MELD score measured day 10 after orthotopic liver transplantation predicts death and re-transplantation within the first year

OBJECTIVE: The impact of early allograft dysfunction on the outcome after liver transplantation is yet to be established. We explored the independent predictive value of the Model for End-Stage Liver Disease (MELD) score measured in the post-transplant period on the risk of mortality or re-transplantation. MATERIAL AND METHODS: Retrospective cohort study on adults undergoing orthotopic deceased donor liver transplantation from 2004 to 2014. The MELD score was determined prior to transplantation and daily until 21 days after. The risk of mortality or re-transplantation within the first year was assessed according to quartiles of MELD using unadjusted and adjusted stepwise Cox regression analysis. RESULTS: We included 374 consecutive liver transplant recipients of whom 60 patients died or were re-transplanted. The pre-transplant MELD score was comparable between patients with good and poor outcome, but from day 1 the MELD score significantly diversified and was higher in the poor outcome group (MELD score quartile 4 versus quartile 1-3 at day 10: HR 5.1, 95% CI: 2.8-9.0). This association remained after adjustment for non-identical blood type, autoimmune liver disease and hepatocellular carcinoma (adjusted HR 5.3, 95% CI: 2.9-9.5 for MELD scores at day 10). The post-transplant MELD score was not associated with pre-transplant MELD score or the Eurotransplant donor risk index. CONCLUSION: Early determination of the MELD score as an indicator of early allograft dysfunction after liver transplantation was a strong independent predictor of mortality or re-transplantation and was not influenced by the quality of the donor, or preoperative recipient risk factors

Aspects of Discrete Breathers and New Directions

We describe results concerning the existence proofs of Discrete Breathers (DBs) in the two classes of dynamical systems with optical linear phonons and with acoustic linear phonons. A standard approach is by continuation of DBs from an anticontinuous limit. A new approach, which is purely variational, is presented. We also review some numerical results on intraband DBs in random nonlinear systems. Some non-conventional physical applications of DBs are suggested. One of them is understanding slow relaxation properties of glassy materials. Another one concerns energy focusing and transport in biomolecules by targeted energy transfer of DBs. A similar theory could be used for describing targeted charge transfer of nonlinear electrons (polarons) and, more generally, for targeted transfer of several excitations (e.g. Davydov soliton).Comment: to appear in the Proceedings of NATO Advanced Research Workshop "Nonlinearity and Disorder: Theory and Applications", Tashkent,Uzbekistan,October 1-6, 200

Kerr-CFT From Black-Hole Thermodynamics

We analyze the near-horizon limit of a general black hole with two commuting killing vector fields in the limit of zero temperature. We use black hole thermodynamics methods to relate asymptotic charges of the complete spacetime to those obtained in the near-horizon limit. We then show that some diffeomorphisms do alter asymptotic charges of the full spacetime, even though they are defined in the near horizon limit and, therefore, count black hole states. We show that these conditions are essentially the same as considered in the Kerr/CFT corresponcence. From the algebra constructed from these diffeomorphisms, one can extract its central charge and then obtain the black hole entropy by use of Cardy's formula.Comment: 19 pages, JHEP3, no figures. V2: References added, small typos fixe

Why do Particle Clouds Generate Electric Charges?

Grains in desert sandstorms spontaneously generate strong electrical charges; likewise volcanic dust plumes produce spectacular lightning displays. Charged particle clouds also cause devastating explosions in food, drug and coal processing industries. Despite the wide-ranging importance of granular charging in both nature and industry, even the simplest aspects of its causes remain elusive, because it is difficult to understand how inert grains in contact with little more than other inert grains can generate the large charges observed. Here, we present a simple yet predictive explanation for the charging of granular materials in collisional flows. We argue from very basic considerations that charge transfer can be expected in collisions of identical dielectric grains in the presence of an electric field, and we confirm the model's predictions using discrete-element simulations and a tabletop granular experiment

Applying the selective Cu electroplating technique to light-emitting diodes

[[abstract]]We successfully fabricated a predefined patterned copper (Cu) substrate for thin GaN light-emitting diodes without barriers by the selective electroplating technique. The contours of Cu bumps fabricated using different electroplating modes and parameters were measured. We observed that the average thickness diminished with increasing current density. The current density conditions to obtain the best upright structure in the process were 40 and 80 mA/cm2.[[notice]]補正完畢[[incitationindex]]SCI[[booktype]]紙本[[booktype]]電子

Trading-off Data Fit and Complexity in Training Gaussian Processes with Multiple Kernels

This is the author accepted manuscript. The final version is available from Springer Verlag via the DOI in this recordLOD 2019: Fifth International Conference on Machine Learning, Optimization, and Data Science, 10-13 September 2019, Siena, ItalyGaussian processes (GPs) belong to a class of probabilistic techniques that have been successfully used in different domains of machine learning and optimization. They are popular because they provide uncertainties in predictions, which sets them apart from other modelling methods providing only point predictions. The uncertainty is particularly useful for decision making as we can gauge how reliable a prediction is. One of the fundamental challenges in using GPs is that the efficacy of a model is conferred by selecting an appropriate kernel and the associated hyperparameter values for a given problem. Furthermore, the training of GPs, that is optimizing the hyperparameters using a data set is traditionally performed using a cost function that is a weighted sum of data fit and model complexity, and the underlying trade-off is completely ignored. Addressing these challenges and shortcomings, in this article, we propose the following automated training scheme. Firstly, we use a weighted product of multiple kernels with a view to relieve the users from choosing an appropriate kernel for the problem at hand without any domain specific knowledge. Secondly, for the first time, we modify GP training by using a multi-objective optimizer to tune the hyperparameters and weights of multiple kernels and extract an approximation of the complete trade-off front between data-fit and model complexity. We then propose to use a novel solution selection strategy based on mean standardized log loss (MSLL) to select a solution from the estimated trade-off front and finalise training of a GP model. The results on three data sets and comparison with the standard approach clearly show the potential benefit of the proposed approach of using multi-objective optimization with multiple kernels.Natural Environment Research Council (NERC

Limited effects of growth hormone replacement in patients with GH deficiency during long-term cure of acromegaly

The aim of this study was to assess the effects of replacement with recombinant human growth hormone (rhGH) in patients with GH deficiency (GHD) after treatment of acromegaly. Intervention study. Sixteen patients (8 men, age 56 years), treated for acromegaly by surgery and radiotherapy, with an insufficient GH response to insulin-induced hypoglycaemia, were treated with 1 year of rhGH replacement. Study parameters were assessed at baseline and after 1 year of rhGH replacement. Study parameters were cardiac function, body composition, bone mineral density (BMD), fasting lipids, glucose, bone turnover markers, and Quality of Life (QoL). During rhGH replacement IGF-I concentrations increased from −0.4 ± 0.7 to 1.0 ± 1.5 SD (P = 0.001), with a mean daily dose of 0.2 ± 0.1 mg in men and 0.3 ± 0.2 mg in women. Nonetheless, rhGH replacement did not alter cardiac function, lipid and glucose concentrations, body composition or QoL. Bone turnover markers (PINP and β crosslaps) levels increased (P = 0.005 and P = 0.021, respectively), paralleled by a small, but significant decrease in BMD of the hip. The beneficial effects of rhGH replacement in patients with GHD during cure from acromegaly are limited in this study