A real‐time eco‐evolutionary dead‐end strategy is mediated by the traits of lineage progenitors and interactions with colony invaders

Evolutionary dead‐end strategies are characterized by short‐term productivity benefits and long‐term evolutionary costs. Here, I detail a real‐time dead‐end strategy associated with the behavioural traits of lineage progenitors in the social spider Anelosimus studiosus. Specifically, colony lineages founded by docile spiders were eight times more likely to suffer extinction, despite their superior reproductive output. However, when inquilines were experimentally removed from progenitor colonies, differences in extinction probability among lineages vanished. Similarly, among lineages founded by purely docile or aggressive individuals, the descendants of lineages with the highest reproductive output suffered the lowest survivorship, whereas lineages founded by a mixture of docile/aggressive lacked such a trade‐off. Finally, lineages with shorter progenitor‐descendant distances gained more inquilines and their descendants had lower survivorship, relative to more diffuse lineages. Overall, this study demonstrates how the traits of lineage progenitors and species interactions can unite to determine the fates of entire lineages.     

Effects of wild and farm-grown macroalgae on the growth of juvenile South African abalone Haliotis midae Linnaeus

The effect of various macroalgal diets on the growth of grow-out (>20 mm shell length) South African abalone Haliotis midae was investigated on a commercial abalone farm. The experiment consisted of four treatments: fresh kelp blades (Ecklonia maxima (Osbeck) Papenfuss) (c. 10% protein); farmed, protein-enriched Ulva lactuca Linnaeus (c. 26% protein) grown in aquaculture effluent; wild U. lactuca (c. 20% protein); and a combination diet of kelp blades + farmed U. lactuca. Abalone grew best on the combination diet (0.423 ± 0.02% weight d^?1 SGR [specific growth rate]; 59.593 ± 0.02 ?m d^?1 DISL [daily increment in shell length]; 1.093 final CF [condition factor]) followed by the kelp only diet (0.367 ± 0.02% weight d^?1 SGR; 53.148 ± 0.02 ?m d^?1 DISL; 1.047 final CF), then the farmed, protein-enriched U. lactuca only diet (0.290 ± 0.02% weight d^?1 SGR; 42.988 ± 0.03 um d”¹ DISL; 1.013 final CF) that in turn outperformed the wild U. lactuca only diet (-0.079 ± 0.01% weight d^?1 SGR; 3.745 ± 0.02 ?m d”^?1 DISL; 0.812 final CF). The results suggest that protein alone could not have accounted for the differences produced by the varieties of U. lactuca and that the gross energy content is probably important.     

Adjustment for exploratory cut-off selection in randomized clinical trials with survival endpoint

Defining the target population based on predictive biomarkers plays an important role during clinical development. After establishing a relationship between a biomarker candidate and response to treatment in exploratory phases, a subsequent confirmatory trial ideally involves only subjects with high potential of benefiting from the new compound. In order to identify those subjects in case of a continuous biomarker, a cut-off is needed. Usually, a cut-off is chosen that resulted in a subgroup with a large observed treatment effect in an exploratory trial. However, such a data-driven selection may lead to overoptimistic expectations for the subsequent confirmatory trial. Treatment effect estimates, probability of success, and posterior probabilities are useful measures for deciding whether or not to conduct a confirmatory trial enrolling the biomarker-defined population. These measures need to be adjusted for selection bias. We extend previously introduced Approximate Bayesian Computation techniques for adjustment of subgroup selection bias to a time-to-event setting with cut-off selection. Challenges in this setting are that treatment effects become time-dependent and that subsets are defined by the biomarker distribution. Simulation studies show that the proposed method provides adjusted statistical measures which are superior to naïve Maximum Likelihood estimators as well as simple shrinkage estimators.     

SIMEX for correction of dietary exposure effects with Box-Cox transformed data

Modelling dietary data, and especially 24-hr dietary recall (24HDR) data, is a challenge. Ignoring the inherent measurement error (ME) leads to biased effect estimates when the association between an exposure and an outcome is investigated. We propose an adapted simulation extrapolation (SIMEX) algorithm for modelling dietary exposures. For this purpose, we exploit the ME model of the NCI method where we assume the assumption of normally distributed errors of the reported intake on the Box-Cox transformed scale and of unbiased recalls on the original scale. According to the SIMEX algorithm, remeasurements of the observed data with additional ME are generated in order to estimate the association between the level of ME and the resulting effect estimate. Subsequently, this association is extrapolated to the case of zero ME to obtain the corrected estimate. We show that the proposed method fulfils the key property of the SIMEX approach, that is, that the MSE of the generated data will converge to zero if the ME variance converges to zero. Furthermore, the method is applied to real 24HDR data of the I.Family study to correct the effects of salt and alcohol intake on blood pressure. In a simulation study, the method is compared with the NCI method resulting in effect estimates with either smaller MSE or smaller bias in certain situations. In addition, we found our method to be more informative and easier to implement. Therefore, we conclude that the proposed method is useful to promote the dissemination of ME correction methods in nutritional epidemiology.     

Sample size recalculation in multicenter randomized controlled clinical trials based on noncomparative data

Many late-phase clinical trials recruit subjects at multiple study sites. This introduces a hierarchical structure into the data that can result in a power-loss compared to a more homogeneous single-center trial. Building on a recently proposed approach to sample size determination, we suggest a sample size recalculation procedure for multicenter trials with continuous endpoints. The procedure estimates nuisance parameters at interim from noncomparative data and recalculates the sample size required based on these estimates. In contrast to other sample size calculation methods for multicenter trials, our approach assumes a mixed effects model and does not rely on balanced data within centers. It is therefore advantageous, especially for sample size recalculation at interim. We illustrate the proposed methodology by a study evaluating a diabetes management system. Monte Carlo simulations are carried out to evaluate operation characteristics of the sample size recalculation procedure using comparative as well as noncomparative data, assessing their dependence on parameters such as between-center heterogeneity, residual variance of observations, treatment effect size and number of centers. We compare two different estimators for between-center heterogeneity, an unadjusted and a bias-adjusted estimator, both based on quadratic forms. The type 1 error probability as well as statistical power are close to their nominal levels for all parameter combinations considered in our simulation study for the proposed unadjusted estimator, whereas the adjusted estimator exhibits some type 1 error rate inflation. Overall, the sample size recalculation procedure can be recommended to mitigate risks arising from misspecified nuisance parameters at the planning stage.     

C1188D mutation abolishes specific recognition between MLL1-CXXC domain and CpG site by inducing conformational switch of flexible N-terminal

Mixed lineage leukemia protein (MLL1 protein) recognizes the CpG site via its CXXC domain and is frequently associated with leukemia. The specific recognition is abolished by C1188D mutation, which also prevents MLL-related leukemia. In this paper, multiple molecular dynamic (MD) simulations were performed to investigate the mechanism of recognition and influences of C1188D mutation. Started from fully dissociated DNA and MLL1-CXXC domain, remarkably, the center of mass (COM) of MLL1-CXXC domain quickly concentrates on the vicinity of the CpG site in all 53 short MD simulations. Extended simulations of the wild type showed that the native complex formed in 500 ns among 4 of 53 simulations. In contrast, the C1188D mutant COM distributed broadly around the DNA and the native complex was not observed in any of the extended simulations. Simulations on the apo MLL1-CXXC domain further suggest that the wild type protein remained predominantly in an open form that closely resembles its structure in the native complex whereas C1188D mutant formed predominantly compact structures in which the N- terminal bends to D1188. This conformational switch hinders the formation of encounter complex, thus abolishes the recognition. Our study also provides clues to the study mechanism of recognition, by the CXXC domain from proteins like DNA methyltransferase and ten-eleven translocation enzymes.     

Noninvasive tool for optical online monitoring of individual biomass concentrations in a defined coculture

Cocultures bear great potential in the conversion of complex substrates and process intensification, as well as, in the formation of unique components only available due to inter-species interactions. Dynamic data of coculture composition is necessary for understanding and optimizing coculture systems. However, most standard online determined parameters measure the sum of all species in the reactor system. The kinetic behavior of the individual species remains unknown. Up to now, different offline methods are available to determine the culture composition, as well as the online measurement of fluorescence of genetically modified organisms. To avoid any genetic modification, a noninvasive online monitoring tool based on the scattered light spectrum was developed for microtiter plate cultivations. To demonstrate the potential, a coculture consisting of the bacterium Lactococcus lactis and the yeast Kluyveromyces marxianus was cultivated. Via partial least squares regression of scattered light spectra, the online determination of the individual biomass concentrations without further sampling and analyses is possible. The results were successfully validated by a Coulter counter-analysis, taking advantage of the different cell sizes of both organisms. The findings prove the applicability of the new method to follow in detail the dynamics of a coculture.     

Liana communities exhibit different species composition,diversity and community structure across forest types in the Congo Basin

Lianas are poorly characterized for central African forests. We quantify variation in liana composition, diversity and community structure in different forest types in the Yangambi Man and Biosphere Reserve, Democratic Republic of Congo. These attributes of liana assemblages were examined in 12 1-ha plots, randomly demarcated within regrowth forest, old growth monodominant forest, old growth mixed forest and old growth edge forest. Using a combination of multivariate and univariate community analyses, we visualize the patterns of these liana assemblage attributes and/or test for their significant differences across forest types. The combined 12 1-ha area contains 2,638 lianas (≥2 cm diameter) representing 105 species, 49 genera and 22 families. Liana species composition differed significantly across forest types. Taxonomic diversity was higher in old growth mixed forests compared to old growth monodominant and regrowth forests. Trait diversity was higher than expected in the regrowth forest as opposed to the rest of forest types. Similarly, the regrowth forest differed from the rest of forest types in the pattern of liana species ecological traits and diameter frequency distribution. The regrowth forest was also less densely populated in lianas and had lower liana total basal area than the rest of forest types. We speculate that the mechanism of liana competitive exclusion by dominant tree species is mainly responsible for the lower liana species diversity in monodominant compared to mixed forests. We attribute variation in liana community structure between regrowth and old growth forests mostly to short development time of size hierarchies.     

Antifungal effect of Penicillium metabolites against some fungi

Microorganisms are increasingly exploited as a source of new biological control agents. Genus Penicillium is a source of novel bioactive molecules which can be used as antifungal agents. The objective of this study was to evaluate the antifungal potential of Penicillium strains. Culture filtrates of two Penicillium species were tested for their antifungal potential by well diffusion assays. Filtrate of Penicillium isolates showed high antifungal effects on mycelial growth of Fusarium oxysporum, Fusarium solani, Macrophomina phaseolina, Aspergillus japonicus var aculeatus and Cladosporium cladosporioides. But Penicillium italicum inhibit the fungal growth from 45 to 68% as compared to Penicillium simplissimum (25–68%). However in case of A. japonicus var aculeatus, Penicillium spp. extracts were equally effective and reduce the colony growth up to 68%. However, P. simplissimum extract was least effective in case of M. phaseolina, where it decreased the colony growth only 25%.     

Temperature response,pathogenicity, seed infection and mutant evaluation against Macrophomina phaseolina causing charcoal rot disease of sesame

Charcoal rot caused by Macrophomina phaseolina is a serious disease of sesame in Pakistan. M. phaseolina sesame isolate was subjected to growth rate test at 10, 15, 20, 25, 30, 35 and 40°C. The optimum temperature for fungal growth and microsclerotia production was found to be 30–35°C. Gray to black, radial fungal colonies with intermediate mycelial growth and jet black oval to round microsclerotia were observed at this optimum range. M. phaseolina was found to be pathogenic against all the 18 tested plant species and this pathogenicity proved its necrophytic behavior. Seed infection efficiency of M. phaseolina was 100% with significant reduction in seed index. For two consecutive years 21 mutants/varieties were screened in the field for their reactions to charcoal rot disease. During 2007 three mutants NS11704S1, NS11304S2 and NS26004 were ranked as resistant while others were moderately resistant to highly susceptible. During 2008 all mutants showed a susceptible to highly susceptible reaction with variable disease reactions. All over screening results revealed that four mutants viz, NS13P1, NS163-1, NS270P1 and NS26004 showed about 50% stand with consistent performance during both years under optimum disease conditions and can be used to manage the disease following the disease management strategies, however in the future improvement for high seed yield along with resistance is a prerequisite for sustainable high production.