A general threshold stress hybrid hazard model for lifetime data

In this paper we propose a hybrid hazard regression model with threshold stress which includes the proportional hazards and the accelerated failure time models as particular cases. To express the behavior of lifetimes the generalized-gamma distribution is assumed and an inverse power law model with a threshold stress is considered. For parameter estimation we develop a sampling-based posterior inference procedure based on Markov Chain Monte Carlo techniques. We assume proper but vague priors for the parameters of interest. A simulation study investigates the frequentist properties of the proposed estimators obtained under the assumption of vague priors. Further, some discussions on model selection criteria are given. The methodology is illustrated on simulated and real lifetime data set.

Three time-based scale formulations for the two-stage lot sizing and scheduling in process industries

In this paper, we propose three novel mathematical models for the two-stage lot-sizing and scheduling problems present in many process industries. The problem shares a continuous or quasi-continuous production feature upstream and a discrete manufacturing feature downstream, which must be synchronized. Different time-based scale representations are discussed. The first formulation encompasses a discrete-time representation. The second one is a hybrid continuous-discrete model. The last formulation is based on a continuous-time model representation. Computational tests with state-of-the-art MIP solver show that the discrete-time representation provides better feasible solutions in short running time. On the other hand, the hybrid model achieves better solutions for longer computational times and was able to prove optimality more often. The continuous-type model is the most flexible of the three for incorporating additional operational requirements, at a cost of having the worst computational performance. Journal of the Operational Research Society (2012) 63, 1613-1630. doi:10.1057/jors.2011.159 published online 7 March 2012

Survival Analysis of Patients with Heart Failure: Implications of Time-Varying Regression Effects in Modeling Mortality

Background: Several models have been designed to predict survival of patients with heart failure. These, while available and widely used for both stratifying and deciding upon different treatment options on the individual level, have several limitations. Specifically, some clinical variables that may influence prognosis may have an influence that change over time. Statistical models that include such characteristic may help in evaluating prognosis. The aim of the present study was to analyze and quantify the impact of modeling heart failure survival allowing for covariates with time-varying effects known to be independent predictors of overall mortality in this clinical setting. Methodology: Survival data from an inception cohort of five hundred patients diagnosed with heart failure functional class III and IV between 2002 and 2004 and followed-up to 2006 were analyzed by using the proportional hazards Cox model and variations of the Cox's model and also of the Aalen's additive model. Principal Findings: One-hundred and eighty eight (188) patients died during follow-up. For patients under study, age, serum sodium, hemoglobin, serum creatinine, and left ventricular ejection fraction were significantly associated with mortality. Evidence of time-varying effect was suggested for the last three. Both high hemoglobin and high LV ejection fraction were associated with a reduced risk of dying with a stronger initial effect. High creatinine, associated with an increased risk of dying, also presented an initial stronger effect. The impact of age and sodium were constant over time. Conclusions: The current study points to the importance of evaluating covariates with time-varying effects in heart failure models. The analysis performed suggests that variations of Cox and Aalen models constitute a valuable tool for identifying these variables. The implementation of covariates with time-varying effects into heart failure prognostication models may reduce bias and increase the specificity of such models.

Tragedy on grade crossing: driver failure or systemic fragility?

In 2010, an accident occurred in Americana-SP, Brazil, involving two trains and one bus on a Grade Crossing, when 10 people died and 17 were injured including workers. This paper aims to analyze the accident using the Model of Analysis and Prevention of Work Accidents (MAPA). The method provides observation of work, interviews and analysis of documents to understand precedents of the event in the following stages: to understand the usual work from the involved people, the changes occurred in the system, the operation of barriers, managerial and organizational aspects. By the end, measures are suggested to avoid new occurrences. The accident took place at night in a site with insufficient lighting. The working conditions of bus drivers, train operators and watchmen are inadequate. There were only symbolic barriers (visual and acoustic signals) triggered manually by watchman upon train operator radio communication. The fragility of the barrier system associated to poor lighting and short time to trigger the signaling seem to play a critical role in the event. Contrary to the official report which resulted in guilt of the bus driver, the conclusion of the paper emphasizes the fragility of the safety system and the need of level crossing reproject.

Linear matrix inequality-based robust model predictive control for time-delayed systems

This work addresses the solution to the problem of robust model predictive control (MPC) of systems with model uncertainty. The case of zone control of multi-variable stable systems with multiple time delays is considered. The usual approach of dealing with this kind of problem is through the inclusion of non-linear cost constraint in the control problem. The control action is then obtained at each sampling time as the solution to a non-linear programming (NLP) problem that for high-order systems can be computationally expensive. Here, the robust MPC problem is formulated as a linear matrix inequality problem that can be solved in real time with a fraction of the computer effort. The proposed approach is compared with the conventional robust MPC and tested through the simulation of a reactor system of the process industry.

A multiple time scale survival model with a cure fraction

Many recent survival studies propose modeling data with a cure fraction, i.e., data in which part of the population is not susceptible to the event of interest. This event may occur more than once for the same individual (recurrent event). We then have a scenario of recurrent event data in the presence of a cure fraction, which may appear in various areas such as oncology, finance, industries, among others. This paper proposes a multiple time scale survival model to analyze recurrent events using a cure fraction. The objective is analyzing the efficiency of certain interventions so that the studied event will not happen again in terms of covariates and censoring. All estimates were obtained using a sampling-based approach, which allows information to be input beforehand with lower computational effort. Simulations were done based on a clinical scenario in order to observe some frequentist properties of the estimation procedure in the presence of small and moderate sample sizes. An application of a well-known set of real mammary tumor data is provided.

The Poisson-exponential regression model under different latent activation schemes

In this paper, a new family of survival distributions is presented. It is derived by considering that the latent number of failure causes follows a Poisson distribution and the time for these causes to be activated follows an exponential distribution. Three different activation schemes are also considered. Moreover, we propose the inclusion of covariates in the model formulation in order to study their effect on the expected value of the number of causes and on the failure rate function. Inferential procedure based on the maximum likelihood method is discussed and evaluated via simulation. The developed methodology is illustrated on a real data set on ovarian cancer.

Exercise training prevents oxidative stress and ubiquitin-proteasome system overactivity and reverse skeletal muscle atrophy in heart failure

Background: Heart failure (HF) is known to lead to skeletal muscle atrophy and dysfunction. However, intracellular mechanisms underlying HF-induced myopathy are not fully understood. We hypothesized that HF would increase oxidative stress and ubiquitin-proteasome system (UPS) activation in skeletal muscle of sympathetic hyperactivity mouse model. We also tested the hypothesis that aerobic exercise training (AET) would reestablish UPS activation in mice and human HF. Methods/Principal Findings: Time-course evaluation of plantaris muscle cross-sectional area, lipid hydroperoxidation, protein carbonylation and chymotrypsin-like proteasome activity was performed in a mouse model of sympathetic hyperactivity-induced HF. At the 7th month of age, HF mice displayed skeletal muscle atrophy, increased oxidative stress and UPS overactivation. Moderate-intensity AET restored lipid hydroperoxides and carbonylated protein levels paralleled by reduced E3 ligases mRNA levels, and reestablished chymotrypsin-like proteasome activity and plantaris trophicity. In human HF (patients randomized to sedentary or moderate-intensity AET protocol), skeletal muscle chymotrypsin-like proteasome activity was also increased and AET restored it to healthy control subjects' levels. Conclusions: Collectively, our data provide evidence that AET effectively counteracts redox imbalance and UPS overactivation, preventing skeletal myopathy and exercise intolerance in sympathetic hyperactivity-induced HF in mice. Of particular interest, AET attenuates skeletal muscle proteasome activity paralleled by improved aerobic capacity in HF patients, which is not achieved by drug treatment itself. Altogether these findings strengthen the clinical relevance of AET in the treatment of HF.

Skin Penetration Time-Profiles for Continuous 810nm and Superpulsed 904nm Lasers in a Rat Model

Objective: The purpose of this study was to investigate the rat skin penetration abilities of two commercially available low-level laser therapy (LLLT) devices during 150 sec of irradiation. Background data: Effective LLLT irradiation typically lasts from 20 sec up to a few minutes, but the LLLT time-profiles for skin penetration of light energy have not yet been investigated. Materials and methods: Sixty-two skin flaps overlaying rat's gastrocnemius muscles were harvested and immediately irradiated with LLLT devices. Irradiation was performed either with a 810 nm, 200mW continuous wave laser, or with a 904 nm, 60mW superpulsed laser, and the amount of penetrating light energy was measured by an optical power meter and registered at seven time points (range, 1-150 sec). Results: With the continuous wave 810nm laser probe in skin contact, the amount of penetrating light energy was stable at similar to 20% (SEM +/- 0.6) of the initial optical output during 150 sec irradiation. However, irradiation with the superpulsed 904 nm, 60mW laser showed a linear increase in penetrating energy from 38% (SEM +/- 1.4) to 58% (SEM +/- 3.5) during 150 sec of exposure. The skin penetration abilities were significantly different (p < 0.01) between the two lasers at all measured time points. Conclusions: LLLT irradiation through rat skin leaves sufficient subdermal light energy to influence pathological processes and tissue repair. The finding that superpulsed 904nm LLLT light energy penetrates 2-3 easier through the rat skin barrier than 810nm continuous wave LLLT, corresponds well with results of LLLT dose analyses in systematic reviews of LLLT in musculoskeletal disorders. This may explain why the differentiation between these laser types has been needed in the clinical dosage recommendations of World Association for Laser Therapy.

The polysurvival model with long-term survivors

Long-term survival models have historically been considered for analyzing time-to-event data with long-term survivors fraction. However, situations in which a fraction (1 - p) of systems is subject to failure from independent competing causes of failure, while the remaining proportion p is cured or has not presented the event of interest during the time period of the study, have not been fully considered in the literature. In order to accommodate such situations, we present in this paper a new long-term survival model. Maximum likelihood estimation procedure is discussed as well as interval estimation and hypothesis tests. A real dataset illustrates the methodology.

Closed-loop stable model predictive control of integrating systems with dead time

Model predictive control (MPC) applications in the process industry usually deal with process systems that show time delays (dead times) between the system inputs and outputs. Also, in many industrial applications of MPC, integrating outputs resulting from liquid level control or recycle streams need to be considered as controlled outputs. Conventional MPC packages can be applied to time-delay systems but stability of the closed loop system will depend on the tuning parameters of the controller and cannot be guaranteed even in the nominal case. In this work, a state space model based on the analytical step response model is extended to the case of integrating time systems with time delays. This model is applied to the development of two versions of a nominally stable MPC, which is designed to the practical scenario in which one has targets for some of the inputs and/or outputs that may be unreachable and zone control (or interval tracking) for the remaining outputs. The controller is tested through simulation of a multivariable industrial reactor system. (C) 2012 Elsevier Ltd. All rights reserved.

Atorvastatin Prevents the Downregulation of Aquaporin-2 Receptor After Bilateral Ureteral Obstruction and Protects Renal Function in a Rat Model

OBJECTIVE To assess the effects of atorvastatin (ATORV) on renal function after bilateral ureteral obstruction (BUO), measuring inulin clearance and its effect on renal hemodynamic, filtration, and inflammatory response, as well as the expression of Aquaporin-2 (AQP2) in response to BUO and after the release of BUO. METHODS Adult Munich-Wistar male rats were subjected to BUO for 24 hours and monitored during the following 48 hours. Rats were divided into 5 groups: sham operated (n = 6); sham + ATORV (n = 6); BUO (n = 6); BUO + ATORV (10 mg/kg in drinking water started 2 days before BUO [n = 5]; and BUO + ATORV (10 mg/kg in drinking water started on the day of the release of BUO [n = 5]). We measured blood pressure (BP, mm Hg); inulin clearance (glomerular filtration rate [GFR]; mL/min/100 g); and renal blood flow (RBF, mL/min, by transient-time flowmeter). Inflammatory response was evaluated by histologic analysis of the interstitial area. AQP2 expression was evaluated by electrophoresis and immunoblotting. RESULTS Renal function was preserved by ATORV treatment, even if initiated on the day of obstruction release, as expressed by GFR, measured by inulin clearance. Relative interstitial area was decreased in both BUO + ATORV groups. Urine osmolality was improved in the ATORV-treated groups. AQP2 protein expression decreased in BUO animals and was reverted by ATORV treatment. CONCLUSION ATORV administration significantly prevented and restored impairment in GFR and renal vascular resistance. Furthermore, ATORV also improved urinary concentration by reversing the BUO-induced downregulation of AQP2. These findings have significant clinical implication in treating obstructive nephropathy. UROLOGY 80: 485.e15-485.e20, 2012. (c) 2012 Elsevier Inc.

Morphologic and biomechanical changes of thoracic and abdominal aorta in a rat model of cigarette smoke exposure

Background: Smoking is the most relevant environmental factor that affects the development of aortic aneurysm. Smokers have elevated levels of elastase activity in the arterial wall, which leads to weakening of the aorta. The aim of this study was to verify whether cigarette smoke exposure itself is capable of altering the aortic wall. Methods: Forty-eight Wistar rats were divided into 2-, 4-, and 6-month experimental periods and into 2 groups: smokers (submitted to smoke exposure at a rate of 40 cigarettes/day) and nonsmokers. At the end of the experimental periods, the aortas were removed and crosssectioned to obtain histologic specimens for light microscopic and morphometric analyses. The remaining longitudinal segments were stretched to rupture and mechanical parameters were determined. Results: A degenerative process (i.e., a reduction in elastic fibers, the loss of lamellar arrangement, and a reduction of smooth muscle cells) was observed, and this effect was proportional in intensity to the period of tobacco exposure. We observed a progressive reduction in the yield point of the thoracic aorta over time (P < 0.05). There was a decrease in stiffness (P < 0.05) and in failure load (P < 0.05) at 6 months in the abdominal aorta of rats in the smoking group. Conclusions: Chronic exposure to tobacco smoke can affect the mechanical properties of the aorta and can also provoke substantial structural changes of the arterial wall