4,118 results on '"Cottrell, P"'
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2. Teaching Students with Autism Spectrum Disorder and Intellectual Disability to Independently Access and Use Point-of-View Video Models for Virtual Instruction
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Jennifer Annette Cottrell, Robert Alex Smith, and Audra I. Classen
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Online instructional delivery has always been viewed as beneficial due to its flexibility in settings and times, but the COVID-19 pandemic produced an essential need for the ability to engage in learning without direct contact with others. For students with Autism Spectrum Disorder and Intellectual Disability (ASD and ID) who have extensive support needs, developing the skills required to engage with online content is critical for utilizing and interacting with distance learning platforms and resources. Using a visual task analysis, least-to-most prompting, and reinforcement, students with ASD and ID can be taught to use technological devices for virtual instruction without adult support. By teaching students to access and use point-of-view video modeling for online instructional delivery, teachers can facilitate skills their students need to access evidence-based practices and meet diverse learning goals and objectives.
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- 2024
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3. Characterizing Long COVID in Children and Adolescents
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Gross, Rachel S, Thaweethai, Tanayott, Kleinman, Lawrence C, Snowden, Jessica N, Rosenzweig, Erika B, Milner, Joshua D, Tantisira, Kelan G, Rhee, Kyung E, Jernigan, Terry L, Kinser, Patricia A, Salisbury, Amy L, Warburton, David, Mohandas, Sindhu, Wood, John C, Newburger, Jane W, Truong, Dongngan T, Flaherman, Valerie J, Metz, Torri D, Karlson, Elizabeth W, Chibnik, Lori B, Pant, Deepti B, Krishnamoorthy, Aparna, Gallagher, Richard, Lamendola-Essel, Michelle F, Hasson, Denise C, Katz, Stuart D, Yin, Shonna, Dreyer, Benard P, Carmilani, Megan, Coombs, K, Fitzgerald, Megan L, Güthe, Nick, Hornig, Mady, Letts, Rebecca J, Peddie, Aimee K, Taylor, Brittany D, Foulkes, Andrea S, Stockwell, Melissa S, Balaraman, Venkataraman, Bogie, Amanda, Bukulmez, Hulya, Dozor, Allen J, Eckrich, Daniel, Elliott, Amy J, Evans, Danielle N, Farkas, Jonathan S, Faustino, E Vincent S, Fischer, Laura, Gaur, Sunanda, Harahsheh, Ashraf S, Hasan, Uzma N, Hsia, Daniel S, Huerta-Montanez, Gredia, Hummel, Kathy D, Kadish, Matt P, Kaelber, David C, Krishnan, Sankaran, Kosut, Jessica S, Larrabee, Jerry, Lim, Peter Paul C, Michelow, Ian C, Oliveira, Carlos R, Raissy, Hengameh, Rosario-Pabon, Zaira, Ross, Judith L, Sato, Alice I, Stevenson, Michelle D, Talavera-Barber, Maria M, Teufel, Ronald J, Weakley, Kathryn E, Zimmerman, Emily, Bind, Marie-Abele C, Chan, James, Guan, Zoe, Morse, Richard E, Reeder, Harrison T, Akshoomoff, Natascha, Aschner, Judy L, Bhattacharjee, Rakesh, Cottrell, Lesley A, Cowan, Kelly, D'Sa, Viren A, Fiks, Alexander G, Gennaro, Maria L, Irby, Katherine, Khare, Manaswitha, Landeo Guttierrez, Jeremy, McCulloh, Russell J, Narang, Shalu, Ness- Cochinwala, Manette, Nolan, Sheila, Palumbo, Paul, Ryu, Julie, Salazar, Juan C, Selvarangan, Rangaraj, Stein, Cheryl R, Werzberger, Alan, Zempsky, William T, Aupperle, Robin, and Baker, Fiona C
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Biomedical and Clinical Sciences ,Clinical Sciences ,Health Sciences ,Emerging Infectious Diseases ,Neurosciences ,Coronaviruses ,Infectious Diseases ,Pediatric ,Minority Health ,Pain Research ,Infection ,Good Health and Well Being ,RECOVER-Pediatrics Consortium ,RECOVER-Pediatrics Group Authors ,Medical and Health Sciences ,General & Internal Medicine ,Biomedical and clinical sciences ,Health sciences - Abstract
ImportanceMost research to understand postacute sequelae of SARS-CoV-2 infection (PASC), or long COVID, has focused on adults, with less known about this complex condition in children. Research is needed to characterize pediatric PASC to enable studies of underlying mechanisms that will guide future treatment.ObjectiveTo identify the most common prolonged symptoms experienced by children (aged 6 to 17 years) after SARS-CoV-2 infection, how these symptoms differ by age (school-age [6-11 years] vs adolescents [12-17 years]), how they cluster into distinct phenotypes, and what symptoms in combination could be used as an empirically derived index to assist researchers to study the likely presence of PASC.Design, setting, and participantsMulticenter longitudinal observational cohort study with participants recruited from more than 60 US health care and community settings between March 2022 and December 2023, including school-age children and adolescents with and without SARS-CoV-2 infection history.ExposureSARS-CoV-2 infection.Main outcomes and measuresPASC and 89 prolonged symptoms across 9 symptom domains.ResultsA total of 898 school-age children (751 with previous SARS-CoV-2 infection [referred to as infected] and 147 without [referred to as uninfected]; mean age, 8.6 years; 49% female; 11% were Black or African American, 34% were Hispanic, Latino, or Spanish, and 60% were White) and 4469 adolescents (3109 infected and 1360 uninfected; mean age, 14.8 years; 48% female; 13% were Black or African American, 21% were Hispanic, Latino, or Spanish, and 73% were White) were included. Median time between first infection and symptom survey was 506 days for school-age children and 556 days for adolescents. In models adjusted for sex and race and ethnicity, 14 symptoms in both school-age children and adolescents were more common in those with SARS-CoV-2 infection history compared with those without infection history, with 4 additional symptoms in school-age children only and 3 in adolescents only. These symptoms affected almost every organ system. Combinations of symptoms most associated with infection history were identified to form a PASC research index for each age group; these indices correlated with poorer overall health and quality of life. The index emphasizes neurocognitive, pain, and gastrointestinal symptoms in school-age children but change or loss in smell or taste, pain, and fatigue/malaise-related symptoms in adolescents. Clustering analyses identified 4 PASC symptom phenotypes in school-age children and 3 in adolescents.Conclusions and relevanceThis study developed research indices for characterizing PASC in children and adolescents. Symptom patterns were similar but distinguishable between the 2 groups, highlighting the importance of characterizing PASC separately for these age ranges.
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- 2024
4. South African Parents’ and Grandparents’ Perspectives on the Acceptability of Implant Delivery of Treatment to Young Children with HIV
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Hawley, Imogen, Baez, Alejandro, Scorgie, Fiona, Fairlie, Lee, Mathebula, Florence, Cottrell, Mackenzie Leigh, Johnson, Leah M., and Montgomery, Elizabeth T.
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- 2024
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5. Predicting criminal offence in adolescents who exhibit antisocial behaviour: a machine learning study using data from a large randomised controlled trial of multisystemic therapy
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Suh, Jae Won, Saunders, Rob, Simes, Elizabeth, Delamain, Henry, Butler, Stephen, Cottrell, David, Kraam, Abdullah, Scott, Stephen, Goodyer, Ian M, Wason, James, Pilling, Stephen, and Fonagy, Peter
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- 2024
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6. Systemic methotrexate (MTX) in early pregnancy: a retrospective study of a tertiary maternity hospital
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Lutfi, Ahmed, Hayes-Ryan, Deirdre, Cottrell, Elmarie, and Greene, Richard A.
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- 2024
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7. Teachers’ Perceptions of the Impact of the COVID-19 Pandemic and Their Implementation of an Evidence-based HIV Prevention Program in the Bahamas
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Schieber, Elizabeth, Cottrell, Lesley, Deveaux, Lynette, Li, Xiaoming, Taylor, Marcellus, Adderley, Richard, Marshall, Sharon, Forbes, Nikkiah, and Wang, Bo
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- 2024
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8. Development of an Intervention Targeted to Patients with Cancers Not Typically Perceived as Smoking-Related
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Martinez, Ursula, Brandon, Thomas H., Cottrell-Daniels, Cherell, McBride, Colleen M., Warren, Graham W., Meade, Cathy D., Palmer, Amanda M., and Simmons, Vani N.
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- 2024
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9. Semantic Analyses of Open-Ended Responses from Professional Development Workshop Promoting Computational Thinking in Rural Schools
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Gillenwaters, Amber, Iqbal, Razib, Piccolo, Diana, Davis, Tammi, Franklin, Keri, Cornelison, David, Martinez, Judith, Homburg, Andrew, Cottrell, Julia, and Page, Melissa
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In this paper, an application of open-ended textual feedback is presented as a tool to evaluate the perceptions and needs of teachers tasked with implementing computational thinking in the K-12 curriculum. Semantic analysis tools, including sentiment analysis and thematic analysis, facilitated the identification of common themes in openended textual feedback. Results show that semantic analysis techniques can be useful in evaluating formative assessment data or open-ended feedback to discover response patterns, which may aid in determining actionable insights related to adult learner perceptions, interests, and self-efficacy. Formative assessment data were collected from a unique professional development workshop to promote computational thinking and curriculum integration in core subjects, including writing, math, science, and social studies, with the goal of discovering the barriers that rural teachers face in developing and implementing lesson plans for grades 3-8 teachers in a rural midwestern state in the USA to promote computational thinking and curriculum integration in core subjects, including writing, math, science, and social studies, with the goal of discovering the barriers that rural teachers face in developing and implementing lesson plans.
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- 2023
10. PECAN Predicts Patterns of Cancer Cell Cytostatic Activity of Natural Products Using Deep Learning.
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Kim, Hyun, Gerwick, William, Cottrell, Garrison, Gahl, Martha, and Glukhov, Evgenia
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Humans ,Cytostatic Agents ,Carya ,Biological Products ,Deep Learning ,Neoplasms - Abstract
Many machine learning techniques are used as drug discovery tools with the intent to speed characterization by determining relationships between compound structure and biological function. However, particularly in anticancer drug discovery, these models often make only binary decisions about the biological activity for a narrow scope of drug targets. We present a feed-forward neural network, PECAN (Prediction Engine for the Cytostatic Activity of Natural product-like compounds), that simultaneously classifies the potential antiproliferative activity of compounds against 59 cancer cell lines. It predicts the activity to be one of six categories, indicating not only if activity is present but the degree of activity. Using an independent subset of NCI data as a test set, we show that PECAN can reach 60.1% accuracy in a six-way classification and present further evidence that it classifies based on useful structural features of compounds using a within-one measure that reaches 93.0% accuracy.
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- 2024
11. Multiscale differential geometry learning of networks with applications to single-cell RNA sequencing data
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Feng, Hongsong, Cottrell, Sean, Hozumi, Yuta, and Wei, Guo-Wei
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Quantitative Biology - Molecular Networks - Abstract
Single-cell RNA sequencing (scRNA-seq) has emerged as a transformative technology, offering unparalleled insights into the intricate landscape of cellular diversity and gene expression dynamics. The analysis of scRNA-seq data poses challenges attributed to both sparsity and the extensive number of genes implicated. An increasing number of computational tools are devised for analyzing and interpreting scRNA-seq data. We present a multiscale differential geometry (MDG) strategy to exploit the geometric and biological properties inherent in scRNA-seq data. We assume that those intrinsic properties of cells lies on a family of low-dimensional manifolds embedded in the high-dimensional space of scRNA-seq data. Subsequently, we explore these properties via multiscale cell-cell interactive manifolds. Our multiscale curvature-based representation serves as a powerful approach to effectively encapsulate the complex relationships in the cell-cell network. We showcase the utility of our novel approach by demonstrating its effectiveness in classifying cell types. This innovative application of differential geometry in scRNA-seq analysis opens new avenues for understanding the intricacies of biological networks and holds great potential for network analysis in other fields.
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- 2023
12. Do stingray feeding pits enhance intertidal macrobenthic biodiversity?
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Barnes, Richard S. K. and Cottrell, Lily G.
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- 2024
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13. Deep, hot, ancient melting recorded by ultralow oxygen fugacity in peridotites
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Birner, Suzanne K., Cottrell, Elizabeth, Davis, Fred A., and Warren, Jessica M.
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- 2024
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14. Vaccination induces broadly neutralizing antibody precursors to HIV gp41
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Schiffner, Torben, Phung, Ivy, Ray, Rashmi, Irimia, Adriana, Tian, Ming, Swanson, Olivia, Lee, Jeong Hyun, Lee, Chang-Chun D., Marina-Zárate, Ester, Cho, So Yeon, Huang, Jiachen, Ozorowski, Gabriel, Skog, Patrick D., Serra, Andreia M., Rantalainen, Kimmo, Allen, Joel D., Baboo, Sabyasachi, Rodriguez, Oscar L., Himansu, Sunny, Zhou, Jianfu, Hurtado, Jonathan, Flynn, Claudia T., McKenney, Katherine, Havenar-Daughton, Colin, Saha, Swati, Shields, Kaitlyn, Schultze, Steven, Smith, Melissa L., Liang, Chi-Hui, Toy, Laura, Pecetta, Simone, Lin, Ying-Cing, Willis, Jordan R., Sesterhenn, Fabian, Kulp, Daniel W., Hu, Xiaozhen, Cottrell, Christopher A., Zhou, Xiaoya, Ruiz, Jennifer, Wang, Xuesong, Nair, Usha, Kirsch, Kathrin H., Cheng, Hwei-Ling, Davis, Jillian, Kalyuzhniy, Oleksandr, Liguori, Alessia, Diedrich, Jolene K., Ngo, Julia T., Lewis, Vanessa, Phelps, Nicole, Tingle, Ryan D., Spencer, Skye, Georgeson, Erik, Adachi, Yumiko, Kubitz, Michael, Eskandarzadeh, Saman, Elsliger, Marc A., Amara, Rama R., Landais, Elise, Briney, Bryan, Burton, Dennis R., Carnathan, Diane G., Silvestri, Guido, Watson, Corey T., Yates, III, John R., Paulson, James C., Crispin, Max, Grigoryan, Gevorg, Ward, Andrew B., Sok, Devin, Alt, Frederick W., Wilson, Ian A., Batista, Facundo D., Crotty, Shane, and Schief, William R.
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- 2024
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15. K-Nearest-Neighbors Induced Topological PCA for scRNA Sequence Data Analysis
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Cottrell, Sean, Hozumi, Yuta, and Wei, Guo-Wei
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Quantitative Biology - Quantitative Methods ,Computer Science - Machine Learning ,Mathematics - Algebraic Topology - Abstract
Single-cell RNA sequencing (scRNA-seq) is widely used to reveal heterogeneity in cells, which has given us insights into cell-cell communication, cell differentiation, and differential gene expression. However, analyzing scRNA-seq data is a challenge due to sparsity and the large number of genes involved. Therefore, dimensionality reduction and feature selection are important for removing spurious signals and enhancing downstream analysis. Traditional PCA, a main workhorse in dimensionality reduction, lacks the ability to capture geometrical structure information embedded in the data, and previous graph Laplacian regularizations are limited by the analysis of only a single scale. We propose a topological Principal Components Analysis (tPCA) method by the combination of persistent Laplacian (PL) technique and L$_{2,1}$ norm regularization to address multiscale and multiclass heterogeneity issues in data. We further introduce a k-Nearest-Neighbor (kNN) persistent Laplacian technique to improve the robustness of our persistent Laplacian method. The proposed kNN-PL is a new algebraic topology technique which addresses the many limitations of the traditional persistent homology. Rather than inducing filtration via the varying of a distance threshold, we introduced kNN-tPCA, where filtrations are achieved by varying the number of neighbors in a kNN network at each step, and find that this framework has significant implications for hyper-parameter tuning. We validate the efficacy of our proposed tPCA and kNN-tPCA methods on 11 diverse benchmark scRNA-seq datasets, and showcase that our methods outperform other unsupervised PCA enhancements from the literature, as well as popular Uniform Manifold Approximation (UMAP), t-Distributed Stochastic Neighbor Embedding (tSNE), and Projection Non-Negative Matrix Factorization (NMF) by significant margins., Comment: 28 pages, 11 figures
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- 2023
16. Structural and Dynamic Analyses of Pathogenic Variants in PIK3R1 Reveal a Shared Mechanism Associated among Cancer, Undergrowth, and Overgrowth Syndromes.
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Dsouza, Nikita, Cottrell, Catherine, Davies, Olivia, Tollefson, Megha, Frieden, Ilona, Basel, Donald, Urrutia, Raul, Drolet, Beth, and Zimmermann, Michael
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PI3K ,PROS ,genomic data interpretation ,genomics ,overgrowth ,precision medicine ,undergrowth - Abstract
The PI3K enzymes modify phospholipids to regulate cell growth and differentiation. Somatic variants in PI3K are recurrent in cancer and drive a proliferative phenotype. Somatic mosaicism of PIK3R1 and PIK3CA are associated with vascular anomalies and overgrowth syndromes. Germline PIK3R1 variants are associated with varying phenotypes, including immunodeficiency or facial dysmorphism with growth delay, lipoatrophy, and insulin resistance associated with SHORT syndrome. There has been limited study of the molecular mechanism to unify our understanding of how variants in PIK3R1 drive both undergrowth and overgrowth phenotypes. Thus, we compiled genomic variants from cancer and rare vascular anomalies and sought to interpret their effects using an unbiased physics-based simulation approach for the protein complex. We applied molecular dynamics simulations to mechanistically understand how genetic variants affect PIK3R1 and its interactions with PIK3CA. Notably, iSH2 genetic variants associated with undergrowth destabilize molecular interactions with the PIK3CA receptor binding domain in simulations, which is expected to decrease activity. On the other hand, overgrowth and cancer variants lead to loss of inhibitory interactions in simulations, which is expected to increase activity. We find that all disease variants display dysfunctions on either structural characteristics or intermolecular interaction energy. Thus, this comprehensive characterization of novel mosaic somatic variants associated with two opposing phenotypes has mechanistic importance and biomedical relevance and may aid in future therapeutic developments.
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- 2024
17. Researching COVID to enhance recovery (RECOVER) pediatric study protocol: Rationale, objectives and design.
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Gross, Rachel, Thaweethai, Tanayott, Rosenzweig, Erika, Chan, James, Chibnik, Lori, Cicek, Mine, Elliott, Amy, Flaherman, Valerie, Foulkes, Andrea, Gage Witvliet, Margot, Gallagher, Richard, Gennaro, Maria, Jernigan, Terry, Karlson, Elizabeth, Katz, Stuart, Kinser, Patricia, Kleinman, Lawrence, Lamendola-Essel, Michelle, Milner, Joshua, Mohandas, Sindhu, Mudumbi, Praveen, Newburger, Jane, Rhee, Kay, Salisbury, Amy, Snowden, Jessica, Stein, Cheryl, Stockwell, Melissa, Tantisira, Kelan, Thomason, Moriah, Truong, Dongngan, Warburton, David, Wood, John, Ahmed, Shifa, Akerlundh, Almary, Alshawabkeh, Akram, Anderson, Brett, Aschner, Judy, Atz, Andrew, Aupperle, Robin, Baker, Fiona, Balaraman, Venkataraman, Banerjee, Dithi, Barch, Deanna, Baskin-Sommers, Arielle, Bhuiyan, Sultana, Bind, Marie-Abele, Bogie, Amanda, Bradford, Tamara, Buchbinder, Natalie, Bueler, Elliott, Bükülmez, Hülya, Casey, B, Chang, Linda, Chrisant, Maryanne, Clark, Duncan, Clifton, Rebecca, Clouser, Katharine, Cottrell, Lesley, Cowan, Kelly, DSa, Viren, Dapretto, Mirella, Dasgupta, Soham, Dehority, Walter, Dionne, Audrey, Dummer, Kirsten, Elias, Matthew, Esquenazi-Karonika, Shari, Evans, Danielle, Faustino, E, Fiks, Alexander, Forsha, Daniel, Foxe, John, Friedman, Naomi, Fry, Greta, Gaur, Sunanda, Gee, Dylan, Gray, Kevin, Handler, Stephanie, Harahsheh, Ashraf, Hasbani, Keren, Heath, Andrew, Hebson, Camden, Heitzeg, Mary, Hester, Christina, Hill, Sophia, Hobart-Porter, Laura, Hong, Travis, Horowitz, Carol, Hsia, Daniel, Huentelman, Matthew, Hummel, Kathy, Irby, Katherine, Jacobus, Joanna, Jacoby, Vanessa, Jone, Pei-Ni, Kaelber, David, Kasmarcak, Tyler, Kluko, Matthew, Kosut, Jessica, and Laird, Angela
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Humans ,COVID-19 ,Adolescent ,Child ,Child ,Preschool ,Female ,Young Adult ,Adult ,Male ,Infant ,SARS-CoV-2 ,Infant ,Newborn ,Prospective Studies ,Research Design ,Cohort Studies ,Post-Acute COVID-19 Syndrome - Abstract
IMPORTANCE: The prevalence, pathophysiology, and long-term outcomes of COVID-19 (post-acute sequelae of SARS-CoV-2 [PASC] or Long COVID) in children and young adults remain unknown. Studies must address the urgent need to define PASC, its mechanisms, and potential treatment targets in children and young adults. OBSERVATIONS: We describe the protocol for the Pediatric Observational Cohort Study of the NIHs REsearching COVID to Enhance Recovery (RECOVER) Initiative. RECOVER-Pediatrics is an observational meta-cohort study of caregiver-child pairs (birth through 17 years) and young adults (18 through 25 years), recruited from more than 100 sites across the US. This report focuses on two of four cohorts that comprise RECOVER-Pediatrics: 1) a de novo RECOVER prospective cohort of children and young adults with and without previous or current infection; and 2) an extant cohort derived from the Adolescent Brain Cognitive Development (ABCD) study (n = 10,000). The de novo cohort incorporates three tiers of data collection: 1) remote baseline assessments (Tier 1, n = 6000); 2) longitudinal follow-up for up to 4 years (Tier 2, n = 6000); and 3) a subset of participants, primarily the most severely affected by PASC, who will undergo deep phenotyping to explore PASC pathophysiology (Tier 3, n = 600). Youth enrolled in the ABCD study participate in Tier 1. The pediatric protocol was developed as a collaborative partnership of investigators, patients, researchers, clinicians, community partners, and federal partners, intentionally promoting inclusivity and diversity. The protocol is adaptive to facilitate responses to emerging science. CONCLUSIONS AND RELEVANCE: RECOVER-Pediatrics seeks to characterize the clinical course, underlying mechanisms, and long-term effects of PASC from birth through 25 years old. RECOVER-Pediatrics is designed to elucidate the epidemiology, four-year clinical course, and sociodemographic correlates of pediatric PASC. The data and biosamples will allow examination of mechanistic hypotheses and biomarkers, thus providing insights into potential therapeutic interventions. CLINICAL TRIALS.GOV IDENTIFIER: Clinical Trial Registration: http://www.clinicaltrials.gov. Unique identifier: NCT05172011.
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- 2024
18. Defining the transcriptome of PIK3CA-altered cells in a human capillary malformation using single cell long-read sequencing
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Michelle A. Wedemeyer, Tianli Ding, Elizabeth A. R. Garfinkle, Jesse J. Westfall, Jaye B. Navarro, Maria Elena Hernandez Gonzalez, Elizabeth A. Varga, Patricia Witman, Elaine R. Mardis, Catherine E. Cottrell, Anthony R. Miller, and Katherine E. Miller
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Medicine ,Science - Abstract
Abstract PIK3CA-related overgrowth spectrum (PROS) disorders are caused by somatic mosaic variants that result in constitutive activation of the phosphatidylinositol-3-kinase/AKT/mTOR pathway. Promising responses to molecularly targeted therapy have been reported, although identification of an appropriate agent can be hampered by the mosaic nature and corresponding low variant allele frequency of the causal variant. Moreover, our understanding of the molecular consequences of these variants—for example how they affect gene expression profiles—remains limited. Here we describe in vitro expansion of a human capillary malformation followed by molecular characterization using exome sequencing, single cell gene expression, and targeted long-read single cell RNA-sequencing in a patient with clinical features consistent with Megalencephaly-Capillary Malformation Syndrome (MCAP, a PROS condition). These approaches identified a targetable PIK3CA variant with expression restricted to PAX3+ fibroblast and undifferentiated keratinocyte populations. This study highlights the innovative combination of next-generation single cell sequencing methods to better understand unique transcriptomic profiles and cell types associated with MCAP, revealing molecular intricacies of this genetic syndrome.
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- 2024
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19. Activation of PKR by a short-hairpin RNA
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Kyle A. Cottrell, Sua Ryu, Helen Donelick, Hung Mai, Addison A. Young, Jackson R. Pierce, Brenda L. Bass, and Jason D. Weber
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Double-stranded RNA ,dsRNA ,PKR ,RNA interference ,RNAi ,Medicine ,Science - Abstract
Abstract Recognition of viral infection often relies on the detection of double-stranded RNA (dsRNA), a process that is conserved in many different organisms. In mammals, proteins such as MDA5, RIG-I, OAS, and PKR detect viral dsRNA, but struggle to differentiate between viral and endogenous dsRNA. This study investigates an shRNA targeting DDX54’s potential to activate PKR, a key player in the immune response to dsRNA. Knockdown of DDX54 by a specific shRNA induced robust PKR activation in human cells, even when DDX54 is overexpressed, suggesting an off-target mechanism. Activation of PKR by the shRNA was enhanced by knockdown of ADAR1, a dsRNA binding protein that suppresses PKR activation, indicating a dsRNA-mediated mechanism. In vitro assays confirmed direct PKR activation by the shRNA. These findings emphasize the need for rigorous controls and alternative methods to validate gene function and minimize unintended immune pathway activation.
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- 2024
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20. The efficacy and functional consequences of interactions between human spermatozoa and seminal fluid extracellular vesicles
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Cottrell T Tamessar, Amanda L Anderson, Elizabeth G Bromfield, Natalie A Trigg, Shanmathi Parameswaran, Simone J Stanger, Judith Weidenhofer, Hui-Ming Zhang, Sarah A Robertson, David J Sharkey, Brett Nixon, and John E Schjenken
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extracellular vesicles ,fertility ,seminal fluid ,sperm capacitation ,sperm motility ,spermatozoa ,Reproduction ,QH471-489 ,Gynecology and obstetrics ,RG1-991 - Abstract
Seminal fluid extracellular vesicles (SFEVs) have previously been shown to interact with spermatozoa and influence their fertilisation capacity. Here, we sought to extend these studies by exploring the functional consequences of SFEV interactions with human spermatozoa. SFEVs were isolated from the seminal fluid of normozoospermic donors prior to assessing the kinetics of sperm-SFEV binding in vitro, as well as the effects of these interactions on sperm capacitation, acrosomal exocytosis, and motility profile. Biotin-labelled SFEV proteins were transferred primarily to the flagellum of spermatozoa within minutes of co-incubation, although additional foci of SFEV biotinylated proteins also labelled the mid-piece and head domain. Functional analyses of high-quality spermatozoa collected following liquefaction revealed that SFEVs did not influence sperm motility during incubation at pH 5, yet SFEVs induced subtle increases in total and progressive motility in sperm incubated with SFEVs at pH 7. Additional investigation of sperm motility kinematic parameters revealed that SFEVs significantly decreased beat cross frequency and increased distance straight line, linearity, straightness, straight line velocity, and wobble. SFEVs did not influence sperm capacitation status or the ability of sperm to undergo acrosomal exocytosis. Functional assessment of both high- and low-quality spermatozoa collected prior to liquefaction showed limited SFEV influence, with these vesicles inducing only subtle decreases in beat cross frequency in spermatozoa of both groups. These findings raise the prospect that, aside from subtle effects on sperm motility, the encapsulated SFEV cargo may be destined for physiological targets other than the male germline, notably the female reproductive tract. Lay Summary A male’s influence over the biological processes of pregnancy extends beyond the provision of sperm. Molecular signals present in the ejaculate can influence the likelihood of pregnancy and healthy pregnancy progression, but the identity and function of these signals remain unclear. In this study, we wanted to understand if nano-sized particles present in the male ejaculate, called seminal fluid extracellular vesicles, can assist sperm in traversing the female reproductive tract to access the egg. To explore this, we isolated seminal fluid extracellular vesicles from human semen and incubated them with sperm. Our data showed that seminal fluid extracellular vesicles act to transfer molecular information to sperm, but this resulted in only subtle changes to the movement of sperm.
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- 2024
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21. A lunar core dynamo limited to the Moon’s first ~140 million years
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Tinghong Zhou, John A. Tarduno, Rory D. Cottrell, Clive R. Neal, Francis Nimmo, Eric G. Blackman, and Mauricio Ibañez-Mejia
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Geology ,QE1-996.5 ,Environmental sciences ,GE1-350 - Abstract
Abstract Single crystal paleointensity (SCP) reveals that the Moon lacked a long-lived core dynamo, though mysteries remain. An episodic dynamo, seemingly recorded by some Apollo basalts, is temporally and energetically problematic. We evaluate this enigma through study of ~3.7 billion-year-old (Ga) Apollo basalts 70035 and 75035. Whole rock analyses show unrealistically high nominal magnetizations, whereas SCP indicate null fields, illustrating that the former do not record an episodic dynamo. However, deep crustal magnetic anomalies might record an early lunar dynamo. SCP studies of 3.97 Ga Apollo breccia 61016 and 4.36 Ga ferroan anorthosite 60025 also yield null values, constraining any core dynamo to the Moon’s first 140 million years. These findings suggest that traces of Earth’s Hadean atmosphere, transferred to the Moon lacking a magnetosphere, could be trapped in the buried lunar regolith, presenting an exceptional target for future exploration.
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- 2024
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22. Active Participation in Catholic School-Based Liturgy
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Matthew Dell and Aidan Cottrell-Boyce
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In England and Wales, diocesan inspectors are charged with assessing the overall quality of Catholic education provided by Catholic schools. As part of this assessment, inspectors are required to give an account of the liturgical life of the school. Often the reports which result from these inspections refer to the degree of students' "active participation" in liturgy. This terminology has its roots in Biblical and patristic theological literature. Its meaning has evolved over time and has been used to describe a wide range of seemingly diffuse human behaviours. This article casts light on the meaning of "active participation" in the context of Diocesan inspectors and offers some reflections on how this term could be refined in order to make diocesan inspections more informative.
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- 2024
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23. Computational econometrics with gretl
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Yalta, A. Talha, Cottrell, Allin, and Rodrigues, Paulo C.
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- 2024
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24. PLPCA: Persistent Laplacian Enhanced-PCA for Microarray Data Analysis
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Cottrell, Sean, Wang, Rui, and Wei, Guowei
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Mathematics - Algebraic Topology ,Computer Science - Machine Learning - Abstract
Over the years, Principal Component Analysis (PCA) has served as the baseline approach for dimensionality reduction in gene expression data analysis. It primary objective is to identify a subset of disease-causing genes from a vast pool of thousands of genes. However, PCA possesses inherent limitations that hinder its interpretability, introduce classification ambiguity, and fail to capture complex geometric structures in the data. Although these limitations have been partially addressed in the literature by incorporating various regularizers such as graph Laplacian regularization, existing improved PCA methods still face challenges related to multiscale analysis and capturing higher-order interactions in the data. To address these challenges, we propose a novel approach called Persistent Laplacian-enhanced Principal Component Analysis (PLPCA). PLPCA amalgamates the advantages of earlier regularized PCA methods with persistent spectral graph theory, specifically persistent Laplacians derived from algebraic topology. In contrast to graph Laplacians, persistent Laplacians enable multiscale analysis through filtration and incorporate higher-order simplicial complexes to capture higher-order interactions in the data. We evaluate and validate the performance of PLPCA using benchmark microarray datasets that involve normal tissue samples and four different cancer tissues. Our extensive studies demonstrate that PLPCA outperforms all other state-of-the-art models for classification tasks after dimensionality reduction., Comment: 24 pages, 15 figures
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- 2023
25. Defining the transcriptome of PIK3CA-altered cells in a human capillary malformation using single cell long-read sequencing
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Wedemeyer, Michelle A., Ding, Tianli, Garfinkle, Elizabeth A. R., Westfall, Jesse J., Navarro, Jaye B., Hernandez Gonzalez, Maria Elena, Varga, Elizabeth A., Witman, Patricia, Mardis, Elaine R., Cottrell, Catherine E., Miller, Anthony R., and Miller, Katherine E.
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- 2024
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26. Activation of PKR by a short-hairpin RNA
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Cottrell, Kyle A., Ryu, Sua, Donelick, Helen, Mai, Hung, Young, Addison A., Pierce, Jackson R., Bass, Brenda L., and Weber, Jason D.
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- 2024
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27. A lunar core dynamo limited to the Moon’s first ~140 million years
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Zhou, Tinghong, Tarduno, John A., Cottrell, Rory D., Neal, Clive R., Nimmo, Francis, Blackman, Eric G., and Ibañez-Mejia, Mauricio
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- 2024
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28. Dataset of replicate Apollo sample magnetizations bearing on impacts and absence of a long-lived lunar dynamo
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Cottrell, Rory D., Zhou, Tinghong, and Tarduno, John A.
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- 2024
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29. Priming antibody responses to the fusion peptide in rhesus macaques
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Cottrell, Christopher A., Pratap, Payal P., Cirelli, Kimberly M., Carnathan, Diane G., Enemuo, Chiamaka A., Antanasijevic, Aleksandar, Ozorowski, Gabriel, Sewall, Leigh M., Gao, Hongmei, Allen, Joel D., Nogal, Bartek, Silva, Murillo, Bhiman, Jinal, Pauthner, Matthias, Irvine, Darrell J., Montefiori, David, Crispin, Max, Burton, Dennis R., Silvestri, Guido, Crotty, Shane, and Ward, Andrew B.
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- 2024
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30. SARS-CoV-2 seroprevalence among Beninese pregnant women in the third year of the pandemic
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Figueroa-Romero, Antía, Atchadé, Aurore, Yadouleton, Anges, Fiogbe, Marc, Bonnet, Emmanuel, Yovo, Emmanuel, Accrombessi, Manfred, Hounsa, Sandrine, Paper, Thierry, Dupont, Raphael, Gaudart, Jean, Le Hesran, Jean-Yves, Massougbodji, Achille, Cottrell, Gilles, and González, Raquel
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- 2024
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31. Long-term cost-utility analysis of family therapy vs. treatment as usual for young people seen after self-harm
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Bojke, Chris, Cottrell, David, Wright-Hughes, Alex, Farrin, Amanda, and Tubeuf, Sandy
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- 2024
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32. Near-collapse of the geomagnetic field may have contributed to atmospheric oxygenation and animal radiation in the Ediacaran Period
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Huang, Wentao, Tarduno, John A., Zhou, Tinghong, Ibañez-Mejia, Mauricio, Dal Olmo-Barbosa, Laércio, Koester, Edinei, Blackman, Eric G., Smirnov, Aleksey V., Ahrendt, Gabriel, Cottrell, Rory D., Kodama, Kenneth P., Bono, Richard K., Sibeck, David G., Li, Yong-Xiang, Nimmo, Francis, Xiao, Shuhai, and Watkeys, Michael K.
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- 2024
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33. “They are saying it’s high, but I think it’s quite low”: exploring cardiovascular disease risk communication in NHS health checks through video-stimulated recall interviews with patients – a qualitative study
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Cowap, Lisa, Riley, Victoria, Grogan, Sarah, Ellis, Naomi J., Crone, Diane, Cottrell, Elizabeth, Chambers, Ruth, Clark-Carter, David, and Gidlow, Christopher J.
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- 2024
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34. Human immunoglobulin gene allelic variation impacts germline-targeting vaccine priming
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deCamp, Allan C., Corcoran, Martin M., Fulp, William J., Willis, Jordan R., Cottrell, Christopher A., Bader, Daniel L. V., Kalyuzhniy, Oleksandr, Leggat, David J., Cohen, Kristen W., Hyrien, Ollivier, Menis, Sergey, Finak, Greg, Ballweber-Fleming, Lamar, Srikanth, Abhinaya, Plyler, Jason R., Rahaman, Farhad, Lombardo, Angela, Philiponis, Vincent, Whaley, Rachael E., Seese, Aaron, Brand, Joshua, Ruppel, Alexis M., Hoyland, Wesley, Mahoney, Celia R., Cagigi, Alberto, Taylor, Alison, Brown, David M., Ambrozak, David R., Sincomb, Troy, Mullen, Tina-Marie, Maenza, Janine, Kolokythas, Orpheus, Khati, Nadia, Bethony, Jeffrey, Roederer, Mario, Diemert, David, Koup, Richard A., Laufer, Dagna S., McElrath, Juliana M., McDermott, Adrian B., Karlsson Hedestam, Gunilla B., and Schief, William R.
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- 2024
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35. Author Correction: Ultra-long-acting in-situ forming implants with cabotegravir protect female macaques against rectal SHIV infection
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Young, Isabella C., Massud, Ivana, Cottrell, Mackenzie L., Shrivastava, Roopali, Maturavongsadit, Panita, Prasher, Alka, Wong-Sam, Andres, Dinh, Chuong, Edwards, Tiancheng, Mrotz, Victoria, Mitchell, James, Seixas, Josilene Nascimento, Pallerla, Aryani, Thorson, Allison, Schauer, Amanda, Sykes, Craig, De la Cruz, Gabriela, Montgomery, Stephanie A., Kashuba, Angela D. M., Heneine, Walid, Dobard, Charles W., Kovarova, Martina, Garcia, J. Victor, Garcίa-Lerma, J. Gerardo, and Benhabbour, S. Rahima
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- 2024
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36. Identification of genes with oscillatory expression in glioblastoma: the paradigm of SOX2
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Fu, Richard Zhiming, Cottrell, Oliver, Cutillo, Luisa, Rowntree, Andrew, Zador, Zsolt, Wurdak, Heiko, Papalopulu, Nancy, and Marinopoulou, Elli
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- 2024
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37. Co-development and testing of an extended community pharmacy model of service delivery for managing osteoarthritis: protocol for a sequential, multi-methods study (PharmOA)
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Babatunde, Opeyemi O., Cottrell, Elizabeth, White, Simon, Chudyk, Adrian, Healey, Emma L., Edwards, John, Nicholls, Elaine, O’Brien, Nicola, Todd, Adam, Walker, Christine, Stanford, Colin, Cork, Tania, Long, Angela, Simkins, Joanna, Mallen, Christian D., Dziedzic, Krysia, and Holden, Melanie A.
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- 2024
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38. Quantification of neurovascular compliance with retrospectively gated phase-contrast MRI
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Nabbout, Marianne, Langham, Michael C., Cottrell, Christiana, and Wehrli, Felix W.
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- 2024
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39. Dataset of replicate Apollo sample magnetizations bearing on impacts and absence of a long-lived lunar dynamo
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Rory D. Cottrell, Tinghong Zhou, and John A. Tarduno
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Science - Abstract
Abstract The absence or presence of a lunar paleomagnetosphere is important because it bears directly on the volatile content of the regolith and exploration targets for Artemis and other missions to the Moon. Recent paleointensity study of samples from the Apollo missions has readdressed this question. Multiple specimens from a young 2-million-year-old glass shows a strong magnetization compatible with that induced by charge-separation in an impact plasma, whereas paleointensities of single crystals yield evidence for null magnetizations spanning 3.9 to 3.2 Ga. Together, these data are consistent with an impact mechanism for the magnetization of some lunar samples, and absence of a long-lived lunar core dynamo and paleomagnetosphere recorded in other samples. Here, we present a dataset that allows researchers to examine replicates of these measurements. For the glass, we present data from specimens that fail standard paleointensity selection criteria but nevertheless imply a complex, changing magnetic field environment. For the single crystals, the replicate measurements further illustrate the initial zero magnetization state of these materials.
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- 2024
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40. Priming antibody responses to the fusion peptide in rhesus macaques
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Christopher A. Cottrell, Payal P. Pratap, Kimberly M. Cirelli, Diane G. Carnathan, Chiamaka A. Enemuo, Aleksandar Antanasijevic, Gabriel Ozorowski, Leigh M. Sewall, Hongmei Gao, Joel D. Allen, Bartek Nogal, Murillo Silva, Jinal Bhiman, Matthias Pauthner, Darrell J. Irvine, David Montefiori, Max Crispin, Dennis R. Burton, Guido Silvestri, Shane Crotty, and Andrew B. Ward
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Immunologic diseases. Allergy ,RC581-607 ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
Abstract Immunodominance of antibodies targeting non-neutralizing epitopes and the high level of somatic hypermutation within germinal centers (GCs) required for most HIV broadly neutralizing antibodies (bnAbs) are major impediments to the development of an effective HIV vaccine. Rational protein vaccine design and non-conventional immunization strategies are potential avenues to overcome these hurdles. Here, we report using implantable osmotic pumps to continuously deliver a series of epitope-targeted immunogens to rhesus macaques over the course of six months to prime and elicit antibody responses against the conserved fusion peptide (FP). GC responses and antibody specificities were tracked longitudinally using lymph node fine-needle aspirates and electron microscopy polyclonal epitope mapping (EMPEM), respectively, to show antibody responses to the FP/N611 glycan hole region were primed, although exhibited limited neutralization breadth. Application of cryoEMPEM delineated key residues for on-target and off-target responses that can drive the next round of structure-based vaccine design.
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- 2024
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41. SARS-CoV-2 seroprevalence among Beninese pregnant women in the third year of the pandemic
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Antía Figueroa-Romero, Aurore Atchadé, Anges Yadouleton, Marc Fiogbe, Emmanuel Bonnet, Emmanuel Yovo, Manfred Accrombessi, Sandrine Hounsa, Thierry Paper, Raphael Dupont, Jean Gaudart, Jean-Yves Le Hesran, Achille Massougbodji, Gilles Cottrell, and Raquel González
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Pregnancy ,SARS-CoV-2 ,Sub-saharan Africa ,Public aspects of medicine ,RA1-1270 - Abstract
Abstract Background Pregnant women are a vulnerable population to COVID-19 given an increased susceptibility to severe SARS-CoV-2 infection and pregnancy complications. However, few SARS-CoV-2 serological surveys have been performed among this population to assess the extent of the infection in sub-Saharan countries. The objectives of this study were to determine SARS-CoV-2 seroprevalence among Beninese pregnant women, to identify spatial seropositivity clusters and to analyse factors associated with the infection. Methods A cross-sectional study including women in their third trimester of pregnancy attending the antenatal care (ANC) clinics at Allada (south Benin) and Natitingou (north Benin) was conducted. Rapid diagnostic tests (RDT) for detection of IgG/IgM against the SARS-CoV-2 spike protein were performed using capillary blood. Seroprevalence of SARS-CoV-2 antibodies and associations between SARS-CoV-2 serostatus and maternal characteristics were analyzed by multivariate logistic regression. Spatial analyses were performed using the spatial scan statistics to identify spatial clusters of SARS-CoV-2 infection. Results A total of 861 pregnant women were enrolled between May 4 and June 29, 2022. 58/861 (6.7%) participants reported having received COVID-19 vaccine. None of the participants had been diagnosed with COVID-19 during their pregnancy. SARS-CoV-2 antibodies were detected in 607/802 (75.7%; 95% CI 72.56%–78.62%) of unvaccinated participants. Several urban and rural spatial clusters of SARS-CoV-2 cases were identified in Allada and one urban spatial cluster was identified in Natitingou. Unvaccinated participants from Allada with at least one previous morbidity were at a three-times higher risk of presenting SARS-CoV-2 antibodies (OR = 2.89; 95%CI 1.19%-7.00%). Conclusion Three out of four pregnant women had SARS-CoV-2 antibodies, suggesting a high virus circulation among pregnant women in Benin, while COVID-19 vaccination coverage was low. Pregnant women with comorbidities may be at increased risk of SARS-CoV-2 infection. This population should be prioritized for COVID-19 diagnosis and vaccination in order to prevent its deleterious effects. Trial registration NCT06170320 (retrospectively registered on December 21, 2023).
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- 2024
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42. DeepSAT: Learning Molecular Structures from Nuclear Magnetic Resonance Data.
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Kim, Hyun, Zhang, Chen, Reher, Raphael, Wang, Mingxun, Alexander, Kelsey, Nothias, Louis-Félix, Han, Yoo, Shin, Hyeji, Lee, Ki, Lee, Kyu, Kim, Myeong, Dorrestein, Pieter, Cottrell, Garrison, and Gerwick, William
- Subjects
Convolutional neural network ,Nuclear magnetic resonance ,Structure prediction - Abstract
The identification of molecular structure is essential for understanding chemical diversity and for developing drug leads from small molecules. Nevertheless, the structure elucidation of small molecules by Nuclear Magnetic Resonance (NMR) experiments is often a long and non-trivial process that relies on years of training. To achieve this process efficiently, several spectral databases have been established to retrieve reference NMR spectra. However, the number of reference NMR spectra available is limited and has mostly facilitated annotation of commercially available derivatives. Here, we introduce DeepSAT, a neural network-based structure annotation and scaffold prediction system that directly extracts the chemical features associated with molecular structures from their NMR spectra. Using only the 1H-13C HSQC spectrum, DeepSAT identifies related known compounds and thus efficiently assists in the identification of molecular structures. DeepSAT is expected to accelerate chemical and biomedical research by accelerating the identification of molecular structures.
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- 2023
43. Hadaean to Palaeoarchaean stagnant-lid tectonics revealed by zircon magnetism.
- Author
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Tarduno, John A, Cottrell, Rory D, Bono, Richard K, Rayner, Nicole, Davis, William J, Zhou, Tinghong, Nimmo, Francis, Hofmann, Axel, Jodder, Jaganmoy, Ibañez-Mejia, Mauricio, Watkeys, Michael K, Oda, Hirokuni, and Mitra, Gautam
- Subjects
General Science & Technology - Abstract
Plate tectonics is a fundamental factor in the sustained habitability of Earth, but its time of onset is unknown, with ages ranging from the Hadaean to Proterozoic eons1-3. Plate motion is a key diagnostic to distinguish between plate and stagnant-lid tectonics, but palaeomagnetic tests have been thwarted because the planet's oldest extant rocks have been metamorphosed and/or deformed4. Herein, we report palaeointensity data from Hadaean-age to Mesoarchaean-age single detrital zircons bearing primary magnetite inclusions from the Barberton Greenstone Belt of South Africa5. These reveal a pattern of palaeointensities from the Eoarchaean (about 3.9 billion years ago (Ga)) to Mesoarchaean (about 3.3 Ga) eras that is nearly identical to that defined by primary magnetizations from the Jack Hills (JH; Western Australia)6,7, further demonstrating the recording fidelity of select detrital zircons. Moreover, palaeofield values are nearly constant between about 3.9 Ga and about 3.4 Ga. This indicates unvarying latitudes, an observation distinct from plate tectonics of the past 600 million years (Myr) but predicted by stagnant-lid convection. If life originated by the Eoarchaean8, and persisted to the occurrence of stromatolites half a billion years later9, it did so when Earth was in a stagnant-lid regime, without plate-tectonics-driven geochemical cycling.
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- 2023
44. Post-Secondary Educational Leadership Working Remotely during a COVID-19 Pandemic in Saskatchewan, Canada: Exploring Best Practices, Experiences, and the 'New Normal Post-Pandemic'
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Papp, Theresa A. and Cottrell, Michael
- Abstract
This mixed methods research design focuses on post-secondary institutions in Saskatchewan, Canada, its employees' experiences of working remotely, and the impact of the global COVID-19 pandemic on school leadership. Presented are the perceived challenges as well as the benefits of the "new" workplace since the COVID-19 crisis. Administrative and instructional leadership had changed dramatically. Most identified their quality of work as better or the same because of having fewer distractions, interruptions, and less wasted time at the workplace. The participants' interviews and survey responses describe the necessary adaptation, flexibility, mental health and wellness, accountability, workload intensification, and future expectations of the workplace and leadership once the pandemic is over.
- Published
- 2022
45. Multimodal Wildland Fire Smoke Detection
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Baldota, Siddhant, Ramaprasad, Shreyas Anantha, Bhamra, Jaspreet Kaur, Luna, Shane, Ramachandra, Ravi, Zen, Eugene, Kim, Harrison, Crawl, Daniel, Perez, Ismael, Altintas, Ilkay, Cottrell, Garrison W., and Nguyen, Mai H.
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Computer Science - Computer Vision and Pattern Recognition - Abstract
Research has shown that climate change creates warmer temperatures and drier conditions, leading to longer wildfire seasons and increased wildfire risks in the United States. These factors have in turn led to increases in the frequency, extent, and severity of wildfires in recent years. Given the danger posed by wildland fires to people, property, wildlife, and the environment, there is an urgency to provide tools for effective wildfire management. Early detection of wildfires is essential to minimizing potentially catastrophic destruction. In this paper, we present our work on integrating multiple data sources in SmokeyNet, a deep learning model using spatio-temporal information to detect smoke from wildland fires. Camera image data is integrated with weather sensor measurements and processed by SmokeyNet to create a multimodal wildland fire smoke detection system. We present our results comparing performance in terms of both accuracy and time-to-detection for multimodal data vs. a single data source. With a time-to-detection of only a few minutes, SmokeyNet can serve as an automated early notification system, providing a useful tool in the fight against destructive wildfires.
- Published
- 2022
46. Rural service coordination programming for women using substances and their families
- Author
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Lesley Cottrell, Charlotte Workman, Melina Danko, Ellis Walker, Anthony Dmytrijuk, Susan Harrison, Mikisha Lee, Ashleigh McKinsey, and Mark C Smith
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Medicine - Abstract
Background: Women experiencing substance use during their pregnancies or after the birth of a child report being fearful of losing their children based on care, stigmatized when seeking assistance, and barriers to care such as having to provide the same information to different providers, and having to repeat their lived experiences with substance use in detail. Particularly these service barriers can be confusing, complicated, and difficult to follow, which could lead to non-compliance or not seeking services. Objectives: We evaluated components of a service coordination program for women experiencing substance use, their children, and larger families who help with caregiving. We examined stakeholder interest in the program, feasibility providing services over time, and initial program effectiveness. Design: Participant enrollment and outcomes as well as service coordination activities provided over a 4-year period was gathered across three demonstration site locations (a birthing hospital, reunification program, and home visiting program). Methods: Program information was gathered from needs assessment data, health survey data from enrolled caregivers and infants, training evaluations, and budget recordings of direct aid. In this mixed method design, we examined potential differences between baseline and the last assessment for women and children enrolled in the program. We also utilized univariate analyses of variance to examine the main effects of maternal and infant characteristics on final maternal and infant outcomes. Results: Three sites enrolled 182 women and families for program services. Patient navigators provided direct aid, training, goal setting, and service coordination and planning. Families remained in the program, on average, 655 days and were satisfied with the services received. Respondents thought the program elements were easy to implement within the rural setting. The program effectively addressed basic needs, violence ( p
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- 2024
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47. Finding and keeping a mentor: a year of reflection
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Sarah Cottrell-Cumber
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Surgery ,RD1-811 ,Medical emergencies. Critical care. Intensive care. First aid ,RC86-88.9 - Abstract
I had the privilege to learn from Dr Sharon Henry, the American Association for the Surgery of Trauma (AAST) vice president, over the past year as the AAST Associate Membership Mentoring Scholarship recipient. This essay serves as a reflection on my year and was presented at the 2024 AAST Annual Meeting. Mentorship breaks down into two stages: finding a mentor and keeping a mentor. Finding a mentor can occur through a formal mentorship process or relationships formed organically. It takes a connection between two people and time for a relationship to form. Keeping a mentor takes effort and intentionality. Mentorship doesn’t end when the scholarship does. It is fluid, without direction, without a timeline, and it will evolve. It will take effort and intention to keep a mentor, but the reward is so great for all that effort put in. Often, what we receive out of mentorship cannot be quantified but the impact is profound.
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- 2024
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48. Crowd-sourced machine learning prediction of long COVID using data from the National COVID Cohort CollaborativeResearch in context
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Timothy Bergquist, Johanna Loomba, Emily Pfaff, Fangfang Xia, Zixuan Zhao, Yitan Zhu, Elliot Mitchell, Biplab Bhattacharya, Gaurav Shetty, Tamanna Munia, Grant Delong, Adbul Tariq, Zachary Butzin-Dozier, Yunwen Ji, Haodong Li, Jeremy Coyle, Seraphina Shi, Rachael V. Philips, Andrew Mertens, Romain Pirracchio, Mark van der Laan, John M. Colford, Jr., Alan Hubbard, Jifan Gao, Guanhua Chen, Neelay Velingker, Ziyang Li, Yinjun Wu, Adam Stein, Jiani Huang, Zongyu Dai, Qi Long, Mayur Naik, John Holmes, Danielle Mowery, Eric Wong, Ravi Parekh, Emily Getzen, Jake Hightower, Jennifer Blase, Ataes Aggarwal, Joseph Agor, Amera Al-Amery, Oluwatobiloba Aminu, Adit Anand, Corneliu Antonescu, Mehak Arora, Sayed Asaduzzaman, Tanner Asmussen, Mahdi Baghbanzadeh, Frazier Baker, Bridget Bangert, Laila Bekhet, Jenny Blase, Brian Caffo, Hao Chang, Zeyuan Chen, Jiandong Chen, Jeffrey Chiang, Peter Cho, Robert Cockrell, Parker Combs, Ciara Crosby, Ran Dai, Anseh Danesharasteh, Elif Yildirim, Ryan Demilt, Kaiwen Deng, Sanjoy Dey, Rohan Dhamdhere, Andrew Dickson, Phoebe Dijour, Dong Dinh, Richard Dixon, Albi Domi, Souradeep Dutta, Mirna Elizondo, Zeynep Ertem, Solomon Feuerwerker, Danica Fliss, Jennifer Fowler, Sunyang Fu, Kelly Gardner, Neil Getty, Mohamed Ghalwash, Logan Gloster, Phil Greer, Yuanfang Guan, Colby Ham, Samer Hanoudi, Jeremy Harper, Nathaniel Hendrix, Leeor Hershkovich, Junjie Hu, Yu Huang, Tongtong Huang, Junguk Hur, Monica Isgut, Hamid Ismail, Grant Izmirlian, Kuk Jang, Christianah Jemiyo, Hayoung Jeong, Xiayan Ji, Ming Jiang, Sihang Jiang, Xiaoqian Jiang, Yuye Jiang, Akin Johnson, Zach Analyst, Saarthak Kapse, Uri Kartoun, Dukka KC, Zahra Fard, Tim Kosfeld, Spencer Krichevsky, Mike Kuo, Dale Larie, Lauren Lederer, Shan Leng, Hongyang Li, Jianfu Li, Tiantian Li, Xinwen Liang, Hengyue Liang, Feifan Liu, Daniel Liu, Gang Luo, Ravi Madduri, Vithal Madhira, Shivali Mani, Farzaneh Mansourifard, Robert Matson, Vangelis Metsis, Pablo Meyer, Catherine Mikhailova, Dante Miller, Christopher Milo, Gourav Modanwal, Ronald Moore, David Morgenthaler, Rasim Musal, Vinit Nalawade, Rohan Narain, Saideep Narendrula, Alena Obiri, Satoshi Okawa, Chima Okechukwu, Toluwanimi Olorunnisola, Tim Ossowski, Harsh Parekh, Jean Park, Saaya Patel, Jason Patterson, Chetan Paul, Le Peng, Diana Perkins, Suresh Pokharel, Dmytro Poplavskiy, Zach Pryor, Sarah Pungitore, Hong Qin, Salahaldeen Rababa, Mahbubur Rahman, Elior Rahmani, Gholamali Rahnavard, Md Raihan, Suraj Rajendran, Sarangan Ravichandran, Chandan Reddy, Abel Reyes, Ali Roghanizad, Sean Rouffa, Xiaoyang Ruan, Arpita Saha, Sahil Sawant, Melody Schiaffino, Diego Seira, Saurav Sengupta, Ruslan Shalaev, Linh Shinguyen, Karnika Singh, Soumya Sinha, Damien Socia, Halen Stalians, Charalambos Stavropoulos, Jan Strube, Devika Subramanian, Jiehuan Sun, Ju Sun, Chengkun Sun, Prathic Sundararajan, Salmonn Talebi, Edward Tawiah, Jelena Tesic, Mikaela Thiess, Raymond Tian, Luke Torre-Healy; Ming-Tse Tsai, David Tyus, Madhurima Vardhan, Benjamin Walzer, Jacob Walzer, Junda Wang, Lu Wang, Will Wang, Jonathan Wang, Yisen Wang, Chad Weatherly, Fanyou Wu, Yifeng Wu, Hao Yan, Zhichao Yang, Biao Ye, Rui Yin, Changyu Yin, Yun Yoo, Albert You, June Yu, Martin Zanaj, Zachary Zaiman, Kai Zhang, Xiaoyi Zhang, Tianmai Zhang, Degui Zhi, Yishan Zhong, Huixue Zhou, Andrea Zhou, Yuanda Zhu, Sophie Zhu, Meredith Adams, Caleb Alexander, Benjamin Amor, Alfred Anzalone, Benjamin Bates, Will Beasley, Tellen Bennett, Mark Bissell, Eilis Boudreau, Samuel Bozzette, Katie Bradwell, Carolyn Bramante, Don Brown, Penny Burgoon, John Buse, Tiffany Callahan, Kenrick Cato, Scott Chapman, Christopher Chute, Jaylyn Clark, Marshall Clark, Will Cooper, Lesley Cottrell, Karen Crowley, Mariam Deacy, Christopher Dillon, David Eichmann, Mary Emmett, Rebecca Erwin-Cohen, Patricia Francis, Evan French, Rafael Fuentes, Davera Gabriel, Joel Gagnier, Nicole Garbarini, Jin Ge, Kenneth Gersing, Andrew Girvin, Valery Gordon, Alexis Graves, Justin Guinney, Melissa Haendel, J.W. Hayanga, Brian Hendricks, Wenndy Hernandez, Elaine Hill, William Hillegass, Stephanie Hong, Dan Housman, Robert Hurley, Jessica Islam, Randeep Jawa, Steve Johnson, Rishi Kamaleswaran, Warren Kibbe, Farrukh Koraishy, Kristin Kostka, Michael Kurilla, Adam Lee, Harold Lehmann, Hongfang Liu, Charisse Madlock-Brown; Sandeep Mallipattu, Amin Manna, Federico Mariona, Emily Marti, Greg Martin, Jomol Mathew, Diego Mazzotti, Julie McMurry, Hemalkumar Mehta, Sam Michael, Robert Miller, Leonie Misquitta, Richard Moffitt, Michele Morris, Kimberly Murray, Lavance Northington, Shawn O’Neil, Amy Olex, Matvey Palchuk, Brijesh Patel, Rena Patel, Philip Payne, Jami Pincavitch, Lili Portilla, Fred Prior, Saiju Pyarajan, Lee Pyles, Nabeel Qureshi, Peter Robinson, Joni Rutter, Ofer Sadan, Nasia Safdar, Amit Saha, Joel Saltz, Mary Saltz, Clare Schmitt, Soko Setoguchi, Noha Sharafeldin, Anjali Sharathkumar, Usman Sheikh, Hythem Sidky, George Sokos, Andrew Southerland, Heidi Spratt, Justin Starren, Vignesh Subbian, Christine Suver, Cliff Takemoto, Meredith Temple-O'Connor, Umit Topaloglu, Satyanarayana Vedula, Anita Walden, Kellie Walters, Cavin Ward-Caviness, Adam Wilcox, Ken Wilkins, Andrew Williams, Chunlei Wu, Elizabeth Zampino, Xiaohan Zhang, and Richard Zhu
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Long COVID ,PASC ,Machine learning ,COVID-19 ,Evaluation ,Community challenge ,Medicine ,Medicine (General) ,R5-920 - Abstract
Summary: Background: While many patients seem to recover from SARS-CoV-2 infections, many patients report experiencing SARS-CoV-2 symptoms for weeks or months after their acute COVID-19 ends, even developing new symptoms weeks after infection. These long-term effects are called post-acute sequelae of SARS-CoV-2 (PASC) or, more commonly, Long COVID. The overall prevalence of Long COVID is currently unknown, and tools are needed to help identify patients at risk for developing long COVID. Methods: A working group of the Rapid Acceleration of Diagnostics-radical (RADx-rad) program, comprised of individuals from various NIH institutes and centers, in collaboration with REsearching COVID to Enhance Recovery (RECOVER) developed and organized the Long COVID Computational Challenge (L3C), a community challenge aimed at incentivizing the broader scientific community to develop interpretable and accurate methods for identifying patients at risk of developing Long COVID. From August 2022 to December 2022, participants developed Long COVID risk prediction algorithms using the National COVID Cohort Collaborative (N3C) data enclave, a harmonized data repository from over 75 healthcare institutions from across the United States (U.S.). Findings: Over the course of the challenge, 74 teams designed and built 35 Long COVID prediction models using the N3C data enclave. The top 10 teams all scored above a 0.80 Area Under the Receiver Operator Curve (AUROC) with the highest scoring model achieving a mean AUROC of 0.895. Included in the top submission was a visualization dashboard that built timelines for each patient, updating the risk of a patient developing Long COVID in response to clinical events. Interpretation: As a result of L3C, federal reviewers identified multiple machine learning models that can be used to identify patients at risk for developing Long COVID. Many of the teams used approaches in their submissions which can be applied to future clinical prediction questions. Funding: Research reported in this RADx® Rad publication was supported by the National Institutes of Health. Timothy Bergquist, Johanna Loomba, and Emily Pfaff were supported by Axle Subcontract: NCATS-STSS-P00438.
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- 2024
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49. Molecular characterization of gliomas and glioneuronal tumors amid Noonan syndrome: cancer predisposition examined
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Margaret Shatara, Kathleen M. Schieffer, Marilena Melas, Elizabeth A. Varga, Diana Thomas, Brianna A. Bucknor, Heather M. Costello, Gregory Wheeler, Benjamin J. Kelly, Katherine E. Miller, Diana P. Rodriguez, Mariam T. Mathew, Kristy Lee, Erin Crotty, Sarah Leary, Vera A. Paulson, Bonnie Cole, Mohamed S. Abdelbaki, Jonathan L. Finlay, Margot A. Lazow, Ralph Salloum, Maryam Fouladi, Daniel R. Boué, Elaine R. Mardis, and Catherine E. Cottrell
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glioma ,glioneuronal tumor ,Noonan syndrome ,cancer predisposition ,PTPN11 ,germline ,Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
IntroductionIn the setting of pediatric and adolescent young adult cancer, increased access to genomic profiling has enhanced the detection of genetic variation associated with cancer predisposition, including germline syndromic conditions. Noonan syndrome (NS) is associated with the germline RAS pathway activating alterations and increased risk of cancer. Herein, we describe our comprehensive molecular profiling approach, the association of NS with glioma and glioneuronal tumors, and the clinical and histopathologic characteristics associated with the disease.MethodsWithin an institutional pediatric cancer cohort (n = 314), molecular profiling comprised of paired somatic disease–germline comparator exome analysis, RNA sequencing, and tumor classification by DNA methylation analysis was performed.ResultsThrough the implementation of paired analysis, this study identified 4 of 314 (1.3%) individuals who harbored a germline PTPN11 variant associated with NS, of which 3 individuals were diagnosed with a glioma or glioneuronal tumor. Furthermore, we extend this study through collaboration with a peer institution to identify two additional individuals with NS and a glioma or glioneuronal tumor. Notably, in three of five (60%) individuals, paired genomic profiling led to a previously unrecognized diagnosis of Noonan syndrome despite an average age of cancer diagnosis of 16.8 years. The study of the disease-involved tissue identified signaling pathway dysregulation through somatic alteration of genes involved in cellular proliferation, survival, and differentiation.DiscussionComparative pathologic findings are presented to enable an in-depth examination of disease characteristics. This comprehensive analysis highlights the association of gliomas and glioneuronal tumors with RASopathies and the potential therapeutic challenges and importantly demonstrates the utility of genomic profiling for the identification of germline cancer predisposition.
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- 2024
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50. Student Performance in Online Classes at a Hispanic-Serving Institution: A Study of the Impact of Student Characteristics in Online Learning
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Cottrell, Rebecca S.
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As online enrollment increases in the United States, it is important to understand the impact of course modality on student outcomes. In particular, there has been limited research on the effect of course enrollment at Hispanic-serving institutions (HSI). The current study evaluated the effect of online course enrollment on student grades and on student withdrawal rates by comparing outcomes in online and face-to-face classes. The main innovation of this study is to use propensity score analysis to control for 15 different student characteristics as a way to control for the selection bias introduced when students self-select into different course modalities. The study used data from a large, public, HSI in the mountain west during the 2017-2018 and 2018-2019 academic years. Baseline results on a two-sample t-test indicated that online students have significantly higher course grades, and non-significantly different withdrawal rates before controlling for student characteristics. The study used a propensity score analysis (PSA) to control for 15 confounding covariates after testing three different PSA models: near-neighbor matching, Mahalanobis' metric, and optimal matching. After evaluating each model for validity and sensitivity, a near-neighbor 1:2 matching PSA shows a non-significant difference in student grades, and higher withdrawal rates in online classes than face-to-face classes. Given these results, institutions should ensure that they are providing adequate academic support for online students to improve retention and success rates for online students.
- Published
- 2021
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