5 resultados para Acc rate P
em Duke University
Resumo:
PURPOSE: The role of PM10 in the development of allergic diseases remains controversial among epidemiological studies, partly due to the inability to control for spatial variations in large-scale risk factors. This study aims to investigate spatial correspondence between the level of PM10 and allergic diseases at the sub-district level in Seoul, Korea, in order to evaluate whether the impact of PM10 is observable and spatially varies across the subdistricts. METHODS: PM10 measurements at 25 monitoring stations in the city were interpolated to 424 sub-districts where annual inpatient and outpatient count data for 3 types of allergic diseases (atopic dermatitis, asthma, and allergic rhinitis) were collected. We estimated multiple ordinary least square regression models to examine the association of the PM10 level with each of the allergic diseases, controlling for various sub-district level covariates. Geographically weighted regression (GWR) models were conducted to evaluate how the impact of PM10 varies across the sub-districts. RESULTS: PM10 was found to be a significant predictor of atopic dermatitis patient count (P<0.01), with greater association when spatially interpolated at the sub-district level. No significant effect of PM10 was observed on allergic rhinitis and asthma when socioeconomic factors were controlled for. GWR models revealed spatial variation of PM10 effects on atopic dermatitis across the sub-districts in Seoul. The relationship of PM10 levels to atopic dermatitis patient counts is found to be significant only in the Gangbuk region (P<0.01), along with other covariates including average land value, poverty rate, level of education and apartment rate (P<0.01). CONCLUSIONS: Our findings imply that PM10 effects on allergic diseases might not be consistent throughout Seoul. GIS-based spatial modeling techniques could play a role in evaluating spatial variation of air pollution impacts on allergic diseases at the sub-district level, which could provide valuable guidelines for environmental and public health policymakers.
Resumo:
<p>This dissertation studies the coding strategies of computational imaging to overcome the limitation of conventional sensing techniques. The information capacity of conventional sensing is limited by the physical properties of optics, such as aperture size, detector pixels, quantum efficiency, and sampling rate. These parameters determine the spatial, depth, spectral, temporal, and polarization sensitivity of each imager. To increase sensitivity in any dimension can significantly compromise the others. p><p>This research implements various coding strategies subject to optical multidimensional imaging and acoustic sensing in order to extend their sensing abilities. The proposed coding strategies combine hardware modification and signal processing to exploiting bandwidth and sensitivity from conventional sensors. We discuss the hardware architecture, compression strategies, sensing process modeling, and reconstruction algorithm of each sensing system. p><p>Optical multidimensional imaging measures three or more dimensional information of the optical signal. Traditional multidimensional imagers acquire extra dimensional information at the cost of degrading temporal or spatial resolution. Compressive multidimensional imaging multiplexes the transverse spatial, spectral, temporal, and polarization information on a two-dimensional (2D) detector. The corresponding spectral, temporal and polarization coding strategies adapt optics, electronic devices, and designed modulation techniques for multiplex measurement. This computational imaging technique provides multispectral, temporal super-resolution, and polarization imaging abilities with minimal loss in spatial resolution and noise level while maintaining or gaining higher temporal resolution. The experimental results prove that the appropriate coding strategies may improve hundreds times more sensing capacity. p><p>Human auditory system has the astonishing ability in localizing, tracking, and filtering the selected sound sources or information from a noisy environment. Using engineering efforts to accomplish the same task usually requires multiple detectors, advanced computational algorithms, or artificial intelligence systems. Compressive acoustic sensing incorporates acoustic metamaterials in compressive sensing theory to emulate the abilities of sound localization and selective attention. This research investigates and optimizes the sensing capacity and the spatial sensitivity of the acoustic sensor. The well-modeled acoustic sensor allows localizing multiple speakers in both stationary and dynamic auditory scene; and distinguishing mixed conversations from independent sources with high audio recognition rate.p>
Resumo:
<p>Fibronectin (FN) is a large extracellular matrix (ECM) protein that is made up ofp><p>type I (FNI), type II (FNII), & type III (FNIII) domains. It assembles into an insolublep><p>supra-‐‑molecular structure: the fibrillar FN matrix. FN fibrillogenesis is a cell‐‑mediated process, which is initiated when FN binds to integrins on the cell surface. The FN matrix plays an important role in cell migration, proliferation, signaling & adhesion. Despite decades of research, the FN matrix is one of the least understood supra-‐‑molecular protein assemblies. There have been several attempts to elucidate the exact mechanism of matrix assembly resulting in significant progress in the field but it is still unclear as to what are FN-‐‑FN interactions, the nature of these interactions and the domains of FN thatp><p>are in contact with each other. FN matrix fibrils are elastic in nature. Two models have been proposed to explain the elasticity of the fibrils. The first model: the ‘domain unfolding’ model postulates that the unraveling of FNIII domains under tension explains fibril elasticity.p><p>The second model relies on the conformational change of FN from compact to extended to explain fibril elasticity. FN contain 15 FNIII domains, each a 7-‐‑strand beta sandwich. Earlier work from our lab used the technique of labeling a buried Cys to study the ‘domain unfolding’ model. They used mutant FNs containing a buried Cys in a single FNIII domain and found that 6 of the 15 FNIII domains label in matrix fibrils. Domain unfolding due to tension, matrix associated conformational changes or spontaneous folding and unfolding are all possible explanation for labeling of the buried Cys. The present study also uses the technique of labeling a buried Cys to address whether it is spontaneous folding and unfolding that labels FNIII domains in cell culture. We used thiol reactive DTNB to measure the kinetics of labeling of buried Cys in eleven FN III domains over a wide range of urea concentrations (0-‐‑9M). The kinetics data were globally fit using Mathematica. The results are equivalent to those of H-‐‑D exchange, andp><p>provide a comprehensive analysis of stability and unfolding/folding kinetics of eachp><p>domain. For two of the six domains spontaneous folding and unfolding is possibly the reason for labeling in cell culture. For the rest of the four domains it is probably matrix associated conformational changes or tension induced unfolding.p><p>A long-‐‑standing debate in the protein-‐‑folding field is whether unfolding ratep><p>constants or folding rate constants correlate to the stability of a protein. FNIII domains all have the same ß sandwich structure but very different stabilities and amino acid sequences. Our study analyzed the kinetics of unfolding and folding and stabilities of eleven FNIII domains and our results show that folding rate constants for FNIII domains are relatively similar and the unfolding rates vary widely and correlate to stability. FN forms a fibrillar matrix and the FN-‐‑FN interactions during matrix fibril formation are not known. FNI 1-‐‑9 or the N-‐‑ terminal region is indispensible for matrix formation and its major binding partner has been shown to be FNIII 2. Earlier work from our lab, using FRET analysis showed that the interaction of FNI 1-‐‑9 with a destabilized FNIII 2 (missing the G strand, FNIII 2ΔG) reduces the FRET efficiency. This efficiency is restored in the presence of FUD (bacterial adhesion from S. pyogenes) that has been known to interact with FNI 1-‐‑9 via a tandem ß zipper. In the present study wep><p>use FRET analysis and a series of deletion mutants of FNIII 2ΔG to study the shortest fragment of FNIII 2ΔG that is required to bind FNI 1-‐‑9. Our results presented here are qualitative and show that FNIII 2ΔC’EFG is the shortest fragment required to bind FNI 1-‐‑9. Deletion of one more strand abolishes the interaction with FNI 1-‐‑9.p>
Resumo:
BACKGROUND: Primary care providers' suboptimal recognition of the severity of chronic kidney disease (CKD) may contribute to untimely referrals of patients with CKD to subspecialty care. It is unknown whether U.S. primary care physicians' use of estimated glomerular filtration rate (eGFR) rather than serum creatinine to estimate CKD severity could improve the timeliness of their subspecialty referral decisions. METHODS: We conducted a cross-sectional study of 154 United States primary care physicians to assess the effect of use of eGFR (versus creatinine) on the timing of their subspecialty referrals. Primary care physicians completed a questionnaire featuring questions regarding a hypothetical White or African American patient with progressing CKD. We asked primary care physicians to identify the serum creatinine and eGFR levels at which they would recommend patients like the hypothetical patient be referred for subspecialty evaluation. We assessed significant improvement in the timing [from eGFR < 30 to ≥ 30 mL/min/1.73m(2)) of their recommended referrals based on their use of creatinine versus eGFR. RESULTS: Primary care physicians recommended subspecialty referrals later (CKD more advanced) when using creatinine versus eGFR to assess kidney function [median eGFR 32 versus 55 mL/min/1.73m(2), p < 0.001]. Forty percent of primary care physicians significantly improved the timing of their referrals when basing their recommendations on eGFR. Improved timing occurred more frequently among primary care physicians practicing in academic (versus non-academic) practices or presented with White (versus African American) hypothetical patients [adjusted percentage(95% CI): 70% (45-87) versus 37% (reference) and 57% (39-73) versus 25% (reference), respectively, both p ≤ 0.01). CONCLUSIONS: Primary care physicians recommended subspecialty referrals earlier when using eGFR (versus creatinine) to assess kidney function. Enhanced use of eGFR by primary care physicians' could lead to more timely subspecialty care and improved clinical outcomes for patients with CKD.
Resumo:
BACKGROUND: Automated reporting of estimated glomerular filtration rate (eGFR) is a recent advance in laboratory information technology (IT) that generates a measure of kidney function with chemistry laboratory results to aid early detection of chronic kidney disease (CKD). Because accurate diagnosis of CKD is critical to optimal medical decision-making, several clinical practice guidelines have recommended the use of automated eGFR reporting. Since its introduction, automated eGFR reporting has not been uniformly implemented by U. S. laboratories despite the growing prevalence of CKD. CKD is highly prevalent within the Veterans Health Administration (VHA), and implementation of automated eGFR reporting within this integrated healthcare system has the potential to improve care. In July 2004, the VHA adopted automated eGFR reporting through a system-wide mandate for software implementation by individual VHA laboratories. This study examines the timing of software implementation by individual VHA laboratories and factors associated with implementation. METHODS: We performed a retrospective observational study of laboratories in VHA facilities from July 2004 to September 2009. Using laboratory data, we identified the status of implementation of automated eGFR reporting for each facility and the time to actual implementation from the date the VHA adopted its policy for automated eGFR reporting. Using survey and administrative data, we assessed facility organizational characteristics associated with implementation of automated eGFR reporting via bivariate analyses. RESULTS: Of 104 VHA laboratories, 88% implemented automated eGFR reporting in existing laboratory IT systems by the end of the study period. Time to initial implementation ranged from 0.2 to 4.0 years with a median of 1.8 years. All VHA facilities with on-site dialysis units implemented the eGFR software (52%, p<0.001). Other organizational characteristics were not statistically significant. CONCLUSIONS: The VHA did not have uniform implementation of automated eGFR reporting across its facilities. Facility-level organizational characteristics were not associated with implementation, and this suggests that decisions for implementation of this software are not related to facility-level quality improvement measures. Additional studies on implementation of laboratory IT, such as automated eGFR reporting, could identify factors that are related to more timely implementation and lead to better healthcare delivery.