Membrane Forces and Key Protein Determinants of Hematopoietic Cell Function: Lamins and Myosin-II in Hematopoiesis and CD47 in Immunotherapy of Cancer

Hematopoiesis in human bone marrow generates every second about 105 – 106 anucleated platelets and red blood cells as well as nucleated white blood cells that are capable of infiltrating distant tissues. The thesis begins in the marrow with a description of (1) nuclear membrane ‘lamina’ physicochemical properties that influence marrow-to-circulation trafficking, and proceeds to detail (2) the physicochemical roles of membrane cortex ‘myosin’ in key marrow processes of motility and division as well as platelet biogenesis and disease. The thesis finishes with (3) studies of macrophages in peripheral tissues far from the marrow and aspects of how such cells distinguish ‘foreign’ cells from ‘self’ cells. Collaborative studies show the lamin–A:B ratio controls nuclear viscoelasticity and in turn cell trafficking relevant to marrow escape. Additionally, differential lamin expression can direct erythroid and megakaryocyte differentiation. Secondly, xenografts show that MIIB is required for blood cell generation, while MIIA is required for long–term HSC/P engraftment. MII inhibition by blebbistatin prior to xenotransplantation enriches for long–term hematopoietic multilineage reconstituting cells, and also multi–nucleated megakaryocytes. Cone and plate rheometry demonstrates an optimal shear stress for platelet–like–particle generation from MKs that is enhanced by MII inhibition, and that MIIA heavy chain phosphorylation at S1943 is shear sensitive. Micropipette aspiration of MKs with mutations of the MIIA gene, MYH9, recapitulates MYH9–RD macrothrombocytopenia. Comparing MYH9–RD patient and normal donor platelets shows a similarity in pre/pro-platelets when normals are treated with blebbistatin. These findings provide evidence that regulation of MIIA activity through S1943 phosphorylation is critical to proper MK fragmentation and proplatelet fission to generate platelets of normal size and number. The dissertation concludes with an investigation of an immunotherapy approach to treat peripheral solid tumors by controlling tumor cell CD47 expression and administering an anti–human polyclonal IgG antibody. These in vivo xenograft models provide a mechanism of selective tumor clearance driven by FcR stimulation of macrophages. In all, this work highlights biophysical factors of cortical and nuclear membranes that govern hematopoietic differentiation and trafficking, normal and pathological thrombopoiesis, and a mechanism of phagocytic clearance of cancer cells through CD47 attenuation and species specific but epitope non–specific antibody infusion

Organizational perspectives on co-teaching triads participating in a science and engineering professional development program

Co-teaching triads composed of grades 3-5 cooperating/student teacher dyads and an engineering graduate student were formed; triads met once per week to collaboratively plan and implement science and engineering lessons. Sharp distinctions in elementary school classroom teaching experience and knowledge of science and engineering content were present in these triads. The purpose of this dissertation was to better understand how participants’ educational and professional backgrounds interacted in the context of the classroom. Research on co-teaching dyads may inform studies of the performance and relational aspects of co-teaching triads, but may not be fully capable of addressing the potential complexities related to three-person group dynamics and asymmetries in distribution of knowledge and skill. In the first study, literature from the areas of research in co-teaching and small group dynamics was synthesized to create a conceptual framework for understanding the nature of co-teaching triad structure and tasks and internal and external factors that may impact triad performance. The second study investigated the roles played by members of the science and engineering co-teaching triads using a multiple case study approach. Data for this study was collected in participant interviews and during observations of collaborative planning meetings and co-taught lessons. Results of this study indicate that triad members took on roles related to their identity within their triads. Conflicting understandings of the role of teachers and content knowledge in elementary science and engineering education may have led to role conflict in some triads. Further, opportunities for participant professional growth may have been impacted by the unique composition of the triads. The final study investigated the team effectiveness of the co-teaching triads. Team effectiveness is a multi-dimensional construct reflecting the degree of performance quality achieved by a team and team member attitudinal and satisfaction-related perspectives. Specifically, this study operationalized team effectiveness as triads’ composite scores on a science lesson evaluation instrument and aggregated triad member satisfaction ratings related to triad lesson planning and implementation activity. Results indicate that triad team effectiveness was impacted by the extent to which triads engaged in surfacing student prior knowledge, use of evidence, and sense making of targeted ideas

Midwest Opportunity Zones: A Regional and Comparative Analysis of Tract Selection

Opportunity Zones were implemented within the Tax Cuts and Jobs Act of 2017 to bring jobs and investment to low-income communities. States were given authority to choose which of their census tracts would be given Opportunity Zone status, and previous research has been conducted to investigate if selected tracts were the ones with the most distress. This study expands upon past national research to investigate state-level Opportunity Zone tract selections and processes by using a sample of seven Midwest states. The results provide an explanation for national studies seeing variance in levels of Opportunity Zone distress by state, and it found that states had differing selection processes, goals in tract selection, and levels of initial distres

Shortening Delivery Times by Predicting Customers' Online Purchases: a Case Study in the Fashion Industry

Online retailers still struggle with the disadvantage of delivery times compared to traditional brick and mortar stores. With the emergence of big data analytics, it has become possible to extract meaningful knowledge from the volume of data that online retailers collect on their website. Nevertheless, limited research exists that investigates how this data can be used to optimize delivery times for customers. The goal of this paper is to develop a prediction model for anticipatory shipping, which predicts customers' online purchases with the aim of shipping products in advance, and subsequently minimize delivery times. Different forecasting methods in combination with k-means clustering are applied to test if, and how early, it is possible to predict online purchases. Results indicate that customer purchases are, to a certain extent, predictable, but anticipatory shipping comes at a high cost due to wrongly sent products. The proposed prediction model can easily be implemented and used to predict purchases, which can also be leveraged for other areas of application besides anticipatory shipping

Novel Data Analytics Meets Conventional Container Shipping: Predicting Delays by Comparing Various Machine Learning Algorithms

Supply chain disruptions are expected to significantly increase over the next decades. In particular, delay of container vessels is likely to escalate due to rising congestion from continued growth of container shipping and higher frequency of extreme weather events. Predicting these delays could result in significant cost savings from optimizing operations. Both academic research and container shipping industry, however, lack analytical solutions to predict delay. To increase transparency on delay, we develop a prediction model based on 315 explanatory variables, 10 regression models, and 7 classification models. Using machine learning algorithms, we obtain best results for neural network and support vector machine with a prediction accuracy of 77 percent compared to only 59 percent of a naive baseline model. Various shipping players including sender, carrier, terminal operator, and receiver benefit from the easy-to-use prediction model to optimize operations such as buffers in schedules and the selection of ports and routes

Shortening Delivery Times by Predicting Customers\u27 Online Purchases: a Case Study in the Fashion Industry

Online retailers still struggle with the disadvantage of delivery times compared to traditional brick and mortar stores. With the emergence of big data analytics, it has become possible to extract meaningful knowledge from the volume of data that online retailers collect on their website. Nevertheless, limited research exists that investigates how this data can be used to optimize delivery times for customers. The goal of this paper is to develop a prediction model for anticipatory shipping, which predicts customers\u27 online purchases with the aim of shipping products in advance, and subsequently minimize delivery times. Different forecasting methods in combination with k-means clustering are applied to test if, and how early, it is possible to predict online purchases. Results indicate that customer purchases are, to a certain extent, predictable, but anticipatory shipping comes at a high cost due to wrongly sent products. The proposed prediction model can easily be implemented and used to predict purchases, which can also be leveraged for other areas of application besides anticipatory shipping

Capacity market design options: a dynamic capacity investment model and a GB case study

Rising feed-in from renewable energy sources decreases margins, load factors, and thereby profitability of conventional generation in several electricity markets around the world. At the same time, conventional generation is still needed to ensure security of electricity supply. Therefore, capacity markets are currently being widely discussed as a measure to ensure generation adequacy in markets such as France, Germany, and the United States (e.g., Texas), or even implemented for example in Great Britain. We assess the effect of different capacity market design options in three scenarios: 1) no capacity market, 2) a capacity market for new capacity only, and 3) a capacity market for new and existing capacity. We compare the results along the three key dimensions of electricity policy ��� affordability, reliability, and sustainability. In a Great Britain case study we find that a capacity market increases generation adequacy since it provides incentives for new generation investments. Furthermore, our results show that a capacity market can lower the total bill of generation because it can reduce lost load and the potential to exercise market power. Additionally, we find that a capacity market for new capacity only is cheaper than a capacity market for new and existing capacity because it remunerates fewer generators in the first years after its introduction.renewable energy source

Effects of lactation and nursery diets supplemented with a feed flavor and increasing tryptophan:lysine ratio in DDGS based diets with or without a DDGS withdrawal strategy in growing-finishing pigs

Master of ScienceDepartment of Animal Sciences and IndustryMajor Professor Not ListedThe first chapter of this thesis analyzed the effects of a feed flavor in the sow lactation and nursery diets on sow feed intake and lactation performance and subsequent weaned pig nursery performance. A total of 105 sows were used across four batch farrowing groups. Dietary treatments included a standard corn-soybean-based lactation diet or the control diet with the addition of a feed flavor included at 0.05% of the diet. Overall, sows fed the flavor treatment had a tendency for greater ADFI compared with control sows. In the nursery portion of the study, 360 weaned pigs were used in a 2 × 2 factorial with main effects of previous sow feed flavoring treatment (control vs flavor) and nursery diets formulated with or without a feed flavor on growth performance in a 38-d trial. Offspring from sows fed the flavor diet were heavier at weaning which was maintained throughout the study. Overall, progeny from sows fed a diet containing a feed flavor had greater ADG, ADFI, and final BW during the trial, but the presence of a feed flavor in the nursery did not improve overall nursery performance. The second chapter compared increasing tryptophan:lysine ratios in DDGS-based diets with or without a DDGS withdrawal strategy on growth performance and iodine value of growing-finishing pigs. A total of 6,240 finishing pigs, divided into 2 groups, were used in a 119 or 120 d study. Pigs were allotted to 1 of 7 treatments consisting of a control corn-soybean meal-based diet formulated to a 19% standardized ileal digestibility Trp:Lys ratio, 4 diets with 30% DDGS fed in all four phases, and formulated to provide SID Trp:Lys ratios of 16, 19, 22, or 25%, and 2 DDGS withdrawal strategy diets with 19% SID Trp:Lys with 30% DDGS in phase 1 through 3 and then 0% DDGS in phase 4 with either a 19 or 25% Trp:Lys ratios. Increasing the SID Trp:Lys ratio in diets with 30% DDGS resulted in a linear increase in ADG, ADFI, G:F, and BW but did not influence carcass fat IV. Removing DDGS from the diet in the last period reduced carcass fat IV and increased growth rate during the withdrawal period compared to pigs fed 30% DDGS throughout, indicating value in a withdrawal strategy

Lactobacillus rhamnosus L34 and Lactobacillus casei L39 suppress Clostridium difficile-induced IL-8 production by colonic epithelial cells

BACKGROUND: Clostridium difficile is the main cause of hospital-acquired diarrhea and colitis known as C. difficile-associated disease (CDAD).With increased severity and failure of treatment in CDAD, new approaches for prevention and treatment, such as the use of probiotics, are needed. Since the pathogenesis of CDAD involves an inflammatory response with a massive influx of neutrophils recruited by interleukin (IL)-8, this study aimed to investigate the probiotic effects of Lactobacillus spp. on the suppression of IL-8 production in response to C. difficile infection. RESULTS: We screened Lactobacillus conditioned media from 34 infant fecal isolates for the ability to suppress C. difficile-induced IL-8 production from HT-29 cells. Factors produced by two vancomycin-resistant lactobacilli, L. rhamnosus L34 (LR-L34) and L.casei L39 (LC-L39), suppressed the secretion and transcription of IL-8 without inhibiting C. difficile viability or toxin production. Conditioned media from LR-L34 suppressed the activation of phospho-NF-κB with no effect on phospho-c-Jun. However, LC-L39 conditioned media suppressed the activation of both phospho-NF-κB and phospho-c-Jun. Conditioned media from LR-L34 and LC-L39 also decreased the production of C. difficile-induced GM-CSF in HT-29 cells. Immunomodulatory factors present in the conditioned media of both LR-L34 and LC-L39 are heat-stable up to 100°C and > 100 kDa in size. CONCLUSIONS: Our results suggest that L. rhamnosus L34 and L. casei L39 each produce factors capable of modulating inflammation stimulated by C. difficile. These vancomycin-resistant Lactobacillus strains are potential probiotics for treating or preventing CDAD

Sustainable Operations Management: An Enduring Stream or a Passing Fancy?

Paul Kleindorfer was among the first to weigh in on and nurture the stream of Sustainable Operations Management. The thoughts laid out here are based on conversations we had with Paul relating to the drivers underlying sustainability as a management issue: population and per capita consumption growth, the limited nature of resources and sinks, and the responsibility and exposure of firms to ensuing ecological risks and costs. We then discuss how an operations management lens contributes to the issue and criteria to help the Sustainable Operations Management perspective endure. This article relates to a presentation delivered by Morris Cohen for Paul's Manufacturing and Service Operations Management Distinguished Fellows Award, given at Columbia University, June 18, 2012. We wrote this article at Paul's request