Characterizing the Viscoelastic Behavior of PDMS/PDPS Copolymers

Viscoelasticity is the property of materials that exhibits both viscous and elastic characteristics when undergoing deformation. In polymeric materials, the mechani- cal behavior is dominated by this viscoelastic phenomenon. Creating computational models for these materials can be quite complicated due to their frequency depen- dent and temperature dependent material properties. The research presented in this paper will use state of the art methods to fully develop a material model for a filled polydimethylsiloxane-polydiphenynlsiloxane (PDMS/PDPS) copolymer foam that has yet to be characterized. Mechanical properties of PDMS/PDPS copoly- mers are currently being studied to assess engineering performance, and to provide accurate models that can be used to gain a fundamental understanding of the ma- terial behavior. The properties for this material have been measured using multiple experiments. All of the parameters required to populate the Simplified Potential Energy Clock (SPEC) model were measured. The SPEC model can now be used to accurately predict the behavior of the material under different shock and loading environments

Discrete Optimization for Interpretable Study Populations and Randomization Inference in an Observational Study of Severe Sepsis Mortality

Motivated by an observational study of the effect of hospital ward versus intensive care unit admission on severe sepsis mortality, we develop methods to address two common problems in observational studies: (1) when there is a lack of covariate overlap between the treated and control groups, how to define an interpretable study population wherein inference can be conducted without extrapolating with respect to important variables; and (2) how to use randomization inference to form confidence intervals for the average treatment effect with binary outcomes. Our solution to problem (1) incorporates existing suggestions in the literature while yielding a study population that is easily understood in terms of the covariates themselves, and can be solved using an efficient branch-and-bound algorithm. We address problem (2) by solving a linear integer program to utilize the worst case variance of the average treatment effect among values for unobserved potential outcomes that are compatible with the null hypothesis. Our analysis finds no evidence for a difference between the sixty day mortality rates if all individuals were admitted to the ICU and if all patients were admitted to the hospital ward among less severely ill patients and among patients with cryptic septic shock. We implement our methodology in R, providing scripts in the supplementary material

Temporal Trends in Incidence, Sepsis-Related Mortality, and Hospital-Based Acute Care After Sepsis.

OBJECTIVES: A growing number of patients survive sepsis hospitalizations each year and are at high risk for readmission. However, little is known about temporal trends in hospital-based acute care (emergency department treat-and-release visits and hospital readmission) after sepsis. Our primary objective was to measure temporal trends in sepsis survivorship and hospital-based acute care use in sepsis survivors. In addition, because readmissions after pneumonia are subject to penalty under the national readmission reduction program, we examined whether readmission rates declined after sepsis hospitalizations related to pneumonia. DESIGN AND SETTING: Retrospective, observational cohort study conducted within an academic healthcare system from 2010 to 2015. PATIENTS: We used three validated, claims-based approaches to identify 17,256 sepsis or severe sepsis hospitalizations to examine trends in hospital-based acute care after sepsis. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: From 2010 to 2015, sepsis as a proportion of medical and surgical admissions increased from 3.9% to 9.4%, whereas in-hospital mortality rate for sepsis hospitalizations declined from 24.1% to 14.8%. As a result, the proportion of medical and surgical discharges at-risk for hospital readmission after sepsis increased from 2.7% to 7.8%. Over 6 years, 30-day hospital readmission rates declined modestly, from 26.4% in 2010 to 23.1% in 2015, driven largely by a decline in readmission rates among survivors of nonsevere sepsis, and nonpneumonia sepsis specifically, as the readmission rate of severe sepsis survivors was stable. The modest decline in 30-day readmission rates was offset by an increase in emergency department treat-and-release visits, from 2.8% in 2010 to a peak of 5.4% in 2014. CONCLUSIONS: Owing to increasing incidence and declining mortality, the number of sepsis survivors at risk for hospital readmission rose significantly between 2010 and 2015. The 30-day hospital readmission rates for sepsis declined modestly but were offset by a rise in emergency department treat-and-release visits

Randomization Inference and Sensitivity Analysis for Composite Null Hypotheses With Binary Outcomes in Matched Observational Studies

We present methods for conducting hypothesis testing and sensitivity analyses for composite null hypotheses in matched observational studies when outcomes are binary. Causal estimands discussed include the causal risk difference, causal risk ratio, and the effect ratio. We show that inference under the assumption of no unmeasured confounding can be performed by solving an integer linear program, while inference allowing for unmeasured confounding of a given strength requires solving an integer quadratic program. Through simulation studies and data examples, we demonstrate that our formulation allows these problems to be solved in an expedient manner even for large datasets and for large strata. We further exhibit that through our formulation, one can assess the impact of various assumptions about the potential outcomes on the performed inference. R scripts are provided that implement our methods. Supplementary materials for this article are available online. Keywords: Causal inference; Causal risk; Effect ratio; Integer programming; Sensitivity analysi

Improving SWE Estimation with Data Assimilation: The Influence of Snow Depth Observation Timing and Uncertainty

Snow depth observations can be leveraged with data assimilation (DA) to improve estimation of snow density and snow water equivalent (SWE). A key consideration for mission and campaign design is how snow depth retrieval characteristics (including observation timing/frequency and sampling error) influence SWE accuracy and uncertainty in a DA framework. To quantify these effects, we implement a particle filter (PF) assimilation technique to assimilate depth and validate this approach against observed snow density and SWE at 49 snow telemetry sites across 9 years. We sample from continuous in-situ snow depth records to test a range of measurement timing scenarios and two sampling error scenarios representative of remote sensing capabilities. Assimilation reduces density bias by over 40% and SWE bias by over 70% across climate zones and in both wet and dry years. There is little incremental benefit to SWE accuracy when assimilating more than one depth observation near peak accumulation. SWE estimates are less sensitive to observation timing than sampling error. Alternatively, more frequent depth observations improve melt-out date timing and reduce SWE uncertainty, a key consideration when evaluating the operational utility of DA. In matching depth observations, the PF mostly acts to increase precipitation inputs to the model, while not systematically shifting other parameter values or forcings across the climate zones represented with the study sites. This demonstrates that precipitation is the largest source of model error. With DA, density errors are still nontrivial, illuminating the need for further improvements to modeled density to achieve SWE error targets.</div

Place attachment in deprived neighbourhoods: The impacts of population turnover and social mix

This paper examines the determinants of individual place attachment, focussing in particular on differences between deprived and others neighbourhoods, and on the impacts of population turnover and social mix. It uses a multi-level modelling approach to take account of both individual- and neighbourhood-level determinants. Data are drawn from a large sample government survey, the Citizenship Survey 2005, to which a variety of neighbourhood-level data have been attached. The paper argues that attachment is significantly lower in more deprived neighbourhoods primarily because these areas have weaker social cohesion but that, in other respects, the drivers of attachment are the same. Turnover has modest direct impacts on attachment through its effect on social cohesion. Social mix has very limited impacts on attachment and the effects vary between social groups. In general, higher status or more dominant groups appear less tolerant of social mix

Hospital-Based Acute Care Use in Survivors of Septic Shock

OBJECTIVES: Septic shock is associated with increased long-term morbidity and mortality. However, little is known about the use of hospital-based acute care in survivors after hospital discharge. The objectives of the study were to examine the frequency, timing, causes, and risk factors associated with emergency department visits and hospital readmissions within 30 days of discharge. DESIGN: Retrospective cohort study. SETTING: Tertiary, academic hospital in the United States. PATIENTS: Patients admitted with septic shock (serum lactate ≥ 4 mmol/L or refractory hypotension) and discharged alive to a nonhospice setting between 2007 and 2010. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The coprimary outcomes were all-cause hospital readmission and emergency department visits (treat-and-release encounters) within 30 days to any of the three health system hospitals. Of 269 at-risk survivors, 63 (23.4%; 95% CI, 18.2-28.5) were readmitted within 30 days of discharge and another 12 (4.5%; 95% CI, 2.3-7.7) returned to the emergency department for a treat-and-release visit. Readmissions occurred within 15 days of discharge in 75% of cases and were more likely in oncology patients (p=0.001) and patients with a longer hospital length of stay (p=0.04). Readmissions were frequently due to another life-threatening condition and resulted in death or discharge to hospice in 16% of cases. The reasons for readmission were deemed potentially related to the index septic shock hospitalization in 78% (49 of 63) of cases. The most common cause was infection related, accounting for 46% of all 30-day readmissions, followed by cardiovascular or thromboembolic events (18%). CONCLUSIONS: The use of hospital-based acute care appeared to be common in septic shock survivors. Encounters often led to readmission within 15 days of discharge, were frequently due to another acute condition, and appeared to result in substantial morbidity and mortality. Given the potential public health implications of these findings, validation studies are needed

Transitions in microbial communities along a 1600 km freshwater trophic gradient

This study examined vertically-resolved patterns in microbial community structure across a freshwater trophic gradient extending 1600 km from the oligotrophic waters of Lake Superior to the eutrophic waters of Lake Erie, the most anthropogenically influenced of the Laurentian Great Lakes system. Planktonic bacterial communities clustered by Principal Coordinates Analysis (PCoA) on UniFrac distance matrices into four groups representing the epilimnion and hypolimnion of the upper Great Lakes (Lakes Superior and Huron), Lake Superior\u27s northern bays (Nipigon and Black bays), and Lake Erie. The microbes within the upper Great Lakes hypolimnion were the most divergent of these groups with elevated abundance of Planctomycetes and Chloroflexi compared to the surface mixed layer. Statistical tests of the correlation between distance matrices identified temperature and sample depth as the most influential community structuring parameters, reflecting the strong UniFrac clustering separating mixed-layer and hypolimnetic samples. Analyzing mixed-layer samples alone showed clustering patterns were correlated with nutrient concentrations. Operational taxonomic units (OTU) which were differentially distributed among these conditions often accounted for a large portion of the reads returned. While limited in coverage of temporal variability, this study contributes a detailed description of community variability that can be related to other large freshwater systems characterized by changing trophic state

Microbiological, histological, immunological, and toxin response to antibiotic treatment in the mouse model of Mycobacterium ulcerans disease.

Mycobacterium ulcerans infection causes a neglected tropical disease known as Buruli ulcer that is now found in poor rural areas of West Africa in numbers that sometimes exceed those reported for another significant mycobacterial disease, leprosy, caused by M. leprae. Unique among mycobacterial diseases, M. ulcerans produces a plasmid-encoded toxin called mycolactone (ML), which is the principal virulence factor and destroys fat cells in subcutaneous tissue. Disease is typically first manifested by the appearance of a nodule that eventually ulcerates and the lesions may continue to spread over limbs or occasionally the trunk. The current standard treatment is 8 weeks of daily rifampin and injections of streptomycin (RS). The treatment kills bacilli and wounds gradually heal. Whether RS treatment actually stops mycolactone production before killing bacilli has been suggested by histopathological analyses of patient lesions. Using a mouse footpad model of M. ulcerans infection where the time of infection and development of lesions can be followed in a controlled manner before and after antibiotic treatment, we have evaluated the progress of infection by assessing bacterial numbers, mycolactone production, the immune response, and lesion histopathology at regular intervals after infection and after antibiotic therapy. We found that RS treatment rapidly reduced gross lesions, bacterial numbers, and ML production as assessed by cytotoxicity assays and mass spectrometric analysis. Histopathological analysis revealed that RS treatment maintained the association of the bacilli with (or within) host cells where they were destroyed whereas lack of treatment resulted in extracellular infection, destruction of host cells, and ultimately lesion ulceration. We propose that RS treatment promotes healing in the host by blocking mycolactone production, which favors the survival of host cells, and by killing M. ulcerans bacilli