Three-Dimensional Spectral-Domain Optical Coherence Tomography Data Analysis for Glaucoma Detection

Purpose: To develop a new three-dimensional (3D) spectral-domain optical coherence tomography (SD-OCT) data analysis method using a machine learning technique based on variable-size super pixel segmentation that efficiently utilizes full 3D dataset to improve the discrimination between early glaucomatous and healthy eyes. Methods: 192 eyes of 96 subjects (44 healthy, 59 glaucoma suspect and 89 glaucomatous eyes) were scanned with SD-OCT. Each SD-OCT cube dataset was first converted into 2D feature map based on retinal nerve fiber layer (RNFL) segmentation and then divided into various number of super pixels. Unlike the conventional super pixel having a fixed number of points, this newly developed variable-size super pixel is defined as a cluster of homogeneous adjacent pixels with variable size, shape and number. Features of super pixel map were extracted and used as inputs to machine classifier (LogitBoost adaptive boosting) to automatically identify diseased eyes. For discriminating performance assessment, area under the curve (AUC) of the receiver operating characteristics of the machine classifier outputs were compared with the conventional circumpapillary RNFL (cpRNFL) thickness measurements. Results: The super pixel analysis showed statistically significantly higher AUC than the cpRNFL (0.855 vs. 0.707, respectively, p = 0.031, Jackknife test) when glaucoma suspects were discriminated from healthy, while no significant difference was found when confirmed glaucoma eyes were discriminated from healthy eyes. Conclusions: A novel 3D OCT analysis technique performed at least as well as the cpRNFL in glaucoma discrimination and even better at glaucoma suspect discrimination. This new method has the potential to improve early detection of glaucomatous damage. © 2013 Xu et al

Collaborative development of diffraction-limited beamline optical systems at US DOE light sources

An ongoing collaboration among four US Department of Energy (DOE) National Laboratories has demonstrated key technology prototypes and software modeling tools required for new high-coherent flux beamline optical systems. New free electron laser (FEL) and diffraction-limited storage ring (DLSR) light sources demand wavefront preservation from source to sample to achieve and maintain optimal performance. Fine wavefront control was achieved using a novel, roomtemperature cooled mirror system called REAL (resistive element adjustable length) that combines cooling with applied, spatially variable auxiliary heating. Single-grating shearing interferometry (also called Talbot interferometry) and Hartmann wavefront sensors were developed and used for optical characterization and alignment on several beamlines, across a range of photon energies. Demonstrations of non-invasive hard x-ray wavefront sensing were performed using a thin diamond single-crystal as a beamsplitter

Star Formation Rate Indicators in Wide-Field Infrared Survey Preliminary Release

With the goal of investigating the degree to which theMIR luminosity in theWidefield Infrared Survey Explorer (WISE) traces the SFR, we analyze 3.4, 4.6, 12 and 22 {\mu}m data in a sample of {\guillemotright} 140,000 star-forming galaxies or star-forming regions covering a wide range in metallicity 7.66 < 12 + log(O/H) < 9.46, with redshift z < 0.4. These star-forming galaxies or star-forming regions are selected by matching the WISE Preliminary Release Catalog with the star-forming galaxy Catalog in SDSS DR8 provided by JHU/MPA 1.We study the relationship between the luminosity at 3.4, 4.6, 12 and 22 {\mu}m from WISE and H\alpha luminosity in SDSS DR8. From these comparisons, we derive reference SFR indicators for use in our analysis. Linear correlations between SFR and the 3.4, 4.6, 12 and 22 {\mu}m luminosity are found, and calibrations of SFRs based on L(3.4), L(4.6), L(12) and L(22) are proposed. The calibrations hold for galaxies with verified spectral observations. The dispersion in the relation between 3.4, 4.6, 12 and 22 {\mu}m luminosity and SFR relates to the galaxy's properties, such as 4000 {\deg}A break and galaxy color.Comment: 10 pages, 3 figure

Patterns of primary care and mortality among patients with schizophrenia or diabetes: a cluster analysis approach to the retrospective study of healthcare utilization

Abstract Background Patients with schizophrenia have difficulty managing their medical healthcare needs, possibly resulting in delayed treatment and poor outcomes. We analyzed whether patients reduced primary care use over time, differentially by diagnosis with schizophrenia, diabetes, or both schizophrenia and diabetes. We also assessed whether such patterns of primary care use were a significant predictor of mortality over a 4-year period. Methods The Veterans Healthcare Administration (VA) is the largest integrated healthcare system in the United States. Administrative extracts of the VA's all-electronic medical records were studied. Patients over age 50 and diagnosed with schizophrenia in 2002 were age-matched 1:4 to diabetes patients. All patients were followed through 2005. Cluster analysis explored trajectories of primary care use. Proportional hazards regression modelled the impact of these primary care utilization trajectories on survival, controlling for demographic and clinical covariates. Results Patients comprised three diagnostic groups: diabetes only (n = 188,332), schizophrenia only (n = 40,109), and schizophrenia with diabetes (Scz-DM, n = 13,025). Cluster analysis revealed four distinct trajectories of primary care use: consistent over time, increasing over time, high and decreasing, low and decreasing. Patients with schizophrenia only were likely to have low-decreasing use (73% schizophrenia-only vs 54% Scz-DM vs 52% diabetes). Increasing use was least common among schizophrenia patients (4% vs 8% Scz-DM vs 7% diabetes) and was associated with improved survival. Low-decreasing primary care, compared to consistent use, was associated with shorter survival controlling for demographics and case-mix. The observational study was limited by reliance on administrative data. Conclusion Regular primary care and high levels of primary care were associated with better survival for patients with chronic illness, whether psychiatric or medical. For schizophrenia patients, with or without comorbid diabetes, primary care offers a survival benefit, suggesting that innovations in treatment retention targeting at-risk groups can offer significant promise of improving outcomes.http://deepblue.lib.umich.edu/bitstream/2027.42/78274/1/1472-6963-9-127.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78274/2/1472-6963-9-127.pdfPeer Reviewe

Enriching rare variants using family-specific linkage information

Genome-wide association studies have been successful in identifying common variants for common complex traits in recent years. However, common variants have generally failed to explain substantial proportions of the trait heritabilities. Rare variants, structural variations, and gene-gene and gene-environment interactions, among others, have been suggested as potential sources of the so-called missing heritability. With the advent of exome-wide and whole-genome next-generation sequencing technologies, finding rare variants in functionally important sites (e.g., protein-coding regions) becomes feasible. We investigate the role of linkage information to select families enriched for rare variants using the simulated Genetic Analysis Workshop 17 data. In each replicate of simulated phenotypes Q1 and Q2 on 697 subjects in 8 extended pedigrees, we select one pedigree with the largest family-specific LOD score. Across all 200 replications, we compare the probability that rare causal alleles will be carried in the selected pedigree versus a randomly chosen pedigree. One example of successful enrichment was exhibited for gene VEGFC. The causal variant had minor allele frequency of 0.0717% in the simulated unrelated individuals and explained about 0.1% of the phenotypic variance. However, it explained 7.9% of the phenotypic variance in the eight simulated pedigrees and 23.8% in the family that carried the minor allele. The carrier’s family was selected in all 200 replications. Thus our results show that family-specific linkage information is useful for selecting families for sequencing, thus ensuring that rare functional variants are segregating in the sequencing samples

Effect of Ti-doping on the framework Structure of Mesoporous silica

The Ti-doped mesoporous silica MCM-41 materials were synthesized under basic condition at room temperature. The characteristics of samples were investigated by using XRD, HREM, IR, and N-2 adsorption techniques. The results show that Ti ions can get into the Si frame work and lead to the vibration of Si-O-Ti bond, with the increase of Ti ion addition, the mesoporous silica framework structure can be disordered and finally deteriorated

Synthesis of ordered mesoporous aluminosilicate under a low surfactant/silica molar ratio condition

Ordered mesoporous aluminosilicate materials with atomic Si/Al ratios of 16 similar to 64 were synthesized at a very low molar ratio of surfactant/silica (0.12) by using aluminium chloride hexahydrate and TEOS as the sources of aluminium and silicon. The resulting materials were characterized by XRD, TEM, FTIR and nitrogen sorption. As the NaOH/Si molar ratio increases from 0.2 to 0.6, the products obtained change from hexagonal MCM-41 to cubic MCM-48. The quality of the product rapidly deteriorates as the aluminium content of the solid increases beyond a certain limit. XRD shows that the substitution of the silicon by the large aluminium atoms leads to the expansion of the unit cell

Study on the synthesis and mechanism of mesoporous silica with hexastyle structure

The mesoporous silica MCM-41 materials with hexastyle structure were synthesized under strongly acidic condition. The characteristics of samples were investigated by using XRD, N-2 adsorption, HREM, and SEM techniques. The results show that MCM-41 powder with hexastyle structure, which is wormlike in micrometer-scale, consists of thousands of mesoporous channels in nano-scale. The morphogenesis of hexastyle mesoporous silica is due to the accretion of surfactant micella combined with silica oligmers in the low concentration of TEOS

On Aggregation in Ensembles of Multilabel Classifiers

While a variety of ensemble methods for multilabel classification have been proposed in the literature, the question of how to aggregate the predictions of the individual members of the ensemble has received little attention so far. In this paper, we introduce a formal framework of ensemble multilabel classification, in which we distinguish two principal approaches: "predict then combine" (PTC), where the ensemble members first make loss minimizing predictions which are subsequently combined, and "combine then predict" (CTP), which first aggregates information such as marginal label probabilities from the individual ensemble members, and then derives a prediction from this aggregation. While both approaches generalize voting techniques commonly used for multilabel ensembles, they allow to explicitly take the target performance measure into account. Therefore, concrete instantiations of CTP and PTC can be tailored to concrete loss functions. Experimentally, we show that standard voting techniques are indeed outperformed by suitable instantiations of CTP and PTC, and provide some evidence that CTP performs well for decomposable loss functions, whereas PTC is the better choice for non-decomposable losses.Comment: 14 pages, 2 figure