A Reanalysis of theUltraviolet Extinction from Interstellar Dust in the Large Magellanic Cloud

We have reanalyzed the Large Magellanic Cloud's (LMC) ultraviolet (UV) extinction using data from the IUE final archive. Our new analysis takes advantage of the improved signal--to--noise of the IUE NEWSIPS reduction, the exclusion of stars with very low reddening, the careful selection of well matched comparison stars, and an analysis of the effects of Galactic foreground dust. Differences between the average extinction curves of the 30 Dor region and the rest of the LMC are reduced compared to previous studies. We find that there is a group of stars with very weak 2175 Ang. bumps that lie in or near the region occupied by the supergiant shell, LMC 2, on the southeast side of 30 Dor. The average extinction curves inside and outside LMC 2 show a very significant difference in 2175 Ang. bump strength, but their far--UV extinctions are similar. While it is unclear whether or not the extinction outside the LMC 2 region can be fit with the relation of Cardelli, Clayton and Mathis (CCM), sightlines near LMC 2 cannot be fit with CCM due to their weak 2175 Ang. bumps. While the extinction properties seen in the LMC lie within the range of properties seen in the Galaxy, the correlations of UV extinction properties with environment seen in the Galaxy do not appear to hold in the LMC.Comment: 29 pages, 10 figures, to be published in Ap

Hypothesis Generation Using Network Structures on Community Health Center Cancer-Screening Performance

RESEARCH OBJECTIVES: Nationally sponsored cancer-care quality-improvement efforts have been deployed in community health centers to increase breast, cervical, and colorectal cancer-screening rates among vulnerable populations. Despite several immediate and short-term gains, screening rates remain below national benchmark objectives. Overall improvement has been both difficult to sustain over time in some organizational settings and/or challenging to diffuse to other settings as repeatable best practices. Reasons for this include facility-level changes, which typically occur in dynamic organizational environments that are complex, adaptive, and unpredictable. This study seeks to understand the factors that shape community health center facility-level cancer-screening performance over time. This study applies a computational-modeling approach, combining principles of health-services research, health informatics, network theory, and systems science. METHODS: To investigate the roles of knowledge acquisition, retention, and sharing within the setting of the community health center and to examine their effects on the relationship between clinical decision support capabilities and improvement in cancer-screening rate improvement, we employed Construct-TM to create simulated community health centers using previously collected point-in-time survey data. Construct-TM is a multi-agent model of network evolution. Because social, knowledge, and belief networks co-evolve, groups and organizations are treated as complex systems to capture the variability of human and organizational factors. In Construct-TM, individuals and groups interact by communicating, learning, and making decisions in a continuous cycle. Data from the survey was used to differentiate high-performing simulated community health centers from low-performing ones based on computer-based decision support usage and self-reported cancer-screening improvement. RESULTS: This virtual experiment revealed that patterns of overall network symmetry, agent cohesion, and connectedness varied by community health center performance level. Visual assessment of both the agent-to-agent knowledge sharing network and agent-to-resource knowledge use network diagrams demonstrated that community health centers labeled as high performers typically showed higher levels of collaboration and cohesiveness among agent classes, faster knowledge-absorption rates, and fewer agents that were unconnected to key knowledge resources. Conclusions and research implications: Using the point-in-time survey data outlining community health center cancer-screening practices, our computational model successfully distinguished between high and low performers. Results indicated that high-performance environments displayed distinctive network characteristics in patterns of interaction among agents, as well as in the access and utilization of key knowledge resources. Our study demonstrated how non-network-specific data obtained from a point-in-time survey can be employed to forecast community health center performance over time, thereby enhancing the sustainability of long-term strategic-improvement efforts. Our results revealed a strategic profile for community health center cancer-screening improvement via simulation over a projected 10-year period. The use of computational modeling allows additional inferential knowledge to be drawn from existing data when examining organizational performance in increasingly complex environments

A Quantitative Comparison of SMC, LMC, and Milky Way UV to NIR Extinction Curves

We present an exhaustive, quantitative comparison of all of the known extinction curves in the Small and Large Magellanic Clouds (SMC and LMC) with our understanding of the general behavior of Milky Way extinction curves. The R_V dependent CCM relationship and the sample of extinction curves used to derive this relationship is used to describe the general behavior of Milky Way extinction curves. The ultraviolet portion of the SMC and LMC extinction curves are derived from archival IUE data, except for one new SMC extinction curve which was measured using HST/STIS observations. The optical extinction curves are derived from new (for the SMC) and literature UBVRI photometry (for the LMC). The near-infrared extinction curves are calculated mainly from 2MASS photometry supplemented with DENIS and new JHK photometry. For each extinction curve, we give R_V = A(V)/E(B-V) and N(HI) values which probe the same dust column as the extinction curve. We compare the properties of the SMC and LMC extinction curves with the CCM relationship three different ways: each curve by itself, the behavior of extinction at different wavelengths with R_V, and behavior of the extinction curve FM fit parameters with R_V. As has been found previously, we find that a small number of LMC extinction curves are consistent with the CCM relationship, but majority of the LMC and all of the SMC curves do not follow the CCM relationship. For the first time, we find that the CCM relationship seems to form a bound on the properties of all of the LMC and SMC extinction curves. This result strengthens the picture of dust extinction curves exhibit a continuum of properties between those found in the Milky Way and the SMC Bar. (abridged)Comment: 18 pages, 10 figures, ApJ in pres

Using computational modeling to assess the impact of clinical decision support on cancer screening improvement strategies within the community health centers

AbstractOur conceptual model demonstrates our goal to investigate the impact of clinical decision support (CDS) utilization on cancer screening improvement strategies in the community health care (CHC) setting. We employed a dual modeling technique using both statistical and computational modeling to evaluate impact. Our statistical model used the Spearman’s Rho test to evaluate the strength of relationship between our proximal outcome measures (CDS utilization) against our distal outcome measure (provider self-reported cancer screening improvement). Our computational model relied on network evolution theory and made use of a tool called Construct-TM to model the use of CDS measured by the rate of organizational learning. We employed the use of previously collected survey data from community health centers Cancer Health Disparities Collaborative (HDCC). Our intent is to demonstrate the added valued gained by using a computational modeling tool in conjunction with a statistical analysis when evaluating the impact a health information technology, in the form of CDS, on health care quality process outcomes such as facility-level screening improvement. Significant simulated disparities in organizational learning over time were observed between community health centers beginning the simulation with high and low clinical decision support capability

Dust Grain-Size Distributions From MRN to MEM

Employing the Maximum Entropy Method algorithm, we fit interstellar extinction measurements which span the wavelength range 0.125-3 micron. We present a uniform set of MEM model fits, all using the same grain materials, optical constants and abundance constraints. In addition, we are taking advantage of improved UV and IR data and better estimates of the gas-to-dust ratio. The model fits cover the entire range of extinction properties that have been seen in the Galaxy and the Magellanic Clouds. The grain models employed for this presentation are the simplistic homogeneous spheres models (i.e., Mathis, Rumpl, & Nordsieck 1977) with two (graphite, silicate) or three (graphite, silicate, amorphous carbon) components. Though such usage is only a first step, the results do provide interesting insight into the use of grain size as a diagnostic of dust environment. We find that the SMC Bar extinction curve cannot be fit using carbon grains alone. This is a challenge to the recent observational result indicating little silicon depletion in the SMC.Comment: 24 pages, 5 figures, accepted for publication in the Astrophysical Journa

Kidney after nonrenal transplantation-the impact of alemtuzumab induction

BACKGROUND.: Calcineurin inhibitor nephrotoxicity in nonrenal allograft recipients can lead to end-stage renal disease and the need for kidney transplantation. We sought to evaluate the role of alemtuzumab induction in this population. PATIENTS AND METHODS.: We evaluated 144 patients undergoing kidney transplantation after nonrenal transplantation between May 18, 1998, and October 8, 2007. Seventy-two patients transplanted between January 15, 2003, and October 8, 2007, received alemtuzumab induction and continued their pretransplant immunosuppression. Seventy-two patients transplanted between May 18, 1998, and July 21, 2007, did not receive alemtuzumab induction, but received additional steroids and maintenance immunosuppression. Donor and recipient demographics were comparable. RESULTS.: Overall, 1-and 3-year patient survival and renal function were comparable between the two groups. One-and 3-year graft survival was 93.0% and 75.3% in the alemtuzumab group and 83.3% and 68.7% in the no alemtuzumab group, respectively (P=0.051). The incidence of acute rejection was lower in the alemtuzumab group, 15.3%, than in the no alemtuzumab group, 41.7% (P=0.0001). The incidence of delayed graft function was lower in the alemtuzumab group, 9.7%, than in the no alemtuzumab group, 25.0% (P=0.003). The incidence of viral complications was comparable. CONCLUSION.: Alemtuzumab induction with simple resumption of baseline immunosuppression in patients undergoing kidney transplantation after nonrenal transplantation represents a reasonable immunosuppressive strategy. Copyright © 2009 by Lippincott Williams & Wilkins

Assembling highly repetitive Xanthomonas TALomes using Oxford Nanopore sequencing

Background: Most plant-pathogenic Xanthomonas bacteria harbor transcription activator-like effector (TALE) genes, which function as transcriptional activators of host plant genes and support infection. The entire repertoire of up to 29 TALE genes of a Xanthomonas strain is also referred to as TALome. The DNA-binding domain of TALEs is comprised of highly conserved repeats and TALE genes often occur in gene clusters, which precludes the assembly of TALE-carrying Xanthomonas genomes based on standard sequencing approaches. Results: Here, we report the successful assembly of the 5 Mbp genomes of five Xanthomonas strains from Oxford Nanopore Technologies (ONT) sequencing data. For one of these strains, Xanthomonas oryzae pv. oryzae (Xoo) PXO35, we illustrate why Illumina short reads and longer PacBio reads are insufficient to fully resolve the genome. While ONT reads are perfectly suited to yield highly contiguous genomes, they suffer from a specific error profile within homopolymers. To still yield complete and correct TALomes from ONT assemblies, we present a computational correction pipeline specifically tailored to TALE genes, which yields at least comparable accuracy as Illumina-based polishing. We further systematically assess the ONT-based pipeline for its multiplexing capacity and find that, combined with computational correction, the complete TALome of Xoo PXO35 could have been reconstructed from less than 20,000 ONT reads. Conclusions: Our results indicate that multiplexed ONT sequencing combined with a computational correction of TALE genes constitutes a highly capable tool for characterizing the TALomes of huge collections of Xanthomonas strains in the future

Community based service providers' perspectives on frequent and/or avoidable admission of older people with chronic disease in rural NSW: a qualitative study

Background: Frequent and potentially avoidable hospital admission amongst older patients with ambulatory care sensitive (ACS) chronic conditions is a major topic for research internationally, driven by the imperative to understand and therefore reduce hospital admissions. Research to date has mostly focused on analysis of routine data using ACS as a proxy for 'potentially avoidable'. There has been less research on the antecedents of frequent and/or avoidable admission from the perspectives of patients or those offering community based care and support for these patients. This study aimed to explore community based service providers' perspectives on the factors contributing to admission among older patients with chronic disease and a history of frequent and potentially avoidable admission. Methods. 15 semi-structured interviews with community based providers of health care and other services, and an emergency department physician were conducted. Summary documents were produced and thematic analysis undertaken. Results: A range of complex barriers which limit or inhibit access to services were reported. We classified these as external and internal barriers. Important external barriers included: complexity of provision of services, patients' limited awareness of different services and their inexperience in accessing services, patients needing a higher level or longer length of service than they currently have access to, or an actual lack of available services, patient poverty, rurality, and transport. Important internal barriers included: fear (of change for example), a 'stoic' attitude to life, and for some, the difficulty of accepting their changed health status. Conclusions: The factors underlying frequent and/or potentially avoidable admission are numerous and complex. Identifying strategies to improve services or interventions for this group requires understanding patient, carer and service providers' perspectives. Improving accessibility of services is also complex, and includes consideration of patients' social, emotional and psychological ability and willingness to use services as well as those services being available and easily accessed