Thionine increases electricity generation from microbial fuel cell using Saccharomyces cerevisiae and exoelectrogenic mixed culture

Microbial fuel cells (MFCs) have been shown to be capable of clean energy production through the oxidation of biodegradable organic waste using various bacterial species as biocatalysts. In this study we found Saccharomyces cerevisiae, previously known electrochemcially inactive or less active species, can be acclimated with an electron mediator thionine for electrogenic biofilm formation in MFC, and electricity production is improved with facilitation of electron transfer. Power generation of MFC was also significantly increased by thionine with both aerated and non-aerated cathode. With electrochemically active biofilm enriched with swine wastewater, MFC power increased more significantly by addition of thionine. The optimum mediator concentration was 500 mM of thionine with S. cerevisae in MFC with the maximum voltage and current generation in the microbial fuel cell were 420 mV and 700 mA/m(2), respectively. Cyclic voltametry shows that thionine improves oxidizing and reducing capability in both pure culture and acclimated biofilm as compared to non-mediated cell. The results obtained indicated that thionine has great potential to enhance power generation from unmediated yeast or electrochemically active biofilm in MFC.     

The Tuning of Human Motor Response to Risk in a Dynamic Environment Task

The role of motor uncertainty in discrete or static space tasks, such as pointing tasks, has been investigated in many experiments. These studies have shown that humans hold an internal representation of intrinsic and extrinsic motor uncertainty and compensate for this variability when planning movement. The aim of this study was to investigate how humans respond to uncertainties during movement execution in a dynamic environment despite indeterminate knowledge of the outcome of actions. Additionally, the role of errors, or lack thereof, in predicting risk was examined. In the experiment, subjects completed a driving simulation game on a two-lane road. The road contained random curves so that subjects were forced to use sensory feedback to complete the task and could not rely only on motor planning. Risk was manipulated by using horizontal perturbations to create the illusion of driving on a bumpy road, thereby imposing motor uncertainty, and altering the cost function of the road. Results suggest continual responsiveness to cost and uncertainty in a dynamic task and provide evidence that subjects avoid risk even in the absence of errors. The results suggest that humans tune their statistical motor behavior based on cost, taking into account probabilities of possible outcomes in response to environmental uncertainty.     

Automatic classification and robust identification of vestibulo-ocular reflex responses: from theory to practice

The Vestibulo-Ocular Reflex (VOR) stabilizes images of the world on our retinae when our head moves. Basic daily activities are thus impaired if this reflex malfunctions. During the past few decades, scientists have modeled and identified this system mathematically to diagnose and treat VOR deficits. However, traditional methods do not analyze VOR data comprehensively because they disregard the switching nature of nystagmus; this can bias estimates of VOR dynamics. Here we propose, for the first time, an automated tool to analyze entire VOR responses (slow and fast phases), without a priori classification of nystagmus segments. We have developed GNL-HybELS (Generalized NonLinear Hybrid Extended Least Squares), an algorithmic tool to simultaneously classify and identify the responses of a multi-mode nonlinear system with delay, such as the horizontal VOR and its alternating slow and fast phases. This algorithm combines the procedures of Generalized Principle Component Analysis (GPCA) for classification, and Hybrid Extended Least Squares (HybELS) for identification, by minimizing a cost function in an optimization framework. It is validated here on clean and noisy VOR simulations and then applied to clinical VOR tests on controls and patients. Prediction errors were less than 1 deg for simulations and ranged from .69 deg to 2.1 deg for the clinical data. Nonlinearities, asymmetries, and dynamic parameters were detected in normal and patient data, in both fast and slow phases of the response. This objective approach to VOR analysis now allows the design of more complex protocols for the testing of oculomotor and other hybrid systems.     

Preparation and Characterization of Zein/Sodium Caseinate/Xanthan Gum Complex for Encapsulation of Piperine and its In Vitro Release Study

To encapsulate piperine (Pip), as a poor water-soluble bioactive compound, zein-sodium caseinate-xanthan gum (Z-SG-XG) nanocomplex was prepared as a colloidal delivery system. The effect of different parameters involved in complexation process, including concentration of proteins, polysaccharide, and Pip on the encapsulation efficiency of Pip, particle size and stability of the nanocomplexes was investigated. Powders obtained by freeze-drying of the colloidal solution had relatively uniform particles compared to those obtained from conventional drying system and showed well redispersibility in water. At the optimal condition, a stable and homogeneous nanocomplex with a mean particle size of 145.9 ± 2.7 nm, PDI of 0.27 ± 0.01, and ζ-potential of −39.7 ± 1.3 mV was obtained. The antioxidant activity of Pip was significantly improved by encapsulation into the Z-SC-XG nanocomplex. Also, the in vitro release of Pip from the synthesized nanocomplexes in phosphate-buffer saline (PBS) solution and simulated gastrointestinal fluids (SGIF) was investigated and the release kinetic was studied as well. The Pip/Z-SG-XG nanocomplex showed a slower release in SGIF compared to the free Pip and nanoparticles without XG and SC, while its antioxidant activity was remarkable. Results suggested a possible utilization of Z-SC-XG nanocomplex for improving the water solubility, bioavailability and storage stability of Pip.