The Potential of Intrinsically Disordered Proteins as Drug Targets

Tumor necrosis factor α-induced protein 3-interacting protein 1 (TNIP1) is a negative regulator of inflammatory signaling in several diseases. TNIP1 is also an intrinsically disordered protein (IDP), which makes it difficult for current drugs to affect it. More research on IDPs could lead to novel drugs targeting TNIP1, leading to improved therapies for patients with acute and chronic inflammatory diseases. The main difference between IDPs and the more common ordered proteins is that IDPs are flexible, a characteristic of TNIP1 which was demonstrated in this study via protease sensitivity. Ordered proteins are rigid, which means that they only have one well-defined three-dimensional structure. The flexibility of IDPs allows them to have multiple conformations that they can switch between quite easily. However, switching between conformations makes it much harder to solve for the structure of an IDP. Since developing drugs relies heavily on knowing a protein’s structure, IDPs have not yet been common therapeutic targets. Several screening approaches for new IDP-targeting drugs are considered here, including those driven by artificial intelligence. There have been some reports of successful small molecule screens, but finding a universal technique is still in high demand. Currently, it is thought that drugs binding to multiple conformations of IDPs may be beneficial over a drug only binding a single conformation. Since 20-30% of the proteins in our body are IDPs, continued characterization of IDPs could lead to better drug designing methods, more structural information about TNIP1, and a better multifaceted approach for treating psoriasis, cancer, Parkinson’s disease, ischemic vascular diseases, and beyond

Identification, analysis and inference of point mutations associated to drug resistance in bacteria: a lesson learnt from the resistance of Streptococcus pneumoniae to quinolones

Antibiotic resistance is one of the biggest public health challenges of our time. Bacterial chemoresistance is the phenomenon whereby bacteria develop the ability to survive and multiply in the presence of an antibacterial drug; the expression of a resistant phenotype may be due to three fundamental mechanisms, including the expression of enzymes that inactivate the antibacterial drug, changes in the membrane permeability to antibiotics and the onset of point mutations causing the physical-chemical alteration of the antimicrobial targets. In recent decades, new antibiotic resistance mechanisms have emerged and are spreading globally, threatening human health and the ability to fight the most common infectious diseases. Quinolones, a novel class of antibiotics that bind bacterial topoisomerases and inhibit cell replication, have been important in limiting the spread of penicillin- and macrolides-resistant Streptococcus pneumoniae. However, alarmingly, resistance to quinolones is spreading recently. Resistance is caused by the appearance of point mutations in the bacterial topoisomerase and gyrase. Some mutations are well known, but some are not and the information about known molecular mechanisms causing resistance is sparse and not systematically collected and organised. This means that it cannot be used to infer new mutations in newly sequenced bacterial genes and study how they may affect the drug binding. The lack of structured, organized, and reusable information about point mutations associated with antibiotic resistance represents a critical issue and is a common pattern in the field. Here, we present a structural analysis of point mutations involved in the resistance to quinolones affecting the gyrase and topoisomerase genes in Streptococcus pneumoniae. Results, extended to other bacterial species, have been collected in a database, Quinores3D db, and can now be used – through a web server, Quinores3D finder - to analyze both known and yet unknown mutations occurring in bacterial topoisomerases and gyrases. The development, testing and deployment of Quinores3D db and Quinores3D finder are further results of this PhD thesis. Furthermore, structural data about point mutations associated with antibiotic resistance were used to train, test and validate a machine learning algorithm for the inference of still unknown mutations potentially involved in bacterial resistance to quinolone. As the performance of the algorithm, measured in terms of accuracy, sensitivity and specificity, is very promising, we plan to incorporate it in the web server to allow users to predict new mutations associated with bacterial resistance to quinolones

Wind tunnel performance tests of coannular plug nozzles

Wind tunnel performance test results and data analyses are presented for dual-flow plug nozzles applicable to supersonic cruise aircraft during takeoff and low-speed flight operation. Outer exhaust stream pressure ratios from 1.5 to 3.5 were tested; inner exhaust stream conditions were varied from very low, or bleed flow rates, up to a pressure ratio of 3.5. Mach numbers tested ranged from zero to 0.45. Measured thrust coefficients for the eight model configurations, operating at an external Mach number of 0.36 and an outer flow pressure ratio of 2.5, varied from 0.95 to 0.974 for high inner flow rates. At low inner flow, the performance ranged from 0.88 to 0.97 for the same operating conditions. The primary design variables influencing the performance levels were the annular height of the inner and outer nozzle throats (denoted by radius ratio - the ratio of inner-to-outer flowpath diameter at the nozzle throat), the plug geometry, and the inner stream flow rate

Acoustic and aerodynamic performance investigation of inverted velocity profile coannular plug nozzles, comprehensive data report, volume 2

Volume 2 of a three volume report is presented. Volume 2 presents acoustic data comparisons in graphic form

Acoustic and aerodynamic performance investigation of inverted velocity profile coannular plug nozzles

The results of model scale parametric static and wind tunnel aerodynamic performance tests on unsuppressed coannular plug nozzle configurations with inverted velocity profile are discussed. The nozzle configurations are high-radius-ratio coannular plug nozzles applicable to dual-stream exhaust systems typical of a variable cycle engine for Advanced Supersonic Transport application. In all, seven acoustic models and eight aerodynamic performance models were tested. The nozzle geometric variables included outer stream radius ratio, inner stream to outer stream ratio, and inner stream plug shape. When compared to a conical nozzle at the same specific thrust, the results of the static acoustic tests with the coannular nozzles showed noise reductions of up to 7 PNdB. Extensive data analysis showed that the overall acoustic results can be well correlated using the mixed stream velocity and the mixed stream density. Results also showed that suppression levels are geometry and flow regulation dependent with the outer stream radius ratio, inner stream-to-outer stream velocity ratio and inner stream velocity ratio and inner stream plug shape, as the primary suppression parameters. In addition, high-radius ratio coannular plug nozzles were found to yield shock associated noise level reductions relative to a conical nozzle. The wind tunnel aerodynamic tests showed that static and simulated flight thrust coefficient at typical takeoff conditions are quite good - up to 0.98 at static conditions and 0.974 at a takeoff Mach number of 0.36. At low inner stream flow conditions significant thrust loss was observed. Using an inner stream conical plug resulted in 1% to 2% higher performance levels than nozzle geometries using a bent inner plug

Statistical Modeling to Support Power System Planning

This dissertation focuses on data-analytic approaches that improve our understanding of power system applications to promote better decision-making. It tackles issues of risk analysis, uncertainty management, resource estimation, and the impacts of climate change. Tools of data mining and statistical modeling are used to bring new insight to a variety of complex problems facing today’s power system. The overarching goal of this research is to improve the understanding of the power system risk environment for improved operation, investment, and planning decisions. The first chapter introduces some challenges faced in planning for a sustainable power system. Chapter 2 analyzes the driving factors behind the disparity in wind energy investments among states with a goal of determining the impact that state-level policies have on incentivizing wind energy. Findings show that policy differences do not explain the disparities; physical and geographical factors are more important. Chapter 3 extends conventional wind forecasting to a risk-based focus of predicting maximum wind speeds, which are dangerous for offshore operations. Statistical models are presented that issue probabilistic predictions for the highest wind speed expected in a three-hour interval. These models achieve a high degree of accuracy and their use can improve safety and reliability in practice. Chapter 4 examines the challenges of wind power estimation for onshore wind farms. Several methods for wind power resource assessment are compared, and the weaknesses of the Jensen model are demonstrated. For two onshore farms, statistical models outperform other methods, even when very little information is known about the wind farm. Lastly, chapter 5 focuses on the power system more broadly in the context of the risks expected from tropical cyclones in a changing climate. Risks to U.S. power system infrastructure are simulated under different scenarios of tropical cyclone behavior that may result from climate change. The scenario-based approach allows me to address the deep uncertainty present by quantifying the range of impacts, identifying the most critical parameters, and assessing the sensitivity of local areas to a changing risk. Overall, this body of work quantifies the uncertainties present in several operational and planning decisions for power system applications

A comparison of methods for assessing power output in non‐uniform onshore wind farms

Wind resource assessments are used to estimate a wind farm’s power production during the planning process. It is important that these estimates are accurate, as they can impact financing agreements, transmission planning, and environmental targets. Here, we analyze the challenges in wind power estimation for onshore farms. Turbine wake effects are a strong determinant of farm power production. With given input wind conditions, wake losses typically cause downstream turbines to produce significantly less power than upstream turbines. These losses have been modeled extensively and are well understood under certain conditions. Most notably, validation of different model types has favored offshore farms. Models that capture the dynamics of offshore wind conditions do not necessarily perform equally as well for onshore wind farms. We analyze the capabilities of several different methods for estimating wind farm power production in 2 onshore farms with non‐uniform layouts. We compare the Jensen model to a number of statistical models, to meteorological downscaling techniques, and to using no model at all. We show that the complexities of some onshore farms result in wind conditions that are not accurately modeled by the Jensen wake decay techniques and that statistical methods have some strong advantages in practice.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142201/1/we2143-sup-0001-supplementary.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142201/2/we2143.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142201/3/we2143_am.pd

The Use of Simulation to Reduce the Domain of “Black Swans” with Application to Hurricane Impacts to Power Systems

Recently, the concept of black swans has gained increased attention in the fields of risk assessment and risk management. Different types of black swans have been suggested, distinguishing between unknown unknowns (nothing in the past can convincingly point to its occurrence), unknown knowns (known to some, but not to relevant analysts), or known knowns where the probability of occurrence is judged as negligible. Traditional risk assessments have been questioned, as their standard probabilistic methods may not be capable of predicting or even identifying these rare and extreme events, thus creating a source of possible black swans.In this article, we show how a simulation model can be used to identify previously unknown potentially extreme events that if not identified and treated could occur as black swans. We show that by manipulating a verified and validated model used to predict the impacts of hazards on a system of interest, we can identify hazard conditions not previously experienced that could lead to impacts much larger than any previous level of impact. This makes these potential black swan events known and allows risk managers to more fully consider them. We demonstrate this method using a model developed to evaluate the effect of hurricanes on energy systems in the United States; we identify hurricanes with potentially extreme impacts, storms well beyond what the historic record suggests is possible in terms of impacts.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138843/1/risa12742_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/138843/2/risa12742-sup-0001-appendix.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/138843/3/risa12742.pd

Acoustic tests of duct-burning turbofan jet noise simulation: Comprehensive data report. Volume 2: Model design and aerodynamic test results

The selection procedure is described which was used to arrive at the configurations tested, and the performance characteristics of the test nozzles are given

Acoustic tests of duct-burning turbofan jet noise simulation

The results of a static acoustic and aerodynamic performance, model-scale test program on coannular unsuppressed and multielement fan suppressed nozzle configurations are summarized. The results of the static acoustic tests show a very beneficial interaction effect. When the measured noise levels were compared with the predicted noise levels of two independent but equivalent conical nozzle flow streams, noise reductions for the unsuppressed coannular nozzles were of the order of 10 PNdB; high levels of suppression (8 PNdB) were still maintained even when only a small amount of core stream flow was used. The multielement fan suppressed coannular nozzle tests showed 15 PNdB noise reductions and up to 18 PNdB noise reductions when a treated ejector was added. The static aerodynamic performance tests showed that the unsuppressed coannular plug nozzles obtained gross thrust coefficients of 0.972, with 1.2 to 1.7 percent lower levels for the multielement fan-suppressed coannular flow nozzles. For the first time anywhere, laser velocimeter velocity profile measurements were made on these types of nozzle configurations and with supersonic heated flow conditions. Measurements showed that a very rapid decay in the mean velocity occurs for the nozzle tested