MECHANISM OF CELL LYSIS IN MICROFLUIDIC CHANNEL WITH INTEGRATED NANOCOMPOSITE ELECTRODES

This paper reports on the characterization of an integrated micro-fluidic platform for controlled electrical lysis of biological cells and subsequent extraction of intracellular biomolecules. The proposed methodology is capable of high throughput electrical cell lysis facilitated by nano-composite coated electrodes. The nano-composites are synthesized using Carbon Nanotube and ZnO nanorod dispersion in polymer. Bacterial cells are used to demonstrate the lysis performance of these nanocomposite electrodes. Investigation of electrical lysis in the microchannel is carried out under different parameters, one with continuous DC application and the other under DC biased AC electric field. Lysis in DC field is dependent on optimal field strength and governed by the cell type. By introducing the AC electrical field, the electrokinetics is controlled to prevent cell clogging in the micro-channel and ensure uniform cell dispersion and lysis. Lysis mechanism is analyzed with time-resolved fluorescence imaging which reveal the time scale of electrical lysis and explain the dynamic behavior of GFP-expressing E. coli cells under the electric field induced by nanocomposite electrodes. The DNA and protein samples extracted after lysis are compared with those obtained from a conventional chemical lysis method by using a UV-Visible spectroscopy and fluorimetry. The paper also focuses on the mechanistic understanding of the nano-composite coating material and the film thickness on the leakage charge densities which lead to differential lysis efficiency.

The effect of cell size and channel density on neuronal information encoding and energy efficiency

Identifying the determinants of neuronal energy consumption and their relationship to information coding is critical to understanding neuronal function and evolution. Three of the main determinants are cell size, ion channel density, and stimulus statistics. Here we investigate their impact on neuronal energy consumption and information coding by comparing single-compartment spiking neuron models of different sizes with different densities of stochastic voltage-gated Na+ and K+ channels and different statistics of synaptic inputs. The largest compartments have the highest information rates but the lowest energy efficiency for a given voltage-gated ion channel density, and the highest signaling efficiency (bits spike(-1)) for a given firing rate. For a given cell size, our models revealed that the ion channel density that maximizes energy efficiency is lower than that maximizing information rate. Low rates of small synaptic inputs improve energy efficiency but the highest information rates occur with higher rates and larger inputs. These relationships produce a Law of Diminishing Returns that penalizes costly excess information coding capacity, promoting the reduction of cell size, channel density, and input stimuli to the minimum possible, suggesting that the trade-off between energy and information has influenced all aspects of neuronal anatomy and physiology.

A unified view of energetic efficiency in active drag reduction, thrust generation and self-propulsion through a loss coefficient with some applications

An analysis of the energy budget for the general case of a body translating in a stationary fluid under the action of an external force is used to define a power loss coefficient. This universal definition of power loss coefficient gives a measure of the energy lost in the wake of the translating body and, in general, is applicable to a variety of flow configurations including active drag reduction, self-propulsion and thrust generation. The utility of the power loss coefficient is demonstrated on a model bluff body flow problem concerning a two-dimensional elliptical cylinder in a uniform cross-flow. The upper and lower boundaries of the elliptic cylinder undergo continuous motion due to a prescribed reflectionally symmetric constant tangential surface velocity. It is shown that a decrease in drag resulting from an increase in the strength of tangential surface velocity leads to an initial reduction and eventual rise in the power loss coefficient. A maximum in energetic efficiency is attained for a drag reducing tangential surface velocity which minimizes the power loss coefficient. The effect of the tangential surface velocity on drag reduction and self-propulsion of both bluff and streamlined bodies is explored through a variation in the thickness ratio (ratio of the minor and major axes) of the elliptical cylinders.

Thermal Efficiency of LPG and PNG-fired burners: Experimental and numerical studies

In the present work, the thermal efficiency of a conventional domestic burner is studied both experimentally and numerically for liquefied petroleum gas (LPG) and piped natural gas (PNG) fuels. Three-dimensional computational fluid dynamic (CFD) modeling of the steady-state flow, combustion and heat transfer to the vessel is reported for the first time in such burners. Based on the insights from the CFD model concerning the flow and heat transfer, design modifications in the form of a circular insert and a radiant sheet are proposed which are observed to increase thermal efficiency for LPG. For PNG, predictions showed that loading height was a much more important factor affecting efficiency than these design modifications and an optimal loading height could be identified. Experiments confirm these trends by showing an improvement in burner thermal efficiency of 2.5% for LPG with the modified design, and 10% for PNG with the optimal loading height, demonstrating that the CFD modeling approach developed in the present work is a useful tool to study domestic burners. (C) 2013 Elsevier Ltd. All rights reserved.

Nitrogen deposition: how important is it for global terrestrial carbon uptake?

Global carbon budget studies indicate that the terrestrial ecosystems have remained a large sink for carbon despite widespread deforestation activities. CO2 fertilization, N deposition and re-growth of mid-latitude forests are believed to be key drivers for land carbon uptake. In this study, we assess the importance of N deposition by performing idealized near-equilibrium simulations using the Community Land Model 4.0 (CLM4). In our equilibrium simulations, only 12-17% of the deposited nitrogen is assimilated into the ecosystem and the corresponding carbon uptake can be inferred from a C : N ratio of 20 : 1. We calculate the sensitivity of the terrestrial biosphere for CO2 fertilization, climate warming and N deposition as changes in total ecosystem carbon for unit changes in global mean atmospheric CO2 concentration, global mean temperature and Tera grams of nitrogen deposition per year, respectively. Based on these sensitivities, it is estimated that about 242 PgC could have been taken up by land due to the CO2 fertilization effect and an additional 175 PgC taken up as a result of the increased N deposition since the pre-industrial period. Because of climate warming, the terrestrial ecosystem could have lost about 152 PgC during the same period. Therefore, since pre-industrial times terrestrial carbon losses due to warming may have been more or less compensated by effects of increased N deposition, whereas the effect of CO2 fertilization is approximately indicative of the current increase in terrestrial carbon stock. Our simulations also suggest that the sensitivity of carbon storage to increased N deposition decreases beyond current levels, indicating that climate warming effects on carbon storage may overwhelm N deposition effects in the future.

Local structural disorder and its influence on the average global structure and polar properties in Na0.5Bi0.5TiO3

Na0.5Bi0.5TiO3 (NBT) and its derivatives have prompted a great surge in interest owing to their potential as lead-free piezoelectrics. In spite of five decades since its discovery, there is still a lack of clarity on crucial issues such as the origin of significant dielectric relaxation at room temperature, structural factors influencing its depoling, and the status of the recently proposed monoclinic (Cc) structure vis-a-vis the nanosized structural heterogeneities. In this work, these issues are resolved by comparative analysis of local and global structures on poled and unpoled NBT specimens using electron, x-ray, and neutron diffraction in conjunction with first-principles calculation, dielectric, ferroelectric, and piezoelectric measurements. The reported global monoclinic (Cc) distortion is shown not to correspond to the thermodynamic equilibrium state at room temperature. The global monocliniclike appearance rather owes its origin to the presence of local structural and strain heterogeneities. Poling removes the structural inhomogeneities and establishes a long-range rhombohedral distortion. In the process the system gets irreversibly transformed from a nonergodic relaxor to a normal ferroelectric state. The thermal depoling is shown to be associated with the onset of incompatible in-phase tilted octahedral regions in the field-stabilized long range rhombohedral distortion.

Adiabatic Eigenfunction Based Approach to Coherent Transfer: Application to the Fenna-Matthews-Olson (FMO) Complex and the Role of Correlations in the Efficiency of Energy Transfer

We have recently suggested a method (Pallavi Bhattacharyya and K. L. Sebastian, Physical Review E 2013, 87, 062712) for the analysis of coherence in finite-level systems that are coupled to the surroundings and used it to study the process of energy transfer in the Fenna-Matthews-Olson (FMO) complex. The method makes use of adiabatic eigenstates of the Hamiltonian, with a subsequent transformation of the Hamiltonian into a form where the terms responsible for decoherence and population relaxation could be separated out at the lowest order. Thus one can account for decoherence nonperturbatively, and a Markovian type of master equation could be used for evaluating the population relaxation. In this paper, we apply this method to a two-level system as well as to a seven-level system. Comparisons with exact numerical results show that the method works quite well and is in good agreement with numerical calculations. The technique can be applied with ease to systems with larger numbers of levels as well. We also investigate how the presence of correlations among the bath degrees of freedom of the different bacteriochlorophyll a molecules of the FMO Complex affect the rate of energy transfer. Surprisingly, in the cases that we studied, our calculations suggest that the presence of anticorrelations, in contrast to correlations, make the excitation transfer more facile.

Balanced Excitatory and Inhibitory Synaptic Currents Promote Efficient Coding and Metabolic Efficiency

A balance between excitatory and inhibitory synaptic currents is thought to be important for several aspects of information processing in cortical neurons in vivo, including gain control, bandwidth and receptive field structure. These factors will affect the firing rate of cortical neurons and their reliability, with consequences for their information coding and energy consumption. Yet how balanced synaptic currents contribute to the coding efficiency and energy efficiency of cortical neurons remains unclear. We used single compartment computational models with stochastic voltage-gated ion channels to determine whether synaptic regimes that produce balanced excitatory and inhibitory currents have specific advantages over other input regimes. Specifically, we compared models with only excitatory synaptic inputs to those with equal excitatory and inhibitory conductances, and stronger inhibitory than excitatory conductances (i.e. approximately balanced synaptic currents). Using these models, we show that balanced synaptic currents evoke fewer spikes per second than excitatory inputs alone or equal excitatory and inhibitory conductances. However, spikes evoked by balanced synaptic inputs are more informative (bits/spike), so that spike trains evoked by all three regimes have similar information rates (bits/s). Consequently, because spikes dominate the energy consumption of our computational models, approximately balanced synaptic currents are also more energy efficient than other synaptic regimes. Thus, by producing fewer, more informative spikes approximately balanced synaptic currents in cortical neurons can promote both coding efficiency and energy efficiency.

Macromolecular Crystallography in India in the Global Context

The most spectacular applications of crystallography are currently concerned with biological macromolecules like proteins and their assemblies. Macromolecular crystallography originated in England in the thirties of the last century, but definitive results began to appear only around 1960. Since then macromolecular crystallography has grown to become central to modern biology. India has a long tradition in crystallography starting with the work of K. Banerjee in the thirties. In addition to their contributions to crystallography, G.N. Ramachandran and his colleagues gave a head start to India in computational biology, molecular modeling and what we now call bioinformatics. However, attempts to initiate macromolecular crystallography in India started only in the seventies. The work took off the ground after the Department of Science and Technology handsomely supported the group at Indian Institute of Science, Bangalore in 1983. The Bangalore group was also recognized as a national nucleus for the development of the area in the country. Since then macromolecular crystallography, practiced in more than 30 institutions in the country, has grown to become an important component of scientific research in India. The articles in this issue provide a flavor of activities in the area in the country. The area is still in an expanding phase and is poised to scale greater heights.

Efficiency limitations in a low band-gap diketopyrrolopyrrole-based polymer solar cell

We report the performance and photophysics of a low band-gap diketopyrrolopyrrole-based copolymer used in bulk heterojunction devices in combination with PC71BM. We show that the short lifetime of photogenerated excitons in the polymer constitutes an obstacle towards device efficiency by limiting the diffusion range of the exciton to the donor-acceptor heterojunction. We employ ultrafast transient-probe and fluorescence spectroscopy techniques to examine the excited state loss channels inside the devices. We use the high boiling point solvent additive 1,8-diiodooctane (DIO) to study the photoexcited state losses in different blend morphologies. The solvent additive acts as a compatibiliser between the donor and the acceptor material and leads to smaller domain sizes, higher charge formation yields and increased device efficiency.

Strategies for high efficiency and stability in biogas-fuelled small engines

This work assesses the performance of small biogas-fuelled engines and explores high-efficiency strategies for power generation in the very low power range of less than 1000 W. Experiments were performed on a small 95-cc, single-cylinder, four-stroke spark-ignition engine operating on biogas. The engine was operated in two modes, i.e., `premixed' and `fuel injection' modes, using both single and dual spark plug configurations. Measurements of in-cylinder pressure, crank angle, brake power, air and fuel flow rates, and exhaust emissions were conducted. Cycle-to-cycle variations in engine in-cylinder pressure and power were also studied and assessed quantitatively for various loading conditions. Results suggest that biogas combustion can be fairly sensitive to the ignition strategies thereby affecting the power output and efficiency. Further, results indicate that continuous fuel injection shows superior performance compared to the premixed case especially at low loads owing to possible charge stratification in the engine cylinder. Overall, this study has demonstrated for the first time that a combination of technologies such as lean burn, fuel injection, and dual spark plug ignition can provide highly efficient and stable operation in a biogas-fuelled small S.I. engine, especially in the low power range of 450-1000W. (C) 2014 Elsevier Inc. All rights reserved.

Consequences of Converting Graded to Action Potentials upon Neural Information Coding and Energy Efficiency

Information is encoded in neural circuits using both graded and action potentials, converting between them within single neurons and successive processing layers. This conversion is accompanied by information loss and a drop in energy efficiency. We investigate the biophysical causes of this loss of information and efficiency by comparing spiking neuron models, containing stochastic voltage-gated Na+ and K+ channels, with generator potential and graded potential models lacking voltage-gated Na+ channels. We identify three causes of information loss in the generator potential that are the by-product of action potential generation: (1) the voltage-gated Na+ channels necessary for action potential generation increase intrinsic noise and (2) introduce non-linearities, and (3) the finite duration of the action potential creates a `footprint' in the generator potential that obscures incoming signals. These three processes reduce information rates by similar to 50% in generator potentials, to similar to 3 times that of spike trains. Both generator potentials and graded potentials consume almost an order of magnitude less energy per second than spike trains. Because of the lower information rates of generator potentials they are substantially less energy efficient than graded potentials. However, both are an order of magnitude more efficient than spike trains due to the higher energy costs and low information content of spikes, emphasizing that there is a two-fold cost of converting analogue to digital; information loss and cost inflation.