Self-organisation in the assembly of gels from mixtures of different dendritic peptide building blocks

This paper investigates dendritic peptides capable of assembling into nanostructured gels, and explores the effect on self-assembly of mixing different molecular building blocks. Thermal measurements, small angle Xray scattering (SAXS) and circular dichroism (CD) spectroscopy are used to probe these materials on macroscopic, nanoscopic and molecular length scales. The results from these investigations demonstrate that in this case, systems with different "size" and "chirality" factors can self-organise, whilst systems with different "shape" factors cannot. The "size" and "chirality" factors are directly connected with the molecular information programmed into the dendritic peptides, whilst the shape factor depends on the group linking these peptides together-this is consistent with molecular recognition hydrogen bond pathways between the peptidic building blocks controlling the ability of these systems to self-recognise. These results demonstrate that mixtures of relatively complex peptides, with only subtle differences on the molecular scale, can self-organise into nanoscale structures, an important step in the spontaneous assembly of ordered systems from complex mixtures.

A simulation model of self-organising evolvability in software systems

The evolvability of a software artifact is its capacity for producing heritable or reusable variants; the inverse quality is the artifact's inertia or resistance to evolutionary change. Evolvability in software systems may arise from engineering and/or self-organising processes. We describe our 'Conditional Growth' simulation model of software evolution and show how, it can be used to investigate evolvability from a self-organisation perspective. The model is derived from the Bak-Sneppen family of 'self-organised criticality' simulations. It shows good qualitative agreement with Lehman's 'laws of software evolution' and reproduces phenomena that have been observed empirically. The model suggests interesting predictions about the dynamics of evolvability and implies that much of the observed variability in software evolution can be accounted for by comparatively simple self-organising processes.

Design of a minimum variance multiple input-multiple output neuro self-tuning proportional-integral-derivative controller for non-linear dynamic systems

In this study a minimum variance neuro self-tuning proportional-integral-derivative (PID) controller is designed for complex multiple input-multiple output (MIMO) dynamic systems. An approximation model is constructed, which consists of two functional blocks. The first block uses a linear submodel to approximate dominant system dynamics around a selected number of operating points. The second block is used as an error agent, implemented by a neural network, to accommodate the inaccuracy possibly introduced by the linear submodel approximation, various complexities/uncertainties, and complicated coupling effects frequently exhibited in non-linear MIMO dynamic systems. With the proposed model structure, controller design of an MIMO plant with n inputs and n outputs could be, for example, decomposed into n independent single input-single output (SISO) subsystem designs. The effectiveness of the controller design procedure is initially verified through simulations of industrial examples.

Self-immolative linkers in polymeric delivery systems

There has been significant interest in the methodologies of controlled release for a diverse range of applications spanning drug delivery, biological and chemical sensors, and diagnostics. The advancement in novel substrate-polymer coupling moieties has led to the discovery of self-immolative linkers. This new class of linker has gained popularity in recent years in polymeric release technology as a result of stable bond formation between protecting and leaving groups, which becomes labile upon activation, leading to the rapid disassembly of the parent polymer. This ability has prompted numerous studies into the design and development of self-immolative linkers and the kinetics surrounding their disassembly. This review details the main concepts that underpin self-immolative linker technologies that feature in polymeric or dendritic conjugate systems and outlines the chemistries of amplified self-immolative elimination.

Neural network enhanced generalised minimum variance self-tuning controller for nonlinear discrete-time systems

A neural network enhanced self-tuning controller is presented, which combines the attributes of neural network mapping with a generalised minimum variance self-tuning control (STC) strategy. In this way the controller can deal with nonlinear plants, which exhibit features such as uncertainties, nonminimum phase behaviour, coupling effects and may have unmodelled dynamics, and whose nonlinearities are assumed to be globally bounded. The unknown nonlinear plants to be controlled are approximated by an equivalent model composed of a simple linear submodel plus a nonlinear submodel. A generalised recursive least squares algorithm is used to identify the linear submodel and a layered neural network is used to detect the unknown nonlinear submodel in which the weights are updated based on the error between the plant output and the output from the linear submodel. The procedure for controller design is based on the equivalent model therefore the nonlinear submodel is naturally accommodated within the control law. Two simulation studies are provided to demonstrate the effectiveness of the control algorithm.

A neural network enhanced generalized minimum variance self-tuning proportional, integral and derivative control algorithm for complex dynamic systems

A neural network enhanced proportional, integral and derivative (PID) controller is presented that combines the attributes of neural network learning with a generalized minimum-variance self-tuning control (STC) strategy. The neuro PID controller is structured with plant model identification and PID parameter tuning. The plants to be controlled are approximated by an equivalent model composed of a simple linear submodel to approximate plant dynamics around operating points, plus an error agent to accommodate the errors induced by linear submodel inaccuracy due to non-linearities and other complexities. A generalized recursive least-squares algorithm is used to identify the linear submodel, and a layered neural network is used to detect the error agent in which the weights are updated on the basis of the error between the plant output and the output from the linear submodel. The procedure for controller design is based on the equivalent model, and therefore the error agent is naturally functioned within the control law. In this way the controller can deal not only with a wide range of linear dynamic plants but also with those complex plants characterized by severe non-linearity, uncertainties and non-minimum phase behaviours. Two simulation studies are provided to demonstrate the effectiveness of the controller design procedure.

Bioactive films produced from self-assembling peptide amphiphiles as versatile substrates for tuning cell adhesion and tissue architecture in serum-free conditions

The development of versatile bioactive surfaces able to emulate in vivo conditions is of enormous importance to the future of cell and tissue therapy. Tuning cell behaviour on two-dimensional surfaces so that the cells perform as if they were in a natural three-dimensional tissue represents a significant challenge, but one that must be met if the early promise of cell and tissue therapy is to be fully realised. Due to the inherent complexities involved in the manufacture of biomimetic three-dimensional substrates, the scaling up of engineered tissue-based therapies may be simpler if based upon proven two-dimensional culture systems. In this work, we developed new coating materials composed of the self-assembling peptide amphiphiles (PAs) C16G3RGD (RGD) and C16G3RGDS (RGDS) shown to control cell adhesion and tissue architecture while avoiding the use of serum. When mixed with the C16ETTES diluent PA at 13 : 87 (mol mol-1) ratio at 1.25 times 10-3 M, the bioactive {PAs} were shown to support optimal adhesion, maximal proliferation, and prolonged viability of human corneal stromal fibroblasts ({hCSFs)}, while improving the cell phenotype. These {PAs} also provided stable adhesive coatings on highly-hydrophobic surfaces composed of striated polytetrafluoroethylene ({PTFE)}, significantly enhancing proliferation of aligned cells and increasing the complexity of the produced tissue. The thickness and structure of this highly-organised tissue were similar to those observed in vivo, comprising aligned newly-deposited extracellular matrix. As such, the developed coatings can constitute a versatile biomaterial for applications in cell biology, tissue engineering, and regenerative medicine requiring serum-free conditions.

Shared neural circuits for mentalizing about the self and others

Although many examples exist for shared neural representations of self and other, it is unknown how such shared representations interact with the rest of the brain. Furthermore, do high-level inference-based shared mentalizing representations interact with lower level embodied/simulation-based shared representations? We used functional neuroimaging (fMRI) and a functional connectivity approach to assess these questions during high-level inference-based mentalizing. Shared mentalizing representations in ventromedial prefrontal cortex, posterior cingulate/precuneus, and temporo-parietal junction (TPJ) all exhibited identical functional connectivity patterns during mentalizing of both self and other. Connectivity patterns were distributed across low-level embodied neural systems such as the frontal operculum/ventral premotor cortex, the anterior insula, the primary sensorimotor cortex, and the presupplementary motor area. These results demonstrate that identical neural circuits are implementing processes involved in mentalizing of both self and other and that the nature of such processes may be the integration of low-level embodied processes within higher level inference-based mentalizing.

The sociology of childhood as scientific communication - Observations from a social systems perspective

This article begins by identifying a close relationship between the image of children generated by several sociologists working within the new sociology of childhood perspective and the claims and ambitions of the proponents of children's autonomy rights. The image of the child as a competent, self-controlled human agent are then subjected to observation from the perspective of Niklas Luhmann's social systems theory. The new sociology of childhood's constructivist approach is compared and contrasted with Niklas Luhmann's theory of 'operational constructivism'. The article applies tenets of Luhmann's theory, to the emergence of the new childhood sociologist's image of the child as a competent, self-controlled social agent, to the epistemological status of this image and, in particular, to claims that it derives from scientific endeavour. The article proceeds to identify two theoretical developments within sociology - sociology of identity and social agency - which have brought about fundamental changes in what may be considered 'sociological' and so 'scientific' and paved the way for sociological communications about what children,really are'. In conclusion, it argues that the merging of sociology with polemics, ideology, opinion and personal beliefs and, at the level of social systems, between science and politics represents in Luhmann's terms 'dedifferentiation'- a tendency he claims may have serious adverse consequences for modern society. This warning is applied to the scientific status of sociology - its claim to be able to produce 'facts' for society, upon which social systems, such as politics and law, may rely. Like the mass media, sociology may now be capable of producing only information, and not facts, about children.

Autopoiesis vs. social autopoiesis: critical evaluation and implications for understanding firms as autopoietic social systems

The main objective of this study is to revisit the fundamental postulations of autopoietic self-production wrapped within the autopoietic six-point key and to investigate whether or not firms as specific social systems can be treated as autopoietic unities. In order to do so firms have to be defined as simple and composite unities whereupon their boundaries have to be clearly identifiable. The test of social autopoiesis reveals that firms can be viewed as autopoietic social systems that exist in the communicative space with employees' firm-specific communicative sub-domains as their components. Furthermore, it is argued that the social reification of autopoiesis (autokoinopoiesis) in firms is quintessentially interconnected with physical autopoiesis of their employees (autophysiopoiesis). Discontiguous focus on productivity as firms' obvious physical implication may thus be upgraded by a very social nature of ideactivity, firms' only real survival force.

Low-molecular-weight gelators: Elucidating the principles of gelation based on gelator solubility and a cooperative self-assembly model

This paper highlights the key role played by solubility in influencing gelation and demonstrates that many facets of the gelation process depend on this vital parameter. In particular, we relate thermal stability (T-gel) and minimum gelation concentration (MGC) values of small-molecule gelation in terms of the solubility and cooperative self-assembly of gelator building blocks. By employing a van't Hoff analysis of solubility data, determined from simple NMR measurements, we are able to generate T-calc values that reflect the calculated temperature for complete solubilization of the networked gelator. The concentration dependence of T-calc allows the previously difficult to rationalize "plateau-region" thermal stability values to be elucidated in terms of gelator molecular design. This is demonstrated for a family of four gelators with lysine units attached to each end of an aliphatic diamine, with different peripheral groups (Z or Bee) in different locations on the periphery of the molecule. By tuning the peripheral protecting groups of the gelators, the solubility of the system is modified, which in turn controls the saturation point of the system and hence controls the concentration at which network formation takes place. We report that the critical concentration (C-crit) of gelator incorporated into the solid-phase sample-spanning network within the gel is invariant of gelator structural design. However, because some systems have higher solubilities, they are less effective gelators and require the application of higher total concentrations to achieve gelation, hence shedding light on the role of the MGC parameter in gelation. Furthermore, gelator structural design also modulates the level of cooperative self-assembly through solubility effects, as determined by applying a cooperative binding model to NMR data. Finally, the effect of gelator chemical design on the spatial organization of the networked gelator was probed by small-angle neutron and X-ray scattering (SANS/SAXS) on the native gel, and a tentative self-assembly model was proposed.

Self-assembly of two-component gels: stoichiometric control and component selection

Two-component systems capable of self-assembling into soft gel-phase materials are of considerable interest due to their tunability and versatility. This paper investigates two-component gels based on a combination of a L-lysine-based dendron and a rigid diamine spacer (1,4-diaminobenzene or 1,4-diaminocyclohexane). The networked gelator was investigated using thermal measurements, circular dichroism, NMR spectroscopy and small angle neutron scattering (SANS) giving insight into the macroscopic properties, nanostructure and molecular-scale organisation. Surprisingly, all of these techniques confirmed that irrespective of the molar ratio of the components employed, the "solid-like" gel network always consisted of a 1:1 mixture of dendron/diamine. Additionally, the gel network was able to tolerate a significant excess of diamine in the "liquid-like" phase before being disrupted. In the light of this observation, we investigated the ability of the gel network structure to evolve from mixtures of different aromatic diamines present in excess. We found that these two-component gels assembled in a component-selective manner, with the dendron preferentially recognising 1,4-diaminobenzene (>70%). when similar competitor diamines (1,2- and 1,3-diaminobenzene) are present. Furthermore, NMR relaxation measurements demonstrated that the gel based oil 1,4-diaminobenzene was better able to form a selective ternary complex with pyrene than the gel based oil 1,4-diaminocyclohexane, indicative of controlled and selective pi-pi interactions within a three-component assembly. As such, the results ill this paper demonstrate how component selection processes in two-component gel systems call control hierarchical self-assembly.