Reaktions‐Diffusions‐Systeme für intrazellulären Transport und Kontrolle

Soh, Siowling; Byrska, Marta; Kandere‐Grzybowska, Kristiana; Grzybowski, Bartosz A.

doi:10.1002/ange.200905513

Cited by 30 publications

(11 citation statements)

References 306 publications

(367 reference statements)

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“…Signal transport through tissues can also be treated, approximately, as a diffusion process by combining membrane permeation with permeability P and bulk diffusion with diffusion coefficient D into an effective diffusion coefficient D eff =[( PL cell ) −1 + D −1 ] −1 , in which L cell is the size of the cells . For a very nice introduction into reaction–diffusion phenomena the reader is also referred to the review by Soh et al …”

Section: Communication Between Artificial Cellsmentioning

confidence: 99%

Establishing Communication Between Artificial Cells

Aufinger

Simmel

2019

Chemistry A European J

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Communication between artificial cells is essential for the realization of complex dynamical behaviors at the multi‐cell level. It is also an important prerequisite for modular systems design, because it determines how spatially separated functional modules can coordinate their actions. Among others, molecular communication is required for artificial cell signaling, synchronization of cellular behaviors, computation, group‐level decision‐making processes and pattern formation in artificial tissues. In this review, an overview of various recent approaches to create communicating artificial cellular systems is provided. In this context, important physicochemical boundary conditions that have to be considered for the design of the communicating cells are also described, and a survey of the most striking emergent behaviors that may be achieved in such systems is given.

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Section: Communication Between Artificial Cellsmentioning

confidence: 99%

Establishing Communication Between Artificial Cells

Aufinger

Simmel

2019

Chemistry A European J

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“…The RD equations were solved numerically using the Crank–Nicolson algorithm15d, 21 with the initial conditions (time t =0) inside the MOF given by [PB] 0 =0 M , [S*] 0 =0.79 M ,22 and [PB⋅S] 0 =0 M , and the boundary condition setting the PB concentration outside of the MOF crystal as constant, [PB]=10 −7 M (since the number of molecules in solution is thousands of times higher than the maximum number of PB molecules adsorbed into the crystal). The RD equations were solved for different trial values of the D PB and K eq parameters, the optimal values of which were then found by minimizing the quadratic error between the experimental and modeled concentration profiles; this procedure was performed according to the Nelder–Mead simplex algorithm 15…”

mentioning

confidence: 99%

Transport into Metal–Organic Frameworks from Solution Is Not Purely Diffusive

et al. 2012

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In virtually all applications of metal-organic frameworks (MOFs), [1] it is important to understand and quantify the transport through their nanoscopic channels. [2] To date, most studies have focused on gas-phase systems and their modeling using molecular dynamics (MD) simulations. This effort has provided a wealth of information on the self-, corrected, and transport diffusivities of molecules from the gas phase into the MOF bulk. [3,4] Significantly fewer studies have examined molecular transport into solvent-filled MOFs [1b, 5] which is becoming increasingly important in heterogeneous catalysis. In the vast majority of these works, the transport has been described as simple Fickian diffusion. [5a, 6] Here, we combine experiment with theory to show that such a pure diffusion approach is a gross oversimplification and, instead, transport equations should be of the reaction-diffusion (RD) form. The RD description is appropriate at both the macroscopic scale (studied using the dye diffusion profiles) and the nanoscale (studied using fluorescence correlation spectroscopy).Currently available techniques for the quantification of transport into nano-or microporous materials (e.g., zeolites, [7] MOFs) include quasi-elastic neutron scattering (QENS), [8] pulsed field gradient nuclear magnetic resonance (PFG NMR), [9] interference microscopy (IFM) and infrared microscopy (IRM). [6a-b, 10] In particular, IFM and IRM, recently developed by Kärger's group, are two techniques which can monitor diffusion in individual nanoporous crystallites, though they cannot easily extract full, three-dimensional concentration profiles [11] -this difficulty might explain why both techniques have not yet been widely used. Other techniques, such as luminescence quenching [5a] and quartzcrystal microbalance (QCM), [6c] provide diffusivity data that are averaged over one or more MOF particles. As mentioned above, the concentration profiles observed during infusion of the MOF are usually explained using pure or effective diffusion models. While in some cases this approach seems to fit the data reasonably well, [5a, 6] there are other instances where it does not-for example, in the separations of liquid mixtures over MOF-crystal "columns" we recently described. [1b] The motivation for the present work is therefore two-fold. First, we wish to develop an experimental method in which the diffusion profiles into MOFs could be studied directly and without ambiguity and, importantly, using equipment that is available to most research groups. Second, we wish to provide a general theoretical framework with which to study transport into MOFs from solution. To meet these objectives, we combine the ability to grow large, millimeter-sized MOF crystals [1b, 12] (here, MOF-5) with confocal laser scanning microscopy (CLSM) [13] and fluorescence correlation spectroscopy (FCS) [14] which have been previously applied to measure the transport of dyes or fluorescently labeled molecules into protein crystal and other materials. The concentration pro...

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“…Self‐organization outside the thermodynamic equilibrium is important in the context of life,1, 2 and has inspired development of artificial dynamic materials and systems3, 4 on scales from molecular,5–9 through nanoscopic10–12 and microscopic,13, 14 to macroscopic 15. 16 One of the singular features of non‐equilibrium self‐organization in cells or organisms is their ability to couple several subsystems into larger, dynamic machinery 2. In man‐made ensembles, such synthetic ability is largely lacking, though there are some interesting examples where molecular‐scale, non‐equilibrium systems such as chemical oscillators control dimensions/contractility of gels or polymers17, 18 or periodically shift complexation or precipitation equilibria 19–22.…”

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confidence: 99%

Nanoparticle Oscillations and Fronts

et al. 2010

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Self-organization outside the thermodynamic equilibrium is important in the context of life, [1,2] and has inspired development of artificial dynamic materials and systems [3,4] on scales from molecular, [5][6][7][8][9] through nanoscopic [10][11][12] and microscopic, [13,14] to macroscopic. [15,16] One of the singular features of non-equilibrium self-organization in cells or organisms is their ability to couple several subsystems into larger, dynamic machinery.[2] In man-made ensembles, such synthetic ability is largely lacking, though there are some interesting examples where molecular-scale, non-equilibrium systems such as chemical oscillators control dimensions/contractility of gels or polymers [17,18] or periodically shift complexation or precipitation equilibria. [19][20][21][22] The motivation of the present work is to design and implement a chemical system in which a molecular-scale subsystem would couple to and control dynamic self-organization of nanoscopic part.[23] This subsystem is a pH oscillator [24][25][26] (pH "clock") that controls the dissociation of acidic head-groups on the surface of metal nanoparticles (NPs). We show that with a proper control over electrostatic and van der Waals (vdW) forces between the NPs, [27] the clock can then cause a rhythmic assembly/ disassembly of the NPs. Additionally, in spatially distributed media, the pH oscillations can translate into the propagation of NP aggregation fronts or surface phenomena, such as deposition and removal of NP-based surface coatings.Although conceptually straightforward (Figure 1 a), the ability to couple pH oscillations with reversible NP aggregation requires careful engineering of the interparticle forces at a molecular scale. The two key effects to consider are the vdW attractions between the NPs and the electrostatic repulsions between the molecules forming self-assembled monolayers (SAMs) [28,29] on nanoparticle surfaces. Specifically, when the pH clock "spikes" to high pH and deprotonates the SAMs, the electrostatic repulsions should be able to overcome vdW attractions; conversely, when the oscillator is in a low-pH state, the vdW forces should be strong enough to affect NP aggregation. To match these criteria, 1) the pK a of the SAMs covering the NPs should be within the pH range of the oscillator (such that the oscillations can significantly affect the fractions of protonated/deprotonated molecules within the SAM, and 2) the magnitudes of electrostatic and vdW forces acting in the system should be commensurate; as we have shown previously, [30] the second point is true for NPs that are a few nanometers in diameter, for which the magnitudes of electrostatic and vdW interactions are on the order of several k T.[31] As the interaction energies are relatively small, the aggregation/dispersion phenomena might be expected to be sensitive to the thickness of the SAMs (determining the distance between the NPs metal cores and thus the maximal magnitude of vdW interactions between the particles). [27] With these design guidelines in mind,...

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Reaktions‐Diffusions‐Systeme für intrazellulären Transport und Kontrolle

Cited by 30 publications

References 306 publications

Establishing Communication Between Artificial Cells

Establishing Communication Between Artificial Cells

Transport into Metal–Organic Frameworks from Solution Is Not Purely Diffusive

Nanoparticle Oscillations and Fronts

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