Synthesis and identification of a new class of (S)-2,6-diamino-4,5,6,7-tetrahydrobenzo[d]thiazole derivatives as potent antileukemic agents

Benzothiazoles are multitarget agents with broad spectrum of biological activity. Among the antitumor agents discovered in recent years, the identification of various 2-(4-aminophenyl) benzothiazoles as potent and selective antitumor drugs against different cancer cell lines has stimulated remarkable interest. Some of the benzothiazoles are known to induce cell cycle arrest, activation of caspases and interaction with DNA molecule. Based on these interesting properties of benzothiazoles and to obtain new biologically active agents, a series of novel 4,5,6,7-tetrahydrobenzo[d]thiazole derivatives 5(a-i) were synthesized and evaluated for their efficacy as antileukemic agents in human leukemia cells (K562 and Reh). The chemical structures of the synthesized compounds were confirmed by H-1 NMR, LCMS and IR analysis. The cytotoxicity of these compounds were determined using trypan blue exclusion, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) and lactate dehydrogenase (LDH) assays. Results showed that, these compounds mediate a significant cytotoxic response to cancer cell lines tested. We found that the compounds having electron withdrawing groups at different positions of the phenyl ring of the thiourea moiety displayed significant cytotoxic effect with IC50 value less than 60 mu M. To rationalize the role of electron withdrawing group in the induction of cytotoxicity, we have chosen molecule 5g (IC50 similar to 15 mu M) which is having chloro substitution at ortho and para positions. Flow cytometric analysis of annexin V-FITC/ propidium iodide (PI) double staining and DNA fragmentation suggest that 5g can induce apoptosis.

Worst inputs and a bound on the highest peak statistics of a class of non-linear systems

A method is developed by which the input leading to the highest possible response in an interval of time can be determined for a class of non-linear systems. The input, if deterministic, is constrained to have a known finite energy (or norm) in the interval under consideration. In the case of random inputs, the energy is constrained to have a known probability distribution function. The approach has applications when a system has to be put to maximum advantage by getting the largest possible output or when a system has to be designed to the highest maximum response with only the input energy or the energy distribution known. The method is also useful in arriving at a bound on the highest peak distribution of the response, when the excitation is a known random process.As an illustration the Duffing oscillator has been analysed and some numerical results have also been presented.

A new class of separators and planarity of chordal graphs

We introduce a new class of clique separators, called base sets, for chordal graphs. Base sets of a chordal graph closely reflect its structure. We show that the notion of base sets leads to structural characterizations of planar k-trees and planar chordal graphs. Using these characterizations, we develop linear time algorithms for recognizing planar k-trees and planar chordal graphs. These algorithms are extensions of the Lexicographic_Breadth_First_Search algorithm for recognizing chordal graphs and are much simpler than the general planarity checking algorithm. Further, we use the notion of base sets to prove the equivalence of hamiltonian 2-trees and maximal outerplanar graphs.

Optimal infinite-horizon feedback laws for a general class of constrained discrete-time systems: stability and moving-horizon approximations

Stability results are given for a class of feedback systems arising from the regulation of time-varying discrete-time systems using optimal infinite-horizon and moving-horizon feedback laws. The class is characterized by joint constraints on the state and the control, a general nonlinear cost function and nonlinear equations of motion possessing two special properties. It is shown that weak conditions on the cost function and the constraints are sufficient to guarantee uniform asymptotic stability of both the optimal infinite-horizon and movinghorizon feedback systems. The infinite-horizon cost associated with the moving-horizon feedback law approaches the optimal infinite-horizon cost as the moving horizon is extended.

Synthesis and Identification of a new class of antileukemic agents containing 2-(arylcarboxamide)-(S)-6-amino-4,5,6,7-tetrahydrobenzod]thiazole

Recently we have reported the effect of (S)-6-aryl urea/thiourea substituted-2-amino-4,5,6,7-tetrahydrobenzod]thiazole derivatives as potent anti-leukemic agents. To elucidate further the Structure Activity Relationship (SAR) studies on the anti-leukemic activity of (S)-2,6-diamino-4,5,6,7 tetrahydrobenzod]thiazole moiety, a series of 2-arlycarboxamide substituted-(S)-6-amino-4,5,6,7-tetrahydrobenzod]thiazole were designed, synthesized and evaluated for their anti-leukemic activity by trypan blue exclusion, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), lactate dehydrogenase (LDH) assays and cell cycle analysis. Results suggest that the position, number and bulkiness of the substituent on the phenyl ring of aryl carboxamide moiety at 2nd position of 6-amino-4,5,6,7-tetrhydrobenzod]thiazole play a key role in inhibiting the proliferation of leukemia cells. Compounds with ortho substitution showed poor activity and with meta and para substitution showed good activity. (C) 2010 Elsevier Masson SAS. All rights reserved.

A structural principle for a class of adaptive systems

A feature common to many adaptive systems for identification and control is the adjustment.of gain parameters in a manner ensuring the stability of the overall system. This paper puts forward a principle which assures such a result for arbitrary systems which are linear and time invariant except for the adjustable parameters. The principle only demands that a transfer function be positive real. This transfer function dependent on the structure of the system with respect to the parameters. Several examples from adaptive identification, control and observer schemes are given as illustrations of the conceptual simplification provided by the structural principle.

Risk Minimizing Option Pricing for a Class of Exotic Options in a Markov-Modulated Market

We address risk minimizing option pricing in a regime switching market where the floating interest rate depends on a finite state Markov process. The growth rate and the volatility of the stock also depend on the Markov process. Using the minimal martingale measure, we show that the locally risk minimizing prices for certain exotic options satisfy a system of Black-Scholes partial differential equations with appropriate boundary conditions. We find the corresponding hedging strategies and the residual risk. We develop suitable numerical methods to compute option prices.

A Flexible Class of Regenerating Codes for Distributed Storage

In the distributed storage setting introduced by Dimakis et al., B units of data are stored across n nodes in the network in such a way that the data can be recovered by connecting to any k nodes. Additionally one can repair a failed node by connecting to any d nodes while downloading at most beta units of data from each node. In this paper, we introduce a flexible framework in which the data can be recovered by connecting to any number of nodes as long as the total amount of data downloaded is at least B. Similarly, regeneration of a failed node is possible if the new node connects to the network using links whose individual capacity is bounded above by beta(max) and whose sum capacity equals or exceeds a predetermined parameter gamma. In this flexible setting, we obtain the cut-set lower bound on the repair bandwidth along with a constructive proof for the existence of codes meeting this bound for all values of the parameters. An explicit code construction is provided which is optimal in certain parameter regimes.

Inhibition of nuclear protein import by a monoclonal antibody against a novel class of nuclear pore proteins

Nuclear import of proteins is mediated by the nuclear pore complexes in the nuclear envelope and requires the presence of a nuclear localization signal (NLS) on the karyophilic protein. In this paper, we describe studies with a monoclonal antibody, Mab E2, which recognizes a class of nuclear pore proteins of 60-76 kDa with a common phosphorylated epitope on rat nuclear envelopes. The Mab Ea-reactive proteins fractionated with the relatively insoluble pore complex-containing component of the envelope and gave a finely punctate pattern of nuclear staining in immunofluorescence assays. The antibody did not bind to any cytosolic proteins. Mab E2 inhibited the interaction of a simian virus 40 large T antigen NLS peptide with a specific 60-kDa NLS-binding protein from rat nuclear envelopes in photoaffinity labeling experiments. The antibody blocked the nuclear import of NLS-albumin conjugates in an in vitro nuclear transport assay with digitonin-permeabilized cells, but did not affect passive diffusion of a small nonnuclear protein, lysozyme, across the pore. Mab E2 may inhibit protein transport by directly interacting with the 60-kDa NLS-binding protein, thereby blocking signal-mediated nuclear import across the nuclear pore complex. (C) 1994 Academic Press, Inc.

A single network adaptive critic (SNAC) architecture for optimal control synthesis for a class of nonlinear systems

Even though dynamic programming offers an optimal control solution in a state feedback form, the method is overwhelmed by computational and storage requirements. Approximate dynamic programming implemented with an Adaptive Critic (AC) neural network structure has evolved as a powerful alternative technique that obviates the need for excessive computations and storage requirements in solving optimal control problems. In this paper, an improvement to the AC architecture, called the �Single Network Adaptive Critic (SNAC)� is presented. This approach is applicable to a wide class of nonlinear systems where the optimal control (stationary) equation can be explicitly expressed in terms of the state and costate variables. The selection of this terminology is guided by the fact that it eliminates the use of one neural network (namely the action network) that is part of a typical dual network AC setup. As a consequence, the SNAC architecture offers three potential advantages: a simpler architecture, lesser computational load and elimination of the approximation error associated with the eliminated network. In order to demonstrate these benefits and the control synthesis technique using SNAC, two problems have been solved with the AC and SNAC approaches and their computational performances are compared. One of these problems is a real-life Micro-Electro-Mechanical-system (MEMS) problem, which demonstrates that the SNAC technique is applicable to complex engineering systems.

Adaptive optimal tuning of a general class of stable LTI systems with restricted inputs

The problem addressed is one of model reference adaptive control (MRAC) of asymptotically stable plants of unknown order with zeros located anywhere in the s-plane except at the origin. The reference model is also asymptotically stable and lacking zero(s) at s = 0. The control law is to be specified only in terms of the inputs to and outputs of the plant and the reference model. For inputs from a class of functions that approach a non-zero constant, the problem is formulated in an optimal control framework. By successive refinements of the sub-optimal laws proposed here, two schemes are finally design-ed. These schemes are characterized by boundedness, convergence and optimality. Simplicity and total time-domain implementation are the additional striking features. Simulations to demonstrate the efficacy of the control schemes are presented.

A note on a class of singular integro-differential equations

A simplified analysis is employed to handle a class of singular integro-differential equations for their solutions

Reduced Order Suboptimal Control Design for a Class of Nonlinear Distributed Parameter Systems Using POD and /spl thetas/-D Techniques

A new computational tool is presented in this paper for suboptimal control design of a class of nonlinear distributed parameter systems. First proper orthogonal decomposition based problem-oriented basis functions are designed, which are then used in a Galerkin projection to come up with a low-order lumped parameter approximation. Next, a suboptimal controller is designed using the emerging /spl thetas/-D technique for lumped parameter systems. This time domain sub-optimal control solution is then mapped back to the distributed domain using the same basis functions, which essentially leads to a closed form solution for the controller in a state feedback form. Numerical results for a real-life nonlinear temperature control problem indicate that the proposed method holds promise as a good suboptimal control design technique for distributed parameter systems.

An optimal dynamic inversion approach for controlling a class of one-dimensional nonlinear distributed parameter systems

Combining the principles of dynamic inversion and optimization theory, a new approach is presented for stable control of a class of one-dimensional nonlinear distributed parameter systems, assuming the availability a continuous actuator in the spatial domain. Unlike the existing approximate-then-design and design-then-approximate techniques, here there is no need of any approximation either of the system dynamics or of the resulting controller. Rather, the control synthesis approach is fairly straight-forward and simple. The controller formulation has more elegance because we can prove the convergence of the controller to its steady state value. To demonstrate the potential of the proposed technique, a real-life temperature control problem for a heat transfer application is solved. It has been demonstrated that a desired temperature profile can be achieved starting from any arbitrary initial temperature profile.