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.     

Inhibition of Autoimmune Diabetes in NOD Mice by miRNA Therapy

Autoimmune destruction of the pancreatic islets in Type 1 diabetes is mediated by both increased proinflammatory (Teff) and decreased regulatory (Treg) T lymphocytes resulting in a significant decrease in the Treg:Teff ratio. The non-obese diabetic (NOD) mouse is an excellent in vivo model for testing potential therapeutics for attenuating the decrease in the Treg:Teff ratio and inhibiting disease pathogenesis. Here we show for the first time that a bioreactor manufactured therapeutic consisting of a complex of miRNA species (denoted as TA1) can effectively reset the NOD immune system from a proinflammatory to a tolerogenic state thus preventing or delaying autoimmune diabetes. Treatment of NOD mice with TA1 resulted in a systemic broad-spectrum upregulation of tolerogenic T cell subsets with a parallel downregulation of Teff subsets yielding a dramatic increase in the Treg:Teff ratio. Moreover, the murine-derived TA1 was highly effective in the inhibition of allorecognition of HLA-disparate human PBMC. TA1 demonstrated dose-responsiveness and exhibited equivalent or better inhibition of allorecognition driven proliferation than etanercept (a soluble TNF receptor). These findings demonstrate that miRNA-based therapeutics can effectively attenuate or arrest autoimmune disease processes and may be of significant utility in a broad range of autoimmune diseases including Type 1 diabetes.     

Side reaction in peptide synthesis. Formation of oxazolidone derivatives

2-Oxazolidone derivatives formed through an intramolecular reaction in the process of alkaline treatment of urethane-type N-protected peptides of which the N-terminal residues were Ser or Thr having unprotected hydroxyl groups. In oder to avoid this side reaction, the esters of these peptides could be cleaved by enzymatic hydrolyses instead of saponification.     

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.