Slow conduction in mixed cultured strands of primary ventricular cells and stem cell-derived cardiomyocytes

Modern concepts for the treatment of myocardial diseases focus on novel cell therapeutic strategies involving stem cell-derived cardiomyocytes (SCMs). However, functional integration of SCMs requires similar electrophysiological properties as primary cardiomyocytes (PCMs) and the ability to establish intercellular connections with host myocytes in order to contribute to the electrical and mechanical activity of the heart. The aim of this project was to investigate the properties of cardiac conduction in a co-culture approach using SCMs and PCMs in cultured cell strands. Murine embryonic SCMs were pooled with fetal ventricular cells and seeded in predefined proportions on microelectrode arrays to form patterned strands of mixed cells. Conduction velocity (CV) was measured during steady state pacing. SCM excitability was estimated from action potentials measured in single cells using the patch clamp technique. Experiments were complemented with computer simulations of conduction using a detailed model of cellular architecture in mixed cell strands. CV was significantly lower in strands composed purely of SCMs (5.5 ± 1.5 cm/s, n = 11) as compared to PCMs (34.9 ± 2.9 cm/s, n = 21) at similar refractoriness (100% SCMs: 122 ± 25 ms, n = 9; 100% PCMs: 139 ± 67 ms, n = 14). In mixed strands combining both cell types, CV was higher than in pure SCMs strands, but always lower than in 100% PCM strands. Computer simulations demonstrated that both intercellular coupling and electrical excitability limit CV. These data provide evidence that in cultures of murine ventricular cardiomyocytes, SCMs cannot restore CV to control levels resulting in slow conduction, which may lead to reentry circuits and arrhythmias.

Disentangling mental imagery and perceptual expectation

Mental imagery and perception are thought to rely on similar neural circuits, and many recent behavioral studies have attempted to demonstrate interactions between actual physical stimulation and sensory imagery in the corresponding sensory modality. However, there has been a lack of theoretical understanding of the nature of these interactions, and both interferential and facilitatory effects have been found. Facilitatory effects appear strikingly similar to those that arise due to experimental manipulations of expectation. Using a self-motion discrimination task, we try to disentangle the effects of mental imagery from those of expectation by using a hierarchical drift diffusion model to investigate both choice data and response times. Manipulations of expectation are reasonably well understood in terms of their selective influence on parameters of the drift diffusion model, and in this study, we make the first attempt to similarly characterize the effects of mental imagery. We investigate mental imagery within the computational framework of control theory and state estimation. • Mental imagery and perception are thought to rely on similar neural circuits; however, on more theoretical grounds, imagery seems to be closely related to the output of forward models (sensory predictions). • We reanalyzed data from a study of imagined self-motion. • Bayesian modeling of response times may allow us to disentangle the effects of mental imagery on behavior from other cognitive (top-down) effects, such as expectation.

Invited review: Growth-promoting effects of colostrum in calves based on interaction with intestinal cell surface receptors and receptor-like transporters

The postnatal development and maturation of the gastrointestinal (GI) tract of neonatal calves is crucial for their survival. Major morphological and functional changes in the calf's GI tract initiated by colostrum bioactive substances promote the establishment of intestinal digestion and absorption of food. It is generally accepted that colostrum intake provokes the maturation of organs and systems in young calves, illustrating the significance of the cow-to-calf connection at birth. These postnatal adaptive changes of the GI tissues in neonatal calves are especially induced by the action of bioactive substances such as insulin-like growth factors, hormones, or cholesterol carriers abundantly present in colostrum. These substances interact with specific cell-surface receptors or receptor-like transporters expressed in the GI wall of neonatal calves to elicit their biological effects. Therefore, the abundance and activity of cell surface receptors and receptor-like transporters binding colostral bioactive substances are a key aspect determining the effects of the cow-to-calf connection at birth. The present review compiles the information describing the effects of colostrum feeding on selected serum metabolic and endocrine traits in neonatal calves. In this context, the current paper discusses specifically the consequences of colostrum feeding on the GI expression and activity of cell-receptors and receptor-like transporters binding growth hormone, insulin-like growth factors, insulin, or cholesterol acceptors in neonatal calves.

[Future cardiac pacemakers – technical visions].

Cardiac pacemakers are routinely used for the treatment of bradyarrhythmias. Contemporary pacemakers are reliable and allow for a patient specific programming. However, pacemaker replacements due to battery depletion are common (~25 % of all implantation procedures) and bear the risk of complications. Batteryless pacemakers may allow overcoming this limitation. To power a batteryless pacemaker, a mechanism for intracorporeal energy harvesting is required. Such a generator may consist out of subcutaneously implanted solar cells, transforming the small amount of transcutaneously available light into electrical energy. Alternatively, intravascular turbines may harvest energy from the blood flow. Energy may also be harvested from the ventricular wall motion by a dedicated mechanical clockwork converting motion into electrical energy. All these approaches have successfully been tested in vivo. Pacemaker leads constitute another Achilles heel of contemporary pacemakers. Thus, leadless devices are desired. Miniaturized pacemaker circuits and suitable energy harvesting mechanisms (incorporated in a single device) may allow catheter-based implantation of the pacemaker in the heart. Such miniaturized battery- and leadless pacemakers would combine the advantages of both approaches and overcome major limitations of today’s systems.

The implementation of DRG-based hospital reimbursement in Switzerland: A population-based perspective

Background Switzerland introduces a DRG (Diagnosis Related Groups) based system for hospital financing in 2012 in order to increase efficiency and transparency of Swiss health care. DRG-based hospital reimbursement is not simultaneously realized in all Swiss cantons and several cantons already implemented DRG-based financing irrespective of the national agenda, a setting that provides an opportunity to compare the situation in different cantons. Effects of introducing DRGs anticipated for providers and insurers are relatively well known but it remains less clear what effects DRGs will have on served populations. The objective of the study is therefore to analyze differences of volume and major quality indicators of care between areas with or without DRG-based hospital reimbursement from a population based perspective. Methods Small area analysis of all hospitalizations in acute care hospitals and of all consultations reimbursed by mandatory basic health insurance for physicians in own practice during 2003-2007. Results The results show fewer hospitalizations and a relocation of resources to outpatient care in areas with DRG reimbursement. Overall burden of disease expressed as per capita DRG cost weights was almost identical between the two types of hospital reimbursement and no distinct temporal differences were detected in this respect. But the results show considerably higher 90-day rehospitalization rates in DRG areas. Conclusion The study provides evidence of both desired and harmful effects related to the implementation of DRGs. Systematic monitoring of outcomes and quality of care are therefore essential elements to maintain in the Swiss health system after DRG's are implemented on a nationwide basis in 2012.

Spatio-temporal credit assignment in population learning

Learning by reinforcement is important in shaping animal behavior, and in particular in behavioral decision making. Such decision making is likely to involve the integration of many synaptic events in space and time. However, using a single reinforcement signal to modulate synaptic plasticity, as suggested in classical reinforcement learning algorithms, a twofold problem arises. Different synapses will have contributed differently to the behavioral decision, and even for one and the same synapse, releases at different times may have had different effects. Here we present a plasticity rule which solves this spatio-temporal credit assignment problem in a population of spiking neurons. The learning rule is spike-time dependent and maximizes the expected reward by following its stochastic gradient. Synaptic plasticity is modulated not only by the reward, but also by a population feedback signal. While this additional signal solves the spatial component of the problem, the temporal one is solved by means of synaptic eligibility traces. In contrast to temporal difference (TD) based approaches to reinforcement learning, our rule is explicit with regard to the assumed biophysical mechanisms. Neurotransmitter concentrations determine plasticity and learning occurs fully online. Further, it works even if the task to be learned is non-Markovian, i.e. when reinforcement is not determined by the current state of the system but may also depend on past events. The performance of the model is assessed by studying three non-Markovian tasks. In the first task, the reward is delayed beyond the last action with non-related stimuli and actions appearing in between. The second task involves an action sequence which is itself extended in time and reward is only delivered at the last action, as it is the case in any type of board-game. The third task is the inspection game that has been studied in neuroeconomics, where an inspector tries to prevent a worker from shirking. Applying our algorithm to this game yields a learning behavior which is consistent with behavioral data from humans and monkeys, revealing themselves properties of a mixed Nash equilibrium. The examples show that our neuronal implementation of reward based learning copes with delayed and stochastic reward delivery, and also with the learning of mixed strategies in two-opponent games.

Modeling Features at Runtime

A feature represents a functional requirement fulfilled by a system. Since many maintenance tasks are expressed in terms of features, it is important to establish the correspondence between a feature and its implementation in source code. Traditional approaches to establish this correspondence exercise features to generate a trace of runtime events, which is then processed by post-mortem analysis. These approaches typically generate large amounts of data to analyze. Due to their static nature, these approaches do not support incremental and interactive analysis of features. We propose a radically different approach called live feature analysis, which provides a model at runtime of features. Our approach analyzes features on a running system and also makes it possible to grow feature representations by exercising different scenarios of the same feature, and identifies execution elements even to the sub-method level. We describe how live feature analysis is implemented effectively by annotating structural representations of code based on abstract syntax trees. We illustrate our live analysis with a case study where we achieve a more complete feature representation by exercising and merging variants of feature behavior and demonstrate the efficiency or our technique with benchmarks.

Run-Time Evolution through Explicit Meta-Objects

Software must be constantly adapted due to evolving domain knowledge and unanticipated requirements changes. To adapt a system at run-time we need to reflect on its structure and its behavior. Object-oriented languages introduced reflection to deal with this issue, however, no reflective approach up to now has tried to provide a unified solution to both structural and behavioral reflection. This paper describes Albedo, a unified approach to structural and behavioral reflection. Albedo is a model of fined-grained unanticipated dynamic structural and behavioral adaptation. Instead of providing reflective capabilities as an external mechanism we integrate them deeply in the environment. We show how explicit meta-objects allow us to provide a range of reflective features and thereby evolve both application models and environments at run-time.

Patient safety--who cares?

Medical errors and adverse events are a serious threat to patients worldwide. In recent years methodologically sound studies have demonstrated that interventions exist, can be implemented and can have sustainable, measurable positive effects on patient safety. Nonetheless, system-wide progress and adoption of safety practices is slow and evidence of improvements on the organisational and systems level is scarce and ambiguous. This paper reports on the Swiss Patient Safety Conference in 2011 and addresses emerging issues for patient safety and future challenges.

Using Smalltalk as a Reflective Executable Meta-Language

Object-oriented meta-languages such as MOF or EMOF are often used to specify domain specific languages. However, these meta-languages lack the ability to describe behavior or operational semantics. Several approaches used a subset of Java mixed with OCL as executable meta-languages. In this paper, we report our experience of using Smalltalk as an executable and integrated meta-language. We validated this approach in incrementally building over the last decade, Moose, a meta-described reengineering environment. The reflective capabilities of Smalltalk support a uniform way of letting the base developer focus on his tasks while at the same time allowing him to meta-describe his domain model. The advantage of our this approach is that the developer uses the same tools and environment