Mean network topology underlying the resettable bistability.

<p>(a) Mean value matrix consisting all six network links. (b) Topology matrix after discretization of Mean value matrix. (c) Mean network topology obtained from the topology matrix.</p

CPSS software implementation.

<p>The major functional modules (above the gray box) are application-independent objects and will not need to be changed for a new application. The modules within the gray box are application-specific objects; they inherit all properties of their “parent” objects, which help minimize the amount of new coding needed. For example, the present study uses a bistability evaluator (under “network feature evaluator”) and a 3-node system (under “ODE solver”). A different feature evaluator (e.g. adaptation) and a network with larger number of nodes can be similarly implemented for a new study.</p

Flowchart describing the CPSS method to determine and analyze network topologies underlying a given dynamic property.

<p>Flowchart describing the CPSS method to determine and analyze network topologies underlying a given dynamic property.</p

Backbone motif underlying resettable bistability under the Constrained situation.

<p>(a) Coefficient Variation matrix. (b) Backbone motifs obtained from the Coefficient Variation matrix. See text for details.</p

Systematic Reverse Engineering of Network Topologies: A Case Study of Resettable Bistable Cellular Responses

<div><p>A focused theme in systems biology is to uncover design principles of biological networks, that is, how specific network structures yield specific systems properties. For this purpose, we have previously developed a reverse engineering procedure to identify network topologies with high likelihood in generating desired systems properties. Our method searches the <i>continuous</i> parameter space of an assembly of network topologies, without enumerating individual network topologies separately as traditionally done in other reverse engineering procedures. Here we tested this CPSS (continuous parameter space search) method on a previously studied problem: the resettable bistability of an Rb-E2F gene network in regulating the quiescence-to-proliferation transition of mammalian cells. From a simplified Rb-E2F gene network, we identified network topologies responsible for generating resettable bistability. The CPSS-identified topologies are consistent with those reported in the previous study based on individual topology search (ITS), demonstrating the effectiveness of the CPSS approach. Since the CPSS and ITS searches are based on different mathematical formulations and different algorithms, the consistency of the results also helps cross-validate both approaches. A unique advantage of the CPSS approach lies in its applicability to biological networks with large numbers of nodes. To aid the application of the CPSS approach to the study of other biological systems, we have developed a computer package that is available in Information S1.</p></div

Robust minimum motifs underlying resettable bistability for Constrained situation.

<p>Robust minimum motifs underlying resettable bistability for Constrained situation.</p

Pairwise correlation between links 3 and 9: 2D correlation heat map.

<p>The x axis denotes the link from EE to MD (link 3); the y axis denotes the link from EE to itself (link 9). The value on each axis denotes the link strength, with the positive and negative segments indicating activation and repression links, respectively. Color bar on the right: the fraction of ‘good’ parameter sets (supporting resettable bistability).</p

Mean network motif for resettable bistability under the Constrained situation.

<p>(a) Mean value matrix consisting all six network links. (b) Topology Matrix after discretization of the Mean value matrix. (c) Mean network topology, which is responsible for resettable bistability under the Constrained situation.</p

Pairwise correlation between links 3 and 9: Diagrams of link combinations that correspond to the heat map in <b>Figure 6</b>.

<p>Pairwise correlation between links 3 and 9: Diagrams of link combinations that correspond to the heat map in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0105833#pone-0105833-g006" target="_blank"><b>Figure 6</b></a>.</p

Surface Modification of PMMA to Improve Adhesion to Corneal Substitutes in a Synthetic Core–Skirt Keratoprosthesis

Patients with advanced corneal disease do poorly with conventional corneal transplantation and require a keratoprosthesis (KPro) for visual rehabilitation. The most widely used KPro is constructed using poly­(methyl methacrylate) (PMMA) in the central optical core and a donor cornea as skirt material. In many cases, poor adherence between the PMMA and the soft corneal tissue is responsible for device “extrusion” and bacterial infiltration. The interfacial adhesion between the tissue and the PMMA was therefore critical to successful implantation and device longevity. In our approach, we modified the PMMA surface using oxygen plasma (plasma group); plasma followed by calcium phosphate (CaP) coating (p-CaP); dopamine followed by CaP coating (d-CaP); or plasma followed by coating with (3-aminopropyl)­triethoxysilane (3-APTES). To create a synthetic KPro model, we constructed and attached 500 μm thick collagen type I hydrogel on the modified PMMA surfaces. Surface modifications produced significantly improved interfacial adhesion strength compared to untreated PMMA (<i>p</i> < 0.001). The p-CaP group yielded the best interfacial adhesion with the hydrogel (177 ± 27 mN/cm²) followed by d-CaP (168 ± 31 mN/cm²), 3-APTES (145 ± 12 mN/cm²), and plasma (119 ± 10 mN/cm²). Longer-term stability of the adhesion was achieved by d-CaP, which, after 14 and 28 days of incubation in phosphate buffered saline, yielded 164 ± 25 mN/cm² (<i>p</i> = 0.906 compared to adhesion at day 1) and 131 ± 20 mN/cm² (<i>p</i> = 0.053), respectively. In contrast, significant reduction of adhesion strength was observed in p-CaP group over time (<i>p</i> < 0.001). All surface coatings were biocompatible to human corneal stromal fibroblasts, except for the 3-APTES group, which showed no live cells at 72 h of culture. In contrast, cells on d-CaP surface showed good anchorage, evidenced by the expression of focal adhesion complex (paxillin and vinculin), and prominent filopodia protrusions. In conclusion, d-CaP can not only enhance and provide stability to the adhesion of collagen hydrogel on the PMMA surface but also promote biointegration