Consequences of somatic mutations of GIRK1 detected in primary malign tumors on expression and function of G-protein activated, inwardly rectifying, K+ channels.

A search in the GDC Data Portal revealed 304 documented somatic mutations of the KCNJ3 gene in primary tumors (out of 10.202 cases). Most affected tumor types were carcinomas from uterus, skin and lung, while breast cancer exerted the lowest number of somatic mutations. We focused our research on 15 missense mutations within the region between TM1 and TM2, comprising the pore helix and ion selectivity signature. Expression was measured by confocal laser scan microscopy of eGFP tagged GIRK1 subunits, expressed with and without GIRK4 in oocytes of Xenopus laevis. GIRK ion currents were activated via coexpressed m2Rs and measured by the Two Electrode Voltage Clamp technique. Magnitude of the total GIRK current, as well as the fraction of current inducible by the agonist, were measured. Ion selectivity was gauged by assessment of the PNa+/PK+ ratio, calculated by the GIRK current reversal potential in extracellular media at different Na+ and K+ concentrations. None of the tested mutations was able to form functional GIRK1 homooligomeric ion channels. One of the mutations, G145A, which locates directly to the ion selectivity signature, exerted an increased PNa+/PK+ ratio. Generally, the missense mutations studied can be categorized into three groups: (i) normal/reduced expression accompanied by reduced/absent function (S132Y, F136L, E139K, G145A, R149Q, R149P, G178D, S185Y, Q186R), (ii) normal/increased expression as well as increased function (E140M, A142T, M184I) and (iii) miniscule expression but increased function relative to expression levels (I151N, G158S). We conclude, that gain of function mutations, identical or similar to categories (ii) and (iii), may potentially be involved in genesis and progression of malignancies in tissues that exert a high rate of occurrence of somatic mutations of KCNJ3.

A novel hybrid modeling approach for the evaluation of integrated care and economic outcome in heart failure treatment.

BACKGROUND: Demographic changes, increased life expectancy and the associated rise in chronic diseases pose challenges to public health care systems. Optimized treatment methods and integrated concepts of care are potential solutions to overcome increasing financial burdens and improve quality of care. In this context modeling is a powerful tool to evaluate potential benefits of different treatment procedures on health outcomes as well as health care budgets. This work presents a novel modeling approach for simulating different treatment procedures of heart failure patients based on extensive data sets from outpatient and inpatient care. METHODS: Our hybrid heart failure model is based on discrete event and agent based methodologies and facilitates the incorporation of different therapeutic procedures for outpatient and inpatient care on patient individual level. The state of health is modeled with the functional classification of the New York Heart Association (NYHA), strongly affecting discrete state transition probabilities alongside age and gender. Cooperation with Austrian health care and health insurance providers allowed the realization of a detailed model structure based on clinical data of more than 25,000 patients. RESULTS: Simulation results of conventional care and a telemonitoring program underline the unfavorable prognosis for heart failure and reveal the correlation of NYHA classes with health and economic outcomes. Average expenses for the treatment of NYHA class IV patients of €10,077 ± €165 were more than doubled compared to other classes. The selected use case of a telemonitoring program demonstrated potential cost savings within two years of application. NYHA classes II and III revealed most potential for additional treatment measures. CONCLUSION: The presented model allows performing extensive simulations of established treatment procedures for heart failure patients and evaluating new holistic methods of care and innovative study designs. This approach offers health care providers a unique, adaptable and comprehensive tool for decision making in the complex and socioeconomically challenging field of cardiovascular diseases.

BMI and specimen weight: impact on personalized risk profiling for optimized informed consent in breast reduction surgery?

We aimed to evaluate the interaction between individual risk factors and institutional complication rates after reduction mammaplasties to develop a chart for a personalized written patient informed consent. We retrospectively reviewed charts of 804 patients who underwent bilateral breast reduction between 2005 and 2015. The Clavien-Dindo classification was used to classify postoperative complications. Relevant predictors were found by applying a stepwise variable selection procedure. Multilevel predictors were assessed through chi-square tests on the respective deviance reductions. 486 patients were included. The most common complications were wound healing problems (n = 270/56%), foreign body reactions (n = 58/12%), wound infections (n = 45/9, 3%) and fat tissue necrosis (n = 41/8%). The risk factors for the personalized patient chart for the most common complications influencing the preoperative informed consent were: smoking, operative technique, resection weight for wound healing problems; body mass index and allergies for wound infections; and patients' age, resection weight for fat tissue necrosis. The resultant chart of institutionally encountered most common complications based on individual risk factors is a graphical template for obtaining patient informed consent in the future. Whether this approach influences patient information retainment, incidence of filed lawsuits or behavioral change needs to be prospectively tested in future studies.