Literature DB >> 22426223

Network physiology reveals relations between network topology and physiological function.

Amir Bashan1, Ronny P Bartsch, Jan W Kantelhardt, Shlomo Havlin, Plamen Ch Ivanov.   

Abstract

The human organism is an integrated network where complex physiological systems, each with its own regulatory mechanisms, continuously interact, and where failure of one system can trigger a breakdown of the entire network. Identifying and quantifying dynamical networks of diverse systems with different types of interactions is a challenge. Here we develop a framework to probe interactions among diverse systems, and we identify a physiological network. We find that each physiological state is characterized by a specific network structure, demonstrating a robust interplay between network topology and function. Across physiological states, the network undergoes topological transitions associated with fast reorganization of physiological interactions on time scales of a few minutes, indicating high network flexibility in response to perturbations. The proposed system-wide integrative approach may facilitate the development of a new field, Network Physiology.

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Year:  2012        PMID: 22426223      PMCID: PMC3518900          DOI: 10.1038/ncomms1705

Source DB:  PubMed          Journal:  Nat Commun        ISSN: 2041-1723            Impact factor:   14.919


  32 in total

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5.  A phylogenetic analysis of sleep architecture in mammals: the integration of anatomy, physiology, and ecology.

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7.  Scaling behaviour of heartbeat intervals obtained by wavelet-based time-series analysis.

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Review 9.  Multiple organ failure. Pathophysiology and potential future therapy.

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  122 in total

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Review 5.  Evidence for a Coupled Oscillator Model of Endocrine Ultradian Rhythms.

Authors:  Azure D Grant; Kathryn Wilsterman; Benjamin L Smarr; Lance J Kriegsfeld
Journal:  J Biol Rhythms       Date:  2018-08-22       Impact factor: 3.182

6.  Delay-correlation landscape reveals characteristic time delays of brain rhythms and heart interactions.

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7.  Predictability decomposition detects the impairment of brain-heart dynamical networks during sleep disorders and their recovery with treatment.

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9.  A network model of correlated growth of tissue stiffening in pulmonary fibrosis.

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10.  Disentangling cardiovascular control mechanisms during head-down tilt via joint transfer entropy and self-entropy decompositions.

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Journal:  Front Physiol       Date:  2015-10-27       Impact factor: 4.566

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