Sequence-Specific and Strand-Specific Cleavage In Oligodeoxyribonucleotides and DNA Containing 3'-Thiothymidine

Oligonucleotides containing a 3'-thiothymidine residue (T3's) at the cleavage site for the EcoRV restriction endonuclease (between the central T and A residues of the sequence GATATC) have been prepared on an automated DNA synthesizer using 5'-O-monomethoxytritylthymidine 3'-S-(2-cyanoethyl N,N-di-isopropylphosphorothioamidite). The self-complementary sequence GACGAT3'sATCGTC was completely resistant to cleavage by EcoRV, while the heteroduplex composed of 5'-TCTGAT3'sATCCTC and 5'-GAGGATATCAGA (duplex 4) was cleaved only in the unmodified strand (5'-GAGGATATCAGA). In contrast, strands containing a 3'-S-phosphorothiolate linkage could be chemically cleaved specifically at this site with Ag+. A T3's residue has also been incorporated in the (-) strand of double-stranded closed circular (RF IV) M13mp18 DNA at the cleavage site of a unique EcoRV recognition sequence by using 5'-pCGAGCTCGAT3'sATCGTAAT as a primer for polymerization on the template (+) strand of M13mp18 DNA. On treatment of this substrate with EcoRV, only one strand was cleaved to produce the RF II or nicked DNA. Taken in conjunction with the cleavage studies on the oligonucleotides, this result demonstrates that the 3'-S-phosphorothiolate linkage is resistant to scission by EcoRV. Additionally, the phosphorothiolate-containing strand of the M13mp18 DNA could be cleaved specifically at the point of modification using iodine in aqueous pyridine. The combination of enzymatic and chemical techniques provides, for the first time, a demonstrated method for the sequence-specific cleavage of either the (+) or (-) strand.

Picking up the Pieces: Self-Healing in reconfigurable networks

We consider the problem of self-healing in networks that are reconfigurable in the sense that they can change their topology during an attack. Our goal is to maintain connectivity in these networks, even in the presence of repeated adversarial node deletion, by carefully adding edges after each attack. We present a new algorithm, DASH, that provably ensures that: 1) the network stays connected even if an adversary deletes up to all nodes in the network; and 2) no node ever increases its degree by more than 2 log n, where n is the number of nodes initially in the network. DASH is fully distributed; adds new edges only among neighbors of deleted nodes; and has average latency and bandwidth costs that are at most logarithmic in n. DASH has these properties irrespective of the topology of the initial network, and is thus orthogonal and complementary to traditional topology- based approaches to defending against attack. We also prove lower-bounds showing that DASH is asymptotically optimal in terms of minimizing maximum degree increase over multiple attacks. Finally, we present empirical results on power-law graphs that show that DASH performs well in practice, and that it significantly outperforms naive algorithms in reducing maximum degree increase.

Edge-preserving self-healing: Keeping network backbones densely connected

Healing algorithms play a crucial part in distributed peer-to-peer networks where failures occur continuously and frequently. Whereas there are approaches for robustness that rely largely on built-in redundancy, we adopt a responsive approach that is more akin to that of biological networks e.g. the brain. The general goal of self-healing distributed graphs is to maintain certain network properties while recovering from failure quickly and making bounded alterations locally. Several self-healing algorithms have been suggested in the recent literature [IPDPS'08, PODC'08, PODC'09, PODC'11]; they heal various network properties while fulfilling competing requirements such as having low degree increase while maintaining connectivity, expansion and low stretch of the network. In this work, we augment the previous algorithms by adding the notion of edge-preserving self-healing which requires the healing algorithm to not delete any edges originally present or adversarialy inserted. This reflects the cost of adding additional edges but more importantly it immediately follows that edge preservation helps maintain any subgraph induced property that is monotonic, in particular important properties such as graph and subgraph densities. Density is an important network property and in certain distributed networks, maintaining it preserves high connectivity among certain subgraphs and backbones. We introduce a general model of self-healing, and introduce xheal+, an edge-preserving version of xheal[PODC'11]. © 2012 IEEE.

The forgiving tree: a self-healing distributed data structure

We consider the problem of self-healing in peer-to-peer networks that are under repeated attack by an omniscient adversary. We assume that the following process continues for up to n rounds where n is the total number of nodes initially in the network: the adversary deletesan arbitrary node from the network, then the network responds by quickly adding a small number of new edges.

We present a distributed data structure that ensures two key properties. First, the diameter of the network is never more than O(log Delta) times its original diameter, where Delta is the maximum degree of the network initially. We note that for many peer-to-peer systems, Delta is polylogarithmic, so the diameter increase would be a O(loglog n) multiplicative factor. Second, the degree of any node never increases by more than 3 over its original degree. Our data structure is fully distributed, has O(1) latency per round and requires each node to send and receive O(1) messages per round. The data structure requires an initial setup phase that has latency equal to the diameter of the original network, and requires, with high probability, each node v to send O(log n) messages along every edge incident to v. Our approach is orthogonal and complementary to traditional topology-based approaches to defending against attack.

Self-healing systems and virtual structures

Modern networks are large, highly complex and dynamic. Add to that the mobility of the agents comprising many of these networks. It is difficult or even impossible for such systems to be managed centrally in an efficient manner. It is imperative for such systems to attain a degree of self-management. Self-healing i.e. the capability of a system in a good state to recover to another good state in face of an attack, is desirable for such systems. In this paper, we discuss the self-healing model for dynamic reconfigurable systems. In this model, an omniscient adversary inserts or deletes nodes from a network and the algorithm responds by adding a limited number of edges in order to maintain invariants of the network. We look at some of the results in this model and argue for their applicability and further extensions of the results and the model. We also look at some of the techniques we have used in our earlier work, in particular, we look at the idea of maintaining virtual graphs mapped over the existing network and assert that this may be a useful technique to use in many problem domains.

Who accesses complementary therapies and why?: An evaluation of a cancer care service

Introduction

Advances in cancer diagnosis and treatment have resulted in longer survival, meaning patients are living with a chronic-type condition. Therefore the needs of such patients have changed placing greater emphasis on survivorship, such as impact on quality of life and sleep patterns. Evidence suggests complementary therapies positively impact not only on the cancer patient's quality of life but also on family members and friends.

Methodology

This service evaluation examines self-reported benefits following a course of complementary therapy offered by a local cancer charity.

Results

Analysis of self-reported sleep scores and perceived quality of life experiences confirmed a number of trends relating to the demographics of people accessing the complementary therapy service.

Conclusion

Results suggest the complementary therapies provided by Action Cancer significantly improved clients' quality of life. Based on these findings the authors make a number of recommendations in relation to the use of complementary therapies by cancer patients.