The evolution of intermediate castration virulence and ant coexistence in a spatially structured environment

Theory suggests that spatial structuring should select for intermediate levels of virulence in parasites, but empirical tests are rare and have never been conducted with castration (sterilizing) parasites. To test this theory in a natural landscape, we construct a spatially explicit model of the symbiosis between the ant-plant Cordia nodosa and its two, protecting ant symbionts, Allomerus and Azteca . Allomerus is also a castration parasite, preventing fruiting to increase colony fecundity. Limiting the dispersal of Allomerus and host plant selects for intermediate castration virulence. Increasing the frequency of the mutualist, Azteca , selects for higher castration virulence in Allomerus , because seeds from Azteca -inhabited plants are a public good that Allomerus exploits. These results are consistent with field observations and, to our knowledge, provide the first empirical evidence supporting the hypothesis that spatial structure can reduce castration virulence and the first such evidence in a natural landscape for either mortality or castration virulence.     

Customized media based on miniaturized screening improve growth rate and cell yield of methane-oxidizing bacteria of the genus Methylomonas

The growth of twelve methanotrophic strains within the genus Methylomonas, including the type strains of Methylomonas methanica and Methylomonas koyamae, was evaluated with 40 different variations of standard diluted nitrate mineral salts medium in 96-well microtiter plates. Unique profiles of growth preference were observed for each strain, showing a strong strain dependency for optimal growth conditions, especially with regards to the preferred concentration and nature of the nitrogen source. Based on the miniaturized screening results, a customized medium was designed for each strain, allowing the improvement of the growth of several strains in a batch setup, either by a reduction of the lag phase or by faster biomass accumulation. As such, the maintenance of fastidious strains could be facilitated while the growth of fast-growing Methylomonas strains could be further improved. Methylomonas sp. R-45378 displayed a 50 % increase in cell dry weight when grown in its customized medium and showed the lowest observed nitrogen and oxygen requirement of all tested strains. We demonstrate that the presented miniaturized approach for medium optimization is a simple tool allowing the quick generation of strain-specific growth preference data that can be applied downstream of an isolation campaign. This approach can also be applied as a first step in the search for strains with biotechnological potential, to facilitate cultivation of fastidious strains or to steer future isolation campaigns.     

On the use of partial area under the ROC curve for comparison of two diagnostic tests

Evaluation of diagnostic performance is typically based on the receiver operating characteristic (ROC) curve and the area under the curve (AUC) as its summary index. The partial area under the curve (pAUC) is an alternative index focusing on the range of practical/clinical relevance. One of the problems preventing more frequent use of the pAUC is the perceived loss of efficiency in cases of noncrossing ROC curves. In this paper, we investigated statistical properties of comparisons of two correlated pAUCs. We demonstrated that outside of the classic model there are practically reasonable ROC types for which comparisons of noncrossing concave curves would be more powerful when based on a part of the curve rather than the entire curve. We argue that this phenomenon stems in part from the exclusion of noninformative parts of the ROC curves that resemble straight‐lines. We conducted extensive simulation studies in families of binormal, straight‐line, and bigamma ROC curves. We demonstrated that comparison of pAUCs is statistically more powerful than comparison of full AUCs when ROC curves are close to a “straight line”. For less flat binormal ROC curves an increase in the integration range often leads to a disproportional increase in pAUCs’ difference, thereby contributing to an increase in statistical power. Thus, efficiency of differences in pAUCs of noncrossing ROC curves depends on the shape of the curves, and for families of ROC curves that are nearly straight‐line shaped, such as bigamma ROC curves, there are multiple practical scenarios in which comparisons of pAUCs are preferable.     

Disentangling the Association between Statins,Cholesterol, and Colorectal Cancer: A Nested Case-Control Study

BackgroundSeveral prior studies have found an association between statin use and reduced risk of colorectal cancer. We hypothesized that these findings may be due to systematic bias and examined the independent association of colorectal cancer risk with statin use, serum cholesterol, and change in cholesterol concentration.ConclusionsAlthough the risk of colorectal cancer was lower in statin users versus nonusers, no difference was observed among those who continued versus discontinued statin therapy, suggesting the potential for indication bias. The association between decreased serum cholesterol and colorectal cancer risk suggests a cholesterol-lowering effect of undiagnosed malignancy. Clinical judgment should be used when considering causes of cholesterol reduction in patients, including those on statin therapy.     

Finite elements/Taguchi method based procedure for the identification of the geometrical parameters significantly affecting the biomechanical behavior of a lumbar disc

The aim of this work is to show a quick and simple procedure able to identify the geometrical parameters of the intervertebral disc that strongly affect the behavior of the FEM model. First, we allocated a selection criterion for the minimum number of geometrical parameters that describe, with a good degree of approximation, a healthy human vertebra. Next, we carried out a sensitivity analysis using the ‘Taguchi orthogonal array’ to arrive at a quick identification of the parameters that strongly affect the behavior of the Fem model.