In the Midwestern US, forested and other woody plant habitats are embedded in a matrix of agricultural and urban landcover that alters configurations of “natural” habitats and creates novel habitat types. Variation in the type and juxtaposition of landcover in the matrix between habitats can profoundly impact the spatial and temporal distributions of insects. Intense urban and agricultural development alters habitats, increases fragmentation, and may decouple trophic interactions if plants or animals cannot disperse to needed resources. Specialist insects represent a substantial proportion of global biodiversity and their fidelity to discrete microhabitats provides a powerful framework for investigating organismal responses to human land use. Specialist herbivores and parasitoids that depend on discrete plant habitats simplify assessment of how trophic interactions, local demographic traits, and dispersal processes affect responses to landcover heterogeneity. Herbivore responses to landcover change are highly idiosyncratic and not well characterized. Parasitoid wasps are predicted to be more prone than their herbivore hosts to local extinction in response to increased habitat fragmentation, but often respond differently to similar landcover contexts. Understanding and predicting idiosyncratic spatial population dynamics of simple host-parasitoid communities and other insect systems requires integration of metacommunity-level ecological paradigms with spatial analyses across multiple spatial scales. We sampled site occupancy and densities for two plant-herbivore-parasitoid systems from 250 sites across a 360 km2 urban/ agricultural landscape across three study years to ask whether and how human development decouples interactions between trophic levels. We first performed a single year analysis to investigate broad scale patterns. We compared patterns of site occupancy, host plant density, herbivory and parasitism rates of insects at two trophic levels with respect to landcover at multiple spatial scales. Geospatial analyses were used to identify landcover characters predictive of insect distributions. We found that herbivorous insect densities were decoupled from host tree densities in urban landcover types at several spatial scales. This effect was amplified for the third trophic level in one of the two insect systems: despite being abundant regionally, a parasitoid species was absent from all urban/ suburban landcover even where its herbivore host was common. Our results indicate that human land use patterns limit distributions of specialist insects. Dispersal constraints associated with urban built development are specifically implicated as a limiting factor. Our multi-year analysis of trophic interactions in urban versus agricultural landcover showed that important results from our single-year study are consistent over time and provided useful insights into the factors mediating spatial distributions of specialist insects in altered landscapes. While we observed that insect species responded to landcover at consistent local- and landscape-scale spatial extents, we observed that coarse grain landcover categories (i.e. urban versus agricultural) at low spatial resolution yielded the most consistent patterns of organismal response. Our results indicate that agricultural versus urban landcover contexts can mediate distinct spatial population structuring across linked trophic levels. This finding has important implications for conservation and pest management strategies in heterogeneous landscapes and is an important consideration when translating heuristics regarding metacommunity dynamics from one broad spatial context to another.

Many social processes influence the amount, quality, and availability of support from an individual's social network. Trait influences are characteristics of the individual that generalize across relationships and affect how much support is received and perceived on average from other people. Social influences comprise characteristics of the individual's social network. They are relationship specific and account for the variability in supportiveness among an individual's providers. Recent studies have taken a multilevel approach to studying social support in order to partition the variance in sets of relationship-specific support measures into trait and social components. These studies have also used multivariate generalizability (G) theory to examine the correlations between social support and other constructs, such as negative mood, at the trait and social level. These multilevel studies have begun to clarify the relative contributions of trait and social influences on social support, but much is yet to be learned about the nature and measurement of social support's trait and social components. One set of aims within this project was to identify characteristics of support recipients and characteristics of support providers that were related to the reception and perception of social support. Another set of aims focused on validating the measurement strategies used by G theory researchers and understanding how the trait and social components of support and mood derived from relationship-specific measures relate to traditional measures of these constructs. My final set of aims involved the application of multilevel analyses of social support and negative mood to three existing theories in the social support literature--the buffering hypothesis, the matching hypothesis, and the platinum rule. The participants in this study comprised two samples--one group of 755 undergraduate psychology students, and one group of 430 community members from across the United States. Participants completed measures of their personality traits, recent depressive symptoms, recent experiences of life adversity and perceived control over life adversity. They also reported on three close relationships including support from those relationships, satisfaction with those relationships, and mood experienced when interacting with those three people. Several multilevel analyses were used in the study. Univariate G theory analyses were used to quantify the relative variance in support, mood, and relationship satisfaction attributable to trait and social influences. Multivariate G theory analyses were used to estimate the links between these variables at the trait and social levels of analysis. Mixed effects models were used to identify trait and relationship-specific constructs that that might partly constitute the trait and social influences on social support. Multilevel Structural Equation Modeling (SEM) was used to evaluate the validity of several constructs employed in previous multilevel studies on social support. Finally, mixed effects and multivariate G theory analyses were used to test the buffering hypothesis, the matching hypothesis, and the platinum rule. Consistent with previous multilevel studies of social support, recipients who received more support, on average, from their social networks also reported more negative mood when interacting with their providers. After taking those average tendencies into account, the amount of support received from an individual support provider was not associated with negative mood experienced when with that provider. The investigation of the trait influences on social support showed that recipients who were younger, more extraverted, and more open to new experiences tended to receive more social support. Women tended to receive more support than men. With respect to social influences, romantic partners tended to provide the most support whereas friends and siblings provided significantly less support on average. Women tended to provide more support than men. The validity assessment showed that the social component of support availability was only modestly distinct from the social component of generic relationship satisfaction. The trait component of support availability showed good discriminant validity from relationship satisfaction and good convergent validity with global support availability. The trait component of relationship-specific mood showed moderate convergent validity with general mood. The buffering and matching hypotheses were not supported by my findings. The platinum rule was supported at the trait level in that recipients who reported greater support adequacy, on average, tended to report more positive mood and less negative mood. The platinum rule was also supported at the social level in that recipients tended to report experiencing the most positive mood and least negative mood when interacting with individual providers who tended to supply the most adequate support.

Recent studies suggest that cardiomyocyte membrane microdomains, caveolae and transverse tubules, play a key role in cardiac arrhythmia. Mutation of caveolin-encoding genes CAV3, co-expressed with genes of caveolae ion channels, leads to a late persistent sodium currents and delayed repolarization stage, called LQT9 disease. A simplified three-current model is created to largely reduce the well-known Pandit rat ventricular myocyte model. The mathematical tractability of the three-current model allows us to conduct asymptotic analysis and efficiently estimate action potential duration. Improvement in the description of the mechanism for caveolae sodium current is incorporated into the three-current model utilizing a probability density approach for the four-state caveolae neck-channel coupling. The prolongation of action potentials and the formation of potential arrhythmia are shown to arise if caveolae neck open probability varies. A minimal model of the Ca2+ spatial distribution of CICR units illustrates the transverse tubule remodeling in failing myocyte causes dysfunction in the Ca2+ profile. With regards to discrimination of protein localization, which is widely used in biological experiments, the bagging pruned decision tree algorithm is tested to be one of the algorithms with best performance on the large data set, and it succeeds in extracting information to be highly predictive on test data. Parallel computation technique is applied to accelerate the speed of implementation in K-nearest neighbor learning algorithms on big data sets.

Although the link between classroom instructor behavior and student engagement has been well documented, the same cannot be said for instructors and students interacting with one another in clinical settings. Given the relatively close nature of the student-clinical instructor (CI) relationship and the considerable differences between the structured environment of the classroom and the unpredictable and often stressful environment of the healthcare clinic, classroom-based assumptions of what constitutes effective or ineffective teaching behavior may or may not be valid for the clinic. This study applied self-determination theory to investigate the degree to which CI psychological need-supporting/thwarting behaviors affect student clinical engagement. An online survey consisting of items from established scales recognized to measure teacher autonomy-, competency- and relatedness-supporting/thwarting behavior was used to question 751 undergraduate students who were currently enrolled in the clinical portion of their education in one of four radiation science disciplines (radiologic technology, radiation therapy, diagnostic medical sonography, and nuclear medicine technology) at one of 387 institutions of higher education across the United States. Correlational and linear regression analysis revealed a strong connection between overall CI need-supporting/thwarting behavior and student clinical engagement (r(749) = 0.75, p = .0000 and ΔR2 = .5181, pr > F = .0000). The study also revealed CI relatedness-supporting/thwarting behaviors to have the most influence on student clinical engagement (β=.4197, p = .000), followed by autonomy-supporting/thwarting behaviors (β=0.1298, p = .001) and competency-supporting/thwarting behaviors (β=0.1110, p=.007). A number of key student background factors proved to have very little or no influence on student clinical engagement. The results of this study brings awareness to the powerful impact clinical instructors have on their students' motivation to engage in educationally productive clinical activities and serves to underscore the need for routine in-service programs specifically designed to teach CIs how to effectively employ psychological need-supporting behaviors and avoid psychological need-thwarting behaviors when working with their students.

Cardiovascular diseases (CVD) and diabetes are the most significant chronic diseases globally due to their high prevalence and mortality. People with CVD or diabetes need to know how to self-manage their health conditions to promote, maintain, and restore their health status. The Nursing Outcomes Classification (NOC) has assisted nurses and other health care providers to evaluate and quantify the status of the patient and has reflected the current health care issues that are to prevent progression of chronic diseases. Based on the current health focus, additional knowledge and self-management NOC outcomes were developed and added to the latest edition of NOC published in 2013. Generally, validation of measurement tools is required to provide trustworthy evidence for use in practice. As measurement tools, NOC outcomes with their definitions, indicators, and measurement scales need to be validated for accuracy, meaningfulness, and usefulness before they are widely used in various health settings. To provide clinical evidence for effective nursing practice such as accurate assessments and evaluations, validation of NOC outcomes is required. The purpose of this study was to validate 12 NOC outcomes focused on knowledge and self-management for people with CVD and diabetes. A descriptive exploratory design was used to validate the selected NOC outcomes, and a two round survey using the Delphi technique was used to collect data from the invited experts via email. Two subject populations were invited. The first expert group was related to standardized nursing languages (SNL) and invited experts were members of NANDA International or a fellow of the Center for Nursing Classification and Clinical Effectiveness (CNC). The second expert group was related to self-management and invited experts were members of two research interest groups which are Health Promoting Behaviors Across the Lifespan and Self Care in the Midwest Nursing Research Society (MNRS). Descriptive statistics were used to determine the definition adequacy, clinical usefulness of measurement scales, and similarity between content of knowledge and self-management outcomes. The Outcome Content Validity (OCV) method was used for the content validity of outcomes and their indicators. A total of 46 and 27 nurse experts participated in the first and second round surveys, respectively. The mean age of participants was 51.87 years (SD=13.03) and the mean of experience in nursing was 27.67 (SD=14.75) years. Most participants had experience using SNL (82.6%). Each outcome reported acceptable psychometric properties. The range of definition adequacy of the 12 NOC outcomes was from 3.71 to 4.29 (perfect score is 5.0). The range of clinical usefulness for using measurement scales was from 3.77 to 4.29. The range of content similarity of the six pairs was from 3.88 to 4.35. Every evaluated NOC outcome identified as critical with over .80 OCV scores (perfect score 1.0). More than 80% of indicators were categorized in the critical level in the first round. Thus, psychometric properties of the 12 NOC outcomes were acceptable to use in the clinical settings. By using validated NOC outcomes, nurses caring of patients with CVD or diabetes can evaluate patient outcomes effectively, and determine the effect of nursing interventions accurately. Development of new NOC outcomes and validation of them will provide nurses with measurement tools to use with patients, clinical evidence for quality improvement and knowledge development in nursing.

This study examined low and high level teachers' questioning patterns and classroom implementations within an argument-based inquiry approach known as the Science Writing Heuristic (SWH) approach, which addresses issues on negotiation, argumentation, learning, and teaching. The level of the teachers was determined by the students' writing scores. This study was conducted in Turkey with seven teacher for preliminary study. Because scoring writing samples examines the students' negotiation level with the different sources and students learn scientific process, as negotiation, which they may transfer into their writing, in classroom, two teachers were selected to represent low and high level teachers. Data collection involved classroom observation through video recordings. The comparative qualitative method was employed throughout the data analysis process with including quantitative results. The research questions that guided the present study were: (1) How are low and high level teachers, determined according to their students' writing scores, questioning patterns different from each other during classroom discourse? (2) Is there a relationship between students' writings and teachers' questioning styles in the classroom? Analysis of Qualitative data showed that teachers' classroom implementations reveal big differences based on argumentation patterns. The high level teacher, whose students had high scores in writing samples, asked more questions and the cognitive levels of questions were higher than the low level teacher. Questions promote an argumentative environment and improve critical thinking skills by discussing different ideas and claims. Asking more questions of teacher influences students to initiate (ask questions) more and to learn the scientific process with science concepts. Implicitly, this learning may improve students' comparison in their writing. Moreover, high level teacher had a more structured and organized classroom than low level teacher.

Nox1 is of considerable importance because of its involvement in a wide variety of pathologies. Activation of Nox1 induces generation of reactive oxygen species (ROS) and cell migration, events critical for the pathogenesis of cardiovascular disease, amyotropic lateral sclerosis, gastrointestinal disease, immunological disorders, and multiple forms of cancer [1-8]. In order to best determine how to treat Nox1-mediated disease, we must gain a better understanding of the mechanisms that control Nox1 activation. Within the last decade, many studies have found that protein phosphorylation and protein trafficking are critical regulatory mechanisms that control the activation of multiple Nox proteins. Yet, to date, no studies have characterized Nox1 phosphorylation or trafficking. We hypothesized that the activity of Nox1 is controlled by its phosphorylation at specific residues and by its sub-cellular localization; and that modifying Nox1 phosphorylation or localization will alter Nox1-dependent signaling. To test this hypothesis, we utilized both in vivo and in vitro approaches. We found that phosphorylation of Nox1 is significantly increased under pathological conditions in three in vivo models: (1) in atherosclerotic vs. normal aorta from monkey, (2) in neointimal vascular smooth muscle cells (VSMCs) vs. medial VSMCs from rat following aortic balloon injury, and (3) in ligated vs. normal carotid from mouse. Studies using mass spectroscopy, pharmacological inhibition, siRNA, and in vitro phosphorylation identify PKC-βI as a kinase that mediates Nox1 phosphorylation and subsequent ROS production and VSMC migration. Site-directed mutagenesis of predicted Nox1 phospho-residues revealed that cells expressing mutant Nox1 T429A have a significant decrease in TNF-α-stimulated ROS production, VSMC migration and Nox1 NADPH oxidase complex assembly compared to cells expressing wild-type Nox1. Isothermal calorimetry (ITC) revealed that a peptide containing the Activation Domain of NoxA1 (LEPMDFLGKAKVV) binds to phosphorylated Nox1 peptide (KLK-phos-T(429)- QKIYF) but not non-phosphorylated Nox1 peptide. These findings indicate that phosphorylation of Nox1 residue T429 by PKC-βI promotes TNF-α-induced Nox1 NADPH oxidase complex assembly, ROS production, and VSMC migration. Nox1 localization and trafficking studies reveal that Nox1 endocytosis is necessary for TNF-α-induced Nox1 ROS production; and that mutation of a Nox1 VLV motif inhibits Nox1 endocytosis and ROS production. These studies have provided new evidence that phosphorylation and sub-cellular localization are involved in the regulation of Nox1 ROS production and cell migration and offer new insights as to how Nox1 activity can be targeted for the purpose of treating Nox1-mediated diseases.

Cardiovascular modeling has the capability to provide valuable information allowing clinicians to better classify patients and aid in surgical planning. Modeling is advantageous for being non-invasive, and also allows for quantification of values not easily obtained from physical measurements. Hemodynamics are heavily dependent on vessel geometry, which varies greatly from patient to patient. For this reason, clinically relevant approaches must perform these simulations on patient-specific geometry. Geometry is acquired from various imaging modalities, including magnetic resonance imaging, computed tomography, and ultrasound. The typical approach for generating a computational model requires construction of a triangulated surface mesh for use with finite volume or finite element solvers. Surface mesh construction can result in a loss of anatomical features and often requires a skilled user to execute manual steps in 3rd party software. An alternative to this method is to use a Cartesian grid solver to conduct the fluid simulation. Cartesian grid solvers do not require a surface mesh. They can use the implicit geometry representation created during the image segmentation process, but they are constrained to a cuboidal domain. Since patient-specific geometry usually deviate from the orthogonal directions of a cuboidal domain, flow extensions are often implemented. Flow extensions are created via a skilled user and 3rd party software, rendering the Cartesian grid solver approach no more clinically useful than the triangulated surface mesh approach. This work presents an alternative to flow extensions by developing a method of applying vessel inlet and outlet boundary conditions to regions inside the Cartesian domain.

The Middle Ordovician Ancell Group, including the St. Peter Sandstone, Glenwood Shale and Starved Rock Formation, records intracontinental basin development during eustatic sea level changes in Iowa and Illinois. The St. Peter Sandstone overlies the Prairie du Chien Group across an erosional unconformity that marks a major sequence boundary, whereas upper contact of the St. Peter Sandstone with the Glenwood Shale also is a second sequence boundary. Data from 80 wells, selected well logs, and 20 cores were integrated to refine the high-resolution sequence stratigraphy of the Ancell Group. Two main sequences bounded by three sequence boundaries are interpreted to represent 3rd order sequences. Distinctive shallowing-upward parasequences bounded by flooding surfaces in many cores record higher frequency relative sea level fluctuations in the Ancell Group, but these cannot presently be correlated regionally. Facies variations define an aggradational transgressive systems tract TST), a prograding highstand systems tract (HST) and down stepping falling stage system tract (FSST) in both the St. Peter Sandstone and the Glenwood Shale-Starved Rock Formation units. The St. Peter Sandstone thickens towards the northeast and thins to the northwest and southwest in Iowa. In contrast, the St. Peter Sandstone in Illinois thickens to the south likely recording a prolonged FSST incised valley or channel fill. Detrital zircon geochronology of 13 samples from the St. Peter Sandstone and Starved Rock Formation define common peaks at 1100-1500 Ma and 2500-2700 Ma with minor components at 1670-1750 Ma and 3000-3600 Ma. The detrital zircon signature is dominated by Archean, and Grenville (1000-1300 Ma) ages. The detrital zircon geochronology indicates that the Ancell Group was sourced directly from the Archean Superior Province to the north and Grenville Province to the northeast, although recycling of Archean grains from the Paleoproterozoic Huron Basin cannot be ruled out. The near complete lack of 1800-1900 Ma ages argues against derivation of detritus from the Trans-Hudson or Penokean Orogens. The Transcontinental Arch northwest of the Iowa Basin acted as a barrier to sediment transport from the Trans-Hudson Orogen. Basement rocks of the Penokean Orogen are inferred to have been covered by water or younger sediments southeast of the Iowa Basin. CIA analyses of Ordovician shale samples from around the Transcontinental Arch indicate that the climate condition during Middle Ordovician time was warm and humid. This is consistent with a paleoclimate interpretation where mechanical erosion and chemical weathering yielded first cycle mature quartz arenites (Witzke, 1980).

Degradation product toxicity is a critical quality issue for a small group of useful drug products--e.g. lidocaine, isoniazid, chlorhexidine, gabapentin. In the traditional risk assessment approaches, a no-observed-adverse-effect level (NOAEL) derived from animal data is determined with the use of generic (and arbitrary) uncertainty factors to obtain an acceptable daily intake. The effects of compound-specific biological complexities and pharmacokinetics are typically not part of the risk calculations. The selection of uncertainty factors that account for interspecies or intraspecies difference concerning biokinetics and biodynamics has also generally failed to consider chemical-specific mechanism information or pharmacokinetics data. The use of combining in-vitro biopharmaceutical characterization methods and physiologically-based pharmacokinetic modeling has undergone extensive study and validation for predicting clinical drug blood level time profiles. The rationale for the proposed research is that a PBPK modeling utilizing rat to human scaling for target tissue toxicity in combination with the Monte Carlo method for estimating human target exposure distributions provides a rational basis for assessing drug stability safety issues for drug substances that potentially degrade to toxic compounds. PBPK models for rats and humans were developed to simulate drug exposure time profiles after oral administration of model compounds including aniline, p-chloroaniline, 2,6-dimethylaniline, o-toluidine and p-aminophenol. The PBPK models were parameterized using a combination of literature values, computational models and standard in vitro experiments. Microsomal and hepatocyte metabolism studies were used to estimate the metabolic constants, and ultrafiltration was used to measure protein binding. Intestinal permeability was predicted using a set of related compound data to correlate measured Caco-2 permeability with molecular descriptors by multivariate regression. Sensitivity analyses were conducted to evaluate the impact of PBPK model parameters on plasma level predictions. To evaluate patient population effects on exposure profiles, the PBPK model parameters were varied in meaningful ways using Monte Carlo methods. Based on population PBPK models, distributions of target tissue exposure in rats and humans were simulated and compared to derive human safe dose. As results, rat PBPK model-predicted aniline concentration time profiles were in reasonable agreement with published profiles. Distributions of target tissue exposure in rats and humans were generated and compared based on a criterion. A human reference dose was then selected at a value of 1% criteria. This approach was compared to traditional risk assessment calculations. In conclusion, the PBPK modeling approach resulted in drug degradation product risk specifications that were less stringent than those estimated by conventional risk assessment approach. The PBPK modeling approach provides a rational basis for drug instability risk assessment by focusing on target tissue exposure and leveraging physiological, biochemical, biophysical knowledge of compounds and species.