Всеобъемлющее понимание болезни и здоровья

Мау Й.

10.11.16, Четверг, 15:00, ИПУ им. В.А.Трапезникова РАН, ауд.7

Базовый семинар: Математическое моделирование и системная биология

Introduction: Preserving health and combating diseases in human populations needs a comprehensive view of human body life context. With elapsing time as the decisive factor in course and life, evolving interactionsbetween functional ‘entities’ come into focus. Systems approaches model interactions as energy (mass, information) transfers; obtained models serve to study conditions for maintaining a dynamic equilibrium and the system’s vulnerability to challenges from transient random disturbances or systematic changes.
With its focus on system-wide coordination of in-system interactions between functional subsystems andtheir roles in body system exchanges of energy with its ‘world outside’, Biokybernetik(engl. bio-automation) aims at a holistic understanding of human body's functional and a person's operational management and control systems from an engineering perspective.

Methods: Automation-engineering systems-control concepts provide a unifying methodology. Systems are sets of interactive componentsthat permanently exchange energy (information, mass) within a structure of internal relations, stimulated by internal and external ‘driving forces’; complexity arises from components that are embedded systems by themselves, creating hierarchy; adaptivenessis an emergentsystem property due to feed-back control loops across all levels of hierarchy. Wiener-sense Kybernetik separates an organizational part from the material part in functional energy transfers. For quantification, dynamic systems equations and in silico experimentation with agent-based models offer challenging opportunities.

To address human body ‘surroundings’, concept GeneSEES (Genetics, Systems medicine, Environmental exposures, Economic and Social settings) integrates individual health and disease modifying factors in genetics, environmental and socio-economic surroundings for study of impact on physiology and behavior.

Results: Implied ‘kybernetic’ understanding of health rests on functional and operational management and control capacity of a human body system that balances out disturbances or compensates systematic changes of energy transfers between interactive components.

In human body, interactive componentsare cells, tissues, and organs as functional unitsthat combine to functional aggregates [1,3] and functional groups [2,3]; in society, it is persons and social groups, again with higher-level organization [4]. Structures of relations are implemented by the nervous and hormone systems for physiology, by legislation, habitual procedures etc. for behavior. ‘Driving forces’ are set by human body design motifs [1, 3], and by policy motifsin society.

Human body disordersarise from internal random variation in processes or their protocols, or from exposures that surpass potentials for autonomous maintenance and repair. Supplementing reductionism, it is disorders of interactions between, e.g., cerebral operational control, functional control, energy supply and waste disposal, protective response, muscular-skeletal and reproductive functions, and communication subsystems, that would arouse particular interest.

Population-level healthpolicy aims at social groups for implementation ofprotective measures in occupation and nutrition, product and traffic safety, health service management and care delivery.

Health-related factors are in environment (living-nature cohabitation, civilization, geographic setting), economic opportunities(access to base resources, education and productivity for living, health insurance, social security, welfare system participation) and social embedding (family, housing neighborhood, workplace, socializing leisure activities).

Conclusions: Permanent energy exchanges between human body and its surroundings let exposures, diseases and interventions exist only in systems context. Biokybernetik makes ground-laying methodology for empirical studies of integrative clinical characterizations, molecular profiling and bio-systems modeling of diseases and impact of medical interventions, best in ethnically varying human populations with genetic admixing [5].

References:

  1. Mau, J. (2016). On reverse engineering of human body system. In: CEUR Workshop Proceedings, 2016; 1638:pp.622-635. DOI: 10.18287/1613-0073-2016-1638-622-635.
  2. Mau, J. (2016). Systems Neuroergonomics. In: Advances in Cognitive Neuroscience (V), Wang RB, Pan XC (eds.), Springer Science+Business Media Singapore, 2016: pp. 431-437. DOI 10.1007/978-981-10-0207-659.
  3. Mau, J. (2016). Kybernetic Modeling of Human Body System. In: Proceedings of the 12th Russian-GermanConference on Biomedical Engineering, Suzdal,4-7 July 2016, L.T. Sushkova, S.V. Selishev, Z.M. Yuldashev, S.I .Shukin (eds), Vladimir State University named after Alexander and Nikolay Stoletovs, Vladimir, Russia, (ISBN 978-5-905527-12-8) pp.11-15.
  4. Mau, J. (2015). Systems modeling in epidemiology. Abstract. In: 10. Jahrestagung der Deutschen Gesellschaft fur Epidemiologie. 30. September bis 2. Oktober 2015, Potsdam, Griebnitzsee.Boeing H (ed.), Deutsches Institut fur Ernahrungsforschung Potsdam-Rehbrucke, Nuthetal, Germany, pp.94-95.
  5. Mau, J. (2014). Eine kontinentubergreifende Zusammenarbeit in Hochschulmedizin und Gesundheit im nordlichen Eurasien. Strukturkonzept. [Transcontinental Collaboration in Health and Academic Medicine across Northern Eurasia. A Structural Concept.] iqmeth Institut fur Quantitative Methodik- Privates Akademisches Beratungsburo fur Forschung und Entwicklung, Krefeld, Germany.

 

Следующий семинар: 17.01.2018 - О микро–макро иерархии (докладчик: Богомолов С.В.).

Предыдущий семинар: 26.02.2016 - Современные математические модели медицинской информатики: От статистики до интеллектуального анализа данных (докладчик: Незнанов А.А.).