93 research outputs found

    Fostering Significant Learning in Sciences

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    The new global economy depends on workforce competencies in science, technology, engineering and mathematics more than ever before. To prepare a strong workforce, attracting and educating underrepresented minority students in science is a challenge within our traditional American educational approach. To meet this challenge, fostering significant learning in science that nurtures 21st Century skills in students is crucial. The purpose of this study was to analyze the effectiveness of a set of teaching and learning approaches that foster significant learning in sciences. Using a new introductory environmental science course in urban water quality management, the effect of a set of learner-centered teaching approaches, including hands-on learning, scientific inquiry, frequent feedback, and critical thinking exercises, was analyzed. The results of the pre- and post-course survey questions together with formative and summative assessments showed that our students’ cognitive learning skills and interests in learning science were significantly improved

    Fostering Significant Learning in Sciences

    Get PDF
    The new global economy depends on workforce competencies in science, technology, engineering and mathematics more than ever before. To prepare a strong workforce, attracting and educating underrepresented minority students in science is a challenge within our traditional American educational approach. To meet this challenge, fostering significant learning in science that nurtures 21st Century skills in students is crucial. The purpose of this study was to analyze the effectiveness of a set of teaching and learning approaches that foster significant learning in sciences. Using a new introductory environmental science course in urban water quality management, the effect of a set of learner-centered teaching approaches, including hands-on learning, scientific inquiry, frequent feedback, and critical thinking exercises, was analyzed. The results of the pre- and post-course survey questions together with formative and summative assessments showed that our students’ cognitive learning skills and interests in learning science were significantly improved

    FM-test: a fuzzy-set-theory-based approach to differential gene expression data analysis

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    Abstract Background Microarray techniques have revolutionized genomic research by making it possible to monitor the expression of thousands of genes in parallel. As the amount of microarray data being produced is increasing at an exponential rate, there is a great demand for efficient and effective expression data analysis tools. Comparison of gene expression profiles of patients against those of normal counterpart people will enhance our understanding of a disease and identify leads for therapeutic intervention. Results In this paper, we propose an innovative approach, fuzzy membership test (FM-test), based on fuzzy set theory to identify disease associated genes from microarray gene expression profiles. A new concept of FM d-value is defined to quantify the divergence of two sets of values. We further analyze the asymptotic property of FM-test, and then establish the relationship between FM d-value and p-value. We applied FM-test to a diabetes expression dataset and a lung cancer expression dataset, respectively. Within the 10 significant genes identified in diabetes dataset, six of them have been confirmed to be associated with diabetes in the literature and one has been suggested by other researchers. Within the 10 significantly overexpressed genes identified in lung cancer data, most (eight) of them have been confirmed by the literatures which are related to the lung cancer. Conclusion Our experiments on synthetic datasets show that FM-test is effective and robust. The results in diabetes and lung cancer datasets validated the effectiveness of FM-test. FM-test is implemented as a Web-based application and is available for free at http://database.cs.wayne.edu/bioinformatics

    MCM-test: a fuzzy-set-theory-based approach to differential analysis of gene pathways

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    Abstract Background Gene pathway can be defined as a group of genes that interact with each other to perform some biological processes. Along with the efforts to identify the individual genes that play vital roles in a particular disease, there is a growing interest in identifying the roles of gene pathways in such diseases. Results This paper proposes an innovative fuzzy-set-theory-based approach, Multi-dimensional Cluster Misclassification test (MCM-test), to measure the significance of gene pathways in a particular disease. Experiments have been conducted on both synthetic data and real world data. Results on published diabetes gene expression dataset and a list of predefined pathways from KEGG identified OXPHOS pathway involved in oxidative phosphorylation in mitochondria and other mitochondrial related pathways to be deregulated in diabetes patients. Our results support the previously supported notion that mitochondrial dysfunction is an important event in insulin resistance and type-2 diabetes. Conclusion Our experiments results suggest that MCM-test can be successfully used in pathway level differential analysis of gene expression datasets. This approach also provides a new solution to the general problem of measuring the difference between two groups of data, which is one of the most essential problems in most areas of research

    Distinct and shared functions of ALS-associated proteins TDP-43, FUS and TAF15 revealed by multisystem analyses

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    The RNA-binding protein (RBP) TAF15 is implicated in amyotrophic lateral sclerosis (ALS). To compare TAF15 function to that of two ALS-associated RBPs, FUS and TDP-43, we integrate CLIP-seq and RNA Bind-N-Seq technologies, and show that TAF15 binds to ∼4,900 RNAs enriched for GGUA motifs in adult mouse brains. TAF15 and FUS exhibit similar binding patterns in introns, are enriched in 3′ untranslated regions and alter genes distinct from TDP-43. However, unlike FUS and TDP-43, TAF15 has a minimal role in alternative splicing. In human neural progenitors, TAF15 and FUS affect turnover of their RNA targets. In human stem cell-derived motor neurons, the RNA profile associated with concomitant loss of both TAF15 and FUS resembles that observed in the presence of the ALS-associated mutation FUS R521G, but contrasts with late-stage sporadic ALS patients. Taken together, our findings reveal convergent and divergent roles for FUS, TAF15 and TDP-43 in RNA metabolism.National Institutes of Health (U.S.) (Grant HG007005

    CRL4^(AMBRA1) targets Elongin C for ubiquitination and degradation to modulate CRL5 signaling

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    Multi‐subunit cullin‐RING ligases (CRLs) are the largest family of ubiquitin E3 ligases in humans. CRL activity is tightly regulated to prevent unintended substrate degradation or autocatalytic degradation of CRL subunits. Using a proteomics strategy, we discovered that CRL4^(AMBRA1) (CRL substrate receptor denoted in superscript) targets Elongin C (ELOC), the essential adapter protein of CRL5 complexes, for polyubiquitination and degradation. We showed that the ubiquitin ligase function of CRL4^(AMBRA1) is required to disrupt the assembly and attenuate the ligase activity of human CRL5^(SOCS3) and HIV‐1 CRL5^(VIF) complexes as AMBRA1 depletion leads to hyperactivation of both CRL5 complexes. Moreover, CRL4^(AMBRA1) modulates interleukin‐6/STAT3 signaling and HIV‐1 infectivity that are regulated by CRL5^(SOCS3) and CRL5^(VIF), respectively. Thus, by discovering a substrate of CRL4^(AMBRA1), ELOC, the shared adapter of CRL5 ubiquitin ligases, we uncovered a novel CRL cross‐regulation pathway

    Ermin deficiency leads to compromised myelin, inflammatory milieu, and susceptibility to demyelinating insult

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    Ermin is an actin-binding protein found almost exclusively in the central nervous system (CNS) as a component of myelin sheaths. Although Ermin has been predicted to play a role in the formation and stability of myelin sheaths, this has not been directly examined in vivo. Here, we show that Ermin is essential for myelin sheath integrity and normal saltatory conduction. Loss of Ermin in mice caused de-compacted and fragmented myelin sheaths and led to slower conduction along with progressive neurological deficits. RNA sequencing of the corpus callosum, the largest white matter structure in the CNS, pointed to inflammatory activation in aged Ermin-deficient mice, which was corroborated by increased levels of microgliosis and astrogliosis. The inflammatory milieu and myelin abnormalities were further associated with increased susceptibility to immune-mediated demyelination insult in Ermin knockout mice. Supporting a possible role of Ermin deficiency in inflammatory white matter disorders, a rare inactivating mutation in the ERMN gene was identified in multiple sclerosis patients. Our findings demonstrate a critical role for Ermin in maintaining myelin integrity. Given its near-exclusive expression in myelinating oligodendrocytes, Ermin deficiency represents a compelling “inside-out” model of inflammatory dysmyelination and may offer a new paradigm for the development of myelin stability-targeted therapies

    Diverse Applications of Nanomedicine

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    The design and use of materials in the nanoscale size range for addressing medical and health-related issues continues to receive increasing interest. Research in nanomedicine spans a multitude of areas, including drug delivery, vaccine development, antibacterial, diagnosis and imaging tools, wearable devices, implants, high-throughput screening platforms, etc. using biological, nonbiological, biomimetic, or hybrid materials. Many of these developments are starting to be translated into viable clinical products. Here, we provide an overview of recent developments in nanomedicine and highlight the current challenges and upcoming opportunities for the field and translation to the clinic. \ua9 2017 American Chemical Society
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