Membrane Permeability Modeling: Kedem–Katchalsky vs a Two-Parameter Formalism

Kleinhans, F.W.

doi:10.1006/cryo.1998.2135

Cited by 239 publications

(154 citation statements)

References 43 publications

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“…The relative volume was obtained from V=S 3/2 . The water-permeability and glycerol-permeability of oocytes/embryos were determined by fitting water-and solute-movement using a twoparameter formalism [8,15]. Various constants and parameters are listed in Table 1.…”

Section: Measurement Of the Permeability To Water And Glycerol Of Moumentioning

confidence: 99%

Developmental Ability of Vitrified Mouse Oocytes Expressing Water Channels

Yamaji

Seki

Matsukawa

et al. 2011

Journal of Reproduction and Development

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Abstract. Previously, we showed that the exogenous expression of aquaporin 3 (AQP3), an aquaglyceroporin, improved the tolerance of mouse oocytes to vitrification with a glycerol-based solution. In the present study, we examined conditions suitable for the expression of AQP3 and the ability of vitrified oocytes to develop in vitro and in vivo after fertilization. After only partial remove of cumulus cells, immature mouse oocytes (germinal vesicle stage) were injected with 5, 10 or 20 pg of AQP3 cRNA and cultured for 12 h for maturation. When matured oocytes were vitrified with a glycerol-based solution, 57-61% survived regardless of the amount of cRNA injected (5-20 pg). By contrast, no oocytes injected with water (control) survived. When the zona pellucida was removed from the vitrified oocytes and the oocytes were then fertilized in vitro and cultured, the proportions that were fertilized and developed into blastocysts were higher when the amount of cRNA injected was 5 pg than 10-20 pg. When 16 blastocysts were transferred to a pseudopregnant mouse, 5 developed to term, demonstrating that oocytes vitrified after injection of AQP3 cRNA retained the ability to develop to term. The water-permeability of cRNA-injected oocytes was higher than that of control oocytes from the maturing stage to the 1-cell zygote stage, whereas glycerol-permeability was higher only at metaphase II. This indicates that AQP3 was expressed for a relatively short period of time. These results suggest that the transient expression of water/cryoprotectant channels is effective for cryopreserving cells that have low membrane-permeability, such as mammalian oocytes. Key words: Aquaporin, Development, Membrane-permeability, Oocyte, Vitrification (J. Reprod. Dev. 57: [403][404][405][406][407][408] 2011) he permeability of the plasma membrane to water and cryoprotectants is one of the most important factors for successful cryopreservation of oocytes/embryos because it influences the formation of intracellular ice, the toxicity of cryoprotectants and osmotic swelling [1]. For cryopreservation of oocytes/embryos, vitrification has advantages over slow freezing in terms of the simplicity of the method and viability of the cells. As the solution used for vitrification contains a high concentration of cryoprotectants, it is much more toxic than the solution for slow-freezing. Therefore, the permeability of the plasma membrane would affect the survival of cryopreserved cells more in vitrification than in slow freezing. If the permeability is low, insufficient exposure to the cryoprotectants causes formation of intracellular ice. However, excessive exposure results in toxic effects of the cryoprotectants. Therefore, high permeability to water and cryoprotectants would be preferable for vitrification.We showed that a simple one-step method is effective for vitrification of mouse morulae [2] but that a two-step method with a pretreatment with a lower concentration of the cryoprotectant is favorable for vitrifying mouse embryos at early cleavage stages...

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Section: Measurement Of the Permeability To Water And Glycerol Of Moumentioning

confidence: 99%

Developmental Ability of Vitrified Mouse Oocytes Expressing Water Channels

Yamaji

Seki

Matsukawa

et al. 2011

Journal of Reproduction and Development

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“…The two-parameter model was firstly presented by Jacob (1932Jacob ( -1933, and further developed by Kleinhans (1998), Katkov (2000) recently. The model utilizes the parameters L p and P s (CPA solute permeability) to characterize membrane permeability when water, a permeable solute and a nonpermeable solute are present:…”

Section: Cell Membrane Transport Models and Mathematical Formulatinsmentioning

confidence: 99%

“…However, more recent literature suggests that aquaporins in cell membrane are highly selective, with nonionic solute transport occurring mainly through the lipid bilayer or through other channels that are distinct from the aquaporins (Gilmore et al, 1995;Preston et al, 1992). In this case, the estimation of σ as independent parameter may be inappropriate and may not be relevant from a biological stand point (Kleinhans, 1998). By assuming that there is no interaction between water and solute during their transport through the membrane, the value of σ can be determined as…”

Section: Cell Membrane Transport Models and Mathematical Formulatinsmentioning

confidence: 99%

Prevention of Lethal Osmotic Injury to Cells During Addition and Removal of Cryoprotective Agents: Theory and Technology

Gao¹,

Zhou²

2012

Current Frontiers in Cryobiology

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“…In nature, cell walls, membranes, biofilms, and similar structures exist in a number of different forms. There are numerous models describing the permeability of these structures in a variety of different contexts and levels of detail [84,87,117,139].…”

Section: Cellular Compartmentsmentioning

confidence: 99%

“…Furthermore, if a cell's total volume is constrained, species can permeate into it only up to a certain point, when the cell becomes 'full.' More detailed models also consider solute permeability, viscosity, hydraulic conductivity [87], pH, and temperature.…”

Section: Cellular Compartmentsmentioning

confidence: 99%

Novel Methods for Learning and Adaptation in Chemical Reaction Networks

Banda¹

2000

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State-of-the-art biochemical systems for medical applications and chemical computing are application-specific and cannot be re-programmed or trained once fabricated. The implementation of adaptive biochemical systems that would offer flexibility through programmability and autonomous adaptation faces major challenges because of the large number of required chemical species as well as the timing-sensitive feedback loops required for learning. Currently, biochemistry lacks a systems vision on how the userlevel programming interface and abstraction with a subsequent translation to chemistry should look like. By developing adaptation in chemistry, we could replace multiple hardwired systems with a single programmable template that can be (re)trained to match a desired input-output profile benefiting smart drug delivery, pattern recognition, and chemical computing.I aimed to address these challenges by proposing several approaches to learning and adaptation in Chemical Reaction Networks (CRNs), a type of simulated chemistry, where species are unstructured, i.e., they are identified by symbols rather than molecular structure, and their dynamics or concentration evolution are driven by reactions and reaction rates that follow mass-action and Michaelis-Menten kinetics.Several CRN and experimental DNA-based models of neural networks exist. However, these models successfully implement only the forward-pass, i.e., the input-weight integration part of a perceptron model. Learning is delegated to a non-chemical system that i computes the weights before converting them to molecular concentrations. Autonomous learning, i.e., learning implemented fully inside chemistry has been absent from both theoretical and experimental research.The research in this thesis offers the first constructive evidence that learning in CRNs is, in fact, possible. I have introduced the original concept of a chemical binary perceptron that can learn all 14 linearly-separable logic functions and is robust to the perturbation of rate constants. That shows learning is universal and substrate-free. To simplify the model I later proposed and applied the "asymmetric" chemical arithmetic providing a compact solution for representing negative numbers in chemistry.To tackle more difficult tasks and to serve more complicated biochemical applications, I introduced several key modular building blocks, each addressing certain aspects of chemical information processing and learning. These parts organically combined into gradually more complex systems. First, instead of simple static Boolean functions, I tackled analog time-series learning and signal processing by modeling an analog chemical perceptron. To store past input concentrations as a sliding window I implemented a chemical delay line, which feeds the values to the underlying chemical perceptron. That allows the system to learn, e.g., the linear moving-average and to some degree predict a highly nonlinear NARMA benchmark series.Another important contribution to the area of chemical learning, which I ...

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Membrane Permeability Modeling: Kedem–Katchalsky vs a Two-Parameter Formalism

Cited by 239 publications

References 43 publications

Developmental Ability of Vitrified Mouse Oocytes Expressing Water Channels

Developmental Ability of Vitrified Mouse Oocytes Expressing Water Channels

Prevention of Lethal Osmotic Injury to Cells During Addition and Removal of Cryoprotective Agents: Theory and Technology

Novel Methods for Learning and Adaptation in Chemical Reaction Networks

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