Quantum Data Hiding

We expand on our work on Quantum Data Hiding -- hiding classical data among parties who are restricted to performing only local quantum operations and classical communication (LOCC). We review our scheme that hides one bit between two parties using Bell states, and we derive upper and lower bounds on the secrecy of the hiding scheme. We provide an explicit bound showing that multiple bits can be hidden bitwise with our scheme. We give a preparation of the hiding states as an efficient quantum computation that uses at most one ebit of entanglement. A candidate data hiding scheme that does not use entanglement is presented. We show how our scheme for quantum data hiding can be used in a conditionally secure quantum bit commitment scheme.Comment: 19 pages, IEEE style, 8 figures, submitted to IEEE Transactions on Information Theor

Locking classical correlation in quantum states

We show that there exist bipartite quantum states which contain large hidden classical correlation that can be unlocked by a disproportionately small amount of classical communication. In particular, there are $(2n+1)$-qubit states for which a one bit message doubles the optimal classical mutual information between measurement results on the subsystems, from $n/2$ bits to $n$ bits. States exhibiting this behavior need not be entangled. We study the range of states exhibiting this phenomenon and bound its magnitude.Comment: 7 pages, revtex

Quantum authentication with unitary coding sets

A general class of authentication schemes for arbitrary quantum messages is proposed. The class is based on the use of sets of unitary quantum operations in both transmission and reception, and on appending a quantum tag to the quantum message used in transmission. The previous secret between partners required for any authentication is a classical key. We obtain the minimal requirements on the unitary operations that lead to a probability of failure of the scheme less than one. This failure may be caused by someone performing a unitary operation on the message in the channel between the communicating partners, or by a potential forger impersonating the transmitter.Comment: RevTeX4, 10 page

Root induction in radiata pine using Agrobacterium rhizogenes

Root induction using Agrobacterium rhizogenes was conducted in hypocotyl explants, intact seedlings, de-rooted seedling cuttings and adventitious shoots of radiata pine ( Pinus radiata D. Don). Use of two A. rhizogenes strains (A4T and LB9402), with or without application of IBA, can trigger root formation in different explants. Strain LBA9402 was more effective than A4T in increasing rooting percentage and root number. Addition of 4.4 uMIBA to the medium further enhanced rooting from the cultured hypocotyl segments inoculated with the two A. rhizogenes strains. Strain LBA9402+IBA induced in about 75% of the cultured hypocotyl segments to form roots. In contrast the controls failed to initiate roots on intact seedlings or cultured segments in presence or absence of IBA. Rooting of adventitious shoots from 3 year-old radiata pine was improved following inoculation with LBA9402, suggesting that this rooting treatment has potential to aid clonal propagation of radiata pine

Ebola virus VP35 interaction with dynein LC8 regulates viral RNA synthesis

Ebola virus VP35 inhibits alpha/beta interferon production and functions as a viral polymerase cofactor. Previously, the 8-kDa cytoplasmic dynein light chain (LC8) was demonstrated to interact with VP35, but the functional consequences were unclear. Here we demonstrate that the interaction is direct and of high affinity and that binding stabilizes the VP35 N-terminal oligomerization domain and enhances viral RNA synthesis. Mutational analysis demonstrates that VP35 interaction is required for the functional effects of LC8

Development and evaluation of a high-throughput, low-cost genotyping platform based on oligonucleotide microarrays in rice

<p>Abstract</p> <p>Background</p> <p>We report the development of a microarray platform for rapid and cost-effective genetic mapping, and its evaluation using rice as a model. In contrast to methods employing whole-genome tiling microarrays for genotyping, our method is based on low-cost spotted microarray production, focusing only on known polymorphic features.</p> <p>Results</p> <p>We have produced a genotyping microarray for rice, comprising 880 single feature polymorphism (SFP) elements derived from insertions/deletions identified by aligning genomic sequences of the <it>japonica </it>cultivar Nipponbare and the <it>indica </it>cultivar 93-11. The SFPs were experimentally verified by hybridization with labeled genomic DNA prepared from the two cultivars. Using the genotyping microarrays, we found high levels of polymorphism across diverse rice accessions, and were able to classify all five subpopulations of rice with high bootstrap support. The microarrays were used for mapping of a gene conferring resistance to <it>Magnaporthe grisea</it>, the causative organism of rice blast disease, by quantitative genotyping of samples from a recombinant inbred line population pooled by phenotype.</p> <p>Conclusion</p> <p>We anticipate this microarray-based genotyping platform, based on its low cost-per-sample, to be particularly useful in applications requiring whole-genome molecular marker coverage across large numbers of individuals.</p

Principles of precision medicine in stroke

The era of precision medicine has arrived and conveys tremendous potential, particularly for stroke neurology. The diagnosis of stroke, its underlying aetiology, theranostic strategies, recurrence risk and path to recovery are populated by a series of highly individualised questions. Moreover, the phenotypic complexity of a clinical diagnosis of stroke makes a simple genetic risk assessment only partially informative on an individual basis. The guiding principles of precision medicine in stroke underscore the need to identify, value, organise and analyse the multitude of variables obtained from each individual to generate a precise approach to optimise cerebrovascular health. Existing data may be leveraged with novel technologies, informatics and practical clinical paradigms to apply these principles in stroke and realise the promise of precision medicine. Importantly, precision medicine in stroke will only be realised once efforts to collect, value and synthesise the wealth of data collected in clinical trials and routine care starts. Stroke theranostics, the ultimate vision of synchronising tailored therapeutic strategies based on specific diagnostic data, demand cerebrovascular expertise on big data approaches to clinically relevant paradigms. This review considers such challenges and delineates the principles on a roadmap for rational application of precision medicine to stroke and cerebrovascular health