Browsing by Subject "Computer Simulation"

Now showing 1 - 6 of 6
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    Inhibition of 12/15-Lipoxygenase Protects Against β-Cell Oxidative Stress and Glycemic Deterioration in Mouse Models of Type 1 Diabetes
    (American Diabetes Association, 2017-11) Hernandez-Perez, Marimar; Chopra, Gaurav; Fine, Jonathan; Conteh, Abass M.; Anderson, Ryan M.; Linnemann, Amelia K.; Benjamin, Chanelle; Nelson, Jennifer B.; Benninger, Kara S.; Nadler, Jerry L.; Maloney, David J.; Tersey, Sarah A.; Mirmira, Raghavendra G.; Pediatrics, School of Medicine
    Islet β-cell dysfunction and aggressive macrophage activity are early features in the pathogenesis of type 1 diabetes (T1D). 12/15-Lipoxygenase (12/15-LOX) is induced in β-cells and macrophages during T1D and produces proinflammatory lipids and lipid peroxides that exacerbate β-cell dysfunction and macrophage activity. Inhibition of 12/15-LOX provides a potential therapeutic approach to prevent glycemic deterioration in T1D. Two inhibitors recently identified by our groups through screening efforts, ML127 and ML351, have been shown to selectively target 12/15-LOX with high potency. Only ML351 exhibited no apparent toxicity across a range of concentrations in mouse islets, and molecular modeling has suggested reduced promiscuity of ML351 compared with ML127. In mouse islets, incubation with ML351 improved glucose-stimulated insulin secretion in the presence of proinflammatory cytokines and triggered gene expression pathways responsive to oxidative stress and cell death. Consistent with a role for 12/15-LOX in promoting oxidative stress, its chemical inhibition reduced production of reactive oxygen species in both mouse and human islets in vitro. In a streptozotocin-induced model of T1D in mice, ML351 prevented the development of diabetes, with coincident enhancement of nuclear Nrf2 in islet cells, reduced β-cell oxidative stress, and preservation of β-cell mass. In the nonobese diabetic mouse model of T1D, administration of ML351 during the prediabetic phase prevented dysglycemia, reduced β-cell oxidative stress, and increased the proportion of anti-inflammatory macrophages in insulitis. The data provide the first evidence to date that small molecules that target 12/15-LOX can prevent progression of β-cell dysfunction and glycemic deterioration in models of T1D.
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    Orthognathic Surgery past, present, and future
    (Taylor & Francis, 2022-09-14) Conley, R Scott
    Orthognathic surgery has been performed for over two centuries with the first procedure occurring in the 1860s. It was not until the late 1950s with the pioneering work of Obwegeser that the modern orthognathic surgery era began. From the beginning, oral surgeons and orthodontists have worked in parallel fashion; advances in both disciplines have led to what is now routinely performed. New and exciting developments are underway not only in diagnosis but also in treatment planning with computer aided surgical simulation and the use of artificial intelligence (AI) to enhance patient treatment outcomes. The purpose of this article is to briefly review the history of orthognathic surgery, to examine the present status and to highlight emerging technologies and advancements.
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    Pediatric sleep-related breathing disorders: advances in imaging and computational modeling
    (IEEE, 2014-09) Ward, Sally L. Davidson; Amin, Raouf; Arens, Raanan; Chen, Zhongping; Davis, Stephanie; Gutmark, Ephraim; Superfine, Richard; Wong, Brian; Zdanski, Carlton; Khoo, Michael C.K.; Department of Medicine, IU School of Medicine
    We understand now that sleep of sufficient length and quality is required for good health. This is particularly true for infants and children, who have the added physiologic task of growth and development, as compared to their adult counterparts. Sleep-related breathing disorders (SRBDs) are common in childhood and if unrecognized and not treated can result in significant morbidity. For example, children with obstructive sleep apnea (OSA) can exhibit behavioral, mood, and learning difficulties. If left untreated, alterations in the function of the autonomic nervous system and a chronic inflammatory state result, contributing to the risk of heart disease, stroke, glucose intolerance, and hypertension in adulthood.
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    RareVar: A Framework for Detecting Low-Frequency Single-Nucleotide Variants
    (Mary Ann Liebert, Inc., 2017-07) Hao, Yangyang; Xuei, Xiaoling; Li, Lang; Nakshatri, Harikrishna; Edenberg, Howard J.; Liu, Yunlong; Medical and Molecular Genetics, School of Medicine
    Accurate identification of low-frequency somatic point mutations in tumor samples has important clinical utilities. Although high-throughput sequencing technology enables capturing such variants while sequencing primary tumor samples, our ability for accurate detection is compromised when the variant frequency is close to the sequencer error rate. Most current experimental and bioinformatic strategies target mutations with ≥5% allele frequency, which limits our ability to understand the cancer etiology and tumor evolution. We present an experimental and computational modeling framework, RareVar, to reliably identify low-frequency single-nucleotide variants from high-throughput sequencing data under standard experimental protocols. RareVar protocol includes a benchmark design by pooling DNAs from already sequenced individuals at various concentrations to target variants at desired frequencies, 0.5%-3% in our case. By applying a generalized, linear model-based, position-specific error model, followed by machine-learning-based variant calibration, our approach outperforms existing methods. Our method can be applied on most capture and sequencing platforms without modifying the experimental protocol.
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    Robust estimation of heterogeneous treatment effects using electronic health record data
    (Wiley, 2021-05) Li, Ruohong; Wang, Honglang; Tu, Wanzhu; Biostatistics, School of Public Health
    Estimation of heterogeneous treatment effects is an essential component of precision medicine. Model and algorithm-based methods have been developed within the causal inference framework to achieve valid estimation and inference. Existing methods such as the A-learner, R-learner, modified covariates method (with and without efficiency augmentation), inverse propensity score weighting, and augmented inverse propensity score weighting have been proposed mostly under the square error loss function. The performance of these methods in the presence of data irregularity and high dimensionality, such as that encountered in electronic health record (EHR) data analysis, has been less studied. In this research, we describe a general formulation that unifies many of the existing learners through a common score function. The new formulation allows the incorporation of least absolute deviation (LAD) regression and dimension reduction techniques to counter the challenges in EHR data analysis. We show that under a set of mild regularity conditions, the resultant estimator has an asymptotic normal distribution. Within this framework, we proposed two specific estimators for EHR analysis based on weighted LAD with penalties for sparsity and smoothness simultaneously. Our simulation studies show that the proposed methods are more robust to outliers under various circumstances. We use these methods to assess the blood pressure-lowering effects of two commonly used antihypertensive therapies.
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    Strategic planning to reduce the burden of stroke among veterans: using simulation modeling to inform decision making
    (Ovid Technologies Wolters Kluwer -American Heart Association, 2014-07) Lich, Kristen Hassmiller; Tian, Yuan; Beadles, Christopher A.; Williams, Linda S.; Bravata, Dawn M.; Cheng, Eric M.; Bosworth, Hayden B.; Homer, Jack B.; Matchar, David B.; Department of Neurology, IU School of Medicine
    BACKGROUND AND PURPOSE: Reducing the burden of stroke is a priority for the Veterans Affairs Health System, reflected by the creation of the Veterans Affairs Stroke Quality Enhancement Research Initiative. To inform the initiative's strategic planning, we estimated the relative population-level impact and efficiency of distinct approaches to improving stroke care in the US Veteran population to inform policy and practice. METHODS: A System Dynamics stroke model of the Veteran population was constructed to evaluate the relative impact of 15 intervention scenarios including both broad and targeted primary and secondary prevention and acute care/rehabilitation on cumulative (20 years) outcomes including quality-adjusted life years (QALYs) gained, strokes prevented, stroke fatalities prevented, and the number-needed-to-treat per QALY gained. RESULTS: At the population level, a broad hypertension control effort yielded the largest increase in QALYs (35,517), followed by targeted prevention addressing hypertension and anticoagulation among Veterans with prior cardiovascular disease (27,856) and hypertension control among diabetics (23,100). Adjusting QALYs gained by the number of Veterans needed to treat, thrombolytic therapy with tissue-type plasminogen activator was most efficient, needing 3.1 Veterans to be treated per QALY gained. This was followed by rehabilitation (3.9) and targeted prevention addressing hypertension and anticoagulation among those with prior cardiovascular disease (5.1). Probabilistic sensitivity analysis showed that the ranking of interventions was robust to uncertainty in input parameter values. CONCLUSIONS: Prevention strategies tend to have larger population impacts, though interventions targeting specific high-risk groups tend to be more efficient in terms of number-needed-to-treat per QALY gained.