Quasi-one dimensional electrical conductivity and thermoelectric power studies on a discotic liquid crystal

We have studied the electrical conductivity of well aligned samples of hexahexylthiotriphenylene (HHTT) in the pure as well as doped states. The dopant used was a small concentration (0.62 mole %) of the electron acceptor trinitrofluorenone (TNF). In the columnar phases, doping causes the AC(1 kHz) conductivity along the columnar axis (σ ||) to increase by a factor of 107 or more relative to that in undoped samples; σ || attains a value of 10-2S/m, which was the maximum measurable limit of our experimental set up. On the other hand, in the isotropic phase doping makes hardly any difference to the conductivity. The frequency dependence of the conductivity has been investigated. The DC conductivity of doped samples exhibits an enormous anisotropy, σ ||/σ⊥ ≥ 1010, which is 7 orders higher than that reported for any liquid crystalline system, and, to our knowledge, the largest observed in an organic conductor. We also report the first thermoelectric power studies on these 'molecular wires'. The sign of the thermoelectric power is in conformity with the expected nature of the charge carriers, namely, holes

Surface Crystallization in a Liquid AuSi Alloy

X-ray measurements reveal a crystalline monolayer at the surface of the eutectic liquid Au_{82}Si_{18}, at temperatures above the alloy's melting point. Surface-induced atomic layering, the hallmark of liquid metals, is also found below the crystalline monolayer. The layering depth, however, is threefold greater than that of all liquid metals studied to date. The crystallinity of the surface monolayer is notable, considering that AuSi does not form stable bulk crystalline phases at any concentration and temperature and that no crystalline surface phase has been detected thus far in any pure liquid metal or nondilute alloy. These results are discussed in relation to recently suggested models of amorphous alloys.Comment: 12 pages, 3 figures, published in Science (2006

Effects of being uninsured or underinsured and living in high poverty neighborhoods on colon cancer care and survival in California: historical cohort analysis, 1996—2011

Background: We examined the mediating effects of health insurance on poverty-colon cancer care and survival relationships and the moderating effects of poverty on health insurance-colon cancer care and survival relationships among women and men in California. Methods: We analyzed registry data for 3,291 women and 3,009 men diagnosed with colon cancer between 1996 and 2000 and followed until 2011 on lymph node investigation, stage at diagnosis, surgery, chemotherapy, wait times and survival. We obtained socioeconomic data for individual residences from the 2000 census to categorize the following neighborhoods: high poverty (30% or more poor), middle poverty (5-29% poor) and low poverty (less than 5% poor). Primary health insurers were Medicaid, Medicare, private or none. Results: Evidence of mediation was observed for women, but not for men. For women, the apparent effect of poverty disappeared in the presence of payer, and the effects of all forms of health insurance seemed strengthened. All were advantaged on 6-year survival compared to the uninsured: Medicaid (RR = 1.83), Medicare (RR = 1.92) and private (RR = 1.83). Evidence of moderation was also only observed for women. The effects of all forms of health insurance were stronger for women in low poverty neighborhoods: Medicaid (RR = 2.90), Medicare (RR = 2.91) and private (RR = 2.60). For men, only main effects of poverty and payers were observed, the advantaging effect of private insurance being largest. Across colon cancer care processes, Medicare seemed most instrumental for women, private payers for men. Conclusions: Health insurance substantially mediates the quality of colon cancer care and poverty seems to make the effects of being uninsured or underinsured even worse, especially among women in the United States. These findings are consistent with the theory that more facilitative social and economic capital is available in more affluent neighborhoods, where women with colon cancer may be better able to absorb the indirect and direct, but uncovered, costs of care

Soap Froths and Crystal Structures

We propose a physical mechanism to explain the crystal symmetries found in macromolecular and supramolecular micellar materials. We argue that the packing entropy of the hard micellar cores is frustrated by the entropic interaction of their brush-like coronas. The latter interaction is treated as a surface effect between neighboring Voronoi cells. The observed crystal structures correspond to the Kelvin and Weaire-Phelan minimal foams. We show that these structures are stable for reasonable areal entropy densities.Comment: 4 pages, RevTeX, 2 included eps figure

Interfaces in Diblocks: A Study of Miktoarm Star Copolymers

We study AB$_n$ miktoarm star block copolymers in the strong segregation limit, focussing on the role that the AB interface plays in determining the phase behavior. We develop an extension of the kinked-path approach which allows us to explore the energetic dependence on interfacial shape. We consider a one-parameter family of interfaces to study the columnar to lamellar transition in asymmetric stars. We compare with recent experimental results. We discuss the stability of the A15 lattice of sphere-like micelles in the context of interfacial energy minimization. We corroborate our theory by implementing a numerically exact self-consistent field theory to probe the phase diagram and the shape of the AB interface.Comment: 12 pages, 11 included figure

Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease

Identifying accurate biomarkers of cognitive decline is essential for advancing early diagnosis and prevention therapies in Alzheimer's disease. The Alzheimer's disease DREAM Challenge was designed as a computational crowdsourced project to benchmark the current state-of-the-art in predicting cognitive outcomes in Alzheimer's disease based on high dimensional, publicly available genetic and structural imaging data. This meta-analysis failed to identify a meaningful predictor developed from either data modality, suggesting that alternate approaches should be considered for prediction of cognitive performance

The properties and applications of single-molecule DNA sequencing

Single-molecule sequencing enables DNA or RNA to be sequenced directly from biological samples, making it well-suited for diagnostic and clinical applications. Here we review the properties and applications of this rapidly evolving and promising technology

Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis

Rheumatoid arthritis (RA) affects millions world-wide. While anti-TNF treatment is widely used to reduce disease progression, treatment fails in Bone-third of patients. No biomarker currently exists that identifies non-responders before treatment. A rigorous community-based assessment of the utility of SNP data for predicting anti-TNF treatment efficacy in RA patients was performed in the context of a DREAM Challenge (http://www.synapse.org/RA_Challenge). An open challenge framework enabled the comparative evaluation of predictions developed by 73 research groups using the most comprehensive available data and covering a wide range of state-of-the-art modelling methodologies. Despite a significant genetic heritability estimate of treatment non-response trait (h(2) = 0.18, P value = 0.02), no significant genetic contribution to prediction accuracy is observed. Results formally confirm the expectations of the rheumatology community that SNP information does not significantly improve predictive performance relative to standard clinical traits, thereby justifying a refocusing of future efforts on collection of other data

Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis

Correction: vol 7, 13205, 2016, doi:10.1038/ncomms13205Rheumatoid arthritis (RA) affects millions world-wide. While anti-TNF treatment is widely used to reduce disease progression, treatment fails in Bone-third of patients. No biomarker currently exists that identifies non-responders before treatment. A rigorous community-based assessment of the utility of SNP data for predicting anti-TNF treatment efficacy in RA patients was performed in the context of a DREAM Challenge (http://www.synapse.org/RA_Challenge). An open challenge framework enabled the comparative evaluation of predictions developed by 73 research groups using the most comprehensive available data and covering a wide range of state-of-the-art modelling methodologies. Despite a significant genetic heritability estimate of treatment non-response trait (h(2) = 0.18, P value = 0.02), no significant genetic contribution to prediction accuracy is observed. Results formally confirm the expectations of the rheumatology community that SNP information does not significantly improve predictive performance relative to standard clinical traits, thereby justifying a refocusing of future efforts on collection of other data.Peer reviewe