Literature DB >> 9788987

Use of intrinsic modes in biology: examples of indicial response of pulmonary blood pressure to +/- step hypoxia.

W Huang1, Z Shen, N E Huang, Y C Fung.   

Abstract

Recently, a new method to analyze biological nonstationary stochastic variables has been presented. The method is especially suitable to analyze the variation of one biological variable with respect to changes of another variable. Here, it is illustrated by the change of the pulmonary blood pressure in response to a step change of oxygen concentration in the gas that an animal breathes. The pressure signal is resolved into the sum of a set of oscillatory intrinsic mode functions, which have zero "local mean," and a final nonoscillatory mode. With this device, we obtain a set of "mean trends," each of which represents a "mean" in a definitive sense, and together they represent the mean trend systematically with different degrees of oscillatory content. Correspondingly, the oscillatory content of the signal about any mean trend can be represented by a set of partial sums of intrinsic mode functions. When the concept of "indicial response function" is used to describe the change of one variable in response to a step change of another variable, we now have a set of indicial response functions of the mean trends and another set of indicial response functions to describe the energy or intensity of oscillations about each mean trend. Each of these can be represented by an analytic function whose coefficients can be determined by a least-squares curve-fitting procedure. In this way, experimental results are stated sharply by analytic functions.

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Year:  1998        PMID: 9788987      PMCID: PMC23580          DOI: 10.1073/pnas.95.22.12766

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  24 in total

1.  Engineering analysis of biological variables: an example of blood pressure over 1 day.

Authors:  W Huang; Z Shen; N E Huang; Y C Fung
Journal:  Proc Natl Acad Sci U S A       Date:  1998-04-28       Impact factor: 11.205

2.  Regression of hypoxic hypertension-induced changes in the elastic laminae of rat pulmonary arteries.

Authors:  S Q Liu
Journal:  J Appl Physiol (1985)       Date:  1997-05

3.  Hypoxia induces type II NOS gene expression in pulmonary artery endothelial cells via HIF-1.

Authors:  L A Palmer; G L Semenza; M H Stoler; R A Johns
Journal:  Am J Physiol       Date:  1998-02

4.  Remodeling of the constitutive equation while a blood vessel remodels itself under stress.

Authors:  Y C Fung; S Q Liu; J B Zhou
Journal:  J Biomech Eng       Date:  1993-11       Impact factor: 2.097

5.  Endothelial and subintimal changes in rat hilar pulmonary artery during recovery from hypoxia. A quantitative ultrastructural study.

Authors:  B Meyrick; L Reid
Journal:  Lab Invest       Date:  1980-06       Impact factor: 5.662

6.  Alterations in structure of elastic laminae of rat pulmonary arteries in hypoxic hypertension.

Authors:  S Q Liu
Journal:  J Appl Physiol (1985)       Date:  1996-11

7.  Hypoxia selectively induces proliferation in a specific subpopulation of smooth muscle cells in the bovine neonatal pulmonary arterial media.

Authors:  J D Wohrley; M G Frid; E P Moiseeva; E C Orton; J K Belknap; K R Stenmark
Journal:  J Clin Invest       Date:  1995-07       Impact factor: 14.808

8.  Persistence, re-expression, and induction of pulmonary arterial fibronectin, tropoelastin, and type I procollagen mRNA expression in neonatal hypoxic pulmonary hypertension.

Authors:  A G Durmowicz; W C Parks; D M Hyde; R P Mecham; K R Stenmark
Journal:  Am J Pathol       Date:  1994-12       Impact factor: 4.307

9.  Angiotensin converting enzyme expression is increased in small pulmonary arteries of rats with hypoxia-induced pulmonary hypertension.

Authors:  N W Morrell; E N Atochina; K G Morris; S M Danilov; K R Stenmark
Journal:  J Clin Invest       Date:  1995-10       Impact factor: 14.808

10.  ETA-receptor antagonist prevents and reverses chronic hypoxia-induced pulmonary hypertension in rat.

Authors:  V S DiCarlo; S J Chen; Q C Meng; J Durand; M Yano; Y F Chen; S Oparil
Journal:  Am J Physiol       Date:  1995-11
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  7 in total

1.  Matching gene activity with physiological functions.

Authors:  Wei Huang; Yuh-Pyng Sher; Konan Peck; Yuan Cheng B Fung
Journal:  Proc Natl Acad Sci U S A       Date:  2002-03-05       Impact factor: 11.205

2.  Nonlinear indicial response of complex nonstationary oscillations as pulmonary hypertension responding to step hypoxia.

Authors:  W Huang; Z Shen; N E Huang; Y C Fung
Journal:  Proc Natl Acad Sci U S A       Date:  1999-03-02       Impact factor: 11.205

3.  Can photoplethysmography variability serve as an alternative approach to obtain heart rate variability information?

Authors:  Sheng Lu; He Zhao; Kihwan Ju; Kunson Shin; Myoungho Lee; Kirk Shelley; Ki H Chon
Journal:  J Clin Monit Comput       Date:  2007-11-07       Impact factor: 2.502

4.  Intrinsic frequency for a systems approach to haemodynamic waveform analysis with clinical applications.

Authors:  Niema M Pahlevan; Peyman Tavallali; Derek G Rinderknecht; Danny Petrasek; Ray V Matthews; Thomas Y Hou; Morteza Gharib
Journal:  J R Soc Interface       Date:  2014-09-06       Impact factor: 4.118

Review 5.  A systems approach to tissue remodeling.

Authors:  Ghassan S Kassab
Journal:  J Biomech Eng       Date:  2009-10       Impact factor: 2.097

6.  Tissue remodeling of rat pulmonary arteries in recovery from hypoxic hypertension.

Authors:  Zhuangjie Li; Wei Huang; Zong Lai Jiang; Hans Gregersen; Yuan-Cheng Fung
Journal:  Proc Natl Acad Sci U S A       Date:  2004-07-26       Impact factor: 11.205

7.  Profiling cellular morphodynamics by spatiotemporal spectrum decomposition.

Authors:  Xiao Ma; Onur Dagliyan; Klaus M Hahn; Gaudenz Danuser
Journal:  PLoS Comput Biol       Date:  2018-08-02       Impact factor: 4.475

  7 in total

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