Data-Driven Reversible Jump for QTL Mapping

We propose a birth–death–merge data-driven reversible jump (DDRJ) for multiple-QTL mapping where the phenotypic trait is modeled as a linear function of the additive and dominance effects of the unknown QTL genotypes. We compare the performance of the proposed methodology, usual reversible jump (RJ) and multiple-interval mapping (MIM), using simulated and real data sets. Compared with RJ, DDRJ shows a better performance to estimate the number of QTLs and their locations on the genome mainly when the QTLs effect is moderate, basically as a result of better mixing for transdimensional moves. The inclusion of a merge step of consecutive QTLs in DDRJ is efficient, under tested conditions, to avoid the split of true QTL’s effects between false QTLs and, consequently, selection of the wrong model. DDRJ is also more precise to estimate the QTLs location than MIM in which the number of QTLs need to be specified in advance. As DDRJ is more efficient to identify and characterize QTLs with smaller effect, this method also appears to be useful and brings contributions to identifying single-nucleotide polymorphisms (SNPs) that usually have a small effect on phenotype.     

Bayesian adaptive regression splines for hierarchical data

This article considers methodology for hierarchical functional data analysis, motivated by studies of reproductive hormone profiles in the menstrual cycle. Current methods standardize the cycle lengths and ignore the timing of ovulation within the cycle, both of which are biologically informative. Methods are needed that avoid standardization, while flexibly incorporating information on covariates and the timing of reference events, such as ovulation and onset of menses. In addition, it is necessary to account for within-woman dependency when data are collected for multiple cycles. We propose an approach based on a hierarchical generalization of Bayesian multivariate adaptive regression splines. Our formulation allows for an unknown set of basis functions characterizing the population-averaged and woman-specific trajectories in relation to covariates. A reversible jump Markov chain Monte Carlo algorithm is developed for posterior computation. Applying the methods to data from the North Carolina Early Pregnancy Study, we investigate differences in urinary progesterone profiles between conception and nonconception cycles.     

ACUTE EFFECTS OF A RESISTED DYNAMIC WARM-UP PROTOCOL ON JUMPING PERFORMANCE

This study aimed to investigate the kinematic and kinetic changes when resistance is applied in horizontal and vertical directions, produced by using different percentages of body weight, caused by jumping movements during a dynamic warm-up. The group of subjects consisted of 35 voluntary male athletes (19 basketball and 16 volleyball players; age: 23.4 ± 1.4 years, training experience: 9.6 ± 2.7 years; height: 177.2 ± 5.7 cm, body weight: 69.9 ± 6.9 kg) studying Physical Education, who had a jump training background and who were training for 2 hours, on 4 days in a week. A dynamic warm-up protocol containing seven specific resistance movements with specific resistance corresponding to different percentages of body weight (2%, 4%, 6%, 8%, 10%) was applied randomly on non consecutive days. Effects of different warm-up protocols were assessed by pre-/post- exercise changes in jump height in the countermovement jump (CMJ) and the squat jump (SJ) measured using a force platform and changes in hip and knee joint angles at the end of the eccentric phase measured using a video camera. A significant increase in jump height was observed in the dynamic resistance warm-up conducted with different percentages of body weight (p < 0.05). On the other hand, no significant difference in different percentages of body weight states was observed (p > 0.05). In jump movements before and after the warm-up, while no significant difference between the vertical ground reaction forces applied by athletes was observed (p > 0.05), in some cases of resistance, a significant reduction was observed in hip and knee joint angles (p < 0.05). The dynamic resistance warm-up method was found to cause changes in the kinematics of jumping movements, as well as an increase in jump height values. As a result, dynamic warm-up exercises could be applicable in cases of resistance corresponding to 6-10% of body weight applied in horizontal and vertical directions in order to increase the jump performance acutely.     

Comparison of discrete-point vs. dimensionality-reduction techniques for describing performance-related aspects of maximal vertical jumping

The aim of this study was to assess and compare the ability of discrete point analysis (DPA), functional principal component analysis (fPCA) and analysis of characterizing phases (ACP) to describe a dependent variable (jump height) using vertical ground reaction force curves captured during the propulsion phase of a countermovement jump. FPCA and ACP are continuous data analysis techniques that reduce the dimensionality of a data set by identifying phases of variation (key phases), which are used to generate subject scores that describe a subject?s behavior. A stepwise multiple regression analysis was used to measure the ability to describe jump height of each data analysis technique. Findings indicated that the order of effectiveness (high to low) across the examined techniques was: ACP (99%), fPCA (78%) and DPA (21%). DPA was outperformed by fPCA and ACP because it can inadvertently compare unrelated features, does not analyze the whole data set and cannot examine important features that occur solely as a phase. ACP outperformed fPCA because it utilizes information within the combined magnitude-time domain, and identifies and examines key phases separately without the deleterious interaction of other key phases.     

Effects of Internal pH on the Acetylcholine Transporter of Synaptic Vesicles

Abstract: Uptake of acetylcholine (ACh) by synaptic vesicles isolated from the electric organ of Torpedo was induced with an artificially imposed proton gradient. The gradient was formed by hyposmotic lysis and resealing of vesicles in a low pH buffer to form vesicular ghosts followed by sudden elevation of the pH of the ghost suspension. [³H]ACh accumulated rapidly, the proton gradient collapsed spontaneously within 5 min as monitored by [¹⁴C]methylamine uptake, and the accumulated ACh leaked out of the ghosts after 5 min. Vesamicol blocked both uptake and efflux of the [³H]ACh, demonstrating that both processes are mediated by the ACh transporter. The protonophore nigericin also blocked uptake very potently. Specific uptake was titrated with variable concentrations of [³H]ACh. It exhibited K _m and V _max values of ∼200–500 µ M and 7–30 nmol [³H]ACh/mg at 5 min, respectively, which are values close to those commonly observed for ATP-dependent uptake by intact vesicles. Specific uptake by ghosts was titrated with variable internal pH and constant external pH. It exhibited maximal uptake between internal pH 4.5 and 5.5. The dependence was very steep and could be fit best by assuming that the active form of the transporter requires protonation of two internal sites of apparent pK value of 5.3 ± 0.2. A similar result was obtained when the uptake was titrated with variable internal pH with a constant thermodynamic driving force maintained by keeping the external pH ∼2.6 units higher. The origin of the transport inhibition that sets in at very low internal pH values is not clear. In vivo, the steep dependence of transport on the transmembrane pH gradient might serve to minimize leakage of ACh from the cytoplasm due to ACh transporter in the plasma membrane.     

Optimal harvesting of a logistic population in an environment with stochastic jumps

Dynamic programming is employed to examine the effects of large, sudden changes in population size on the optimal harvest strategy of an exploited resource population. These changes are either adverse or favorable and are assumed to occur at times of events of a Poisson process. The amplitude of these jumps is assumed to be density independent. In between the jumps the population is assumed to grow logistically. The Bellman equation for the optimal discounted present value is solved numerically and the optimal feedback control computed for the random jump model. The results are compared to the corresponding results for the quasi-deterministic approximation. In addition, the sensitivity of the results to the discount rate, the total jump rate and the quadratic cost factor is investigated. The optimal results are most strongly sensitive to the rate of stochastic jumps and to the quadratic cost factor to a lesser extent when the deterministic bioeconomic parameters are taken from aggregate antarctic pelagic whaling data.Research supported in part by the National Science Foundation under grants MCS 81-01698 and MCS 83-00562.     

Assessment of unloaded and loaded squat jump performance with a force platform: Which jump starting threshold provides more reliable outcomes?

This study aimed to explore the influence of different onset thresholds on the between-session reliability and magnitude of squat jump (SJ) performance. Twenty men were tested on two sessions separated by 48 h against external loads of 0.5, 30 and 60 kg. The initiation of the jump was defined as the first instant in which the vertical ground reaction force exceeded system weight by 10 N (10 N), 50 N (50 N), 1% of system weight (1%SW), 10% of system weight (10%SW) and five standard deviation of system weight minus 30 ms (5SDSW). The following variables were calculated from the force-time signal collected on a force platform: mean, peak and time to peak values of force, power and velocity, average rate of force development, peak rate of force development, rate of force development index, impulse, jump height, and push-off time. The 50 N, 10%SW and 5SDSW thresholds generally revealed a higher reliability than the 10 N and 1%SW thresholds (97 and 21 out of 252 comparisons for the coefficient of variation and intraclass correlation coefficient, respectively). The magnitude of most of the variables calculated using the 50 N and 10%SW thresholds significantly differed with respect to the 10 N, 1%SW and 5SDSW thresholds (P < 0.05). These results suggest that both the reliability and magnitude of SJ performance variables are influenced by the jump starting threshold. The 50 N, 10%SW and 5SDSW thresholds maximise the reliability of SJ performance variables, while the 5SDSW should be recommended since it considers more force signal than the 50 N and 10%SW thresholds.