Inbreeding in the greater white-toothed shrew, Crocidura russula.

We combined mark-and-recapture studies with genetic techniques of parentage assignment to evaluate the interactions between mating, dispersal, and inbreeding, in a free-ranging population of Crocidura russula. We found a pattern of limited and female-biased dispersal, followed by random mating within individual neighborhoods. This results in significant inbreeding at the population level: mating among relatives occurs more often than random, and F(IT) analyses reveal significant deficits in heterozygotes. However, related mating partners were not less fecund, and inbred offspring had no lower lifetime reproductive output. Power analyses show these negative results to be quite robust. Absence of phenotypic evidence of inbreeding depression might result from a history of purging: local populations are small and undergo disequilibrium gene dynamics. Dispersal is likely caused by local saturation and (re)colonization of empty breeding sites, rather than inbreeding avoidance.

Accuracy of indirect estimation of power output from uphill performance in cycling.

PURPOSE: To use measurement by cycling power meters (Pmes) to evaluate the accuracy of commonly used models for estimating uphill cycling power (Pest). Experiments were designed to explore the influence of wind speed and steepness of climb on accuracy of Pest. The authors hypothesized that the random error in Pest would be largely influenced by the windy conditions, the bias would be diminished in steeper climbs, and windy conditions would induce larger bias in Pest. METHODS: Sixteen well-trained cyclists performed 15 uphill-cycling trials (range: length 1.3-6.3 km, slope 4.4-10.7%) in a random order. Trials included different riding position in a group (lead or follow) and different wind speeds. Pmes was quantified using a power meter, and Pest was calculated with a methodology used by journalists reporting on the Tour de France. RESULTS: Overall, the difference between Pmes and Pest was -0.95% (95%CI: -10.4%, +8.5%) for all trials and 0.24% (-6.1%, +6.6%) in conditions without wind (<2 m/s). The relationship between percent slope and the error between Pest and Pmes were considered trivial. CONCLUSIONS: Aerodynamic drag (affected by wind velocity and orientation, frontal area, drafting, and speed) is the most confounding factor. The mean estimated values are close to the power-output values measured by power meters, but the random error is between ±6% and ±10%. Moreover, at the power outputs (>400 W) produced by professional riders, this error is likely to be higher. This observation calls into question the validity of releasing individual values without reporting the range of random errors.

Using active learning for monitoring networks design: The example of wind power plants sites evaluation

Locating new wind farms is of crucial importance for energy policies of the next decade. To select the new location, an accurate picture of the wind fields is necessary. However, characterizing wind fields is a difficult task, since the phenomenon is highly nonlinear and related to complex topographical features. In this paper, we propose both a nonparametric model to estimate wind speed at different time instants and a procedure to discover underrepresented topographic conditions, where new measuring stations could be added. Compared to space filling techniques, this last approach privileges optimization of the output space, thus locating new potential measuring sites through the uncertainty of the model itself.

Inference about the number of contributors to a DNA mixture: Comparative analyses of a Bayesian network approach and the maximum allele count method.

In the forensic examination of DNA mixtures, the question of how to set the total number of contributors (N) presents a topic of ongoing interest. Part of the discussion gravitates around issues of bias, in particular when assessments of the number of contributors are not made prior to considering the genotypic configuration of potential donors. Further complication may stem from the observation that, in some cases, there may be numbers of contributors that are incompatible with the set of alleles seen in the profile of a mixed crime stain, given the genotype of a potential contributor. In such situations, procedures that take a single and fixed number contributors as their output can lead to inferential impasses. Assessing the number of contributors within a probabilistic framework can help avoiding such complication. Using elements of decision theory, this paper analyses two strategies for inference on the number of contributors. One procedure is deterministic and focuses on the minimum number of contributors required to 'explain' an observed set of alleles. The other procedure is probabilistic using Bayes' theorem and provides a probability distribution for a set of numbers of contributors, based on the set of observed alleles as well as their respective rates of occurrence. The discussion concentrates on mixed stains of varying quality (i.e., different numbers of loci for which genotyping information is available). A so-called qualitative interpretation is pursued since quantitative information such as peak area and height data are not taken into account. The competing procedures are compared using a standard scoring rule that penalizes the degree of divergence between a given agreed value for N, that is the number of contributors, and the actual value taken by N. Using only modest assumptions and a discussion with reference to a casework example, this paper reports on analyses using simulation techniques and graphical models (i.e., Bayesian networks) to point out that setting the number of contributors to a mixed crime stain in probabilistic terms is, for the conditions assumed in this study, preferable to a decision policy that uses categoric assumptions about N.

Maximal aerobic power during running and cycling in obese and non-obese children.

The maximal aerobic capacity while running and cycling was measured in 22 prepubertal children (mean age +/- SD 9.5 +/- 0.8 years): 14 obese (47.3 +/- 10 kg) and 8 non-obese (31.1 +/- 6.1 kg). Oxygen consumption (VO2) and carbon dioxide production were measured by an open circuit method. Steady state VO2 was determined at different levels of exercise up to the maximal power on the cycloergometer (92 W in obese and 77 W in non-obese subjects) and up to the maximal running speed on the treadmill at a 2% slope (8.3 km/h in obese and 9.0 km/h in lean children). Expressed in absolute values, the VO2max in obese children was significantly higher than in controls (1.55 +/- 0.29 l/min versus 1.23 +/- 0.22 l/min, p < 0.05) for the treadmill test and comparable in the two groups (1.4 +/- 0.2 l/min versus 1.16 +/- 0.2 l/min, ns) for the cycloergometer test. When VO2max was expressed per kg fat free mass, the difference between the two groups disappeared for both tests. These data suggest that obese children had no limitation of maximal aerobic power. Therefore, the magnitude of the workload prescribed when a physical activity program is intended for the therapy of childhood obesity, it should be designed to increase caloric output rather than to improve cardiorespiratory fitness.

Acute supra-therapeutic oral terbutaline administration has no ergogenic effect in non-asthmatic athletes.

This study aimed to investigate the effects on a possible improvement in aerobic and anaerobic performance of oral terbutaline (TER) at a supra-therapeutic dose in 7 healthy competitive male athletes. On day 1, ventilatory threshold, maximum oxygen uptake [Formula: see text] and corresponding power output were measured and used to determine the exercise load on days 2 and 3. On days 2 and 3, 8 mg of TER or placebo were orally administered in a double-blind process to athletes who rested for 3 h, and then performed a battery of tests including a force-velocity exercise test, running sprint and a maximal endurance cycling test at Δ50 % (50 % between VT and [Formula: see text]). Lactatemia, anaerobic parameters and endurance performance ([Formula: see text] and time until exhaustion) were raised during the corresponding tests. We found that TER administration did not improve any of the parameters of aerobic performance (p > 0.05). In addition, no change in [Formula: see text] kinetic parameters was found with TER compared to placebo (p > 0.05). Moreover, no enhancement of the force-velocity relationship was observed during sprint exercises after TER intake (p > 0.05) and, on the contrary, maximal strength decreased significantly after TER intake (p < 0.05) but maximal power remained unchanged (p > 0.05). In conclusion, oral acute administration of TER at a supra-therapeutic dose seems to be without any relevant ergogenic effect on anaerobic and aerobic performances in healthy athletes. However, all participants experienced adverse side effects such as tremors.

Comparative performance of supertree algorithms in large data sets using the soapberry family (Sapindaceae) as a case study.

For the last 2 decades, supertree reconstruction has been an active field of research and has seen the development of a large number of major algorithms. Because of the growing popularity of the supertree methods, it has become necessary to evaluate the performance of these algorithms to determine which are the best options (especially with regard to the supermatrix approach that is widely used). In this study, seven of the most commonly used supertree methods are investigated by using a large empirical data set (in terms of number of taxa and molecular markers) from the worldwide flowering plant family Sapindaceae. Supertree methods were evaluated using several criteria: similarity of the supertrees with the input trees, similarity between the supertrees and the total evidence tree, level of resolution of the supertree and computational time required by the algorithm. Additional analyses were also conducted on a reduced data set to test if the performance levels were affected by the heuristic searches rather than the algorithms themselves. Based on our results, two main groups of supertree methods were identified: on one hand, the matrix representation with parsimony (MRP), MinFlip, and MinCut methods performed well according to our criteria, whereas the average consensus, split fit, and most similar supertree methods showed a poorer performance or at least did not behave the same way as the total evidence tree. Results for the super distance matrix, that is, the most recent approach tested here, were promising with at least one derived method performing as well as MRP, MinFlip, and MinCut. The output of each method was only slightly improved when applied to the reduced data set, suggesting a correct behavior of the heuristic searches and a relatively low sensitivity of the algorithms to data set sizes and missing data. Results also showed that the MRP analyses could reach a high level of quality even when using a simple heuristic search strategy, with the exception of MRP with Purvis coding scheme and reversible parsimony. The future of supertrees lies in the implementation of a standardized heuristic search for all methods and the increase in computing power to handle large data sets. The latter would prove to be particularly useful for promising approaches such as the maximum quartet fit method that yet requires substantial computing power.

The branch-site test of positive selection is surprisingly robust but lacks power under synonymous substitution saturation and variation in GC

Positive selection is widely estimated from protein coding sequence alignments by the nonsynonymous-to-synonymous ratio omega. Increasingly elaborate codon models are used in a likelihood framework for this estimation. Although there is widespread concern about the robustness of the estimation of the omega ratio, more efforts are needed to estimate this robustness, especially in the context of complex models. Here, we focused on the branch-site codon model. We investigated its robustness on a large set of simulated data. First, we investigated the impact of sequence divergence. We found evidence of underestimation of the synonymous substitution rate for values as small as 0.5, with a slight increase in false positives for the branch-site test. When dS increases further, underestimation of dS is worse, but false positives decrease. Interestingly, the detection of true positives follows a similar distribution, with a maximum for intermediary values of dS. Thus, high dS is more of a concern for a loss of power (false negatives) than for false positives of the test. Second, we investigated the impact of GC content. We showed that there is no significant difference of false positives between high GC (up to similar to 80%) and low GC (similar to 30%) genes. Moreover, neither shifts of GC content on a specific branch nor major shifts in GC along the gene sequence generate many false positives. Our results confirm that the branch-site is a very conservative test.