A validated model of passive skeletal muscle to predict force and intramuscular pressure

The passive properties of skeletal muscle are often overlooked in muscle studies, yet they play a key role in tissue function in vivo. Studies analyzing and modeling muscle passive properties, while not uncommon, have never investigated the role of fluid content within the tissue. Additionally, intramuscular pressure (IMP) has been shown to correlate with muscle force in vivo and could be used to predict muscle force in the clinic. In this study, a novel model of skeletal muscle was developed and validated to predict both muscle stress and IMP under passive conditions for the New Zealand White Rabbit tibialis anterior. This model is the first to include fluid content within the tissue and uses whole muscle geometry. A nonlinear optimization scheme was highly effective at fitting model stress output to experimental stress data (normalized mean square error or NMSE fit value of 0.993) and validation showed very good agreement to experimental data (NMSE fit values of 0.955 and 0.860 for IMP and stress, respectively). While future work to include muscle activation would broaden the physiological application of this model, the passive implementation could be used to guide surgeries where passive muscle is stretched.     

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.     

Corrosion of metals in natural waters influenced by manganese oxidizing microorganisms

Case histories and proposed mechanisms formicrobiologically influenced corrosion of metals andalloys by metal depositing microorganisms arereviewed. Mechanisms with indirect participation ofthese microorganisms, usually iron- and manganeseoxidizing species, are distinguished from anothermechanism which accounts specifically for theelectrochemical properties of deposits containingoxides and hydroxides of Mn in higher oxidationstates. The possible influence of such deposits whichwere formed microbiologically is evaluated. Theevaluation is based on the principles ofelectrochemical corrosion of metals and on theelectrochemical properties of Mn^3+/4+- compounds.After briefly reviewing the microbiologicalMn-oxidation, experimental evidence for the predictedcorrosion by such deposits is provided and a model formicrobiologically influenced corrosion by manganeseoxidizing microorganisms is proposed for stainlesssteel. Possible consequences of the model andpractical aspects of such a corrosion are discussed.     

How reliable are the Powell–Wetherall plot method and the maximum-length approach? Implications for length-based studies of growth and mortality

Length-based methods are the cornerstone of many population studies and stock assessments. This study tested two widely used methods: the Powell–Wetherall (P–W) plot and the L_max approach (i.e., estimating L_∞ directly from L_max). In most simulations, P–W estimates of the ratio total mortality/growth (Z/K ratio) were biased beyond acceptable limits (bias?>?30%). Bias in Z/K showed a complex behavior, without possible corrections. Estimates of asymptotic length (L_∞) were less biased than Z/K, but were very sensitive to intra-cohort variability in growth and to changes in the occurrence of large individuals in the sample. Exclusion of the largest size classes during the regression procedure or weighing by abundance does not solve these issues. Perfect linearization of the data and extremely narrow confidence intervals for Z/K will lead users to erroneous overconfidence in outputs. Clearly, the P–W method is not suitable for the assessment of Z/K ratios of natural populations. Estimation of L_∞ may be tentatively possible under very specific conditions, with necessary external verifications. Also, this study demonstrates that there is no way to estimate L_∞ directly from L_max, since there is no particular relationship to expect a priori between L_∞ and L_max. Errors in estimating L_∞ directly affect the estimate of the growth constant K and all other subsequent calculations in population studies, stock assessments and ecosystem models. New approaches are urgently needed for length-based studies of body growth (e.g., unconstrained curve fit with subsequent bootstrapping), that consider the inherent uncertainty regarding the underlying data and processes.     

Capturing pair-wise epistatic effects associated with three agronomic traits in barley

Genetic association mapping has been widely applied to determine genetic markers favorably associated with a trait of interest and provide information for marker-assisted selection. Many association mapping studies commonly focus on main effects due to intolerable computing intensity. This study aims to select several sets of DNA markers with potential epistasis to maximize genetic variations of some key agronomic traits in barley. By doing so, we integrated a MDR (multifactor dimensionality reduction) method with a forward variable selection approach. This integrated approach was used to determine single nucleotide polymorphism pairs with epistasis effects associated with three agronomic traits: heading date, plant height, and grain yield in barley from the barley Coordinated Agricultural Project. Our results showed that four, seven, and five SNP pairs accounted for 51.06, 45.66 and 40.42% for heading date, plant height, and grain yield, respectively with epistasis being considered, while corresponding contributions to these three traits were 45.32, 31.39, 31.31%, respectively without epistasis being included. The results suggested that epistasis model was more effective than non-epistasis model in this study and can be more preferred for other applications.