CXCL9 Expression and Purification: Identifying Further Structural and Functional Relationships with Ligands

Chemokines are proteins that induce tissue extravasation, promote differentiation, and induce chemotaxis. Because of these properties, the chemokine’s role in antitumor immune response is of great interest to researchers. The CXCL9,10,11/CXCR3 axis is specific in that it regulates immune cell migration, differentiation, and activation, leading to tumor suppression. CXCL9 mainly mediates lymphatic infiltration to the focal sites and suppresses tumor growth. In this research, we expressed the novel CXCL9 protein within competent BL21 cells. Two variations of a pET22b plasmid were used, one with PelB (to cleave initial methionine on protein sequence) and one without. It was found that after induction, CXCL9 was expressed without the PelB leader sequence. From here we purified the CXCL9 protein and deduced that the overall expression of the protein was more than favorable. After isolating and concentrating the protein, a final concentration of 92 mg/ml was determined. With the purified protein, X-ray crystallographic studies will be used to determine the 3-D structure of the protein. This interface is important because it will impact the interaction with the receptor; therefore, altering the CXCL9/CXCR3 axis

A Framework for Statistical Modeling of Wind Speed and Wind Direction

Atmospheric near surface wind speed and wind direction play an important role in many applications, ranging from air quality modeling, building design, wind turbine placement to climate change research. It is therefore crucial to accurately estimate the joint probability distribution of wind speed and direction. This dissertation aims to provide a modeling framework for studying the variation of wind speed and wind direction. To this end, three projects are conducted to address some of the key issues for modeling wind vectors.\\ First, a conditional decomposition approach is developed to model the joint distribution of wind speed and direction. Specifically, the joint distribution is decomposed into the product of the marginal distribution of wind direction and the conditional distribution of wind speed given wind direction. Von Mises mixture model is used to accommodate the circular nature of wind direction. The conditional wind speed distribution is modeled as a directional dependent Weibull distribution via a two-stage estimation procedure, consisting of a directional binned Weibull parameter estimation, followed by a harmonic regression to estimate the functional dependence of the Weibull parameters on wind direction. The conditional decomposition approach allows the modeling of complex distributions with relatively simple and flexible univariate models. Moreover, by studying the variations of wind speed with respect to wind direction, we gain valuable insights that would be overlooked if we solely focused on studying wind speed alone. These insights have significant implications for a wide range of applications involving wind data. This conditional modeling framework is further extended to investigate the potential enhancement of estimating extreme wind speeds. Specifically, parametric extreme value modeling approaches, including block maxima, peaks-over-thresholds, and point process methods, are utilized to model the upper tail of its conditional distribution. The purpose of this extension is to avoid misspecification issues associated with the Weibull model and to improve estimation efficiency. Simulation studies, analysis of output from climate model simulation, and model comparisons are discussed.\\ A key feature of the wind field data is its complicated temporal and spatial structure. Therefore, the final goal of this dissertation involves the spatio-temporal modeling of wind speed. The proposed model captures the seasonal variation and temporal and spatial variability by decomposing the wind speed process into the ``global structure\u27\u27 of the spatio-temporal mean component, the ``local structure\u27\u27 that consists of a combination of time varying empirical orthogonal functions (EOFs), and a first-order dynamical spatial Gaussian process (GP). A crucial element of the proposed decomposition is leveraging the inherent circularity of the annual seasonal cycle to create effective replications in time. This enables us to employ more flexible nonstationary space-time modeling through EOF analysis and enhance computation efficiency using dynamical GPs

Developing Critical Social Justice Literacy in an Online Seminar

The purpose of this article is to report on an effort to cultivate a critical social justice perspective and critical social justice praxis among educators enrolled in an online graduate program. Although the entire program was organized around themes of equity, collaboration, and leadership, this study focused on educators’ perspectives of the purposes, pedagogy, and outcomes of one course, Critical Pedagogy. Fourteen of the 19 students enrolled in the online course participated in one of six online focus groups following the conclusion of the course. Using constructivist grounded theory methods, the researchers identified the different ways in which students responded to the course, what they learned, and how they enacted their learning as well as the features of the course that the students believed contributed to their learning and practice. The study provides insight into features of online pedagogy that appear to facilitate transformative learning. It further provides insight into the kinds of content and assignments that may promote critical social justice praxis among educators

Inclusive Design In Action – A Case Study Describing The Design Of Social Area Seating In A University

This practice paper outlines the inclusive design process used in the redesign of communal/social seating in an Engineering faculty in a University in Ireland. The old seating was not being utilised by the students. Engineering courses often present challenging assignments to students; literature shows that access to information, knowledge exchanges and opportunities for learning through social interaction can be crucial to student success. Equality, Diversity, and Inclusion (EDI) has grown as an important agenda item across society. Therefore, the methodology used in this redesign was inclusive design. Inclusive design is a design framework that takes into account the diversity of the human race and embraces co-design to ensure no one is excluded. It is “…not designing one product for all people; instead, it’s designing a diversity of ways to participate so that everyone has a sense of belonging”(Holmes 2018). The design team on this project was composed of a voluntary, diverse group of students and staff. The data collection methods employed was a design walk through of the University, a faculty-wide survey, and a design hackathon. The inclusive design process resulted in various social seating designs that addressed the needs of a broad range of users, including those with physical disabilities and sensory impairments. The final designs are available for perusal in Appendix 2, that show a more inclusive space for students and staff to interact and collaborate. The findings of this study highlight the importance of using an inclusive design process when designing academic environments. By involving a diverse group of stakeholders in the design process, the resulting spaces can better cater to the needs of all users. The recommendation is for other higher education institutions to consider implementing inclusive design principles in their design processes to ensure all members of their community are catered for, leading to a more inclusive and accessible academic environment for all

Final report: Member state and other donor approaches to good governance in development cooperation

This report presents an overview on approaches to governance-related issues and links with poverty reduction objectives of development cooperation among a sample of European Union (EU) Member States and other donors. The report forms part of a study commissioned by the European Community Poverty Reduction Effectiveness Programme (EC-PREP) to contribute to the definition of a consistent and common EU approach to governance related issues within the EC Directorate General Development (EC-DEV) initiative on Institutional Capacity Building. The Development Policy Coherence and Forward Studies unit within EC-DEV/B1 is coordinating this initiative. The report is divided into four main sections: Section 1: provides contextual information including study objectives, core good governance areas covered, study methodology and analytical framework used; Sections 2 & 3: provide summary profiles of both Member State and other donor approaches to good governance; Section 3: offers an analysis of emerging themes and issues arising from the donor profiles in line with the study objectives; Section 4: presents the study's main conclusions and recommendations

Neutral genomic microevolution of a recently emerged pathogen, salmonella enterica serovar agona

Salmonella enterica serovar Agona has caused multiple food-borne outbreaks of gastroenteritis since it was first isolated in 1952. We analyzed the genomes of 73 isolates from global sources, comparing five distinct outbreaks with sporadic infections as well as food contamination and the environment. Agona consists of three lineages with minimal mutational diversity: only 846 single nucleotide polymorphisms (SNPs) have accumulated in the non-repetitive, core genome since Agona evolved in 1932 and subsequently underwent a major population expansion in the 1960s. Homologous recombination with other serovars of S. enterica imported 42 recombinational tracts (360 kb) in 5/143 nodes within the genealogy, which resulted in 3,164 additional SNPs. In contrast to this paucity of genetic diversity, Agona is highly diverse according to pulsed-field gel electrophoresis (PFGE), which is used to assign isolates to outbreaks. PFGE diversity reflects a highly dynamic accessory genome associated with the gain or loss (indels) of 51 bacteriophages, 10 plasmids, and 6 integrative conjugational elements (ICE/IMEs), but did not correlate uniquely with outbreaks. Unlike the core genome, indels occurred repeatedly in independent nodes (homoplasies), resulting in inaccurate PFGE genealogies. The accessory genome contained only few cargo genes relevant to infection, other than antibiotic resistance. Thus, most of the genetic diversity within this recently emerged pathogen reflects changes in the accessory genome, or is due to recombination, but these changes seemed to reflect neutral processes rather than Darwinian selection. Each outbreak was caused by an independent clade, without universal, outbreak-associated genomic features, and none of the variable genes in the pan-genome seemed to be associated with an ability to cause outbreaks

Comparison of Wild-Type versus Mutant L1CAM Expression in Cultured Neurons

The correct targeting of proteins to axons and dendrites of neurons is essential for the proper development of the nervous system. L1CAM is a cell-adhesion molecule responsible for multiple aspects of neuronal development; mutations are known to result in a developmental syndrome characterized by cognitive and motor disabilities. We expressed wild-type L1CAM and known L1CAM mutant proteins, P941L and D544N, in cultured embryonic chick forebrain neurons and compared their cellular distributions. Preliminary data suggests that both the wild-type L1CAM and the P941L L1CAM mutant are targeted to axons in a similar fashion. In contrast, the D544N L1CAM mutant does not appear to reach the cell surface of the neuron

Joint modeling of wind speed and wind direction through a conditional approach

Atmospheric near surface wind speed and wind direction play an important role in many applications, ranging from air quality modeling, building design, wind turbine placement to climate change research. It is therefore crucial to accurately estimate the joint probability distribution of wind speed and direction. In this work we develop a conditional approach to model these two variables, where the joint distribution is decomposed into the product of the marginal distribution of wind direction and the conditional distribution of wind speed given wind direction. To accommodate the circular nature of wind direction a von Mises mixture model is used; the conditional wind speed distribution is modeled as a directional dependent Weibull distribution via a two-stage estimation procedure, consisting of a directional binned Weibull parameter estimation, followed by a harmonic regression to estimate the dependence of the Weibull parameters on wind direction. A Monte Carlo simulation study indicates that our method outperforms an alternative method that uses periodic spline quantile regression in terms of estimation efficiency. We illustrate our method by using the output from a regional climate model to investigate how the joint distribution of wind speed and direction may change under some future climate scenarios.Comment: 29 pages, 15 figure