Posobiye dlya prakticheskikh zanyatiy po meditsinskoy informatike. Blagoveshchensk: AGMA; 2014. s. 176. [in Russian].
- Batushansky A, Toubiana D, Fait A. Correlation-Based Network Generation, Visualization, and Analysis as a Powerful Tool in Biological Studies: A Case Study in Cancer Cell Metabolism. BioMed Research International. 2016; ID 8313272:9. Available from: http://dx.doi. org/10.1155/2016/8313272
- Murray JD. Mathematical Biology ІІ: Spatial Models and Biomedical Applications (Interdisciplinary applied mathematics). 3rd ed. New York: Springer. 2003;18:811.
Publication of the article:
«Bulletin of problems biology and medicine» Issue 3 (145), 2018 year, 234-237 pages, index UDK 611.441-018.1:001.4