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.     

Insecticidal and Repellent Activity of Siparuna guianensis Aubl. (Negramina) against Aedes aegypti and Culex quinquefasciatus

This study investigated the toxic effects of essential oils isolated from Siparuna guianensis against Aedes aegypti, Culex quinquefasciatus (eggs, larvae, pupae, and adult) and Aedes albopictus (C6/36) cells. The oviposition-deterring activity, egg viability, and repellence activity in the presence of different essential oils concentrations were determined. The essential oils showed high toxicity to all developmental stages of A. aegypti and C. quinquefasciatus. Furthermore, the oils also showed high repellent activity towards the adult stage of mosquitoes (0.025 to 0.550 μg/cm2 skin conferred 100% repellence up to 120 min) and in contact with cultured insect cells (C6/36) induced death possibly by necrosis. The results presented in this work show the potential of S. guianensis essential oils for the development of an alternative and effective method for the natural control of mosquitoes in homes and urban areas.     

Direct evidence for intra- and intermolecular disulfide bond formation in the human glucocorticoid receptor. Inhibition of DNA binding and identification of a new receptor-associated protein

We have investigated the potential for the steroid affinity-labeled human glucocorticoid receptor to form both intramolecular and intermolecular disulfide bonds. Glucocorticoid receptors labeled in intact HeLa S3 cells with the covalent affinity label [3H]dexamethasone mesylate ([3H]DM) were analyzed on denaturing 5-12% polyacrylamide gels under both nonreducing and reducing conditions. Under nonreducing conditions the affinity-labeled receptor migrated as a heterogeneous species having an average molecular mass of approximately 96 kDa whereas, under reducing conditions, the receptor migrated as a more discrete form. These data suggest that a reducing environment can influence the structure of the glucocorticoid receptor monomer and further imply that sulfhydryl groups within the affinity-labeled receptor are available for modification. To pursue this observation in greater detail, we tested the effect of oxidizing conditions on the structure of the glucocorticoid receptor. The presence of low concentrations (0.125-0.5 mM) of three oxidizing reagents (sodium tetrathionate, disulfiram, and iodosobenzoate) altered the migration of the affinity-labeled receptor resulting in forms of apparent lower molecular mass (as low as 78 kDa). This altered migration, not seen with most other cytosolic proteins, is consistent with the formation of intramolecular disulfide bonds within the receptor which presumably cause it to assume a folded conformation and migrate faster through the gel. At higher concentrations of these reagents (up to 5.0 mM), we also detect a saturably labeled [3H]DM band which has a higher molecular mass (approximately 140 kDa), indicating the formation of intermolecular disulfide bonds between the [3H]DM-labeled receptor and another closely associated protein(s) having a molecular mass of approximately 40 kDa. The effects which these oxidizing reagents have on glucocorticoid receptor structure are completely reversed upon the addition of dithiothreitol, indicating that the observed changes in migration do not reflect receptor proteolysis but rather a folding and unfolding within the receptor monomeric protein. We have also analyzed the effect of this oxidation/reduction on the function of the glucocorticoid receptor. Oxidation of the [3H]DM-labeled receptor complex with 0.5 mM sodium tetrathionate inhibited activation of receptor to a form capable of binding to DNA-cellulose. This inhibition can be reversed with dithiothreitol at 25 degrees C but not at 0 degrees C, suggesting that these oxidizing reagents are inhibitory at the transformation and/or activation steps.(ABSTRACT TRUNCATED AT 400 WORDS)     

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.     

Exotic grass invasion impacts fitness of an endangered prairie butterfly, <Emphasis Type="Italic">Icaricia icarioides fenderi</Emphasis>

Fender’s blue butterfly is an endangered species restricted to fragmented, grassland remnants that are becoming increasingly dominated by tall, invasive grasses in western Oregon, USA. I performed a removal experiment to assess the impacts of structural degradation accompanying the invasion of Arrhenatherum elatius, tall oat grass, on butterfly fitness and fitness related behaviors. Clipping of A. elatius to native grass sward height resulted in 2.5–5 times as many eggs laid per leaf of host plant. Both male and female butterflies basked more frequently in areas removed of A. elatius inflorescences and upon encountering the treatment edge butterflies had a high rate of return into a large area removed of the grass inflorescences. Although butterfly behavior appeared to be affected by the change in sward height on the treatment edge, there was no evidence for the edge causing a disproportionate egg load. Invasion and dominance by A. elatius appeared to diminish host plant apparency which may result in overloading of eggs on conspicuous host plants, increased incidence of emigration, and a decrease in the likelihood of colonization because female butterflies appeared indifferent to larval resources beneath A. elatius inflorescences. Dominance of natural shortgrass prairies by tall stature grasses like A. elatius may be an insidious form of habitat degradation for grassland Lepidoptera worldwide, but it may go largely unnoticed because larval and adult resources can persist under the unnaturally tall grass canopy.     

Multi-model recursive identification for nonlinear systems with non-uniformly sampling

A recursive least squares based on Multi-model is proposed for non-uniformly sampled-data nonlinear (NUSDN) systems. The corresponding state space model of an NUSDN system is derived using lifting technique. Taking advantage of the Fuzzy c-Mean Clustering algorithm, NUSDN is divided into several local models. The basic idea is that the NUSDN system is viewed as a model switching system under a given rule. Once the local models are identified, the global model is determined. A pH neutralization process validate the performance of the proposed algorithm.