Search

Escherichia coli and other bacteria navigating through 'open' environments are under the impact of noise from the environment and from within the cells. This generates fluctuations in the kinetic parameters that characterize the intra-cellular reactions of the chemosensory network, thus affecting the chemotaxis of the cells. This aspect has been studied here for E. coli synthesizing recombinant glucoamylase in a continuous-flow microreactor. Response coefficient analysis (RCA) was applied to a new four-parameter model of the chemotaxis of E. coli. The model considered two types of responses of the cells - linear and adaptive - and two rates of movement of the chemoattractant - slow and fast. Some cells at each position in the microreactor were considered to be moving to the left, some to the right and others in a tumbling state. Striking similarities and differences were observed between the different types of cells, between linear and adaptive responses, and between the kinetic responses to a slow-moving and a fast-moving chemoattractant distribution. One salient observation was that the response coefficients of the left-moving and right-moving subpopulations were mirror images of each other. Tumbling cells either had intermediate characteristics in some situations, as might be expected, or, in other circumstances, resembled the left-moving cells more than they corresponded to the right-moving bacteria. Under certain conditions, cells with normal linear responses exhibited pseudo-adaptive kinetic behavior. Such unexpected observations have been explained. The results offer new insights into possible quantitative effects of environmental noise on the chemotaxis of E. coli and other bacteria. [ABSTRACT FROM AUTHOR]

Even though microreactors are performing an increasing number of chemical and biological reactions better than conventional macroreactors, their weaknesses are being observed and overcome. A recent method is to conduct reactions inside liquid microdroplets. Each droplet contains all the reagents and catalysts required and the conditions are controlled to promote the most favorable processes. By populating a microreactor with millions of microdroplets, each performing as a complete reactor or sub-reactor, it is possible to distribute different reactions at different rates. Then the droplets may be fused or fissioned as required so that complementary processes are brought into contact with one another at the appropriate points in time. The present article provides an overview of the width and potential of this new and exciting technology across chemical and biological applications. [ABSTRACT FROM AUTHOR]

The chemotaxis of Escherichia coli (E. coli) and other bacteria in real environments is subject to noise from outside, in addition to that within the cells. While the cells have internal mechanisms to filter intracellular noise, external intervention is needed for noise from the environment. In previous microbial applications, neural networks have been more effective in filtering environmental noise than algorithmic devices. On this basis, a number of neural network configurations are explored for their effectiveness as external filters in consonance with internal filtering in the chemotaxis of E. coli. Simulations showed significant improvements with neural filters, with the auto-associative filter being the best. The results also revealed the possibility of stochastic resonance between the filtered internal and external noise being a cause of such improvement, and this likelihood is supported by previous reports in different applications. [ABSTRACT FROM AUTHOR]

The kinetics of immobilized enzyme-catalyzed reactions in microreactors differ from those in macro-scale reactors. Recognizing this, a recent study (Patnaik 2011) based on a new interpretation of the kinetics of AP-catalyzed reactions showed that dynamic behavior is feasible only certain loci relating key kinetic parameters. That work has been extended here, and the kinetic parameters have now been related to bulk phase concentrations, thereby providing a link with the reaction system per se. It has also been shown that under certain conditions the reaction may become self-quenching but either monotonically or as damped oscillations. These two studies thus establish the importance of understanding kinetic dynamics in microreactors and in selecting feasible operating conditions. [ABSTRACT FROM AUTHOR]

A sensitive and selective LC-MS/MS method has been developed and validated for the estimation of novel antidiabetic synthetic flavonoid S002-853 in rat plasma using centchroman as an internal standard. The method involves a simple two-step liquid-liquid extraction with diethyl ether. The analyte was chromatographed on a Pierce Spheri-5, guard cyano column (30 × 4.6 mm i.d., 5 µm) with isocratic mobile phase consisting of methanol-ammonium acetate buffer (pH 4.6, 10 m m; 90 : 10, v/v) at a flow rate of 0.75 mL/min. The API 4000 triple-quadrupole LC-MS/MS system was operated under multiple reaction-monitoring mode. The ionization was performed by electrospray ionization technique in positive ion mode. The chromatographic run time was 6 min and the weighted (1/ x2) calibration curves were linear over the range 0.78-400 ng/mL. The limit of detection and lower limit of quantification were 0.195 and 0.78 ng/mL, respectively. The intra- and inter-batch accuracy (%bias) and precision (%RSD) were found to be less than 8.47 and 11.6% respectively. The average absolute recoveries of S002-853 and internal standard from spiked plasma samples were >90%. S002-853 was stable for 8 h at ambient temperature, 4 weeks at −60°C and after three freeze-thaw cycles. The assay was successfully applied to determine the pharmacokinetic parameters in male Sprague-Dawley rats after an oral dose administration at 25 mg/kg. Copyright © 2009 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The complexity of microbial processes, coupled with the effects of incomplete mixing and the influx of noise, makes it difficult to describe quantitatively the behavior of bioreactors under realistic conditions. By circumventing the need for phenomenological equations, neural networks offer viable descriptions of such systems. However, such networks also require large amounts of carefully screened data and long training schedules. They also have limited extrapolation capability and poor physiological fidelity. Since phenomenological models are derived from physical descriptions of cellular processes, combinations of such models with neural networks, and sometimes also fuzzy logic, have provided good portrayals of nonideal bioreactor behavior while reducing the weaknesses of both approaches. However, like neural networks themselves, different architectures are possible for hybrid neural models. The rationale, architectures and illustrative applications of hybrid models for biological reactors are discussed here, with the possibility of combining them with cybernetic models, exploiting cellular intelligence, to develop self-evolving intelligent systems for optimization and control of microbial processes. [ABSTRACT FROM AUTHOR]

Bacteria moving in response to chemical attractants are subject to noise from the environment in addition to that within the cells. Environmental noise is observed typically through fluctuations in the concentrations of the chemoattractant. Interactions between two or more sources of noise may upset the chemotactic motility of the cells. This possibility is investigated here for Escherichia coli through a pair of conditions derived earlier. These conditions relate the tumbling time, the sensing time and the adaptation time of the cells. It is observed that chemotaxis is not feasible if the normalized variance of the external noise exceeds a critical value. This critical value does not depend on the expression of CheR, a key protein in the chemosensory system, and it agrees with similar values reported by others for intra-cellular noise. These observations indicate that stochastic resonance may be a prime factor enhancing chemotaxis in the presence of noise. [ABSTRACT FROM AUTHOR]

This paper deals with a group theoretic approach to the finite element analysis of linear free vibrations of shells with dihedral symmetry. Examples of such shell structures are cylindrical shells, conical shells, shells with circumferential stiffeners, corrugated shells, spherical shells, etc. The group theoretic approach is used to exploit the inherent symmetry in the problem. For vibration analysis, the group theoretic results give the correct symmetry-adapted basis for the displacement field. The stiffness matrix K and the mass matrix M are identically block diagonalized in this basis. The generalized linear eigenvalue problem of free vibration gets split into independent subproblems due to this block diagonalization. The Simo element is used in the finite element formulation of the shell equilibrium equations. Numerical results for natural frequencies and natural modes of vibration of several dihedral shell structures are presented. The results are shown to be in very good agreement with those reported in the literature. The computational advantages and physical insights due to the group theoretic approach are also discussed. [Copyright &y& Elsevier]

Presents information on a study which examined a damped, bilinear hysteretic oscillator. Equation of motion; Approximate frequency response equation; Bilinear elastic oscillator and equivalent viscous damping.

The motor symptoms of PD are key in the early diagnosis of the disease and are the most-impactful throughout the course of PD. According to the Parkinson's Foundation, at present nearly one million persons in the US suffer from Parkinson's Disease (PD). Prescribing exercise for PD patients is vitally important in improving motor symptoms in PD as well in improving anxiety/mood symptoms and quality of life. [Extracted from the article]

Copyright of Il Nuovo Cimento: B is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The temporal evolution of pressure in solar coronal loops is studied using the ideal theory of magnetohydrodynamic turbulence in cylindrical geometry. The velocity and the magnetic fields are expanded in terms of the Chandrasekhar-Kendall (C-K) functions. The three-mode representation of the velocity and the magnetic fields submits to the investigation of chaos. When the initial values of the velocity and the magnetic field coefficients are very nearly equal, the system shows periodicities. For randomly chosen initial values of these parameters, the evolution of the velocity and the magnetic fields is nonlinear and chaotic. The consequent plasma pressure is determined in the linear and nonlinear regimes. The evidence for the existence of chaos is established by evaluating the invariant correlation dimension of the attractor D, a fractal value of which indicates the existence of deterministic chaos. [ABSTRACT FROM AUTHOR]