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.     

Analysis of conformational motions and related key residue interactions responsible for a specific function of proteins with elastic network model

Protein collective motions play a critical role in many biochemical processes. How to predict the functional motions and the related key residue interactions in proteins is important for our understanding in the mechanism of the biochemical processes. Normal mode analysis (NMA) of the elastic network model (ENM) is one of the effective approaches to investigate the structure-encoded motions in proteins. However, the motion modes revealed by the conventional NMA approach do not necessarily correspond to a specific function of protein. In the present work, a new analysis method was proposed to identify the motion modes responsible for a specific function of proteins and then predict the key residue interactions involved in the functional motions by using a perturbation approach. In our method, an internal coordinate that accounts for the specific function was introduced, and the Cartesian coordinate space was transformed into the internal/Cartesian space by using linear approximation, where the introduced internal coordinate serves as one of the axes of the coordinate space. NMA of ENM in this internal/Cartesian space was performed and the function-relevant motion modes were identified according to their contributions to the specific function of proteins. Then the key residue interactions important for the functional motions of the protein were predicted as the interactions whose perturbation largely influences the fluctuation along the internal coordinate. Using our proposed methods, the maltose transporter (MalFGK₂) from E. Coli was studied. The functional motions and the key residue interactions that are related to the channel-gating function of this protein were successfully identified.     

The detection of two antigenic groups among Renibacterium salmoninarum isolates

The analysis of the membrane proteins and their antigenic properties in a group of 14 geographically diverse strains of Renibacterium salmoninarum revealed the existence of antigenic diversity within this species. Eleven isolates, including the type strain ATCC 33209, shared a similar protein profile with a major component of 57 kDa whereas three strains showed a common pattern with a major protein of 30 kDa. The quantitative agglutination tests and Western blotting assays seem to indicate the existence of serological heterogeneity, with two distinct groups being detected.     

Protein factors that bind to the murine 2',5'-oligoadenylate synthetase ME-12 gene 5' upstream regulatory region

The murine 2',5'-oligoadenylate synthetase ME-12 gene regulatory region AB forms six complexes with protein factors in murine BALB/c 3T3 cells as demonstrated by the mobility shift electrophoresis assay under the reaction conditions used. The complexes, designated C1-C6 in order of their decreasing electrophoretic mobility, showed three distinctive specificities with regulatory region AB, element A, and element B as probes or competing DNA: 1) C1 is region AB-specific (this complex did not form with either element A or B used alone or as a mixture); 2) C5 formed both with element A and element B; 3) C2, C3, C4, and C6 formed with element B, but not A. The protein factors that give rise to these complexes show differential DNA binding activities in various buffer solutions at different pH values. The C4-forming protein factor is the interferon (IFN)-alpha/beta-stimulated response factor (ISRF) which shows element B specificity. It preexists in the cytoplasm. ISRF appears to be complexed to an inhibitor (ISRFI) in the cytoplasm and to dissociate from the inhibitor and to translocate into the nucleus upon treatment of cells with IFN-alpha/beta. We propose that IFN-alpha/beta treatment of BALB/c 3T3 can trigger at least two events: 1) loosening of a tight inhibitor-ISRF complex with the release of free ISRF; this may be mediated via phosphorylation of ISRF or ISRFI; 2) translocation of ISRF into the nucleus and binding to the enhancer element B, which results in the activation of 2',5'-oligoadenylate synthetase gene expression.     

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.