Enhanced Depth Imaging Optical Coherence Tomography of Optic Nerve Head Drusen: A Comparison of Cases with and without Visual Field Loss

PURPOSE: Enhanced depth imaging (EDI) spectral-domain optical coherence tomography (SD OCT) has been recognized as the most sensitive tool to diagnose optic nerve head drusen (ONHD). The relationship between OCT characteristics and visual loss has not been well documented. This study compares EDI SD OCT-determined morphologic characteristics of drusen in eyes with or without visual field (VF) defects. DESIGN: Descriptive study of patients attending the neuro-ophthalmology service of Moorfields Eye Hospital between January 2013 and October 2014. SUBJECTS: Patients with diagnosed ONHD and EDI SD OCT imaging of the optic nerve head. METHODS: Eyes with and without VF defects were compared with regard to retinal nerve fiber layer (RNFL) thickness, drusen morphology, size, extent, visibility on funduscopy, ultrasound, and fundus autofluorescence. MAIN OUTCOME MEASURES: Difference in OCT characteristics of ONHD between patients with or without VF defects. RESULTS: Of 38 patients, 69 eyes with ONHD were included. Thirty-three eyes had a normal VF with average mean deviation (MD) -0.96 (±1.2) dB and pattern standard deviation (PSD) 1.6 (±0.3) dB (group I), and 36 eyes had VF defects with MD -13.7 (±10.4) dB and PSD 7.2 (±3.6) dB (group II). Mean global RNFL thickness was 62 (±20.9) μm in the latter group and 99.0 (±12.9) μm in group I. In group I, the predominant drusen type was peripapillary drusen, of variable size. In group II, most eyes had confluent (P 500 μm; P < 0.003) drusen, and drusen were more commonly visible on funduscopy (P = 0.001), ultrasound (P = 0.013), and autofluorescence (P = 0.002). Differences between the 2 groups reached statistical significance in a clustered analysis. RNFL thinning and autofluorescence showed relative sparing of the temporal sector. Sixty-four percent of patients with a VF defect in 1 eye also had a VF defect in their fellow eye. CONCLUSIONS: Drusen size and drusen type as classified by OCT morphologic characteristics are significantly different in patients with or without VF defects. Confluent, large, and autofluorescent drusen were more commonly found in patients with VF defects. These findings may assist in clarifying how drusen give rise to visual loss, which is currently not known

Thermal Grease Evaluation for ATLAS Upgrade Micro-Strip Detector.

The ATLAS upgrade detector foreseen at the phase 2 upgrade of LHC requires a complete new inner detector using silicon pixel and strip detectors. For both technologies, a specific mechanical and thermal design is required. Such a design may use soft thermal interfaces such as grease between the various parts. One foreseeable use would be between the cooling pipe and the thermal block allowing the strip modules to be decoupled from the mechanical and cooling structure. This note describes the technique used and the results obtained when characterizing a few grease samples. The results have been compared with thermal FEA simulations. A thermal conductivity measurement for each sample could be extracted from the measurements, with a systematic uncertainty of less than 6%. Some samples were irradiated to the expected fluence at sLHC and their resulting thermal conductivity compared with the non-irradiated samples

Climate impacts of energy technologies depend on emissions timing

Energy technologies emit greenhouse gases with differing radiative efficiencies and atmospheric lifetimes. Standard practice for evaluating technologies, which uses the global warming potential (GWP) to compare the integrated radiative forcing of emitted gases over a fixed time horizon, does not acknowledge the importance of a changing background climate relative to climate change mitigation targets. Here we demonstrate that the GWP misvalues the impact of CH[subscript 4]-emitting technologies as mid-century approaches, and we propose a new class of metrics to evaluate technologies based on their time of use. The instantaneous climate impact (ICI) compares gases in an expected radiative forcing stabilization year, and the cumulative climate impact (CCI) compares their time-integrated radiative forcing up to a stabilization year. Using these dynamic metrics, we quantify the climate impacts of technologies and show that high-CH[subscript 4]-emitting energy sources become less advantageous over time. The impact of natural gas for transportation, with CH[subscript 4] leakage, exceeds that of gasoline within 1–2 decades for a commonly cited 3 W m[superscript −2] stabilization target. The impact of algae biodiesel overtakes that of corn ethanol within 2–3 decades, where algae co-products are used to produce biogas and corn co-products are used for animal feed. The proposed metrics capture the changing importance of CH[subscript 4] emissions as a climate threshold is approached, thereby addressing a major shortcoming of the GWP for technology evaluation.New England University Transportation Center (DOT Grant DTRT07-G-0001

Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline

From medical charts to national census, healthcare has traditionally operated under a paper-based paradigm. However, the past decade has marked a long and arduous transformation bringing healthcare into the digital age. Ranging from electronic health records, to digitized imaging and laboratory reports, to public health datasets, today, healthcare now generates an incredible amount of digital information. Such a wealth of data presents an exciting opportunity for integrated machine learning solutions to address problems across multiple facets of healthcare practice and administration. Unfortunately, the ability to derive accurate and informative insights requires more than the ability to execute machine learning models. Rather, a deeper understanding of the data on which the models are run is imperative for their success. While a significant effort has been undertaken to develop models able to process the volume of data obtained during the analysis of millions of digitalized patient records, it is important to remember that volume represents only one aspect of the data. In fact, drawing on data from an increasingly diverse set of sources, healthcare data presents an incredibly complex set of attributes that must be accounted for throughout the machine learning pipeline. This chapter focuses on highlighting such challenges, and is broken down into three distinct components, each representing a phase of the pipeline. We begin with attributes of the data accounted for during preprocessing, then move to considerations during model building, and end with challenges to the interpretation of model output. For each component, we present a discussion around data as it relates to the healthcare domain and offer insight into the challenges each may impose on the efficiency of machine learning techniques.Comment: Healthcare Informatics, Machine Learning, Knowledge Discovery: 20 Pages, 1 Figur

A statistical model that predicts the length from the left subclavian artery to the celiac axis; towards accurate intra aortic balloon sizing

<p>Abstract</p> <p>Background</p> <p>Ideally the length of the Intraaortic balloon membrane (22-27.5 cm) should match to the distance from the left subclavian artery (LSA) to the celiac axis (CA), (LSA - CA). By being able to estimate this distance, better guidance regarding IABP sizing could be recommended.</p> <p>Methods</p> <p>Internal aortic lengths and demographic values were collected from a series of 40 cadavers during autopsy. External somatometric measurements were also obtained.</p> <p>There were 23 males and 17 females. The mean age was 73.1+/-13.11 years, weight 56.75+/-12.51 kg and the height 166+/-9.81 cm.</p> <p>Results</p> <p>Multiple regression analysis revealed the following predictor variables (R2 > 0.70) for estimating the length from LSA to CA: height (standardized coefficient (SRC) = 0.37, p = 0.004), age (SRC = 0.35, p < 0.001), sex (SRC = 0.21, p = 0.088) and the distance from the jugular notch to trans-pyloric plane (SRC = 0.61, p < 0.001).</p> <p>Recommendations: If LSA-CA < 21.9 cm use 34 cc IABP & if LSA-CA > 26.3 cm use 50 cc IABP. However if LSA-CA = 21.9- 26.3 cm use 40 cc, but be aware that it could be "aortic length-balloon membrane length" mismatching.</p> <p>Conclusions</p> <p>Routinely, IABP size selection is being dictated by the patient's height. Inevitably, this leads to pitfalls. We reported a mathematical model of accurate intraaortic balloon sizing, which is easy to be applied and has a high predictive value.</p

Microbial community metabolic profiles in saturated constructed wetlands treating iohexol and ibuprofen

The aim of the present study was to elucidate the microbial community metabolic profiles in saturated constructed wetland (CW) mesocosms planted with five different wetland plant species fed with water individually spiked with 100 μg L-1 ibuprofen or iohexol. Community-level physiological profiling (CLPP) using Biolog Ecoplates was performed and coupled with the assessment of water quality parameters (water temperature, pH, DO and TOC, TN, NH4-N, PO4-P removal efficiency). The microbial community metabolic profiles (microbial acitivity, richness, and carbon source utilization), as well as the water quality parameters revelead similar trends among the control mesocosms and the mescocosms fed with water spiked with iohexol and ibuprofen. Significant differences were observed between the planted and unplanted mesocosms and between seasons (summer and winter) within each of the feeding lines (control, iohexol or ibuprofen). The microbial community metabolic profiles in the saturated CW were shaped by plant presence and plant species, while no impact of iohexol and ibuprofen presence was noticed at the 100 μg L-1. In addition, the microbial activity and richness were generally higher in planted mesocosms than in the unplanted systems in the summer. For the first time, a positive correlation between iohexol removal and the microbial community metabolic profiles (activity, richness and amines and amides utilization in summer, and carbohydrates utilization in winter) in the saturated mesocosms was observed. Biodegradation was a main driver for iohexol and ibuprofen removal. Putrescine utilization in the summer and D-cellobiose, D,L-alpha-glycerol phosphate in winter were linked with the metabolic processing of iohexol, while glycogen in summer and L-phenylalanine, Glycyl-L-glutamic acid in winter linked with the ibuprofen removal efficiency in the saturated CW

Description of an aerodynamic levitation apparatus with applications in Earth sciences

<p>Abstract</p> <p>Background</p> <p>In aerodynamic levitation, solids and liquids are floated in a vertical gas stream. In combination with CO₂-laser heating, containerless melting at high temperature of oxides and silicates is possible. We apply aerodynamic levitation to bulk rocks in preparation for microchemical analyses, and for evaporation and reduction experiments.</p> <p>Results</p> <p>Liquid silicate droplets (~2 mm) were maintained stable in levitation using a nozzle with a 0.8 mm bore and an opening angle of 60°. The gas flow was ~250 ml min^-1. Rock powders were melted and homogenized for microchemcial analyses. Laser melting produced chemically homogeneous glass spheres. Only highly (e.g. H₂O) and moderately volatile components (Na, K) were partially lost. The composition of evaporated materials was determined by directly combining levitation and inductively coupled plasma mass spectrometry. It is shown that the evaporated material is composed of Na > K >> Si. Levitation of metal oxide-rich material in a mixture of H₂and Ar resulted in the exsolution of liquid metal.</p> <p>Conclusions</p> <p>Levitation melting is a rapid technique or for the preparation of bulk rock powders for major, minor and trace element analysis. With exception of moderately volatile elements Na and K, bulk rock analyses can be performed with an uncertainty of ± 5% relative. The technique has great potential for the quantitative determination of evaporated materials from silicate melts. Reduction of oxides to metal is a means for the extraction and analysis of siderophile elements from silicates and can be used to better understand the origin of chondritic metal.</p