Adaptive Algorithms for Personalized Diabetes Treatment

Dynamic systems, especially in real-life applications, are often determined by inter-/intra-variability, uncertainties and time-varying components. Physiological systems are probably the most representative example in which population variability, vital signal measurement noise and uncertain dynamics render their explicit representation and optimization a rather difficult task. Systems characterized by such challenges often require the use of adaptive algorithmic solutions able to perform an iterative structural and/or parametrical update process towards optimized behavior. Adaptive optimization presents the advantages of (i) individualization through learning of basic system characteristics, (ii) ability to follow time-varying dynamics and (iii) low computational cost. In this chapter, the use of online adaptive algorithms is investigated in two basic research areas related to diabetes management: (i) real-time glucose regulation and (ii) real-time prediction of hypo-/hyperglycemia. The applicability of these methods is illustrated through the design and development of an adaptive glucose control algorithm based on reinforcement learning and optimal control and an adaptive, personalized early-warning system for the recognition and alarm generation against hypo- and hyperglycemic events.

Modeling corrective experiences as motivational mountain pass

Aim: The landscape metaphor allows viewing corrective experiences (CE) as pathway to a state with relatively lower 'tension' (local minimum). However, such local minima are not easily accessible but obstructed by states with relatively high tension (local maxima) according to the landscape metaphor (Caspar & Berger, 2012). For example, an individual with spider phobia has to transiently tolerate high levels of tension during an exposure therapy to access the local minimum of habituation. To allow for more specific therapeutic guidelines and empirically testable hypotheses, we advance the landscape metaphor to a scientific model which bases on motivational processes. Specifically, we conceptualize CEs as available but unusual trajectories (=pathways) through a motivational space. The dimensions of the motivational state are set up by basic motives such as need for agency or attachment. Methods: Dynamic system theory is used to model motivational states and trajectories using mathematical equations. Fortunately, these equations have easy-to-comprehend and intuitive visual representations similar to the landscape metaphor. Thus, trajectories that represent CEs are informative and action guiding for both therapists and patients without knowledge on dynamic systems. However, the mathematical underpinnings of the model allow researchers to deduct hypotheses for empirical testing. Results: First, the results of simulations of CEs during exposure therapy in anxiety disorders are presented and compared to empirical findings. Second, hypothetical CEs in an autonomy-attachment conflict are reported from a simulation study. Discussion: Preliminary clinical implications for the evocation of CEs are drawn after a critical discussion of the proposed model.

Influence of screw augmentation in posterior dynamic and rigid stabilization systems in osteoporotic lumbar vertebrae: a biomechanical cadaveric study.

STUDY DESIGN Biomechanical cadaveric study. OBJECTIVE To determine whether augmentation positively influence screw stability or not. SUMMARY OF BACKGROUND DATA Implantation of pedicle screws is a common procedure in spine surgery to provide an anchorage of posterior internal fixation into vertebrae. Screw performance is highly correlated to bone quality. Therefore, polymeric cement is often injected through specifically designed perforated pedicle screws into osteoporotic bone to potentially enhance screw stability. METHODS Caudocephalic dynamic loading was applied as quasi-physiological alternative to classical pull-out tests on 16 screws implanted in osteoporotic lumbar vertebrae and 20 screws in nonosteoporotic specimen. Load was applied using 2 different configurations simulating standard and dynamic posterior stabilization devices. Screw performance was quantified by measurement of screwhead displacement during the loading cycles. To reduce the impact of bone quality and morphology, screw performance was compared for each vertebra and averaged afterward. RESULTS All screws (with or without cement) implanted in osteoporotic vertebrae showed lower performances than the ones implanted into nonosteoporotic specimen. Augmentation was negligible for screws implanted into nonosteoporotic specimen, whereas in osteoporotic vertebrae pedicle screw stability was significantly increased. For dynamic posterior stabilization system an increase of screwhead displacement was observed in comparison with standard fixation devices in both setups. CONCLUSION Augmentation enhances screw performance in patients with poor bone stock, whereas no difference is observed for patients without osteoporosis. Furthermore, dynamic stabilization systems have the possibility to fail when implanted in osteoporotic bone.

Dynamic computer simulations of electrophoresis: a versatile research and teaching tool

Software is available, which simulates all basic electrophoretic systems, including moving boundary electrophoresis, zone electrophoresis, ITP, IEF and EKC, and their combinations under almost exactly the same conditions used in the laboratory. These dynamic models are based upon equations derived from the transport concepts such as electromigration, diffusion, electroosmosis and imposed hydrodynamic buffer flow that are applied to user-specified initial distributions of analytes and electrolytes. They are able to predict the evolution of electrolyte systems together with associated properties such as pH and conductivity profiles and are as such the most versatile tool to explore the fundamentals of electrokinetic separations and analyses. In addition to revealing the detailed mechanisms of fundamental phenomena that occur in electrophoretic separations, dynamic simulations are useful for educational purposes. This review includes a list of current high-resolution simulators, information on how a simulation is performed, simulation examples for zone electrophoresis, ITP, IEF and EKC and a comprehensive discussion of the applications and achievements.

A Systems-Level Approach to Human Epileptic Seizures

Epileptic seizures are due to the pathological collective activity of large cellular assemblies. A better understanding of this collective activity is integral to the development of novel diagnostic and therapeutic procedures. In contrast to reductionist analyses, which focus solely on small-scale characteristics of ictogenesis, here we follow a systems-level approach, which combines both small-scale and larger-scale analyses. Peri-ictal dynamics of epileptic networks are assessed by studying correlation within and between different spatial scales of intracranial electroencephalographic recordings (iEEG) of a heterogeneous group of patients suffering from pharmaco-resistant epilepsy. Epileptiform activity as recorded by a single iEEG electrode is determined objectively by the signal derivative and then subjected to a multivariate analysis of correlation between all iEEG channels. We find that during seizure, synchrony increases on the smallest and largest spatial scales probed by iEEG. In addition, a dynamic reorganization of spatial correlation is observed on intermediate scales, which persists after seizure termination. It is proposed that this reorganization may indicate a balancing mechanism that decreases high local correlation. Our findings are consistent with the hypothesis that during epileptic seizures hypercorrelated and therefore functionally segregated brain areas are re-integrated into more collective brain dynamics. In addition, except for a special sub-group, a highly significant association is found between the location of ictal iEEG activity and the location of areas of relative decrease of localised EEG correlation. The latter could serve as a clinically important quantitative marker of the seizure onset zone (SOZ).

A global ”imaging” view on systems approaches in immunology

The immune system exhibits an enormous complexity. High throughput methods such as the "-omic'' technologies generate vast amounts of data that facilitate dissection of immunological processes at ever finer resolution. Using high-resolution data-driven systems analysis, causal relationships between complex molecular processes and particular immunological phenotypes can be constructed. However, processes in tissues, organs, and the organism itself (so-called higher level processes) also control and regulate the molecular (lower level) processes. Reverse systems engineering approaches, which focus on the examination of the structure, dynamics and control of the immune system, can help to understand the construction principles of the immune system. Such integrative mechanistic models can properly describe, explain, and predict the behavior of the immune system in health and disease by combining both higher and lower level processes. Moving from molecular and cellular levels to a multiscale systems understanding requires the development of methodologies that integrate data from different biological levels into multiscale mechanistic models. In particular, 3D imaging techniques and 4D modeling of the spatiotemporal dynamics of immune processes within lymphoid tissues are central for such integrative approaches. Both dynamic and global organ imaging technologies will be instrumental in facilitating comprehensive multiscale systems immunology analyses as discussed in this review.

The new insight into dynamic crossover in glass forming liquids from the apparent enthalpy analysis

One of the most intriguing phenomena in glass forming systems is the dynamic crossover (T(B)), occurring well above the glass temperature (T(g)). So far, it was estimated mainly from the linearized derivative analysis of the primary relaxation time τ(T) or viscosity η(T) experimental data, originally proposed by Stickel et al. [J. Chem. Phys. 104, 2043 (1996); J. Chem. Phys. 107, 1086 (1997)]. However, this formal procedure is based on the general validity of the Vogel-Fulcher-Tammann equation, which has been strongly questioned recently [T. Hecksher et al. Nature Phys. 4, 737 (2008); P. Lunkenheimer et al. Phys. Rev. E 81, 051504 (2010); J. C. Martinez-Garcia et al. J. Chem. Phys. 134, 024512 (2011)]. We present a qualitatively new way to identify the dynamic crossover based on the apparent enthalpy space (H(a)(') = dlnτ/d(1/T)) analysis via a new plot lnH(a)(') vs. 1∕T supported by the Savitzky-Golay filtering procedure for getting an insight into the noise-distorted high order derivatives. It is shown that depending on the ratio between the "virtual" fragility in the high temperature dynamic domain (m(high)) and the "real" fragility at T(g) (the low temperature dynamic domain, m = m(low)) glass formers can be splitted into two groups related to f < 1 and f > 1, (f = m(high)∕m(low)). The link of this phenomenon to the ratio between the apparent enthalpy and activation energy as well as the behavior of the configurational entropy is indicated.

Predicting asthma control and exacerbations: chronic asthma as a complex dynamic model

PURPOSE OF REVIEW: Predicting asthma episodes is notoriously difficult but has potentially significant consequences for the individual, as well as for healthcare services. The purpose of this review is to describe recent insights into the prediction of acute asthma episodes in relation to classical clinical, functional or inflammatory variables, as well as present a new concept for evaluating asthma as a dynamically regulated homeokinetic system. RECENT FINDINGS: Risk prediction for asthma episodes or relapse has been attempted using clinical scoring systems, considerations of environmental factors and lung function, as well as inflammatory and immunological markers in induced sputum or exhaled air, and these are summarized here. We have recently proposed that newer mathematical methods derived from statistical physics may be used to understand the complexity of asthma as a homeokinetic, dynamic system consisting of a network comprising multiple components, and also to assess the risk for future asthma episodes based on fluctuation analysis of long time series of lung function. SUMMARY: Apart from the classical analysis of risk factor and functional parameters, this new approach may be used to assess asthma control and treatment effects in the individual as well as in future research trials.

Theoretical considerations to the verification of dynamic multileaf collimated fields with a SLIC-type portal image detector

The verification possibilities of dynamically collimated treatment beams with a scanning liquid ionization chamber electronic portal image device (SLIC-EPID) are investigated. The ion concentration in the liquid of a SLIC-EPID and therefore the read-out signal is determined by two parameters of a differential equation describing the creation and recombination of the ions. Due to the form of this equation, the portal image detector describes a nonlinear dynamic system with memory. In this work, the parameters of the differential equation were experimentally determined for the particular chamber in use and for an incident open 6 MV photon beam. The mathematical description of the ion concentration was then used to predict portal images of intensity-modulated photon beams produced by a dynamic delivery technique, the sliding window approach. Due to the nature of the differential equation, a mathematical condition for 'reliable leaf motion verification' in the sliding window technique can be formulated. It is shown that the time constants for both formation and decay of the equilibrium concentration in the chamber is in the order of seconds. In order to guarantee reliable leaf motion verification, these time constants impose a constraint on the rapidity of the image-read out for a given maximum leaf speed. For a leaf speed of 2 cm s(-1), a minimum image acquisition frequency of about 2 Hz is required. Current SLIC-EPID systems are usually too slow since they need about a second to acquire a portal image. However, if the condition is fulfilled, the memory property of the system can be used to reconstruct the leaf motion. It is shown that a simple edge detecting algorithm can be employed to determine the leaf positions. The method is also very robust against image noise.

Dynamic computer simulations of electrophoresis: three decades of active research

Dynamic models for electrophoresis are based upon model equations derived from the transport concepts in solution together with user-inputted conditions. They are able to predict theoretically the movement of ions and are as such the most versatile tool to explore the fundamentals of electrokinetic separations. Since its inception three decades ago, the state of dynamic computer simulation software and its use has progressed significantly and Electrophoresis played a pivotal role in that endeavor as a large proportion of the fundamental and application papers were published in this periodical. Software is available that simulates all basic electrophoretic systems, including moving boundary electrophoresis, zone electrophoresis, ITP, IEF and EKC, and their combinations under almost exactly the same conditions used in the laboratory. This has been employed to show the detailed mechanisms of many of the fundamental phenomena that occur in electrophoretic separations. Dynamic electrophoretic simulations are relevant for separations on any scale and instrumental format, including free-fluid preparative, gel, capillary and chip electrophoresis. This review includes a historical overview, a survey of current simulators, simulation examples and a discussion of the applications and achievements of dynamic simulation.