A Facile Synthesis of Highly Stable Modified Carbon Nanotubes as Efficient Oxygen Reduction Reaction Catalysts

© 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim In this work a facile synthetic process for modified carbon nanotubes for ORR catalysis is described. X-ray photoemission spectroscopy (XPS) and Raman spectroscopy confirm the inclusion of surface carbonyl groups in these modified nanotubes. Via rotating disk electrode (RDE) experiments in an alkaline medium, the modified nanotubes were found to equal the activity of a Pt/C standard and exceed the stability of the platinum catalyst. Density functional theory (DFT) and scanning tunneling microscopy (STM) studies serve to provide theoretical and experimental electronic property information which explain the improved ORR activity seen by the modified nanotubes

A population scale analysis of rare SNCA variation in the UK Biobank

Parkinson's disease (PD) is a complex neurodegenerative disease with a variety of genetic and environmental factors contributing to disease. The SNCA gene encodes for the alpha-synuclein protein which plays a central role in PD, where aggregates of this protein are one of the pathological hallmarks of disease. Rare point mutations and copy number gains of the SNCA gene have been shown to cause autosomal dominant PD, and common DNA variants identified using Genome-Wide Association Studies (GWAS) are a moderate risk factor for PD. The UK Biobank is a large-scale population prospective study including ~500,000 individuals that has revolutionized human genetics. Here we assessed the frequency of SNCA variation in this cohort and identified 30 subjects carrying variants of interest including duplications (n = 6), deletions (n = 6) and large complex likely mosaic events (n = 18). No known pathogenic missense variants were identified. None of these subjects were reported to be a PD case, although it is possible that these individuals may develop PD at a later age, and whilst three had known prodromal features, these did not meet defined clinical criteria for being considered ‘prodromal’ cases. Seven of the 18 large complex carriers showed a history of blood based cancer. Overall, we identified copy number variants in the SNCA region in a large population based cohort without reported PD phenotype and symptoms. Putative mosaicism of the SNCA gene was identified, however, it is unclear whether it is associated with PD. These individuals are potential candidates for further investigation by performing SNCA RNA and protein expression studies, as well as promising clinical trial candidates to understand how duplication carriers potentially escape PD

Pretransplant assessment of human liver grafts by plasma lecithin: cholesterol acyltransferase (LCAT) activity in multiple organ donors.

In spite of the improved outcome of orthotopic liver transplantation (OLTx), primary graft nonfunction remains one of the life-threatening problems following OLTx. The purpose of this study was to evaluate plasma lecithin: cholesterol acyltransferase (LCAT) activity in multiple organ donors as a predictor of liver allograft viability prior to OLTx. Thirty-nine donors were studied during a 5-month period between April and August 1988. Allograft hepatectomy was performed using a rapid technique or its minor modification with hilar dissections, and the allografts were stored cold (4 degrees C) in University of Wisconsin (UW) solution. Early post-transplant allograft function was classified as good, fair, or poor, according to the highest SGOT, SGPT, and prothrombin time within 5 days following OLTx. Procurement records were reviewed to identify donor data, which included conventional liver function tests, duration of hospital stay, history of cardiac arrest, and graft ischemic time. Blood samples from the donors were drawn immediately prior to aortic crossclamp, and from these plasma LCAT activity was determined. Plasma LCAT activity of all donors was significantly lower than that of healthy controls (12.4 +/- 8.0 vs 39.2 +/- 13.3 micrograms/ml per hour, P less than 0.01). LCAT activity (16.4 +/- 8.3 micrograms/ml per hour) in donors of grafts with good function was significantly higher than that in those with fair (8.6 +/- 4.5 micrograms/ml per hour, P less than 0.01) or poor (7.3 +/- 2.4 micrograms/ml per hour, P less than 0.01) function.(ABSTRACT TRUNCATED AT 250 WORDS

Reasons for accepting or declining to participate in randomized clinical trials for cancer therapy

This paper reports on the reasons why patients agreed to or declined entry into randomized trials of cancer following discussions conducted by clinicians in both District General and University Hospitals. Two hundred and four patients completed a 16-item questionnaire following the consultation, of these 112 (55%) were women with breast cancer. Overall results showed that 147 (72.1%) patients accepted entry to a randomized clinical trial (RCT). The main reasons nominated for participating in a trial were that ‘others will benefit’ (23.1%) and ‘trust in the doctor’ (21.1%). One of the main reasons for declining trial entry was that patients were ‘worried about randomization’ (19.6%). There was a significantly higher acceptance rate for trials providing active treatment in every arm 98 (80.6%) compared with those trials with a no treatment arm 46 (60.5%), χ2test P = 0.003. The study outlines a number of factors that appear to influence a patient’s decision to accept or decline entry into an RCT of cancer therapy. An important factor is whether or not the trial offers active treatment in all arms of the study. Communication that promotes trust and confidence in the doctor is also a powerful motivating influence. © 2000 Cancer Research Campaig

Mechanical Systems with Symmetry, Variational Principles, and Integration Algorithms

This paper studies variational principles for mechanical systems with symmetry and their applications to integration algorithms. We recall some general features of how to reduce variational principles in the presence of a symmetry group along with general features of integration algorithms for mechanical systems. Then we describe some integration algorithms based directly on variational principles using a discretization technique of Veselov. The general idea for these variational integrators is to directly discretize Hamilton’s principle rather than the equations of motion in a way that preserves the original systems invariants, notably the symplectic form and, via a discrete version of Noether’s theorem, the momentum map. The resulting mechanical integrators are second-order accurate, implicit, symplectic-momentum algorithms. We apply these integrators to the rigid body and the double spherical pendulum to show that the techniques are competitive with existing integrators

Identification and prediction of Parkinson's disease subtypes and progression using machine learning in two cohorts.

The clinical manifestations of Parkinson's disease (PD) are characterized by heterogeneity in age at onset, disease duration, rate of progression, and the constellation of motor versus non-motor features. There is an unmet need for the characterization of distinct disease subtypes as well as improved, individualized predictions of the disease course. We used unsupervised and supervised machine learning methods on comprehensive, longitudinal clinical data from the Parkinson's Disease Progression Marker Initiative (n = 294 cases) to identify patient subtypes and to predict disease progression. The resulting models were validated in an independent, clinically well-characterized cohort from the Parkinson's Disease Biomarker Program (n = 263 cases). Our analysis distinguished three distinct disease subtypes with highly predictable progression rates, corresponding to slow, moderate, and fast disease progression. We achieved highly accurate projections of disease progression 5 years after initial diagnosis with an average area under the curve (AUC) of 0.92 (95% CI: 0.95 ± 0.01) for the slower progressing group (PDvec1), 0.87 ± 0.03 for moderate progressors, and 0.95 ± 0.02 for the fast-progressing group (PDvec3). We identified serum neurofilament light as a significant indicator of fast disease progression among other key biomarkers of interest. We replicated these findings in an independent cohort, released the analytical code, and developed models in an open science manner. Our data-driven study provides insights to deconstruct PD heterogeneity. This approach could have immediate implications for clinical trials by improving the detection of significant clinical outcomes. We anticipate that machine learning models will improve patient counseling, clinical trial design, and ultimately individualized patient care

Interacting Supernovae: Types IIn and Ibn

Supernovae (SNe) that show evidence of strong shock interaction between their ejecta and pre-existing, slower circumstellar material (CSM) constitute an interesting, diverse, and still poorly understood category of explosive transients. The chief reason that they are extremely interesting is because they tell us that in a subset of stellar deaths, the progenitor star may become wildly unstable in the years, decades, or centuries before explosion. This is something that has not been included in standard stellar evolution models, but may significantly change the end product and yield of that evolution, and complicates our attempts to map SNe to their progenitors. Another reason they are interesting is because CSM interaction is an efficient engine for making bright transients, allowing super-luminous transients to arise from normal SN explosion energies, and allowing transients of normal SN luminosities to arise from sub-energetic explosions or low radioactivity yield. CSM interaction shrouds the fast ejecta in bright shock emission, obscuring our normal view of the underlying explosion, and the radiation hydrodynamics of the interaction is challenging to model. The CSM interaction may also be highly non-spherical, perhaps linked to binary interaction in the progenitor system. In some cases, these complications make it difficult to definitively tell the difference between a core-collapse or thermonuclear explosion, or to discern between a non-terminal eruption, failed SN, or weak SN. Efforts to uncover the physical parameters of individual events and connections to possible progenitor stars make this a rapidly evolving topic that continues to challenge paradigms of stellar evolution.Comment: Final draft of a chapter in the "SN Handbook". Accepted. 25 pages, 3 fig

Persistent anthrax as a major driver of wildlife mortality in a tropical rainforest

Anthrax is a globally important animal disease and zoonosis. Despite this, our current knowledge of anthrax ecology is largely limited to arid ecosystems, where outbreaks are most commonly reported. Here we show that the dynamics of an anthrax-causing agent, Bacillus cereus biovar anthracis, in a tropical rainforest have severe consequences for local wildlife communities. Using data and samples collected over three decades, we show that rainforest anthrax is a persistent and widespread cause of death for a broad range of mammalian hosts. We predict that this pathogen will accelerate the decline and possibly result in the extirpation of local chimpanzee (Pan troglodytes verus) populations. We present the epidemiology of a cryptic pathogen and show that its presence has important implications for conservation