University of Illinois at Chicago
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Criminalidad y Democracia en América Latina
No full textEn la última década, el crimen organizado ha dejado de ser un fenómeno localizado para convertirse en una amenaza estructural a las democracias de América Latina. Redes criminales diversificadas y adaptativas influyen en la economía, la política y la vida cotidiana, erosionando el Estado de derecho y debilitando la gobernabilidad. Este informe de IDEA Internacional ofrece un marco analítico para entender la “política criminalizada” y su impacto en las instituciones democráticas. Plantea estrategias para fortalecer la transparencia, la justicia y la cooperación regional, promoviendo respuestas a la inseguridad basadas en derechos humanos y en la resiliencia democrática.</p
TENDENCIAS MIGRATORIAS EN AMÉRICA Y PERSPECTIVAS PARA LA PRÓXIMA DÉCADA
No full textEl artículo presenta una breve reflexión sobre las tendencias migratorias actuales en las Américas. La reflexión analiza los cambios en la naturaleza, el volumen, la dinámica y la política de la migración y aborda algunas consecuencias no deseadas relacionadas con ellos. A partir del examen de las condiciones actuales, profundizamos en los retos apremiantes que se vislumbran en el horizonte y que, según suponemos, determinarán la labor de la Congregación de las Hermanas de San Scalabrini en los próximos años.</p
<i>Toxic Masterpiece: The Art of Pollution in the Chicago River</i>
No full textThis iconic image might look like a mesmerizing piece of abstract art, but it tells a deeper story of pollution and environmental challenges. The vibrant colors on the water’s surface result from hydrophobic pollutants, such as oils, petroleum, and other chemicals, brought up from contaminated sediment (the soil underneath a waterway) by gas ebullition. Gas ebullition is a process where bubbles form in organic rich muddy sediment and rise to the surface, carrying pollutants with them. This beautiful photo captures a part of the Chicago River where gas ebullition is very active because of sediment contamination caused by historical industrial activity and organic waste buildup. This creates ideal conditions for gas ebullition, and the resulting colorful displays. During my PhD fieldwork, I took an image showcasing the beautiful warning signals of nature. My research focuses on developing predictive models for gas ebullition using advanced machine learning techniques. This work is essential for improving sediment management and clean up in our waterways.</p
<i>Correspondences</i>
No full textThis image of research, 'Correspondence,' uses my examination of my family's archive to create a large-scale interdisciplinary artwork and poetry palimpsest. I have investigated the text that relates to the diasporic life after my family's escape, survival and loss in the Holocaust. I have scanned textual fragments and projected them onto a paper scroll to enable the retracing of selected passages. By enlarging and elevating the font, the text, and the specific turn of phrase that we see in this myriad of personal and bureaucratic archival materials, I'm intrigued by how these simple pieces of paper, hand-marked or typed, contain multiple layers of meaning and can end up being life and death, truth and despair. Through my artistic dialogue with the texts, I repeat, reorganise and rewrite lines drawn from the archive, creating multiple layers that form an image unto themselves and, at times, reach for the abyss. These are love letters, letters of concern and safety; sometimes, the letters intermingle until they become conversations with themselves. I made this piece using three letters from the archive, two relating to my grandparents' escape from Germany to South Africa and the other letter detailing the German Jewish story of my family.</p
Multi-Omic Approaches Reveal Novel Targets and Mechanisms in Intestinal Inflammation and Gut-Liver Axis
No full textDue to rapid advances in sequencing technology, multi-omic approaches integrating RNA sequencing, shotgun metagenomics, 16S rRNA sequencing, and metabolomics have emerged as appealing options for the study of complex disorders in the gut-liver axis due to their ability to generate large amounts of high-throughput data in a relatively short period of time. These approaches are especially attractive in the gut-liver axis as we are learning more about the roles of the gut microbiome in the development of such diseases such as inflammatory bowel diseases, alcoholic liver disease, and non-alcoholic liver disease.
Inflammatory bowel diseases (IBD) and alcoholic liver disease (ALD) are complex disorders which present several challenges to public health. Some common factors in both diseases include the involvement of intestinal functions such as impairment of intestinal barrier function, and gut microbial dysbiosis. We investigated the pathophysiology of both diseases through the integration of biochemical approaches with transgenic animal models, the use of metabolomics, and bioinformatic analysis.
The downregulation of SLC6A4, otherwise known as the serotonin transporter (SERT), has been implicated in IBD patients and in pre-clinical models of IBD. While SERT is emerging as a novel therapeutic target for gut disorders, its underlying mechanisms remain unclear and were the scope of the first aim of this work as presented in Chapter II. In order to investigate the mechanisms of SERT downregulation in intestinal inflammation, we utilized SERT KO mice as well as a newly generated model for intestinal epithelial cell specific SERT overexpression (SOEΔIEC). We performed serum and fecal metabolomics in SERT KO mice subjected to chronic DSS colitis and found diminished intestinal barrier function in SERT KO mice during inflammatory insult, basal metabolic profiles resembling those of WT mice with chronic colitis, and changes in microbial metabolites that corresponded to disease severity. Further, we found in a proof of concept that IEC SERT overexpression conferred protection against intestinal inflammation.
Regarding ALD, recent studies have begun to explore the roles of the aryl hydrocarbon receptor (AhR), an environmental sensing transcription factor, in the pathogenesis of alcohol mediated liver injury due to the roles of AhR in the maintenance of intestinal barrier function. It is also worth noting that our group has recently uncovered that serotonin, or 5-HT is an indirect activator of AhR. In Chapter III, our preliminary studies have shown that a loss of intestinal epithelial cell AhR is protective towards the development of alcohol induced liver injury in female mice, with significant clinical implications given that women have a higher susceptibility to the development of ALD. In parallel, we have also utilized metabolomic approaches in the serum of a cohort of ALD patients with and without cirrhosis at the University of Illinois Hospital (UIH). Our studies have corroborated previous metabolomic studies in patients with ALD while contributing novel findings such as increases in the microbial metabolite methionine sulfoxide and decreases in guanosine. Furthermore, we were able to construct multiple linear regression models containing patient demographic, clinical, and metabolite data that were predictive of fibrosis stage. Finally, we were able to construct receiver operator curves for the measured metabolites and also found several candidate biomarkers with potential for the diagnosis of cirrhosis which is often diagnosed once patients have uncompensated cirrhosis with severe clinical complications.
This work demonstrates the utility of utilizing multiple approaches for the investigation of complex diseases in the gut-liver axis. This work has shown the benefits of integrating novel, cell-specific, inducible transgenic mouse models, with broad scale metabolomics and bioinformatics. With these tools, we were able to gain mechanistic insight into how SERT deficiency leads to increased intestinal inflammation, discover a potential new treatment strategy for IBD in the form of intestinal epithelial SERT overexpression, find a protective role for the loss of intestinal epithelial cell AhR in the development of alcohol mediated liver injury in females, and contribute to the relatively few metabolomic studies of patients with alcoholic cirrhosis with the identification of new potential biomarkers for identifying those with severe disease
Automata Minimization and Beyond: A Systematic Evaluation of DFA-based Pattern Matching
No full textPattern-matching based on Regular Expressions (REs) is crucial in several applications, including network intrusion detection, Deep Packet Inspection (DPI), genome analysis, spam filters, database queries, and natural language preprocessing. Finite State Automata (FSAs) are a representation with equivalent power to REs commonly employed to analyze patterns against data efficiently. FSAs can be divided into two macro categories: Deterministic Finite State Automata (DFAs) and Non-Deterministic Finite State Automata (NFAs). The former ensures bounded execution times at the cost of state-explosion issues – as they have a larger memory footprint – while the latter significantly reduces memory usage but demands higher throughput capability in the processing engine. In this context, numerous works aim at compressing DFAs to reduce their memory footprint while exploiting their attractive computation characteristics. These compressed DFAs often require modifying their execution algorithm to perform pattern matching on a data stream with new automata representation. However, most of these techniques focus on state and transition compression, potentially lacking a thorough evaluation of the impact the compression has when running the modified execution algorithms. This thesis proposes a new framework to systematically analyze two classes of highly effective DFA-compression algorithms stressing their impact on pattern-matching execution. Firstly, this thesis characterizes the most impacting DFA-based compression techniques regarding state compression, transition compression, and compression time. Then, it thoroughly assesses the memory footprint and execution time of pattern-matching applications exploiting these compression algorithms across modern benchmarks and architectures, thus enriching the analysis proposed in previous works. With this in-depth evaluation, this thesis clarifies the tradeoff between memory compression and the execution impact of DFA-based compression algorithms in a modern context, supporting the design of ad-hoc pattern matching engines
Mechanistic Understanding of Synthesis Pathways of Porous Crystalline Frameworks (MOFs & COFs)
No full textThe exponential progression of material discovery has catalyzed a series of important and exceptional breakthroughs in addressing climate changes, driving manufacturing advancements, and pioneering medicinal breakthroughs. Dedicated efforts have been deployed towards navigating the intricacies of synthesizing nanomaterials with precision, while tuning their properties to align with the requirements of their intended applications. It is essential to have a profound understanding of the fundamental configuration and formation of these materials to smoothen the “tuning” effort, since the molecular configurations dictate their functionality. The primary focus of this work revolves around delving into the core principles of chemistry, synthesizing techniques, and precisely controlling the physical and chemical attributes of porous crystalline frameworks
Optimizing Channels for Non-dispersive Infrared Sensors for Fuel Property Prediction
No full textThe variability of jet fuels, amplified by the increasing use of Sustainable Aviation Fuels (SAFs), presents significant challenges for ensuring consistent engine performance and operational efficiency. Key properties such as Derived Cetane Number (DCN) and density directly impact engine control, fuel-air mixing, and combustion stability. DCN, which measures ignition propensity, is critical for optimizing parameters like injection timing and pressure, especially in engines operating with SAFs that exhibit a wider property range than conventional fuels. Similarly, fuel density influences energy content, atomization, and emissions, making its accurate measurement essential for fuel loading and flight performance.
Traditional methods for measuring DCN and density, such as the Ignition Quality Tester (IQT) and oscillating U-tube method, rely on large, benchtop systems unsuitable for real-time or onboard applications. To address this limitation, this dissertation explores the development of miniaturized, real-time fuel property sensors using Non-Dispersive Infrared (NDIR) spectroscopy. Advances in Filter Array Detector Array (FADA) technology enable NDIR systems to achieve narrow-channel infrared measurements, detecting key functional groups responsible for DCN and density. This research focuses on optimizing spectral channel selection to enhance prediction accuracy while adhering to size, weight, and power (SWaP) constraints.
The proposed system integrates NDIR-based sensors with feed-forward engine control models to ensure efficient and adaptable operation across diverse fuel types, including SAFs. This work provides a foundation for compact, high-performance fuel sensors that enable next-generation aviation engines to operate reliably in a variable and multi-fuel environment
Chemical Exposures and Epidermal Growth Factor-mediated Placental Cell Dysfunction
No full textPlacental development is essential for fetal growth, with the epidermal growth factor receptor (EGFR) playing a critical role in trophoblast cell functions such as proliferation, fusion, and invasion. Dysfunction in EGFR signaling has been linked to pregnancy complications like preeclampsia and intrauterine growth restriction. Environmental chemical, including polychlorinated biphenyls (PCBs), bisphenols, and pesticides, are known to interfere with EGFR activation, potentially affecting placental function.
This study explores the effects of a mixture of EGFR-disrupting chemicals (Chem-Mix), including PCB-126, PCB-153, atrazine, bisphenol S, trans-nonachlor, and niclosamide, on placental trophoblast cells. The impact of Chem-Mix on EGFR activation, trophoblast cell functions (proliferation, invasion, and differentiation), and placental bioenergetics was evaluated using HTR-8/SVneo cells and third-trimester human primary cytotrophoblasts. Methods included EGFR binding assays, RNA sequencing, mitochondrial and glycolytic stress tests, ATP production, glucose consumption, and super-resolution imaging. Additionally, first-trimester placental villus explants exposed to Chem-Mix were analyzed for cytokine, human chorionic gonadotropin (hCG), and soluble fms-like tyrosine kinase-1 (sFlt-1) secretion.
Chem-Mix competed with EGF for EGFR binding and reduced EGFR phosphorylation in a dose-dependent manner, impairing trophoblast cell invasion independent of EGF. The mixture altered mitochondrial function by diminishing the maximum respiratory capacity and ATP production in a dose-dependent manner. While EGF increased oxygen consumption and glycolytic acidification, Chem-Mix reduced both EGF-mediated and basal bioenergetic functions. Super-resolution imaging revealed a disruption in mitochondrial network architecture, supported by a decrease in the mitochondrial fusion protein OPA1. RNA sequencing further showed changes in the transcriptional profile of genes involved in cellular energetics. Cytokine analysis of placental villus explants showed altered secretion of IL-1RA, IL-27, EGF, and Fractalkine by the Chem-Mix in an EGF-dependent manner. Concentrations of hCG and sFlt-1 decreased with gestational age, with reduced concentrations by Chem-Mix plus EGF and these effects were sex specific.
Exposure to a mixture of EGFR-disrupting chemicals alters placental function, bioenergetics, and secretory profiles during early pregnancy, potentially contributing to adverse pregnancy outcomes. These findings underscore the need for further research into the mechanisms of chemical-induced disruptions in placental development and the implications for pregnancy health
Corrosion Inhibition of Orthopedic Implants with Antioxidants
No full textThe demand for orthopedic implants will continue to rise, as millions of people need it to alleviate pain and increase mobility concerns lost due to joint related disorders. Though largely successful, cases of implant failure remain as cases of aseptic loosening and periprosthetic osteolysis resulting from wear particles and metal ions accelerate harmful processes that detach the implant from its environment. Wear particles and metal ions are degradation products resulting from processes like corrosion. To lessen the concern of corrosion for titanium and other metallic implants, antioxidants that are anti-inflammatory in nature are being researched as potential corrosion inhibitors. In this study, vitamin E and curcumin are present in solutions of bovine calf serum (BCS) at different concentrations of 0.05, 0.5, and 1.0 µg/mL to test the corrosion resistance of Ti-6Al-4V samples. The aims of this project include the assessment of vitamin E as a corrosion inhibitor, the evaluation of curcumin as a corrosion inhibitor, and the determination of curcumin or vitamin E as the more effective corrosion inhibitor. By using electrochemical corrosion characterization and surface characterization methods such as Scanning Electron Microscopy (SEM) and 3D profilometry, the effect of these antioxidants as corrosion inhibitors will be evaluated and compared based on parameters such as corrosion current density, corrosion potential, polarization resistance, and double layer capacitance values, as well as surface roughness and inhibition efficiency. The novelty in this work is that corrosion research has not been done so far with vitamin E, curcumin, and titanium samples in a small range (µg/mL). Our results showed that both higher concentrations of curcumin and vitamin E present in BCS displayed more corrosion resistance and higher inhibitor efficiencies compared to the control. It is hypothesized that curcumin and vitamin E formed protective films on the Ti-6Al-4V surface, but curcumin had the greater protection in lower concentrations than vitamin E, awarding it as the more effective inhibitor. More research is needed to further investigate concentrations of vitamin E and curcumin to increase inhibitor efficiencies, as well as performing toxicity tests, and exploring methods to incorporate antioxidants into implant design
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