Entanglement Structure: Entanglement Partitioning in Multipartite Systems and Its Experimental Detection Using Optimizable Witnesses

Creating large-scale entanglement lies at the heart of many quantum information processing protocols and the investigation of fundamental physics. For multipartite quantum systems, it is crucial to identify not only the presence of entanglement but also its detailed structure. This is because in a generic experimental situation with sufficiently many subsystems involved, the production of so-called genuine multipartite entanglement remains a formidable challenge. Consequently, focusing exclusively on the identification of this strongest type of entanglement may result in an all or nothing situation where some inherently quantum aspects of the resource are overlooked. On the contrary, even if the system is not genuinely multipartite entangled, there may still be many-body entanglement present in the system. An identification of the entanglement structure may thus provide us with a hint about where imperfections in the setup may occur, as well as where we can identify groups of subsystems that can still exhibit strong quantum-information-processing capabilities. However, there is no known efficient methods to identify the underlying entanglement structure. Here, we propose two complementary families of witnesses for the identification of such structures. They are based on the detection of entanglement intactness and entanglement depth, each requires only the implementation of solely two local measurements. Our method is also robust against noises and other imperfections, as reflected by our experimental implementation of these tools to verify the entanglement structure of five different eight-photon entangled states. We demonstrate how their entanglement structure can be precisely and systematically inferred from the experimental data. In achieving this goal, we also illustrate how the same set of data can be classically postprocessed to learn the most about the measured system.Comment: 21 pages, 13 figure

Tacky Elastomers to Enable Tear-Resistant and Autonomous Self-Healing Semiconductor Composites

Mechanical failure of π-conjugated polymer thin films is unavoidable under cyclic loading conditions, due to intrinsic defects and poor resistance to crack propagation. Here, the first tear-resistant and room-temperature self-healable semiconducting composite is presented, consisting of conjugated polymers and butyl rubber elastomers. This new composite displays both a record-low elastic modulus

FOXA1 regulates androgen receptor variant activity in models of castrate-resistant prostate cancer

Retention of androgen receptor (AR) signalling in castrate-resistant prostate cancer (CRPC) highlights the requirement for the development of more effective AR targeting therapies. A key mechanism of resistance to anti-androgens is through expression of constitutively active AR variants (AR-Vs) that are refractory to next-generation therapies, including Enzalutamide and Abiraterone. By maintaining an androgenic gene signature, AR-Vs drive tumour survival and progression in castrate conditions. Critically, however, our understanding of the mechanics of AR-V-driven transcription is limited, particularly with respect to dependency on pioneer factor function. Here we show that depletion of FOXA1 in the CWR22Rv1 CRPC cell line abrogates the oncogenic potential of AR-Vs. Gene expression profiling reveals that approximately 41% of the AR-V transcriptome requires FOXA1 and that depletion of FOXA1 attenuates AR-V binding at a sub-set of analysed co-regulated genes. Interestingly, AR-V levels are elevated in cells depleted of FOXA1 as a consequence of attenuated negative feedback on the AR gene, but is insufficient to maintain cell growth as evidenced by marked anti-proliferative effects in FOXA1 knockdown cells. In all, our data suggests that AR-Vs are dependent on FOXA1 for sustaining a pro-proliferative gene signature and agents targeting FOXA1 may represent novel therapeutic options for CRPC patients

Type II seesaw mechanism for Higgs doublets and the scale of new physics

We elaborate on an earlier proposal by Ernest Ma of a type II seesaw mechanism for suppressing the vacuum expectation values of some Higgs doublets. We emphasize that, by nesting this form of seesaw mechanism into various other seesaw mechanisms, one may obtain light neutrino masses in such a way that the new-physics scale present in the seesaw mechanism - the masses of scalar gauge-SU(2) triplets, scalar SU(2) doublets, or right-handed neutrinos - does not need to be higher than a few 10 TeV. We also investigate other usages of the type II seesaw mechanism for Higgs doublets. For instance, the suppression of the vacuum expectation values of Higgs doublets may realize Froggatt-Nielsen suppression factors in some entries of the fermion mass matrices.Comment: 14 pages, no figures, some references and clarifications added, final version for Phys. Lett.

miRNA-135a promotes breast cancer cell migration and invasion by targeting HOXA10

<p>Abstract</p> <p>Background</p> <p>miRNAs are a group of small RNA molecules regulating target genes by inducing mRNA degradation or translational repression. Aberrant expression of miRNAs correlates with various cancers. Although miR-135a has been implicated in several other cancers, its role in breast cancer is unknown. <it>HOXA10 </it>however, is associated with multiple cancer types and was recently shown to induce p53 expression in breast cancer cells and reduce their invasive ability. Because <it>HOXA10 </it>is a confirmed miR-135a target in more than one tissue, we examined miR-135a levels in relation to breast cancer phenotypes to determine if miR-135a plays role in this cancer type.</p> <p>Methods</p> <p>Expression levels of miR-135a in tissues and cells were determined by poly (A)-RT PCR. The effect of miR-135a on proliferation was evaluated by CCK8 assay, cell migration and invasion were evaluated by transwell migration and invasion assays, and target protein expression was determined by western blotting. GFP and luciferase reporter plasmids were constructed to confirm the action of miR-135a on downstream target genes including <it>HOXA10</it>. Results are reported as means ± S.D. and differences were tested for significance using 2-sided Student"s t-test.</p> <p>Results</p> <p>Here we report that miR-135a was highly expressed in metastatic breast tumors. We found that the expression of miR-135a was required for the migration and invasion of breast cancer cells, but not their proliferation. <it>HOXA10</it>, which encodes a transcription factor required for embryonic development and is a metastasis suppressor in breast cancer, was shown to be a direct target of miR-135a in breast cancer cells. Our analysis showed that miR-135a suppressed the expression of <it>HOXA10 </it>both at the mRNA and protein level, and its ability to promote cellular migration and invasion was partially reversed by overexpression of <it>HOXA10</it>.</p> <p>Conclusions</p> <p>In summary, our results indicate that miR-135a is an onco-miRNA that can promote breast cancer cell migration and invasion. <it>HOXA10 </it>is a target gene for miR-135a in breast cancer cells and overexpression of <it>HOXA10 </it>can partially reverse the miR-135a invasive phenotype.</p

The role of Guanxi in green supply chain management in Asia's emerging economies: A conceptual framework

In recent decades, rapid industrial modernization and economic growth have brought substantial environmental problems such as air pollution, hazardous waste, and water pollution for the Asian Emerging Economies (AEE), in particular China, Taiwan, India, Malaysia, Indonesia, Thailand, and South Korea. These countries have started to adopt green supply chain management (GSCM) as a strategy to reduce the environmental impact. There are anecdotal evidences that the adoption of GSCM in this region is partly influenced by Guanxi – a cultural norm, which plays a significant role in relationship governance within supply chain activities among the AEE. Based on a systematic literature review, we develop a conceptual framework that characterizes the drivers and barriers for the adoption of GSCM practices, incorporating Guanxi as a moderator in the manufacturing sector of the AEE. The conceptual framework addresses the roles of two types of Guanxi in the adoption of GSCM: the relational Guanxi at individual level based on social exchange theory and the aggregated Guanxi at firm level derived from social capital theory. This recognition of Guanxi at two separate decision levels help companies better manage their relationships while they green their supply chains. Directions for future research and managerial implications are discussed accordingly