Machine-learning of atomic-scale properties based on physical principles

We briefly summarize the kernel regression approach, as used recently in materials modelling, to fitting functions, particularly potential energy surfaces, and highlight how the linear algebra framework can be used to both predict and train from linear functionals of the potential energy, such as the total energy and atomic forces. We then give a detailed account of the Smooth Overlap of Atomic Positions (SOAP) representation and kernel, showing how it arises from an abstract representation of smooth atomic densities, and how it is related to several popular density-based representations of atomic structure. We also discuss recent generalisations that allow fine control of correlations between different atomic species, prediction and fitting of tensorial properties, and also how to construct structural kernels---applicable to comparing entire molecules or periodic systems---that go beyond an additive combination of local environments

The Production of Antibody by Invading B Cells Is Required for the Clearance of Rabies Virus from the Central Nervous System

Every year over 50,000 people die from rabies worldwide, primarily due to the poor availability of rabies vaccine in developing countries. However, even when vaccines are available, human deaths from rabies occur if exposure to the causative virus is not recognized and vaccination is not sought in time. This is because rabies virus immunity induced by the natural infection or current vaccines is generally not effective at removing disease-causing rabies virus from brain tissues. Our studies provide insight into why this is the case and how vaccination can be changed so that the immune response can clear the virus from brain tissues. We show that the type of immune response induced by a live-attenuated rabies virus vaccine may be the key. In animal models, live-attenuated rabies virus vaccines are effective at delivering the immune cells capable of clearing the virus into CNS tissues and promote recovery from a rabies virus infection that has spread to the brain while conventional vaccines based on killed rabies virus do not. The production of rabies-specific antibody by B cells that invade the CNS tissues is important for complete elimination of the virus. We hypothesize that similar mechanisms may promote rabies virus clearance from individuals who are diagnosed after the virus has reached, but not extensively spread, through the CNS

Myocardial ischemia with left ventricular outflow obstruction

We report an unusual case of a 32-year old man who was treated for a hypertrophic obstructive cardiomyopathy (HOCM) with a DDD pacing with short AV delay reduction in the past. Without prior notice the patient developed ventricular fibrillation and an invasive cardiac diagnostic was performed, which revealed a myocardial bridging around of the left anterior descending artery (LAD). We suspected ischemia that could be either related to LAD artery compression or perfusion abnormalities due to AV delay reduction with related to diastolic dysfunction

Physics, Astrophysics and Cosmology with Gravitational Waves

Gravitational wave detectors are already operating at interesting sensitivity levels, and they have an upgrade path that should result in secure detections by 2014. We review the physics of gravitational waves, how they interact with detectors (bars and interferometers), and how these detectors operate. We study the most likely sources of gravitational waves and review the data analysis methods that are used to extract their signals from detector noise. Then we consider the consequences of gravitational wave detections and observations for physics, astrophysics, and cosmology.Comment: 137 pages, 16 figures, Published version <http://www.livingreviews.org/lrr-2009-2

Performance of the CMS Cathode Strip Chambers with Cosmic Rays

The Cathode Strip Chambers (CSCs) constitute the primary muon tracking device in the CMS endcaps. Their performance has been evaluated using data taken during a cosmic ray run in fall 2008. Measured noise levels are low, with the number of noisy channels well below 1%. Coordinate resolution was measured for all types of chambers, and fall in the range 47 microns to 243 microns. The efficiencies for local charged track triggers, for hit and for segments reconstruction were measured, and are above 99%. The timing resolution per layer is approximately 5 ns

Systems Biology Modeling Reveals a Possible Mechanism of the Tumor Cell Death upon Oncogene Inactivation in EGFR Addicted Cancers

Despite many evidences supporting the concept of “oncogene addiction” and many hypotheses rationalizing it, there is still a lack of detailed understanding to the precise molecular mechanism underlying oncogene addiction. In this account, we developed a mathematic model of epidermal growth factor receptor (EGFR) associated signaling network, which involves EGFR-driving proliferation/pro-survival signaling pathways Ras/extracellular-signal-regulated kinase (ERK) and phosphoinositol-3 kinase (PI3K)/AKT, and pro-apoptotic signaling pathway apoptosis signal-regulating kinase 1 (ASK1)/p38. In the setting of sustained EGFR activation, the simulation results show a persistent high level of proliferation/pro-survival effectors phospho-ERK and phospho-AKT, and a basal level of pro-apoptotic effector phospho-p38. The potential of p38 activation (apoptotic potential) due to the elevated level of reactive oxygen species (ROS) is largely suppressed by the negative crosstalk between PI3K/AKT and ASK1/p38 pathways. Upon acute EGFR inactivation, the survival signals decay rapidly, followed by a fast increase of the apoptotic signal due to the release of apoptotic potential. Overall, our systems biology modeling together with experimental validations reveals that inhibition of survival signals and concomitant release of apoptotic potential jointly contribute to the tumor cell death following the inhibition of addicted oncogene in EGFR addicted cancers

TRPA1 is essential for the vascular response to environmental cold exposure

This work was supported by the British Heart Foundation and a Capacity Building Award in Integrative Mammalian Biology. It was also supported by Arthritis Research UK and XK is supported by a British Pharmacological Society AJ Clark studentship

Database-driven High-Throughput Calculations and Machine Learning Models for Materials Design

This paper reviews past and ongoing efforts in using high-throughput ab-inito calculations in combination with machine learning models for materials design. The primary focus is on bulk materials, i.e., materials with fixed, ordered, crystal structures, although the methods naturally extend into more complicated configurations. Efficient and robust computational methods, computational power, and reliable methods for automated database-driven high-throughput computation are combined to produce high-quality data sets. This data can be used to train machine learning models for predicting the stability of bulk materials and their properties. The underlying computational methods and the tools for automated calculations are discussed in some detail. Various machine learning models and, in particular, descriptors for general use in materials design are also covered.Comment: 19 pages, 2 figure

Multi-Level Targeting of the Phosphatidylinositol-3-Kinase Pathway in Non-Small Cell Lung Cancer Cells

Introduction: We assessed expression of p85 and p110a PI3K subunits in non-small cell lung cancer (NSCLC) specimens and the association with mTOR expression, and studied effects of targeting the PI3K/AKT/mTOR pathway in NSCLC cell lines. Methods: Using Automated Quantitative Analysis we quantified expression of PI3K subunits in two cohorts of 190 and 168 NSCLC specimens and correlated it with mTOR expression. We studied effects of two PI3K inhibitors, LY294002 and NVP-BKM120, alone and in combination with rapamycin in 6 NSCLC cell lines. We assessed activity of a dual PI3K/mTOR inhibitor