Modification of a three-compartment muscle fatigue model to predict peak torque decline during intermittent tasks

This study aimed to test whether adding a rest recovery parameter, r, to the analytical three-compartment controller (3CC) fatigue model (Xia and Frey Law, 2008) will improve fatigue estimates during intermittent contractions. The 3CC muscle fatigue model uses differential equations to predict the flow of muscle between three muscle states: Resting (M_R), Active (M_A), and Fatigued (M_F). This model uses a feedback controller to match the active state to target loads and two joint-specific parameters: F, fatigue rate controlling flow from active to fatigued compartments) and R, the recovery rate controlling flow from the fatigued to the resting compartments. This model does well to predict intensity-endurance time curves for sustained isometric tasks. However, previous studies find when rest intervals are present that the model over predicts fatigue. Intermittent rest periods would allow for the occurrence of subsequent reactive vasodilation and post-contraction hyperemia. We hypothesize a modified 3CC-r fatigue model will improve predictions of force decay during intermittent contractions with the addition of a rest recovery parameter, r, to augment recovery during rest intervals, representing muscle re-perfusion. A meta-analysis compiling intermittent fatigue data from 63 publications reporting decline in peak torque (% torque decline) were used for comparison. The original model over-predicted fatigue development from 19 to 29% torque decline; the addition of a rest multiplier significantly improved fatigue estimates to 6–10% torque decline. We conclude the addition of a rest multiplier to the three-compartment controller fatigue model provides a physiologically consistent modification for tasks involving rest intervals, resulting in improved estimates of muscle fatigue.     

Optimization of three-dimensional modeling for geometric precision and efficiency for healthy and diseased aortas

The study purpose is to optimize modeling parameters, specifically segmentation spacing and centerline extraction, to efficiently construct accurate 3D aortic models. Models are constructed by centerline extraction and orthogonal 2D segmentations. We examine the effect of segmentation interval spacing (2, 1, 0.5, 0.25 cm) and orthogonal segmentation and centerline extraction iteration (one, two, three iterations) for constructing models of Healthy, Tortuous, Aneurysmal, and Dissected human thoracic aortas. Aortic arclength, curvature, and cross-sectional axis ratio were computed to compare variations in modeling parameters. Centerline arclength is precisely characterized for all aortas with a single iteration of centerline extraction (≤1% deviation), however, complex anatomies required 1 cm segmentation intervals whereas the Healthy aorta only required 2 cm intervals. Centerline curvature is more sensitive to modeling methods, requiring 1 cm intervals for ≤5% deviation in peak curvature for the three diseased anatomies, and two iterations of segmentation and centerline extraction for the Aneurysmal and Dissected aortas. Accurate lumen cross-sectional characterization required 1 or 0.5 cm segmentation intervals, and two or three segmentation and centerline iterations, with greater refinement needed for more complex geometries. Depending on the geometric characteristic and complexity of anatomy and pathology, different levels of segmentation interval refinement and iterations of segmentation and centerline extraction are required.     

Incorporating biophysical ecology into high‐resolution restoration targets: insect pollinator habitat suitability models

Species distribution models can be informative of the biodiversity impacts of changing environments at global, national, and regional scales, but are often constrained in their resolution to extents not relevant to individual, intensive ecological management programs. We constructed a high‐resolution topoclimatic model of spring and summer temperatures across a 152 km² restoration area on the Swan Coastal Plain, Western Australia, and used it to project energetic expenditure and habitat suitability estimates for four major hymenopteran pollinators. For all species, the most heavily modified landscapes were the least suitable, but only for one species, Zapsilothynnus nigripes, was there evidence that the upper thermal tolerance threshold was exceeded broadly. However, at the higher environmental temperatures that we modeled, some species would need to forage up to 10 times their own body mass every hour to meet their energetic requirements. It seems unlikely that the nutritional requirements of most insect pollinators operating at these higher metabolic rates could be met in an impoverished restoration ecosystem, although resource availability remains to be quantified in these habitats. Hence, to increase the likelihood of restoration success by restoring insect pollination networks, nutritional resources may need to be increased during restoration. Accounting for the way that thermoenergetic requirements shape ecological interactions better positions management trajectories aimed at restoring and maintaining key insect pollinators in “novel” ecosystems.     

Environmental Impact Assessment of the Heterogeneity in Consumers’ Usage Behavior: An Agent‐Based Modeling Approach

The aim of this study is to develop a framework for understanding the heterogeneity and uncertainties present in the usage phase of the product life cycle through utilizing the capabilities of an agent‐based modeling (ABM) technique. An ABM framework is presented to model consumers’ daily product usage decisions and to assess the corresponding electricity consumption patterns. The theory of planned behavior (TPB), with the addition of the habit construct, is used to model agents’ decision‐making criteria. A case study is presented on the power management behavior of personal computer users and the possible benefits of using smart metering and feedback systems. The results of the simulation demonstrate that the utilization of smart metering and feedback systems can promote the energy conservation behaviors and reduce the total PC electricity consumption of households by 20%.     

Probing the interaction of cephalosporin with bovine serum albumin: A structural and comparative perspective

Cephalosporins belong the largest class of antibiotics used in the treatment of a wide range of infectious diseases caused by susceptible organisms. In the present study, we chose two typical antibiotics cefalexin/cefixime based on their structure, and investigated the interaction of cephalexin/cefixime with bovine serum albumin (BSA) using UV–vis absorption spectra, fluorescence spectroscopy, circular dichroism (CD) spectroscopy and molecular modeling approaches. Spectroscopic experiments revealed the formation of a BSA ? cefalexin/cefixime complex. The binding parameters calculated using a modified Stern ? Volmer method and the Scatchard method reached 10³–10⁴ L·mol^?1. Thermodynamic parameter studies revealed that binding characteristics by negative enthalpy and positive entropy changes, and electrostatic interactions play a major role. Site marker competitive displacement experiments and molecular modeling approaches demonstrated that cefalexin and cefixime bind with appropriate affinity to site I (subdomain IIA) of BSA. Furthermore, synchronous fluorescence spectra, CD spectra and molecular modeling results indicated that the secondary structure of BSA was changed in the presence of cefalexin and cefixime. Additionally, the effects of metal ions on the BSA ? cefalexin/cefixime system were also assessed.     

2-OMe-lysophosphatidylcholine analogues are GPR119 ligands and activate insulin secretion from βTC-3 pancreatic cells: Evaluation of structure-dependent biological activity

GPR119 receptor has been proposed as a metabolic regulator playing a pivotal role in the modulation of glucose homeostasis in type 2 diabetes. GPR119 was identified on pancreatic β cells and its ligands have the ability to enhance glucose-stimulated insulin secretion (GSIS). Lysophosphatidylcholine (LPC) was shown to potentiate GSIS and our present studies indicate that 2-methoxy-lysophosphatidylcholine (2-OMe-LPC) analogues, unable to undergo 1 → 2 acyl migration, stimulate GSIS from murine βTC-3 pancreatic cells even more efficiently. Moreover, biological assays in engineered Tango? GPR119-bla U2OS cells were carried out to ascertain the agonist activity of 2-OMe-LPC at GPR119. 2-OMe-LPC possessing in sn-1 position the residues of myristic, palmitic, stearic and oleic acid were also evaluated as factors regulating [Ca^2 +]_i mobilization and cAMP levels. Extension of these studies to R- and S-enantiomers of 14:0 2-OMe-LPC revealed that the overall impact on GSIS does not depend on chirality, however, the intracellular calcium mobilization data show that the R enantiomer is significantly more active than S one. Taking into account differences in chemical structure between various native LPCs and their 2-methoxy counterparts the possible binding mode of 2-OMe-LPC to the GPR119 receptor was determined using molecular modeling approach.     

Reengineering the ligand sensitivity of the broadly tuned human bitter taste receptor TAS2R14

Background

In humans, bitterness perception is mediated by ~25 bitter taste receptors present in the oral cavity. Among these receptors three, TAS2R10, TAS2R14 and TAS2R46, exhibit extraordinary wide agonist profiles and hence contribute disproportionally high to the perception of bitterness. Perhaps the most broadly tuned receptor is the TAS2R14, which may represent, because of its prominent expression in extraoral tissues, a receptor of particular importance for the physiological actions of bitter compounds beyond taste.