Thiol/disulphide exchange reaction: A key regulatory process in biological systems

Cysteine residues in proteins serve many important functions such as stabilizing and maintaining the three-dimensional conformation of many proteins(1), in enzyme catalysis, as a residue undergoing post-translational 2 and in the formation of DNA-binding modification domain of a class of transcriptional activators(3), It is also involved in biological redox coupling(4) and xenobiotic metabolism(5). Disulphide bonds formed by xenobiotic metabolism oxidation of cysteine residues have been used as a probe to study the structure/function relationships of proteins, Introducing novel disulphide bonds in proteins to increase their thermal stability and, therefore, the shelf life is an important goal of protein engineering(6,7), In addition, the thiol group of cysteine residue participates in a reaction termed as thiol/disulphide exchange reaction, the biological significance of this reaction being the theme of this review.

Non-Gaussianity and direction-dependent systematics in HST Key Project data

Two new statistics, namely Delta(chi 2) and Delta(chi), based on the extreme value theory, were derived by Gupta et al. We use these statistics to study the direction dependence in the HST Key Project data, which provides one of the most precise measurements of the Hubble constant. We also study the non-Gaussianity in this data set using these statistics. Our results for Delta(chi 2) show that the significance of direction-dependent systematics is restricted to well below the 1 sigma confidence limit; however, the presence of non-Gaussian features is subtle. On the other hand, the Delta(chi). statistic, which is more sensitive to direction dependence, shows direction dependence systematics to be at a slightly higher confidence level, and the presence of non-Gaussian features at a level similar to the Delta(chi 2) statistic.

Efficient Key Management and Distribution for MANET

Ad hoc networks are being used in applications ranging from disaster recovery to distributed collaborative entertainment applications. Ad hoc networks have become one of the most attractive solution for rapid deployment of interconnecting large number of mobile personal devices. The user community of mobile personal devices are demanding a variety of value added multimedia entertainment services. The popularity of peer group is increasing and one or some members of the peer group need to send data to some or all members of the peer group. The increasing demand for group oriented value added services is driving for efficient multicast service over ad hoc networks. Access control mechanisms need to be deployed to provide guarantee that the unauthorized users cannot access the multicast content. In this paper, we present a topology aware key management and distribution scheme for secure overlay multicast over MANET to address node mobility related issues for multicast key management. We use overlay approach for key distribution and our objective is to keep communication overhead low for key management and distribution. We also incorporate reliability using explicit acknowledgments with the key distribution scheme. Through simulations we show that the proposed key management scheme has low communication overhead for rekeying and improves the reliability of key distribution.

Evolutionary Algorithm for the Determination of Optimal Mode of Bioreactor Operation

Stirred tank bioreactors, employed in the production of a variety of biologically active chemicals, are often operated in batch, fed-batch, and continuous modes of operation. The optimal design of bioreactor is dependent on the kinetics of the biological process, as well as the performance criteria (yield, productivity, etc.) under consideration. In this paper, a general framework is proposed for addressing the two key issues related to the optimal design of a bioreactor, namely, (i) choice of the best operating mode and (ii) the corresponding flow rate trajectories. The optimal bioreactor design problem is formulated with initial conditions and inlet and outlet flow rate trajectories as decision variables to maximize more than one performance criteria (yield, productivity, etc.) as objective functions. A computational methodology based on genetic algorithm approach is developed to solve this challenging multiobjective optimization problem with multiple decision variables. The applicability of the algorithm is illustrated by solving two challenging problems from the bioreactor optimization literature.

Methods for Detecting Early Warnings of Critical Transitions in Time Series Illustrated Using Simulated Ecological Data

Many dynamical systems, including lakes, organisms, ocean circulation patterns, or financial markets, are now thought to have tipping points where critical transitions to a contrasting state can happen. Because critical transitions can occur unexpectedly and are difficult to manage, there is a need for methods that can be used to identify when a critical transition is approaching. Recent theory shows that we can identify the proximity of a system to a critical transition using a variety of so-called `early warning signals', and successful empirical examples suggest a potential for practical applicability. However, while the range of proposed methods for predicting critical transitions is rapidly expanding, opinions on their practical use differ widely, and there is no comparative study that tests the limitations of the different methods to identify approaching critical transitions using time-series data. Here, we summarize a range of currently available early warning methods and apply them to two simulated time series that are typical of systems undergoing a critical transition. In addition to a methodological guide, our work offers a practical toolbox that may be used in a wide range of fields to help detect early warning signals of critical transitions in time series data.

Mobile node authentication using key distribution scheme in wireless sensor networks

We consider the problem of secure communication in mobile Wireless Sensor Networks (WSNs). Achieving security in WSNs requires robust encryption and authentication standards among the sensor nodes. Severe resources constraints in typical Wireless Sensor nodes hinder them in achieving key agreements. It is proved from past studies that many notable key management schemes do not work well in sensor networks due to their limited capacities. The idea of key predistribution is not feasible considering the fact that the network could scale to millions. We prove a novel algorithm that provides robust and secure communication channel in WSNs. Our Double Encryption with Validation Time (DEV) using Key Management Protocol algorithm works on the basis of timed sessions within which a secure secret key remains valid. A mobile node is used to bootstrap and exchange secure keys among communicating pairs of nodes. Analysis and simulation results show that the performance of the DEV using Key Management Protocol Algorithm is better than the SEV scheme and other related work.

A generic variant of NIST’s KAS2 key agreement protocol

We propose a generic three-pass key agreement protocol that is based on a certain kind of trapdoor one-way function family. When specialized to the RSA setting, the generic protocol yields the so-called KAS2 scheme that has recently been standardized by NIST. On the other hand, when specialized to the discrete log setting, we obtain a new protocol which we call DH2. An interesting feature of DH2 is that parties can use different groups (e.g., different elliptic curves). The generic protocol also has a hybrid implementation, where one party has an RSA key pair and the other party has a discrete log key pair. The security of KAS2 and DH2 is analyzed in an appropriate modification of the extended Canetti-Krawczyk security model.

Application of a modified jogged-screw model for creep of titanium aluminides: evaluation of the key substructural parameters

A modification of the jogged-screw model has been adopted recently by the authors to explain observations of 1/2[110]-type jogged-screw dislocations in equiaxed Ti-48Al under creep conditions. The aim of this study has been to verify and validate the parameters and functional dependencies that have been assumed in this previous work. The original solution has been reformulated to take into account the finite length of the moving jog. This is a better approximation of the tall jog. The substructural model parameters have been further investigated in light of the Finite Length Moving Line (FLML) source approximation. The original model assumes that the critical jog height (beyond which the jog is not dragged) is inversely proportional to the applied stress. By accounting for the fact that there are three competing mechanisms (jog dragging, dipole dragging, dipole bypass) possible, we can arrive at a modified critical jog height. The critical jog height was found to be more strongly stress dependent than assumed previously. The original model assumes the jog spacing to be invariant over the stress range. However, dynamic simulation using a line tension model has shown that the jog spacing is inversely proportional to the applied stress. This has also been confirmed by TEM measurements of jog spacings over a range of stresses. Taylor's expression assumed previously to provide the dependence of dislocation density on the applied stress, has now been confirmed by actual dislocation density measurements. Combining all of these parameters and dependencies, derived both from experiment and theory, leads to an excellent prediction of creep rates and stress exponents. The further application of this model to other materials, and the important role of atomistic and dislocation dynamics simulations in its continued development is also discussed.

Robust formulations for clustering-based large-scale classification

Chebyshev-inequality-based convex relaxations of Chance-Constrained Programs (CCPs) are shown to be useful for learning classifiers on massive datasets. In particular, an algorithm that integrates efficient clustering procedures and CCP approaches for computing classifiers on large datasets is proposed. The key idea is to identify high density regions or clusters from individual class conditional densities and then use a CCP formulation to learn a classifier on the clusters. The CCP formulation ensures that most of the data points in a cluster are correctly classified by employing a Chebyshev-inequality-based convex relaxation. This relaxation is heavily dependent on the second-order statistics. However, this formulation and in general such relaxations that depend on the second-order moments are susceptible to moment estimation errors. One of the contributions of the paper is to propose several formulations that are robust to such errors. In particular a generic way of making such formulations robust to moment estimation errors is illustrated using two novel confidence sets. An important contribution is to show that when either of the confidence sets is employed, for the special case of a spherical normal distribution of clusters, the robust variant of the formulation can be posed as a second-order cone program. Empirical results show that the robust formulations achieve accuracies comparable to that with true moments, even when moment estimates are erroneous. Results also illustrate the benefits of employing the proposed methodology for robust classification of large-scale datasets.

On the secret key capacity of the harary graph PIN model

A pairwise independent network (PIN) model consists of pairwise secret keys (SKs) distributed among m terminals. The goal is to generate, through public communication among the terminals, a group SK that is information-theoretically secure from an eavesdropper. In this paper, we study the Harary graph PIN model, which has useful fault-tolerant properties. We derive the exact SK capacity for a regular Harary graph PIN model. Lower and upper bounds on the fault-tolerant SK capacity of the Harary graph PIN model are also derived.

Structural Integrity of the Greek Key Motif in beta gamma-Crystallins Is Vital for Central Eye Lens Transparency

Background: We highlight an unrecognized physiological role for the Greek key motif, an evolutionarily conserved super-secondary structural topology of the beta gamma-crystallins. These proteins constitute the bulk of the human eye lens, packed at very high concentrations in a compact, globular, short-range order, generating transparency. Congenital cataract (affecting 400,000 newborns yearly worldwide), associated with 54 mutations in beta gamma-crystallins, occurs in two major phenotypes nuclear cataract, which blocks the central visual axis, hampering the development of the growing eye and demanding earliest intervention, and the milder peripheral progressive cataract where surgery can wait. In order to understand this phenotypic dichotomy at the molecular level, we have studied the structural and aggregation features of representative mutations. Methods: Wild type and several representative mutant proteins were cloned, expressed and purified and their secondary and tertiary structural details, as well as structural stability, were compared in solution, using spectroscopy. Their tendencies to aggregate in vitro and in cellulo were also compared. In addition, we analyzed their structural differences by molecular modeling in silico. Results: Based on their properties, mutants are seen to fall into two classes. Mutants A36P, L45PL54P, R140X, and G165fs display lowered solubility and structural stability, expose several buried residues to the surface, aggregate in vitro and in cellulo, and disturb/distort the Greek key motif. And they are associated with nuclear cataract. In contrast, mutants P24T and R77S, associated with peripheral cataract, behave quite similar to the wild type molecule, and do not affect the Greek key topology. Conclusion: When a mutation distorts even one of the four Greek key motifs, the protein readily self-aggregates and precipitates, consistent with the phenotype of nuclear cataract, while mutations not affecting the motif display `native state aggregation', leading to peripheral cataract, thus offering a protein structural rationale for the cataract phenotypic dichotomy ``distort motif, lose central vision''.

Certificate-less on-demand public key management (CLPKM) for self-organized MANETs

In this paper, we have proposed a novel certificate-less on-demand public key management (CLPKM) protocol for self-organized MANETs. The protocol works on flat network architecture, and distinguishes between authentication layer and routing layer of the network. We put an upper limit on the length of verification route and use the end-to-end trust value of a route to evaluate its strength. The end-to-end trust value is used by the protocol to select the most trusted verification route for accomplishing public key verification. Also, the protocol uses MAC function instead of RSA certificates to perform public key verification. By doing this, the protocol saves considerable computation power, bandwidth and storage space. The saved storage space is utilized by the protocol to keep a number of pre-established routes in the network nodes, which helps in reducing the average verification delay of the protocol. Analysis and simulation results confirm the effectiveness of the proposed protocol.

Identification of key amino acid residues in the catalytic mechanism of diaminopropionate ammonialyase from Salmonella typhimurium

Diaminopropionate ammonialyase (DAPAL), a fold-typeII pyridoxal 5-phosphate-dependent enzyme, catalyzes the ,-elimination of diaminopropionate (DAP) to pyruvate and ammonia. DAPAL was able to utilize both d- and l-DAP as substrates with almost equal efficiency. Mutational analysis of functionally important residues such as Thr385, Asp125 and Asp194 was carried out to understand the mechanism by which the isomers are hydrolyzed. Further, the putative residues involved in the formation of disulfide bond Cys271 and Cys299 were also mutated. T385S, T385D sDAPAL were as active with dl-DAP as substrate as sDAPAL, whereas the later exhibited a threefold increase in catalytic efficiency with d-Ser as substrate. Further analysis of these mutants suggested that DAPAL might follow an anti-E-2 mechanism of catalysis that does not involve the formation of a quinonoid intermediate. Of the two mutants of Asp125, D125E showed complete loss of activity with d-DAP as substrate, whereas the reaction with l-DAP was not affected significantly, demonstrating that Asp125 was essential for abstraction of protons from the d-isomer. By contrast, mutational analysis of Asp194 showed that the residue may not be directly involved in proton abstraction from l-DAP. sDAPAL does not form a disulfide bond in solution, although the position of Cys299 and Cys271 in the modeled structure of sDAPAL favored the formation of a disulfide bond. Further, unlike eDAPAL, sDAPAL could be activated by monovalent cations. Mutation of the cysteine residues showed that Cys271 may be involved in coordinating the monovalent cation, as observed in the case of other fold-typeII enzymes.

Fault-tolerant secret key generation

Mobile nodes observing correlated data communicate using an insecure bidirectional switch to generate a secret key, which must remain concealed from the switch. We are interested in fault-tolerant secret key rates, i.e., the rates of secret key generated even if a subset of nodes drop out before the completion of the communication protocol. We formulate a new notion of fault-tolerant secret key capacity, and present an upper bound on it. This upper bound is shown to be tight when the random variables corresponding to the observations of nodes are exchangeable. Further, it is shown that one round of interaction achieves the fault-tolerant secret key capacity in this case. The upper bound is also tight for the case of a pairwise independent network model consisting of a complete graph, and can be attained by a noninteractive protocol.

Stable atmospheric methane in the 2000s: key-role of emissions from natural wetlands

Two atmospheric inversions (one fine-resolved and one process-discriminating) and a process-based model for land surface exchanges are brought together to analyse the variations of methane emissions from 1990 to 2009. A focus is put on the role of natural wetlands and on the years 2000-2006, a period of stable atmospheric concentrations. From 1990 to 2000, the top-down and bottom-up visions agree on the time-phasing of global total and wetland emission anomalies. The process-discriminating inversion indicates that wetlands dominate the time-variability of methane emissions (90% of the total variability). The contribution of tropical wetlands to the anomalies is found to be large, especially during the post-Pinatubo years (global negative anomalies with minima between -41 and -19 Tg yr(-1) in 1992) and during the alternate 1997-1998 El-Nino/1998-1999 La-Nina (maximal anomalies in tropical regions between +16 and +22 Tg yr(-1) for the inversions and anomalies due to tropical wetlands between +12 and +17 Tg yr(-1) for the process-based model). Between 2000 and 2006, during the stagnation of methane concentrations in the atmosphere, the top-down and bottom-up approaches agree on the fact that South America is the main region contributing to anomalies in natural wetland emissions, but they disagree on the sign and magnitude of the flux trend in the Amazon basin. A negative trend (-3.9 +/- 1.3 Tg yr(-1)) is inferred by the process-discriminating inversion whereas a positive trend (+1.3 +/- 0.3 Tg yr(-1)) is found by the process model. Although processed-based models have their own caveats and may not take into account all processes, the positive trend found by the B-U approach is considered more likely because it is a robust feature of the process-based model, consistent with analysed precipitations and the satellite-derived extent of inundated areas. On the contrary, the surface-data based inversions lack constraints for South America. This result suggests the need for a re-interpretation of the large increase found in anthropogenic methane inventories after 2000.