A technology pathway program in data technology and applications

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

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

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

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

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

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

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

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

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 alpha-synuclein, 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&gt;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&gt;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.</p

Mammal responses to global changes in human activity vary by trophic group and landscape

Wildlife must adapt to human presence to survive in the Anthropocene, so it is critical to understand species responses to humans in different contexts. We used camera trapping as a lens to view mammal responses to changes in human activity during the COVID-19 pandemic. Across 163 species sampled in 102 projects around the world, changes in the amount and timing of animal activity varied widely. Under higher human activity, mammals were less active in undeveloped areas but unexpectedly more active in developed areas while exhibiting greater nocturnality. Carnivores were most sensitive, showing the strongest decreases in activity and greatest increases in nocturnality. Wildlife managers must consider how habituation and uneven sensitivity across species may cause fundamental differences in human–wildlife interactions along gradients of human influence.Peer reviewe

Symptom-based stratification of patients with primary Sjögren's syndrome: multi-dimensional characterisation of international observational cohorts and reanalyses of randomised clinical trials

Background Heterogeneity is a major obstacle to developing effective treatments for patients with primary Sjögren's syndrome. We aimed to develop a robust method for stratification, exploiting heterogeneity in patient-reported symptoms, and to relate these differences to pathobiology and therapeutic response. Methods We did hierarchical cluster analysis using five common symptoms associated with primary Sjögren's syndrome (pain, fatigue, dryness, anxiety, and depression), followed by multinomial logistic regression to identify subgroups in the UK Primary Sjögren's Syndrome Registry (UKPSSR). We assessed clinical and biological differences between these subgroups, including transcriptional differences in peripheral blood. Patients from two independent validation cohorts in Norway and France were used to confirm patient stratification. Data from two phase 3 clinical trials were similarly stratified to assess the differences between subgroups in treatment response to hydroxychloroquine and rituximab. Findings In the UKPSSR cohort (n=608), we identified four subgroups: Low symptom burden (LSB), high symptom burden (HSB), dryness dominant with fatigue (DDF), and pain dominant with fatigue (PDF). Significant differences in peripheral blood lymphocyte counts, anti-SSA and anti-SSB antibody positivity, as well as serum IgG, κ-free light chain, β2-microglobulin, and CXCL13 concentrations were observed between these subgroups, along with differentially expressed transcriptomic modules in peripheral blood. Similar findings were observed in the independent validation cohorts (n=396). Reanalysis of trial data stratifying patients into these subgroups suggested a treatment effect with hydroxychloroquine in the HSB subgroup and with rituximab in the DDF subgroup compared with placebo. Interpretation Stratification on the basis of patient-reported symptoms of patients with primary Sjögren's syndrome revealed distinct pathobiological endotypes with distinct responses to immunomodulatory treatments. Our data have important implications for clinical management, trial design, and therapeutic development. Similar stratification approaches might be useful for patients with other chronic immune-mediated diseases. Funding UK Medical Research Council, British Sjogren's Syndrome Association, French Ministry of Health, Arthritis Research UK, Foundation for Research in Rheumatology