529 research outputs found

    Septic Pulmonary Embolism Requiring Critical Care: Clinicoradiological Spectrum, Causative Pathogens and Outcomes

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    OBJECTIVES: Septic pulmonary embolism is an uncommon but life-threatening disorder. However, data on patients with septic pulmonary embolism who require critical care have not been well reported. This study elucidated the clinicoradiological spectrum, causative pathogens and outcomes of septic pulmonary embolism in patients requiring critical care. METHODS: The electronic medical records of 20 patients with septic pulmonary embolism who required intensive care unit admission between January 2005 and December 2013 were reviewed. RESULTS: Multiple organ dysfunction syndrome developed in 85% of the patients, and acute respiratory failure was the most common organ failure (75%). The most common computed tomographic findings included a feeding vessel sign (90%), peripheral nodules without cavities (80%) or with cavities (65%), and peripheral wedge-shaped opacities (75%). The most common primary source of infection was liver abscess (40%), followed by pneumonia (25%). The two most frequent causative pathogens were Klebsiella pneumoniae (50%) and Staphylococcus aureus (35%). Compared with survivors, nonsurvivors had significantly higher serum creatinine, arterial partial pressure of carbon dioxide, and Acute Physiology and Chronic Health Evaluation II and Sequential Organ Failure Assessment scores, and they were significantly more likely to have acute kidney injury, disseminated intravascular coagulation and lung abscesses. The in-hospital mortality rate was 30%. Pneumonia was the most common cause of death, followed by liver abscess. CONCLUSIONS: Patients with septic pulmonary embolism who require critical care, especially those with pneumonia and liver abscess, are associated with high mortality. Early diagnosis, appropriate antibiotic therapy, surgical intervention and respiratory support are essential

    Identification of Biomarkers for Esophageal Squamous Cell Carcinoma Using Feature Selection and Decision Tree Methods

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    Esophageal squamous cell cancer (ESCC) is one of the most common fatal human cancers. The identification of biomarkers for early detection could be a promising strategy to decrease mortality. Previous studies utilized microarray techniques to identify more than one hundred genes; however, it is desirable to identify a small set of biomarkers for clinical use. This study proposes a sequential forward feature selection algorithm to design decision tree models for discriminating ESCC from normal tissues. Two potential biomarkers of RUVBL1 and CNIH were identified and validated based on two public available microarray datasets. To test the discrimination ability of the two biomarkers, 17 pairs of expression profiles of ESCC and normal tissues from Taiwanese male patients were measured by using microarray techniques. The classification accuracies of the two biomarkers in all three datasets were higher than 90%. Interpretable decision tree models were constructed to analyze expression patterns of the two biomarkers. RUVBL1 was consistently overexpressed in all three datasets, although we found inconsistent CNIH expression possibly affected by the diverse major risk factors for ESCC across different areas

    MLPerf Inference Benchmark

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    Machine-learning (ML) hardware and software system demand is burgeoning. Driven by ML applications, the number of different ML inference systems has exploded. Over 100 organizations are building ML inference chips, and the systems that incorporate existing models span at least three orders of magnitude in power consumption and five orders of magnitude in performance; they range from embedded devices to data-center solutions. Fueling the hardware are a dozen or more software frameworks and libraries. The myriad combinations of ML hardware and ML software make assessing ML-system performance in an architecture-neutral, representative, and reproducible manner challenging. There is a clear need for industry-wide standard ML benchmarking and evaluation criteria. MLPerf Inference answers that call. In this paper, we present our benchmarking method for evaluating ML inference systems. Driven by more than 30 organizations as well as more than 200 ML engineers and practitioners, MLPerf prescribes a set of rules and best practices to ensure comparability across systems with wildly differing architectures. The first call for submissions garnered more than 600 reproducible inference-performance measurements from 14 organizations, representing over 30 systems that showcase a wide range of capabilities. The submissions attest to the benchmark's flexibility and adaptability.Comment: ISCA 202

    LAMOST Experiment for Galactic Understanding and Exploration (LEGUE) The survey science plan

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    We describe the current plans for a spectroscopic survey of millions of stars in the Milky Way galaxy using the Guo Shou Jing Telescope (GSJT, formerly the Large Area Multi-Object Spectroscopic Telescope - LAMOST). The survey will obtain spectra for 2.5 million stars brighter than r<19r<19 during dark/grey time, and 5 million stars brighter than r<17r<17 or J<16J<16 on nights that are moonlit or have low transparency. The survey will begin in fall of 2012, and will run for at least four years. The telescope design constrains the optimal declination range for observations to 10<δ<5010^\circ<\delta<50^\circ, and site conditions lead to an emphasis on stars in the direction of the Galactic anticenter. The survey is divided into three parts with different target selection strategies: disk, anticenter, and spheroid. The resulting dataset will be used to study the merger history of the Milky Way, the substructure and evolution of the disks, the nature of the first generation of stars through identification of the lowest metallicity stars, and star formation through study of open clusters and the OB associations. Detailed design of the LEGUE survey will be completed after a review of the results of the pilot survey in summer 2012.Comment: 19 pages, 1 figure, accepted for publication in RA

    Phosphorene: Fabrication, Properties and Applications

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    Phosphorene, the single- or few-layer form of black phosphorus, was recently rediscovered as a twodimensional layered material holding great promise for applications in electronics and optoelectronics. Research into its fundamental properties and device applications has since seen exponential growth. In this Perspective, we review recent progress in phosphorene research, touching upon topics on fabrication, properties, and applications; we also discuss challenges and future research directions. We highlight the intrinsically anisotropic electronic, transport, optoelectronic, thermoelectric, and mechanical properties of phosphorene resulting from its puckered structure in contrast to those of graphene and transition-metal dichalcogenides. The facile fabrication and novel properties of phosphorene have inspired design and demonstration of new nanodevices; however, further progress hinges on resolutions to technical obstructions like surface degradation effects and non-scalable fabrication techniques. We also briefly describe the latest developments of more sophisticated design concepts and implementation schemes that address some of the challenges in phosphorene research. It is expected that this fascinating material will continue to offer tremendous opportunities for research and development for the foreseeable future.Comment: invited perspective for JPC

    The 5p15.33 Locus Is Associated with Risk of Lung Adenocarcinoma in Never-Smoking Females in Asia

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    Genome-wide association studies of lung cancer reported in populations of European background have identified three regions on chromosomes 5p15.33, 6p21.33, and 15q25 that have achieved genome-wide significance with p-values of 10−7 or lower. These studies have been performed primarily in cigarette smokers, raising the possibility that the observed associations could be related to tobacco use, lung carcinogenesis, or both. Since most women in Asia do not smoke, we conducted a genome-wide association study of lung adenocarcinoma in never-smoking females (584 cases, 585 controls) among Han Chinese in Taiwan and found that the most significant association was for rs2736100 on chromosome 5p15.33 (p = 1.30×10−11). This finding was independently replicated in seven studies from East Asia totaling 1,164 lung adenocarcinomas and 1,736 controls (p = 5.38×10−11). A pooled analysis achieved genome-wide significance for rs2736100. This SNP marker localizes to the CLPTM1L-TERT locus on chromosome 5p15.33 (p = 2.60×10−20, allelic risk = 1.54, 95% Confidence Interval (CI) 1.41–1.68). Risks for heterozygote and homozygote carriers of the minor allele were 1.62 (95% CI; 1.40–1.87), and 2.35 (95% CI: 1.95–2.83), respectively. In summary, our results show that genetic variation in the CLPTM1L-TERT locus of chromosome 5p15.33 is directly associated with the risk of lung cancer, most notably adenocarcinoma

    Robust estimation of bacterial cell count from optical density

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    Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data
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