Literature DB >> 12067242

Quantitative dual-probe microdialysis: mathematical model and analysis.

Kevin C Chen1, Malin Höistad, Jan Kehr, Kjell Fuxe, Charles Nicholson.   

Abstract

Steady-state microdialysis is a widely used technique to monitor the concentration changes and distributions of substances in tissues. To obtain more information about brain tissue properties from microdialysis, a dual-probe approach was applied to infuse and sample the radiotracer, [3H]mannitol, simultaneously both in agar gel and in the rat striatum. Because the molecules released by one probe and collected by the other must diffuse through the interstitial space, the concentration profile exhibits dynamic behavior that permits the assessment of the diffusion characteristics in the brain extracellular space and the clearance characteristics. In this paper a mathematical model for dual-probe microdialysis was developed to study brain interstitial diffusion and clearance processes. Theoretical expressions for the spatial distribution of the infused tracer in the brain extracellular space and the temporal concentration at the probe outlet were derived. A fitting program was developed using the simplex algorithm, which finds local minima of the standard deviations between experiments and theory by adjusting the relevant parameters. The theoretical curves accurately fitted the experimental data and generated realistic diffusion parameters, implying that the mathematical model is capable of predicting the interstitial diffusion behavior of [3H]mannitol and that it will be a valuable quantitative tool in dual-probe microdialysis.

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Year:  2002        PMID: 12067242     DOI: 10.1046/j.1471-4159.2002.00792.x

Source DB:  PubMed          Journal:  J Neurochem        ISSN: 0022-3042            Impact factor:   5.372


  9 in total

Review 1.  Diffusion in brain extracellular space.

Authors:  Eva Syková; Charles Nicholson
Journal:  Physiol Rev       Date:  2008-10       Impact factor: 37.312

2.  Unifying the mathematical modeling of in vivo and in vitro microdialysis.

Authors:  Peter M Bungay; Rachita K Sumbria; Ulrich Bickel
Journal:  J Pharm Biomed Anal       Date:  2011-01-19       Impact factor: 3.935

3.  A model for simulation and patient-specific visualization of the tissue volume of influence during brain microdialysis.

Authors:  Elin Diczfalusy; Peter Zsigmond; Nil Dizdar; Anita Kullman; Dan Loyd; Karin Wårdell
Journal:  Med Biol Eng Comput       Date:  2011-11-13       Impact factor: 2.602

Review 4.  Volume transmission and its different forms in the central nervous system.

Authors:  Kjell Fuxe; Dasiel O Borroto-Escuela; Wilber Romero-Fernandez; Wei-Bo Zhang; Luigi F Agnati
Journal:  Chin J Integr Med       Date:  2013-05-15       Impact factor: 1.978

5.  Insulin and contraction increase nutritive blood flow in rat muscle in vivo determined by microdialysis of L-[14C]glucose.

Authors:  John M B Newman; Renee M Ross; Stephen M Richards; Michael G Clark; Stephen Rattigan
Journal:  J Physiol       Date:  2007-09-20       Impact factor: 5.182

Review 6.  Microdialysis as an Important Technique in Systems Pharmacology-a Historical and Methodological Review.

Authors:  Margareta Hammarlund-Udenaes
Journal:  AAPS J       Date:  2017-07-31       Impact factor: 4.009

7.  Extrasynaptic neurotransmission in the modulation of brain function. Focus on the striatal neuronal-glial networks.

Authors:  Kjell Fuxe; Dasiel O Borroto-Escuela; Wilber Romero-Fernandez; Zaida Diaz-Cabiale; Alicia Rivera; Luca Ferraro; Sergio Tanganelli; Alexander O Tarakanov; Pere Garriga; José Angel Narváez; Francisco Ciruela; Michele Guescini; Luigi F Agnati
Journal:  Front Physiol       Date:  2012-06-04       Impact factor: 4.566

Review 8.  The need for mathematical modelling of spatial drug distribution within the brain.

Authors:  Esmée Vendel; Vivi Rottschäfer; Elizabeth C M de Lange
Journal:  Fluids Barriers CNS       Date:  2019-05-16

9.  Improving the Prediction of Local Drug Distribution Profiles in the Brain with a New 2D Mathematical Model.

Authors:  E Vendel; V Rottschäfer; E C M de Lange
Journal:  Bull Math Biol       Date:  2018-08-08       Impact factor: 1.758

  9 in total

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