A New Generating Function for Calculating the Igusa Local Zeta Function

A new method is devised for calculating the Igusa local zeta function $Z_f$ of a polynomial $f(x_1,\dots,x_n)$ over a $p$-adic field. This involves a new kind of generating function $G_f$ that is the projective limit of a family of generating functions, and contains more data than $Z_f$. This $G_f$ resides in an algebra whose structure is naturally compatible with operations on the underlying polynomials, facilitating calculation of local zeta functions. This new technique is used to expand significantly the set of quadratic polynomials whose local zeta functions have been calculated explicitly. Local zeta functions for arbitrary quadratic polynomials over $p$-adic fields with $p$ odd are presented, as well as for polynomials over unramified $2$-adic fields of the form $Q+L$ where $Q$ is a quadratic form and $L$ is a linear form where $Q$ and $L$ have disjoint variables. For a quadratic form over an arbitrary $p$-adic field with odd $p$, this new technique makes clear precisely which of the three candidate poles are actual poles.Comment: 54 page

The effects of heterogeneity in individual infectiousness on disease modeling predictions

University of Minnesota Ph.D. dissertation. June 2018. Major: Ecology, Evolution and Behavior. Advisors: Meggan Craft, James Forester. 1 computer file (PDF); xiii, 272 pages.Individual variation in infectiousness is generated by heterogeneities in the host, the pathogen, and the environment. However, many models of disease transmission, especially those designed for wildlife and livestock populations, do not typically allow for such variation in individual infectiousness. The objective of my research is to explore the effects of heterogeneity in individual infectiousness on disease modeling predictions within and across populations. My dissertation research explores three different types of heterogeneity that can alter individual infectiousness: (i) host heterogeneity resulting from individual differences in susceptibility, infectiousness, and behavioral contact rates, (ii) contact heterogeneity that arises within a population from underlying social systems and interactions; and (iii) spatial heterogeneity that arises from variation in host density as a function of resource quality and variable individual movement rates across a landscape. An improved understanding of the factors that lead to variability in individual infectiousness and the conditions that necessitate the inclusion of such variability in future disease models will be critical to address the growing global threats of zoonoses and emerging infectious diseases

Essential Components of Early Intervention Programs for Psychosis: Available Intervention Services in the United States

Programs providing interventions for early psychosis are becoming commonplace in the United States (U.S.); however, the characteristics of existing services remain undocumented. We examined program characteristics, clinical services, and program eligibility criteria for outpatient early intervention programs across the U.S. using a semi-structured telephone interview. Content analysis was used to identify the presence or absence of program components, based in part on a recent list of essential evidence-based components recommended for early intervention programs (Addington, MacKenzie, Norman, Wang and Bond, 2013) as well as program characteristics, including eligibility criteria. A total of 34 eligible programs were identified; 31 (91.2%) program representatives agreed to be interviewed. Of the examined components, the most prevalent were individual psychoeducation and outcomes tracking; the least prevalent were outreach services and communication with inpatient units. The populations served by US programs were most frequently defined by restrictions on the duration of psychosis and age. This study provides critical feedback on services for the early psychosis population and identifies research to practice gaps and areas for future improvement

Genotype and sex-based host variation in behavior and susceptibility drives population disease dynamics

Host heterogeneity in pathogen transmission is widespread and presents a major hurdle to predicting and minimizing disease outbreaks. Using Drosophila melanogaster infected with Drosophila C virus as a model system, we integrated experimental measurements of social aggregation, virus shedding, and disease-induced mortality from different genetic lines and sexes into a disease modelling framework. The experimentally measured host heterogeneity produced substantial differences in simulated disease outbreaks, providing evidence for genetic and sex-specific effects on disease dynamics at a population level. While this was true for homogeneous populations of single sex/genetic line, the genetic background or sex of the index case did not alter outbreak dynamics in simulated, heterogeneous populations. Finally, to explore the relative effects of social aggregation, viral shedding and mortality, we compared simulations where we allowed these traits to vary, as measured experimentally, to simulations where we constrained variation in these traits to the population mean. In this context, variation in infectiousness, followed by social aggregation, was the most influential component of transmission. Overall, we show that host heterogeneity in three host traits dramatically affects population-level transmission, but the relative impact of this variation depends on both the susceptible population diversity and the distribution of population-level variation

Ovarian Cancer Incidence Corrected for Oophorectomy

Current reported incidence rates for ovarian cancer may significantly underestimate the true rate because of the inclusion of women in the calculations who are not at risk for ovarian cancer due to prior benign salpingo-oophorectomy (SO). We have considered prior SO to more realistically estimate risk for ovarian cancer. Kentucky Health Claims Data, International Classification of Disease 9 (ICD-9) codes, Current Procedure Terminology (CPT) codes, and Kentucky Behavioral Risk Factor Surveillance System (BRFSS) Data were used to identify women who have undergone SO in Kentucky, and these women were removed from the at-risk pool in order to re-assess incidence rates to more accurately represent ovarian cancer risk. The protective effect of SO on the population was determined on an annual basis for ages 5–80+ using data from the years 2009–2013. The corrected age-adjusted rates of ovarian cancer that considered SO ranged from 33% to 67% higher than age-adjusted rates from the standard population. Correction of incidence rates for ovarian cancer by accounting for women with prior SO gives a better understanding of risk for this disease faced by women. The rates of ovarian cancer were substantially higher when SO was taken into consideration than estimates from the standard population

Targeting Adenosine Receptors for the Treatment of Cardiac Fibrosis

Adenosine is a ubiquitous molecule with key regulatory and cytoprotective mechanisms at times of metabolic imbalance in the body. Among a plethora of physiological actions, adenosine has an important role in attenuating ischaemia-reperfusion injury and modulating the ensuing fibrosis and tissue remodeling following myocardial damage. Adenosine exerts these actions through interaction with four adenosine G protein-coupled receptors expressed in the heart. The adenosine A2B receptor (A2BAR) is the most abundant adenosine receptor (AR) in cardiac fibroblasts and is largely responsible for the influence of adenosine on cardiac fibrosis. In vitro and in vivo studies demonstrate that acute A2BAR stimulation can decrease fibrosis through the inhibition of fibroblast proliferation and reduction in collagen synthesis. However, in contrast, there is also evidence that chronic A2BAR antagonism reduces tissue fibrosis. This review explores the opposing pro- and anti-fibrotic activity attributed to the activation of cardiac ARs and investigates the therapeutic potential of targeting ARs for the treatment of cardiac fibrosis

The Relationship Between Professional Burnout and Quality and Safety in Healthcare: A Meta-Analysis

BACKGROUND: Healthcare provider burnout is considered a factor in quality of care, yet little is known about the consistency and magnitude of this relationship. This meta-analysis examined relationships between provider burnout (emotional exhaustion, depersonalization, and reduced personal accomplishment) and the quality (perceived quality, patient satisfaction) and safety of healthcare. METHODS: Publications were identified through targeted literature searches in Ovid MEDLINE, PsycINFO, Web of Science, CINAHL, and ProQuest Dissertations & Theses through March of 2015. Two coders extracted data to calculate effect sizes and potential moderators. We calculated Pearson's r for all independent relationships between burnout and quality measures, using a random effects model. Data were assessed for potential impact of study rigor, outliers, and publication bias. RESULTS: Eighty-two studies including 210,669 healthcare providers were included. Statistically significant negative relationships emerged between burnout and quality (r = -0.26, 95 % CI [-0.29, -0.23]) and safety (r = -0.23, 95 % CI [-0.28, -0.17]). In both cases, the negative relationship implied that greater burnout among healthcare providers was associated with poorer-quality healthcare and reduced safety for patients. Moderators for the quality relationship included dimension of burnout, unit of analysis, and quality data source. Moderators for the relationship between burnout and safety were safety indicator type, population, and country. Rigor of the study was not a significant moderator. DISCUSSION: This is the first study to systematically, quantitatively analyze the links between healthcare provider burnout and healthcare quality and safety across disciplines. Provider burnout shows consistent negative relationships with perceived quality (including patient satisfaction), quality indicators, and perceptions of safety. Though the effects are small to medium, the findings highlight the importance of effective burnout interventions for healthcare providers. Moderator analyses suggest contextual factors to consider for future study

Reduced habituation of auditory evoked potentials indicate cortical hyper-excitability in Fragile X Syndrome

Sensory hypersensitivities are common, clinically distressing features of Fragile X Syndrome (FXS). Preclinical evidence suggests this abnormality may result from synaptic hyper-excitability in sensory systems. This model predicts reduced sensory habituation to repeated stimulus presentation. Fourteen adolescents and adults with FXS and 15 age-matched controls participated in a modified auditory gating task using trains of 4 identical tones during dense array electroencephalography (EEG). Event-related potential and single trial time–frequency analyses revealed decreased habituation of the N1 event-related potential response in FXS, and increased gamma power coupled with decreases in gamma phase-locking during the early-stimulus registration period. EEG abnormalities in FXS were associated with parent reports of heightened sensory sensitivities and social communication deficits. Reduced habituation and altered gamma power and phase-locking to auditory cues demonstrated here in FXS patients parallels preclinical findings with Fmr1 KO mice. Thus, the EEG abnormalities seen in FXS patients support the model of neocortical hyper-excitability in FXS, and may provide useful translational biomarkers for evaluating novel treatment strategies targeting its neural substrate