Inhibition of Fas-associated death domain-containing protein (FADD) protects against myocardial ischemia/reperfusion injury in a heart failure mouse model

AIM As technological interventions treating acute myocardial infarction (MI) improve, post-ischemic heart failure increasingly threatens patient health. The aim of the current study was to test whether FADD could be a potential target of gene therapy in the treatment of heart failure. METHODS Cardiomyocyte-specific FADD knockout mice along with non-transgenic littermates (NLC) were subjected to 30 minutes myocardial ischemia followed by 7 days of reperfusion or 6 weeks of permanent myocardial ischemia via the ligation of left main descending coronary artery. Cardiac function were evaluated by echocardiography and left ventricular (LV) catheterization and cardiomyocyte death was measured by Evans blue-TTC staining, TUNEL staining, and caspase-3, -8, and -9 activities. In vitro, H9C2 cells transfected with ether scramble siRNA or FADD siRNA were stressed with chelerythrin for 30 min and cleaved caspase-3 was assessed. RESULTS FADD expression was significantly decreased in FADD knockout mice compared to NLC. Ischemia/reperfusion (I/R) upregulated FADD expression in NLC mice, but not in FADD knockout mice at the early time. FADD deletion significantly attenuated I/R-induced cardiac dysfunction, decreased myocardial necrosis, and inhibited cardiomyocyte apoptosis. Furthermore, in 6 weeks long term permanent ischemia model, FADD deletion significantly reduced the infarct size (from 41.20 ± 3.90% in NLC to 26.83 ± 4.17% in FADD deletion), attenuated myocardial remodeling, improved cardiac function and improved survival. In vitro, FADD knockdown significantly reduced chelerythrin-induced the level of cleaved caspase-3. CONCLUSION Taken together, our results suggest FADD plays a critical role in post-ischemic heart failure. Inhibition of FADD retards heart failure progression. Our data supports the further investigation of FADD as a potential target for genetic manipulation in the treatment of heart failure.

BNP-guided vs symptom-guided heart failure therapy: the Trial of Intensified vs Standard Medical Therapy in Elderly Patients With Congestive Heart Failure (TIME-CHF) randomized trial

CONTEXT: It is uncertain whether intensified heart failure therapy guided by N-terminal brain natriuretic peptide (BNP) is superior to symptom-guided therapy. OBJECTIVE: To compare 18-month outcomes of N-terminal BNP-guided vs symptom-guided heart failure therapy. DESIGN, SETTING, AND PATIENTS: Randomized controlled multicenter Trial of Intensified vs Standard Medical Therapy in Elderly Patients With Congestive Heart Failure (TIME-CHF) of 499 patients aged 60 years or older with systolic heart failure (ejection fraction < or = 45%), New York Heart Association (NYHA) class of II or greater, prior hospitalization for heart failure within 1 year, and N-terminal BNP level of 2 or more times the upper limit of normal. The study had an 18-month follow-up and it was conducted at 15 outpatient centers in Switzerland and Germany between January 2003 and June 2008. INTERVENTION: Uptitration of guideline-based treatments to reduce symptoms to NYHA class of II or less (symptom-guided therapy) and BNP level of 2 times or less the upper limit of normal and symptoms to NYHA class of II or less (BNP-guided therapy). MAIN OUTCOME MEASURES: Primary outcomes were 18-month survival free of all-cause hospitalizations and quality of life as assessed by structured validated questionnaires. RESULTS: Heart failure therapy guided by N-terminal BNP and symptom-guided therapy resulted in similar rates of survival free of all-cause hospitalizations (41% vs 40%, respectively; hazard ratio [HR], 0.91 [95% CI, 0.72-1.14]; P = .39). Patients' quality-of-life metrics improved over 18 months of follow-up but these improvements were similar in both the N-terminal BNP-guided and symptom-guided strategies. Compared with the symptom-guided group, survival free of hospitalization for heart failure, a secondary end point, was higher among those in the N-terminal BNP-guided group (72% vs 62%, respectively; HR, 0.68 [95% CI, 0.50-0.92]; P = .01). Heart failure therapy guided by N-terminal BNP improved outcomes in patients aged 60 to 75 years but not in those aged 75 years or older (P < .02 for interaction) CONCLUSION: Heart failure therapy guided by N-terminal BNP did not improve overall clinical outcomes or quality of life compared with symptom-guided treatment. TRIAL REGISTRATION: isrctn.org Identifier: ISRCTN43596477.

Appropriateness and long-term discontinuation rate of biological therapies in ulcerative colitis

BACKGROUND Anti-TNFα agents are commonly used for ulcerative colitis (UC) therapy in the event of non-response to conventional strategies or as colon-salvaging therapy. The objectives were to assess the appropriateness of biological therapies for UC patients and to study treatment discontinuation over time, according to appropriateness of treatment, as a measure of outcome. METHODS We selected adult ulcerative colitis patients from the Swiss IBD cohort who had been treated with anti-TNFα agents. Appropriateness of the first-line anti-TNFα treatment was assessed using detailed criteria developed during the European Panel on the Appropriateness of Therapy for UC. Treatment discontinuation as an outcome was assessed for categories of appropriateness. RESULTS Appropriateness of the first-line biological treatment was determined in 186 UC patients. For 64% of them, this treatment was considered appropriate. During follow-up, 37% of all patients discontinued biological treatment, 17% specifically because of failure. Time-to-failure of treatment was significantly different among patients on an appropriate biological treatment compared to those for whom the treatment was considered not appropriate (p=0.0007). Discontinuation rate after 2years was 26% compared to 54% between those two groups. Patients on inappropriate biological treatment were more likely to have severe disease, concomitant steroids and/or immunomodulators. They were also consistently more likely to suffer a failure of efficacy and to stop therapy during follow-up. CONCLUSION Appropriateness of first-line anti-TNFα therapy results in a greater likelihood of continuing with the therapy. In situations where biological treatment is uncertain or inappropriate, physicians should consider other options instead of prescribing anti-TNFα agents.

A model of ischemic isolated acute liver failure in pigs: standardizing monitoring and treatment

Acute liver failure (ALF) models in pigs have been widely used for evaluating newly developed liver support systems. But hardly any guidelines are available for the surgical methods and the clinical management.

An Urn Model for Cascading Failures on a Lattice

A cascading failure is a failure in a system of interconnected parts, in which the breakdown of one element can lead to the subsequent collapse of the others. The aim of this paper is to introduce a simple combinatorial model for the study of cascading failures. In particular, having in mind particle systems and Markov random fields, we take into consideration a network of interacting urns displaced over a lattice. Every urn is Pólya-like and its reinforcement matrix is not only a function of time (time contagion) but also of the behavior of the neighboring urns (spatial contagion), and of a random component, which can represent either simple fate or the impact of exogenous factors. In this way a non-trivial dependence structure among the urns is built, and it is used to study default avalanches over the lattice. Thanks to its flexibility and its interesting probabilistic properties, the given construction may be used to model different phenomena characterized by cascading failures such as power grids and financial networks.

Evolutionary demography of long-lived monocarpic perennials: a time-lagged integral projection model

1. The evolution of flowering strategies (when and at what size to flower) in monocarpic perennials is determined by balancing current reproduction with expected future reproduction, and these are largely determined by size-specific patterns of growth and survival. However, because of the difficulty in following long-lived individuals throughout their lives, this theory has largely been tested using short-lived species (< 5 years). 2. Here, we tested this theory using the long-lived monocarpic perennial Campanula thyrsoides which can live up to 16 years. We used a novel approach that combined permanent plot and herb chronology data from a 3-year field study to parameterize and validate integral projection models (IPMs). 3. Similar to other monocarpic species, the rosette leaves of C. thyrsoides wither over winter and so size cannot be measured in the year of flowering. We therefore extended the existing IPM framework to incorporate an additional time delay that arises because flowering demography must be predicted from rosette size in the year before flowering. 4. We found that all main demographic functions (growth, survival probability, flowering probability and fecundity) were strongly size-dependent and there was a pronounced threshold size of flowering. There was good agreement between the predicted distribution of flowering ages obtained from the IPMs and that estimated in the field. Mostly, there was good agreement between the IPM predictions and the direct quantitative field measurements regarding the demographic parameters lambda, R-0 and T. We therefore conclude that the model captures the main demographic features of the field populations. 5. Elasticity analysis indicated that changes in the survival and growth function had the largest effect (c. 80%) on lambda and this was considerably larger than in short-lived monocarps. We found only weak selection pressure operating on the observed flowering strategy which was close to the predicted evolutionary stable strategy. 6. Synthesis. The extended IPM accurately described the demography of a long-lived monocarpic perennial using data collected over a relatively short period. We could show that the evolution of flowering strategies in short- and long-lived monocarps seem to follow the same general rules but with a longevity-related emphasis on survival over fecundity.

A real time simulation model of glucose-insulin metabolism for type 1 diabetes patients

In this paper, a simulation model of glucose-insulin metabolism for Type 1 diabetes patients is presented. The proposed system is based on the combination of Compartmental Models (CMs) and artificial Neural Networks (NNs). This model aims at the development of an accurate system, in order to assist Type 1 diabetes patients to handle their blood glucose profile and recognize dangerous metabolic states. Data from a Type 1 diabetes patient, stored in a database, have been used as input to the hybrid system. The data contain information about measured blood glucose levels, insulin intake, and description of food intake, along with the corresponding time. The data are passed to three separate CMs, which produce estimations about (i) the effect of Short Acting (SA) insulin intake on blood insulin concentration, (ii) the effect of Intermediate Acting (IA) insulin intake on blood insulin concentration, and (iii) the effect of carbohydrate intake on blood glucose absorption from the gut. The outputs of the three CMs are passed to a Recurrent NN (RNN) in order to predict subsequent blood glucose levels. The RNN is trained with the Real Time Recurrent Learning (RTRL) algorithm. The resulted blood glucose predictions are promising for the use of the proposed model for blood glucose level estimation for Type 1 diabetes patients.

A continuous-time MILP model for short-term scheduling of make-and-pack production processes

In process industries, make-and-pack production is used to produce food and beverages, chemicals, and metal products, among others. This type of production process allows the fabrication of a wide range of products in relatively small amounts using the same equipment. In this article, we consider a real-world production process (cf. Honkomp et al. 2000. The curse of reality – why process scheduling optimization problems are diffcult in practice. Computers & Chemical Engineering, 24, 323–328.) comprising sequence-dependent changeover times, multipurpose storage units with limited capacities, quarantine times, batch splitting, partial equipment connectivity, and transfer times. The planning problem consists of computing a production schedule such that a given demand of packed products is fulfilled, all technological constraints are satisfied, and the production makespan is minimised. None of the models in the literature covers all of the technological constraints that occur in such make-and-pack production processes. To close this gap, we develop an efficient mixed-integer linear programming model that is based on a continuous time domain and general-precedence variables. We propose novel types of symmetry-breaking constraints and a preprocessing procedure to improve the model performance. In an experimental analysis, we show that small- and moderate-sized instances can be solved to optimality within short CPU times.

A Nonstationary Space-Time Gaussian Process Model for Partially Converged Simulations

In the context of expensive numerical experiments, a promising solution for alleviating the computational costs consists of using partially converged simulations instead of exact solutions. The gain in computational time is at the price of precision in the response. This work addresses the issue of fitting a Gaussian process model to partially converged simulation data for further use in prediction. The main challenge consists of the adequate approximation of the error due to partial convergence, which is correlated in both design variables and time directions. Here, we propose fitting a Gaussian process in the joint space of design parameters and computational time. The model is constructed by building a nonstationary covariance kernel that reflects accurately the actual structure of the error. Practical solutions are proposed for solving parameter estimation issues associated with the proposed model. The method is applied to a computational fluid dynamics test case and shows significant improvement in prediction compared to a classical kriging model.

The long arm of time pressure at work: Cognitive failure and commuting near-accidents

This study tests whether cognitive failures mediate effects of work-related time pressure and time control on commuting accidents and near-accidents. Participants were 83 employees (56% female) who each commuted between their regular place of residence and place of work using vehicles. The Workplace Cognitive Failure Scale (WCFS) asked for the frequency of failure in memory function, failure in attention regulation, and failure in action execution. Time pressure and time control at work were assessed by the Instrument for Stress Oriented Task Analysis (ISTA). Commuting accidents in the last 12 months were reported by 10% of participants, and half of the sample reported commuting near-accidents in the last 4 weeks. Cognitive failure significantly mediated the influence of time pressure at work on near-accidents even when age, gender, neuroticism, conscientiousness, commuting duration, commuting distance, and time pressure during commuting were controlled for. Time control was negatively related to cognitive failure and neuroticism, but no association with commuting accidents or near-accidents was found. Time pressure at work is likely to increase cognitive load. Time pressure might, therefore, increase cognitive failures during work and also during commuting. Hence, time pressure at work can decrease commuting safety. The result suggests a reduction of time pressure at work should improve commuting safety.