Bioenergetics and neuromuscular determinants of the time to exhaustion at velocity corresponding to (V) over dotO(2)max in recreational long-distance runners

Bertuzzi, R, Bueno, S, Pasqua, LA, Acquesta, FM, Batista, MB, Roschel, H, Kiss, MAPDM, Serrao, JC, Tricoli, V, and Ugrinowitsch, C. Bioenergetics and neuromuscular determinants of the time to exhaustion at velocity corresponding to (V) over dotO(2)max in recreational long-distance runners. J Strength Cond Res 26(8): 2096-2102, 2012-The purpose of this study was to investigate the main bioenergetics and neuromuscular determinants of the time to exhaustion (T-lim) at the velocity corresponding to maximal oxygen uptake in recreational long-distance runners. Twenty runners performed the following tests on 5 different days: (a) maximal incremental treadmill test, (b) 2 submaximal tests to determine running economy and vertical stiffness, (c) exhaustive test to measured the T-lim, (d) maximum dynamic strength test, and (e) muscle power production test. Aerobic and anaerobic energy contributions during the T-lim test were also estimated. The stepwise multiple regression method selected 3 independent variables to explain T-lim variance. Total energy production explained 84.1% of the shared variance (p = 0.001), whereas peak oxygen uptake ((V) over dotO(2)peak) measured during T-lim and lower limb muscle power ability accounted for the additional 10% of the shared variance (p = 0.014). These data suggest that the total energy production, (V) over dotO(2)peak, and lower limb muscle power ability are the main physiological and neuromuscular determinants of T-lim in recreational long-distance runners.

Congenital Chagas disease: time to screen pregnant women?

The congenital transmission of Trypanosoma cruzi has gained epidemiological importance because it is partially responsible for the spread of Chagas disease worldwide. The feasibility of a cure when infected children are treated early makes the detection of congenital infection a valuable goal toward the control of the disease. Here, the authors review and discuss the findings of Bua et al., who quantified the parasitemia of infected women and their newborns by quantitative PCR. The authors demonstrate that the maternal parasite burden is directly related to the risk of neonatal infection. This study points out the importance of a quantitative screen for T. cruzi in pregnant women who live in, or have traveled to, endemic areas for improving the diagnosis of infected newborns and providing prompt treatment.

The geometric Birnbaum-Saunders regression model with cure rate

In this paper, we propose a cure rate survival model by assuming the number of competing causes of the event of interest follows the Geometric distribution and the time to event follow a Birnbaum Saunders distribution. We consider a frequentist analysis for parameter estimation of a Geometric Birnbaum Saunders model with cure rate. Finally, to analyze a data set from the medical area. (C) 2011 Elsevier B.V. All rights reserved.

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.

Time course of the hemodynamic responses to aortic depressor nerve stimulation in conscious spontaneously hypertensive rats

The time to reach the maximum response of arterial pressure, heart rate and vascular resistance (hindquarter and mesenteric) was measured in conscious male spontaneously hypertensive (SHR) and normotensive control rats (NCR; Wistar; 18-22 weeks) subjected to electrical stimulation of the aortic depressor nerve (ADN) under thiopental anesthesia. The parameters of stimulation were 1 mA intensity and 2 ms pulse length applied for 5 s, using frequencies of 10, 30, and 90 Hz. The time to reach the hemodynamic responses at different frequencies of ADN stimulation was similar for SHR (N = 15) and NCR (N = 14); hypotension = NCR (4194 +/- 336 to 3695 +/- 463 ms) vs SHR ( 3475 +/- 354 to 4494 +/- 300 ms); bradycardia = NCR (1618 +/- 152 to 1358 +/- 185 ms) vs SHR (1911 +/- 323 to 1852 +/- 431 ms), and the fall in hindquarter vascular resistance = NCR (6054 +/- 486 to 6550 +/- 847 ms) vs SHR (4849 +/- 918 to 4926 +/- 646 ms); mesenteric = NCR (5574 +/- 790 to 5752 +/- 539 ms) vs SHR (5638 +/- 648 to 6777 +/- 624 ms). In addition, ADN stimulation produced baroreflex responses characterized by a faster cardiac effect followed by a vascular effect, which together contributed to the decrease in arterial pressure. Therefore, the results indicate that there is no alteration in the conduction of the electrical impulse after the site of baroreceptor mechanical transduction in the baroreflex pathway (central and/or efferent) in conscious SHR compared to NCR.

Bootstrap confidence intervals for industrial recurrent event data

Industrial recurrent event data where an event of interest can be observed more than once in a single sample unit are presented in several areas, such as engineering, manufacturing and industrial reliability. Such type of data provide information about the number of events, time to their occurrence and also their costs. Nelson (1995) presents a methodology to obtain asymptotic confidence intervals for the cost and the number of cumulative recurrent events. Although this is a standard procedure, it can not perform well in some situations, in particular when the sample size available is small. In this context, computer-intensive methods such as bootstrap can be used to construct confidence intervals. In this paper, we propose a technique based on the bootstrap method to have interval estimates for the cost and the number of cumulative events. One of the advantages of the proposed methodology is the possibility for its application in several areas and its easy computational implementation. In addition, it can be a better alternative than asymptotic-based methods to calculate confidence intervals, according to some Monte Carlo simulations. An example from the engineering area illustrates the methodology.