Conversion of no/low value waste frying oils into biodiesel and polyhydroxyalkanoates

A sustainable bioprocess was developed for the valorization of a no/low value substrate, i.e. waste frying oils (WFOs) with high content of free fatty acids (FFAs), otherwise unsuitable for biodiesel production. The bioprocess was verified using both recombinant (Escherichia coli) and native (Pseudomonas resinovorans) polyhydroxyalkanoates (PHAs) producing cell factories. Microbial fermentation of WFOs provided a 2-fold advantage: i) the reduction of FFAs content resulting into an upgrading of the "exhausted waste oils" and ii) the production of a bio-based microbial polymer. Proper strain designing and process optimization allowed to achieve up to 1.5 g L-1 of medium chain length, mcl-PHAs, together with an efficient conversion (80% yield) of the treated WFO into biodiesel

Measuring Information Transfer

An information theoretic measure is derived that quantifies the statistical coherence between systems evolving in time. The standard time delayed mutual information fails to distinguish information that is actually exchanged from shared information due to common history and input signals. In our new approach, these influences are excluded by appropriate conditioning of transition probabilities. The resulting transfer entropy is able to distinguish driving and responding elements and to detect asymmetry in the coupling of subsystems.Comment: 4 pages, 4 Figures, Revte

Fermentation of biodegradable organic waste by the family thermotogaceae

The abundance of organic waste generated from agro-industrial processes throughout the world has become an environmental concern that requires immediate action in order to make the global economy sustainable and circular. Great attention has been paid to convert such nutrient-rich organic waste into useful materials for sustainable agricultural practices. Instead of being an environmental hazard, biodegradable organic waste represents a promising resource for the production of high value-added products such as bioenergy, biofertilizers, and biopolymers. The ability of some hyperthermophilic bacteria, e.g., the genera Thermotoga and Pseudothermotoga, to anaerobically ferment waste with the concomitant formation of bioproducts has generated great interest in the waste management sector. These biotechnologically significant bacteria possess a complementary set of thermostable enzymes to degrade complex sugars, with high production rates of biohydrogen gas and organic molecules such as acetate and lactate. Their high growth temperatures allow not only lower contamination risks but also improve substrate solubilization. This review highlights the promises and challenges related to using Thermotoga and Pseudothermotoga spp. as sustainable systems to convert a wide range of biodegradable organic waste into high value-added products

Dimethylsulfide oxidation over the tropical South Atlantic: OH and other oxidants

The general course of events in the formation of a marine cloud begins with the emission of species which can eventually serve as nuclei around which water can condense to form a cloud droplet. In remote marine regions, cloud condensation nuclei (CCN) are primarily composed of sulfate, in either its acid or ammonium salt form. Most sulfate in these regions is the product of atmospheric oxidation of dimethyl sulfide (DMS), a reduced sulfur gas that is released by phytoplankton at the ocean surface. Therefore, in order to effectively quantify the links in the cloud-formation cycle, one must begin with a well-defined description of the atmospheric chemistry of DMS. The intent of this project has been to initiate development of a comprehensive model of the chemistry and dynamics responsible for the formation of clouds in the remote marine boundary layer. The primary tool in this work has been the Global/Regional Atmospheric Chemistry Event Simulator (GRACES), a global atmospheric chemistry model, which is under development within the Atmospheric Chemistry and Dynamics Branch of NASA-Ames Research Center. In this effort, GRACES was used to explore the first chemical link between DMS and sulfate by modeling the diurnal variation of DMS

Surface displaced alfa-enolase of Lactobacillus plantarum is a fibronectin binding protein.

BACKGROUND: Lactic acid bacteria of the genus Lactobacillus and Bifidobacterium are one of the most important health promoting groups of the human intestinal microbiota. Their protective role within the gut consists in out competing invading pathogens for ecological niches and metabolic substrates. Among the features necessary to provide health benefits, commensal microorganisms must have the ability to adhere to human intestinal cells and consequently to colonize the gut. Studies on mechanisms mediating adhesion of lactobacilli to human intestinal cells showed that factors involved in the interaction vary mostly among different species and strains, mainly regarding interaction between bacterial adhesins and extracellular matrix or mucus proteins. We have investigated the adhesive properties of Lactobacillus plantarum, a member of the human microbiota of healthy individuals. RESULTS: We show the identification of a Lactobacillus plantarum LM3 cell surface protein (48 kDa), which specifically binds to human fibronectin (Fn), an extracellular matrix protein. By means of mass spectrometric analysis this protein was identified as the product of the L. plantarum enoA1 gene, coding the EnoA1 alfa-enolase. Surface localization of EnoA1 was proved by immune electron microscopy. In the mutant strain LM3-CC1, carrying the enoA1 null mutation, the 48 kDa adhesin was not anymore detectable neither by anti-enolase Western blot nor by Fn-overlay immunoblotting assay. Moreover, by an adhesion assay we show that LM3-CC1 cells bind to fibronectin-coated surfaces less efficiently than wild type cells, thus demonstrating the significance of the surface displaced EnoA1 protein for the L. plantarum LM3 adhesion to fibronectin. CONCLUSION: Adhesion to host tissues represents a crucial early step in the colonization process of either pathogens or commensal bacteria. We demonstrated the involvement of the L. plantarum Eno A1 alfa-enolase in Fn-binding, by studying LM3 and LM3-CC1 surface proteins. Isolation of LM3-CC1 strain was possible for the presence of expressed enoA2 gene in the L. plantarum genome, giving the possibility, for the first time to our knowledge, to quantitatively compare adhesion of wild type and mutant strain, and to assess doubtless the role of L. plantarum Eno A1 as a fibronectin binding protein

Polymer Chemistry Applications of Cyrene and its Derivative Cygnet 0.0 as Safer Replacements for Polar Aprotic Solvents

This study explores a binary solvent system composed of biobased Cyrene and its derivative Cygnet 0.0 for application in membrane technology and in biocatalytic synthesis of polyesters. Cygnet-Cyrene blends could represent viable replacements for toxic polar aprotic solvents. The use of a 50 wt Cygnet-Cyrene mixture makes a practical difference in the production of flat sheet membranes by nonsolvent-induced phase separation. New polymeric membranes from cellulose acetate, polysulfone, and polyimide are manufactured by using Cyrene, Cygnet 0.0, and their blend. The resultant membranes have different morphology when the solvent/mixture and temperature of the casting solution change. Moreover, Cyrene, Cygnet 0.0, and Cygnet-Cyrene are also explored for substituting diphenyl ether for the biocatalytic synthesis of polyesters. The results indicate that Cygnet 0.0 is a very promising candidate for the enzymatic synthesis of high molecular weight polyesters

Lyapunov spectral analysis of a nonequilibrium Ising-like transition

By simulating a nonequilibrium coupled map lattice that undergoes an Ising-like phase transition, we show that the Lyapunov spectrum and related dynamical quantities such as the dimension correlation length~$\xi_\delta$ are insensitive to the onset of long-range ferromagnetic order. As a function of lattice coupling constant~$g$ and for certain lattice maps, the Lyapunov dimension density and other dynamical order parameters go through a minimum. The occurrence of this minimum as a function of~$g$ depends on the number of nearest neighbors of a lattice point but not on the lattice symmetry, on the lattice dimensionality or on the position of the Ising-like transition. In one-space dimension, the spatial correlation length associated with magnitude fluctuations and the length~$\xi_\delta$ are approximately equal, with both varying linearly with the radius of the lattice coupling.Comment: 29 pages of text plus 15 figures, uses REVTeX macros. Submitted to Phys. Rev. E

HERMES: Towards an Integrated Toolbox to Characterize Functional and Effective Brain Connectivity

The analysis of the interdependence between time series has become an important field of research in the last years, mainly as a result of advances in the characterization of dynamical systems from the signals they produce, the introduction of concepts such as generalized and phase synchronization and the application of information theory to time series analysis. In neurophysiology, different analytical tools stemming from these concepts have added to the ‘traditional’ set of linear methods, which includes the cross-correlation and the coherency function in the time and frequency domain, respectively, or more elaborated tools such as Granger Causality. This increase in the number of approaches to tackle the existence of functional (FC) or effective connectivity (EC) between two (or among many) neural networks, along with the mathematical complexity of the corresponding time series analysis tools, makes it desirable to arrange them into a unified-easy-to-use software package. The goal is to allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of these analysis methods from a single integrated toolbox. Here we present HERMES (http://hermes.ctb.upm.es), a toolbox for the Matlab® environment (The Mathworks, Inc), which is designed to study functional and effective brain connectivity from neurophysiological data such as multivariate EEG and/or MEG records. It includes also visualization tools and statistical methods to address the problem of multiple comparisons. We believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis

Memory in Microbes: Quantifying History-Dependent Behavior in a Bacterium

Memory is usually associated with higher organisms rather than bacteria. However, evidence is mounting that many regulatory networks within bacteria are capable of complex dynamics and multi-stable behaviors that have been linked to memory in other systems. Moreover, it is recognized that bacteria that have experienced different environmental histories may respond differently to current conditions. These “memory” effects may be more than incidental to the regulatory mechanisms controlling acclimation or to the status of the metabolic stores. Rather, they may be regulated by the cell and confer fitness to the organism in the evolutionary game it participates in. Here, we propose that history-dependent behavior is a potentially important manifestation of memory, worth classifying and quantifying. To this end, we develop an information-theory based conceptual framework for measuring both the persistence of memory in microbes and the amount of information about the past encoded in history-dependent dynamics. This method produces a phenomenological measure of cellular memory without regard to the specific cellular mechanisms encoding it. We then apply this framework to a strain of Bacillus subtilis engineered to report on commitment to sporulation and degradative enzyme (AprE) synthesis and estimate the capacity of these systems and growth dynamics to ‘remember’ 10 distinct cell histories prior to application of a common stressor. The analysis suggests that B. subtilis remembers, both in short and long term, aspects of its cell history, and that this memory is distributed differently among the observables. While this study does not examine the mechanistic bases for memory, it presents a framework for quantifying memory in cellular behaviors and is thus a starting point for studying new questions about cellular regulation and evolutionary strategy