In health care the reimbursement of medical providers is an important topic and can influence the overall outcome. We present the agent-based GAP-DRG model, which allows a comparison of reimbursement schemes in outpatient care. It models patients and medical providers as agents. In the simulation patients develop medical problems (i.e., diseases) and a need for medical services. This leads to utilization of medical providers. The reimbursement system receives information on the patients' visits via its generic interface, which facilitates an easy replacement. We describe the assumptions of the model in detail and show how it makes extensive use of available Austrian routine care data for its parameterization. The model design is optimized for utilizing as much of these data as possible. However, many assumptions have to be simplifications. Further work and detailed comparisons with health care data will provide insight on which assumptions are valid descriptions of the real process.

The decision to adopt organized screening is likely an efficient use of limited health care resources in Austria.

Anti-fibrotic therapies are of increasing interest to combat cardiac remodeling and heart failure progression. Recently, anti-fibrotic circular RNAs (circRNAs) have been identified in human and rodent cardiac tissue. In vivo (rodent) experiments proved cardiac anti-fibrotic effects of the natural compounds bufalin and lycorine by downregulating miRNA-671-5p, associated with a theoretic increase in the tissue level of circRNA CDR1as. Accordingly, we hypothesized that both anti-fibrotic drugs may inhibit focal myocardial fibrosis of the remodeled left ventricle (LV) also in a translational large animal model of heart failure (HF). Domestic pigs were repeatedly treated with subcutaneous injections of either bufalin, lycorine, or saline, (n = 5/group) between days 7–21 post acute myocardial infarction (AMI). At the 2-month follow-up, both bufalin and lycorine led to significantly reduced cardiac fibrosis. Bufalin treatment additionally led to smaller end-diastolic volumes, higher LV ejection fraction (EF), and increased expression of CDR1as of the AMI region. Elevated tissue levels of the circRNA CDR1as in the AMI region of the pig heart correlated significantly with LV and right ventricular EF, LV stroke volume, and negatively with infarct size. In conclusion, we successfully identified the circRNA CDR1as in pig hearts and show a significant association with improved LV and RV function by anti-fibrotic therapies in a translational animal model of HF.

Circular RNAs (circRNAs) are classified as long non-coding RNAs (lncRNAs) that are characterized by a covalent closed-loop structure. This closed-loop shape is the result of a backsplicing event in which the 3' and 5' splice sites are ligated. Through the lack of 3' poly(A) tails and 5' cap structures, circRNAs are more stable than linear RNAs because these adjustments make the circular loop less susceptible to exonucleases. The majority of identified circRNAs possess cell-and tissue-specific expression patterns. In addition, high-throughput RNA-sequencing combined with novel bioinformatics algorithms revealed that circRNA sequences are often conserved across different species suggesting a positive evolutionary pressure. Implicated as regulators of protein turnover, micro RNA (miRNA) sponges, or broad effectors in cell differentiation, proliferation, and senescence, research of circRNA has increased in recent years. Particularly in cardiovascular research, circRNArelated discoveries have opened the door for the development of potential diagnostic and therapeutic tools. Increasing evidence links deviating circRNA expression patterns to various cardiovascular diseases including ischemic heart failure. In this mini-review, we summarize the current state of knowledge on circRNAs in cardiac regeneration with a focus on cardiac cell proliferation, differentiation, cardiomyocyte survival, and cardiac reprogramming.

Part 1: Information & Communication Technology-EurAsia Conference 2014, ICT-EurAsia 2014International audienceAgent-based modeling is a method to model a system by autonomous entities. The proposed framework models single persons with personal behavior, different health states and ability to spread the disease. Upon simulation, the epidemic emerges automatically. This approach is clear and easily understandable but requires extensive knowledge of the epidemic’s background. Such real-world model structures produce realistic epidemics, allowing detailed examination of the transmission process or testing and analyzing the outcome of interventions like vaccinations. Due to changed epidemic propagation, effects like herd immunity or serotype shift arise automatically. Beyond that, a modular structure splits the model into parts, which can be developed and validated separately. This approach makes development more efficient, increases credibility of the results and allows reusability and exchangeability of existing modules. Thus, knowledge and models can be easily and efficiently transferred, for example to compute scenarios for different countries and similar diseases