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.     

Application of Rice-Straw Biochar and Microorganisms in Nonylphenol Remediation: Adsorption-Biodegradation Coupling Relationship and Mechanism

Biochar adsorption presents a potential remediation method for the control of hydrophobic organic compounds (HOCs) pollution in the environment. It has been found that HOCs bound on biochar become less bioavailable, so speculations have been proposed that HOCs will persist for longer half-life periods in biochar-amended soil/sediment. To investigate how biochar application affects coupled adsorption-biodegradation, nonylphenol was selected as the target contaminant, and biochar derived from rice straw was applied as the adsorbent. The results showed that there was an optimal dosage of biochar in the presence of both adsorption and biodegradation for a given nonylphenol concentration, thus allowing the transformation of nonylphenol to be optimized. Approximately 47.6% of the nonylphenol was biodegraded in two days when 0.005 g biochar was added to 50 mg/L of nonylphenol, which was 125% higher than the relative quantity biodegraded without biochar, though the resistant desorption component of nonylphenol reached 87.1%. All adsorptive forms of nonylphenol (f _rap, f _slow, f _r) decreased gradually during the biodegradation experiment, and the resistant desorption fraction of nonylphenol (f _r) on biochar could also be biodegraded. It was concluded that an appropriate amount of biochar could stimulate biodegradation, not only illustrating that the dosage of biochar had an enormous influence on the half-life periods of HOCs but also alleviating concerns that enhanced HOCs binding by biochar may cause secondary pollution in biochar-modified environment.     

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.     

The Effects of Mobile Phone Radiofrequency Radiation on Cochlear Stria Marginal Cells in Sprague–Dawley Rats

To investigate the possible mechanisms for biological effects of 1,800 MHz mobile radiofrequency radiation (RFR), the radiation-specific absorption rate was applied at 2 and 4 W/kg, and the exposure mode was 5 min on and 10 min off (conversation mode). Exposure time was 24 h short-term exposure. Following exposure, to detect cell DNA damage, cell apoptosis, and reactive oxygen species (ROS) generation, the Comet assay test, flow cytometry, DAPI (4′,6-diamidino-2-phenylindole dihydrochloride) staining, and a fluorescent probe were used, respectively. Our experiments revealed that mobile phone RFR did not cause DNA damage in marginal cells, and the rate of cell apoptosis did not increase (P > 0.05). However, the production of ROS in the 4 W/kg exposure group was greater than that in the control group (P < 0.05). In conclusion, these results suggest that mobile phone energy was insufficient to cause cell DNA damage and cell apoptosis following short-term exposure, but the cumulative effect of mobile phone radiation still requires further confirmation. Activation of the ROS system plays a significant role in the biological effects of RFR. Bioelectromagnetics. © 2020 The Authors. Bioelectromagnetics published by Wiley Periodicals, Inc.     

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.