The Volume Available to Diffusion in the Muscle Fiber

1974 ◽  
Vol 52 (4) ◽  
pp. 814-828 ◽  
Author(s):  
J. P. Caillé ◽  
J. A. M. Hinke
Keyword(s):  
Diffusion Coefficient ◽  
Muscle Fiber ◽  
Diffusion Coefficients ◽  
Pure Water ◽  
Bound Water ◽  
Water Volume ◽  
Glass Capillary ◽  
Fiber Volume ◽  
Binding Effect ◽  
Polyelectrolyte Solutions

Intrafiber diffusion of 3HOH, dimethyl-3H-sulfoxide (DMSO), D-14C-sorbitol, and 36Cl was measured along the longitudinal axis of the single muscle fiber (Balanus nubilus) that had been placed inside the lumen of a glass capillary at least 24 h beforehand. When the fiber contained 75% water, the mean self-diffusion coefficients (× 10−5 cm2/s) at 10 °C and at pH 7.5 were 0.908 ± 0.008 for water, 0.418 ± 0.008 for DMSO, 0.216 ± 0.005 for sorbitol, and 0.683 ± 0.006 for chloride. These diffusion coefficients in myoplasm were 0.53–0.58 times the values in pure water. Diffusions of the above were also measured in fibers with reduced water content, as low as 45% by weight. In all cases, the diffusion coefficient decreased in proportion to the reduction in the fiber water. With the aid of Wang's theory for diffusion in polyelectrolyte solutions, we have attempted to separate the "obstruction effect" from the "binding effect", both of which operate to reduce the diffusion coefficient of substances in the myoplasm. Our analysis indicates that the diffusible volume in myoplasm (75% water) for all substances is about 80% of the water volume or 65% of the fiber volume. So-called "bound" water in myoplasm is estimated to be 0.57 g water per gram dry weight.

scholarly journals Combined bound water and water vapour diffusion of Norway spruce and European beech in and between the principal anatomical directions

Holzforschung ◽  
2011 ◽  
Vol 65 (6) ◽  
pp. 819-828 ◽  
Author(s):  
Walter Sonderegger ◽  
Manuele Vecellio ◽  
Pascal Zwicker ◽  
Peter Niemz
Keyword(s):  
Diffusion Coefficient ◽  
Steady State ◽  
Water Vapour ◽  
Diffusion Coefficients ◽  
Bound Water ◽  
European Beech ◽  
Unsteady State ◽  
Water Vapour Diffusion ◽  
Vapour Diffusion ◽  
Water Vapour Resistance

Abstract The combined bound water and water vapour diffusion of wood is of great interest in the field of building physics. Due to swelling stresses, the steady-state-determined diffusion coefficient clearly differs from the unsteady-state-determined diffusion coefficient. In this study, both diffusion coefficients and the water vapour resistance factor of Norway spruce (Picea abies [L.] Karst.) and European beech (Fagus sylvatica L.) were investigated for the principal anatomical directions (radial, tangential and longitudinal) and in 15° steps between these directions. The values were determined with the cup method as the basic principle. The unsteady-state-determined diffusion coefficient is, independent of the direction, about half that of the steady-state-determined diffusion coefficient. Both diffusion coefficients are about two to three times higher for spruce than for beech. They are up to 12 times higher in the longitudinal direction than perpendicular to the grain for spruce, and up to 15 times higher for beech. With increasing moisture content, the diffusion coefficients exponentially increase. The water vapour resistance factor shows converse values to the diffusion coefficients.

Evidence for K+ and Cl− Binding Inside Muscle from Diffusion Studies

1973 ◽  
Vol 51 (5) ◽  
pp. 390-400 ◽  
Author(s):  
J. P. Caillé ◽  
J. A. M. Hinke
Keyword(s):  
Diffusion Coefficients ◽  
Binding Capacity ◽  
Dry Weight ◽  
Longitudinal Axis ◽  
Single Muscle ◽  
Glass Capillary ◽  
Diffusion Data ◽  
Diffusion Studies ◽  
The Mean ◽  
Polyelectrolyte Solutions

Intrafiber diffusion of 42K+, 36Cl−, and 14C-sorbitol was measured along the longitudinal axis of a single muscle fiber which had been placed inside the lumen of a glass capillary at least 24 h beforehand. The mean diffusion coefficients (× 10−5 cm2/s) in myoplasm at 10 °C and at pH 7.5 were 0.728 ± 0.008, 0.683 ± 0.006, and 0.216 ± 0.005 for K+, Cl−, and sorbitol, respectively. The K+ coefficient decreased, the Cl− coefficient increased, and the sorbitol coefficient remained unchanged as the pH of the muscle-capillary preparation was increased. By applying Wang's theory to explain diffusion in polyelectrolyte solutions (1954), we have estimated the diffusible volume (1 − ϕ) and the binding fractions (ƒK and ƒCl) of K+ and Cl− in myoplasm. From pH 5.2 to 10, ƒK varied from 0 to 0.13 and ƒCl varied from 0.13 to 0. Analysis of this K+ diffusion data along with the Na+ diffusion data from an earlier study (Can. J. Physiol. Pharmacol. 50, 228–237, 1972) leads to the prediction that myoplasm at physiological pH has a minimum binding capacity for Na+ and K+ of about 70 mmol/kg dry weight and a selectivity of 3.3 for Na+ over K+. Estimations of the diffusible volume ranged from 0.7 to 0.8, indicating that probably all the intrafiber water (74–78% by weight) is being utilized in the diffusion process.

Evidence for Na Sequestration in muscle from Na Diffusion Measurements

1972 ◽  
Vol 50 (3) ◽  
pp. 228-237 ◽  
Author(s):  
J. P. Caillé ◽  
J. A. M. Hinke
Keyword(s):  
Muscle Fiber ◽  
Diffusion Coefficients ◽  
Negative Charge ◽  
Longitudinal Axis ◽  
The Self ◽  
Theoretical Curve ◽  
Single Muscle ◽  
Glass Capillary ◽  
Single Muscle Fiber ◽  
Self Diffusion

Intrafiber diffusion of 22Na and 14C-sorbitol was measured along the longitudinal axis of a single muscle fiber which had been placed inside the lumen of a glass capillary at least 24 h beforehand. Compared to their diffusion in 1% agar, the self-diffusion coefficients of 22Na at 10 °C (0.438 × 10−5 cm2/s) and 14C-sorbitol (0.216 × 10−5 cm2/s) were reduced by a factor of 2 when intrafiber pH was 7.5. However, the theoretical and experimental concentration–distance profile curves only matched for 14C-sorbitol but not for 22Na. In the latter case, the experimental curves were consistently higher than the theoretical curve indicating an excess accumulation of 22Na at all x values (axis distance). This Na accumulation was found to be highly dependent on the pH inside the fiber. From pH 10.1 to 5.2, the fraction of excess Na (excess 22Na per total 22Na at a given x) decreased from 0.34 to zero. We interpret this excess Na to be a measure of the amount of myoplasmic Na which is acting as counterion for the fixed negative charge on the contractile filaments.

scholarly journals Effect of Modification on the Fluid Diffusion Coefficient in Silica Nanochannels

Molecules ◽  
2021 ◽  
Vol 26 (13) ◽  
pp. 4030
Author(s):  
Gengbiao Chen ◽  
Zhiwen Liu
Keyword(s):  
Diffusion Coefficient ◽  
Diffusion Coefficients ◽  
Surface Effect ◽  
Bulk Water ◽  
Self Diffusion ◽  
Average Diffusion Coefficient ◽  
Average Diffusion ◽  
Chain Lengths ◽  
Fluid Diffusion ◽  
Self Diffusion Coefficient

The diffusion behavior of fluid water in nanochannels with hydroxylation of silica gel and silanization of different modified chain lengths was simulated by the equilibrium molecular dynamics method. The diffusion coefficient of fluid water was calculated by the Einstein method and the Green–Kubo method, so as to analyze the change rule between the modification degree of nanochannels and the diffusion coefficient of fluid water. The results showed that the diffusion coefficient of fluid water increased with the length of the modified chain. The average diffusion coefficient of fluid water in the hydroxylated nanochannels was 8.01% of the bulk water diffusion coefficient, and the diffusion coefficients of fluid water in the –(CH2)3CH3, –(CH2)7CH3, and –(CH2)11CH3 nanochannels were 44.10%, 49.72%, and 53.80% of the diffusion coefficients of bulk water, respectively. In the above four wall characteristic models, the diffusion coefficients in the z direction were smaller than those in the other directions. However, with an increase in the silylation degree, the increased self-diffusion coefficient due to the surface effect could basically offset the decreased self-diffusion coefficient owing to the scale effect. In the four nanochannels, when the local diffusion coefficient of fluid water was in the range of 8 Å close to the wall, Dz was greater than Dxy, and beyond the range of 8 Å of the wall, the Dz was smaller than Dxy.

scholarly journals Time-Dependent Diffusion Coefficients for Chaotic Advection due to Fluctuations of Convective Rolls

Fluids ◽  
2018 ◽  
Vol 3 (4) ◽  
pp. 99 ◽  
Author(s):  
Kazuma Yamanaka ◽  
Takayuki Narumi ◽  
Megumi Hashiguchi ◽  
Hirotaka Okabe ◽  
Kazuhiro Hara ◽  
...  
Keyword(s):  
Diffusion Coefficient ◽  
Liquid Crystals ◽  
Diffusion Coefficients ◽  
Coarse Graining ◽  
Chaotic Advection ◽  
Time Dependent ◽  
Local Order ◽  
Weak Turbulence ◽  
Normal Diffusion ◽  
Convective Rolls

The properties of chaotic advection arising from defect turbulence, that is, weak turbulence in the electroconvection of nematic liquid crystals, were experimentally investigated. Defect turbulence is a phenomenon in which fluctuations of convective rolls arise and are globally disturbed while maintaining convective rolls locally. The time-dependent diffusion coefficient, as measured from the motion of a tagged particle driven by the turbulence, was used to clarify the dependence of the type of diffusion on coarse-graining time. The results showed that, as coarse-graining time increases, the type of diffusion changes from superdiffusion → subdiffusion → normal diffusion. The change in diffusive properties over the observed timescale reflects the coexistence of local order and global disorder in the defect turbulence.

Diffusion of Zinc in Two-Phase Mg-Al Alloy

2007 ◽  
Vol 263 ◽  
pp. 189-194
Author(s):  
Ivo Stloukal ◽  
Jiří Čermák
Keyword(s):  
Diffusion Coefficient ◽  
Diffusion Coefficients ◽  
Effective Diffusion ◽  
Residual Activity ◽  
Diffusion Path ◽  
Al Alloy ◽  
Serial Sectioning ◽  
Two Phase ◽  
Interphase Boundaries ◽  
The Mean

Coefficient of 65Zn heterodiffusion in Mg17Al12 intermetallic and in eutectic alloy Mg - 33.4 wt. % Al was measured in the temperature region 598 – 698 K using serial sectioning and residual activity methods. Diffusion coefficient of 65Zn in the intermetallic can be written as DI = 1.7 × 10-2 m2 s-1 exp (-155.0 kJ mol-1 / RT). At temperatures T ≥ 648 K, where the mean diffusion path was greater than the mean interlamellar distance in the eutectic, the effective diffusion coefficient Def = 2.7 × 10-2 m2 s-1 exp (-155.1 kJ mol-1 / RT) was evaluated. At two lower temperatures, the diffusion coefficients 65Zn in interphase boundaries were estimated: Db (623 K) = 1.6 × 10-12 m2 s-1 and Db (598 K) = 4.4 × 10-13 m2 s-1.

Molten Slag Structure and Diffusion Coefficients of Cr3+ and Si4+ during Micro-Carbon Cr-Fe Alloy Production

2011 ◽  
Vol 79 ◽  
pp. 77-82
Author(s):  
Yi Min ◽  
Jian Huang ◽  
Cheng Jun Liu ◽  
Mao Fa Jiang
Keyword(s):  
Diffusion Coefficient ◽  
Diffusion Coefficients ◽  
Molten Slag ◽  
Optimization Method ◽  
Structure Theory ◽  
Average Diffusion Coefficient ◽  
Slag Structure ◽  
Initial Stage ◽  
Silicate Structure ◽  
Average Diffusion

Based on the silicate structure theory, the molten slag structure and the existential state of and during micro-carbon Cr-Fe alloy production process were analysised, and then their diffusion coefficients were calculated. The results showed that, during the initial stage, the average diffusion coeffecient of and is close to the , the reaction process is controlled by the diffusion of () and corporately, during the later stage, the diffusion coefficient of is less than average diffusion coefficient of and , the controlling step is the diffusion of . According to the evolution of diffusion coefficient, molten slag composition optimization method was advised to increase the diffusion ability of and for enhancing the reaction efficiency and the recovery rate of chromium.

Induced polarization and pore radius — A discussion

Geophysics ◽  
2016 ◽  
Vol 81 (5) ◽  
pp. D519-D526 ◽  
Author(s):  
Andreas Weller ◽  
Zeyu Zhang ◽  
Lee Slater ◽  
Sabine Kruschwitz ◽  
Matthias Halisch
Keyword(s):  
Diffusion Coefficient ◽  
Relaxation Time ◽  
Diffusion Coefficients ◽  
Pore Radius ◽  
Mercury Porosimetry ◽  
Induced Polarization ◽  
Reliable Estimate ◽  
Characteristic Relaxation Time ◽  
A Value ◽  
Apparent Diffusion

Permeability estimation from induced polarization (IP) measurements is based on a fundamental premise that the characteristic relaxation time [Formula: see text] is related to the effective hydraulic radius [Formula: see text] controlling fluid flow. The approach requires a reliable estimate of the diffusion coefficient of the ions in the electrical double layer. Others have assumed a value for the diffusion coefficient, or postulated different values for clay versus clay-free rocks. We have examined the link between a widely used single estimate of [Formula: see text] and [Formula: see text] for an extensive database of sandstone samples, in which mercury porosimetry data confirm that [Formula: see text] is reliably determined from a modification of the Hagen-Poiseuille equation assuming that the electrical tortuosity is equal to the hydraulic tortuosity. Our database does not support the existence of one or two distinct representative diffusion coefficients but instead demonstrates strong evidence for six orders of magnitude of variation in an apparent diffusion coefficient that is well-correlated with [Formula: see text] and the specific surface area per unit pore volume [Formula: see text]. Two scenarios can explain our findings: (1) the length scale defined by [Formula: see text] is not equal to [Formula: see text] and is likely much longer due to the control of pore-surface roughness or (2) the range of diffusion coefficients is large and likely determined by the relative proportions of the different minerals (e.g., silica and clays) making up the rock. In either case, the estimation of [Formula: see text] (and hence permeability) is inherently uncertain from a single characteristic IP relaxation time as considered in this study.

Diffusion of Water in Composite Filling Materials

1976 ◽  
Vol 55 (5) ◽  
pp. 730-732 ◽  
Author(s):  
M. Braden ◽  
E.E. Causton ◽  
R.L. Clarke
Keyword(s):  
Diffusion Coefficient ◽  
Composite Materials ◽  
Diffusion Coefficients ◽  
Diffusion Processes ◽  
Resin Phase ◽  
Filling Materials ◽  
Irreversible Breakdown

The absorption and desorption of water by seven composite materials are diffusion processes, with the diffusion coefficient decreasing with concentration. The magnitude of the diffusion coefficients were consistent with diffusion occurring in the resin phase. Although most materials showed reversible behavior during repeated sorption-desorption cycles, one material showed irreversible breakdown.

Anisotropic diffusion of oxygen in slices of rat muscle

1984 ◽  
Vol 246 (1) ◽  
pp. R107-R113 ◽  
Author(s):  
L. D. Homer ◽  
J. B. Shelton ◽  
C. H. Dorsey ◽  
T. J. Williams
Keyword(s):  
Diffusion Coefficient ◽  
Fluorescence Quenching ◽  
Muscle Fiber ◽  
Extracellular Space ◽  
Anisotropic Diffusion ◽  
Muscle Fibers ◽  
Rat Muscle ◽  
Hamstring Muscles ◽  
Standard Deviations ◽  
Diffusion Coefficient Of Oxygen

The diffusion coefficient of oxygen (D) and the fluorescence quenching coefficient (K') of pyrenebutyric acid (PBA) were measured in sections of rat hamstring muscles. Values of D and K' at temperatures (Tc) of 20, 30, and 40 degrees C were determined and referred to the values in water. In sections cut parallel to the muscle fibers, D = DH2O (0.380 +/- 0.038), whereas in sections cut across the grain of the fibers, D = DH2O (0.985 +/- 0.039). Oxygen diffuses along the length of a muscle fiber over twice as rapidly as it diffuses in directions perpendicular to the long axis of the fiber. This suggests that fibers, myofibrils, or myofilaments offer substantial barriers to the diffusion of oxygen, whereas extracellular space and spaces around fibers or myofibrils or myofilaments offer no more resistance than water to the diffusion of oxygen. Corresponding estimates for K' were K' = K'H2O[0.14 (1 + 0.25 Tc)] and K' = K'H2O[0.21 (1 + 0.25 Tc)] for slices cut parallel to the long axis of muscle fibers and across the long axis, respectively. Standard deviations of K' were 9%.

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