116 research outputs found
A maximum stress at a distance criterion for the prediction of crack propagation in adhesively-bonded joints
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Toll-like receptor 3 blockade in rhinovirus-induced experimental asthma exacerbations:A Randomized Controlled Study
BACKGROUND: Human rhinoviruses (HRVs) commonly precipitate asthma exacerbations. Toll-like receptor 3, an innate pattern recognition receptor, is triggered by HRV, driving inflammation that can worsen asthma. OBJECTIVE: We sought to evaluate an inhibitory mAb to Toll-like receptor 3, CNTO3157, on experimental HRV-16 inoculation in healthy subjects and asthmatic patients. METHODS: In this double-blind, multicenter, randomized, parallel-group study in North America and Europe, healthy subjects and patients with mild-to-moderate stable asthma received single or multiple doses of CNTO3157 or placebo, respectively, and were then inoculated with HRV-16 within 72 hours. All subjects were monitored for respiratory symptoms, lung function, and nasal viral load. The primary end point was maximal decrease in FEV1 during 10 days after inoculation. RESULTS: In asthmatic patients (n = 63) CNTO3157 provided no protection against FEV1 decrease (least squares mean: CNTO3157 [n = 30] = -7.08% [SE, 8.15%]; placebo [n = 25] = -5.98% [SE, 8.56%]) or symptoms after inoculation. In healthy subjects (n = 12) CNTO3157 versus placebo significantly attenuated upper (P = .03) and lower (P = .02) airway symptom scores, with area-under-the-curve increases of 9.1 (15.1) versus 34.9 (17.6) and 13.0 (18.4) versus 50.4 (25.9) for the CNTO3157 (n = 8) and placebo (n = 4) groups, respectively, after inoculation. All of the severe and 4 of the nonserious asthma exacerbations occurred while receiving CNTO3157. CONCLUSION: In summary, CNTO3157 was ineffective in attenuating the effect of HRV-16 challenge on lung function, asthma control, and symptoms in asthmatic patients but suppressed cold symptoms in healthy subjects. Other approaches, including blockade of multiple pathways or antiviral agents, need to be sought for this high unmet medical need
CANDELS: The Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey - The Hubble Space Telescope Observations, Imaging Data Products and Mosaics
This paper describes the Hubble Space Telescope imaging data products and
data reduction procedures for the Cosmic Assembly Near-IR Deep Extragalactic
Legacy Survey (CANDELS). This survey is designed to document the evolution of
galaxies and black holes at , and to study Type Ia SNe beyond
. Five premier multi-wavelength sky regions are selected, each with
extensive multiwavelength observations. The primary CANDELS data consist of
imaging obtained in the Wide Field Camera 3 / infrared channel (WFC3/IR) and
UVIS channel, along with the Advanced Camera for Surveys (ACS). The
CANDELS/Deep survey covers \sim125 square arcminutes within GOODS-N and
GOODS-S, while the remainder consists of the CANDELS/Wide survey, achieving a
total of \sim800 square arcminutes across GOODS and three additional fields
(EGS, COSMOS, and UDS). We summarize the observational aspects of the survey as
motivated by the scientific goals and present a detailed description of the
data reduction procedures and products from the survey. Our data reduction
methods utilize the most up to date calibration files and image combination
procedures. We have paid special attention to correcting a range of
instrumental effects, including CTE degradation for ACS, removal of electronic
bias-striping present in ACS data after SM4, and persistence effects and other
artifacts in WFC3/IR. For each field, we release mosaics for individual epochs
and eventual mosaics containing data from all epochs combined, to facilitate
photometric variability studies and the deepest possible photometry. A more
detailed overview of the science goals and observational design of the survey
are presented in a companion paper.Comment: 39 pages, 25 figure
Identification of the constitutive behaviour of multiphase materials undergoing ductile fracture: an inverse analysis procedure with genetic algorithms
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