Bogdan I. Epureanu

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• Computational dynamics focused on nonlinear dynamics and finite elements (e.g., a new approach for forecasting bifurcations/tipping points in aeroelastic and ecological systems, new finite element methods for thin walled beams that leads to novel reduced order models).
• Modeling nonlinear phenomena and mechano-chemical processes in molecular motor dynamics, such as motor proteins, toward early detection of neurodegenerative diseases.
• Computational methods for robotics, manufacturing, modeling multi-body dynamics, developed methods for identifying limit cycle oscillations in large-dimensional (fluid) systems.
• Turbomachinery and aeroelasticity providing a better understanding of fundamental complex fluid dynamics and cutting-edge models for predicting, identifying and characterizing the response of blisks and flade systems through integrated experimental & computational approaches.
• Structural health monitoring & sensing providing increased sensibility / capabilities by the discovery, characterization and exploitation of sensitivity vector fields, smart system interrogation through nonlinear feedback excitation, nonlinear minimal rank perturbation and system augmentation, pattern recognition for attractors, damage detection using bifurcation morphing.

Annette Ostling

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Biodiversity in nature can be puzzlingly high in the light of competition between species, which arguably should eventually result in a single winner. The coexistence mechanisms that allow for this biodiversity shape the dynamics of communities and ecosystems. My research focuses on understanding the mechanisms of competitive coexistence, how competition influences community structure and diversity, and what insights observed patterns of community structure might provide about competitive coexistence.

I am interested in the use and development of data science approaches to draw insights regarding coexistence mechanisms from the structural patterns of ecological communities with respect to species’ functional traits, relative abundance, spatial distribution, and phylogenetic relatedness, through as community dynamics proceed. I am also interested in the use of Maximum Likelihood and Bayesian approaches for fitting demographic models to forest census data sets, demographic models that can then be used to quantitatively assess the role of different competitive coexistence mechanisms.

Thomas Schmidt

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The current goal of our research is to learn enough about the physiology and ecology of microbes and microbial communities in the gut that we are able to engineer the gut microbiome to improve human health. The first target of our engineering is the production of butyrate – a common fermentation product of some gut microbes that is essential for human health. Butyrate is the preferred energy source for mitochondria in the epithelial cells lining the gut and it also regulates their gene expression.

One of the most effective ways to influence the composition and metabolism of the gut microbiota is through diet. In an interventional study, we have tracked responses in the composition and fermentative metabolism of the gut microtiota in >800 healthy individuals. Emerging patterns suggest several configurations of the microbiome that can result in increased production of butyrate acid. We have isolated the microbes that form an anaerobic food web to convert dietary fiber to butyrate and continue to make discoveries about their physiology and interactions. Based on these results, we have initiated a clinical trial in which we are hoping to prevent the development of Graft versus Host Disease following bone marrow transplants by managing butyrate production by the gut microbiota.

We are also beginning to track hundreds of other metabolites from the gut microbiome that may influence human health. We use metagenomes and metabolomes to identify patterns that link the microbiota with their metabolites and then test those models in human organoids and gnotobiotic mice colonized with synthetic communities of microbes. This blend of wet-lab research in basic microbiology, data science and in ecology is moving us closer to engineering the gut microbiome to improve human health.

Carlos Aguilar

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The Aguilar group is focused understanding transcriptional and epigenetic mechanisms of skeletal muscle stem cells in diverse contexts such as regeneration after injury and aging. We focus on this area because there are little to no therapies for skeletal muscle after injury or aging. We use various types of in-vivo and in-vitro models in combination with genomic assays and high-throughput sequencing to study these molecular mechanisms.

Evan Keller

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Our laboratory focuses on (1) the biology of cancer metastasis, especially bone metastasis, including the role of the host microenvironment; and (2) mechanisms of chemoresistance. We explore for genes that regulate metastasis and the interaction between the host microenvironment and cancer cells. We are performing single cell multiomics and spatial analysis to enable us to identify rare cell populations and promote precision medicine. Our research methodology uses a combination of molecular, cellular, and animal studies. The majority of our work is highly translational to provide clinical relevance to our work. In terms of data science, we collaborate on applications of both established and novel methodologies to analyze high dimensional; deconvolution of high dimensional data into a cellular and tissue context; spatial mapping of multiomic data; and heterogenous data integration.

Matthew J Delano

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Obesity promotes type 2 diabetes (T2D) the 3rd leading cause of death in the United States and accounts for $237 billion healthcare cost. T2D and obesity promote infections that cause sepsis, the leading cause of mortality in the intensive care unit following traumatic injury. Despite advances in supportive care, sepsis mortality remains 25% and escalates over time. Survival from sepsis depends on emergency myelopoiesis of macrophages (MΦ) to clear bacteria and deescalate inflammation. Resolving inflammation requires MΦ polarization from pro-inflammatory M1 to anti-inflammatory MΦ states. The MΦ ability to polarize depends on the intrinsic plasticity inherited from hematopoietic stem and progenitor cells (HSPCs) during emergency myelopoiesis. Our published data in trauma and sepsis in mice and humans demonstrates that obesity and T2D alter HSPC myelopoiesis, inhibit MΦ plasticity and prevent M1Φ polarization to other functional MΦ states. However, the impact of altered MΦ myelopoiesis and restricted M1Φ polarity on sepsis pathogenesis is unknown. A critical need exists to understand the mechanisms by which obesity and T2D alter myelopoiesis, inhibit MΦ plasticity and prevent MΦ polarity to promote bacterial sepsis mortality. We hypothesize that obesity and T2D prime HSPC myelopoiesis to produce dysfunctional M1Φs incapable of bacterial clearance, and effective polarization which hinder inflammation resolution during sepsis and cause mortality. We will test the hypothesis with the following aims that, when completed, will fill the current knowledge void and improve sepsis survival. In Aim 1 we will determine the mechanisms in T2D and obesity that alter myelopoiesis in bacterial sepsis. The findings will reveal how obesity and T2D prime HSPCs and alter myelopoiesis to prevent MΦ polarity in mice and humans with sepsis. In Aim 2 we will identify the functional consequences of obese, T2D M1Φs unable to polarize to other activation states during bacterial sepsis. We will explore how restricted MΦ polarity effects immune cell responses and cytokine production to define how T2D and obesity impede inflammation resolution. The data generated will identify new pathways that promote aberrant myeloid production, restricted MΦ plasticity and prevent inflammation resolution during bacterial sepsis. Novel targeted therapies can then be developed for clinical implementation for bacterial eradication, wound healing and survival from sepsis in obesity and T2D.

Yulia Sevryugina

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Study of Pandemic Publishing: How Scholarly Literature is Affected by COVID-19 Pandemic
This project addresses the quality of recently published COVID-19 publications. With the COVID-19 pandemic, researchers publish a lot their research as preprints. And while preprints are an important development in scholarly publishing, they are works in progress that need further refinement to become a more rigorous final product. Scholarly publishers are also taking initiatives to accelerate publication process, for example, by asking reviewers to curtail requests for additional experiments upon revisions. Sacrificing rigor for haste inevitably increases the likelihood of article correction and retraction, leading to spread of false information within supposedly trustworthy sources that have a peer-reviewing process in place to ensure proper verification. I study the quality of COVID-19 related scholarly works by using CADRE’s datasets to identify signs of incoherency, irreproducibility, and haste.

9.9.2020 MIDAS Faculty Research Pitch Video.

Rudy J. Richardson

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Applications of computational tools for molecular modeling (Discovery Studio, ICM-Pro, MOE, and YASARA) and data science (ADMET Predictor, KNIME, Origin Pro, Prism, Python, and R) to computational toxicology, drug discovery, homology modeling, molecular dynamics, and protein structure/function prediction. Current special interests include therapeutics for neurodegenerative disorders (Alzheimer’s, Parkinson’s, and motor neuron diseases) and infectious diseases (COVID-19).

3D alignment of acetylcholinesterase (AChE) from mouse (magenta) and electric eel (gray) showing the amino acid residues of the catalytic triad.

Robert Ploutz-Snyder

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My work falls into three general application areas. I am an applied (accredited) biostatistician with a strong team science motivation and I collaborate with scientists in primarily the biomedical sciences, contributing expertise in experimental design, statistical analysis/modeling, and data visualization. I have held faculty appointments in Schools of Medicine and Nursing, and also worked as a senior scientist in the Human Research Program at the NASA Johnson Space Center. I currently direct an Applied Biostatistics Laboratory and Data Management Core within the UM School of Nursing, and maintain several collaborative research programs within the School, at NASA, and with collaborators elsewhere.