DNA Binding and Oxidative Cleavage Activity of Ternary (alpha-Lipoic Acid) Copper(II) Complex of Heterocyclic Base

Ternary copper(II) complex Cu(a-lipo)(phen)(Cl)](NO3) where a-lipo = a-lipoic acid, phen is N, N-donor heterocyclic base, 1,10-phenanthroline was synthesized, characterized, and its DNA binding and cleavage activity were studied. Binding interactions of the complex with calf thymus (CT) DNA has been investigated by emission, viscosity, and DNA melting studies. The complex shows efficient oxidative cleavage of SC-DNA in the presence of 3-mercaptopropionic acid involving hydroxyl radical species, and results of control experiments exhibit the inhibition of DNA cleavage in the presence of hydroxyl radical scavengers, viz. DMSO and KI.

Force and ATP hydrolysis dependent regulation of RecA nucleoprotein filament by single-stranded DNA binding protein

In Escherichia coli, the filament of RecA formed on single-stranded DNA (ssDNA) is essential for recombinational DNA repair. Although ssDNA-binding protein (SSB) plays a complicated role in RecA reactions in vivo, much of our understanding of the mechanism is based on RecA binding directly to ssDNA. Here we investigate the role of SSB in the regulation of RecA polymerization on ssDNA, based on the differential force responses of a single 576-nucleotide-long ssDNA associated with RecA and SSB. We find that SSB outcompetes higher concentrations of RecA, resulting in inhibition of RecA nucleation. In addition, we find that pre-formed RecA filaments de-polymerize at low force in an ATP hydrolysis- and SSB-dependent manner. At higher forces, re-polymerization takes place, which displaces SSB from ssDNA. These findings provide a physical picture of the competition between RecA and SSB under tension on the scale of the entire nucleoprotein SSB array, which have broad biological implications particularly with regard to competitive molecular binding.

An estimate of equilibrium sensitivity of global terrestrial carbon cycle using NCAR CCSM4

Increasing concentrations of atmospheric CO2 influence climate, terrestrial biosphere productivity and ecosystem carbon storage through its radiative, physiological and fertilization effects. In this paper, we quantify these effects for a doubling of CO2 using a low resolution configuration of the coupled model NCAR CCSM4. In contrast to previous coupled climate-carbon modeling studies, we focus on the near-equilibrium response of the terrestrial carbon cycle. For a doubling of CO2, the radiative effect on the physical climate system causes global mean surface air temperature to increase by 2.14 K, whereas the physiological and fertilization on the land biosphere effects cause a warming of 0.22 K, suggesting that these later effects increase global warming by about 10 % as found in many recent studies. The CO2-fertilization leads to total ecosystem carbon gain of 371 Gt-C (28 %) while the radiative effect causes a loss of 131 Gt-C (10 %) indicating that climate warming damps the fertilization-induced carbon uptake over land. Our model-based estimate for the maximum potential terrestrial carbon uptake resulting from a doubling of atmospheric CO2 concentration (285-570 ppm) is only 242 Gt-C. This highlights the limited storage capacity of the terrestrial carbon reservoir. We also find that the terrestrial carbon storage sensitivity to changes in CO2 and temperature have been estimated to be lower in previous transient simulations because of lags in the climate-carbon system. Our model simulations indicate that the time scale of terrestrial carbon cycle response is greater than 500 years for CO2-fertilization and about 200 years for temperature perturbations. We also find that dynamic changes in vegetation amplify the terrestrial carbon storage sensitivity relative to a static vegetation case: because of changes in tree cover, changes in total ecosystem carbon for CO2-direct and climate effects are amplified by 88 and 72 %, respectively, in simulations with dynamic vegetation when compared to static vegetation simulations.

Implications of Higgs boson to diphoton decay rate in the bilinear R-parity violating supersymmetric model

The Large Hadron Collider has recently discovered a Higgs-like particle having a mass around 125 GeVand also indicated that there is an enhancement in the Higgs to diphoton decay rate as compared to that in the standard model. We have studied implications of these discoveries in the bilinear R-parity violating supersymmetric model, whose main motivation is to explain the nonzero masses for neutrinos. The R-parity violating parameters in this model are epsilon and b(epsilon), and these parameters determine the scale of neutrino masses. If the enhancement in the Higgs to diphoton decay rate is true, then we have found epsilon greater than or similar to 0.01 GeV and b epsilon similar to 1 GeV2 in order to be compatible with the neutrino oscillation data. Also, in the above mentioned analysis, we can determine the soft masses of sleptons (m(L)) and CP-odd Higgs boson mass (mA). We have estimated that m(L) greater than or similar to 300 GeV and m(A) greater than or similar to 700 GeV. We have also commented on the allowed values of epsilon and b(epsilon), in case there is no enhancement in the Higgs to diphoton decay rate. Finally, we present a model to explain the smallness of epsilon and b(epsilon).

Stochastic analysis of epidemics on adaptive time varying networks

Many studies investigating the effect of human social connectivity structures (networks) and human behavioral adaptations on the spread of infectious diseases have assumed either a static connectivity structure or a network which adapts itself in response to the epidemic (adaptive networks). However, human social connections are inherently dynamic or time varying. Furthermore, the spread of many infectious diseases occur on a time scale comparable to the time scale of the evolving network structure. Here we aim to quantify the effect of human behavioral adaptations on the spread of asymptomatic infectious diseases on time varying networks. We perform a full stochastic analysis using a continuous time Markov chain approach for calculating the outbreak probability, mean epidemic duration, epidemic reemergence probability, etc. Additionally, we use mean-field theory for calculating epidemic thresholds. Theoretical predictions are verified using extensive simulations. Our studies have uncovered the existence of an ``adaptive threshold,'' i.e., when the ratio of susceptibility (or infectivity) rate to recovery rate is below the threshold value, adaptive behavior can prevent the epidemic. However, if it is above the threshold, no amount of behavioral adaptations can prevent the epidemic. Our analyses suggest that the interaction patterns of the infected population play a major role in sustaining the epidemic. Our results have implications on epidemic containment policies, as awareness campaigns and human behavioral responses can be effective only if the interaction levels of the infected populace are kept in check.

Science of geoengineering

Carbon dioxide emissions from the burning of coal, oil, and gas are increasing atmospheric carbon dioxide concentrations. These increased concentrations cause additional energy to be retained in Earth's climate system, thus increasing Earth's temperature. Various methods have been proposed to prevent this temperature increase either by reflecting to space sunlight that would otherwise warm Earth or by removing carbon dioxide from the atmosphere. Such intentional alteration of planetary-scale processes has been termed geoengineering. The first category of geoengineering method, solar geoengineering (also known as solar radiation management, or SRM), raises novel global-scale governance and environmental issues. Some SRM approaches are thought to be low in cost, so the scale of SRM deployment will likely depend primarily on considerations of risk. The second category of geoengineering method, carbon dioxide removal (CDR), raises issues related primarily to scale, cost, effectiveness, and local environmental consequences. The scale of CDR deployment will likely depend primarily on cost.

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.

Assessing resilience and state-transition models with historical records of cheatgrass Bromus tectorum invasion in North American sagebrush-steppe

1. Resilience-based approaches are increasingly being called upon to inform ecosystem management, particularly in arid and semi-arid regions. This requires management frameworks that can assess ecosystem dynamics, both within and between alternative states, at relevant time scales. 2. We analysed long-term vegetation records from two representative sites in the North American sagebrush-steppe ecosystem, spanning nine decades, to determine if empirical patterns were consistent with resilience theory, and to determine if cheatgrass Bromus tectorum invasion led to thresholds as currently envisioned by expert-based state-and-transition models (STM). These data span the entire history of cheatgrass invasion at these sites and provide a unique opportunity to assess the impacts of biotic invasion on ecosystem resilience. 3. We used univariate and multivariate statistical tools to identify unique plant communities and document the magnitude, frequency and directionality of community transitions through time. Community transitions were characterized by 37-47% dissimilarity in species composition, they were not evenly distributed through time, their frequency was not correlated with precipitation, and they could not be readily attributed to fire or grazing. Instead, at both sites, the majority of community transitions occurred within an 8-10year period of increasing cheatgrass density, became infrequent after cheatgrass density peaked, and thereafter transition frequency declined. 4. Greater cheatgrass density, replacement of native species and indication of asymmetry in community transitions suggest that thresholds may have been exceeded in response to cheatgrass invasion at one site (more arid), but not at the other site (less arid). Asymmetry in the direction of community transitions also identified communities that were at-risk' of cheatgrass invasion, as well as potential restoration pathways for recovery of pre-invasion states. 5. Synthesis and applications. These results illustrate the complexities associated with threshold identification, and indicate that criteria describing the frequency, magnitude, directionality and temporal scale of community transitions may provide greater insight into resilience theory and its application for ecosystem management. These criteria are likely to vary across biogeographic regions that are susceptible to cheatgrass invasion, and necessitate more in-depth assessments of thresholds and alternative states, than currently available.