108 research outputs found

    A technology pathway program in data technology and applications

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    With an exponential increase in user-generated data, there is a strong and increasing demand for employees possessing both technical skills and knowledge of human behavior. Supported by funds from the National Science Foundation Division of Undergraduate Education, we have begun to address this need by developing a technology pathway program in data technology and applications at a large, minority-serving public university. As part of this program, an interdisciplinary team of faculty created a new minor in Applied Computing for Behavioral and Social Sciences. A large number of diverse students are studying behavioral and social sciences, and the ability to model human behaviors and social interactions is a highly valuable skill set in our increasingly data-driven world. Applied Computing students complete a four-course sequence that focuses on data analytics and includes data structures and algorithms, data cleaning and management, SQL, and a culminating project. Our first full cohort of students completed the Applied Computing minor in Spring 2019. To assess the success of the minor, we conduct student surveys and interviews in each course. Here, we focus on survey data from the beginning and end of the first course, given that it served as a particularly important feedback loop to optimize the course and to inform the design and execution of subsequent courses. The data reflect a significant increase in confidence in programming abilities over time, as well as a shift in attitudes about programming that more closely matches those of experts. The data did not show a significant change in mindset over time, such that students maintained a growth mindset across the semester. Finally, with respect to goals, students placed a greater emphasis on data and tech at the end of the semester, highlighting specific career paths such as user experience and human factors. In the future, we plan to administer this same survey to social science students not involved in the minor to serve as a control group and to begin exploring the large dataset obtained from other courses in the minor. We believe that embedding computing education into the social sciences is a promising means of diversifying the technical workforce and filling the need for interdisciplinary computing professionals, as evidenced by high rates of female and underrepresented minority enrollment in our courses, as well as promising shifts in student confidence, attitudes, and career goals as a result of taking Applied Computing courses

    Learning Experiences of Social Science Students in an Interdisciplinary Computing Minor

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    The rapid growth of the digital economy and an associated increase in user-generated data has created a strong need for interdisciplinary computing professionals possessing both technical skills and knowledge of human behavior. To help meet this need and with funds from NSF IUSE, we developed an academic minor in Applied Computing for Behavioral and Social Sciences at San Jose State University. The minor involves a four-course sequence that includes programming fundamentals, data structures and algorithms, data cleaning and management, and a culminating project. At our institution and nationwide, social science students are more diverse than engineering students, with respect to gender, race, and ethnicity. By providing social science students with computing skills that complement their domain expertise, we aim to expand their career options and address the nation\u27s need for a diverse, technology-capable workforce. We administered an exit survey on student learning experiences to two cohorts of students completing the minor. Given that the minor is new and that the first cohorts were relatively small, the number of students completing the survey was modest (n = 15). Results indicate that students were motivated to minor in Applied Computing by a desire to improve their data analysis skills and better prepare themselves for the job market/graduate school, as well as a belief that programming is a necessary skill for the future. A large majority of students indicated that their peers, instructors, and homework assignments supported their learning very well, whereas they found topics covered and course projects to be less supportive, followed by pacing of course content. With respect to career plans, a majority of students agreed that the minor provided them with their desired skills and allowed them to learn about careers in applied computing, and a large majority indicated that they planned to pursue a career utilizing applied computing. They expressed interest in fields such as human factors, data analytics, project management, teaching, clinical psychology, and various types of research. Finally, common themes that arose when providing advice to future students included not being shy in seeking help, tips for managing the level of course difficulty, encouragement to regularly practice, suggestions for how to master course content, and advice for adopting a successful mindset. These results will be instrumental in helping to optimize students\u27 experiences in the minor, ranging from how we recruit new students to how we can better support their professional development. Given the largely positive experiences of our students and their plans to pursue careers involving applied computing, we believe that our approach of adding computing education alongside a social science degree demonstrates a promising model for meeting the increasing demand for diverse interdisciplinary computing workers in this digital age

    Structured purpose: Implementing Python in Purposive Sample Selection for Evaluation Interviews

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    We demonstrated implementation of Python-based programming to select participants for qualitative evaluation. We used a National Institutes of Health (NIH)-funded multi-site COVID-19 testing program, Rapid Diagnostics for Underserved Populations Program, as our case example. During Phase I, the NIH funded 69 projects, each with known characteristics like underserved focus population(s). Using Python coding, we selected nine sites. We established preliminary conditions for the sample based on key populations. We iteratively applied additional conditions based on site target sample, study design, and geography. For each condition, Python checked every potential sample set against the condition, removed incompatible sets, then added another condition until a single set of sites to interview emerged. The code maximized sample diversity and prioritized projects addressing multiple populations concurrently. Full implementation of code takes about thirty minutes on an ordinary laptop computer. We explain the generation of the code and make it available in Carolina Digital Repository

    Age-related differences in memory after attending to distinctiveness or similarity during learning

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    Episodic memory is vulnerable to age-related change, with older adults demonstrating both impairments in retrieving contextual details and susceptibility to interference among similar events. Such impairments may be due in part to an age-related decline in the ability to encode distinct memory representations. Recent research has examined how manipulating stimulus properties to emphasize distinctiveness can reduce age-related deficits in memory. However, few studies have addressed whether learning strategies that differentially encourage distinctiveness processing attenuate age-related differences in episodic memory. In the present study, participants engaged in two incidental encoding tasks emphasizing either distinctiveness or similarity processing. Results demonstrated higher rates of recollection for stimuli studied under the distinctiveness task than the similarity task in younger but not older adults. These findings suggest a declining capacity for distinctiveness processing to benefit memory in older adults, and raise the possibility that strategies that enhance gist-based encoding may attenuate age-related memory deficits

    Dimensions of Community Inclusion in Research: Using Evaluation to Improve Community Engagement Across the Research Design-to-Dissemination Continuum

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    Background: Rapid Diagnostics for Underserved Populations (RADx-UP) is a multisite grant with a coordinating center funded by the National Institutes of Health to increase COVID-19 testing access. RADx-UP includes over 125 research projects working with underserved communities across the United States, its territories, and Tribal Nations. Program evaluation includes tracking and analyzing RADx-UP peer-reviewed publications across multiple community inclusion dimensions to (1) assess contributions to community engagement knowledge base and (2) strengthen community partner inclusion throughout the research design-to-dissemination continuum across the consortium.Methods: We identify RADx-UP publications through monthly grant number searches in PubMed and Scopus and quarterly PI surveys. Through April 2022, 76 publications have been identified and analyzed as part of ongoing evaluation through 2024. We analyze publications quarterly to (1) thematically code, (2) extract community engagement strategies, and (3) examine patterns of academic-community collaborations among co-authorship networks.Results: A key emergent theme from content analysis was collaborative partnerships; effective community engagement strategies identified included social media, community-collaborative partnerships, and community stakeholder meetings. Collaboration analyses of publications indicated that 11% included community-based coauthor(s), and 37% included a community stakeholder acknowledgement. Evaluation findings were shared via interactive dashboards on the RADx-UP website, which project teams report allow for contextualization of findings.Conclusion: We developed an evaluation approach for tracking and analyzing community engagement across the research design-to-dissemination continuum. Findings support RADx-UP consortium efforts to increase community inclusion in research by augmenting training and support. Program evaluators can adapt our approach to foster research equity and inclusion

    Hippocampal and cortical mechanisms at retrieval explain variability in episodic remembering in older adults

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    Age-related episodic memory decline is characterized by striking heterogeneity across individuals. Hippocampal pattern completion is a fundamental process supporting episodic memory. Yet, the degree to which this mechanism is impaired with age, and contributes to variability in episodic memory, remains unclear. We combine univariate and multivariate analyses of fMRI data from a large cohort of cognitively normal older adults (N=100) to measure hippocampal activity and cortical reinstatement during retrieval of trial-unique associations. Trial-wise analyses revealed that (a) hippocampal activity scaled with reinstatement strength, (b) cortical reinstatement partially mediated the relationship between hippocampal activity and associative retrieval, (c) older age weakened cortical reinstatement and its relationship to memory behaviour. Moreover, individual differences in the strength of hippocampal activity and cortical reinstatement explained unique variance in performance across multiple assays of episodic memory. These results indicate that fMRI indices of hippocampal pattern completion explain within-and across-individual memory variability in older adults

    Mapping the human platelet lipidome reveals cytosolic phospholipase A2 as a regulator of mitochondrial bioenergetics during activation

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    Human platelets acutely increase mitochondrial energy generation following stimulation. Herein, a lipidomic circuit was uncovered whereby the substrates for this are exclusively provided by cPLA2, including multiple fatty acids and oxidized species that support energy generation via β-oxidation. This indicates that acute lipid membrane remodeling is required to support energetic demands during platelet activation. Phospholipase activity is linked to energy metabolism, revealing cPLA2 as a central regulator of both lipidomics and energy flux. Using a lipidomic approach (LipidArrays), we also estimated the total number of lipids in resting, thrombin-activated, and aspirinized platelets. Significant diversity between genetically unrelated individuals and a wealth of species was revealed. Resting platelets demonstrated ∼5,600 unique species, with only ∼50% being putatively identified. Thrombin elevated ∼900 lipids >2-fold with 86% newly appearing and 45% inhibited by aspirin supplementation, indicating COX-1 is required for major activation-dependent lipidomic fluxes. Many lipids were structurally identified. With ∼50% of the lipids being absent from databases, a major opportunity for mining lipids relevant to human health and disease is presente

    Nε-lysine acetylation of the histone-like protein HBsu influences antibiotic survival and persistence in Bacillus subtilis

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    Nε-lysine acetylation is recognized as a prevalent post-translational modification (PTM) that regulates proteins across all three domains of life. In Bacillus subtilis, the histone-like protein HBsu is acetylated at seven sites, which regulates DNA compaction and the process of sporulation. In Mycobacteria, DNA compaction is a survival strategy in response antibiotic exposure. Acetylation of the HBsu ortholog HupB decondenses the chromosome to escape this drug-induced, non-growing state, and in addition, regulates the formation of drug-tolerant subpopulations by altering gene expression. We hypothesized that the acetylation of HBsu plays similar regulatory roles. First, we measured nucleoid area by fluorescence microscopy and in agreement, we found that wild-type cells compacted their nucleoids upon kanamycin exposure, but not exposure to tetracycline. We analyzed a collection of HBsu mutants that contain lysine substitutions that mimic the acetylated (glutamine) or unacetylated (arginine) forms of the protein. Our findings indicate that some level of acetylation is required at K3 for a proper response and K75 must be deacetylated. Next, we performed time-kill assays of wild-type and mutant strains in the presence of different antibiotics and found that interfering with HBsu acetylation led to faster killing rates. Finally, we examined the persistent subpopulation and found that altering the acetylation status of HBsu led to an increase in persister cell formation. In addition, we found that most of the deacetylation-mimic mutants, which have compacted nucleoids, were delayed in resuming growth following removal of the antibiotic, suggesting that acetylation is required to escape the persistent state. Together, this data adds an additional regulatory role for HBsu acetylation and further supports the existence of a histone-like code in bacteria

    PTPA variants and impaired PP2A activity in early-onset Parkinsonism with intellectual disability

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    APPENDIX 1 : French and Mediterranean clinicians’ network for Parkinson’s disease genetics (the PDG group) collaborators French PDG collaborators Yves Agid, Mathieu Anheim, Michel Borg, Alexis Brice, Emmanuel Broussolle, Jean-Christophe Corvol, Philippe Damier, Luc Defebvre, Alexandra Dürr, Franck Durif, Jean Luc Houeto, Paul Krack, Stephan Klebe, Suzanne Lesage, Ebba Lohmann, Maria Martinez, Graziella Mangone, Louise-Laure Mariani, Pierre Pollak, Olivier Rascol, François Tison, Christine Tranchant, Marc Vérin, François Viallet, and Marie Vidailhet. Collaborators from Mediterranean countries Ebba Lohmann, Murat Emre, Hasmet Hanagasi, Basar Bilgic, Bedia Marangozoğlu, Mustapha Benmahdjoub, Mohammed Arezki, Sofiane A. Bouchetara, Traki Benhassine, Meriem Tazir, Mouna Ben Djebara, Riadh Gouider, Sawssan Ben Romdhan, Chokri Mhiri, Ahmed Bouhouche.APPENDIX 2 : Collaborators of the International Parkinsonism Genetics Network. Vincenzo Bonifati, Wim Mandemakers, Anneke J. A. Kievit, Agnita J. W. Boon, Joaquim J. Ferreira, Leonor Correia Guedes, Murat Emre, Hasmet A. Hanagasi, Basar Bilgic, Zeynep Tufekcioglu, Bülent Elibol, Okan Doğu, Murat Gultekin, Hsin F. Chien, Egberto Barbosa, Laura Bannach Jardim, Carlos R. M. Rieder, Hsiu-Chen Chang, Chin-Song Lu, Yah-Huei Wu-Chou, Tu-Hsueh Yeh, Leonardo Lopiano, Cristina Tassorelli, Claudio Pacchetti, Cristoforo Comi, Francesco Raudino, Laura Bertolasi, Michele Tinazzi, Alberto Bonizzato, Carlo Ferracci, Roberto Marconi, Marco Guidi, Marco Onofrj, Astrid Thomas, Nicola Vanacore, Giuseppe Meco, Edito Fabrizio, Giovanni Fabbrini, Alfredo Berardelli, Fabrizio Stocchi, Laura Vacca, Paolo Barone, Marina Picillo, Giuseppe De Michele, Chiara Criscuolo, Michele De Mari, Claudia Dell’Aquila, Giovanni Iliceto, Vincenzo Toni, Giorgio Trianni, Valeria Saddi, Gianni Cossu, Maurizio Melis.The protein phosphatase 2A complex (PP2A), the major Ser/Thr phosphatase in the brain, is involved in a number of signalling pathways and functions, including the regulation of crucial proteins for neurodegeneration, such as alphasynuclein, tau and LRRK2. Here, we report the identification of variants in the PTPA/PPP2R4 gene, encoding a major PP2A activator, in two families with early-onset parkinsonism and intellectual disability. We carried out clinical studies and genetic analyses, including genome-wide linkage analysis, whole-exome sequencing, and Sanger sequencing of candidate variants. We next performed functional studies on the disease-associated variants in cultured cells and knock-down of ptpa in Drosophila melanogaster. We first identified a homozygous PTPA variant, c.893T>G (p.Met298Arg), in patients from a South African family with early-onset parkinsonism and intellectual disability. Screening of a large series of additional families yielded a second homozygous variant, c.512C>A (p.Ala171Asp), in a Libyan family with a similar phenotype. Both variants co-segregate with disease in the respective families. The affected subjects display juvenile-onset parkinsonism and intellectual disability. The motor symptoms were responsive to treatment with levodopa and deep brain stimulation of the subthalamic nucleus. In overexpression studies, both the PTPA p.Ala171Asp and p.Met298Arg variants were associated with decreased PTPA RNA stability and decreased PTPA protein levels; the p.Ala171Asp variant additionally displayed decreased PTPA protein stability. Crucially, expression of both variants was associated with decreased PP2A complex levels and impaired PP2A phosphatase activation. PTPA orthologue knock-down in Drosophila neurons induced a significant impairment of locomotion in the climbing test. This defect was age-dependent and fully reversed by L-DOPA treatment. We conclude that bi-allelic missense PTPA variants associated with impaired activation of the PP2A phosphatase cause autosomal recessive early-onset parkinsonism with intellectual disability. Our findings might also provide new insights for understanding the role of the PP2A complex in the pathogenesis of more common forms of neurodegeneration.The Stichting ParkinsonFonds (The Netherlands); the Fondation pour la Recherche Médicale; PTC Therapeutics, the Fondation de France, France-Parkinson Association, la Fédération pour la Recherche sur le Cerveau (FRC) and the French program ‘Investissements d’avenir’ (ANR-10-IAIHU-06) to AB; and grants from the South African Medical Research Council (Self-Initiated Research Grant) and the National Research Foundation of South Africa.https://academic.oup.com/brainNeurologySDG-03:Good heatlh and well-bein
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