Algebraic, geometric, and stochastic aspects of genetic operators

Genetic algorithms for function optimization employ genetic operators patterned after those observed in search strategies employed in natural adaptation. Two of these operators, crossover and inversion, are interpreted in terms of their algebraic and geometric properties. Stochastic models of the operators are developed which are employed in Monte Carlo simulations of their behavior

Proportional-Integral Degradation (PI-Deg) control allows accurate tracking of biomolecular concentrations with fewer chemical reactions

We consider the design of synthetic embedded feedback circuits that can implement desired changes in the concentration of the output of a biomolecular process (reference tracking in control terminology). Such systems require the use of a "subtractor", to generate an error signal that captures the difference between the current and desired value of the process output. Unfortunately, standard implementations of the subtraction operator using chemical reaction networks are one-sided, i.e. they cannot produce negative error signals. Previous attempts to deal with this problem by representing signals as the difference in concentrations of two different biomolecular species lead to a doubling of the number of chemical reactions required to generate the circuit, hence sharply increasing the difficulty of experimental implementations and limiting the complexity of potential designs. Here we propose an alternative approach that introduces a degradation term into the classical proportion-integral control scheme. The extra tuning flexibility of the resulting PI-Deg controller compensates for the limitations of the one-sided subtraction operator, providing robust high-performance tracking of concentration changes with a minimal number of chemical reactions

System identification of gene regulatory networks for perturbation mitigation via feedback control

In Synthetic Biology, the idea of using feedback control for the mitigation of perturbations to gene regulatory networks due to disease and environmental disturbances is gaining popularity. To facilitate the design of such synthetic control circuits, a suitable model that captures the relevant dynamics of the gene regulatory network is essential. Traditionally, Michaelis-Menten models with Hill-type nonlinearities have often been used to model gene regulatory networks. Here, we show that such models are not suitable for the purposes of controller design, and propose an alternative formalism. Using tools from system identification, we show how to build so-called S-System models that capture the key dynamics of the gene regulatory network and are suitable for controller design. Using the identified S-System model, we design a genetic feedback controller for an example gene regulatory network with the objective of rejecting an external perturbation. Using a sine sweeping method, we show how the S-System model can be approximated by a second order linear transfer function and, based on this transfer function, we design our controller. Simulation results using the full nonlinear S-System model of the network show that the designed controller is able to mitigate the effect of external perturbations. Our findings highlight the usefulness of the S-System modelling formalism for the design of synthetic control circuits for gene regulatory networks

Density and conformation with relaxed substrate, bulk, and interface electrophoretic deposition of polymer chains

Characteristics of relaxed density profile and conformation of polymer chains are studied by a Monte Carlo simulation on a discrete lattice in three dimensions using different segmental (kink-jump $K$, crank-shaft $C$, reptation $R$) dynamics. Three distinct density regimes, substrate, bulk, and interface, are identified. With the $KC$ segmental dynamics we find that the substrate coverage grows with a power-law, $d_s \propto t^{\gamma}$ with a field dependent nonuniversal exponent $\gamma = 0.23 + 0.7 E$. The bulk volume fraction $d_b$ and the substrate polymer density ($d_s$) increases exponentially with the field ($d_b \propto E^{0.4}$, $d_s \propto E^{0.2}$) in the low field regime. The interface polymer density $d_f$ increases with the molecular weight. With the $KCR$ segmental dynamics, bulk and substrate density decreases linearly with the temperature at high temperatures. The bulk volume fraction is found to decay with the molecular weight, $d_b \propto L_c^{-0.11}$. The radius of gyration remains Gaussian in all density regions.Comment: Changed double to single spacin

Patient-Related Barriers to Timely Dialysis Access Preparation: A Qualitative Study of the Perspectives of Patients, Family Members, and Health Care Providers

Rational & Objective A key aspect of smooth transition to dialysis is the timely creation of a permanent access. Despite early referral to kidney care, initiation onto dialysis is still suboptimal for many patients, which has clinical and cost implications. This study aimed to explore perspectives of various stakeholders on barriers to timely access creation. Study Design Qualitative study. Setting & Participants Semi-structured interviews with 96 participants (response rate, 67%), including patients with stage 4 chronic kidney disease (n = 30), new hemodialysis patients with (n = 18) and without (n = 20) permanent access (arteriovenous fistula), family members (n = 19), and kidney health care providers (n = 9). Analytical Approach Thematic analysis. Results Patients reported differential levels of behavioral activation toward access creation: avoidance/denial, wait and see, or active intention. 6 core themes were identified: (1) lack of symptoms, (2) dialysis fear and practical concerns (exaggerated fear, pain, cost, lifestyle disruptions, work-related concerns, burdening their families), (3) evaluating value against costs/risks of access creation (benefits, threat of operation, viability, prompt for early initiation), (4) preference for alternatives, (5) social influences (hearsay, family involvement, experiences of others), and (6) health care provider interactions (mistrust, interpersonal tension, lack of clarity on information). Themes were common to all groups, whereas nuanced perspectives of family members and health care providers were noted in some subthemes. Limitations Response bias. Conclusions Individual, interpersonal, and psychosocial factors compromise dialysis preparation and contribute to suboptimal dialysis initiation. Our findings support the need for interventions to improve patient and family engagement and address emotional concerns and misperceptions about preparing for dialysis