Making sense of risk. Donor risk communication in families considering living liverdonation to a child

This paper contributes to the growing line of thought in bioethics that respect for autonomy should not be equated to the facilitation of individualistic self determination through standard requirements of informed consent in all healthcare contexts. The paper describes how in the context of donation for living related liver transplantation (LRLT) meaningful, responsible decision making is often embedded within family processes and its negotiation. We suggest that good donor risk communication in families promote “conscientious autonomy” and “reflective trust”. From this, the paper offers the suggestion that transplant teams and other relevant professionals have to broaden their role and responsibility for risk communication beyond proper disclosure by addressing the impact of varied psychosocial conditions on risk interpretation and assessment for potential donors and family stakeholders. In conclusion, we suggest further research questions on how professional responsibility and role-taking in risk communication should be morally understood

Confined conversion of CuS nanowires to CuO nanotubes by annealing-induced diffusion in nanochannels

Copper oxide (CuO) nanotubes were successfully converted from CuS nanowires embedded in anodic aluminum oxide (AAO) template by annealing-induced diffusion in a confined tube-type space. The spreading of CuO and formation of CuO layer on the nanochannel surface of AAO, and the confinement offered by AAO nanochannels play a key role in the formation of CuO nanotubes

Specific-heat study of superconducting and normal states in FeSe1-xTex (0.6<=x<=1) single crystals: Strong-coupling superconductivity, strong electron-correlation, and inhomogeneity

The electronic specific heat of as-grown and annealed single-crystals of FeSe1-xTex (0.6<=x<=1) has been investigated. It has been found that annealed single-crystals with x=0.6-0.9 exhibit bulk superconductivity with a clear specific-heat jump at the superconducting (SC) transition temperature, Tc. Both 2Delta_0/kBTc [Delta_0: the SC gap at 0 K estimated using the single-band BCS s-wave model] and Delta C/(gamma_n-gamma_0)Tc [Delta C$: the specific-heat jump at Tc, gamma_n: the electronic specific-heat coefficient in the normal state, gamma_0: the residual electronic specific-heat coefficient at 0 K in the SC state] are largest in the well-annealed single-crystal with x=0.7, i.e., 4.29 and 2.76, respectively, indicating that the superconductivity is of the strong coupling. The thermodynamic critical field has also been estimated. gamma_n has been found to be one order of magnitude larger than those estimated from the band calculations and increases with increasing x at x=0.6-0.9, which is surmised to be due to the increase in the electronic effective mass, namely, the enhancement of the electron correlation. It has been found that there remains a finite value of gamma_0 in the SC state even in the well-annealed single-crystals with x=0.8-0.9, suggesting an inhomogeneous electronic state in real space and/or momentum space.Comment: 22 pages, 1 table, 6 figures, Version 2 has been accepted for publication in J. Phys. Soc. Jp

Strategies used as spectroscopy of financial markets reveal new stylized facts

We propose a new set of stylized facts quantifying the structure of financial markets. The key idea is to study the combined structure of both investment strategies and prices in order to open a qualitatively new level of understanding of financial and economic markets. We study the detailed order flow on the Shenzhen Stock Exchange of China for the whole year of 2003. This enormous dataset allows us to compare (i) a closed national market (A-shares) with an international market (B-shares), (ii) individuals and institutions and (iii) real investors to random strategies with respect to timing that share otherwise all other characteristics. We find that more trading results in smaller net return due to trading frictions. We unveiled quantitative power laws with non-trivial exponents, that quantify the deterioration of performance with frequency and with holding period of the strategies used by investors. Random strategies are found to perform much better than real ones, both for winners and losers. Surprising large arbitrage opportunities exist, especially when using zero-intelligence strategies. This is a diagnostic of possible inefficiencies of these financial markets.Comment: 13 pages including 5 figures and 1 tabl

Plan de negocio para la importaci?n y comercializaci?n de bicicletas, repuestos y accesorios en el mercado peruano

En el desarrollo del presente plan de negocio se determin? que el negocio de importaci?n y comercializaci?n de bicicletas, accesorios y repuestos en el mercado peruano es viable y rentable, ya que el valor actual neto (VAN) resulta ser de $20,562 y la tasa interna de retorno (TIR) de 14.25%, el cual supera al WACC (costo promedio de capital). Para lograr este escenario favorable y viable del negocio la empresa BIKELIFE deber? ejecutar los planes: estrat?gico, marketing, operaciones, recursos humanos y TI detallados en la presente tesis, que servir?n para la implementaci?n y buen funcionamiento de la empresa. De la misma forma se desarroll? las partes de la cadena de abastecimiento de tal forma de optimizar las operaciones en costo y tiempo

From Nonspecific DNA–Protein Encounter Complexes to the Prediction of DNA–Protein Interactions

©2009 Gao, Skolnick. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.doi:10.1371/journal.pcbi.1000341DNA–protein interactions are involved in many essential biological activities. Because there is no simple mapping code between DNA base pairs and protein amino acids, the prediction of DNA–protein interactions is a challenging problem. Here, we present a novel computational approach for predicting DNA-binding protein residues and DNA–protein interaction modes without knowing its specific DNA target sequence. Given the structure of a DNA-binding protein, the method first generates an ensemble of complex structures obtained by rigid-body docking with a nonspecific canonical B-DNA. Representative models are subsequently selected through clustering and ranking by their DNA–protein interfacial energy. Analysis of these encounter complex models suggests that the recognition sites for specific DNA binding are usually favorable interaction sites for the nonspecific DNA probe and that nonspecific DNA–protein interaction modes exhibit some similarity to specific DNA–protein binding modes. Although the method requires as input the knowledge that the protein binds DNA, in benchmark tests, it achieves better performance in identifying DNA-binding sites than three previously established methods, which are based on sophisticated machine-learning techniques. We further apply our method to protein structures predicted through modeling and demonstrate that our method performs satisfactorily on protein models whose root-mean-square Ca deviation from native is up to 5 Å from their native structures. This study provides valuable structural insights into how a specific DNA-binding protein interacts with a nonspecific DNA sequence. The similarity between the specific DNA–protein interaction mode and nonspecific interaction modes may reflect an important sampling step in search of its specific DNA targets by a DNA-binding protein

Momentum-resolved superconducting gap in the bulk of Ba1−x_{1-x}Kx_{x}Fe2_2As2_2 from combined ARPES and μ\muSR measurements

Here we present a calculation of the temperature-dependent London penetration depth, $\lambda(T)$, in Ba$_{1-x}$K$_{x}$Fe$_2$As$_2$ (BKFA) on the basis of the electronic band structure [1,2] and momentum-dependent superconducting gap [3] extracted from angle-resolved photoemission spectroscopy (ARPES) data. The results are compared to the direct measurements of $\lambda(T)$ by muon spin rotation ($\mu$SR) [4]. The value of $\lambda(T=0)$, calculated with \emph{no} adjustable parameters, equals 270 nm, while the directly measured one is 320 nm; the temperature dependence $\lambda(T)$ is also easily reproduced. Such agreement between the two completely different approaches allows us to conclude that ARPES studies of BKFA are bulk-representative. Our review of the available experimental studies of the superconducting gap in the new iron-based superconductors in general allows us to state that all hole-doped of them bear two nearly isotropic gaps with coupling constants $2\Delta/k_{\rm B}T_{\rm c}=2.5\pm1.5$ and $7\pm2$

Computational prediction of neural progenitor cell fates

Understanding how stem and progenitor cells choose between alternative cell fates is a major challenge in developmental biology. Efforts to tackle this problem have been hampered by the scarcity of markers that can be used to predict cell division outcomes. Here we present a computational method, based on algorithmic information theory, to analyze dynamic features of living cells over time. Using this method, we asked whether rat retinal progenitor cells (RPCs) display characteristic phenotypes before undergoing mitosis that could foretell their fate. We predicted whether RPCs will undergo a self-renewing or terminal division with 99% accuracy, or whether they will produce two photoreceptors or another combination of offspring with 87% accuracy. Our implementation can segment, track and generate predictions for 40 cells simultaneously on a standard computer at 5 min per frame. This method could be used to isolate cell populations with specific developmental potential, enabling previously impossible investigations.The computational aspects of this work were supported by the Center for Subsurface Sensing and Imaging Systems (NSF Grant EEC-9986821), by the Rensselaer Polytechnic Institute and by the University of Wisconsin-Milwaukee. This work was supported by grants from the Canadian Institutes of Health Research and the Foundation Fighting Blindness – Canada (to M.C). M.C. is a CIHR New Investigator and a W.K. Stell Scholar of the Foundation Fighting Blindness – Canada

Exploring hypotheses of the actions of TGF-beta 1 in epidermal wound healing using a 3D computational multiscale model of the human epidermis

In vivo and in vitro studies give a paradoxical picture of the actions of the key regulatory factor TGF-beta 1 in epidermal wound healing with it stimulating migration of keratinocytes but also inhibiting their proliferation. To try to reconcile these into an easily visualized 3D model of wound healing amenable for experimentation by cell biologists, a multiscale model of the formation of a 3D skin epithelium was established with TGF-beta 1 literature-derived rule sets and equations embedded within it. At the cellular level, an agent-based bottom-up model that focuses on individual interacting units ( keratinocytes) was used. This was based on literature-derived rules governing keratinocyte behavior and keratinocyte/ECM interactions. The selection of these rule sets is described in detail in this paper. The agent-based model was then linked with a subcellular model of TGF-beta 1 production and its action on keratinocytes simulated with a complex pathway simulator. This multiscale model can be run at a cellular level only or at a combined cellular/subcellular level. It was then initially challenged ( by wounding) to investigate the behavior of keratinocytes in wound healing at the cellular level. To investigate the possible actions of TGF-beta 1, several hypotheses were then explored by deliberately manipulating some of these rule sets at subcellular levels. This exercise readily eliminated some hypotheses and identified a sequence of spatial-temporal actions of TGF-beta 1 for normal successful wound healing in an easy-to-follow 3D model. We suggest this multiscale model offers a valuable, easy-to-visualize aid to our understanding of the actions of this key regulator in wound healing, and provides a model that can now be used to explore pathologies of wound healing

Gap structure in the electron-doped Iron-Arsenide Superconductor Ba(Fe0.92Co0.08)2As2: low-temperature specific heat study

We report the field and temperature dependence of the low-temperature specific heat down to 400 mK and in magnetic fields up to 9 T of the electron-doped Ba(Fe0.92Co0.08)2As2 superconductor. Using the phonon specific heat obtained from pure BaFe2As2 we find the normal state Sommerfeld coefficient to be 18 mJ/mol.K^2 and a condensation energy of 1.27 J/mol. The temperature dependence of the electronic specific heat clearly indicate the presence of the low-energy excitations in the system. The magnetic field variation of field-induced specific heat cannot be described by single clean s- or d-wave models. Rather, the data require an anisotropic gap scenario which may or may not have nodes. We discuss the implications of these results.Comment: New Journal of Physics in press, 10 pages, 5 figure