Browsing by Subject "Biology"

Now showing 1 - 10 of 12
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    Assignment: Learning the Scientific Method by Analyzing Study Skills Research
    (Indiana University, 2021-07) Hass-Jacobus, Barbara
    In this activity, which is typically completed during the second week of the semester, students read and analyze the data presented in a one-page newsletter article describing cognitive psychology research on study methods presented in an education workshop at an American Society of Plant Biologists annual meeting. Students practice identifying parts of the scientific method within the study's design and analyze the data presented to determine which study methods were shown to be most effective. They also answer questions designed to have them think about those conclusions in the context of the course. After a class discussion, students are broken into groups and asked to reflect on their study habits in light of this research and develop a study plan for the semester incorporating what they've learned from the research study's conclusions.
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    Decision and discovery in defining 'disease'
    (Springer, 2007) Schwartz, Peter H.
    The debate over how to analyze the concept of disease has often centered on the question of whether to include a reference to values, in particular the ‘disvalue’of diseases, or whether to avoid such notions. ‘Normativists,’such as King ([1954], 1981) and Culver and Gert (1982) emphasize the undesirability of diseases, while ‘Naturalists,’ most prominently Christopher Boorse (1977, 1987, 1997), instead require just the presence of biological dysfunction. The debate between normativism and naturalism often deteriorates into stalemate, with each side able to point out significant problems with the other. It starts to look as if neither approach can work. In this paper, I argue that the standoff stems from deeply questionable assumptions that have been used to formulate the opposing positions and guide the debate. In the end, I propose an alternative set of guidelines that offer a more constructive way to devise and compare theories.
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    Defining dysfunction: natural selection, design, and drawing a line.
    (Philosophy of Science, 2007-07) Schwartz, Peter H.
    Accounts of the concepts of function and dysfunction have not adequately explained what factors determine the line between low-normal function and dysfunction. I call the challenge of doing so the line-drawing problem. Previous approaches emphasize facts involving the action of natural selection (Wakefield 1992a, 1999a, 1999b) or the statistical distribution of levels of functioning in the current population (Boorse 1977, 1997). I point out limitations of these two approaches and present a solution to the line-drawing problem that builds on the second one.
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    Ex Vivo Method for Assessing the Mouse Reproductive Tract Spontaneous Motility and a MATLAB-based Uterus Motion Tracking Algorithm for Data Analysis
    (Journal of Visualized Experiments, 2019-09-01) Liang, Kaley L.; Bursova, Julia O.; Lam, Frank; Chen, Xingjuan; Obukhov, Alexander G.; Cellular and Integrative Physiology, School of Medicine
    Dysmenorrhea, or painful cramping, is the most common symptom associated with menses in females and its severity can hinder women's everyday lives. Here, we present an easy and inexpensive method that would be instrumental for testing new drugs decreasing uterine contractility. This method utilizes the unique ability of the entire mouse reproductive tract to exhibit spontaneous motility when maintained ex vivo in a Petri dish containing oxygenated Krebs buffer. This spontaneous motility resembles the wave-like myometrial activity of the human uterus, referred to as endometrial waves. To demonstrate the effectiveness of the method, we employed a well-known uterine relaxant drug, epinephrine. We demonstrate that the spontaneous motility of the entire mouse reproductive tract can be quickly and reversibly inhibited by 1 µM epinephrine in this Petri dish model. Documenting the changes of uterine motility can be easily done using an ordinary smart phone or a sophisticated digital camera. We developed a MATLAB-based algorithm allowing motion tracking to quantify spontaneous uterine motility changes by measuring the rate of uterine horn movements. A major advantage of this ex vivo approach is that the reproductive tract remains intact throughout the entire experiment, preserving all intrinsic intrauterine cellular interactions. The major limitation of this approach is that up to 10-20% of uteri may exhibit no spontaneous motility. Thus far, this is the first quantitative ex vivo method for assessing spontaneous uterine motility in a Petri dish model.
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    Glycogen and its metabolism: some new developments and old themes
    (Portland Press Ltd., 2012-02-01) Roach, Peter J.; Depaoli-Roach, Anna A.; Hurley, Thomas D.; Tagliabracci, Vincent S.; Department of Biochemistry & Molecular Biology, IU School of Medicine
    Glycogen is a branched polymer of glucose that acts as a store of energy in times of nutritional sufficiency for utilization in times of need. Its metabolism has been the subject of extensive investigation and much is known about its regulation by hormones such as insulin, glucagon and adrenaline (epinephrine). There has been debate over the relative importance of allosteric compared with covalent control of the key biosynthetic enzyme, glycogen synthase, as well as the relative importance of glucose entry into cells compared with glycogen synthase regulation in determining glycogen accumulation. Significant new developments in eukaryotic glycogen metabolism over the last decade or so include: (i) three-dimensional structures of the biosynthetic enzymes glycogenin and glycogen synthase, with associated implications for mechanism and control; (ii) analyses of several genetically engineered mice with altered glycogen metabolism that shed light on the mechanism of control; (iii) greater appreciation of the spatial aspects of glycogen metabolism, including more focus on the lysosomal degradation of glycogen; and (iv) glycogen phosphorylation and advances in the study of Lafora disease, which is emerging as a glycogen storage disease.
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    The International Conference on Intelligent Biology and Medicine (ICIBM) 2018: genomics with bigger data and wider applications
    (Biomed Central, 2019-02-04) Wu, Zhijin; Yan, Jingwen; Wang, Kai; Liu, Xiaoming; Guo, Yan; Zhi, Degui; Ruan, Jianhua; Zhao, Zhongming; BioHealth Informatics, School of Informatics and Computing
    The sixth International Conference on Intelligent Biology and Medicine (ICIBM) took place in Los Angeles, California, USA on June 10-12, 2018. This conference featured eleven regular scientific sessions, four tutorials, one poster session, four keynote talks, and four eminent scholar talks. The scientific program covered a wide range of topics from bench to bedside, including 3D Genome Organization, reconstruction of large scale evolution of genomes and gene functions, artificial intelligence in biological and biomedical fields, and precision medicine. Both method development and application in genomic research continued to be a main component in the conference, including studies on genetic variants, regulation of transcription, genetic-epigenetic interaction at both single cell and tissue level and artificial intelligence. Here, we write a summary of the conference and also briefly introduce the four high quality papers selected to be published in BMC Genomics that cover novel methodology development or innovative data analysis.
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    A Proximal Culture Method to Study Paracrine Signaling Between Cells
    (MyJove Corporation, 2018-08-28) Dasari, Subramanyam; Pandhiri, Taruni; Haley, James; Lenz, Dean; Mitra, Anirban K.; Medical and Molecular Genetics, School of Medicine
    Intercellular interactions play an important role in many biological processes, including tumor progression, immune responses, angiogenesis, and development. Paracrine or juxtacrine signaling mediates such interactions. The use of a conditioned medium and coculture studies are the most common methods to discriminate between these two types of interactions. However, the effect of localized high concentrations of secreted factors in the microenvironment during the paracrine interactions is not accurately recapitulated by conditioned medium and, thus, may lead to imprecise conclusions. To overcome this problem, we have devised a proximal culture method to study paracrine signaling. The two cell types are grown on either surface of a 10 µm-thick polycarbonate membrane with 0.4 µm pores. The pores allow the exchange of secreted factors and, at the same time, inhibit juxtacrine signaling. The cells can be collected and lysed at the endpoint to determine the effects of the paracrine signaling. In addition to allowing for localized concentration gradients of secreted factors, this method is amenable to experiments involving prolonged periods of culture, as well as the use of inhibitors. While we use this method to study the interactions between ovarian cancer cells and the mesothelial cells they encounter at the site of metastasis, it can be adapted to any two adherent cell types for researchers to study paracrine signaling in various fields, including tumor microenvironment, immunology, and development.
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    Remote Assessment of ADHD Symptoms Based on Mobile Game Performance in Children with ADHD: A Proof of Concept
    (IEEE, 2023-07) Song, Jeong-Heon; Kim, Byeongil; Kim, Seon-Chil; Toom, Niharika; Kaur, Charanjit; Rodriguez, Gabriela Marie; Hord, Melissa Kay; Jung, Hee-Tae; Psychiatry, School of Medicine
    The use of game-based digital medicine is gaining increasing interest in helping children with ADHD to improve their attention outside the clinical setting. In this process, it is important to continue monitoring children’s responses to the use of digital medicine. In this work, we introduce novel digital markers and an analytic pipeline to estimate ADHD-related symptomatic levels during the self-administration of attention games. The digital markers, capturing the children’s characteristics of attention and inattention spans, were extracted and translated into clinically-accepted measures of ADHD symptoms, specifically the ADHD-Rating Scale (ADHD-RS) and Child Behavior Checklist (CBCL). To validate the feasibility of our approach, we collected game-specific performance data from 15 children with ADHD, which was used to train machine learning-based regression models to estimate their corresponding ADHD-RS and CBCL scores. Our experiment results showed mean absolute errors of 5.14 and 4.05 points between the actual and estimated ADHD-RS and CBCL scores respectively. This study enables new clinical and research opportunities for accurate longitudinal assessment of symptomatic levels of ADHD via an interactive means of playing mobile games.