Simulating of human physiological supersystems: interactions of cardiovascular, thermoregulatory and respiratory systems
Special quantitative model of the human thermoregulatory system (MTS) functioning with cardiovascular and lung systems is created. These systems form a human physiological supersystem (HPSS). MTS describes thermoregulatory responses to alterations of both external environmental physical characterist...
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pp_isofts_kiev_ua-article-5842024-04-28T11:55:00Z Simulating of human physiological supersystems: interactions of cardiovascular, thermoregulatory and respiratory systems Симулятор фізіологічних надсистем лю- дини: взаємодія систем кровообігу, терморегуляції та зовнішнього дихання Grygoryan, R.D. Degoda, A.G. Lyudovyk, T.V. Yurchak, O.I. physical health; cell energy balance; control mechanisms;quantitative models; simulator UDC 517.958:57 +519.711.3 + 612.51.001 фізичне здоров’я; енергетичний баланс клітини; механізми управління; кількісні моделі; симулятор УДК 517.958:57 +519.711.3 + 612.51.001 Special quantitative model of the human thermoregulatory system (MTS) functioning with cardiovascular and lung systems is created. These systems form a human physiological supersystem (HPSS). MTS describes thermoregulatory responses to alterations of both external environmental physical characteristics and internal biological characteristics. Algorithms provide designing of scenarios including simulation of either short-time or long-time (hours or days) observations. Input data include different combinations of environmental variables (air or water temperature, air humidity, wind or water flow speed, light intensity, infrared radiation) for a naked or wear human, as well as for given dynamics of biological characteristics (rate of heat production including its components associated with metabolism and ATP molecules leasing during mental and physical activities). Human body is presented by a core, blood, and a skin compartments. Skin and lung evaporation are under hypothalamic control based on afferent impulse patterns from internal, and skin heat and cold receptors. Dynamic output data include blood, hypothalamic, and skin temperatures, hemodynamic parameters like heart rate, cardiac output, regional blood flows, vascular resistances, blood pressures, and regional blood volumes. Serotonin and melatonin concentrations modulating biological heat production rate are associated with a day/night light intensity. Currently, the PCbased simulator is autonomous software to be used both for educational purposes and for providing of special computer research. In a near future, this simulator has to be widened by models of kidneys, and a mechanism of liverpancreas interaction.Problems in programming 2023; 3: 81-90 Створено спеціальну кількісну модель взаємодії терморегуляторної системи (МТС) людини із серцево-судинною та легеневою системами. Ці системи утворюють фізіологічну суперсистему людини (ФССС). MTС описує реакції терморегуляції на зміни фізичних характеристик зовнішнього середовища та внутрішніх біологічних характеристик. Алгоритми забезпечують сценарії моделювання короткочасних або тривалих (години чи дні) спостережень. Вхідні дані включають різні комбінації змінних навколишнього середовища (температура повітря або води, вологість повітря, швидкість вітру, інтенсивність світла) для голої або одягненої людини, а також для заданої динаміки біологічних характеристик (швидкість теплопродукції, включаючи його компоненти, пов’язані з метаболізмом і виділенням молекул АТФ під час розумової та фізичної діяльності). Організм людини представлений відділами серцевини, крові та шкіри. Випаровування шкіри та легенів контролюється гіпоталамусом на основі аферентних імпульсів від внутрішніх і шкірних теплових і холодових рецепторів. Динамічні вихідні дані включають температуру крові, гіпоталамуса та шкіри, гемодинамічні параметри, такі як частота серцевих скорочень, серцевий викид, регіональні кровотоки, судинний опір, артеріальний тиск і регіональні об’єми крові. Концентрація серотоніну та мелатоніну, яка регулює швидкість виробництва біологічного тепла, пов’язана з денною/нічною інтенсивністю світла. На сьогоднішній день симулятор на базі ПК є автономним програмним забезпеченням (мова С+) для використання як у навчальних цілях, так і для проведення спеціальних комп’ютерних досліджень. Найближчим часом цей симулятор має бути розширений моделями нирок та механізму взаємодії печінки та підшлункової залози.Prombles in programming 2023; 3: 81-90 Інститут програмних систем НАН України 2023-10-06 Article Article application/pdf https://pp.isofts.kiev.ua/index.php/ojs1/article/view/584 10.15407/pp2023.03.081 PROBLEMS IN PROGRAMMING; No 3 (2023); 81-90 ПРОБЛЕМЫ ПРОГРАММИРОВАНИЯ; No 3 (2023); 81-90 ПРОБЛЕМИ ПРОГРАМУВАННЯ; No 3 (2023); 81-90 1727-4907 10.15407/pp2023.03 en https://pp.isofts.kiev.ua/index.php/ojs1/article/view/584/634 Copyright (c) 2023 PROBLEMS IN PROGRAMMING |
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Problems in programming |
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physical health cell energy balance control mechanisms;quantitative models simulator UDC 517.958:57 +519.711.3 + 612.51.001 |
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physical health cell energy balance control mechanisms;quantitative models simulator UDC 517.958:57 +519.711.3 + 612.51.001 Grygoryan, R.D. Degoda, A.G. Lyudovyk, T.V. Yurchak, O.I. Simulating of human physiological supersystems: interactions of cardiovascular, thermoregulatory and respiratory systems |
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physical health cell energy balance control mechanisms;quantitative models simulator UDC 517.958:57 +519.711.3 + 612.51.001 фізичне здоров’я енергетичний баланс клітини механізми управління кількісні моделі симулятор УДК 517.958:57 +519.711.3 + 612.51.001 |
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Article |
| author |
Grygoryan, R.D. Degoda, A.G. Lyudovyk, T.V. Yurchak, O.I. |
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Grygoryan, R.D. Degoda, A.G. Lyudovyk, T.V. Yurchak, O.I. |
| author_sort |
Grygoryan, R.D. |
| title |
Simulating of human physiological supersystems: interactions of cardiovascular, thermoregulatory and respiratory systems |
| title_short |
Simulating of human physiological supersystems: interactions of cardiovascular, thermoregulatory and respiratory systems |
| title_full |
Simulating of human physiological supersystems: interactions of cardiovascular, thermoregulatory and respiratory systems |
| title_fullStr |
Simulating of human physiological supersystems: interactions of cardiovascular, thermoregulatory and respiratory systems |
| title_full_unstemmed |
Simulating of human physiological supersystems: interactions of cardiovascular, thermoregulatory and respiratory systems |
| title_sort |
simulating of human physiological supersystems: interactions of cardiovascular, thermoregulatory and respiratory systems |
| title_alt |
Симулятор фізіологічних надсистем лю- дини: взаємодія систем кровообігу, терморегуляції та зовнішнього дихання |
| description |
Special quantitative model of the human thermoregulatory system (MTS) functioning with cardiovascular and lung systems is created. These systems form a human physiological supersystem (HPSS). MTS describes thermoregulatory responses to alterations of both external environmental physical characteristics and internal biological characteristics. Algorithms provide designing of scenarios including simulation of either short-time or long-time (hours or days) observations. Input data include different combinations of environmental variables (air or water temperature, air humidity, wind or water flow speed, light intensity, infrared radiation) for a naked or wear human, as well as for given dynamics of biological characteristics (rate of heat production including its components associated with metabolism and ATP molecules leasing during mental and physical activities). Human body is presented by a core, blood, and a skin compartments. Skin and lung evaporation are under hypothalamic control based on afferent impulse patterns from internal, and skin heat and cold receptors. Dynamic output data include blood, hypothalamic, and skin temperatures, hemodynamic parameters like heart rate, cardiac output, regional blood flows, vascular resistances, blood pressures, and regional blood volumes. Serotonin and melatonin concentrations modulating biological heat production rate are associated with a day/night light intensity. Currently, the PCbased simulator is autonomous software to be used both for educational purposes and for providing of special computer research. In a near future, this simulator has to be widened by models of kidneys, and a mechanism of liverpancreas interaction.Problems in programming 2023; 3: 81-90 |
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Інститут програмних систем НАН України |
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2023 |
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https://pp.isofts.kiev.ua/index.php/ojs1/article/view/584 |
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Методи та засоби комп′ютерного моделювання
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УДК 517.958:57 +519.711.3 + 612.51.001 http://doi.org/10.15407/pp2023.03.81
R.D. Grygoryan, A.G. Degoda, T.V. Lyudovyk, O.I.Yurchak
SIMULATING OF HUMAN PHYSIOLOGICAL SUPERSYSTEMS:
INTERACTIONS OF CARDIOVASCULAR, THERMOREGULATORY
AND RESPIRATORY SYSTEMS
A special quantitative model of the human thermoregulatory system (MT) functioning with cardiovascular and
lung systems is created. These systems form a physiological super-system (PSS). For a naked or cloth human,
algorithms provide designing of scenarios including simulation of either short-time or long-time (hours or days)
observations. Input data include different combinations of environmental variables (air or water temperature,
air humidity, wind or water flow speed, light intensity), as well as designing of dynamics for certain biological
characteristics (rate of heat production including its components associated with metabolism and ATP molecules
leasing during mental and physical activities). The human body consists of three compartments – core, blood,
and skin. Dynamic output data include blood, hypothalamic, and skin temperatures, hemodynamic parameters
(heart rate, cardiac output, regional blood flows, vascular resistances, blood pressures, and regional blood vol-
umes), and lung ventilation. Using associations of dynamics of day/night light intensity with concentrations of
serotonin and melatonin hormones, a model for biological heat production rate dynamics is proposed. Currently,
the PC-based simulator is autonomous C+ software. Its users can be both student-medics and physiologists in-
terested in providing theoretical research. Shortly, this simulator has to be widened by models of kidneys and
liver-pancreas interaction mechanism.
Key words: physical health, cell energy balance, control mechanisms,quantitative models, simulator.
Introduction
Human organs and certain anatomi-
cal-functional systems (AFS) form very com-
plex functional systems known as physiologi-
cal super-systems (PSS). The general concept
of human PSS [1-3] explained deep cellular
mechanisms that determine cells interaction
for dynamic providing of every AFS’s opti-
mal parameters. However, traditional empiric
physiology possesses not by research technol-
ogies capable of establishing the main quan-
titative laws ruling the functionalities of PSS.
Potentially, mathematical models could help in
solving of this problem. However, almost all
models were created for solving specific par-
tial problems therefore they not concern the
problem of PSS. To fill this methodological
gap in, we are consequentially creating proper
mathematical models and computer simulators
[4-7]. Their main novelty is in combining of
multi-level physiological mechanisms for ex-
plaining of organism-scale adaptive physio-
logical responses to environmental alterations.
In fact, this approach also creates potentials for
explaining mechanisms that determine the dy-
namic multi-parametric shape of human physi-
cal health (HPH). Such a theoretical fundament
is extreme necessary for the individualization
of the medical assessment of HPH.
The goal of this article is to present our
latest development that made possible theoret-
ical investigations of human thermoregulatory
system under unpredictable challenges from a
certain AFS namely, from the cardiovascular
system (CVS) and lung system.
Mathematical model
of thermoregulatory system
The model of CVS is presented in [6,7],
thus there is no necessity for its de-scription
in detail. Perhaps, it is sufficient to note that
our CVS-model currently is the most complex
model, including in it both mechanisms of cir-
culation’s acute control and mechanisms that
determine the long-term parameters of CVS.
As to our model of the thermoregulatory sys-
tem (MT), the main reason for its creation was
that despite a lot of such models (for example,
[8-14]), MT should be compatible with our
other models.
For solving our problems in the frame
of human PSS, it is sufficient to have an MT
containing three body compartments: a core
© R.D. Grygoryan, A.G. Degoda, T.V. Lyudovyk, O.I.Yurchak, 2023
ISSN 1727-4907. Проблеми програмування. 2023. №3
Методи та засоби комп′ютерного моделювання
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Методи та засоби комп′ютерного моделювання
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Методи та засоби комп′ютерного моделювання
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Методи та засоби комп′ютерного моделювання
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Fig.2. User interface fragment: special window for setting initial data for processing the
thermoregulatory model
Main simulation results
and discussion
As the reader can see in Fig.3, in this
simulation, both air humidity (50%) and the
wind speed (1 m/sec) are stable. It was as-
sumed that the durations of night and day times
are equal. Night time light intensity assumed
to be for 100 times less than it is during the day
time. Both for the sun rise time and for the sun
set time is set 0,5 hour.
Fig.3. Environmental parameters day/night dynamics: Input data
Методи та засоби комп′ютерного моделювання
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Fig.4. Body temperatures day/night (circadian) dynamics: Output data
Fig.5. Day/night (circadian) dynamics of body parameters related to thermoregulation: Output data
Fig.6. Day/night (circadian) dynamics of thermal receptors, serotonin, and melatonin: Output data
Методи та засоби комп′ютерного моделювання
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Fig.7. Day/night (circadian) dynamics of systolic and diastolic arterial pressures: Output data
Fig.8. Day/night (circadian) dynamics of heart rate and lung ventilation: Output data
Output data are presented by tempera-
tures in the core, blood, hypothalamus, and skin
(Fig.4), by 12 characteristics concerning heat,
and cooling (Fig.5), by dynamics of thermal
receptors (heat and cold), and blood concen-
trations of serotonin and melatonin hormones
(Fig.6), by dynamics of systolic and diastolic
pressures (Fig.7), and at last, by dynamics of
heart rate and lung ventilation (Fig.8).
Fig.4 illustrates day/night alterations of
temperatures in modeled body areas while the
last two illustrations obviously show day/night
alterations of pressures and heart rate.
Certainly, our simulator yields much
more output data concerning blood circula-
tion parameters, baroreceptors, and chemo-
receptors activities, and dynamics of main
endocrine hormones modulating not only the
state of CVS but also the state of those body
structures that concern functionality of ther-
moregulatory sys-tem. We do not present this
additional data for two reasons. The first one is
Методи та засоби комп′ютерного моделювання
89
already mentioned above – the paper volume.
The second reason is concerned with the “raw”
state of the MT model. It is not able yet to re-
alistically simulate dynamics. Values of sever-
al constants and variables are included in the
model in conventional units only. We plan to
advance it when all component models will be
created and integrated into the complex simu-
lator of human PSS.
Conclusion
In order to extend the potentials of the
PC-based simulator of the human physiological
super-system (PSS), a special quantitative
model of the human thermoregulatory system
(MT) is created and previously tested for spe-
cific scenarios.
Currently, MT is functioning with mod-
els of cardiovascular and lung systems. MT
describes thermoregulatory responses to alter-
ations of both external environmental physical
characteristics and internal biological character-
istics. Algorithms provide designing of scenar-
ios including simulation of either short-time or
long-time (hours or days) observations. Input
data include different combinations of environ-
mental variables (air or water temperature, air
humidity, wind or water flow speed, light inten-
sity, infrared radiation) for a naked or wear hu-
man, as well as for given dynamics of biological
characteristics (rate of heat production including
its components associated with metabolism and
ATP molecules leasing during mental and phys-
ical activities). Human body is presented by a
core, blood, and a skin compartments. Skin and
lung evaporation are under hypothalamic control
based on afferent impulse patterns from internal,
and skin heat and cold receptors. Dynamic out-
put data include blood, hypothalamic, and skin
temperatures, hemodynamic parameters like
heart rate, cardiac output, regional blood flows,
vascular resistances, blood pressures, and re-
gional blood volumes. Serotonin and melatonin
concentrations modulating biological heat pro-
duction rate are associated with light’s day/night
intensity. Currently, the PC-based simulator is
autonomous soft-ware to be used both for edu-
cational purposes and for providing of special
computer research. In a near future, this simula-
tor has to be widened by models of kidneys, and
a mechanism of liver-pancreas interaction.
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Received: 10.08.2023
About authors:
Grygoryan Rafik,
Department chief, PhD, D-r in biology
Publications number in Ukraine journals – 153
Publications number in English journals – 49.
Hirsch index – 11
http://orcid.org/0000-0001-8762-733X.
Degoda Anna,
Senior scientist, PhD.
Publications number in Ukraine journals – 16.
Publications number in English journals – 1.
Hirsch index – 3.
http://orcid.org/0000-0001-6364-5568.
Lyudovyk Tetyana,
Senior scientist, PhD.
Publications number in Ukraine journals – 31.
Publications number in English journals – 17.
Hirsch index – 5.
https://orcid.org/0000-0003-0209-2001.
Yurchak Oksana,
Leading software engineer.
Publications number in Ukraine journals – 15.
Publications number in English journals – 0.
Hirsch index –0.
https://orcid.org/0000-0003-3941-1555.
Place of work:
Institute of software systems
of Ukraine National Academy of Sciences
03187, Кyїv,
Acad. Glushkov avenue, 40,
Phone.: 526 5169.
Е-mail: rgrygoryan@gmail.com,
anna@silverlinecrm.com,
tetyana.lyudovyk@gmail.com,
daravatan@gmail.com,
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